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Koraishy FM, Mann FD, Waszczuk MA, Kuan PF, Jonas K, Yang X, Docherty A, Shabalin A, Clouston S, Kotov R, Luft B. Polygenic association of glomerular filtration rate decline in world trade center responders. BMC Nephrol 2022; 23:347. [PMID: 36307804 PMCID: PMC9615399 DOI: 10.1186/s12882-022-02967-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 09/26/2022] [Accepted: 10/06/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND The factors associated with estimated glomerular filtrate rate (eGFR) decline in low risk adults remain relatively unknown. We hypothesized that a polygenic risk score (PRS) will be associated with eGFR decline. METHODS We analyzed genetic data from 1,601 adult participants with European ancestry in the World Trade Center Health Program (baseline age 49.68 ± 8.79 years, 93% male, 23% hypertensive, 7% diabetic and 1% with cardiovascular disease) with ≥ three serial measures of serum creatinine. PRSs were calculated from an aggregation of single nucleotide polymorphisms (SNPs) from a recent, large-scale genome-wide association study (GWAS) of rapid eGFR decline. Generalized linear models were used to evaluate the association of PRS with renal outcomes: baseline eGFR and CKD stage, rate of change in eGFR, stable versus declining eGFR over a 3-5-year observation period. eGFR decline was defined in separate analyses as "clinical" (> -1.0 ml/min/1.73 m2/year) or "empirical" (lower most quartile of eGFR slopes). RESULTS The mean baseline eGFR was ~ 86 ml/min/1.73 m2. Subjects with decline in eGFR were more likely to be diabetic. PRS was significantly associated with lower baseline eGFR (B = -0.96, p = 0.002), higher CKD stage (OR = 1.17, p = 0.010), decline in eGFR (OR = 1.14, p = 0.036) relative to stable eGFR, and the lower quartile of eGFR slopes (OR = 1.21, p = 0.008), after adjusting for established risk factors for CKD. CONCLUSION Common genetic variants are associated with eGFR decline in middle-aged adults with relatively low comorbidity burdens.
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Affiliation(s)
- Farrukh M Koraishy
- Division of Nephrology, Department of Medicine, Stony Brook University, 100 Nicolls Road, HSCT16-080E, Stony Brook, NY, USA.
| | - Frank D Mann
- Department of Family, Population, and Preventative Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Monika A Waszczuk
- Department of Psychology, Rosalind Franklin University, North Chicago, IL, USA
| | - Pei-Fen Kuan
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA
| | - Katherine Jonas
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
| | - Xiaohua Yang
- Department of Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Anna Docherty
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
| | - Andrey Shabalin
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
| | - Sean Clouston
- Department of Family, Population, and Preventative Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Roman Kotov
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
| | - Benjamin Luft
- Department of Medicine, Stony Brook University, Stony Brook, NY, USA
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302
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Effects of Selenium on Chronic Kidney Disease: A Mendelian Randomization Study. Nutrients 2022; 14:nu14214458. [PMID: 36364721 PMCID: PMC9654848 DOI: 10.3390/nu14214458] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 10/18/2022] [Accepted: 10/21/2022] [Indexed: 12/05/2022] Open
Abstract
BACKGROUND Previous observational studies have shown that there is a controversial association between selenium levels and chronic kidney disease (CKD). Our aim was to assess the causal relationship between selenium levels and CKD using Mendelian randomization (MR) analysis. METHODS We used the two-sample Mendelian randomization (MR) method to analyze the causal role of selenium levels on CKD risk. The variants associated with selenium levels were extracted from a large genome-wide association study (GWAS) meta-analysis of circulating selenium levels (n = 5477) and toenail selenium levels (n = 4162) in the European population. Outcome data were from the largest GWAS meta-analysis of European-ancestry participants for kidney function to date. Inverse variance weighted (IVW) method was used as the main analysis and a series of sensitivity analyses were carried out to detect potential violations of MR assumptions. RESULTS The MR analysis results indicate that the genetically predicted selenium levels were associated with decreased estimated glomerular filtration (eGFR) (effect = -0.0042, 95% confidence interval [CI]: -0.0053-0.0031, p = 2.186 × 10-13) and increased blood urea nitrogen (BUN) (effect = 0.0029, 95% confidence interval [CI]: 0.0006-0.0052, p = 0.0136) with no pleiotropy detected. CONCLUSIONS The MR study indicated that an increased level of selenium is a causative factor for kidney function impairment.
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Larach DB, Lewis A, Bastarache L, Pandit A, He J, Sinha A, Douville NJ, Heung M, Mathis MR, Mosley JD, Wanderer JP, Kheterpal S, Zawistowski M, Brummett CM, Siew ED, Robinson-Cohen C, Kertai MD. Limited clinical utility for GWAS or polygenic risk score for postoperative acute kidney injury in non-cardiac surgery in European-ancestry patients. BMC Nephrol 2022; 23:339. [PMID: 36271344 PMCID: PMC9587619 DOI: 10.1186/s12882-022-02964-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 09/27/2022] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND Prior studies support a genetic basis for postoperative acute kidney injury (AKI). We conducted a genome-wide association study (GWAS), assessed the clinical utility of a polygenic risk score (PRS), and estimated the heritable component of AKI in patients who underwent noncardiac surgery. METHODS We performed a retrospective large-scale genome-wide association study followed by a meta-analysis of patients who underwent noncardiac surgery at the Vanderbilt University Medical Center ("Vanderbilt" cohort) or Michigan Medicine, the academic medical center of the University of Michigan ("Michigan" cohort). In the Vanderbilt cohort, the relationship between polygenic risk score for estimated glomerular filtration rate and postoperative AKI was also tested to explore the predictive power of aggregating multiple common genetic variants associated with AKI risk. Similarly, in the Vanderbilt cohort genome-wide complex trait analysis was used to estimate the heritable component of AKI due to common genetic variants. RESULTS The study population included 8248 adults in the Vanderbilt cohort (mean [SD] 58.05 [15.23] years, 50.2% men) and 5998 adults in Michigan cohort (56.24 [14.76] years, 49% men). Incident postoperative AKI events occurred in 959 patients (11.6%) and in 277 patients (4.6%), respectively. No loci met genome-wide significance in the GWAS and meta-analysis. PRS for estimated glomerular filtration rate explained a very small percentage of variance in rates of postoperative AKI and was not significantly associated with AKI (odds ratio 1.050 per 1 SD increase in polygenic risk score [95% CI, 0.971-1.134]). The estimated heritability among common variants for AKI was 4.5% (SE = 4.5%) suggesting low heritability. CONCLUSION The findings of this study indicate that common genetic variation minimally contributes to postoperative AKI after noncardiac surgery, and likely has little clinical utility for identifying high-risk patients.
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Affiliation(s)
- Daniel B Larach
- Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Adam Lewis
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Anita Pandit
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Jing He
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Anik Sinha
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas J Douville
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
- Institute of Healthcare Policy & Innovation, University of Michigan, Ann Arbor, MI, USA
| | - Michael Heung
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Michael R Mathis
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Jonathan D Mosley
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jonathan P Wanderer
- Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sachin Kheterpal
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | | | - Chad M Brummett
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - Edward D Siew
- Division of Nephrology and Hypertension, Vanderbilt Center for Kidney Disease (VCKD) and Integrated Program for AKI (VIP-AKI), Tennessee Valley Health System, Nashville Veterans Affairs Hospital, Nashville, TN, USA
| | - Cassianne Robinson-Cohen
- Vanderbilt O'Brien Kidney Center, Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Miklos D Kertai
- Division of Adult Cardiothoracic Anesthesiology, Department of Anesthesiology, Vanderbilt University Medical Center, 1211 21st Avenue South, Medical Arts Building, Office 526E, Nashville, TN, 37212, USA.
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304
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Yuan S, Mason AM, Burgess S, Larsson SC. Differentiating Associations of Glycemic Traits With Atherosclerotic and Thrombotic Outcomes: Mendelian Randomization Investigation. Diabetes 2022; 71:2222-2232. [PMID: 35499407 PMCID: PMC7613853 DOI: 10.2337/db21-0905] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 04/04/2022] [Indexed: 11/13/2022]
Abstract
We conducted a Mendelian randomization analysis to differentiate associations of four glycemic indicators with a broad range of atherosclerotic and thrombotic diseases. Independent genetic variants associated with fasting glucose (FG), 2 h glucose after an oral glucose challenge (2hGlu), fasting insulin (FI), and glycated hemoglobin (HbA1c) at the genome-wide significance threshold were used as instrumental variables. Summary-level data for 12 atherosclerotic and 4 thrombotic outcomes were obtained from large genetic consortia and the FinnGen and UK Biobank studies. Higher levels of genetically predicted glycemic traits were consistently associated with increased risk of coronary atherosclerosis-related diseases and symptoms. Genetically predicted glycemic traits except HbA1c showed positive associations with peripheral artery disease risk. Genetically predicted FI levels were positively associated with risk of ischemic stroke and chronic kidney disease. Genetically predicted FG and 2hGlu were positively associated with risk of large artery stroke. Genetically predicted 2hGlu levels showed positive associations with risk of small vessel stroke. Higher levels of genetically predicted glycemic traits were not associated with increased risk of thrombotic outcomes. Most associations for genetically predicted levels of 2hGlu and FI remained after adjustment for other glycemic traits. Increase in glycemic status appears to increase risks of coronary and peripheral artery atherosclerosis but not thrombosis.
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Affiliation(s)
- Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Amy M. Mason
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, U.K
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, U.K
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, U.K
| | - Susanna C. Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
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305
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Zhao SS, Rajasundaram S, Karhunen V, Alam U, Gill D. Sodium-glucose cotransporter 1 inhibition and gout: Mendelian randomisation study. Semin Arthritis Rheum 2022; 56:152058. [PMID: 35839537 DOI: 10.1016/j.semarthrit.2022.152058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 06/03/2022] [Accepted: 06/27/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVE Sodium-glucose cotransporter 2 inhibitors (SGLT2i) reduce serum urate, but their efficacy depends on renal function which is often impaired in people with gout. SGLT1 is primarily expressed in the small intestine and its inhibition may be a more suitable therapeutic target. We aimed to investigate the association of genetically proxied SGLT1i with gout risk, serum urate levels and cardiovascular safety using Mendelian randomisation (MR). METHODS Leveraging data from a genome-wide association study of 344,182 individuals in the UK Biobank, we identified a missense variant in the SLC5A1 gene that associated with glycated haemoglobin (HbA1c) to proxy SGLT1i. Outcome genetic data comprised 13,179 gout cases and 750,634 controls, 457,690 individuals for serum urate levels, and up to 977,323 individuals for cardiovascular safety outcomes. We applied the Wald ratio method and investigated potential genetic confounding using colocalization. RESULTS The rs17683430 missense variant was selected to instrument SGLT1i. Genetically proxied SGLT1i was associated with 75% reduction in gout risk (OR 0.25; 95%CI 0.06, 0.99; p = 0.048) and 32.0 μmol/L reduction in serum urate (95%CI -56.7, -7.3; p = 0.01), per 6.7 mmol/mol reduction in HbA1c. SGLT1i was associated with increased levels of low-density lipoprotein cholesterol (0.37 mmol/L; 95%CI 0.17, 0.56; p = 0.0002) but not risk of coronary heart disease, stroke, or chronic kidney disease. Colocalization did not suggest that results are attributable to genetic confounding. CONCLUSION SGLT1 inhibition may represent a novel therapeutic option for preventing gout in people with or without comorbid diabetes. Randomised trials are needed to formally investigate efficacy and safety.
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Affiliation(s)
- Sizheng Steven Zhao
- Centre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Science, School of Biological Sciences, Faculty of Biological Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Stopford Building, Oxford Road, Manchester M13 9PT, UK.
| | - Skanda Rajasundaram
- Centre for Evidence-Based Medicine, University of Oxford, Oxford, UK; Faculty of Medicine, Imperial College London, London, UK
| | - Ville Karhunen
- Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland; Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Uazman Alam
- Institute of Life Course and Medical Sciences and the Pain Research Institute, University of Liverpool, Liverpool, UK; Department of Diabetes & Endocrinology, Liverpool University Hospital NHS Foundation Trust, Liverpool, UK; Division of Diabetes, Endocrinology and Gastroenterology, Institute of Human Development, University of Manchester, Manchester, UK
| | - Dipender Gill
- Centre of Excellence in Genetics, Novo Nordisk Research Centre Oxford, Oxford, UK; Department of Epidemiology and Biostatistics, Imperial College London, London, UK; Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
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306
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Thompson M, Gordon MG, Lu A, Tandon A, Halperin E, Gusev A, Ye CJ, Balliu B, Zaitlen N. Multi-context genetic modeling of transcriptional regulation resolves novel disease loci. Nat Commun 2022; 13:5704. [PMID: 36171194 PMCID: PMC9519579 DOI: 10.1038/s41467-022-33212-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 09/07/2022] [Indexed: 12/01/2022] Open
Abstract
A majority of the variants identified in genome-wide association studies fall in non-coding regions of the genome, indicating their mechanism of impact is mediated via gene expression. Leveraging this hypothesis, transcriptome-wide association studies (TWAS) have assisted in both the interpretation and discovery of additional genes associated with complex traits. However, existing methods for conducting TWAS do not take full advantage of the intra-individual correlation inherently present in multi-context expression studies and do not properly adjust for multiple testing across contexts. We introduce CONTENT-a computationally efficient method with proper cross-context false discovery correction that leverages correlation structure across contexts to improve power and generate context-specific and context-shared components of expression. We apply CONTENT to bulk multi-tissue and single-cell RNA-seq data sets and show that CONTENT leads to a 42% (bulk) and 110% (single cell) increase in the number of genetically predicted genes relative to previous approaches. We find the context-specific component of expression comprises 30% of heritability in tissue-level bulk data and 75% in single-cell data, consistent with cell-type heterogeneity in bulk tissue. In the context of TWAS, CONTENT increases the number of locus-phenotype associations discovered by over 51% relative to previous methods across 22 complex traits.
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Affiliation(s)
- Mike Thompson
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA.
| | - Mary Grace Gordon
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Biological and Medical Informatics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Andrew Lu
- UCLA-Caltech Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Anchit Tandon
- Department of Mathematics, Indian Institute of Technology Delhi, Hauz Khas, Delhi, India
| | - Eran Halperin
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University of California Los Angeles, Los Angeles, CA, USA
- Department of Anesthesiology and Perioperative Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Alexander Gusev
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, US
- Division of Genetics, Brigham and Women's Hospital, Boston, MA, US
| | - Chun Jimmie Ye
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Chan-Zuckerberg Biohub, San Francisco, CA, USA
- Division of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Institute for Computational Health Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Brunilda Balliu
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Noah Zaitlen
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA.
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA.
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307
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Yavaş C, Ün C, Çelebi E, Gezdirici A, Doğan M, İli EG, Doğan T, Özgentürk NÖ. Whole-Exome Sequencing (WES) results of 50 patients with chronic kidney diseases: a perspective of Alport syndrome. Rev Assoc Med Bras (1992) 2022; 68:1282-1287. [PMID: 36134775 PMCID: PMC9575037 DOI: 10.1590/1806-9282.20220405] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 06/12/2022] [Indexed: 11/25/2022] Open
Abstract
OBJECTIVE: Chronic kidney disease (CKD) remains one of the major common health problems, and the number of people affected by the disease is progressively increasing in Turkey and worldwide. This study aimed to investigate molecular defects in Alport syndrome (AS) and other genes in patients with clinically suspected CKD using whole-exome sequencing (WES). METHODS: Patients with clinical suspicion of CKD were included in the study. Molecular genetic analyses were performed on genomic DNA by using WES. RESULTS: A total of 15 with 5 different pathogenic or likely pathogenic variants were identified in CKD patients, with a diagnostic rate of 30%. Eight variants of uncertain significance were also detected. In this study, 10 variants were described for the first time. As a result, we detected variants associated with CKD in our study population and found AS as the most common CKD after other related kidney diseases. CONCLUSIONS: Our results suggest that in heterogeneous diseases such as CKD, WES analysis enables accurate identification of underlying molecular defects promptly. Although CKD accounts for 10–14% of all renal dysfunction, molecular genetic diagnosis is necessary for optimal long-term treatment, prognosis, and effective genetic counseling.
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Affiliation(s)
- Cüneyd Yavaş
- Yildiz Technical University, Turkey; Başaksehir Çam and Sakura City Hospital, Turkey
| | | | | | | | | | | | - Tunay Doğan
- Başaksehir Çam and Sakura City Hospital, Turkey
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308
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Wilson PC, Muto Y, Wu H, Karihaloo A, Waikar SS, Humphreys BD. Multimodal single cell sequencing implicates chromatin accessibility and genetic background in diabetic kidney disease progression. Nat Commun 2022; 13:5253. [PMID: 36068241 PMCID: PMC9448792 DOI: 10.1038/s41467-022-32972-z] [Citation(s) in RCA: 94] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 08/25/2022] [Indexed: 11/09/2022] Open
Abstract
The proximal tubule is a key regulator of kidney function and glucose metabolism. Diabetic kidney disease leads to proximal tubule injury and changes in chromatin accessibility that modify the activity of transcription factors involved in glucose metabolism and inflammation. Here we use single nucleus RNA and ATAC sequencing to show that diabetic kidney disease leads to reduced accessibility of glucocorticoid receptor binding sites and an injury-associated expression signature in the proximal tubule. We hypothesize that chromatin accessibility is regulated by genetic background and closely-intertwined with metabolic memory, which pre-programs the proximal tubule to respond differently to external stimuli. Glucocorticoid excess has long been known to increase risk for type 2 diabetes, which raises the possibility that glucocorticoid receptor inhibition may mitigate the adverse metabolic effects of diabetic kidney disease.
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Affiliation(s)
- Parker C Wilson
- Division of Anatomic and Molecular Pathology, Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO, USA
| | - Yoshiharu Muto
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Haojia Wu
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Anil Karihaloo
- Novo Nordisk Research Center Seattle Inc, Seattle, WA, USA
| | - Sushrut S Waikar
- Section of Nephrology, Department of Medicine, Boston University School of Medicine, Boston Medical Center, Boston, MA, USA
| | - Benjamin D Humphreys
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
- Department of Developmental Biology, Washington University in St. Louis, St. Louis, MO, USA.
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309
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Park S, Lee S, Kim Y, Lee Y, Kang MW, Kim K, Kim YC, Han SS, Lee H, Lee JP, Joo KW, Lim CS, Kim YS, Kim DK. Serum bilirubin and kidney function: a Mendelian randomization study. Clin Kidney J 2022; 15:1755-1762. [PMID: 36003670 PMCID: PMC9394720 DOI: 10.1093/ckj/sfac120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Indexed: 11/19/2022] Open
Abstract
Background Further investigation is needed to determine the causal effects of serum bilirubin on the risk of chronic kidney disease (CKD). Methods This study is a Mendelian randomization (MR) analysis. Among the well-known single-nucleotide polymorphisms (SNPs) related to serum bilirubin levels, rs4149056 in the SLCO1B1 gene was selected as the genetic instrument for single-variant MR analysis, as it was found to be less related to possible confounders than other SNPs. The association between genetic predisposition for bilirubin levels and estimated glomerular filtration rate (eGFR) or CKD was assessed in 337 129 individuals of white British ancestry from the UK Biobank cohort. Two-sample MR based on summary-level data was also performed. SNPs related to total or direct bilirubin levels were collected from a previous genome-wide association study and confounder-associated SNPs were discarded. The independent CKDGen meta-analysis data for CKD were employed as the outcome summary statistics. Results The alleles of rs4149056 associated with higher bilirubin levels were associated with better kidney function in the UK Biobank data. In the summary-level MR, both of the genetically predicted total bilirubin {per 5 µmol/L increase; odds ratio [OR] 0.931 [95% confidence interval (CI) 0.871-0.995]} and direct bilirubin [per 1 µmol/L increase; OR 0.910 (95% CI 0.834-0.993)] levels were significantly associated with a lower risk of CKD, supported by the causal estimates from various MR sensitivity analyses. Conclusion Genetic predisposition for higher serum bilirubin levels is associated with better kidney function. This result suggests that higher serum bilirubin levels may have causal protective effects against kidney function impairment.
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Affiliation(s)
- Sehoon Park
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
| | - Soojin Lee
- Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Seoul, Korea
| | - Yaerim Kim
- Department of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea
| | - Yeonhee Lee
- Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Seoul, Korea
| | - Min Woo Kang
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Kwangsoo Kim
- Transdisciplinary Department of Medicine and Advanced Technology, Seoul National University Hospital, Seoul, Korea
| | - Yong Chul Kim
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Seung Seok Han
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Hajeong Lee
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Jung Pyo Lee
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Kwon Wook Joo
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Chun Soo Lim
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Yon Su Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
| | - Dong Ki Kim
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
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310
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Ferolito B, do Valle IF, Gerlovin H, Costa L, Casas JP, Gaziano JM, Gagnon DR, Begoli E, Barabási AL, Cho K. Visualizing novel connections and genetic similarities across diseases using a network-medicine based approach. Sci Rep 2022; 12:14914. [PMID: 36050444 PMCID: PMC9436158 DOI: 10.1038/s41598-022-19244-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 08/26/2022] [Indexed: 11/08/2022] Open
Abstract
Understanding the genetic relationships between human disorders could lead to better treatment and prevention strategies, especially for individuals with multiple comorbidities. A common resource for studying genetic-disease relationships is the GWAS Catalog, a large and well curated repository of SNP-trait associations from various studies and populations. Some of these populations are contained within mega-biobanks such as the Million Veteran Program (MVP), which has enabled the genetic classification of several diseases in a large well-characterized and heterogeneous population. Here we aim to provide a network of the genetic relationships among diseases and to demonstrate the utility of quantifying the extent to which a given resource such as MVP has contributed to the discovery of such relations. We use a network-based approach to evaluate shared variants among thousands of traits in the GWAS Catalog repository. Our results indicate many more novel disease relationships that did not exist in early studies and demonstrate that the network can reveal clusters of diseases mechanistically related. Finally, we show novel disease connections that emerge when MVP data is included, highlighting methodology that can be used to indicate the contributions of a given biobank.
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Affiliation(s)
- Brian Ferolito
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA.
| | - Italo Faria do Valle
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
- Center for Complex Network Research, Department of Physics, Northeastern University, Boston, 02115, USA
| | - Hanna Gerlovin
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
| | - Lauren Costa
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
| | - Juan P Casas
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
- Brigham and Women's Hospital, Division of Aging, Department of Medicine, Harvard Medical School, Boston, 02115, USA
| | - J Michael Gaziano
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
- Brigham and Women's Hospital, Division of Aging, Department of Medicine, Harvard Medical School, Boston, 02115, USA
| | - David R Gagnon
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
- School of Public Health, Department of Biostatistics, Boston University, Boston, 02215, USA
| | - Edmon Begoli
- Oak Ridge National Laboratory, Oak Ridge, 37830, USA
| | - Albert-László Barabási
- Center for Complex Network Research, Department of Physics, Northeastern University, Boston, 02115, USA
| | - Kelly Cho
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
- Brigham and Women's Hospital, Division of Aging, Department of Medicine, Harvard Medical School, Boston, 02115, USA
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311
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Khan A, Kiryluk K. Kidney disease progression and collider bias in GWAS. Kidney Int 2022; 102:476-478. [PMID: 35988936 DOI: 10.1016/j.kint.2022.06.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 06/03/2022] [Accepted: 06/10/2022] [Indexed: 02/01/2023]
Abstract
New genome-wide meta-analysis for longitudinal kidney function decline identified several genetic loci related to kidney disease progression. The study illustrated the complexity of modeling longitudinal traits in genome-wide association studies and highlighted the issue of a collider bias that can be introduced when a kidney disease progression phenotype is adjusted for baseline kidney function. Herein, we briefly outline the key findings of this study, their limitations, and implications for future studies.
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Affiliation(s)
- Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA.
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312
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Chen Y, Xu X, Wang L, Li K, Sun Y, Xiao L, Dai J, Huang M, Wang Y, Wang DW. Genetic insights into therapeutic targets for aortic aneurysms: A Mendelian randomization study. EBioMedicine 2022; 83:104199. [PMID: 35952493 PMCID: PMC9385553 DOI: 10.1016/j.ebiom.2022.104199] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 07/11/2022] [Accepted: 07/19/2022] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND As aortic aneurysms (AAs) enlarge, they can become life-threatening if left undiagnosed or neglected. At present, there is a lack of radical treatments for preventing disease progression. Therefore, we aimed to identify effective drug targets that slow the progression of AAs. METHODS A Mendelian randomization (MR) analysis was conducted to identify therapeutic targets which are associated with AAs. Summary statistics for AAs were obtained from two datasets: the UK Biobank (2228 cases and 408,565 controls) and the FinnGen study (3658 cases and 244,907 controls). Cis-expression quantitative trait loci (cis-eQTL) for druggable genes were retrieved from the eQTLGen Consortium and used as genetic instrumental variables. Colocalization analysis was performed to determine the probability that single nucleotide polymorphisms (SNPs) associated with AAs and eQTL shared causal genetic variants. FINDINGS Four drug targets (BTN3A1, FASN, PLAU, and PSMA4) showed significant MR results in two independent datasets. Proteasome 20S subunit alpha 4 (PSMA4) and plasminogen activator, urokinase (PLAU) in particular, were found to have strong evidence for colocalization with AAs, and abdominal aortic aneurysm in particular. Additionally, except for the association between PSMA4 and intracranial aneurysms, no association between genetically proxied inhibition of PLAU and PSMA4 was detected in increasing the risk of other cardiometabolic risks and diseases. INTERPRETATION This study supports that drug-targeting PLAU and PSMA4 inhibition may reduce the risk of AAs. FUNDING This work was supported by National Key R&D Program of China (NO. 2017YFC0909400), Nature Science Foundation of China (No. 91839302, 81790624), Project supported by Shanghai Municipal Science and Technology Major Project (Grant No. 2017SHZDZX01), and Tongji Hospital Clinical Research Flagship Program (no. 2019CR207).
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Affiliation(s)
- Yanghui Chen
- Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, PR China
| | - Xin Xu
- Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, PR China
| | - Linlin Wang
- Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, PR China
| | - Ke Li
- Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, PR China
| | - Yang Sun
- Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, PR China
| | - Lei Xiao
- Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, PR China
| | - Jiaqi Dai
- Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, PR China
| | - Man Huang
- Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, PR China
| | - Yan Wang
- Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, PR China
| | - Dao Wen Wang
- Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, PR China; Department of Internal Medicine, Tongji Shanxi Hospital, Taiyuan 030032, Shanxi Province, China.
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313
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Gorski M, Rasheed H, Teumer A, Thomas LF, Graham SE, Sveinbjornsson G, Winkler TW, Günther F, Stark KJ, Chai JF, Tayo BO, Wuttke M, Li Y, Tin A, Ahluwalia TS, Ärnlöv J, Åsvold BO, Bakker SJL, Banas B, Bansal N, Biggs ML, Biino G, Böhnke M, Boerwinkle E, Bottinger EP, Brenner H, Brumpton B, Carroll RJ, Chaker L, Chalmers J, Chee ML, Chee ML, Cheng CY, Chu AY, Ciullo M, Cocca M, Cook JP, Coresh J, Cusi D, de Borst MH, Degenhardt F, Eckardt KU, Endlich K, Evans MK, Feitosa MF, Franke A, Freitag-Wolf S, Fuchsberger C, Gampawar P, Gansevoort RT, Ghanbari M, Ghasemi S, Giedraitis V, Gieger C, Gudbjartsson DF, Hallan S, Hamet P, Hishida A, Ho K, Hofer E, Holleczek B, Holm H, Hoppmann A, Horn K, Hutri-Kähönen N, Hveem K, Hwang SJ, Ikram MA, Josyula NS, Jung B, Kähönen M, Karabegović I, Khor CC, Koenig W, Kramer H, Krämer BK, Kühnel B, Kuusisto J, Laakso M, Lange LA, Lehtimäki T, Li M, Lieb W, Lind L, Lindgren CM, Loos RJF, Lukas MA, Lyytikäinen LP, Mahajan A, Matias-Garcia PR, Meisinger C, Meitinger T, Melander O, Milaneschi Y, Mishra PP, Mononen N, Morris AP, Mychaleckyj JC, Nadkarni GN, Naito M, et alGorski M, Rasheed H, Teumer A, Thomas LF, Graham SE, Sveinbjornsson G, Winkler TW, Günther F, Stark KJ, Chai JF, Tayo BO, Wuttke M, Li Y, Tin A, Ahluwalia TS, Ärnlöv J, Åsvold BO, Bakker SJL, Banas B, Bansal N, Biggs ML, Biino G, Böhnke M, Boerwinkle E, Bottinger EP, Brenner H, Brumpton B, Carroll RJ, Chaker L, Chalmers J, Chee ML, Chee ML, Cheng CY, Chu AY, Ciullo M, Cocca M, Cook JP, Coresh J, Cusi D, de Borst MH, Degenhardt F, Eckardt KU, Endlich K, Evans MK, Feitosa MF, Franke A, Freitag-Wolf S, Fuchsberger C, Gampawar P, Gansevoort RT, Ghanbari M, Ghasemi S, Giedraitis V, Gieger C, Gudbjartsson DF, Hallan S, Hamet P, Hishida A, Ho K, Hofer E, Holleczek B, Holm H, Hoppmann A, Horn K, Hutri-Kähönen N, Hveem K, Hwang SJ, Ikram MA, Josyula NS, Jung B, Kähönen M, Karabegović I, Khor CC, Koenig W, Kramer H, Krämer BK, Kühnel B, Kuusisto J, Laakso M, Lange LA, Lehtimäki T, Li M, Lieb W, Lind L, Lindgren CM, Loos RJF, Lukas MA, Lyytikäinen LP, Mahajan A, Matias-Garcia PR, Meisinger C, Meitinger T, Melander O, Milaneschi Y, Mishra PP, Mononen N, Morris AP, Mychaleckyj JC, Nadkarni GN, Naito M, Nakatochi M, Nalls MA, Nauck M, Nikus K, Ning B, Nolte IM, Nutile T, O'Donoghue ML, O'Connell J, Olafsson I, Orho-Melander M, Parsa A, Pendergrass SA, Penninx BWJH, Pirastu M, Preuss MH, Psaty BM, Raffield LM, Raitakari OT, Rheinberger M, Rice KM, Rizzi F, Rosenkranz AR, Rossing P, Rotter JI, Ruggiero D, Ryan KA, Sabanayagam C, Salvi E, Schmidt H, Schmidt R, Scholz M, Schöttker B, Schulz CA, Sedaghat S, Shaffer CM, Sieber KB, Sim X, Sims M, Snieder H, Stanzick KJ, Thorsteinsdottir U, Stocker H, Strauch K, Stringham HM, Sulem P, Szymczak S, Taylor KD, Thio CHL, Tremblay J, Vaccargiu S, van der Harst P, van der Most PJ, Verweij N, Völker U, Wakai K, Waldenberger M, Wallentin L, Wallner S, Wang J, Waterworth DM, White HD, Willer CJ, Wong TY, Woodward M, Yang Q, Yerges-Armstrong LM, Zimmermann M, Zonderman AB, Bergler T, Stefansson K, Böger CA, Pattaro C, Köttgen A, Kronenberg F, Heid IM. Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies. Kidney Int 2022; 102:624-639. [PMID: 35716955 PMCID: PMC10034922 DOI: 10.1016/j.kint.2022.05.021] [Show More Authors] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 04/19/2022] [Accepted: 05/11/2022] [Indexed: 12/15/2022]
Abstract
Estimated glomerular filtration rate (eGFR) reflects kidney function. Progressive eGFR-decline can lead to kidney failure, necessitating dialysis or transplantation. Hundreds of loci from genome-wide association studies (GWAS) for eGFR help explain population cross section variability. Since the contribution of these or other loci to eGFR-decline remains largely unknown, we derived GWAS for annual eGFR-decline and meta-analyzed 62 longitudinal studies with eGFR assessed twice over time in all 343,339 individuals and in high-risk groups. We also explored different covariate adjustment. Twelve genome-wide significant independent variants for eGFR-decline unadjusted or adjusted for eGFR-baseline (11 novel, one known for this phenotype), including nine variants robustly associated across models were identified. All loci for eGFR-decline were known for cross-sectional eGFR and thus distinguished a subgroup of eGFR loci. Seven of the nine variants showed variant-by-age interaction on eGFR cross section (further about 350,000 individuals), which linked genetic associations for eGFR-decline with age-dependency of genetic cross-section associations. Clinically important were two to four-fold greater genetic effects on eGFR-decline in high-risk subgroups. Five variants associated also with chronic kidney disease progression mapped to genes with functional in-silico evidence (UMOD, SPATA7, GALNTL5, TPPP). An unfavorable versus favorable nine-variant genetic profile showed increased risk odds ratios of 1.35 for kidney failure (95% confidence intervals 1.03-1.77) and 1.27 for acute kidney injury (95% confidence intervals 1.08-1.50) in over 2000 cases each, with matched controls). Thus, we provide a large data resource, genetic loci, and prioritized genes for kidney function decline, which help inform drug development pipelines revealing important insights into the age-dependency of kidney function genetics.
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Affiliation(s)
- Mathias Gorski
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany; Department of Nephrology, University Hospital Regensburg, Regensburg, Germany.
| | - Humaira Rasheed
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway; MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany; Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland
| | - Laurent F Thomas
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway; Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway; BioCore-Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
| | - Sarah E Graham
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Felix Günther
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany; Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Munich, Germany
| | - Klaus J Stark
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Bamidele O Tayo
- Department of Public Health Sciences, Loyola University Chicago, Maywood, Illinois, USA
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany; Renal Division, Department of Medicine IV, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Yong Li
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Adrienne Tin
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, Mississippi, USA; Division of Nephrology, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Tarunveer S Ahluwalia
- Steno Diabetes Center Copenhagen, Gentofte, Denmark; The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Johan Ärnlöv
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; School of Health and Social Studies, Dalarna University, Stockholm, Sweden
| | - Bjørn Olav Åsvold
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway; Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Stephan J L Bakker
- Division of Nephrology, Department of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Bernhard Banas
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Nisha Bansal
- Division of Nephrology, University of Washington, Seattle, Washington, USA; Kidney Research Institute, University of Washington, Seattle, Washington, USA
| | - Mary L Biggs
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA; Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Ginevra Biino
- Institute of Molecular Genetics, National Research Council of Italy, Pavia, Italy
| | - Michael Böhnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center, Houston, Texas, USA
| | - Erwin P Bottinger
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Digital Health Center, Hasso Plattner Institute and University of Potsdam, Potsdam, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Ben Brumpton
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway; MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; Clinic of Thoracic and Occupational Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Robert J Carroll
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Layal Chaker
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - John Chalmers
- The George Institute for Global Health, University of New South Wales, Sydney, Australia
| | - Miao-Li Chee
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | - Miao-Ling Chee
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore; Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Audrey Y Chu
- Genetics, Merck & Co, Inc., Kenilworth, New Jersey, USA
| | - Marina Ciullo
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso"-CNR, Naples, Italy; IRCCS Neuromed, Pozzilli, Italy
| | - Massimiliano Cocca
- Institute for Maternal and Child Health, IRCCS "Burlo Garofolo," Trieste, Italy
| | - James P Cook
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Daniele Cusi
- Institute of Biomedical Technologies, National Research Council of Italy, Milan, Italy; Bio4Dreams-Business Nursery for Life Sciences, Milan, Italy
| | - Martin H de Borst
- Division of Nephrology, Department of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Frauke Degenhardt
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany; Department of Nephrology and Hypertension, Friedrich Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Karlhans Endlich
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany; Department of Anatomy and Cell Biology, University Medicine Greifswald, Greifswald, Germany
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, US National Institutes of Health, Baltimore, Maryland, USA
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Sandra Freitag-Wolf
- Institute of Medical Informatics and Statistics, Kiel University, University Hospital Schleswig-Holstein, Kiel, Germany
| | - Christian Fuchsberger
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA; Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
| | - Piyush Gampawar
- Institute of Molecular Biology and Biochemistry, Center for Molecular Medicine, Medical University of Graz, Graz, Austria
| | - Ron T Gansevoort
- Division of Nephrology, Department of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Sahar Ghasemi
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Vilmantas Giedraitis
- Molecular Geriatrics, Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland; Iceland School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Stein Hallan
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway; Department of Nephrology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Pavel Hamet
- Montreal University Hospital Research Center, CHUM, Montreal, Quebec, Canada; Medpharmgene, Montreal, Quebec, Canada; CRCHUM, Montreal, Quebec, Canada
| | - Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kevin Ho
- Kidney Health Research Institute (KHRI), Geisinger, Danville, Pennsylvania, USA; Department of Nephrology, Geisinger, Danville, Pennsylvania, USA
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria; Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Bernd Holleczek
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hilma Holm
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
| | - Anselm Hoppmann
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Katrin Horn
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany; LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Nina Hutri-Kähönen
- Department of Pediatrics, Tampere University Hospital, Tampere, Finland; Department of Pediatrics, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Shih-Jen Hwang
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Navya Shilpa Josyula
- Geisinger Research, Biomedical and Translational Informatics Institute, Rockville, Maryland, USA
| | - Bettina Jung
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany; Department of Nephrology and Rheumatology, Kliniken Südostbayern, Traunstein, Germany; KfH Kidney Centre Traunstein, Traunstein, Germany
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland; Department of Clinical Physiology, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Irma Karabegović
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Chiea-Chuen Khor
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore; Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
| | - Wolfgang Koenig
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany; DZHK (German Center for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany; Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Holly Kramer
- Department of Public Health Sciences, Loyola University Chicago, Maywood, Illinois, USA; Division of Nephrology and Hypertension, Loyola University Chicago, Chicago, Illinois, USA
| | - Bernhard K Krämer
- Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Brigitte Kühnel
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Johanna Kuusisto
- Department of Medicine, Kuopio University Hospital, Kuopio, Finland; Centre for Medicine and Clinical Research, University of Eastern Finland School of Medicine, Kuopio, Finland
| | - Markku Laakso
- Department of Medicine, Kuopio University Hospital, Kuopio, Finland; Centre for Medicine and Clinical Research, University of Eastern Finland School of Medicine, Kuopio, Finland
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado Denver-Anschutz Medical Campus, Aurora, Colorado, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Man Li
- Division of Nephrology and Hypertension, Department of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Wolfgang Lieb
- Institute of Epidemiology and Biobank Popgen, Kiel University, Kiel, Germany
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Cecilia M Lindgren
- Nuffield Department of Population Health, University of Oxford, Oxford, UK; Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA; Wellcome Center for Human Genetics, University of Oxford, Oxford, UK; Nuffield Department of Women's and Reproductive Health, University of Oxford, Level 3, Women's Centre, John Radcliffe Hospital, Oxford, UK; Li Ka Shing Centre for Health Information and Discovery, The Big Data Institute, University of Oxford, Oxford, UK
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mary Ann Lukas
- Clinical Sciences, GlaxoSmithKline, Albuquerque, New Mexico, USA
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Anubha Mahajan
- Wellcome Center for Human Genetics, University of Oxford, Oxford, UK; Oxford Center for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Pamela R Matias-Garcia
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Christa Meisinger
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Chair of Epidemiology, University of Augsburg, University Hospital Augsburg, Augsburg, Germany
| | - Thomas Meitinger
- DZHK (German Center for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany; Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany; Institute of Human Genetics, Technische Universität München, Munich, Germany
| | - Olle Melander
- Hypertension and Cardiovascular Disease, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC/Vrije Universiteit and GGZ inGeest, Amsterdam, the Netherlands
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Nina Mononen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Andrew P Morris
- Department of Health Data Science, University of Liverpool, Liverpool, UK; Wellcome Center for Human Genetics, University of Oxford, Oxford, UK; Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
| | - Josyf C Mychaleckyj
- Center for Public Health Genomics, University of Virginia, Charlottesville, Charlottesville, Virginia, USA
| | - Girish N Nadkarni
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mariko Naito
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan; Department of Oral Epidemiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA; Data Tecnica International, Glen Echo, Maryland, USA
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany; Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Kjell Nikus
- Department of Cardiology, Heart Center, Tampere University Hospital, Tampere, Finland; Department of Cardiology, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Boting Ning
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Teresa Nutile
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso"-CNR, Naples, Italy
| | - Michelle L O'Donoghue
- Cardiovascular Division, Brigham and Women's Hospital, Boston, Massachusetts, USA; TIMI Study Group, Boston, Massachusetts, USA
| | | | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali University Hospital, Reykjavik, Iceland
| | - Marju Orho-Melander
- Diabetes and Cardiovascular Disease-Genetic Epidemiology, Department of Clinical Sciences in Malmö, Lund University, Malmö, Sweden
| | - Afshin Parsa
- Division of Kidney, Urologic and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, USA; Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Sarah A Pendergrass
- Geisinger Research, Biomedical and Translational Informatics Institute, Danville, Pennsylvania, USA
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC/Vrije Universiteit and GGZ inGeest, Amsterdam, the Netherlands
| | - Mario Pirastu
- Institute of Genetic and Biomedical Research, National Research Council of Italy, UOS of Sassari, Li Punti, Sassari, Italy
| | - Michael H Preuss
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, Department of Epidemiology, Department of Health Services, University of Washington, Seattle, Washington, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland; Research Center of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Myriam Rheinberger
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany; Department of Nephrology and Rheumatology, Kliniken Südostbayern, Traunstein, Germany; KfH Kidney Centre Traunstein, Traunstein, Germany
| | - Kenneth M Rice
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Federica Rizzi
- Department of Health Sciences, University of Milan, Milano, Italy; ePhood Scientific Unit, ePhood SRL, Milano, Italy
| | - Alexander R Rosenkranz
- Division of Nephrology, Department of Internal Medicine, Medical University Graz, Graz, Austria
| | - Peter Rossing
- Steno Diabetes Center Copenhagen, Gentofte, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Daniela Ruggiero
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso"-CNR, Naples, Italy; IRCCS Neuromed, Pozzilli, Italy
| | - Kathleen A Ryan
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Erika Salvi
- Department of Health Sciences, University of Milan, Milano, Italy; Neuroalgology Unit, Fondazione IRCCS Istituto Neurologico "Carlo Besta," Milan, Italy
| | - Helena Schmidt
- Institute of Molecular Biology and Biochemistry, Center for Molecular Medicine, Medical University of Graz, Graz, Austria
| | - Reinhold Schmidt
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany; LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Christina-Alexandra Schulz
- Diabetes and Cardiovascular Disease-Genetic Epidemiology, Department of Clinical Sciences in Malmö, Lund University, Malmö, Sweden
| | - Sanaz Sedaghat
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Preventive Medicine, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA
| | - Christian M Shaffer
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Karsten B Sieber
- Human Genetics, GlaxoSmithKline, Collegeville, Pennsylvania, USA
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Mario Sims
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Kira J Stanzick
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland; Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Hannah Stocker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Chair of Genetic Epidemiology, IBE, Faculty of Medicine, Ludwig-Maximilians-Universität München, München, Germany; Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Silke Szymczak
- Institute of Medical Informatics and Statistics, Kiel University, University Hospital Schleswig-Holstein, Kiel, Germany; Institute of Medical Biometry and Statistics, University of Lübeck, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Chris H L Thio
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Johanne Tremblay
- Montreal University Hospital Research Center, CHUM, Montreal, Quebec, Canada; CRCHUM, Montreal, Quebec, Canada; Medpharmgene, Montreal, Quebec, Canada
| | - Simona Vaccargiu
- Institute of Genetic and Biomedical Research, National Research Council of Italy, UOS of Sassari, Li Punti, Sassari, Italy
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Durrer Center for Cardiovascular Research, The Netherlands Heart Institute, Utrecht, the Netherlands
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Uwe Völker
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany; Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; DZHK (German Center for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
| | - Lars Wallentin
- Cardiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden; Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden
| | - Stefan Wallner
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, Regensburg, Germany
| | - Judy Wang
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA
| | | | - Harvey D White
- Green Lane Cardiovascular Service, Auckland City Hospital and University of Auckland, Auckland, New Zealand
| | - Cristen J Willer
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, Michigan, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA; Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, USA
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Mark Woodward
- The George Institute for Global Health, University of New South Wales, Sydney, Australia; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA; The George Institute for Global Health, University of Oxford, Oxford, UK
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | | | - Martina Zimmermann
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, US National Institutes of Health, Baltimore, Maryland, USA
| | - Tobias Bergler
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland; Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Carsten A Böger
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany; Department of Nephrology and Rheumatology, Kliniken Südostbayern, Traunstein, Germany; KfH Kidney Centre Traunstein, Traunstein, Germany
| | - Cristian Pattaro
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.
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Ilori T, Watanabe A, Ng KH, Solarin A, Sinha A, Gbadegesin R. Genetics of Chronic Kidney Disease in Low-Resource Settings. Semin Nephrol 2022; 42:151314. [PMID: 36801667 PMCID: PMC10272019 DOI: 10.1016/j.semnephrol.2023.151314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
Advances in kidney genomics in the past 20 years has opened the door for more precise diagnosis of kidney disease and identification of new and specific therapeutic agents. Despite these advances, an imbalance exists between low-resource and affluent regions of the world. Individuals of European ancestry from the United States, United Kingdom, and Iceland account for 16% of the world's population, but represent more than 80% of all genome-wide association studies. South Asia, Southeast Asia, Latin America, and Africa together account for 57% of the world population but less than 5% of genome-wide association studies. Implications of this difference include limitations in new variant discovery, inaccurate interpretation of the effect of genetic variants in non-European populations, and unequal access to genomic testing and novel therapies in resource-poor regions. It also further introduces ethical, legal, and social pitfalls, and ultimately may propagate global health inequities. Ongoing efforts to reduce the imbalance in low-resource regions include funding and capacity building, population-based genome sequencing, population-based genome registries, and genetic research networks. More funding, training, and capacity building for infrastructure and expertise is needed in resource-poor regions. Focusing on this will ensure multiple-fold returns on investments in genomic research and technology.
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Affiliation(s)
- Titilayo Ilori
- Division of Nephrology, Boston University School of Medicine, Boston, MA
| | - Andreia Watanabe
- Division of Molecular Medicine, Department of Pediatrics, University of São Paulo School of Medicine, São Paulo, Brazil
| | - Kar-Hui Ng
- Department of Pediatrics, Yong Loo Lin School of Medicine, Singapore
| | - Adaobi Solarin
- Department of Pediatrics and Child Health, Lagos State University College of Medicine, Ikeja, Lagos, Nigeria
| | - Aditi Sinha
- Department of Pediatrics, All India Institute of Medical Sciences, New Delhi, India
| | - Rasheed Gbadegesin
- Division of Nephrology, Department of Pediatrics, Duke University School of Medicine, Durham, NC.
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315
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Vanent KN, Leasure AC, Acosta JN, Kuohn LR, Woo D, Murthy SB, Kamel H, Messé SR, Mullen MT, Cohen JB, Cohen DL, Townsend RR, Petersen NH, Sansing LH, Gill TM, Sheth KN, Falcone GJ. Association of Chronic Kidney Disease With Risk of Intracerebral Hemorrhage. JAMA Neurol 2022; 79:911-918. [PMID: 35969388 PMCID: PMC9379821 DOI: 10.1001/jamaneurol.2022.2299] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 06/24/2022] [Indexed: 11/14/2022]
Abstract
Importance The evidence linking chronic kidney disease (CKD) to spontaneous intracerebral hemorrhage (ICH) is inconclusive owing to possible confounding by comorbidities that frequently coexist in patients with these 2 diseases. Objective To determine whether there is an association between CKD and ICH risk. Design, Setting, and Participants A 3-stage study that combined observational and genetic analyses was conducted. First, the association between CKD and ICH risk was tested in the Ethnic/Racial Variations of Intracerebral Hemorrhage (ERICH) study, a multicenter case-control study in the US. All participants with available data on CKD from ERICH were included. Second, this analysis was replicated in the UK Biobank (UKB), an ongoing population study in the UK. All participants in the UKB were included in this study. Third, mendelian randomization analyses were implemented in the UKB using 27 CKD-related genetic variants to test for genetic associations. ERICH was conducted from August 1, 2010, to August 1, 2017, and observed participants for 1 year. The UKB enrolled participants between 2006 and 2010 and will continue to observe them for 30 years. Data analysis was performed from November 11, 2019, to May 10, 2022. Exposures CKD stages 1 to 5. Main Outcomes and Measures The outcome of interest was ICH, ascertained in ERICH via expert review of neuroimages and in the UKB via a combination of self-reported data and International Statistical Classification of Diseases, Tenth Revision, codes. Results In the ERICH study, a total of 2914 participants with ICH and 2954 controls who had available data on CKD were evaluated (mean [SD] age, 61.6 [14.0] years; 2433 female participants [41.5%]; 3435 male participants [58.5%]); CKD was found to be independently associated with higher risk of ICH (odds ratio [OR], 1.95; 95% CI, 1.35-2.89; P < .001). This association was not modified by race and ethnicity. Replication in the UKB with 1341 participants with ICH and 501 195 controls (mean [SD] age, 56.5 [8.1] years; 273 402 female participants [54.4%]; 229 134 male participants [45.6%]) confirmed this association (OR, 1.28; 95% CI, 1.01-1.62; P = .04). Mendelian randomization analyses indicated that genetically determined CKD was associated with ICH risk (OR, 1.56; 95% CI, 1.13-2.16; P = .007). Conclusions and Relevance In this 3-stage study that combined observational and genetic analyses among study participants enrolled in 2 large observational studies with different characteristics and study designs, CKD was consistently associated with higher risk of ICH. Mendelian randomization analyses suggest that this association was causal. Further studies are needed to identify the specific biological pathways that mediate this association.
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Affiliation(s)
- Kevin N. Vanent
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut
| | - Audrey C. Leasure
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut
| | - Julian N. Acosta
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut
| | - Lindsey R. Kuohn
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut
| | - Daniel Woo
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, Ohio
| | - Santosh B. Murthy
- Clinical and Translational Neuroscience Unit, Department of Neurology, Weill Cornell Medicine, New York, New York
| | - Hooman Kamel
- Clinical and Translational Neuroscience Unit, Department of Neurology, Weill Cornell Medicine, New York, New York
- Deputy Editor, JAMA Neurology
| | - Steven R. Messé
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Michael T. Mullen
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Jordana B. Cohen
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Department of Biostatistics, Epidemiology, and Information, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Debbie L. Cohen
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Raymond R. Townsend
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Nils H. Petersen
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut
| | - Lauren H. Sansing
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut
| | - Thomas M. Gill
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Kevin N. Sheth
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut
| | - Guido J. Falcone
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut
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316
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Sandholm N, Cole JB, Nair V, Sheng X, Liu H, Ahlqvist E, van Zuydam N, Dahlström EH, Fermin D, Smyth LJ, Salem RM, Forsblom C, Valo E, Harjutsalo V, Brennan EP, McKay GJ, Andrews D, Doyle R, Looker HC, Nelson RG, Palmer C, McKnight AJ, Godson C, Maxwell AP, Groop L, McCarthy MI, Kretzler M, Susztak K, Hirschhorn JN, Florez JC, Groop PH. Genome-wide meta-analysis and omics integration identifies novel genes associated with diabetic kidney disease. Diabetologia 2022; 65:1495-1509. [PMID: 35763030 PMCID: PMC9345823 DOI: 10.1007/s00125-022-05735-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 03/30/2022] [Indexed: 11/29/2022]
Abstract
AIMS/HYPOTHESIS Diabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets. METHODS We performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets. RESULTS The meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR<60 ml/min per 1.73 m2) and DKD (microalbuminuria or worse) phenotype (p=9.8×10-9; although not withstanding correction for multiple testing, p>9.3×10-9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN-RESP18, GPR158, INIP-SNX30, LSM14A and MFF; p<2.7×10-6). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in individuals with vs without DKD (p=1.1×10-6). The lead SNPs within six loci significantly altered DNA methylation of a nearby CpG site in kidneys (p<1.5×10-11). Expression of lead genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes (e.g. TENM2 expression correlated positively with eGFR [p=1.6×10-8] and negatively with tubulointerstitial fibrosis [p=2.0×10-9], tubular DCLK1 expression correlated positively with fibrosis [p=7.4×10-16], and SNX30 expression correlated positively with eGFR [p=5.8×10-14] and negatively with fibrosis [p<2.0×10-16]). CONCLUSIONS/INTERPRETATION Altogether, the results point to novel genes contributing to the pathogenesis of DKD. DATA AVAILABILITY The GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages ( https://t1d.hugeamp.org/downloads.html ; https://t2d.hugeamp.org/downloads.html ; https://hugeamp.org/downloads.html ).
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Affiliation(s)
- Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Joanne B Cole
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Viji Nair
- Michigan Medicine, Ann Arbor, MI, USA
| | - Xin Sheng
- Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Diabetes, Obesity, and Metabolism, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Hongbo Liu
- Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Diabetes, Obesity, and Metabolism, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Emma Ahlqvist
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University and Skåne University Hospital, Malmö, Sweden
| | - Natalie van Zuydam
- Pat Macpherson Centre for Pharmacogenetics & Pharmacogenomics, Cardiovascular & Diabetes Medicine, School of Medicine, University of Dundee, Dundee, UK
- Oxford Centre for Diabetes, Endocrinology & Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Emma H Dahlström
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | | | - Laura J Smyth
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Rany M Salem
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Carol Forsblom
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Erkka Valo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Valma Harjutsalo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Eoin P Brennan
- Diabetes Complications Research Centre, Conway Institute, School of Medicine, University College Dublin, Dublin, Ireland
| | - Gareth J McKay
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Darrell Andrews
- Diabetes Complications Research Centre, Conway Institute, School of Medicine, University College Dublin, Dublin, Ireland
| | - Ross Doyle
- Diabetes Complications Research Centre, Conway Institute, School of Medicine, University College Dublin, Dublin, Ireland
| | - Helen C Looker
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Robert G Nelson
- Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Colin Palmer
- Pat Macpherson Centre for Pharmacogenetics & Pharmacogenomics, Cardiovascular & Diabetes Medicine, School of Medicine, University of Dundee, Dundee, UK
| | - Amy Jayne McKnight
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Catherine Godson
- Diabetes Complications Research Centre, Conway Institute, School of Medicine, University College Dublin, Dublin, Ireland
| | - Alexander P Maxwell
- Molecular Epidemiology Research Group, Centre for Public Health, Queen's University Belfast, Belfast, UK
- Regional Nephrology Unit, Belfast City Hospital, Belfast, Northern Ireland, UK
| | - Leif Groop
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University and Skåne University Hospital, Malmö, Sweden
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Mark I McCarthy
- Oxford Centre for Diabetes, Endocrinology & Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - Katalin Susztak
- Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Diabetes, Obesity, and Metabolism, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Joel N Hirschhorn
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA.
- Departments of Pediatrics and Genetics, Harvard Medical School, Boston, MA, USA.
| | - Jose C Florez
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, Victoria, Australia.
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317
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Zhuo WQ, Wen Y, Luo HJ, Luo ZL, Wang L. Mechanisms of ferroptosis in chronic kidney disease. Front Mol Biosci 2022; 9:975582. [PMID: 36090053 PMCID: PMC9448928 DOI: 10.3389/fmolb.2022.975582] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 07/28/2022] [Indexed: 11/13/2022] Open
Abstract
Ferroptosis is a newly identified form of regulated cell death characterized by iron accumulation and lipid peroxidation. Ferroptosis plays an essential role in the pathology of numerous diseases and has emerged as a key area of focus in studies of chronic kidney disease (CKD). CKD is a major public health problem with high incidence and mortality that is characterized by a gradual loss of kidney function over time. The severity and complexity of CKD combined with the limited knowledge of its underlying molecular mechanism(s) have led to increased interest in this disease area. Here, we summarize recent advances in our understanding of the regulatory mechanism(s) of ferroptosis and highlight recent studies describing its role in the pathogenesis and progression of CKD. We further discuss the potential therapeutic benefits of targeting ferroptosis for the treatment of CKD and the major hurdles to overcome for the translation of in vitro studies into the clinic.
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Affiliation(s)
- Wen-Qing Zhuo
- Department of Nephrology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, China
| | - Yi Wen
- Department of General Surgery and Pancreatic Injury and Repair Key Laboratory of Sichuan Province, The General Hospital of Western Theater Command (Chengdu Military General Hospital), Chengdu, Sichuan, China
| | - Hui-Jun Luo
- Department of Biochemistry and Molecular Biology, Mayo Clinic Arizona, Scottsdale, AZ, United States
| | - Zhu-Lin Luo
- Department of General Surgery and Pancreatic Injury and Repair Key Laboratory of Sichuan Province, The General Hospital of Western Theater Command (Chengdu Military General Hospital), Chengdu, Sichuan, China
| | - Li Wang
- Department of Nephrology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
- Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, China
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318
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Olinger E, Schaeffer C, Kidd K, Elhassan EAE, Cheng Y, Dufour I, Schiano G, Mabillard H, Pasqualetto E, Hofmann P, Fuster DG, Kistler AD, Wilson IJ, Kmoch S, Raymond L, Robert T, Genomics England Research Consortium, Eckardt KU, Bleyer AJ, Köttgen A, Conlon PJ, Wiesener M, Sayer JA, Rampoldi L, Devuyst O. An intermediate-effect size variant in UMOD confers risk for chronic kidney disease. Proc Natl Acad Sci U S A 2022; 119:e2114734119. [PMID: 35947615 PMCID: PMC9388113 DOI: 10.1073/pnas.2114734119] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 05/04/2022] [Indexed: 12/12/2022] Open
Abstract
The kidney-specific gene UMOD encodes for uromodulin, the most abundant protein excreted in normal urine. Rare large-effect variants in UMOD cause autosomal dominant tubulointerstitial kidney disease (ADTKD), while common low-impact variants strongly associate with kidney function and the risk of chronic kidney disease (CKD) in the general population. It is unknown whether intermediate-effect variants in UMOD contribute to CKD. Here, candidate intermediate-effect UMOD variants were identified using large-population and ADTKD cohorts. Biological and phenotypical effects were investigated using cell models, in silico simulations, patient samples, and international databases and biobanks. Eight UMOD missense variants reported in ADTKD are present in the Genome Aggregation Database (gnomAD), with minor allele frequency (MAF) ranging from 10-5 to 10-3. Among them, the missense variant p.Thr62Pro is detected in ∼1/1,000 individuals of European ancestry, shows incomplete penetrance but a high genetic load in familial clusters of CKD, and is associated with kidney failure in the 100,000 Genomes Project (odds ratio [OR] = 3.99 [1.84 to 8.98]) and the UK Biobank (OR = 4.12 [1.32 to 12.85). Compared with canonical ADTKD mutations, the p.Thr62Pro carriers displayed reduced disease severity, with slower progression of CKD and an intermediate reduction of urinary uromodulin levels, in line with an intermediate trafficking defect in vitro and modest induction of endoplasmic reticulum (ER) stress. Identification of an intermediate-effect UMOD variant completes the spectrum of UMOD-associated kidney diseases and provides insights into the mechanisms of ADTKD and the genetic architecture of CKD.
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Affiliation(s)
- Eric Olinger
- Institute of Physiology, University of Zurich, CH-8057 Zurich, Switzerland
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne NE1 3BZ, United Kingdom
| | - Céline Schaeffer
- Molecular Genetics of Renal Disorders, Division of Genetics and Cell Biology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Ospedale San Raffaele, Milan, 20132 Italy
| | - Kendrah Kidd
- Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC 27101
- Department of Pediatrics and Inherited Metabolic Disorders, First Faculty of Medicine, Charles University, 128 08 Prague, Czech Republic
| | - Elhussein A. E. Elhassan
- Division of Nephrology, Beaumont General Hospital, 1297 Dublin, Ireland
- Department of Medicine, Royal College of Surgeons in Ireland, 1297 Dublin, Ireland
| | - Yurong Cheng
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, D-79106 Freiburg, Germany
- Faculty of Biology, University of Freiburg, D-79106 Freiburg, Germany
| | - Inès Dufour
- Institute of Physiology, University of Zurich, CH-8057 Zurich, Switzerland
- Division of Nephrology, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
| | - Guglielmo Schiano
- Institute of Physiology, University of Zurich, CH-8057 Zurich, Switzerland
| | - Holly Mabillard
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne NE1 3BZ, United Kingdom
- Renal Services, Newcastle Upon Tyne Hospitals National Health Service Trust, Newcastle upon Tyne NE7 7DN, United Kingdom
| | - Elena Pasqualetto
- Molecular Genetics of Renal Disorders, Division of Genetics and Cell Biology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Ospedale San Raffaele, Milan, 20132 Italy
| | - Patrick Hofmann
- Institute of Physiology, University of Zurich, CH-8057 Zurich, Switzerland
| | - Daniel G. Fuster
- Department of Nephrology and Hypertension, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
| | - Andreas D. Kistler
- Department of Medicine, Cantonal Hospital Frauenfeld, 8501 Frauenfeld, Switzerland
| | - Ian J. Wilson
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE1 3BZ, United Kingdom
| | - Stanislav Kmoch
- Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC 27101
- Department of Pediatrics and Inherited Metabolic Disorders, First Faculty of Medicine, Charles University, 128 08 Prague, Czech Republic
| | - Laure Raymond
- Genetics Department, Laboratoire Eurofins Biomnis, Lyon, 69007 France
| | - Thomas Robert
- Centre de Néphrologie et Transplantation Rénale, Centre Hospitalier Universitaire (CHU) la Conception, Assistance Publique - Hôpitaux de Marseille (AP-HM), Marseille, 13005 France
- Marseille Medical Genetics, Bioinformatics & Genetics, Unité Mixte de Recherche (UMR)_S910, Aix-Marseille Université, Marseille, 13005 France
| | | | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, 91054 Erlangen, Germany
| | - Anthony J. Bleyer
- Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC 27101
- Department of Pediatrics and Inherited Metabolic Disorders, First Faculty of Medicine, Charles University, 128 08 Prague, Czech Republic
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, D-79106 Freiburg, Germany
- Centre for Integrative Biological Signalling Studies, University of Freiburg, D-79106 Freiburg, Germany
| | - Peter J. Conlon
- Division of Nephrology, Beaumont General Hospital, 1297 Dublin, Ireland
- Department of Medicine, Royal College of Surgeons in Ireland, 1297 Dublin, Ireland
| | - Michael Wiesener
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, 91054 Erlangen, Germany
| | - John A. Sayer
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne NE1 3BZ, United Kingdom
- Renal Services, Newcastle Upon Tyne Hospitals National Health Service Trust, Newcastle upon Tyne NE7 7DN, United Kingdom
- National Institute for Health and Care Research (NIHR) Newcastle Biomedical Research Centre, Newcastle upon Tyne NE4 5PL, United Kingdom
| | - Luca Rampoldi
- Molecular Genetics of Renal Disorders, Division of Genetics and Cell Biology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Ospedale San Raffaele, Milan, 20132 Italy
| | - Olivier Devuyst
- Institute of Physiology, University of Zurich, CH-8057 Zurich, Switzerland
- Division of Nephrology, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
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319
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A polygenic score predicts CKD across ancestries. Nat Rev Nephrol 2022; 18:681-682. [PMID: 35953653 DOI: 10.1038/s41581-022-00622-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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320
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Vaura F, Kim H, Udler MS, Salomaa V, Lahti L, Niiranen T, FinnGen*. Multi-Trait Genetic Analysis Reveals Clinically Interpretable Hypertension Subtypes. Circ Genom Precis Med 2022; 15:e003583. [PMID: 35604428 PMCID: PMC9558213 DOI: 10.1161/circgen.121.003583] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Hypertension comprises a heterogeneous range of phenotypes. We asked whether underlying genetic structure could explain a part of this heterogeneity.
Methods:
Our study sample comprised N=198 148 FinnGen participants (56% women, mean age 58 years) and N=21 168 well-phenotyped FINRISK participants (53% women, mean age 50 years). First, we identified genetic hypertension components with an unsupervised Bayesian non-negative matrix factorization algorithm using public genome-wide association data for 144 genetic hypertension variants and 16 clinical traits. For these components, we computed their (1) cross-sectional associations with clinical traits in FINRISK using linear regression and (2) longitudinal associations with incident adverse outcomes in FinnGen using Cox regression.
Results:
We observed 4 genetic hypertension components corresponding to recognizable clinical phenotypes: obesity (high body mass index), dyslipidemia (low high-density lipoprotein cholesterol and high triglycerides), hypolipidemia (low low-density lipoprotein cholesterol and low total cholesterol), and short stature. In FINRISK, all hypertension components had robust associations with their respective clinical characteristics. In FinnGen, the Obesity component was associated with increased diabetes risk (hazard ratio per 1 SD increase 1.08 [Bonferroni corrected CI, 1.05–1.10]) and the Hypolipidemia component with increased autoimmune disease risk (hazard ratio per 1 SD increase 1.05 [Bonferroni corrected CI, 1.03–1.07]). In addition, all hypertension components were related to both hypertension and cardiovascular disease.
Conclusions:
Our unsupervised analysis demonstrates that the genetic basis of hypertension can be understood as a mixture of 4 broad, clinically interpretable components capturing disease heterogeneity. These components could be used to stratify individuals into specific genetic subtypes and, therefore, to benefit personalized health care and pharmaceutical research.
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Affiliation(s)
- Felix Vaura
- Department of Internal Medicine (F.V., T.N.), University of Turku, Turku, Finland
| | - Hyunkyung Kim
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston (H.K., M.U.)
- Broad Institute of MIT and Harvard, Cambridge, MA (H.K., M.U.)
| | - Miriam S. Udler
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston (H.K., M.U.)
| | - Veikko Salomaa
- Department of Public Health & Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland (V.S., T.N.)
| | - Leo Lahti
- Department of Computing (L.L.), University of Turku, Turku, Finland
| | - Teemu Niiranen
- Department of Internal Medicine (F.V., T.N.), University of Turku, Turku, Finland
- Department of Public Health & Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland (V.S., T.N.)
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321
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Devuyst O, Bochud M, Olinger E. UMOD and the architecture of kidney disease. Pflugers Arch 2022; 474:771-781. [PMID: 35881244 PMCID: PMC9338900 DOI: 10.1007/s00424-022-02733-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 07/12/2022] [Accepted: 07/13/2022] [Indexed: 12/17/2022]
Abstract
The identification of genetic factors associated with the risk, onset, and progression of kidney disease has the potential to provide mechanistic insights and therapeutic perspectives. In less than two decades, technological advances yielded a trove of information on the genetic architecture of chronic kidney disease. The spectrum of genetic influence ranges from (ultra)rare variants with large effect size, involved in Mendelian diseases, to common variants, often non-coding and with small effect size, which contribute to polygenic diseases. Here, we review the paradigm of UMOD, the gene coding for uromodulin, to illustrate how a kidney-specific protein of major physiological importance is involved in a spectrum of kidney disorders. This new field of investigation illustrates the importance of genetic variation in the pathogenesis and prognosis of disease, with therapeutic implications.
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Affiliation(s)
- Olivier Devuyst
- Institute of Physiology, University of Zurich, 8057, Zurich, Switzerland.
| | - Murielle Bochud
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1010, Lausanne, Switzerland
| | - Eric Olinger
- Institute of Physiology, University of Zurich, 8057, Zurich, Switzerland
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE1 3BZ, UK
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322
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Jefferis J, Pelecanos A, Catts V, Mallett A. The Heritability of Kidney Function Using an Older Australian Twin Population. Kidney Int Rep 2022; 7:1819-1830. [PMID: 35967118 PMCID: PMC9366362 DOI: 10.1016/j.ekir.2022.05.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 03/31/2022] [Accepted: 05/10/2022] [Indexed: 11/25/2022] Open
Abstract
Introduction Twin studies are unique population models which estimate observed rather than inferred genetic components of complex traits. Nonmonogenic chronic kidney disease (CKD) is a complex disease process with strong genetic and environmental influences, amenable to twin studies. We aimed to assess the heritability of CKD using twin analysis and modeling within Older Australian Twin Study (OATS) data. Methods OATS had 109 dizygotic (DZ) and 126 monozygotic (MZ) twin pairs with paired serum creatinine levels. Heritability of kidney function as estimated glomerular filtration rate (eGFR CKD Epidemiology Collaboration [CKD-EPI]) was modeled using the ACE model to estimate additive heritability (A), common (C), and unique (E) environmental factors. Intratwin pair analysis using mixed effects logistic regression allowed analysis of variation in eGFR from established CKD risk factors. Results The median age was 69.71 (interquartile range 78.4-83.0) years, with 65% female, and a mean CKD-EPI of 82.8 ml/min (SD 6.7). The unadjusted ACE model determined kidney function to be 33% genetically determined (A), 18% shared genetic-environmental (C), and 49% because of unique environment (E). This remained unchanged when adjusted for age, hypertension, and sex. Hypertension was associated with eGFR; however, intertwin variance in hypertension did not explain variance in eGFR. Two or more hypertension medications were associated with decreased eGFR (P = 0.009). Conclusion This study estimates observed heritability at 33%, notably higher than inferred heritability in genome-wide association study (GWAS) (7.1%-18%). Epigenetics and other genomic phenomena may explain this heritability gap. Difference in antihypertension medications explains part of unique environmental exposures, though discordance in hypertension and diabetes does not.
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Affiliation(s)
- Julia Jefferis
- Department of Renal Medicine, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia
| | - Anita Pelecanos
- Statistics Unit, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Vibeke Catts
- Centre for Healthy Brain Ageing, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Andrew Mallett
- Institute for Molecular Bioscience and Faculty of Medicine, The University of Queensland, St Lucia, Queensland, Australia
- Department of Renal Medicine, Townsville University Hospital, Douglas, Queensland, Australia
- College of Medicine and Dentistry, James Cook University, Douglas, Queensland, Australia
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323
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Akwo EA, Chen HC, Liu G, Triozzi JL, Tao R, Yu Z, Chung CP, Giri A, Ikizler TA, Stein CM, Siew ED, Feng Q, Robinson-Cohen C, Hung AM, the VA Million Veteran Program 12. Phenome-Wide Association Study of UMOD Gene Variants and Differential Associations With Clinical Outcomes Across Populations in the Million Veteran Program a Multiethnic Biobank. Kidney Int Rep 2022; 7:1802-1818. [PMID: 35967117 PMCID: PMC9366371 DOI: 10.1016/j.ekir.2022.05.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 04/22/2022] [Accepted: 05/09/2022] [Indexed: 11/19/2022] Open
Abstract
Introduction Common variants in the UMOD gene are considered an evolutionary adaptation against urinary tract infections (UTIs) and have been implicated in kidney stone formation, chronic kidney disease (CKD), and hypertension. However, differences in UMOD variant-phenotype associations across population groups are unclear. Methods We tested associations between UMOD/PDILT variants and up to 1528 clinical diagnosis codes mapped to phenotype groups in the Million Veteran Program (MVP), using published phenome-wide association study (PheWAS) methodology. Associations were tested using logistic regression adjusted for age, sex, and 10 principal components of ancestry. Bonferroni correction for multiple comparisons was applied. Results Among 648,593 veterans, mean (SD) age was 62 (14) years; 9% were female, 19% Black, and 8% Hispanic. In White patients, the rs4293393 UMOD risk variant associated with increased uromodulin was associated with increased odds of CKD (odds ratio [OR]: 1.22, 95% CI: 1.20-1.24, P = 5.90 × 10-111), end-stage kidney disease (OR: 1.17, 95% CI: 1.11-1.24, P = 2.40 × 10-09), and hypertension (OR: 1.03, 95% CI: 1.05-1.05, P = 2.11 × 10-06) and significantly lower odds of UTIs (OR: 0.94, 95% CI: 0.92-0.96, P = 1.21 × 10-10) and kidney calculus (OR: 0.85, 95% CI: 0.83-0.86, P = 4.27 × 10-69). Similar findings were observed across UMOD/PDILT variants. The rs77924615 PDILT variant had stronger associations with acute cystitis in White female (OR: 0.73, 95% CI: 0.59-0.91, P = 4.98 × 10-03) versus male (OR: 0.99, 95% CI: 0.89-1.11, P = 8.80 × 10-01) (P interaction = 0.01) patients. In Black patients, the rs77924615 PDILT variant was significantly associated with pyelonephritis (OR: 0.65, 95% CI: 0.54-0.79, P = 1.05 × 10-05), whereas associations with UMOD promoter variants were attenuated. Conclusion Robust associations were observed between UMOD/PDILT variants linked with increased uromodulin expression and lower odds of UTIs and calculus and increased odds of CKD and hypertension. However, these associations varied significantly across ancestry groups and sex.
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Affiliation(s)
- Elvis A. Akwo
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Center for Kidney Disease, Nashville, Tennessee, USA
- VA Tennessee Valley Healthcare System, Nashville, Tennessee, USA
| | - Hua-Chang Chen
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Ge Liu
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jefferson L. Triozzi
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Genetics Institute, Nashville, Tennessee, USA
| | - Zhihong Yu
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Cecilia P. Chung
- VA Tennessee Valley Healthcare System, Nashville, Tennessee, USA
- Vanderbilt Genetics Institute, Nashville, Tennessee, USA
- Division of Rheumatology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Ayush Giri
- Vanderbilt Genetics Institute, Nashville, Tennessee, USA
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - T. Alp Ikizler
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Center for Kidney Disease, Nashville, Tennessee, USA
- VA Tennessee Valley Healthcare System, Nashville, Tennessee, USA
| | - C. Michael Stein
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Edward D. Siew
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Center for Kidney Disease, Nashville, Tennessee, USA
- VA Tennessee Valley Healthcare System, Nashville, Tennessee, USA
| | - QiPing Feng
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Cassianne Robinson-Cohen
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Center for Kidney Disease, Nashville, Tennessee, USA
- VA Tennessee Valley Healthcare System, Nashville, Tennessee, USA
| | - Adriana M. Hung
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Center for Kidney Disease, Nashville, Tennessee, USA
- VA Tennessee Valley Healthcare System, Nashville, Tennessee, USA
| | - the VA Million Veteran Program12
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Center for Kidney Disease, Nashville, Tennessee, USA
- VA Tennessee Valley Healthcare System, Nashville, Tennessee, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Genetics Institute, Nashville, Tennessee, USA
- Division of Rheumatology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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324
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Akwo E, Pike MM, Ertuglu LA, Vartanian N, Farber-Eger E, Lipworth L, Perwad F, Siew E, Hung A, Bansal N, de Boer I, Kestenbaum B, Cox NJ, Ikizler TA, Wells Q, Robinson-Cohen C. Association of Genetically Predicted Fibroblast Growth Factor-23 with Heart Failure: A Mendelian Randomization Study. Clin J Am Soc Nephrol 2022; 17:1183-1193. [PMID: 35902130 PMCID: PMC9435988 DOI: 10.2215/cjn.00960122] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Accepted: 05/31/2022] [Indexed: 01/12/2023]
Abstract
BACKGROUND AND OBJECTIVES Elevated fibroblast growth factor-23 (FGF23) has been consistently associated with heart failure, particularly heart failure with preserved ejection fraction, among patients with CKD and in the general population. FGF23 may directly induce cardiac remodeling and heart failure. However, biases affecting observational studies impede robust causal inferences. Mendelian randomization leverages genetic determinants of a risk factor to examine causality. We performed a two-sample Mendelian randomization to assess causal associations between FGF23 and heart failure. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS Genetic instruments were genome-wide significant genetic variants associated with FGF23, including variants near PIP5K1B, RGS14, LINC01229, and CYP24A1. We analyzed data from the Heart Failure Molecular Epidemiology for Therapeutic Targets and BioVU biobanks to examine associations of the four variants with overall heart failure, heart failure with preserved ejection fraction, and heart failure with reduced and mid-range ejection fraction. We developed an eGFR polygenic risk score using summary statistics from the Chronic Kidney Disease Genetics Consortium (CKDGen) genome-wide association study of eGFR in >1 million individuals and performed stratified analyses across eGFR polygenic risk score strata. RESULTS Genetically determined FGF23 was not associated with overall heart failure in the Heart Failure Molecular Epidemiology for Therapeutic Targets consortium (odds ratio, 1.13; 95% confidence interval, 0.89 to 1.42 per unit higher genetically predicted log FGF23) and the full BioVU sample (odds ratio, 1.32; 95% confidence interval, 0.95 to 1.84). In stratified analyses in BioVU, higher FGF23 was associated with overall heart failure (odds ratio, 3.09; 95% confidence interval, 1.38 to 6.91) among individuals with low eGFR-polygenic risk score (<1 SD below the mean), but not those with high eGFR-polygenic risk score (P interaction = 0.02). Higher FGF23 was also associated with heart failure with preserved ejection fraction among all BioVU participants (odds ratio, 1.47; 95% confidence interval, 1.01 to 2.14) and individuals with low eGFR-polygenic risk score (odds ratio, 7.20; 95% confidence interval, 2.80 to 18.49), but not those high eGFR-polygenic risk score (P interaction = 2.25 × 10-4). No significant associations were observed with heart failure with reduced and midrange ejection fraction. CONCLUSION We found no association between genetically predicted FGF23 and heart failure in the Heart Failure Molecular Epidemiology for Therapeutic Targets consortium. In BioVU, genetically elevated FGF23 was associated with higher heart failure risk, specifically heart failure with preserved ejection fraction, particularly among individuals with low genetically predicted eGFR. PODCAST This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_07_28_CJN00960122.mp3.
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Affiliation(s)
- Elvis Akwo
- Division of Nephrology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Mindy M. Pike
- Division of Nephrology, Vanderbilt University Medical Center, Nashville, Tennessee,Division of Cardiovascular Medicine, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Lale A. Ertuglu
- Division of Nephrology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Nicholas Vartanian
- Division of Nephrology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Eric Farber-Eger
- Division of Cardiovascular Medicine, Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee,Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Loren Lipworth
- Division of Nephrology, Vanderbilt University Medical Center, Nashville, Tennessee,Division of Cardiovascular Medicine, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Farzana Perwad
- Division of Pediatric Nephrology, University of California San Francisco, San Francisco, California
| | - Edward Siew
- Division of Nephrology, Vanderbilt University Medical Center, Nashville, Tennessee,Division of Nephrology, Vanderbilt Tennessee Valley Healthcare System, Nashville, Tennessee
| | - Adriana Hung
- Division of Nephrology, Vanderbilt University Medical Center, Nashville, Tennessee,Division of Nephrology, Vanderbilt Tennessee Valley Healthcare System, Nashville, Tennessee
| | - Nisha Bansal
- Division of Nephrology, Vanderbilt Tennessee Valley Healthcare System, Nashville, Tennessee
| | - Ian de Boer
- Division of Nephrology, University of Washington, Seattle, Washington
| | - Bryan Kestenbaum
- Division of Nephrology, University of Washington, Seattle, Washington
| | - Nancy J. Cox
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - T. Alp Ikizler
- Division of Nephrology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Quinn Wells
- Division of Cardiovascular Medicine, Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, Tennessee,Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
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325
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Rajcsanyi LS, Diebels I, Pastoors L, Kanber D, Peters T, Volckmar AL, Zheng Y, Grosse M, Dieterich C, Hebebrand J, Kaiser FJ, Horsthemke B, Hinney A. Evidence for correlations between BMI-associated SNPs and circRNAs. Sci Rep 2022; 12:12643. [PMID: 35879369 PMCID: PMC9314347 DOI: 10.1038/s41598-022-16495-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 07/11/2022] [Indexed: 11/25/2022] Open
Abstract
Circular RNAs (circRNAs) are regulators of processes like adipogenesis. Their expression can be modulated by SNPs. We analysed links between BMI-associated SNPs and circRNAs. First, we detected an enrichment of BMI-associated SNPs on circRNA genomic loci in comparison to non-significant variants. Analysis of sex-stratified GWAS data revealed that circRNA genomic loci encompassed more genome-wide significant BMI-SNPs in females than in males. To explore whether the enrichment is restricted to BMI, we investigated nine additional GWAS studies. We showed an enrichment of trait-associated SNPs in circRNAs for four analysed phenotypes (body height, chronic kidney disease, anorexia nervosa and autism spectrum disorder). To analyse the influence of BMI-affecting SNPs on circRNA levels in vitro, we examined rs4752856 located on hsa_circ_0022025. The analysis of heterozygous individuals revealed an increased level of circRNA derived from the BMI-increasing SNP allele. We conclude that genetic variation may affect the BMI partly through circRNAs.
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Affiliation(s)
- Luisa Sophie Rajcsanyi
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany. .,Center for Translational Neuro- and Behavioural Sciences, University Hospital Essen, Essen, Germany.
| | - Inga Diebels
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Lydia Pastoors
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Deniz Kanber
- Institute of Human Genetics, University Hospital Essen, Essen, Germany
| | - Triinu Peters
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.,Center for Translational Neuro- and Behavioural Sciences, University Hospital Essen, Essen, Germany
| | - Anna-Lena Volckmar
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
| | - Yiran Zheng
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.,Center for Translational Neuro- and Behavioural Sciences, University Hospital Essen, Essen, Germany
| | - Martin Grosse
- Institute of Human Genetics, University Hospital Essen, Essen, Germany
| | - Christoph Dieterich
- Department of Internal Medicine III, University Hospital Heidelberg, Heidelberg, Germany.,German Center for Cardiovascular Research (DZHK), Partner site Heidelberg/Mannheim, Heidelberg, Germany
| | - Johannes Hebebrand
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.,Center for Translational Neuro- and Behavioural Sciences, University Hospital Essen, Essen, Germany
| | - Frank J Kaiser
- Institute of Human Genetics, University Hospital Essen, Essen, Germany
| | | | - Anke Hinney
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany. .,Center for Translational Neuro- and Behavioural Sciences, University Hospital Essen, Essen, Germany.
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326
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Park S, Lee S, Kim Y, Cho S, Huh H, Kim K, Kim YC, Han SS, Lee H, Lee JP, Joo KW, Lim CS, Kim YS, Kim DK. Mendelian randomization reveals causal effects of kidney function on various biochemical parameters. Commun Biol 2022; 5:713. [PMID: 35856088 PMCID: PMC9293908 DOI: 10.1038/s42003-022-03659-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Accepted: 06/28/2022] [Indexed: 11/30/2022] Open
Abstract
The kidney is a vital organ with diverse biological effects and the burden of kidney function impairment is increasing in modern medicine. As the effects from kidney function on diverse biochemical parameters are yet fully understood, additional investigation to reveal the causal effects is warranted. Here we show the causal estimates from kidney function parameter, estimated glomerular filtration rate (eGFR), on 60 biochemical parameters by performing two-sample Mendelian randomization (MR) study in 337,138 white British UK Biobank participants. A higher genetically predicted eGFR was significantly associated with higher lymphocyte percentage, HDL cholesterol, and alanine aminotransferase. The causal estimates indicated that a higher genetically predicted eGFR was associated with lower urea, urate, insulin growth factor-1, and triglycerides levels. The parameters with significant but non-linear causal estimates were hemoglobin concentration, calcium, vitamin D, and urine creatinine values, identified by non-linear MR. Healthcare providers should understand that changes in eGFR may affect the identified biochemical parameters in diverse patterns. Future study is warranted to expand the knowledge of the mechanisms and clinical implications of the causal effects of eGFR on various biochemical parameters.
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Affiliation(s)
- Sehoon Park
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
| | - Soojin Lee
- Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Korea.,Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Yaerim Kim
- Department of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea
| | - Semin Cho
- Department of Internal Medicine, Chung-Ang University Gwangmyeong Hospital, Gyeonggi-do, Korea
| | - Hyeok Huh
- Department of Internal Medicine, Inje University Busan Paik Hospital, Busan, Korea
| | - Kwangsoo Kim
- Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul, Korea
| | - Yong Chul Kim
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Seung Seok Han
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea.,Kidney Research Institute, Seoul National University, Seoul, Korea
| | - Hajeong Lee
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea
| | - Jung Pyo Lee
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.,Kidney Research Institute, Seoul National University, Seoul, Korea.,Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Korea
| | - Kwon Wook Joo
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.,Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea.,Kidney Research Institute, Seoul National University, Seoul, Korea
| | - Chun Soo Lim
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.,Kidney Research Institute, Seoul National University, Seoul, Korea.,Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Korea
| | - Yon Su Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea.,Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.,Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea.,Kidney Research Institute, Seoul National University, Seoul, Korea
| | - Dong Ki Kim
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea. .,Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea. .,Kidney Research Institute, Seoul National University, Seoul, Korea.
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327
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Ortiz A. Benchmarking CKD: incidence of CKD in a European country with low prevalence of CKD and kidney replacement therapy. Clin Kidney J 2022; 15:1221-1225. [PMID: 35756737 PMCID: PMC9217648 DOI: 10.1093/ckj/sfac074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Indexed: 12/03/2022] Open
Abstract
Iceland was one of six European countries with an adjusted incidence of kidney replacement therapy (KRT) in 2018 lower than 100 per million persons (pmp), along with Estonia, Montenegro, Russia, Serbia and Finland. It was also one of 10 countries with an adjusted KRT prevalence <900 pmp. Furthermore, the prevalence of chronic kidney disease (CKD) in Iceland is up to 2.44-fold lower and the death rate from CKD up to 3.44-fold lower than in other countries with a low incidence of KRT, suggesting that the low KRT incidence actually reflects a low need for KRT rather than low uptake or availability of KRT. This identifies Iceland as a benchmark for countries trying to reduce KRT incidence. Iceland also represents one of the best genetically characterized populations in the world, facilitating studies on the influence of the genetic background versus environment and lifestyle on CKD. This issue of CKJ reports the incidence and risk factors for CKD in Icelandic adults. Diabetes, acute kidney injury, hypertension, cardiovascular disease, chronic lung disease, malignancy and major psychiatric illness were associated with an increased risk of incident CKD, as were obesity and sleep apnea in women. However, in 75% of incident CKD cases, CKD was first detected in category G3 or higher, emphasizing the need for new tools that allow an earlier diagnosis of CKD that precedes the loss of >50% of the functioning kidney mass and/or wider use of albuminuria as a screening tool. The European Society of Cardiology just recommended assessing albuminuria for routine cardiovascular risk workups for all.
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Affiliation(s)
- Alberto Ortiz
- IIS-Fundacion Jimenez Diaz UAM,
Madrid, Spain
- RICORS2040, Madrid, Spain
- Department of Medicine, School of Medicine, Universidad Autonoma de
Madrid, Madrid, Spain
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328
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Cross-ancestry genome-wide polygenic score predicts chronic kidney disease. Nat Med 2022; 28:1355-1356. [PMID: 35739270 DOI: 10.1038/s41591-022-01871-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
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329
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Liu H, Doke T, Guo D, Sheng X, Ma Z, Park J, Vy HMT, Nadkarni GN, Abedini A, Miao Z, Palmer M, Voight BF, Li H, Brown CD, Ritchie MD, Shu Y, Susztak K. Epigenomic and transcriptomic analyses define core cell types, genes and targetable mechanisms for kidney disease. Nat Genet 2022; 54:950-962. [PMID: 35710981 PMCID: PMC11626562 DOI: 10.1038/s41588-022-01097-w] [Citation(s) in RCA: 114] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 05/09/2022] [Indexed: 12/29/2022]
Abstract
More than 800 million people suffer from kidney disease, yet the mechanism of kidney dysfunction is poorly understood. In the present study, we define the genetic association with kidney function in 1.5 million individuals and identify 878 (126 new) loci. We map the genotype effect on the methylome in 443 kidneys, transcriptome in 686 samples and single-cell open chromatin in 57,229 kidney cells. Heritability analysis reveals that methylation variation explains a larger fraction of heritability than gene expression. We present a multi-stage prioritization strategy and prioritize target genes for 87% of kidney function loci. We highlight key roles of proximal tubules and metabolism in kidney function regulation. Furthermore, the causal role of SLC47A1 in kidney disease is defined in mice with genetic loss of Slc47a1 and in human individuals carrying loss-of-function variants. Our findings emphasize the key role of bulk and single-cell epigenomic information in translating genome-wide association studies into identifying causal genes, cellular origins and mechanisms of complex traits.
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Affiliation(s)
- Hongbo Liu
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Tomohito Doke
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Dong Guo
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Baltimore, MD, USA
| | - Xin Sheng
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ziyuan Ma
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Joseph Park
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ha My T Vy
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Girish N Nadkarni
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Hasso Plattner Institute of Digital Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Amin Abedini
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Zhen Miao
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew Palmer
- Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, USA
| | - Benjamin F Voight
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Hongzhe Li
- Department of Biostatistics, Epidemiology, and Informatics, and Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yan Shu
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Baltimore, MD, USA
| | - Katalin Susztak
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA.
- Institute of Diabetes Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA.
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330
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Mohammadi-Shemirani P, Chong M, Perrot N, Pigeyre M, Steinberg GR, Paré G, Krepinsky JC, Lanktree MB. ACLY and CKD: A Mendelian Randomization Analysis. Kidney Int Rep 2022; 7:1673-1681. [PMID: 35812273 PMCID: PMC9263230 DOI: 10.1016/j.ekir.2022.04.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 04/06/2022] [Accepted: 04/11/2022] [Indexed: 11/15/2022] Open
Abstract
Introduction Adenosine triphosphate-citrate lyase (ACLY) inhibition is a therapeutic strategy under investigation for atherosclerotic cardiovascular disease, nonalcoholic steatohepatitis, and metabolic syndrome. Mouse models suggest that ACLY inhibition could reduce inflammation and kidney fibrosis. Genetic analysis of ACLY in chronic kidney disease (CKD) has not been performed. Methods We constructed a genetic instrument by selecting variants associated with ACLY expression in the expression quantitative trait loci genetics consortium (eQTLGen) from blood samples from 31,684 participants. In a 2-sample Mendelian randomization analysis, we evaluated the effect of genetically predicted ACLY expression on the risk of CKD, estimated glomerular filtration rate (eGFR), and albumin-to-creatinine ratio (ACR) using the CKD Genetics (CKDGen) consortium, UK Biobank, and the Finnish Genetics (FinnGen) consortium totaling 66,396 CKD cases and 958,517 controls. Results ACLY is constitutively expressed in all cell types including in whole blood. The genetic instrument included 13 variants and explained 1.5% of the variation in whole blood ACLY gene expression. A 34% reduction in ACLY expression score was associated with a 0.04 mmol/l reduced low-density lipoprotein (LDL) cholesterol (P = 3.4 × 10-4) and a 9% reduced risk of CKD (stages 3, 4, 5, dialysis, or eGFR < 60 ml/min per 1.73 m2) (odds ratio [OR] = 0.91, 95% CI: 0.85-0.98, P = 0.008), but no association was observed with either eGFR or ACR. Conclusion Mendelian randomization analyses revealed that genetically reduced ACLY expression was associated with reduced risk of CKD but had no effect on either eGFR or ACR. Further evaluation of ACLY in kidney disease is warranted.
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Affiliation(s)
- Pedrum Mohammadi-Shemirani
- Department of Biomarkers and Genetics, Population Health Research Institute, Hamilton, Ontario, Canada.,Experimental Program, Thrombosis and Atherosclerosis Research Institute, Hamilton, Ontario, Canada.,Department of Medical Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Michael Chong
- Department of Biomarkers and Genetics, Population Health Research Institute, Hamilton, Ontario, Canada.,Experimental Program, Thrombosis and Atherosclerosis Research Institute, Hamilton, Ontario, Canada.,Department of Medical Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Nicolas Perrot
- Department of Biomarkers and Genetics, Population Health Research Institute, Hamilton, Ontario, Canada
| | - Marie Pigeyre
- Department of Biomarkers and Genetics, Population Health Research Institute, Hamilton, Ontario, Canada.,Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Gregory R Steinberg
- Division of Endocrinology and Metabolism, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.,Centre for Metabolism, Obesity, and Diabetes Research, McMaster University, Hamilton, Ontario, Canada.,Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Guillaume Paré
- Department of Biomarkers and Genetics, Population Health Research Institute, Hamilton, Ontario, Canada.,Experimental Program, Thrombosis and Atherosclerosis Research Institute, Hamilton, Ontario, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada.,Department of Health Research Methods, Evidence & Impact, McMaster University, Hamilton, Ontario, Canada
| | - Joan C Krepinsky
- Centre for Metabolism, Obesity, and Diabetes Research, McMaster University, Hamilton, Ontario, Canada.,Division of Nephrology, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.,Division of Nephrology, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada
| | - Matthew B Lanktree
- Department of Biomarkers and Genetics, Population Health Research Institute, Hamilton, Ontario, Canada.,Department of Health Research Methods, Evidence & Impact, McMaster University, Hamilton, Ontario, Canada.,Division of Nephrology, Department of Medicine, McMaster University, Hamilton, Ontario, Canada.,Division of Nephrology, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada
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331
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Khan A, Turchin MC, Patki A, Srinivasasainagendra V, Shang N, Nadukuru R, Jones AC, Malolepsza E, Dikilitas O, Kullo IJ, Schaid DJ, Karlson E, Ge T, Meigs JB, Smoller JW, Lange C, Crosslin DR, Jarvik GP, Bhatraju PK, Hellwege JN, Chandler P, Torvik LR, Fedotov A, Liu C, Kachulis C, Lennon N, Abul-Husn NS, Cho JH, Ionita-Laza I, Gharavi AG, Chung WK, Hripcsak G, Weng C, Nadkarni G, Irvin MR, Tiwari HK, Kenny EE, Limdi NA, Kiryluk K. Genome-wide polygenic score to predict chronic kidney disease across ancestries. Nat Med 2022; 28:1412-1420. [PMID: 35710995 PMCID: PMC9329233 DOI: 10.1038/s41591-022-01869-1] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 05/11/2022] [Indexed: 01/03/2023]
Abstract
Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (n = 97,050), 6 cohorts of African ancestry (n = 14,544), 4 cohorts of Asian ancestry (n = 8,625) and 2 admixed Latinx cohorts (n = 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the APOL1 risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.
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Affiliation(s)
- Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Michael C Turchin
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Amit Patki
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Vinodh Srinivasasainagendra
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Ning Shang
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Rajiv Nadukuru
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alana C Jones
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Ozan Dikilitas
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Daniel J Schaid
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Elizabeth Karlson
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Tian Ge
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - James B Meigs
- Division of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Jordan W Smoller
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Christoph Lange
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - David R Crosslin
- Division of Biomedical Informatics and Genomics, John W. Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA
| | - Gail P Jarvik
- Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Seattle, WA, USA
| | - Pavan K Bhatraju
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jacklyn N Hellwege
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Paulette Chandler
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Laura Rasmussen Torvik
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Alex Fedotov
- Irving Institute for Clinical and Translational Research, Columbia University, New York, NY, USA
| | - Cong Liu
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | | | - Niall Lennon
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Noura S Abul-Husn
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Division of Genomic Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Judy H Cho
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Ali G Gharavi
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Wendy K Chung
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Girish Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hemant K Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Division of Genomic Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Division of General Internal Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nita A Limdi
- Department of Neurology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA.
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Hill C, Avila-Palencia I, Maxwell AP, Hunter RF, McKnight AJ. Harnessing the Full Potential of Multi-Omic Analyses to Advance the Study and Treatment of Chronic Kidney Disease. FRONTIERS IN NEPHROLOGY 2022; 2:923068. [PMID: 37674991 PMCID: PMC10479694 DOI: 10.3389/fneph.2022.923068] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 05/30/2022] [Indexed: 09/08/2023]
Abstract
Chronic kidney disease (CKD) was the 12th leading cause of death globally in 2017 with the prevalence of CKD estimated at ~9%. Early detection and intervention for CKD may improve patient outcomes, but standard testing approaches even in developed countries do not facilitate identification of patients at high risk of developing CKD, nor those progressing to end-stage kidney disease (ESKD). Recent advances in CKD research are moving towards a more personalised approach for CKD. Heritability for CKD ranges from 30% to 75%, yet identified genetic risk factors account for only a small proportion of the inherited contribution to CKD. More in depth analysis of genomic sequencing data in large cohorts is revealing new genetic risk factors for common diagnoses of CKD and providing novel diagnoses for rare forms of CKD. Multi-omic approaches are now being harnessed to improve our understanding of CKD and explain some of the so-called 'missing heritability'. The most common omic analyses employed for CKD are genomics, epigenomics, transcriptomics, metabolomics, proteomics and phenomics. While each of these omics have been reviewed individually, considering integrated multi-omic analysis offers considerable scope to improve our understanding and treatment of CKD. This narrative review summarises current understanding of multi-omic research alongside recent experimental and analytical approaches, discusses current challenges and future perspectives, and offers new insights for CKD.
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Affiliation(s)
| | | | | | | | - Amy Jayne McKnight
- Centre for Public Health, Queen’s University Belfast, Belfast, United Kingdom
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333
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Rysz J, Franczyk B, Rysz-Górzyńska M, Gluba-Brzózka A. Are Alterations in DNA Methylation Related to CKD Development? Int J Mol Sci 2022; 23:7108. [PMID: 35806113 PMCID: PMC9267048 DOI: 10.3390/ijms23137108] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 06/17/2022] [Accepted: 06/18/2022] [Indexed: 12/29/2022] Open
Abstract
The modifications in genomic DNA methylation are involved in the regulation of normal and pathological cellular processes. The epigenetic regulation stimulates biological plasticity as an adaptive response to variations in environmental factors. The role of epigenetic changes is vital for the development of some diseases, including atherogenesis, cancers, and chronic kidney disease (CKD). The results of studies presented in this review have suggested that altered DNA methylation can modulate the expression of pro-inflammatory and pro-fibrotic genes, as well those essential for kidney development and function, thus stimulating renal disease progression. Abnormally increased homocysteine, hypoxia, and inflammation have been suggested to alter epigenetic regulation of gene expression in CKD. Studies of renal samples have demonstrated the relationship between variations in DNA methylation and fibrosis and variations in estimated glomerular filtration rate (eGFR) in human CKD. The unravelling of the genetic-epigenetic profile would enhance our understanding of processes underlying the development of CKD. The understanding of multifaceted relationship between DNA methylation, genes expression, and disease development and progression could improve the ability to identify individuals at risk of CKD and enable the choice of appropriate disease management.
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Affiliation(s)
- Jacek Rysz
- Department of Nephrology, Hypertension and Family Medicine, Medical University of Lodz, 113 Żeromskego Street, 90-549 Lodz, Poland; (J.R.); (B.F.)
| | - Beata Franczyk
- Department of Nephrology, Hypertension and Family Medicine, Medical University of Lodz, 113 Żeromskego Street, 90-549 Lodz, Poland; (J.R.); (B.F.)
| | - Magdalena Rysz-Górzyńska
- Department of Otolaryngology, Laryngological Oncology, Audiology and Phoniatrics, Medical Univesity of Lodz, 113 Żeromskego Street, 90-549 Lodz, Poland;
| | - Anna Gluba-Brzózka
- Department of Nephrology, Hypertension and Family Medicine, Medical University of Lodz, 113 Żeromskego Street, 90-549 Lodz, Poland; (J.R.); (B.F.)
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334
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Sex-specific association between coffee consumption and incident chronic kidney disease: a population-based analysis of 359,906 participants from the UK Biobank. Chin Med J (Engl) 2022; 135:1414-1424. [PMID: 35940879 PMCID: PMC9481436 DOI: 10.1097/cm9.0000000000002234] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND The risk for chronic kidney disease (CKD) is influenced by genetic predisposition, sex, and lifestyle. Previous research indicates that coffee is a potentially protective factor in CKD. The current study aims to investigate whether sex disparity exists in the coffee-CKD association, and whether genetic risk of CKD or genetic polymorphisms of caffeine metabolism affect this association. METHODS A total of 359,906 participants from the UK Biobank who were enrolled between 2006 and 2010 were included in this prospective cohort study, which aimed to estimate the hazard ratios for coffee intake and incident CKD using a Cox proportional hazard model. Allele scores of CKD and caffeine metabolism were additionally adjusted for in a subsample with qualified genetic data ( n = 255,343). Analyses stratified by genetic predisposition, comorbidities, and sex hormones were performed. Tests based on Bayesian model averaging were conducted to ascertain the robustness of the results. RESULTS Coffee was inversely associated with CKD in a dose-dependent manner. The effects of coffee did not differ across different strata of genetic risk for CKD, but were more evident among slower genetically predicted caffeine metabolizers. Significant sex disparity was observed ( P value for interaction = 0.013), in that coffee drinking was only associated with the risk reduction of CKD in females. Subgroup analysis revealed that testosterone and sex hormone-binding globulin (SHBG), but not estradiol, modified the coffee-CKD association. CONCLUSIONS In addition to the overall inverse coffee-CKD association that was observed in the general population, we could also establish that a sex disparity existed, in that females were more likely to experience the benefit of the association. Testosterone and SHBG may partly account for the sex disparity.
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335
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Winkler TW, Rasheed H, Teumer A, Gorski M, Rowan BX, Stanzick KJ, Thomas LF, Tin A, Hoppmann A, Chu AY, Tayo B, Thio CHL, Cusi D, Chai JF, Sieber KB, Horn K, Li M, Scholz M, Cocca M, Wuttke M, van der Most PJ, Yang Q, Ghasemi S, Nutile T, Li Y, Pontali G, Günther F, Dehghan A, Correa A, Parsa A, Feresin A, de Vries APJ, Zonderman AB, Smith AV, Oldehinkel AJ, De Grandi A, Rosenkranz AR, Franke A, Teren A, Metspalu A, Hicks AA, Morris AP, Tönjes A, Morgan A, Podgornaia AI, Peters A, Körner A, Mahajan A, Campbell A, Freedman BI, Spedicati B, Ponte B, Schöttker B, Brumpton B, Banas B, Krämer BK, Jung B, Åsvold BO, Smith BH, Ning B, Penninx BWJH, Vanderwerff BR, Psaty BM, Kammerer CM, Langefeld CD, Hayward C, Spracklen CN, Robinson-Cohen C, Hartman CA, Lindgren CM, Wang C, Sabanayagam C, Heng CK, Lanzani C, Khor CC, Cheng CY, Fuchsberger C, Gieger C, Shaffer CM, Schulz CA, Willer CJ, Chasman DI, Gudbjartsson DF, Ruggiero D, Toniolo D, Czamara D, Porteous DJ, Waterworth DM, Mascalzoni D, Mook-Kanamori DO, Reilly DF, Daw EW, Hofer E, Boerwinkle E, Salvi E, Bottinger EP, Tai ES, Catamo E, Rizzi F, Guo F, et alWinkler TW, Rasheed H, Teumer A, Gorski M, Rowan BX, Stanzick KJ, Thomas LF, Tin A, Hoppmann A, Chu AY, Tayo B, Thio CHL, Cusi D, Chai JF, Sieber KB, Horn K, Li M, Scholz M, Cocca M, Wuttke M, van der Most PJ, Yang Q, Ghasemi S, Nutile T, Li Y, Pontali G, Günther F, Dehghan A, Correa A, Parsa A, Feresin A, de Vries APJ, Zonderman AB, Smith AV, Oldehinkel AJ, De Grandi A, Rosenkranz AR, Franke A, Teren A, Metspalu A, Hicks AA, Morris AP, Tönjes A, Morgan A, Podgornaia AI, Peters A, Körner A, Mahajan A, Campbell A, Freedman BI, Spedicati B, Ponte B, Schöttker B, Brumpton B, Banas B, Krämer BK, Jung B, Åsvold BO, Smith BH, Ning B, Penninx BWJH, Vanderwerff BR, Psaty BM, Kammerer CM, Langefeld CD, Hayward C, Spracklen CN, Robinson-Cohen C, Hartman CA, Lindgren CM, Wang C, Sabanayagam C, Heng CK, Lanzani C, Khor CC, Cheng CY, Fuchsberger C, Gieger C, Shaffer CM, Schulz CA, Willer CJ, Chasman DI, Gudbjartsson DF, Ruggiero D, Toniolo D, Czamara D, Porteous DJ, Waterworth DM, Mascalzoni D, Mook-Kanamori DO, Reilly DF, Daw EW, Hofer E, Boerwinkle E, Salvi E, Bottinger EP, Tai ES, Catamo E, Rizzi F, Guo F, Rivadeneira F, Guilianini F, Sveinbjornsson G, Ehret G, Waeber G, Biino G, Girotto G, Pistis G, Nadkarni GN, Delgado GE, Montgomery GW, Snieder H, Campbell H, White HD, Gao H, Stringham HM, Schmidt H, Li H, Brenner H, Holm H, Kirsten H, Kramer H, Rudan I, Nolte IM, Tzoulaki I, Olafsson I, Martins J, Cook JP, Wilson JF, Halbritter J, Felix JF, Divers J, Kooner JS, Lee JJM, O'Connell J, Rotter JI, Liu J, Xu J, Thiery J, Ärnlöv J, Kuusisto J, Jakobsdottir J, Tremblay J, Chambers JC, Whitfield JB, Gaziano JM, Marten J, Coresh J, Jonas JB, Mychaleckyj JC, Christensen K, Eckardt KU, Mohlke KL, Endlich K, Dittrich K, Ryan KA, Rice KM, Taylor KD, Ho K, Nikus K, Matsuda K, Strauch K, Miliku K, Hveem K, Lind L, Wallentin L, Yerges-Armstrong LM, Raffield LM, Phillips LS, Launer LJ, Lyytikäinen LP, Lange LA, Citterio L, Klaric L, Ikram MA, Ising M, Kleber ME, Francescatto M, Concas MP, Ciullo M, Piratsu M, Orho-Melander M, Laakso M, Loeffler M, Perola M, de Borst MH, Gögele M, Bianca ML, Lukas MA, Feitosa MF, Biggs ML, Wojczynski MK, Kavousi M, Kanai M, Akiyama M, Yasuda M, Nauck M, Waldenberger M, Chee ML, Chee ML, Boehnke M, Preuss MH, Stumvoll M, Province MA, Evans MK, O'Donoghue ML, Kubo M, Kähönen M, Kastarinen M, Nalls MA, Kuokkanen M, Ghanbari M, Bochud M, Josyula NS, Martin NG, Tan NYQ, Palmer ND, Pirastu N, Schupf N, Verweij N, Hutri-Kähönen N, Mononen N, Bansal N, Devuyst O, Melander O, Raitakari OT, Polasek O, Manunta P, Gasparini P, Mishra PP, Sulem P, Magnusson PKE, Elliott P, Ridker PM, Hamet P, Svensson PO, Joshi PK, Kovacs P, Pramstaller PP, Rossing P, Vollenweider P, van der Harst P, Dorajoo R, Sim RZH, Burkhardt R, Tao R, Noordam R, Mägi R, Schmidt R, de Mutsert R, Rueedi R, van Dam RM, Carroll RJ, Gansevoort RT, Loos RJF, Felicita SC, Sedaghat S, Padmanabhan S, Freitag-Wolf S, Pendergrass SA, Graham SE, Gordon SD, Hwang SJ, Kerr SM, Vaccargiu S, Patil SB, Hallan S, Bakker SJL, Lim SC, Lucae S, Vogelezang S, Bergmann S, Corre T, Ahluwalia TS, Lehtimäki T, Boutin TS, Meitinger T, Wong TY, Bergler T, Rabelink TJ, Esko T, Haller T, Thorsteinsdottir U, Völker U, Foo VHX, Salomaa V, Vitart V, Giedraitis V, Gudnason V, Jaddoe VWV, Huang W, Zhang W, Wei WB, Kiess W, März W, Koenig W, Lieb W, Gao X, Sim X, Wang YX, Friedlander Y, Tham YC, Kamatani Y, Okada Y, Milaneschi Y, Yu Z, Stark KJ, Stefansson K, Böger CA, Hung AM, Kronenberg F, Köttgen A, Pattaro C, Heid IM. Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals. Commun Biol 2022; 5:580. [PMID: 35697829 PMCID: PMC9192715 DOI: 10.1038/s42003-022-03448-z] [Show More Authors] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 05/04/2022] [Indexed: 01/14/2023] Open
Abstract
Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM.
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Affiliation(s)
- Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.
| | - Humaira Rasheed
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Division of Medicine and Laboratory Sciences, University of Oslo, Oslo, Norway
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland
| | - Mathias Gorski
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Bryce X Rowan
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Veteran's Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
| | - Kira J Stanzick
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Laurent F Thomas
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- BioCore-Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
| | - Adrienne Tin
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Anselm Hoppmann
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | | | - Bamidele Tayo
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, USA
| | - Chris H L Thio
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Daniele Cusi
- Institute of Biomedical Technologies, National Research Council of Italy, Milan, Italy
- Bio4Dreams-Business Nursery for Life Sciences, Milan, Italy
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Karsten B Sieber
- Target Sciences-Genetics, GlaxoSmithKline, Collegeville, PA, USA
| | - Katrin Horn
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Man Li
- Division of Nephrology and Hypertension, Department of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Massimiliano Cocca
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
- Renal Division, Department of Medicine IV, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Sahar Ghasemi
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Teresa Nutile
- Institute of Genetics and Biophysics 'Adriano Buzzati-Traverso'-CNR, Naples, Italy
| | - Yong Li
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Giulia Pontali
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
- University of Trento, Department of Cellular, Computational and Integrative Biology-CIBIO, Trento, Italy
| | - Felix Günther
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
- Statistical Consulting Unit StaBLab, Department of Statistics, LMU Munich, Munich, Germany
| | - Abbas Dehghan
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
- Dementia Research Institute, Imperial College London, London, UK
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Afshin Parsa
- Division of Kidney, Urologic and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - Agnese Feresin
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Aiko P J de Vries
- Section of Nephrology, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, US National Institutes of Health, Baltimore, MD, USA
| | - Albert V Smith
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille, France
| | - Albertine J Oldehinkel
- Interdisciplinary Center of Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Alessandro De Grandi
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
| | - Alexander R Rosenkranz
- Department of Internal Medicine, Division of Nephrology, Medical University Graz, Graz, Austria
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Andrej Teren
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Heart Center Leipzig, Leipzig, Germany
| | - Andres Metspalu
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Andrew A Hicks
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
| | - Andrew P Morris
- Department of Health Data Science, University of Liverpool, Liverpool, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
| | - Anke Tönjes
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
| | - Anna Morgan
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | | | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Chair of Epidemiology, IBE, Faculty of Medicine, Ludwig-Maximilians-Universität München, München, Germany
| | - Antje Körner
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Department of Women and Child Health, Hospital for Children and Adolescents, University of Leipzig, Leipzig, Germany
- Center for Pediatric Research, University of Leipzig, Leipzig, Germany
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Archie Campbell
- Center for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Barry I Freedman
- Section on Nephrology, Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Beatrice Spedicati
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Belen Ponte
- Service de Néphrologie et Hypertension, Medicine Department, Geneva University Hospitals, Geneva, Switzerland
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research, University of Heidelberg, Heidelberg, Germany
| | - Ben Brumpton
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, 7030, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, 7600, Norway
| | - Bernhard Banas
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Bernhard K Krämer
- Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology, Pneumology), Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Bettina Jung
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
- Department of Nephrology and Rheumatology, Kliniken Südostbayern, Traunstein, Germany
| | - Bjørn Olav Åsvold
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Blair H Smith
- Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Boting Ning
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Brenda W J H Penninx
- Department of Psychiatry, VU University Medical Centre, Amsterdam, The Netherlands
| | - Brett R Vanderwerff
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Candace M Kammerer
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Carl D Langefeld
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Cassandra N Spracklen
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Cassianne Robinson-Cohen
- Department of Veteran's Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
- Vanderbilt University Medical Center, Division of Nephrology and Hypertension, Vanderbilt Center for Kidney Disease and Integrated Program for Acute Kidney Injury Research, and Vanderbilt Precision Nephrology Program Nashville, Nashville, TN, USA
| | - Catharina A Hartman
- Interdisciplinary Center of Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Cecilia M Lindgren
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, OX3 7LF, UK
| | - Chaolong Wang
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Chew-Kiat Heng
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Khoo Teck Puat-National University Children's Medical Institute, National University Health System, Singapore, Singapore
| | - Chiara Lanzani
- Nephrology and Dialysis Unit, Genomics of Renal Diseases and Hypertension Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Chiea-Chuen Khor
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Christian Fuchsberger
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Christian M Shaffer
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Cristen J Willer
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Iceland School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Daniela Ruggiero
- Institute of Genetics and Biophysics 'Adriano Buzzati-Traverso'-CNR, Naples, Italy
- IRCCS Neuromed, Pozzilli, Italy
| | | | - Darina Czamara
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - David J Porteous
- Center for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Center for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | | | - Deborah Mascalzoni
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
- Centre for Research Ethics & Bioethics, Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Dennis O Mook-Kanamori
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | | | - E Warwick Daw
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center, Houston, TX, USA
| | - Erika Salvi
- Neuroalgology Unit, Fondazione IRCCS Istituto Neurologico 'Carlo Besta', Milan, Italy
| | - Erwin P Bottinger
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Digital Health Center, Hasso Plattner Institute and University of Potsdam, Potsdam, Germany
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Duke - NUS Medical School, Singapore, Singapore
| | - Eulalia Catamo
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Federica Rizzi
- Bio4Dreams-Business Nursery for Life Sciences, Milan, Italy
- ePhood Scientific Unit, ePhood SRL, Milano, Italy
| | - Feng Guo
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Franco Guilianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Georg Ehret
- Cardiology, Geneva University Hospitals, Geneva, Switzerland
| | - Gerard Waeber
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ginevra Biino
- Institute of Molecular Genetics "Luigi Luca Cavalli-Sforza", National Research Council of Italy, Pavia, Italy
| | - Giorgia Girotto
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Giorgio Pistis
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Girish N Nadkarni
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Graciela E Delgado
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Grant W Montgomery
- Institute for Molecular Bioscience, University of Queensland, St Lucia, QLD, Australia
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Harry Campbell
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Harvey D White
- Green Lane Cardiovascular Service, Auckland City Hospital and University of Auckland, Auckland, New Zealand
| | - He Gao
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Helena Schmidt
- Research Unit Genetic Epidemiology, Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Medical University of Graz, Graz, Austria
| | - Hengtong Li
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research, University of Heidelberg, Heidelberg, Germany
| | - Hilma Holm
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
| | - Holgen Kirsten
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Holly Kramer
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, USA
- Division of Nephrology and Hypertension, Loyola University Chicago, Chicago, IL, USA
| | - Igor Rudan
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ioanna Tzoulaki
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
- Dementia Research Institute, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali University Hospital, Reykjavik, Iceland
| | - Jade Martins
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - James P Cook
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - James F Wilson
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Jan Halbritter
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
- Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Janine F Felix
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Jasmin Divers
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
- MRC-PHE Center for Environment and Health, School of Public Health, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Jeannette Jen-Mai Lee
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | | | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institutefor Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Jie Xu
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Joachim Thiery
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University of Leipzig, Leipzig, Germany
| | - Johan Ärnlöv
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- School of Health and Social Studies, Dalarna University, Stockholm, Sweden
| | - Johanna Kuusisto
- University of Eastern Finland, Kuopio, Finland
- Kuopio University Hospital, Kuopio, Finland
| | - Johanna Jakobsdottir
- Icelandic Heart Association, Kopavogur, Iceland
- The Center of Public Health Sciences, University of Iceland, Reykjavík, Iceland
| | - Johanne Tremblay
- Montreal University Hospital Research Center, CHUM, Montreal, QC, Canada
- CRCHUM, Montreal, QC, Canada
| | - John C Chambers
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
- MRC-PHE Center for Environment and Health, School of Public Health, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - John B Whitfield
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - John M Gaziano
- Department of Internal Medicine, Harvard Medical School, Boston, MA, USA
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, USA
| | - Jonathan Marten
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jost B Jonas
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Department of Ophthalmology, Medical Faculty Mannheim, University Heidelberg, Mannheim, Germany
- Instituteof Molecular and Clinical Ophthalmology, Basel, Switzerland
- Privatpraxis Prof Jonas und Dr Panda-Jonas, Heidelberg, Germany
| | - Josyf C Mychaleckyj
- Center for Public Health Genomics, University of Virginia, Charlottesville, Charlottesville, VA, USA
| | - Kaare Christensen
- Danish Aging Research Center, University of Southern Denmark, Odense C, Denmark
| | - Kai-Uwe Eckardt
- Intensive Care Medicine, Charité, Berlin, Germany
- Department of Nephrology and Hypertension, Friedrich Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Karlhans Endlich
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Department of Anatomy and Cell Biology, University Medicine Greifswald, Greifswald, Germany
| | - Katalin Dittrich
- Department of Women and Child Health, Hospital for Children and Adolescents, University of Leipzig, Leipzig, Germany
- Center for Pediatric Research, University of Leipzig, Leipzig, Germany
| | - Kathleen A Ryan
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kenneth M Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institutefor Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kevin Ho
- Geisinger Research, Biomedical and Translational Informatics Institute, Rockville, MD, USA
- Department of Nephrology, Geisinger, Danville, PA, USA
| | - Kjell Nikus
- Department of Cardiology, Heart Center, Tampere University Hospital, Tampere, Finland
- Department of Cardiology, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Koichi Matsuda
- Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, Ludwig-Maximilians-Universität München, München, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Kozeta Miliku
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Lars Lind
- Cardiovascular Epidemiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Lars Wallentin
- Cardiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden
| | | | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Lawrence S Phillips
- Atlanta VA Health Care System, Decatur, GA, USA
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, US National Institutes of Health, Bethesda, MD, USA
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado Denver-Anschutz Medical Campus, Aurora, CO, USA
| | - Lorena Citterio
- Nephrology and Dialysis Unit, Genomics of Renal Diseases and Hypertension Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Lucija Klaric
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marcus Ising
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Marcus E Kleber
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | | | - Maria Pina Concas
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Marina Ciullo
- Institute of Genetics and Biophysics 'Adriano Buzzati-Traverso'-CNR, Naples, Italy
- IRCCS Neuromed, Pozzilli, Italy
| | - Mario Piratsu
- Institute of Genetic and Biomedical Research, National Research Council of Italy, Cagliari, Italy
| | | | - Markku Laakso
- University of Eastern Finland, Kuopio, Finland
- Kuopio University Hospital, Kuopio, Finland
| | - Markus Loeffler
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Markus Perola
- Finnish Institute for Health and Welfare, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Martin H de Borst
- Division of Nephrology, Department of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Martin Gögele
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
| | - Martina La Bianca
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Mary Ann Lukas
- Target Sciences-Genetics, GlaxoSmithKline, Albuquerque, NM, USA
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Mary L Biggs
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Mary K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Masahiro Kanai
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Japan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Japan
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Masayuki Yasuda
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
- Department of Ophthalmology, Tohoku University Graduate School of Medicine, Miyagi, Japan
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Melanie Waldenberger
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
| | - Miao-Li Chee
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | - Miao-Ling Chee
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Michael H Preuss
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael Stumvoll
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, US National Institutes of Health, Baltimore, MD, USA
| | - Michelle L O'Donoghue
- Cardiovascular Division, Brigham and Women's Hospital, Boston, MA, USA
- TIMI Study Group, Boston, MA, USA
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences (IMS), Yokohama (Kanagawa), Japan
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
- Department of Clinical Physiology, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | | | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Glen Echo, MD, USA
| | - Mikko Kuokkanen
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- The Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- South Texas Diabetes and Obesity Institute and Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Murielle Bochud
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1010, Lausanne, Switzerland
| | - Navya Shilpa Josyula
- Department of Population Health Sciences, Geisinger Health, 100 N. Academy Ave., Danville, PA, USA
| | | | - Nicholas Y Q Tan
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | | | - Nicola Pirastu
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Nicole Schupf
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, USA
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Nina Hutri-Kähönen
- Tampere Centre for Skills Training and Simulation, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Nina Mononen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Nisha Bansal
- Division of Nephrology, University of Washington, Seattle, WA, USA
- Kidney Research Institute, University of Washington, Seattle, WA, USA
| | - Olivier Devuyst
- Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Olle Melander
- Department of Clincial Sciences in Malmö, Lund University, Malmö, Sweden
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Center of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Ozren Polasek
- Faculty of Medicine, University of Split, Split, Croatia
- Algebra University College, Ilica 242, Zagreb, Croatia
| | - Paolo Manunta
- Nephrology and Dialysis Unit, Genomics of Renal Diseases and Hypertension Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paolo Gasparini
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | | | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Paul Elliott
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
- Dementia Research Institute, Imperial College London, London, UK
- Imperial College NIHR Biomedical Research Center, Imperial College London, London, UK
- Health Data Research UK-London, London, UK
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Pavel Hamet
- Montreal University Hospital Research Center, CHUM, Montreal, QC, Canada
- Medpharmgene, Montreal, QC, Canada
| | - Per O Svensson
- Department of Clinical Science and Education, Karolinska Institutet, Södersjukhuset, Stockholm, Sweden
- Department of Cardiology, Södersjukhuset, Stockholm, Sweden
| | - Peter K Joshi
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Peter Kovacs
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
- Integrated Research and Treatment Center Adiposity Diseases, University of Leipzig, Leipzig, Germany
| | - Peter P Pramstaller
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
| | - Peter Rossing
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
| | - Ralene Z H Sim
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | - Ralph Burkhardt
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University of Leipzig, Leipzig, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, Regensburg, Germany
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Reinhold Schmidt
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Rico Rueedi
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Robert J Carroll
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ron T Gansevoort
- Division of Nephrology, Department of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Department of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Sanaz Sedaghat
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Sandra Freitag-Wolf
- Institute of Medical Informatics and Statistics, Kiel University, University Hospital Schleswig-Holstein, Kiel, Germany
| | - Sarah A Pendergrass
- Geisinger Research, Biomedical and Translational Informatics Institute, Danville, PA, USA
| | - Sarah E Graham
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Scott D Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Shih-Jen Hwang
- NHLBI's Framingham Heart Study, Framingham, MA, USA
- The Center for Population Studies, NHLBI, Framingham, MA, USA
| | - Shona M Kerr
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Simona Vaccargiu
- Institute of Genetic and Biomedical Research, National Research Council of Italy, Cagliari, Italy
| | - Snehal B Patil
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, 48109, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Stein Hallan
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Nephrology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Stephan J L Bakker
- Division of Nephrology, Department of Internal Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Su-Chi Lim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Diabetes Center, Khoo Teck Puat Hospital, Singapore, Singapore
| | | | - Suzanne Vogelezang
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Tanguy Corre
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1010, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Tarunveer S Ahluwalia
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- The Bioinformatics Center, Department of Biology, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Thibaud S Boutin
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Thomas Meitinger
- DZHK (German Center for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
- Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, Munich, Germany
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Tobias Bergler
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Ton J Rabelink
- Section of Nephrology, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
- Einthoven Laboratory of Experimental Vascular Research, Leiden University Medical Center, Leiden, The Netherlands
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Toomas Haller
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Unnur Thorsteinsdottir
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
| | - Uwe Völker
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Valencia Hui Xian Foo
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | - Veikko Salomaa
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Vilmantas Giedraitis
- Molecular Geriatrics, Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Vilmundur Gudnason
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Kopavogur, Iceland
| | - Vincent W V Jaddoe
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Wei Huang
- Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center, Shanghai, China
- Shanghai Industrial Technology Institute, Shanghai, China
| | - Weihua Zhang
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UK
| | - Wen Bin Wei
- Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Wieland Kiess
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Department of Women and Child Health, Hospital for Children and Adolescents, University of Leipzig, Leipzig, Germany
- Center for Pediatric Research, University of Leipzig, Leipzig, Germany
| | - Winfried März
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- Synlab Academy, Synlab Holding Deutschland GmbH, Mannheim, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Wolfgang Koenig
- DZHK (German Center for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Wolfgang Lieb
- Institute of Epidemiology and Biobank Popgen, Kiel University, Kiel, Germany
| | - Xin Gao
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Yechiel Friedlander
- School of Public Health and Community Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yih-Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences (IMS), Osaka, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Yuri Milaneschi
- Department of Psychiatry, VU University Medical Centre, Amsterdam, The Netherlands
| | - Zhi Yu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
| | - Klaus J Stark
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Kari Stefansson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
| | - Carsten A Böger
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
- Department of Nephrology and Rheumatology, Kliniken Südostbayern, Traunstein, Germany
| | - Adriana M Hung
- Department of Veteran's Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
- Vanderbilt University Medical Center, Division of Nephrology and Hypertension, Vanderbilt Center for Kidney Disease and Integrated Program for Acute Kidney Injury Research, and Vanderbilt Precision Nephrology Program Nashville, Nashville, TN, USA
| | - Florian Kronenberg
- Department of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Anna Köttgen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Cristian Pattaro
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.
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336
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Genetics in chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference. Kidney Int 2022; 101:1126-1141. [PMID: 35460632 PMCID: PMC9922534 DOI: 10.1016/j.kint.2022.03.019] [Citation(s) in RCA: 89] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 03/16/2022] [Accepted: 03/29/2022] [Indexed: 01/19/2023]
Abstract
Numerous genes for monogenic kidney diseases with classical patterns of inheritance, as well as genes for complex kidney diseases that manifest in combination with environmental factors, have been discovered. Genetic findings are increasingly used to inform clinical management of nephropathies, and have led to improved diagnostics, disease surveillance, choice of therapy, and family counseling. All of these steps rely on accurate interpretation of genetic data, which can be outpaced by current rates of data collection. In March of 2021, Kidney Diseases: Improving Global Outcomes (KDIGO) held a Controversies Conference on "Genetics in Chronic Kidney Disease (CKD)" to review the current state of understanding of monogenic and complex (polygenic) kidney diseases, processes for applying genetic findings in clinical medicine, and use of genomics for defining and stratifying CKD. Given the important contribution of genetic variants to CKD, practitioners with CKD patients are advised to "think genetic," which specifically involves obtaining a family history, collecting detailed information on age of CKD onset, performing clinical examination for extrarenal symptoms, and considering genetic testing. To improve the use of genetics in nephrology, meeting participants advised developing an advanced training or subspecialty track for nephrologists, crafting guidelines for testing and treatment, and educating patients, students, and practitioners. Key areas of future research, including clinical interpretation of genome variation, electronic phenotyping, global representation, kidney-specific molecular data, polygenic scores, translational epidemiology, and open data resources, were also identified.
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337
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Tang L, Li C, Chen W, Zeng Y, Yang H, Hu Y, Song H, Zeng X, Li Q, Fu P. Causal Association between Chronic Kidney Disease and Risk of 19 Site-Specific Cancers: A Mendelian Randomization Study. Cancer Epidemiol Biomarkers Prev 2022; 31:1233-1242. [PMID: 35333923 DOI: 10.1158/1055-9965.epi-21-1318] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 02/16/2022] [Accepted: 03/16/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Results of previous observational studies examining the risk of cancer among patients with chronic kidney disease (CKD) are conflicting. We here explore the causal relationship between estimated glomerular filtration rate (eGFR) and albuminuria, two principal measurements of CKD, and 19 site-specific cancers using Mendelian randomization (MR) analysis. METHODS Single-nucleotide polymorphisms reported to be strongly correlated with eGFR and albuminuria in recent large genome-wide association studies were used as instrumental variables to investigate the causal relationship with cancer using summary-level statistics from several cancer-specific consortia, as well as data of 347,408 participants in the UK Biobank and 260,405 participants in the FinnGen. RESULTS Our data showed that impaired kidney function was associated with higher odds of leukemia [OR = 1.23; 95% confidence interval (CI), 1.06-1.43; P = 0.007], cervical cancer (OR = 1.22; 95% CI, 1.04-1.43; P = 0.017), and female renal cell carcinoma (OR = 1.4; 95% CI, 1.12-1.77; P = 0.004), per 10% decrease in eGFR. The ORs were 1.21 (95% CI, 1.07-1.36; P = 0.002) for colorectal cancer and 0.76 (95% CI, 0.62-0.92; P = 0.006) for non-Hodgkin lymphoma, per doubling odds of albuminuria. In multivariable MR, effect sizes of eGFR-cervical cancer remained strong after adjusting for confounders. CONCLUSIONS The current study indicates that progression of CKD contributes to carcinogenesis of renal cell carcinoma, leukemia, cervical, and colorectal cancer. IMPACT The potential association of kidney function and albuminuria with certain cancers warrants further investigation in order to provide appropriate recommendations regarding cancer screening among patients with CKD.
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Affiliation(s)
- Lei Tang
- Kidney Research Institute, Division of Nephrology, West China Hospital of Sichuan University, Chengdu, Sichiuan, China
| | - Chunyang Li
- West China Biomedical Big Data Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Wenwen Chen
- West China Biomedical Big Data Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Yu Zeng
- West China Biomedical Big Data Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Huazhen Yang
- West China Biomedical Big Data Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Yao Hu
- West China Biomedical Big Data Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Huan Song
- West China Biomedical Big Data Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Xiaoxi Zeng
- Kidney Research Institute, Division of Nephrology, West China Hospital of Sichuan University, Chengdu, Sichiuan, China.,West China Biomedical Big Data Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiu Li
- Department of Medical Oncology, Cancer Center, West China Hospitalof Sichuan University, Chengdu, Sichuan, China
| | - Ping Fu
- Kidney Research Institute, Division of Nephrology, West China Hospital of Sichuan University, Chengdu, Sichiuan, China.,West China Biomedical Big Data Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
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338
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Vujkovic M, Ramdas S, Lorenz KM, Guo X, Darlay R, Cordell HJ, He J, Gindin Y, Chung C, Myers RP, Schneider CV, Park J, Lee KM, Serper M, Carr RM, Kaplan DE, Haas ME, MacLean MT, Witschey WR, Zhu X, Tcheandjieu C, Kember RL, Kranzler HR, Verma A, Giri A, Klarin DM, Sun YV, Huang J, Huffman JE, Creasy KT, Hand NJ, Liu CT, Long MT, Yao J, Budoff M, Tan J, Li X, Lin HJ, Chen YDI, Taylor KD, Chang RK, Krauss RM, Vilarinho S, Brancale J, Nielsen JB, Locke AE, Jones MB, Verweij N, Baras A, Reddy KR, Neuschwander-Tetri BA, Schwimmer JB, Sanyal AJ, Chalasani N, Ryan KA, Mitchell BD, Gill D, Wells AD, Manduchi E, Saiman Y, Mahmud N, Miller DR, Reaven PD, Phillips LS, Muralidhar S, DuVall SL, Lee JS, Assimes TL, Pyarajan S, Cho K, Edwards TL, Damrauer SM, Wilson PW, Gaziano JM, O'Donnell CJ, Khera AV, Grant SFA, Brown CD, Tsao PS, Saleheen D, Lotta LA, Bastarache L, Anstee QM, Daly AK, Meigs JB, Rotter JI, Lynch JA, Rader DJ, Voight BF, Chang KM. A multiancestry genome-wide association study of unexplained chronic ALT elevation as a proxy for nonalcoholic fatty liver disease with histological and radiological validation. Nat Genet 2022; 54:761-771. [PMID: 35654975 PMCID: PMC10024253 DOI: 10.1038/s41588-022-01078-z] [Citation(s) in RCA: 120] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 04/18/2022] [Indexed: 02/05/2023]
Abstract
Nonalcoholic fatty liver disease (NAFLD) is a growing cause of chronic liver disease. Using a proxy NAFLD definition of chronic elevation of alanine aminotransferase (cALT) levels without other liver diseases, we performed a multiancestry genome-wide association study (GWAS) in the Million Veteran Program (MVP) including 90,408 cALT cases and 128,187 controls. Seventy-seven loci exceeded genome-wide significance, including 25 without prior NAFLD or alanine aminotransferase associations, with one additional locus identified in European American-only and two in African American-only analyses (P < 5 × 10-8). External replication in histology-defined NAFLD cohorts (7,397 cases and 56,785 controls) or radiologic imaging cohorts (n = 44,289) replicated 17 single-nucleotide polymorphisms (SNPs) (P < 6.5 × 10-4), of which 9 were new (TRIB1, PPARG, MTTP, SERPINA1, FTO, IL1RN, COBLL1, APOH and IFI30). Pleiotropy analysis showed that 61 of 77 multiancestry and all 17 replicated SNPs were jointly associated with metabolic and/or inflammatory traits, revealing a complex model of genetic architecture. Our approach integrating cALT, histology and imaging reveals new insights into genetic liability to NAFLD.
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Affiliation(s)
- Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Shweta Ramdas
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kim M Lorenz
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Rebecca Darlay
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Heather J Cordell
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Jing He
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | - Robert P Myers
- Gilead Sciences, Inc., Foster City, CA, USA
- The Liver Company, Palo Alto, CA, USA
| | - Carolin V Schneider
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Joseph Park
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kyung Min Lee
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Marina Serper
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Rotonya M Carr
- Division of Gastroenterology, University of Washington, Seattle, WA, USA
| | - David E Kaplan
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Mary E Haas
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matthew T MacLean
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Walter R Witschey
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Xiang Zhu
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Statistics, The Pennsylvania State University, University Park, PA, USA
- Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Catherine Tcheandjieu
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Rachel L Kember
- Mental Illness Research Education and Clinical Center, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Henry R Kranzler
- Mental Illness Research Education and Clinical Center, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Anurag Verma
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ayush Giri
- Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Derek M Klarin
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Division of Vascular Surgery, Stanford University School of Medicine, Palo Alto, CA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yan V Sun
- Atlanta VA Medical Center, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Jie Huang
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | | | - Kate Townsend Creasy
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Nicholas J Hand
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Michelle T Long
- Department of Medicine, Section of Gastroenterology, Boston University School of Medicine, Boston, MA, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Matthew Budoff
- Department of Cardiology, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Xiaohui Li
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Henry J Lin
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Ruey-Kang Chang
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Ronald M Krauss
- Departments of Pediatrics and Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Silvia Vilarinho
- Section of Digestive Diseases, Department of Internal Medicine, and Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Joseph Brancale
- Section of Digestive Diseases, Department of Internal Medicine, and Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | | | | | | | | | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - K Rajender Reddy
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | - Jeffrey B Schwimmer
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Arun J Sanyal
- Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Naga Chalasani
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kathleen A Ryan
- Program for Personalized and Genomic Medicine, Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Braxton D Mitchell
- Program for Personalized and Genomic Medicine, Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Andrew D Wells
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pathology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Elisabetta Manduchi
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yedidya Saiman
- Department of Medicine, Section of Hepatology, Lewis Katz School of Medicine at Temple University, Temple University Hospital, Philadelphia, PA, USA
| | - Nadim Mahmud
- Department of Medicine, Division of Gastroenterology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Donald R Miller
- Center for Healthcare Organization and Implementation Research, Bedford VA Healthcare System, Bedford, MA, USA
- Center for Population Health, Department of Biomedical and Nutritional Sciences, University of Massachusetts, Lowell, MA, USA
| | - Peter D Reaven
- Phoenix VA Health Care System, Phoenix, AZ, USA
- College of Medicine, University of Arizona, Phoenix, AZ, USA
| | - Lawrence S Phillips
- Atlanta VA Medical Center, Decatur, GA, USA
- Division of Endocrinology, Emory University School of Medicine, Atlanta, GA, USA
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Scott L DuVall
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Jennifer S Lee
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Themistocles L Assimes
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Saiju Pyarajan
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kelly Cho
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Todd L Edwards
- Nashville VA Medical Center, Nashville, TN, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Scott M Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Peter W Wilson
- Atlanta VA Medical Center, Decatur, GA, USA
- Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA
| | - J Michael Gaziano
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
| | - Christopher J O'Donnell
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Amit V Khera
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Struan F A Grant
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Christopher D Brown
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Danish Saleheen
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
| | | | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Quentin M Anstee
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
- Newcastle NIHR Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Ann K Daly
- Newcastle NIHR Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - James B Meigs
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Julie A Lynch
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
- College of Nursing and Health Sciences, University of Massachusetts, Lowell, MA, USA
| | - Daniel J Rader
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Benjamin F Voight
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
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339
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Millischer V, Matheson GJ, Bergen SE, Coombes BJ, Ponzer K, Wikström F, Jagiello K, Lundberg M, Stenvinkel P, Biernacka JM, Breuer O, Martinsson L, Landén M, Backlund L, Lavebratt C, Schalling M. Improving lithium dose prediction using population pharmacokinetics and pharmacogenomics: a cohort genome-wide association study in Sweden. Lancet Psychiatry 2022; 9:447-457. [PMID: 35569502 DOI: 10.1016/s2215-0366(22)00100-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 02/25/2022] [Accepted: 03/09/2022] [Indexed: 01/05/2023]
Abstract
BACKGROUND Lithium is the most effective treatment for bipolar disorder, resulting in strong suicide prevention effects. The therapeutic range of lithium, however, is narrow and treatment initiation requires individual titration to address inter-individual variability. We aimed to improve lithium dose prediction using clinical and genomic data. METHODS We performed a population pharmacokinetic study followed by a genome-wide association study (GWAS), including two clinical Swedish cohorts. Participants in cohort 1 were from specialised outpatient clinics at Huddinge Hospital, in Stockholm, Sweden, and participants in cohort 2 were identified using the Swedish National Quality Registry for Bipolar disorder (BipoläR). Patients who received a lithium dose corresponding to at least one tablet of lithium sulphate (6 mmol) per day and had clinically relevant plasma concentrations of lithium were included in the study. Data on age, sex, bodyweight, height, creatinine concentration, estimated glomerular filtration rate (eGFR), lithium preparation, number of tablets of lithium per day, serum lithium concentration, and medications affecting kidney function (C09 antihypertensives, C03 [except C03D] sodium-retaining diuretics, and non-steroidal anti-inflammatory drugs) were obtained retrospectively for several timepoints when possible from electronic health records, BipoläR, and the Swedish prescription registry. The median time between timepoints was 1·07 years for cohort 1 and 1·09 years for cohort 2. The primary outcome of interest was the natural logarithm of total body clearance for lithium (CLLi) associated with the clinical variables. The residual effects after accounting for age and sex, representing the individual-level effects (CLLi,age/sex), were used as the dependent variable in a GWAS. FINDINGS 2357 patients who were administered lithium (1423 women [60·4%] and 934 men [39·6%]; mean age 53·6 years [range 17-89], mainly of European descent) were included and 5627 data points were obtained. Age (variance explained [R2]: R2cohort1=0·41 and R2cohort2=0·31; both p<0·0001), sex (R2cohort1=0·0063 [p=0·045] and R2cohort2=0·026 [p<0·0001]), eGFR (R2cohort1=0·38 and R2cohort2=0·20; both p<0·0001), comedication with diuretics (R2cohort1=0·0058 [p=0·014] and R2cohort2=0·0026 [p<0·0001]), and agents acting on the renin-aldosterone-angiotensin system (R2cohort1=0·028 and R2cohort2=0·015; both p<0·0001) were clinical predictors of CLLi. Notably, an association between CLLi and serum lithium was observed, with a lower CLLi being associated with higher serum lithium (R2cohort1=0·13 and R2cohort2=0·15; both p<0·0001). In a GWAS of CLLi,age/sex, one locus was associated with a change in CLLi (rs583503; β=-0·053 [95% CI -0·071 to -0·034]; p<0·00000005). We also found enrichment of the associations with genes expressed in the medulla (p=0·0014, corrected FDR=0·04) and cortex of the kidney (p=0·0015, corrected FDR=0·04), as well as associations with polygenic risk scores for eGFR (p value threshold: 0·05, p=0·01), body-mass index (p value threshold: 0·05, p=0·00025), and blood urea nitrogen (p value threshold: 0·001, p=0·00043). The model based on six clinical predictors explained 61·4% of the variance in CLLi in cohort 1 and 49·8% in cohort 2. Adding genetic markers did not lead to major improvement of the models: within the subsample of genotyped individuals, the variance explained only increased from 59·32% to 59·36% in cohort 1 and from 49·21% to 50·03% in cohort 2 when including rs583503 and the four first principal components. INTERPRETATION Our model predictors could be used clinically to better guide lithium dosage, shortening the time to reach therapeutic concentrations, thus improving care. Identification of the first genomic locus and PRS to be associated with CLLi introduces the opportunity of individualised medicine in lithium treatment. FUNDING Stanley Medical Research Institute, Swedish Research Council, Swedish Foundation for Strategic Research, Swedish Brain Foundation, Swedish Research Council, Söderström-Königska Foundation, Bror Gadelius Minnesfond, Swedish Mental Health Fund, Karolinska Institutet and Hospital.
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Affiliation(s)
- Vincent Millischer
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden; Centre for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
| | - Granville J Matheson
- Department of Psychiatry, Columbia University, NY, USA; Department of Biostatistics, Columbia University Mailman School of Public Health, NY, USA; Centre for Psychiatric Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Healthcare Services, Stockholm, Sweden
| | - Sarah E Bergen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Brandon J Coombes
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Katja Ponzer
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden; Psychiatry Southwest, Stockholm Healthcare Services, Stockholm, Sweden
| | - Fredrik Wikström
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden; Psychiatry Southwest, Stockholm Healthcare Services, Stockholm, Sweden
| | - Karolina Jagiello
- Psychiatry Southwest, Stockholm Healthcare Services, Stockholm, Sweden
| | - Martin Lundberg
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden; Centre for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Peter Stenvinkel
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Joanna M Biernacka
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA; Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Olof Breuer
- Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Lina Martinsson
- Psychiatry Southwest, Stockholm Healthcare Services, Stockholm, Sweden; Centre for Psychiatric Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Healthcare Services, Stockholm, Sweden
| | - Mikael Landén
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Gothenburg University, Gothenburg, Sweden
| | - Lena Backlund
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden; Centre for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Centre for Psychiatric Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Healthcare Services, Stockholm, Sweden
| | - Catharina Lavebratt
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden; Centre for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Martin Schalling
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden; Centre for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden
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340
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Engel C, Wirkner K, Zeynalova S, Baber R, Binder H, Ceglarek U, Enzenbach C, Fuchs M, Hagendorff A, Henger S, Hinz A, Rauscher FG, Reusche M, Riedel-Heller SG, Röhr S, Sacher J, Sander C, Schroeter ML, Tarnok A, Treudler R, Villringer A, Wachter R, Witte AV, Thiery J, Scholz M, Loeffler M. Cohort Profile: The LIFE-Adult-Study. Int J Epidemiol 2022; 52:e66-e79. [PMID: 35640047 PMCID: PMC9908058 DOI: 10.1093/ije/dyac114] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 05/10/2022] [Indexed: 01/14/2023] Open
Affiliation(s)
- Christoph Engel
- Corresponding author. Institute for Medical Informatics, Statistics and Epidemiology, Leipzig University, Haertelstrasse 16–18, 04107 Leipzig, Germany. E-mail:
| | | | | | - Ronny Baber
- Leipzig Research Centre for Civilization Diseases, Leipzig University, Leipzig, Germany,Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University of Leipzig Medical Center, Leipzig, Germany
| | - Hans Binder
- Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany
| | - Uta Ceglarek
- Leipzig Research Centre for Civilization Diseases, Leipzig University, Leipzig, Germany,Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University of Leipzig Medical Center, Leipzig, Germany
| | - Cornelia Enzenbach
- Institute for Medical Informatics, Statistics and Epidemiology, Leipzig University, Leipzig, Germany,Leipzig Research Centre for Civilization Diseases, Leipzig University, Leipzig, Germany
| | - Michael Fuchs
- Leipzig Research Centre for Civilization Diseases, Leipzig University, Leipzig, Germany,Division Otolaryngology, Head and Neck Surgery, Phoniatrics and Audiology, University of Leipzig Medical Center, Leipzig, Germany
| | - Andreas Hagendorff
- Department of Cardiology, University of Leipzig Medical Center, Leipzig, Germany
| | - Sylvia Henger
- Institute for Medical Informatics, Statistics and Epidemiology, Leipzig University, Leipzig, Germany,Leipzig Research Centre for Civilization Diseases, Leipzig University, Leipzig, Germany
| | - Andreas Hinz
- Department of Medical Psychology and Medical Sociology, Leipzig University, Leipzig, Germany
| | - Franziska G Rauscher
- Institute for Medical Informatics, Statistics and Epidemiology, Leipzig University, Leipzig, Germany,Leipzig Research Centre for Civilization Diseases, Leipzig University, Leipzig, Germany
| | - Matthias Reusche
- Institute for Medical Informatics, Statistics and Epidemiology, Leipzig University, Leipzig, Germany,Leipzig Research Centre for Civilization Diseases, Leipzig University, Leipzig, Germany
| | - Steffi G Riedel-Heller
- Institute of Social Medicine, Occupational Medicine and Public Health (ISAP), Leipzig University, Leipzig, Germany
| | - Susanne Röhr
- Institute of Social Medicine, Occupational Medicine and Public Health (ISAP), Leipzig University, Leipzig, Germany,Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
| | - Julia Sacher
- Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany,Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Christian Sander
- Leipzig Research Centre for Civilization Diseases, Leipzig University, Leipzig, Germany,Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany
| | - Matthias L Schroeter
- Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany,Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Attila Tarnok
- Institute for Medical Informatics, Statistics and Epidemiology, Leipzig University, Leipzig, Germany,Department of Preclinical Development and Validation, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany
| | - Regina Treudler
- Department of Dermatology, Venerology and Allergology, University of Leipzig Medical Center, Leipzig, Germany,Leipzig Interdisciplinary Allergy Center (LICA)—Comprehensive Allergy Center, University of Leipzig Medical Center, Leipzig, Germany
| | - Arno Villringer
- Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany,Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Rolf Wachter
- Clinic and Policlinic for Cardiology, University of Leipzig Medical Center, Leipzig, Germany
| | - A Veronica Witte
- Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany,Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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341
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Li Y, Cheng Y, Consolato F, Schiano G, Chong MR, Pietzner M, Nguyen NQH, Scherer N, Biggs ML, Kleber ME, Haug S, Göçmen B, Pigeyre M, Sekula P, Steinbrenner I, Schlosser P, Joseph CB, Brody JA, Grams ME, Hayward C, Schultheiss UT, Krämer BK, Kronenberg F, Peters A, Seissler J, Steubl D, Then C, Wuttke M, März W, Eckardt KU, Gieger C, Boerwinkle E, Psaty BM, Coresh J, Oefner PJ, Pare G, Langenberg C, Scherberich JE, Yu B, Akilesh S, Devuyst O, Rampoldi L, Köttgen A. Genome-wide studies reveal factors associated with circulating uromodulin and its relationships to complex diseases. JCI Insight 2022; 7:e157035. [PMID: 35446786 PMCID: PMC9220927 DOI: 10.1172/jci.insight.157035] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 04/07/2022] [Indexed: 11/28/2022] Open
Abstract
Uromodulin (UMOD) is a major risk gene for monogenic and complex forms of kidney disease. The encoded kidney-specific protein uromodulin is highly abundant in urine and related to chronic kidney disease, hypertension, and pathogen defense. To gain insights into potential systemic roles, we performed genome-wide screens of circulating uromodulin using complementary antibody-based and aptamer-based assays. We detected 3 and 10 distinct significant loci, respectively. Integration of antibody-based results at the UMOD locus with functional genomics data (RNA-Seq, ATAC-Seq, Hi-C) of primary human kidney tissue highlighted an upstream variant with differential accessibility and transcription in uromodulin-synthesizing kidney cells as underlying the observed cis effect. Shared association patterns with complex traits, including chronic kidney disease and blood pressure, placed the PRKAG2 locus in the same pathway as UMOD. Experimental validation of the third antibody-based locus, B4GALNT2, showed that the p.Cys466Arg variant of the encoded N-acetylgalactosaminyltransferase had a loss-of-function effect leading to higher serum uromodulin levels. Aptamer-based results pointed to enzymes writing glycan marks present on uromodulin and to their receptors in the circulation, suggesting that this assay permits investigating uromodulin's complex glycosylation rather than its quantitative levels. Overall, our study provides insights into circulating uromodulin and its emerging functions.
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Affiliation(s)
- Yong Li
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
| | - Yurong Cheng
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
- Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Francesco Consolato
- Molecular Genetics of Renal Disorders group, Division of Genetics and Cell Biology, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Michael R. Chong
- Population Health Research Institute and Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences, Hamilton, Ontario, Canada
- Department of Biochemistry and Biomedical Sciences and
- Department of Pathology and Molecular Medicine, Faculty of Health Science, McMaster University, Hamilton, Ontario, Canada
| | - Maik Pietzner
- Medical Research Council (MRC) Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
- Computational Medicine, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Ngoc Quynh H. Nguyen
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Nora Scherer
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
- Spemann Graduate School of Biology and Medicine, University of Freiburg, Freiburg, Germany
| | - Mary L. Biggs
- Cardiovascular Health Research Unit, Department of Medicine, and
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Marcus E. Kleber
- SYNLAB MVZ Humangenetik Mannheim GmbH, Mannheim, Germany
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stefan Haug
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
| | - Burulça Göçmen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
| | - Marie Pigeyre
- Population Health Research Institute and Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences, Hamilton, Ontario, Canada
- Department of Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Christina B. Joseph
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | | | - Morgan E. Grams
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Division of Nephrology, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Ulla T. Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
- Department of Medicine IV: Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Bernhard K. Krämer
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-Universität (LMU), Munich, Germany
| | - Jochen Seissler
- Medical Clinic and Policlinic IV, Hospital of the University of Munich, LMU Munich, Munich, Germany
| | - Dominik Steubl
- Division of Nephrology, Tufts Medical Center, Boston, Massachusetts, USA
- Department of Nephrology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
- Boehringer Ingelheim International GmbH, Ingelheim, Germany
| | - Cornelia Then
- Medical Clinic and Policlinic IV, Hospital of the University of Munich, LMU Munich, Munich, Germany
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
- Department of Medicine IV: Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
- SYNLAB Academy, SYNLAB Holding Deutschland GmbH, Augsburg and Mannheim, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Partner Munich, Neuherberg, Germany
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, and
- Department of Epidemiology and
- Department of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, Washington, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Peter J. Oefner
- Institute of Functional Genomics, University of Regensburg, Regensburg, Germany
| | - Guillaume Pare
- Population Health Research Institute and Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Faculty of Health Science, McMaster University, Hamilton, Ontario, Canada
| | - Claudia Langenberg
- Medical Research Council (MRC) Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
- Computational Medicine, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | | | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Shreeram Akilesh
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
| | - Olivier Devuyst
- Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Luca Rampoldi
- Molecular Genetics of Renal Disorders group, Division of Genetics and Cell Biology, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, and
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Centre for Integrative Biological Signalling Studies (CIBSS), University of Freiburg, Freiburg, Germany
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342
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Pham KO, Hara A, Tsujiguchi H, Suzuki K, Suzuki F, Miyagi S, Kannon T, Sato T, Hosomichi K, Tsuboi H, Nguyen TTT, Shimizu Y, Kambayashi Y, Nakamura M, Takazawa C, Nakamura H, Hamagishi T, Shibata A, Konoshita T, Tajima A, Nakamura H. Association between Vitamin Intake and Chronic Kidney Disease According to a Variant Located Upstream of the PTGS1 Gene: A Cross-Sectional Analysis of Shika Study. Nutrients 2022; 14:2082. [PMID: 35631221 PMCID: PMC9143472 DOI: 10.3390/nu14102082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 05/02/2022] [Accepted: 05/14/2022] [Indexed: 11/22/2022] Open
Abstract
Chronic kidney disease (CKD) patients have been advised to take vitamins; however, the effects have been controversial. The individual differences in developing CKD might involve genetic variants of inflammation, including variant rs883484 located upstream of the prostaglandin-endoperoxide synthase 1 (PTGS1) gene. We aimed to identify whether the 12 dietary vitamin intake interacts with genotypes of the rs883484 on developing CKD. The population-based, cross-sectional study had 684 Japanese participants (≥40 years old). The study used a validated, brief, self-administered diet history questionnaire to estimate the intake of the dietary vitamins. CKD was defined as estimated glomerular filtration < 60 mL/min/1.73 m2. The study participants had an average age of 62.1 ± 10.8 years with 15.4% minor homozygotes of rs883484, and 114 subjects had CKD. In the fully adjusted model, the higher intake of vitamins, namely niacin (odds ratio (OR) = 0.74, 95% confidence interval (CI): 0.57−0.96, p = 0.024), α-tocopherol (OR = 0.49, 95% CI: 0.26−0.95, p = 0.034), and vitamin C (OR = 0.97, 95% CI: 0.95−1.00, p = 0.037), was independently associated with lower CKD tendency in the minor homozygotes of rs883484. The results suggested the importance of dietary vitamin intake in the prevention of CKD in middle-aged to older-aged Japanese with minor homozygous of rs883484 gene variant.
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Affiliation(s)
- Kim-Oanh Pham
- Information Management Department, Asia Center for Air Pollution Research, Niigata City 950-2144, Japan
- Department of Hygiene and Public Health, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (A.H.); (H.T.); (K.S.); (F.S.); (M.N.); (C.T.); (H.N.); (T.H.); (A.S.); (H.N.)
| | - Akinori Hara
- Department of Hygiene and Public Health, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (A.H.); (H.T.); (K.S.); (F.S.); (M.N.); (C.T.); (H.N.); (T.H.); (A.S.); (H.N.)
| | - Hiromasa Tsujiguchi
- Department of Hygiene and Public Health, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (A.H.); (H.T.); (K.S.); (F.S.); (M.N.); (C.T.); (H.N.); (T.H.); (A.S.); (H.N.)
| | - Keita Suzuki
- Department of Hygiene and Public Health, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (A.H.); (H.T.); (K.S.); (F.S.); (M.N.); (C.T.); (H.N.); (T.H.); (A.S.); (H.N.)
| | - Fumihiko Suzuki
- Department of Hygiene and Public Health, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (A.H.); (H.T.); (K.S.); (F.S.); (M.N.); (C.T.); (H.N.); (T.H.); (A.S.); (H.N.)
- Community Medicine Support Dentistry, Faculty of Dentist, Ohu University Hospital, Koriyama 963-8611, Japan
| | - Sakae Miyagi
- Innovative Clinical Research Center, Takaramachi Campus, Kanazawa University, Kanazawa City 920-8640, Japan;
| | - Takayuki Kannon
- Department of Bioinformatics and Genomics, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (T.K.); (T.S.); (K.H.); (A.T.)
| | - Takehiro Sato
- Department of Bioinformatics and Genomics, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (T.K.); (T.S.); (K.H.); (A.T.)
| | - Kazuyoshi Hosomichi
- Department of Bioinformatics and Genomics, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (T.K.); (T.S.); (K.H.); (A.T.)
| | - Hirohito Tsuboi
- Institute of Medical, Pharmaceutical and Health Sciences, Kakuma Campus, Kanazawa University, Kanazawa City 920-1192, Japan;
| | - Thao Thi Thu Nguyen
- Department of Epidemiology, Faculty of Public Health, Haiphong University of Medicine and Pharmacy, Hai Phong 180000, Vietnam;
| | - Yukari Shimizu
- Department of Nursing, Faculty of Health Sciences, Komatsu University, Komatsu City 923-0961, Japan;
| | - Yasuhiro Kambayashi
- Department of Public Health, Faculty of Veterinary Medicine, Okayama University of Science, Imabari 794-8555, Japan;
| | - Masaharu Nakamura
- Department of Hygiene and Public Health, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (A.H.); (H.T.); (K.S.); (F.S.); (M.N.); (C.T.); (H.N.); (T.H.); (A.S.); (H.N.)
| | - Chie Takazawa
- Department of Hygiene and Public Health, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (A.H.); (H.T.); (K.S.); (F.S.); (M.N.); (C.T.); (H.N.); (T.H.); (A.S.); (H.N.)
| | - Haruki Nakamura
- Department of Hygiene and Public Health, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (A.H.); (H.T.); (K.S.); (F.S.); (M.N.); (C.T.); (H.N.); (T.H.); (A.S.); (H.N.)
| | - Toshio Hamagishi
- Department of Hygiene and Public Health, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (A.H.); (H.T.); (K.S.); (F.S.); (M.N.); (C.T.); (H.N.); (T.H.); (A.S.); (H.N.)
| | - Aki Shibata
- Department of Hygiene and Public Health, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (A.H.); (H.T.); (K.S.); (F.S.); (M.N.); (C.T.); (H.N.); (T.H.); (A.S.); (H.N.)
| | - Tadashi Konoshita
- Third Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Tsuruga 914-0055, Japan;
| | - Atsushi Tajima
- Department of Bioinformatics and Genomics, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (T.K.); (T.S.); (K.H.); (A.T.)
| | - Hiroyuki Nakamura
- Department of Hygiene and Public Health, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa City 920-8640, Japan; (A.H.); (H.T.); (K.S.); (F.S.); (M.N.); (C.T.); (H.N.); (T.H.); (A.S.); (H.N.)
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Keshawarz A, Hwang SJ, Lee GY, Yu Z, Yao C, Köttgen A, Levy D. Cardiovascular disease protein biomarkers are associated with kidney function: The Framingham Heart Study. PLoS One 2022; 17:e0268293. [PMID: 35544531 PMCID: PMC9094507 DOI: 10.1371/journal.pone.0268293] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 04/27/2022] [Indexed: 11/18/2022] Open
Abstract
Background Biomarkers common to chronic kidney disease (CKD) and cardiovascular disease (CVD) may reflect early impairments underlying both diseases. Methods We evaluated associations of 71 CVD-related plasma proteins measured in 2,873 Framingham Heart Study (FHS) Offspring cohort participants with cross-sectional continuous eGFR and with longitudinal change in eGFR from baseline to follow-up (ΔeGFR). We also evaluated the associations of the 71 CVD proteins with the following dichotomous secondary outcomes: prevalent CKD stage ≥3 (cross-sectional), new-onset CKD stage ≥3 (longitudinal), and rapid decline in eGFR (longitudinal). Proteins significantly associated with eGFR and ΔeGFR were subsequently validated in 3,951 FHS Third Generation cohort participants and were tested using Mendelian randomization (MR) analysis to infer putatively causal relations between plasma protein biomarkers and kidney function. Results In cross-sectional analysis, 37 protein biomarkers were significantly associated with eGFR at FDR<0.05 in the FHS Offspring cohort and 20 of these validated in the FHS Third Generation cohort at p<0.05/37. In longitudinal analysis, 27 protein biomarkers were significantly associated with ΔeGFR at FDR<0.05 and 12 of these were validated in the FHS Third Generation cohort at p<0.05/27. Additionally, 35 protein biomarkers were significantly associated with prevalent CKD, five were significantly associated with new-onset CKD, and 17 were significantly associated with rapid decline in eGFR. MR suggested putatively causal relations of melanoma cell adhesion molecule (MCAM; -0.011±0.003 mL/min/1.73m2, p = 5.11E-5) and epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1; -0.006±0.002 mL/min/1.73m2, p = 0.0001) concentration with eGFR. Discussion/conclusions Eight protein biomarkers were consistently associated with eGFR in cross-sectional and longitudinal analysis in both cohorts and may capture early kidney impairment; others were implicated in association and causal inference analyses. A subset of CVD protein biomarkers may contribute causally to the pathogenesis of kidney impairment and should be studied as targets for CKD treatment and early prevention.
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Affiliation(s)
- Amena Keshawarz
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America
- Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Shih-Jen Hwang
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America
- Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Gha Young Lee
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America
- Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Zhi Yu
- Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Chen Yao
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America
- Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Anna Köttgen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Daniel Levy
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America
- Framingham Heart Study, Framingham, Massachusetts, United States of America
- * E-mail:
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Adebamowo CA, Adeyemo A, Ashaye A, Akpa OM, Chikowore T, Choudhury A, Fakim YJ, Fatumo S, Hanchard N, Hauser M, Mitchell B, Mulder N, Ofori-Acquah SF, Owolabi M, Ramsay M, Tayo B, VasanthKumar AB, Zhang Y, Adebamowo SN. Polygenic risk scores for CARDINAL study. Nat Genet 2022; 54:527-530. [PMID: 35513726 PMCID: PMC9907721 DOI: 10.1038/s41588-022-01074-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The Cardiometabolic Disorders in African-Ancestry Populations (CARDINAL) study site is a well-powered, first-of-its-kind resource for developing, refining and validating methods for research into polygenic risk scores that accounts for local ancestry, to improve risk prediction in diverse populations.
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Affiliation(s)
- Clement A Adebamowo
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
- University of Maryland Marlene and Stewart Greenbaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - Adeyinka Ashaye
- Department of Ophthalmology, University of Ibadan, Ibadan, Nigeria
| | - Onoja M Akpa
- Department of Epidemiology and Medical Statistics, University of Ibadan, Ibadan, Nigeria
| | - Tinashe Chikowore
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Ananyo Choudhury
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Yasmina J Fakim
- Department of Biotechnology, University of Mauritius, Reduit, MU, Mauritius
| | - Segun Fatumo
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM (Uganda Research Unit), Entebbe, Uganda
- London School of Hygiene and Tropical Medicine, London, UK
| | - Neil Hanchard
- National Human Genome Research Institute, Rockville, MD, USA
| | - Michael Hauser
- Department of Medicine, Duke University, Durham, NC, USA
| | - Braxton Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Nicola Mulder
- Computational Biology Division, IDM, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Solomon F Ofori-Acquah
- West African Genetic Medicine Centre (WAGMC), University of Ghana, Accra, Ghana
- Center for Translational and International Hematology, Vascular Medicine Institute, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mayowa Owolabi
- Department of Medicine and Center for Genomic and Precision Medicine, University of Ibadan, Ibadan, Nigeria
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Bamidele Tayo
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, USA
| | | | - Yuji Zhang
- University of Maryland Marlene and Stewart Greenbaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Sally N Adebamowo
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA.
- University of Maryland Marlene and Stewart Greenbaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA.
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Yang F, Lu Y, Chen S, Wang K, Hu T, Cui H. Sex-specific effect of serum urate levels on coronary heart disease and myocardial infarction prevention: A Mendelian randomization study. Nutr Metab Cardiovasc Dis 2022; 32:1266-1274. [PMID: 35197211 DOI: 10.1016/j.numecd.2022.01.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 01/12/2022] [Accepted: 01/14/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND AND AIMS Observational studies have examined serum urate levels in relation to coronary heart disease (CHD) and myocardial infarction (MI). Whether these associations are causal remains controversial, due to confounding factors and reverse causality. We aim to investigate the causality of these associations using Mendelian randomization method. METHODS AND RESULTS Instrumental variables were obtained from the largest genome-wide association studies of serum urate (457,690 individuals) to date. Summary statistics were from CARDIoGRAMplusC4D consortium (60,801 CHD cases; 43,676 MI cases), FinnGen (21,012 CHD cases; 12,801 MI cases), UK Biobank (10,157 CHD cases; 7018 MI cases), and Biobank Japan (29,319 CHD cases). Inverse-variance weighted method was applied as the main results. Other statistical methods and reverse MR analysis were conducted in the supplementary analyses. Elevated genetically determined serum urate levels were associated with increased risks of CHD and MI. The association pattern remained for the datasets in FinnGen, the combined results of three independent data sources (CHD: odds ratio (OR), 1.10; 95%CI, 1.06-1.15; p = 4.2 × 10-6; MI: OR, 1.12; 95%CI, 1.07-1.18; p = 2.7 × 10-6), and East Asian population. Interestingly, sex-specific subgroup analyses revealed that these associations kept in men only, but not among women in individuals of European ancestry. No consistent evidence was found for the causal effect of CHD or MI on serum urate levels. CONCLUSION We provide consistent evidence for the causal effect of genetically predicted serum urate levels on CHD and MI, but not the reverse effect. Urate-lowering therapy may be of cardiovascular benefit in the prevention of CHD and MI, especially for men.
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Affiliation(s)
- Fangkun Yang
- Department of Cardiology, Ningbo Hospital of Zhejiang University (Ningbo First Hospital), School of Medicine, Zhejiang University, Ningbo, Zhejiang, China
| | - Yunlong Lu
- Department of Cardiology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Songzan Chen
- School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Kai Wang
- Eye Center of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Teng Hu
- School of Medicine, Ningbo University, Ningbo, China
| | - Hanbin Cui
- Cardiology Center, Ningbo First Hospital, Ningbo University, Ningbo, Zhejiang, China.
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Suzuki M, Tomita M. Genetic Variations of Vitamin A-Absorption and Storage-Related Genes, and Their Potential Contribution to Vitamin A Deficiency Risks Among Different Ethnic Groups. Front Nutr 2022; 9:861619. [PMID: 35571879 PMCID: PMC9096837 DOI: 10.3389/fnut.2022.861619] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 03/23/2022] [Indexed: 12/01/2022] Open
Abstract
Vitamin A, an essential fat-soluble micronutrient, plays a critical role in the body, by regulating vision, immune responses, and normal development, for instance. Vitamin A deficiency (VAD) is a major cause of xerophthalmia and increases the risk of death from infectious diseases. It is also emerging that prenatal exposure to VAD is associated with disease risks later in life. The overall prevalence of VAD has significantly declined over recent decades; however, the rate of VAD is still high in many low- and mid-income countries and even in high-income countries among specific ethnic/race groups. While VAD occurs when dietary intake is insufficient to meet demands, establishing a strong association between food insecurity and VAD, and vitamin A supplementation is the primary solution to treat VAD, genetic contributions have also been reported to effect serum vitamin A levels. In this review, we discuss genetic variations associated with vitamin A status and vitamin A bioactivity-associated genes, specifically those linked to uptake of the vitamin in the small intestine and its storage in the liver, as well as their potential contribution to vitamin A deficiency risks among different ethnic groups.
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Affiliation(s)
- Masako Suzuki
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, United States
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Henry A, Gordillo-Marañón M, Finan C, Schmidt AF, Ferreira JP, Karra R, Sundström J, Lind L, Ärnlöv J, Zannad F, Mälarstig A, Hingorani AD, Lumbers RT, HERMES and SCALLOP Consortia. Therapeutic Targets for Heart Failure Identified Using Proteomics and Mendelian Randomization. Circulation 2022; 145:1205-1217. [PMID: 35300523 PMCID: PMC9010023 DOI: 10.1161/circulationaha.121.056663] [Citation(s) in RCA: 91] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Accepted: 02/09/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Heart failure (HF) is a highly prevalent disorder for which disease mechanisms are incompletely understood. The discovery of disease-associated proteins with causal genetic evidence provides an opportunity to identify new therapeutic targets. METHODS We investigated the observational and causal associations of 90 cardiovascular proteins, which were measured using affinity-based proteomic assays. First, we estimated the associations of 90 cardiovascular proteins with incident heart failure by means of a fixed-effect meta-analysis of 4 population-based studies, composed of a total of 3019 participants with 732 HF events. The causal effects of HF-associated proteins were then investigated by Mendelian randomization, using cis-protein quantitative loci genetic instruments identified from genomewide association studies in more than 30 000 individuals. To improve the precision of causal estimates, we implemented an Mendelian randomization model that accounted for linkage disequilibrium between instruments and tested the robustness of causal estimates through a multiverse sensitivity analysis that included up to 120 combinations of instrument selection parameters and Mendelian randomization models per protein. The druggability of candidate proteins was surveyed, and mechanism of action and potential on-target side effects were explored with cross-trait Mendelian randomization analysis. RESULTS Forty-four of ninety proteins were positively associated with risk of incident HF (P<6.0×10-4). Among these, 8 proteins had evidence of a causal association with HF that was robust to multiverse sensitivity analysis: higher CSF-1 (macrophage colony-stimulating factor 1), Gal-3 (galectin-3) and KIM-1 (kidney injury molecule 1) were positively associated with risk of HF, whereas higher ADM (adrenomedullin), CHI3L1 (chitinase-3-like protein 1), CTSL1 (cathepsin L1), FGF-23 (fibroblast growth factor 23), and MMP-12 (matrix metalloproteinase-12) were protective. Therapeutics targeting ADM and Gal-3 are currently under evaluation in clinical trials, and all the remaining proteins were considered druggable, except KIM-1. CONCLUSIONS We identified 44 circulating proteins that were associated with incident HF, of which 8 showed evidence of a causal relationship and 7 were druggable, including adrenomedullin, which represents a particularly promising drug target. Our approach demonstrates a tractable roadmap for the triangulation of population genomic and proteomic data for the prioritization of therapeutic targets for complex human diseases.
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Affiliation(s)
- Albert Henry
- Institute of Cardiovascular Science (A.H., M.G.-M., C.F., A.F.S., A.D.H.), University College London, United Kingdom
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
- Institute of Health Informatics (A.H., R.T.L.), University College London, United Kingdom
| | - María Gordillo-Marañón
- Institute of Cardiovascular Science (A.H., M.G.-M., C.F., A.F.S., A.D.H.), University College London, United Kingdom
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
| | - Chris Finan
- Institute of Cardiovascular Science (A.H., M.G.-M., C.F., A.F.S., A.D.H.), University College London, United Kingdom
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, The Netherlands (C.F., A.F.S.)
| | - Amand F. Schmidt
- Institute of Cardiovascular Science (A.H., M.G.-M., C.F., A.F.S., A.D.H.), University College London, United Kingdom
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, The Netherlands (C.F., A.F.S.)
| | - João Pedro Ferreira
- Unidade de Investigação e Desenvolvimento Cardiovascular, Rede de Investigação em Saúde, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, Portugal (J.P.F.)
- Université de Lorraine, Inserm, Centre d’Investigations Cliniques - Plurithématique 14-33, and Inserm U1116, Centre Hospitalier Régional Universitaire, French Clinical Research Infrastructure Network, Investigation Network Initiative - Cardiovascular and Renal Clinical Trialists, Nancy, France (J.P.F., F.Z.)
| | - Ravi Karra
- Division of Cardiology, Department of Medicine (R.K.), Duke University Medical Center, Durham, NC
- Department of Pathology (R.K.), Duke University Medical Center, Durham, NC
| | - Johan Sundström
- Department of Medical Sciences, Uppsala University, Sweden (J.S., L.L.)
- The George Institute for Global Health, University of New South Wales, Sydney, Australia (J.S.)
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Sweden (J.S., L.L.)
| | - Johan Ärnlöv
- School of Health and Social Studies, Dalarna University, Falun, Sweden (J.Ä.)
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Huddinge, Sweden (J.Ä.)
| | - Faiez Zannad
- Université de Lorraine, Inserm, Centre d’Investigations Cliniques - Plurithématique 14-33, and Inserm U1116, Centre Hospitalier Régional Universitaire, French Clinical Research Infrastructure Network, Investigation Network Initiative - Cardiovascular and Renal Clinical Trialists, Nancy, France (J.P.F., F.Z.)
| | - Anders Mälarstig
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Solna‚ Sweden (A.M.)
- Emerging Science and Innovation, Pfizer Worldwide Research, Development and Medical, Cambridge, MA (A.M.)
| | - Aroon D. Hingorani
- Institute of Cardiovascular Science (A.H., M.G.-M., C.F., A.F.S., A.D.H.), University College London, United Kingdom
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
| | - R. Thomas Lumbers
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
- Institute of Health Informatics (A.H., R.T.L.), University College London, United Kingdom
- Health Data Research UK London (R.T.L.), University College London, United Kingdom
| | - HERMES and SCALLOP Consortia
- Institute of Cardiovascular Science (A.H., M.G.-M., C.F., A.F.S., A.D.H.), University College London, United Kingdom
- British Heart Foundation Research Accelerator (A.H., M.G.-M., C.F., A.F.S., A.D.H., R.T.L.), University College London, United Kingdom
- Institute of Health Informatics (A.H., R.T.L.), University College London, United Kingdom
- Health Data Research UK London (R.T.L.), University College London, United Kingdom
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, The Netherlands (C.F., A.F.S.)
- Unidade de Investigação e Desenvolvimento Cardiovascular, Rede de Investigação em Saúde, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, Portugal (J.P.F.)
- Université de Lorraine, Inserm, Centre d’Investigations Cliniques - Plurithématique 14-33, and Inserm U1116, Centre Hospitalier Régional Universitaire, French Clinical Research Infrastructure Network, Investigation Network Initiative - Cardiovascular and Renal Clinical Trialists, Nancy, France (J.P.F., F.Z.)
- Division of Cardiology, Department of Medicine (R.K.), Duke University Medical Center, Durham, NC
- Department of Pathology (R.K.), Duke University Medical Center, Durham, NC
- Department of Medical Sciences, Uppsala University, Sweden (J.S., L.L.)
- The George Institute for Global Health, University of New South Wales, Sydney, Australia (J.S.)
- School of Health and Social Studies, Dalarna University, Falun, Sweden (J.Ä.)
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Science and Society, Karolinska Institutet, Huddinge, Sweden (J.Ä.)
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Solna‚ Sweden (A.M.)
- Emerging Science and Innovation, Pfizer Worldwide Research, Development and Medical, Cambridge, MA (A.M.)
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Hubacek JA, Hruba P, Adamkova V, Pokorna E, Viklicky O. Apolipoprotein L1 variability is associated with increased risk of renal failure in the Czech population. Gene X 2022; 818:146248. [PMID: 35085711 DOI: 10.1016/j.gene.2022.146248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 12/23/2021] [Accepted: 01/21/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND With stage 5 chronic kidney disease (CKD5) more prevalent in the Czech Republic than in most European countries, genetic susceptibility is potentially implicated. METHODS In a group of 1489 CKD5 kidney transplantation patients (93% with complete clinical characteristics; mean age 52.0 years, 37% females) and 2559 healthy controls (mean age 49.0 years, 51% females), we examined the prevalence of six APOL1 SNPs (rs73885319, rs71785313, rs13056427, rs136147, rs10854688 and rs9610473) and one newly detected 55-nucleotide insertion/deletion polymorphism. RESULTS The rs73885319 and rs71785313 variants were monomorphic in the Czech Caucasian population. Genotype frequencies of the three SNPs examined (rs13056427, rs136147 and rs9610473) were almost identical in patients and controls (all P values were between 0.39 and 0.91). Minor homozygotes of rs10854688 were more common between the patients (13.2%) than in controls (10.7%) (OR [95% CI]; 1.32 [1.08-1.64]; P < 0.01). Prevalence of the newly detected 55-bp APOL1 deletion was significantly higher in CKD5 patients (3.0% vs. 1.7%; OR [95% CI]; 1.80 [1.16-2.80]; P < 0.01) compared to controls. Frequencies of some individual APOL1 haplotypes were borderline different between patients and controls. CONCLUSION We found an association between rs10854688 SNP within the APOL1 gene and end-stage renal disease in the Czech Caucasian population. Further independent studies are required before a conclusive association between the newly detected APOL1 insertion/deletion polymorphism and CKD5 can be confirmed.
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Affiliation(s)
- Jaroslav A Hubacek
- Experimental Medicine Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic.
| | - Petra Hruba
- Transplant Laboratory, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Vera Adamkova
- Department of Preventive Cardiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Eva Pokorna
- Transplantation Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Ondrej Viklicky
- Transplant Laboratory, Institute for Clinical and Experimental Medicine, Prague, Czech Republic; Department of Nephrology, Transplantation Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
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349
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Wilson PC, Humphreys BD. Understanding How Genetic Background Affects Kidney Function at the Single-Cell Level. Am J Kidney Dis 2022; 79:613-615. [PMID: 34871702 DOI: 10.1053/j.ajkd.2021.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 11/01/2021] [Indexed: 11/11/2022]
Affiliation(s)
- Parker C Wilson
- Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, Missouri.
| | - Benjamin D Humphreys
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri; Department of Developmental Biology, Washington University in St. Louis, St. Louis, Missouri
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350
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Park JS, Kim Y, Kang J. Genome-wide meta-analysis revealed several genetic loci associated with serum uric acid levels in Korean population: an analysis of Korea Biobank data. J Hum Genet 2022; 67:231-237. [PMID: 34719683 DOI: 10.1038/s10038-021-00991-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 10/19/2021] [Accepted: 10/20/2021] [Indexed: 11/09/2022]
Abstract
The serum uric acid (SUA) level is an important determinant of gout, hypertension, metabolic syndrome, and cardiovascular disease. Although previous genome-wide studies have identified multiple genetic variants associated with SUA, most genetic analyses have focused on individuals with European ancestry; thus, understanding of the genetic architecture of SUA is currently limited for Asian populations. We conducted a genome-wide meta-analysis based on Korea Biobank data consistent with three cohorts; namely, the Korean Genome and Epidemiology Study (KoGES) Ansan and Ansung, KoGES Health Examinee, and KoGES Cardiovascular Disease Association studies. In total, 60,585 participants aged ≥40 years were included in the analysis of the three cohorts. We used logistic regression analyses to perform genome-wide association study (GWAS) adjustments for confounding variables. Subsequently, a meta-analysis was conducted by combining the analyses of the three GWASs. We identified 8,105 variants at 22 genetic loci with a P value < 5 × 10-8. Among these, six novel genetic loci associated with SUA in the Korean population were identified (rs4715517 in HCRTR2, rs145099458 in 3.2 kb 3' of MLXIPL, rs1137642 in B4GALT1, rs659107 in LOC105378410, rs7919329 in LOC107984274, and rs2240751 in MFSD12). Our meta-analysis provides insights into the genetic architecture of SUA in the Korean population. Further studies are warranted to replicate the study results and elucidate the specific role of these variants in SUA homeostasis.
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Affiliation(s)
- Jin Sung Park
- Department of Medicine, Kosin University Gospel Hospital, Kosin University College of Medicine, Busan, Republic of Korea
| | - Yunkyung Kim
- Division of Rheumatology, Department of Internal Medicine, Kosin University Gospel Hospital, Kosin University College of Medicine, Busan, Republic of Korea
| | - Jihun Kang
- Department of Family Medicine, Kosin University Gospel Hospital, Kosin University College of Medicine, Busan, Republic of Korea.
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