351
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Multi-omics studies reveal genes critical for AKI and ferroptosis. Kidney Int 2022; 101:665-667. [DOI: 10.1016/j.kint.2021.10.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 10/28/2021] [Indexed: 11/21/2022]
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352
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Kjaergaard AD, Teumer A, Witte DR, Stanzick KJ, Winkler TW, Burgess S, Ellervik C. Obesity and Kidney Function: A Two-Sample Mendelian Randomization Study. Clin Chem 2022; 68:461-472. [PMID: 34922334 PMCID: PMC7614591 DOI: 10.1093/clinchem/hvab249] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 10/05/2021] [Indexed: 09/12/2023]
Abstract
BACKGROUND Obesity and type 2 diabetes (T2D) are correlated risk factors for chronic kidney disease (CKD). METHODS Using summary data from GIANT (Genetic Investigation of Anthropometric Traits), DIAGRAM (DIAbetes Genetics Replication And Meta-analysis), and CKDGen (CKD Genetics), we examined causality and directionality of the association between obesity and kidney function. Bidirectional 2-sample Mendelian randomization (MR) estimated the total causal effects of body mass index (BMI) and waist-to-hip ratio (WHR) on kidney function, and vice versa. Effects of adverse obesity and T2D were examined by stratifying BMI variants by their association with WHR and T2D. Multivariable MR estimated the direct causal effects of BMI and WHR on kidney function. The inverse variance weighted random-effects MR for Europeans was the main analysis, accompanied by several sensitivity MR analyses. RESULTS One standard deviation (SD ≈ 4.8 kg/m2) genetically higher BMI was associated with decreased estimated glomerular filtration rate (eGFR) [β=-0.032 (95% confidence intervals: -0.036, -0.027) log[eGFR], P = 1 × 10-43], increased blood urea nitrogen (BUN) [β = 0.010 (0.005, 0.015) log[BUN], P = 3 × 10-6], increased urinary albumin-to-creatinine ratio [β = 0.199 (0.067, 0.332) log[urinary albumin-to-creatinine ratio (UACR)], P = 0.003] in individuals with diabetes, and increased risk of microalbuminuria [odds ratios (OR) = 1.15 [1.04-1.28], P = 0.009] and CKD [1.13 (1.07-1.19), P = 3 × 10-6]. Corresponding estimates for WHR and for trans-ethnic populations were overall similar. The associations were driven by adverse obesity, and for microalbuminuria additionally by T2D. While genetically high BMI, unlike WHR, was directly associated with eGFR, BUN, and CKD, the pathway to albuminuria was likely through T2D. Genetically predicted kidney function was not associated with BMI or WHR. CONCLUSIONS Genetically high BMI is associated with impaired kidney function, driven by adverse obesity, and for albuminuria additionally by T2D.
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Affiliation(s)
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany, and DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Daniel R. Witte
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark, and Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Kira-Julia Stanzick
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Thomas W. Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, and Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge
| | - Christina Ellervik
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DK-2200, Denmark; Department of Data and Development, Sorø, Region Zealand, Denmark; Department of Pathology, Harvard Medical School, Boston, MA-02215, USA; and Department of Laboratory Medicine, Boston Children’s Hospital, Boston, MA-02215, USA
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353
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Pedersen EM, Agerbo E, Plana-Ripoll O, Grove J, Dreier JW, Musliner KL, Bækvad-Hansen M, Athanasiadis G, Schork A, Bybjerg-Grauholm J, Hougaard DM, Werge T, Nordentoft M, Mors O, Dalsgaard S, Christensen J, Børglum AD, Mortensen PB, McGrath JJ, Privé F, Vilhjálmsson BJ. Accounting for age of onset and family history improves power in genome-wide association studies. Am J Hum Genet 2022; 109:417-432. [PMID: 35139346 PMCID: PMC8948165 DOI: 10.1016/j.ajhg.2022.01.009] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 01/07/2022] [Indexed: 11/01/2022] Open
Abstract
Genome-wide association studies (GWASs) have revolutionized human genetics, allowing researchers to identify thousands of disease-related genes and possible drug targets. However, case-control status does not account for the fact that not all controls may have lived through their period of risk for the disorder of interest. This can be quantified by examining the age-of-onset distribution and the age of the controls or the age of onset for cases. The age-of-onset distribution may also depend on information such as sex and birth year. In addition, family history is not routinely included in the assessment of control status. Here, we present LT-FH++, an extension of the liability threshold model conditioned on family history (LT-FH), which jointly accounts for age of onset and sex as well as family history. Using simulations, we show that, when family history and the age-of-onset distribution are available, the proposed approach yields statistically significant power gains over LT-FH and large power gains over genome-wide association study by proxy (GWAX). We applied our method to four psychiatric disorders available in the iPSYCH data and to mortality in the UK Biobank and found 20 genome-wide significant associations with LT-FH++, compared to ten for LT-FH and eight for a standard case-control GWAS. As more genetic data with linked electronic health records become available to researchers, we expect methods that account for additional health information, such as LT-FH++, to become even more beneficial.
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Affiliation(s)
- Emil M Pedersen
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark; Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark.
| | - Esben Agerbo
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark; Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark; Centre for Integrated Register-Based Research at Aarhus University, 8210 Aarhus, Denmark
| | - Oleguer Plana-Ripoll
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark
| | - Jakob Grove
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark; Bioinformatics Research Centre, Aarhus University, 8000 Aarhus, Denmark; Department of Biomedicine and Center for Integrative Sequencing, Aarhus University, 8000 Aarhus, Denmark; Center for Genomics and Personalized Medicine, Aarhus University, 8000 Aarhus, Denmark
| | - Julie W Dreier
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark; Centre for Integrated Register-Based Research at Aarhus University, 8210 Aarhus, Denmark
| | - Katherine L Musliner
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark; Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark; Centre for Integrated Register-Based Research at Aarhus University, 8210 Aarhus, Denmark
| | - Marie Bækvad-Hansen
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark; Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, 2300 Copenhagen, Denmark
| | - Georgios Athanasiadis
- Institute of Biological Psychiatry, MHC Sct. Hans, Mental Health Services Copenhagen, 4000 Roskilde, Denmark
| | - Andrew Schork
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark; Institute of Biological Psychiatry, MHC Sct. Hans, Mental Health Services Copenhagen, 4000 Roskilde, Denmark
| | - Jonas Bybjerg-Grauholm
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark; Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, 2300 Copenhagen, Denmark
| | - David M Hougaard
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark; Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, 2300 Copenhagen, Denmark
| | - Thomas Werge
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark; Institute of Biological Psychiatry, MHC Sct. Hans, Mental Health Services Copenhagen, 4000 Roskilde, Denmark; Department of Clinical Medicine, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Merete Nordentoft
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark; Mental Health Services in the Capital Region of Denmark, Mental Health Center Copenhagen, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Ole Mors
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark; Psychosis Research Unit, Aarhus University Hospital, 8245 Risskov, Denmark
| | - Søren Dalsgaard
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark
| | - Jakob Christensen
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark; Department of Neurology, Aarhus University Hospital, 8200 Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, 8200 Aarhus, Denmark
| | - Anders D Børglum
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark; Center for Genomics and Personalized Medicine, Aarhus University, 8000 Aarhus, Denmark; Department of Biomedicine - Human Genetics, Aarhus University, 8000 Aarhus, Denmark
| | - Preben B Mortensen
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark; Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark; Centre for Integrated Register-Based Research at Aarhus University, 8210 Aarhus, Denmark
| | - John J McGrath
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark; Queensland Brain Institute, University of Queensland, St Lucia, QLD 4072, Australia; Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Wacol, QLD 4076, Australia
| | - Florian Privé
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark
| | - Bjarni J Vilhjálmsson
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus, Denmark; Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8210 Aarhus, Denmark; Bioinformatics Research Centre, Aarhus University, 8000 Aarhus, Denmark.
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354
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Joseph CB, Mariniello M, Yoshifuji A, Schiano G, Lake J, Marten J, Richmond A, Huffman JE, Campbell A, Harris SE, Troyanov S, Cocca M, Robino A, Thériault S, Eckardt KU, Wuttke M, Cheng Y, Corre T, Kolcic I, Black C, Bruat V, Concas MP, Sala C, Aeschbacher S, Schaefer F, Bergmann S, Campbell H, Olden M, Polasek O, Porteous DJ, Deary IJ, Madore F, Awadalla P, Girotto G, Ulivi S, Conen D, Wuehl E, Olinger E, Wilson JF, Bochud M, Köttgen A, Hayward C, Devuyst O. Meta-GWAS Reveals Novel Genetic Variants Associated with Urinary Excretion of Uromodulin. J Am Soc Nephrol 2022; 33:511-529. [PMID: 35228297 PMCID: PMC8975067 DOI: 10.1681/asn.2021040491] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 12/27/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Uromodulin, the most abundant protein excreted in normal urine, plays major roles in kidney physiology and disease. The mechanisms regulating the urinary excretion of uromodulin remain essentially unknown. METHODS We conducted a meta-analysis of genome-wide association studies for raw (uUMOD) and indexed to creatinine (uUCR) urinary levels of uromodulin in 29,315 individuals of European ancestry from 13 cohorts. We tested the distribution of candidate genes in kidney segments and investigated the effects of keratin-40 (KRT40) on uromodulin processing. RESULTS Two genome-wide significant signals were identified for uUMOD: a novel locus (P 1.24E-08) over the KRT40 gene coding for KRT40, a type 1 keratin expressed in the kidney, and the UMOD-PDILT locus (P 2.17E-88), with two independent sets of single nucleotide polymorphisms spread over UMOD and PDILT. Two genome-wide significant signals for uUCR were identified at the UMOD-PDILT locus and at the novel WDR72 locus previously associated with kidney function. The effect sizes for rs8067385, the index single nucleotide polymorphism in the KRT40 locus, were similar for both uUMOD and uUCR. KRT40 colocalized with uromodulin and modulating its expression in thick ascending limb (TAL) cells affected uromodulin processing and excretion. CONCLUSIONS Common variants in KRT40, WDR72, UMOD, and PDILT associate with the levels of uromodulin in urine. The expression of KRT40 affects uromodulin processing in TAL cells. These results, although limited by lack of replication, provide insights into the biology of uromodulin, the role of keratins in the kidney, and the influence of the UMOD-PDILT locus on kidney function.
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Affiliation(s)
- Christina B Joseph
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
| | - Marta Mariniello
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Ayumi Yoshifuji
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Guglielmo Schiano
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Jennifer Lake
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Jonathan Marten
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
| | - Anne Richmond
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
| | - Jennifer E Huffman
- Center for Population Genomics,VA Boston Healthcare System, Jamaica Plain, Massachusetts
- The Framingham Heart Study, Framingham, Massachusetts
| | - Archie Campbell
- Centre for Genomic & Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Stephan Troyanov
- Division of Nephrology, Hôpital du Sacre-Coeur de Montreal, Montreal, Canada
| | - Massimiliano Cocca
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
| | - Antonietta Robino
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
| | - Sébastien Thériault
- Department of Molecular Biology, Medical Biochemistry and Pathology, Laval University, Quebec City, Canada
- Population Health Research Institute, McMaster University, Hamilton, Canada
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charite Universitätsmedizin Berlin, Berlin, Germany
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Yurong Cheng
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Tanguy Corre
- Center for Primary Care and Public Health (Unisante), University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ivana Kolcic
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - Corrinda Black
- Aberdeen Centre for Health Data Science, School of Medicine, Medical Science and Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - Vanessa Bruat
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Maria Pina Concas
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
| | - Cinzia Sala
- Genetics of Common Disorders Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Franz Schaefer
- Division of Pediatric Nephrology, Center for Pediatrics and Adolescent Medicine, University Hospital Heidelberg, Heidelberg, Germany
| | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Harry Campbell
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Matthias Olden
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Ozren Polasek
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - David J Porteous
- Centre for Genomic & Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Francois Madore
- Division of Nephrology, Hôpital du Sacre-Coeur de Montreal, Montreal, Canada
| | - Philip Awadalla
- Division of Nephrology, Hôpital du Sacre-Coeur de Montreal, Montreal, Canada
| | - Giorgia Girotto
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149, Trieste, Italy
| | - Sheila Ulivi
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
| | - David Conen
- Population Health Research Institute, McMaster University, Hamilton, Canada
| | - Elke Wuehl
- Cardiology Division, University Hospital Basel, Basel, Switzerland
| | - Eric Olinger
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
- Translational and Clinical Research Institute, Newcastle upon Tyne, Newcastle, United Kingdom
| | - James F Wilson
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Murielle Bochud
- Center for Primary Care and Public Health (Unisante), University of Lausanne, Lausanne, Switzerland
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Genomic & Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Olivier Devuyst
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
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355
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Disentangling the association between kidney function and atrial fibrillation: A bidirectional Mendelian randomization study. Int J Cardiol 2022; 355:15-22. [DOI: 10.1016/j.ijcard.2022.03.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 03/03/2022] [Accepted: 03/07/2022] [Indexed: 11/17/2022]
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356
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Kelly DM, Rothwell PM. Disentangling the Relationship Between Chronic Kidney Disease and Cognitive Disorders. Front Neurol 2022; 13:830064. [PMID: 35280286 PMCID: PMC8914950 DOI: 10.3389/fneur.2022.830064] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 02/03/2022] [Indexed: 12/12/2022] Open
Abstract
Chronic kidney disease (CKD) is a rapidly rising global health burden that affects nearly 40% of older adults. Epidemiologic data suggest that individuals at all stages of chronic kidney disease (CKD) have a higher risk of developing cognitive disorders and dementia, and thus represent a vulnerable population. It is currently unknown to what extent this risk may be attributable to a clustering of traditional risk factors such as hypertension and diabetes mellitus leading to a high prevalence of both symptomatic and subclinical ischaemic cerebrovascular lesions, or whether other potential mechanisms, including direct neuronal injury by uraemic toxins or dialysis-specific factors could also be involved. These knowledge gaps may lead to suboptimal prevention and treatment strategies being implemented in this group. In this review, we explore the mechanisms of susceptibility and risk in the relationship between CKD and cognitive disorders.
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Affiliation(s)
- Dearbhla M. Kelly
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Peter M. Rothwell
- Wolfson Center for Prevention of Stroke and Dementia, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
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357
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Schubert R, Geoffroy E, Gregga I, Mulford AJ, Aguet F, Ardlie K, Gerszten R, Clish C, Van Den Berg D, Taylor KD, Durda P, Johnson WC, Cornell E, Guo X, Liu Y, Tracy R, Conomos M, Blackwell T, Papanicolaou G, Lappalainen T, Mikhaylova AV, Thornton TA, Cho MH, Gignoux CR, Lange L, Lange E, Rich SS, Rotter JI, NHLBI TOPMed Consortium, Manichaikul A, Im HK, Wheeler HE. Protein prediction for trait mapping in diverse populations. PLoS One 2022; 17:e0264341. [PMID: 35202437 PMCID: PMC8870552 DOI: 10.1371/journal.pone.0264341] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 02/08/2022] [Indexed: 11/18/2022] Open
Abstract
Genetically regulated gene expression has helped elucidate the biological mechanisms underlying complex traits. Improved high-throughput technology allows similar interrogation of the genetically regulated proteome for understanding complex trait mechanisms. Here, we used the Trans-omics for Precision Medicine (TOPMed) Multi-omics pilot study, which comprises data from Multi-Ethnic Study of Atherosclerosis (MESA), to optimize genetic predictors of the plasma proteome for genetically regulated proteome-wide association studies (PWAS) in diverse populations. We built predictive models for protein abundances using data collected in TOPMed MESA, for which we have measured 1,305 proteins by a SOMAscan assay. We compared predictive models built via elastic net regression to models integrating posterior inclusion probabilities estimated by fine-mapping SNPs prior to elastic net. In order to investigate the transferability of predictive models across ancestries, we built protein prediction models in all four of the TOPMed MESA populations, African American (n = 183), Chinese (n = 71), European (n = 416), and Hispanic/Latino (n = 301), as well as in all populations combined. As expected, fine-mapping produced more significant protein prediction models, especially in African ancestries populations, potentially increasing opportunity for discovery. When we tested our TOPMed MESA models in the independent European INTERVAL study, fine-mapping improved cross-ancestries prediction for some proteins. Using GWAS summary statistics from the Population Architecture using Genomics and Epidemiology (PAGE) study, which comprises ∼50,000 Hispanic/Latinos, African Americans, Asians, Native Hawaiians, and Native Americans, we applied S-PrediXcan to perform PWAS for 28 complex traits. The most protein-trait associations were discovered, colocalized, and replicated in large independent GWAS using proteome prediction model training populations with similar ancestries to PAGE. At current training population sample sizes, performance between baseline and fine-mapped protein prediction models in PWAS was similar, highlighting the utility of elastic net. Our predictive models in diverse populations are publicly available for use in proteome mapping methods at https://doi.org/10.5281/zenodo.4837327.
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Affiliation(s)
- Ryan Schubert
- Department of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, United States of America
- Department of Biology, Loyola University Chicago, Chicago, IL, United States of America
- Program in Bioinformatics, Loyola University Chicago, Chicago, IL, United States of America
| | - Elyse Geoffroy
- Program in Bioinformatics, Loyola University Chicago, Chicago, IL, United States of America
| | - Isabelle Gregga
- Department of Biology, Loyola University Chicago, Chicago, IL, United States of America
| | - Ashley J. Mulford
- Department of Biology, Loyola University Chicago, Chicago, IL, United States of America
- Program in Bioinformatics, Loyola University Chicago, Chicago, IL, United States of America
| | - Francois Aguet
- Broad Institute, Cambridge, MA, United States of America
| | - Kristin Ardlie
- Broad Institute, Cambridge, MA, United States of America
| | - Robert Gerszten
- Beth Israel Deaconess Medical Center, Boston, MA, United States of America
| | - Clary Clish
- Broad Institute, Cambridge, MA, United States of America
| | - David Van Den Berg
- University of Southern California, Los Angeles, CA, United States of America
| | - 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, United States of America
| | - Peter Durda
- Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, VT, United States of America
| | - W. Craig Johnson
- Collaborative Health Studies Coordinating Center, University of Washington, Seattle, WA, United States of America
| | - Elaine Cornell
- Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, VT, United States of America
| | - 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, United States of America
| | - Yongmei Liu
- Department of Medicine, Duke University School of Medicine, Durham, NC, United States of America
| | - Russell Tracy
- Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, VT, United States of America
| | - Matthew Conomos
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Tom Blackwell
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States of America
| | - George Papanicolaou
- Epidemiology Branch, National Heart, Lung and Blood Institute, Bethesda, MD, United States of America
| | - Tuuli Lappalainen
- New York Genome Center and Department of Systems Biology, Columbia University, New York, NY United States of America
| | - Anna V. Mikhaylova
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Timothy A. Thornton
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Michael H. Cho
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
| | - Christopher R. Gignoux
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Leslie Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Ethan Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, United States of America
| | - 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, United States of America
| | | | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, United States of America
| | - Hae Kyung Im
- Section of Genetic Medicine, The University of Chicago, Chicago, IL, United States of America
| | - Heather E. Wheeler
- Department of Biology, Loyola University Chicago, Chicago, IL, United States of America
- Program in Bioinformatics, Loyola University Chicago, Chicago, IL, United States of America
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Tsao CW, Aday AW, Almarzooq ZI, Alonso A, Beaton AZ, Bittencourt MS, Boehme AK, Buxton AE, Carson AP, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Ferguson JF, Generoso G, Ho JE, Kalani R, Khan SS, Kissela BM, Knutson KL, Levine DA, Lewis TT, Liu J, Loop MS, Ma J, Mussolino ME, Navaneethan SD, Perak AM, Poudel R, Rezk-Hanna M, Roth GA, Schroeder EB, Shah SH, Thacker EL, VanWagner LB, Virani SS, Voecks JH, Wang NY, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association. Circulation 2022; 145:e153-e639. [PMID: 35078371 DOI: 10.1161/cir.0000000000001052] [Citation(s) in RCA: 3174] [Impact Index Per Article: 1058.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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359
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First genome-wide association study investigating blood pressure and renal traits in domestic cats. Sci Rep 2022; 12:1899. [PMID: 35115544 PMCID: PMC8813908 DOI: 10.1038/s41598-022-05494-3] [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: 03/05/2021] [Accepted: 12/28/2021] [Indexed: 11/08/2022] Open
Abstract
Hypertension (HTN) and chronic kidney disease (CKD) are common in ageing cats. In humans, blood pressure (BP) and renal function are complex heritable traits. We performed the first feline genome-wide association study (GWAS) of quantitative traits systolic BP and creatinine and binary outcomes HTN and CKD, testing 1022 domestic cats with a discovery, replication and meta-analysis design. No variants reached experimental significance level in the discovery stage for any phenotype. Follow up of the top 9 variants for creatinine and 5 for systolic BP, one SNP reached experimental-wide significance for association with creatinine in the combined meta-analysis (chrD1.10258177; P = 1.34 × 10–6). Exploratory genetic risk score (GRS) analyses were performed. Within the discovery sample, GRS of top SNPs from the BP and creatinine GWAS show strong association with HTN and CKD but did not validate in independent replication samples. A GRS including SNPs corresponding to human CKD genes was not significant in an independent subset of cats. Gene-set enrichment and pathway-based analysis (GSEA) was performed for both quantitative phenotypes, with 30 enriched pathways with creatinine. Our results support the utility of GWASs and GSEA for genetic discovery of complex traits in cats, with the caveat of our findings requiring validation.
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360
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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. Nonlinear causal effects of estimated glomerular filtration rate on myocardial infarction risks: Mendelian randomization study. BMC Med 2022; 20:44. [PMID: 35109828 PMCID: PMC8811984 DOI: 10.1186/s12916-022-02251-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 01/11/2022] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Previous observational studies suggested that a reduction in estimated glomerular filtration rate (eGFR) or a supranormal eGFR value was associated with adverse cardiovascular risks. However, a previous Mendelian randomization (MR) study under the linearity assumption reported null causal effects from eGFR on myocardial infarction (MI) risks. Further investigation of the nonlinear causal effect of kidney function assessed by eGFR on the risk of MI by nonlinear MR analysis is warranted. METHODS In this MR study, genetic instruments for log-eGFR based on serum creatinine were developed from European samples included in the CKDGen genome-wide association study (GWAS) meta-analysis (N=567,460). Alternate instruments for log-eGFR based on cystatin C were developed from a GWAS of European individuals that included the CKDGen and UK Biobank data (N=460,826). Nonlinear MR analysis for the risk of MI was performed using the fractional polynomial method and the piecewise linear method on data from individuals of white British ancestry in the UK Biobank (N=321,024, with 12,205 MI cases). RESULTS Nonlinear MR analysis demonstrated a U-shaped (quadratic P value < 0.001) association between MI risk and genetically predicted eGFR (creatinine) values, as MI risk increased as eGFR declined in the low eGFR range and the risk increased as eGFR increased in the high eGFR range. The results were similar even after adjustment for clinical covariates, such as blood pressure, diabetes mellitus, dyslipidemia, or urine microalbumin levels, or when genetically predicted eGFR (cystatin C) was included as the exposure. CONCLUSION Genetically predicted eGFR is significantly associated with the risk of MI with a parabolic shape, suggesting that kidney function impairment, either by reduced or supranormal eGFR, may be causally linked to a higher MI risk.
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Affiliation(s)
- Sehoon Park
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, South Korea.,Department of Internal Medicine, Armed Forces Capital Hospital, Gyeonggi-do, South Korea
| | - Soojin Lee
- Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Seoul, South Korea.,Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
| | - Yaerim Kim
- Department of Internal Medicine, Keimyung University School of Medicine, Daegu, South Korea
| | - Semin Cho
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea.,Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
| | - Hyeok Huh
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
| | - Kwangsoo Kim
- Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul, South Korea
| | - Yong Chul Kim
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
| | - Seung Seok Han
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea.,Kidney Research Institute, Seoul National University, Seoul, South Korea
| | - Hajeong Lee
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
| | - Jung Pyo Lee
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea.,Kidney Research Institute, Seoul National University, Seoul, South Korea.,Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, South Korea
| | - Kwon Wook Joo
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea.,Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea.,Kidney Research Institute, Seoul National University, Seoul, South Korea
| | - Chun Soo Lim
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea.,Kidney Research Institute, Seoul National University, Seoul, South Korea.,Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, South Korea
| | - Yon Su Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, South Korea.,Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea.,Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea.,Kidney Research Institute, Seoul National University, Seoul, South Korea
| | - Dong Ki Kim
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea. .,Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea. .,Kidney Research Institute, Seoul National University, Seoul, South Korea.
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361
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Dawoud AAZ, Gilbert RD, Tapper WJ, Cross NCP. Clonal myelopoiesis promotes adverse outcomes in chronic kidney disease. Leukemia 2022; 36:507-515. [PMID: 34413458 PMCID: PMC8807385 DOI: 10.1038/s41375-021-01382-3] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 07/29/2021] [Accepted: 08/02/2021] [Indexed: 12/18/2022]
Abstract
We sought to determine the relationship between age-related clonal hematopoiesis (CH) and chronic kidney disease (CKD). CH, defined as mosaic chromosome abnormalities (mCA) and/or driver mutations was identified in 5449 (2.9%) eligible UK Biobank participants (n = 190,487 median age = 58 years). CH was negatively associated with glomerular filtration rate estimated from cystatin-C (eGFR.cys; β = -0.75, P = 2.37 × 10-4), but not with eGFR estimated from creatinine, and was specifically associated with CKD defined by eGFR.cys < 60 (OR = 1.02, P = 8.44 × 10-8). In participants without prevalent myeloid neoplasms, eGFR.cys was associated with myeloid mCA (n = 148, β = -3.36, P = 0.01) and somatic driver mutations (n = 3241, β = -1.08, P = 6.25 × 10-5) associated with myeloid neoplasia (myeloid CH), specifically mutations in CBL, TET2, JAK2, PPM1D and GNB1 but not DNMT3A or ASXL1. In participants with no history of cardiovascular disease or myeloid neoplasms, myeloid CH increased the risk of adverse outcomes in CKD (HR = 1.6, P = 0.002) compared to those without myeloid CH. Mendelian randomisation analysis provided suggestive evidence for a causal relationship between CH and CKD (P = 0.03). We conclude that CH, and specifically myeloid CH, is associated with CKD defined by eGFR.cys. Myeloid CH promotes adverse outcomes in CKD, highlighting the importance of the interaction between intrinsic and extrinsic factors to define the health risk associated with CH.
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Affiliation(s)
| | - Rodney D Gilbert
- Faculty of Medicine, University of Southampton, Southampton, UK
- Southampton Children's Hospital, Southampton, UK
| | | | - Nicholas C P Cross
- Faculty of Medicine, University of Southampton, Southampton, UK.
- Wessex Regional Genetics Laboratory, Salisbury NHS Foundation Trust, Salisbury, UK.
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362
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Research Priorities for Kidney-Related Research-An Agenda to Advance Kidney Care: A Position Statement From the National Kidney Foundation. Am J Kidney Dis 2022; 79:141-152. [PMID: 34627932 DOI: 10.1053/j.ajkd.2021.08.018] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 08/26/2021] [Indexed: 02/01/2023]
Abstract
Despite the high prevalence and economic burden of chronic kidney disease (CKD) in the United States, federal funding for kidney-related research, prevention, and education activities under the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) remains substantially lower compared to other chronic diseases. More federal support is needed to promote critical research that will expand knowledge of kidney health and disease, develop new and effective therapies, and reduce health disparities. In 2021, the National Kidney Foundation (NKF) convened 2 Research Roundtables (preclinical and clinical research), comprising nephrology leaders from prominent US academic institutions and the pharmaceutical industry, key bodies with expertise in research, and including individuals with CKD and their caregivers and kidney donors. The goal of these roundtables was to identify priorities for preclinical and clinical kidney-related research. The research priorities identified by the Research Roundtables and presented in this position statement outline attainable opportunities for groundbreaking and critically needed innovations that will benefit patients with kidney disease in the next 5-10 years. Research priorities fall within 4 preclinical science themes (expand data science capability, define kidney disease mechanisms and utilize genetic tools to identify new therapeutic targets, develop better models of human disease, and test cell-specific drug delivery systems and utilize gene editing) and 3 clinical science themes (expand number and inclusivity of clinical trials, develop and test interventions to reduce health disparities, and support implementation science). These priorities in kidney-related research, if supported by additional funding by federal agencies, will increase our understanding of the development and progression of kidney disease among diverse populations, attract additional industry investment, and lead to new and more personalized treatments.
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363
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Gonzalez-Fernandez E, Fan L, Wang S, Liu Y, Gao W, Thomas KN, Fan F, Roman RJ. The adducin saga: pleiotropic genomic targets for precision medicine in human hypertension-vascular, renal, and cognitive diseases. Physiol Genomics 2022; 54:58-70. [PMID: 34859687 PMCID: PMC8799388 DOI: 10.1152/physiolgenomics.00119.2021] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 11/23/2021] [Accepted: 11/29/2021] [Indexed: 02/03/2023] Open
Abstract
Hypertension is a leading risk factor for stroke, heart disease, chronic kidney disease, vascular cognitive impairment, and Alzheimer's disease. Previous genetic studies have nominated hundreds of genes linked to hypertension, and renal and cognitive diseases. Some have been advanced as candidate genes by showing that they can alter blood pressure or renal and cerebral vascular function in knockout animals; however, final validation of the causal variants and underlying mechanisms has remained elusive. This review chronicles 40 years of work, from the initial identification of adducin (ADD) as an ACTIN-binding protein suggested to increase blood pressure in Milan hypertensive rats, to the discovery of a mutation in ADD1 as a candidate gene for hypertension in rats that were subsequently linked to hypertension in man. More recently, a recessive K572Q mutation in ADD3 was identified in Fawn-Hooded Hypertensive (FHH) and Milan Normotensive (MNS) rats that develop renal disease, which is absent in resistant strains. ADD3 dimerizes with ADD1 to form functional ADD protein. The mutation in ADD3 disrupts a critical ACTIN-binding site necessary for its interactions with actin and spectrin to regulate the cytoskeleton. Studies using Add3 KO and transgenic strains, as well as a genetic complementation study in FHH and MNS rats, confirmed that the K572Q mutation in ADD3 plays a causal role in altering the myogenic response and autoregulation of renal and cerebral blood flow, resulting in increased susceptibility to hypertension-induced renal disease and cerebral vascular and cognitive dysfunction.
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Affiliation(s)
- Ezekiel Gonzalez-Fernandez
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi
| | - Letao Fan
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi
| | - Shaoxun Wang
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi
| | - Yedan Liu
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi
| | - Wenjun Gao
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi
| | - Kirby N Thomas
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi
| | - Fan Fan
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi
| | - Richard J Roman
- Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, Mississippi
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364
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Park S, Lee S, Kim Y, Cho S, Kim K, Chul Kim Y, Han SS, Lee H, Lee JP, Joo KW, Lim CS, Kim YS, Kim DK. Causal effects from non-alcoholic fatty liver disease on kidney function: A Mendelian randomization study. Liver Int 2022; 42:412-418. [PMID: 34843158 DOI: 10.1111/liv.15118] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 11/25/2021] [Indexed: 12/22/2022]
Abstract
BACKGROUND AND AIMS An observational association between nonalcoholic fatty liver disease (NAFLD) and kidney function impairment has been reported. We aimed to investigate the causal effects from NAFLD on estimated glomerular filtration rate (eGFR) by a Mendelian randomization (MR) study. METHODS We first performed single-variant MR with rs738409 as a genetic instrument for NAFLD. Another genetic instrument was developed from a genome-wide association study for biopsy-confirmed NAFLD among individuals of European ancestry (1483 cases and 17 781 controls). The eGFR outcome was assessed in individuals of white British ancestry from the UK Biobank (N = 321 405). The associations were reassessed in the negative control subgroup (body mass index < 30 kg/m2 , absence of central obesity, and serum alanine aminotransferase level ≤ 20 IU/mL) with a low probability of developing NAFLD. As a replication analysis, a summary-level MR was performed with the European ancestry CKDGen dataset (N = 567 460). RESULTS In the UK Biobank, a genetic predisposition for NAFLD, determined either by the single SNP rs738409 or by the group of variants, was significantly associated with a reduced eGFR even with adjustment for metabolic disorders. Although the associations were not significant in the negative control subgroup with a low probability of developing NAFLD, they were significant in the subgroup with a remaining risk of NAFLD, suggesting the absence of a horizontal pleiotropic pathway. The summary-level MR from the CKDGen dataset supported the causal effects of NAFLD on reduced eGFR. CONCLUSIONS This MR analysis supports the causal reduction in kidney function by NAFLD.
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Affiliation(s)
- Sehoon Park
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea.,Department of Internal Medicine, Armed Forces Capital Hospital, Gyeonggi-do, Korea
| | - Soojin Lee
- Division of Nephrology, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Korea
| | - Yaerim Kim
- Department of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea
| | - Semin Cho
- Department of Internal Medicine, Seoul National University Hospital, Seoul, 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.,Kidney Research Institute, Seoul National University, 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 Hospital, Seoul, Korea.,Department of Internal Medicine, Seoul National University College of Medicine, 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 Hospital, Seoul, Korea.,Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.,Kidney Research Institute, Seoul National University, Seoul, Korea
| | - Dong Ki Kim
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea.,Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.,Kidney Research Institute, Seoul National University, Seoul, Korea
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365
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Piras D, Lepori N, Cabiddu G, Pani A. How Genetics Can Improve Clinical Practice in Chronic Kidney Disease: From Bench to Bedside. J Pers Med 2022; 12:jpm12020193. [PMID: 35207681 PMCID: PMC8875178 DOI: 10.3390/jpm12020193] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/17/2022] [Accepted: 01/24/2022] [Indexed: 01/27/2023] Open
Abstract
Chronic kidney disease (CKD) is considered a major global health problem with high socio-economic costs: the risk of CKD in individuals with an affected first degree relative has been found to be three times higher than in the general population. Genetic factors are known to be involved in CKD pathogenesis, both due to the possible presence of monogenic pathologies as causes of CKD, and to the role of numerous gene variants in determining susceptibility to the development of CKD. The genetic study of CKD patients can represent a useful tool in the hands of the clinician; not only in the diagnostic and prognostic field, but potentially also in guiding therapeutic choices and in designing clinical trials. In this review we discuss the various aspects of the role of genetic analysis on clinical management of patients with CKD with a focus on clinical applications. Several topics are discussed in an effort to provide useful information for daily clinical practice: definition of susceptibility to the development of CKD, identification of unrecognized monogenic diseases, reclassification of the etiological diagnosis, role of pharmacogenetics.
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Affiliation(s)
- Doloretta Piras
- Struttura Complessa di Nefrologia, Dialisi e Trapianto, ARNAS Brotzu, 09134 Cagliari, Italy; (N.L.); (G.C.); (A.P.)
- Correspondence:
| | - Nicola Lepori
- Struttura Complessa di Nefrologia, Dialisi e Trapianto, ARNAS Brotzu, 09134 Cagliari, Italy; (N.L.); (G.C.); (A.P.)
| | - Gianfranca Cabiddu
- Struttura Complessa di Nefrologia, Dialisi e Trapianto, ARNAS Brotzu, 09134 Cagliari, Italy; (N.L.); (G.C.); (A.P.)
- Dipartimento di Scienze Mediche e Sanità Pubblica, Università degli Studi di Cagliari, 09134 Cagliari, Italy
| | - Antonello Pani
- Struttura Complessa di Nefrologia, Dialisi e Trapianto, ARNAS Brotzu, 09134 Cagliari, Italy; (N.L.); (G.C.); (A.P.)
- Dipartimento di Scienze Mediche e Sanità Pubblica, Università degli Studi di Cagliari, 09134 Cagliari, Italy
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerce (CNR), 09042 Monserrato, Italy
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366
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Alcina A, Fedetz M, Vidal-Cobo I, Andrés-León E, García-Sánchez MI, Barroso-Del-Jesus A, Eichau S, Gil-Varea E, Villar LM, Saiz A, Leyva L, Vandenbroeck K, Otaegui D, Izquierdo G, Comabella M, Urcelay E, Matesanz F. Identification of the genetic mechanism that associates L3MBTL3 to multiple sclerosis. Hum Mol Genet 2022; 31:2155-2163. [PMID: 35088080 PMCID: PMC9262392 DOI: 10.1093/hmg/ddac009] [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: 07/29/2021] [Revised: 12/19/2021] [Accepted: 01/10/2022] [Indexed: 11/13/2022] Open
Abstract
Multiple sclerosis (MS) is a complex and demyelinating disease of the central nervous system. One of the challenges of the post-GWAS era is to understand the molecular basis of statistical associations to reveal gene networks and potential therapeutic targets. The L3MBTL3 locus has been associated with MS risk by GWAS. To identify the causal variant of the locus, we performed fine mapping in a cohort of 3440 MS patients and 1688 healthy controls. The variant that best explained the association was rs6569648 (P = 4.13E-10, OR = 0.71, 95% CI = 0.64-0.79), which tagged rs7740107, located in intron 7 of L3MBTL3. The rs7740107 (A/T) variant has been reported to be the best expression and splice quantitative trait locus (eQTL and sQTL) of the region in up to 35 human GTEx tissues. By sequencing RNA from blood of 17 MS patients and quantification by digital qPCR, we determined that this eQTL/sQTL originated from the expression of a novel short transcript starting in intron 7 near rs7740107. The short transcript was translated into three proteins starting at different translation initiation codons. These N-terminal truncated proteins lacked the region where L3MBTL3 interacts with the transcriptional regulator RBPJ (Recombination Signal Binding Protein for Immunoglobulin Kappa J Region) which, in turn, regulates the Notch signaling pathway. Our data and other functional studies suggest that the genetic mechanism underlying the MS association of rs7740107 affects not only the expression of L3MBTL3 isoforms, but might also involve the Notch signaling pathway.
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Affiliation(s)
- Antonio Alcina
- Department of Cell Biology and Immunology, Instituto de Parasitología y Biomedicina "López Neyra", Consejo Superior de Investigaciones Científicas (IPBLN-CSIC) 18016 Granada, Spain
| | - Maria Fedetz
- Department of Cell Biology and Immunology, Instituto de Parasitología y Biomedicina "López Neyra", Consejo Superior de Investigaciones Científicas (IPBLN-CSIC) 18016 Granada, Spain
| | - Isabel Vidal-Cobo
- Department of Cell Biology and Immunology, Instituto de Parasitología y Biomedicina "López Neyra", Consejo Superior de Investigaciones Científicas (IPBLN-CSIC) 18016 Granada, Spain
| | - Eduardo Andrés-León
- Bioinformatic Unit, Instituto de Parasitología y Biomedicina López Neyra (IPBLN-CSIC), Granada, Spain
| | - Maria-Isabel García-Sánchez
- UGC Neurología. Nodo Hospital Universitario Virgen Macarena, Biobanco del Sistema Sanitario Público de Andalucía, Sevilla, (Spain)
| | - Alicia Barroso-Del-Jesus
- Genomics Unit, Instituto de Parasitología y Biomedicina López Neyra (IPBLN-CSIC), Granada, Spain
| | - Sara Eichau
- UGC Neurología. Hospital Universitario Virgen Macarena, Sevilla, Spain
| | - Elia Gil-Varea
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat). Institut de Recerca Vall d'Hebron (VHIR). Hospital Universitari Vall d'Hebron. Universitat Autònoma de Barcelona, 08035 Barcelona, Spain
| | - Luisa-Maria Villar
- Departments of Immunology, Hospital Ramon y Cajal, (IRYCIS), Madrid, Spain
| | - Albert Saiz
- Servicio de Neurología, Hospital Clinic and Institut d'Investigació Biomèdica Pi i Sunyer (IDIBAPS), Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain
| | - Laura Leyva
- Instituto de Investigación Biomédica de Málaga-IBIMA, UGC Neurología, Hospital Regional Universitario de Málaga, 29010 Málaga, Spain
| | - Koen Vandenbroeck
- Inflammation & Biomarkers Group, Biocruces Bizkaia Health Research Institute, 48903 Barakaldo, Spain.,IKERBASQUE, Basque Foundation for Science, 48013 Bilbao, Spain
| | - David Otaegui
- Neurosciences Area, Biodonostia Health Research Institute, 20014 San Sebastián, Spain
| | - Guillermo Izquierdo
- Multiple Sclerosis Unit, Neurology Service, Vithas Nisa Hospital, 41950 Seville, Spain
| | - Manuel Comabella
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat). Institut de Recerca Vall d'Hebron (VHIR). Hospital Universitari Vall d'Hebron. Universitat Autònoma de Barcelona, 08035 Barcelona, Spain
| | - Elena Urcelay
- Lab. of Genetics of Complex Diseases, Hospital Clinico San Carlos, Instituto de Investigacion Sanitaria San Carlos (IdISSC), 28040 Madrid, Spain
| | - Fuencisla Matesanz
- Department of Cell Biology and Immunology, Instituto de Parasitología y Biomedicina "López Neyra", Consejo Superior de Investigaciones Científicas (IPBLN-CSIC) 18016 Granada, Spain
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367
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Martin S, Tyrrell J, Thomas EL, Bown MJ, Wood AR, Beaumont RN, Tsoi LC, Stuart PE, Elder JT, Law P, Houlston R, Kabrhel C, Papadimitriou N, Gunter MJ, Bull CJ, Bell JA, Vincent EE, Sattar N, Dunlop MG, Tomlinson IPM, Lindström S, INVENT consortium , Bell JD, Frayling TM, Yaghootkar H. Disease consequences of higher adiposity uncoupled from its adverse metabolic effects using Mendelian randomisation. eLife 2022; 11:e72452. [PMID: 35074047 PMCID: PMC8789289 DOI: 10.7554/elife.72452] [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: 07/23/2021] [Accepted: 12/21/2021] [Indexed: 12/13/2022] Open
Abstract
Background Some individuals living with obesity may be relatively metabolically healthy, whilst others suffer from multiple conditions that may be linked to adverse metabolic effects or other factors. The extent to which the adverse metabolic component of obesity contributes to disease compared to the non-metabolic components is often uncertain. We aimed to use Mendelian randomisation (MR) and specific genetic variants to separately test the causal roles of higher adiposity with and without its adverse metabolic effects on diseases. Methods We selected 37 chronic diseases associated with obesity and genetic variants associated with different aspects of excess weight. These genetic variants included those associated with metabolically 'favourable adiposity' (FA) and 'unfavourable adiposity' (UFA) that are both associated with higher adiposity but with opposite effects on metabolic risk. We used these variants and two sample MR to test the effects on the chronic diseases. Results MR identified two sets of diseases. First, 11 conditions where the metabolic effect of higher adiposity is the likely primary cause of the disease. Here, MR with the FA and UFA genetics showed opposing effects on risk of disease: coronary artery disease, peripheral artery disease, hypertension, stroke, type 2 diabetes, polycystic ovary syndrome, heart failure, atrial fibrillation, chronic kidney disease, renal cancer, and gout. Second, 9 conditions where the non-metabolic effects of excess weight (e.g. mechanical effect) are likely a cause. Here, MR with the FA genetics, despite leading to lower metabolic risk, and MR with the UFA genetics, both indicated higher disease risk: osteoarthritis, rheumatoid arthritis, osteoporosis, gastro-oesophageal reflux disease, gallstones, adult-onset asthma, psoriasis, deep vein thrombosis, and venous thromboembolism. Conclusions Our results assist in understanding the consequences of higher adiposity uncoupled from its adverse metabolic effects, including the risks to individuals with high body mass index who may be relatively metabolically healthy. Funding Diabetes UK, UK Medical Research Council, World Cancer Research Fund, National Cancer Institute.
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Affiliation(s)
- Susan Martin
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter HospitalExeterUnited Kingdom
| | - Jessica Tyrrell
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter HospitalExeterUnited Kingdom
| | - E Louise Thomas
- Research Centre for Optimal Health, School of Life Sciences, University of WestminsterLondonUnited Kingdom
| | - Matthew J Bown
- Department of Cardiovascular Sciences, University of LeicesterLeicesterUnited Kingdom
- NIHR Leicester Biomedical Research CentreLeicesterUnited Kingdom
| | - Andrew R Wood
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter HospitalExeterUnited Kingdom
| | - Robin N Beaumont
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter HospitalExeterUnited Kingdom
| | - Lam C Tsoi
- Department of Dermatology, University of MichiganAnn ArborUnited States
| | - Philip E Stuart
- Department of Dermatology, University of MichiganAnn ArborUnited States
| | - James T Elder
- Department of Dermatology, University of MichiganAnn ArborUnited States
- Ann Arbor Veterans Affairs HospitalAnn ArborUnited States
| | - Philip Law
- The Institute of Cancer ResearchLondonUnited Kingdom
| | | | - Christopher Kabrhel
- Department of Emergency Medicine, Massachusetts General HospitalBostonUnited States
- Department of Emergency Medicine, Harvard Medical SchoolBostonUnited States
| | - Nikos Papadimitriou
- Nutrition and Metabolism Branch, International Agency for Research on CancerLyonFrance
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research on CancerLyonFrance
| | - Caroline J Bull
- MRC Integrative Epidemiology Unit at the University of BristolBristolUnited Kingdom
- Population Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
- School of Cellular and Molecular Medicine, University of BristolBristolUnited Kingdom
| | - Joshua A Bell
- MRC Integrative Epidemiology Unit at the University of BristolBristolUnited Kingdom
- Population Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
| | - Emma E Vincent
- MRC Integrative Epidemiology Unit at the University of BristolBristolUnited Kingdom
- Population Health Sciences, Bristol Medical School, University of BristolBristolUnited Kingdom
- School of Cellular and Molecular Medicine, University of BristolBristolUnited Kingdom
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of GlasgowGlasgowUnited Kingdom
| | - Malcolm G Dunlop
- University of EdinburghEdinburghUnited Kingdom
- Western General HospitalEdinburghUnited Kingdom
| | - Ian PM Tomlinson
- Edinburgh Cancer Research Centre, IGMM, University of EdinburghEdinburghUnited Kingdom
| | - Sara Lindström
- Department of Epidemiology, University of WashingtonSeattleUnited States
- Division of Public Health Sciences, Fred Hutchinson Cancer Research CenterSeattleUnited States
| | | | - Jimmy D Bell
- Research Centre for Optimal Health, School of Life Sciences, University of WestminsterLondonUnited Kingdom
| | - Timothy M Frayling
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter HospitalExeterUnited Kingdom
| | - Hanieh Yaghootkar
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Learning and Development building, Royal Devon & Exeter HospitalExeterUnited Kingdom
- Research Centre for Optimal Health, School of Life Sciences, University of WestminsterLondonUnited Kingdom
- Centre for Inflammation Research and Translational Medicine (CIRTM), Department of Life Sciences, Brunel University LondonUxbridgeUnited Kingdom
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368
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Defective Cystinosin, Aberrant Autophagy−Endolysosome Pathways, and Storage Disease: Towards Assembling the Puzzle. Cells 2022; 11:cells11030326. [PMID: 35159136 PMCID: PMC8834619 DOI: 10.3390/cells11030326] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/03/2022] [Accepted: 01/11/2022] [Indexed: 02/05/2023] Open
Abstract
Epithelial cells that form the kidney proximal tubule (PT) rely on an intertwined ecosystem of vesicular membrane trafficking pathways to ensure the reabsorption of essential nutrients—a key requisite for homeostasis. The endolysosome stands at the crossroads of this sophisticated network, internalizing molecules through endocytosis, sorting receptors and nutrient transporters, maintaining cellular quality control via autophagy, and toggling the balance between PT differentiation and cell proliferation. Dysregulation of such endolysosome-guided trafficking pathways might thus lead to a generalized dysfunction of PT cells, often causing chronic kidney disease and life-threatening complications. In this review, we highlight the biological functions of endolysosome-residing proteins from the perspectives of understanding—and potentially reversing—the pathophysiology of rare inherited diseases affecting the kidney PT. Using cystinosis as a paradigm of endolysosome disease causing PT dysfunction, we discuss how the endolysosome governs the homeostasis of specialized epithelial cells. This review also provides a critical analysis of the molecular mechanisms through which defects in autophagy pathways can contribute to PT dysfunction, and proposes potential interventions for affected tissues. These insights might ultimately accelerate the discovery and development of new therapeutics, not only for cystinosis, but also for other currently intractable endolysosome-related diseases, eventually transforming our ability to regulate homeostasis and health.
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369
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Kuo FC, Chao CT, Lin SH. The Dynamics and Plasticity of Epigenetics in Diabetic Kidney Disease: Therapeutic Applications Vis-à-Vis. Int J Mol Sci 2022; 23:ijms23020843. [PMID: 35055027 PMCID: PMC8777872 DOI: 10.3390/ijms23020843] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/11/2022] [Accepted: 01/11/2022] [Indexed: 02/01/2023] Open
Abstract
Chronic kidney disease (CKD) refers to the phenomenon of progressive decline in the glomerular filtration rate accompanied by adverse consequences, including fluid retention, electrolyte imbalance, and an increased cardiovascular risk compared to those with normal renal function. The triggers for the irreversible renal function deterioration are multifactorial, and diabetes mellitus serves as a major contributor to the development of CKD, namely diabetic kidney disease (DKD). Recently, epigenetic dysregulation emerged as a pivotal player steering the progression of DKD, partly resulting from hyperglycemia-associated metabolic disturbances, rising oxidative stress, and/or uncontrolled inflammation. In this review, we describe the major epigenetic molecular mechanisms, followed by summarizing current understandings of the epigenetic alterations pertaining to DKD. We highlight the epigenetic regulatory processes involved in several crucial renal cell types: Mesangial cells, podocytes, tubular epithelia, and glomerular endothelial cells. Finally, we highlight epigenetic biomarkers and related therapeutic candidates that hold promising potential for the early detection of DKD and the amelioration of its progression.
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Affiliation(s)
- Feng-Chih Kuo
- National Defense Medical Center, Department of Internal Medicine, Division of Endocrinology and Metabolism, Tri-Service General Hospital, Taipei 114, Taiwan
| | - Chia-Ter Chao
- Department of Internal Medicine, Nephrology Division, National Taiwan University Hospital, Taipei 100, Taiwan
- Graduate Institute of Toxicology, National Taiwan University College of Medicine, Taipei 100, Taiwan
- Department of Internal Medicine, Nephrology Division, National Taiwan University College of Medicine, Taipei 100, Taiwan
| | - Shih-Hua Lin
- National Defense Medical Center, Graduate Institute of Medical Sciences, Taipei 114, Taiwan
- National Defense Medical Center, Department of Internal Medicine, Nephrology Division, Taipei 114, Taiwan
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370
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Olinger E, Wilson I, Devuyst O, Sayer JA. Translational Science Kidney traits on repeat - the role of MUC1 VNTR. Kidney Int 2022; 101:863-866. [PMID: 35031326 DOI: 10.1016/j.kint.2021.12.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 12/30/2021] [Indexed: 10/19/2022]
Affiliation(s)
- Eric Olinger
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Central Parkway, Newcastle upon Tyne, UK
| | - Ian Wilson
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Central Parkway, Newcastle upon Tyne NE1 3BZ, UK
| | - Olivier Devuyst
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology, University of Zurich, Zürich, Switzerland
| | - John A Sayer
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Central Parkway, Newcastle upon Tyne, UK; Renal Services, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE7 7DN, UK.
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371
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Yan Z, Wang G, Shi X. Advances in the Progression and Prognosis Biomarkers of Chronic Kidney Disease. Front Pharmacol 2022; 12:785375. [PMID: 34992536 PMCID: PMC8724575 DOI: 10.3389/fphar.2021.785375] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 11/30/2021] [Indexed: 12/29/2022] Open
Abstract
Chronic kidney disease (CKD) is one of the increasingly serious public health concerns worldwide; the global burden of CKD is increasingly due to high morbidity and mortality. At present, there are three key problems in the clinical treatment and management of CKD. First, the current diagnostic indicators, such as proteinuria and serum creatinine, are greatly interfered by the physiological conditions of patients, and the changes in the indicator level are not synchronized with renal damage. Second, the established diagnosis of suspected CKD still depends on biopsy, which is not suitable for contraindication patients, is also traumatic, and is not sensitive to early progression. Finally, the prognosis of CKD is affected by many factors; hence, it is ineviatble to develop effective biomarkers to predict CKD prognosis and improve the prognosis through early intervention. Accurate progression monitoring and prognosis improvement of CKD are extremely significant for improving the clinical treatment and management of CKD and reducing the social burden. Therefore, biomarkers reported in recent years, which could play important roles in accurate progression monitoring and prognosis improvement of CKD, were concluded and highlighted in this review article that aims to provide a reference for both the construction of CKD precision therapy system and the pharmaceutical research and development.
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Affiliation(s)
- Zhonghong Yan
- Heilongjiang University of Chinese Medicine, Harbin, China
| | - Guanran Wang
- Heilongjiang University of Chinese Medicine, Harbin, China.,Department of Nephrology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Xingyang Shi
- Heilongjiang University of Chinese Medicine, Harbin, China
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372
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Zheng J, Zhang Y, Rasheed H, Walker V, Sugawara Y, Li J, Leng Y, Elsworth B, Wootton RE, Fang S, Yang Q, Burgess S, Haycock PC, Borges MC, Cho Y, Carnegie R, Howell A, Robinson J, Thomas LF, Brumpton BM, Hveem K, Hallan S, Franceschini N, Morris AP, Köttgen A, Pattaro C, Wuttke M, Yamamoto M, Kashihara N, Akiyama M, Kanai M, Matsuda K, Kamatani Y, Okada Y, Walters R, Millwood IY, Chen Z, Davey Smith G, Barbour S, Yu C, Åsvold BO, Zhang H, Gaunt TR. Trans-ethnic Mendelian-randomization study reveals causal relationships between cardiometabolic factors and chronic kidney disease. Int J Epidemiol 2022; 50:1995-2010. [PMID: 34999880 PMCID: PMC8743120 DOI: 10.1093/ije/dyab203] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Accepted: 09/01/2021] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND This study was to systematically test whether previously reported risk factors for chronic kidney disease (CKD) are causally related to CKD in European and East Asian ancestries using Mendelian randomization. METHODS A total of 45 risk factors with genetic data in European ancestry and 17 risk factors in East Asian participants were identified as exposures from PubMed. We defined the CKD by clinical diagnosis or by estimated glomerular filtration rate of <60 ml/min/1.73 m2. Ultimately, 51 672 CKD cases and 958 102 controls of European ancestry from CKDGen, UK Biobank and HUNT, and 13 093 CKD cases and 238 118 controls of East Asian ancestry from Biobank Japan, China Kadoorie Biobank and Japan-Kidney-Biobank/ToMMo were included. RESULTS Eight risk factors showed reliable evidence of causal effects on CKD in Europeans, including genetically predicted body mass index (BMI), hypertension, systolic blood pressure, high-density lipoprotein cholesterol, apolipoprotein A-I, lipoprotein(a), type 2 diabetes (T2D) and nephrolithiasis. In East Asians, BMI, T2D and nephrolithiasis showed evidence of causality on CKD. In two independent replication analyses, we observed that increased hypertension risk showed reliable evidence of a causal effect on increasing CKD risk in Europeans but in contrast showed a null effect in East Asians. Although liability to T2D showed consistent effects on CKD, the effects of glycaemic phenotypes on CKD were weak. Non-linear Mendelian randomization indicated a threshold relationship between genetically predicted BMI and CKD, with increased risk at BMI of >25 kg/m2. CONCLUSIONS Eight cardiometabolic risk factors showed causal effects on CKD in Europeans and three of them showed causality in East Asians, providing insights into the design of future interventions to reduce the burden of CKD.
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Affiliation(s)
- Jie Zheng
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Yuemiao Zhang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Key Laboratory of Renal Disease, Ministry of Health of China, Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, P. R. China
| | - Humaira Rasheed
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Venexia Walker
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yuka Sugawara
- Division of Nephrology and Endocrinology, The University of Tokyo Hospital, Tokyo, Japan
| | - Jiachen Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, P. R. China
| | - Yue Leng
- Department of Psychiatry, University of California, San Francisco, CA, USA
| | - Benjamin Elsworth
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Robyn E Wootton
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Si Fang
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Qian Yang
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Philip C Haycock
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Yoonsu Cho
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Rebecca Carnegie
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Amy Howell
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Jamie Robinson
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Laurent F Thomas
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Ben Michael Brumpton
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Thoracic Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - 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
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Andrew P Morris
- Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, 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
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center–University of Freiburg, Freiburg, Germany
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization and Tohoku University Graduate School of Medicine, Tohoku University, Sendai, Miyagi, Japan
| | - Naoki Kashihara
- Department of Nephrology and Hypertension, Kawasaki Medical School, Kurashiki, Okayama, Japan
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Masahiro Kanai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, the University of Tokyo, Tokyo, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, 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
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
| | - Robin Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, UK
| | - Sean Barbour
- Division of Nephrology, University of British Columbia, Vancouver, British Columbia, Canada
- British Columbia Provincial Renal Agency, Vancouver, British Columbia, Canada
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, P. R. China
| | - Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Hong Zhang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Key Laboratory of Renal Disease, Ministry of Health of China, Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, P. R. China
| | - Tom R Gaunt
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, UK
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Galuška D, Dlouhá L, Hubáček JA, Kaňová K. Genetics of T2DM and Its Chronic Complications: Are We Any Closer to the Individual Prediction of Genetic Risk? Folia Biol (Praha) 2022; 68:159-179. [PMID: 37256551 DOI: 10.14712/fb2022068050159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2024]
Abstract
Type 2 diabetes mellitus (T2DM) is a complex disease that has risen in global prevalence over recent decades, resulting in concomitant and enormous socio-economic impacts. In addition to the well-documented risk factors of obesity, poor dietary habits and sedentary lifestyles, genetic background plays a key role in the aetiopathogenesis of diabetes and the development of associated micro- and macrovascular complications. Recent advances in genomic research, notably next-generation sequencing and genome- wide association studies, have greatly improved the efficiency with which genetic backgrounds to complex diseases are analysed. To date, several hundred single-nucleotide polymorphisms have been associated with T2DM or its complications. Given the polygenic background to T2DM (and numerous other complex diseases), the degree of genetic predisposition can be treated as a "continuous trait" quantified by a genetic risk score. Focusing mainly on the Central European population, this review summarizes recent state-of-the-art methods that have enabled us to better determine the genetic architecture of T2DM and the utility of genetic risk scores in disease prediction.
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Affiliation(s)
- D Galuška
- Department of Pathophysiology, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - L Dlouhá
- Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Prague, Czech Republic
| | - J A Hubáček
- Experimental Medicine Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
- 3rd Department of Medicine - Department of Endocrinology and Metabolism, First Faculty of Medicine, Charles University and General University Hospital in Prague, Czech Republic
| | - K Kaňová
- Department of Pathophysiology, Faculty of Medicine, Masaryk University, Brno, Czech Republic
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374
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Sagmeister MS, Harper L, Hardy RS. Cortisol excess in chronic kidney disease - A review of changes and impact on mortality. Front Endocrinol (Lausanne) 2022; 13:1075809. [PMID: 36733794 PMCID: PMC9886668 DOI: 10.3389/fendo.2022.1075809] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 12/27/2022] [Indexed: 01/18/2023] Open
Abstract
Chronic kidney disease (CKD) describes the long-term condition of impaired kidney function from any cause. CKD is common and associated with a wide array of complications including higher mortality, cardiovascular disease, hypertension, insulin resistance, dyslipidemia, sarcopenia, osteoporosis, aberrant immune function, cognitive impairment, mood disturbances and poor sleep quality. Glucocorticoids are endogenous pleiotropic steroid hormones and their excess produces a pattern of morbidity that possesses considerable overlap with CKD. Circulating levels of cortisol, the major active glucocorticoid in humans, are determined by a complex interplay between several processes. The hypothalamic-pituitary-adrenal axis (HPA) regulates cortisol synthesis and release, 11β-hydroxysteroid dehydrogenase enzymes mediate metabolic interconversion between active and inactive forms, and clearance from the circulation depends on irreversible metabolic inactivation in the liver followed by urinary excretion. Chronic stress, inflammatory states and other aspects of CKD can disturb these processes, enhancing cortisol secretion via the HPA axis and inducing tissue-resident amplification of glucocorticoid signals. Progressive renal impairment can further impact on cortisol metabolism and urinary clearance of cortisol metabolites. Consequently, significant interest exists to precisely understand the dysregulation of cortisol in CKD and its significance for adverse clinical outcomes. In this review, we summarize the latest literature on alterations in endogenous glucocorticoid regulation in adults with CKD and evaluate the available evidence on cortisol as a mechanistic driver of excess mortality and morbidity. The emerging picture is one of subclinical hypercortisolism with blunted diurnal decline of cortisol levels, impaired negative feedback regulation and reduced cortisol clearance. An association between cortisol and adjusted all-cause mortality has been reported in observational studies for patients with end-stage renal failure, but further research is required to assess links between cortisol and clinical outcomes in CKD. We propose recommendations for future research, including therapeutic strategies that aim to reduce complications of CKD by correcting or reversing dysregulation of cortisol.
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Affiliation(s)
- Michael S. Sagmeister
- Institute for Metabolism and Systems Research, University of Birmingham, Birmingham, United Kingdom
- Renal Medicine, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
- *Correspondence: Michael S. Sagmeister,
| | - Lorraine Harper
- Renal Medicine, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
- Institute for Applied Health Research, University of Birmingham, Birmingham, United Kingdom
| | - Rowan S. Hardy
- Institute for Metabolism and Systems Research, University of Birmingham, Birmingham, United Kingdom
- Research into Inflammatory Arthritis Centre Versus Arthritis, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, United Kingdom
- Institute of Clinical Science, University of Birmingham, Birmingham, United Kingdom
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Zhang Y, Xiong Y, Shen S, Yang J, Wang W, Wu T, Chen L, Yu Q, Zuo H, Wang X, Lei X. Causal Association Between Tea Consumption and Kidney Function: A Mendelian Randomization Study. Front Nutr 2022; 9:801591. [PMID: 35425787 PMCID: PMC9002236 DOI: 10.3389/fnut.2022.801591] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 02/07/2022] [Indexed: 12/23/2022] Open
Abstract
Background Causal research concerning the consumption of tea and the risk of chronic kidney disease (CKD) is limited. This study identified the potential causal effects of tea intake on CKD, the estimated glomerular filtration rate (eGFR), and albuminuria. Methods Genome-wide association studies (GWASs) from UK Biobank were able to identify single-nucleotide polymorphisms (SNPs) associated with an extra cup of tea each day. The summary statistics for the kidney function from the CKDGen consortium include 11,765 participants (12,385 cases of CKD) and 54,116 participants for the urinary albumin-to-creatinine ratio who were mostly of European descent. A two-sample Mendelian randomization (MR) analysis was performed to test the relationship between the selected SNPs and the risk of CKD. Results A total of 2,672 SNPs associated with tea consumption (p < 5 × 10-8) were found, 45 of which were independent and usable in CKDGen. Drinking more cups of tea per day indicates a protective effect for CKD G3-G5 [odds ratio (OR) = 0.803; p = 0.004] and increases eGFR (β = 0.019 log ml/min/1.73 m2 per cup per day; p = 2.21 × 10-5). Excluding two SNPs responsible for directional heterogeneity (Cochran Q p = 0.02), a high consumption of tea was also negatively correlated with a lower risk of albuminuria (OR = 0.758; p = 0.002). Conclusion From the perspective of genes, causal relationships exist between daily extra cup of tea and the reduced risk of CKD and albuminuria and increased eGFR.
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Affiliation(s)
- Yangchang Zhang
- School of Public Health and Management, Chongqing Medical University, Chongqing, China.,Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing, China.,The Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, China.,Research Center for Public Health Security, Chongqing Medical University, Chongqing, China
| | - Yang Xiong
- The West China Hospital, Sichuan University, Chengdu, China
| | - Shisi Shen
- The First School of Clinical Medicine, Chongqing Medical University, Chongqing, China
| | - Jialu Yang
- School of Public Health and Management, Chongqing Medical University, Chongqing, China.,Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing, China.,The Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, China
| | - Wei Wang
- School of Public Health and Management, Chongqing Medical University, Chongqing, China.,Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing, China.,The Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, China
| | - Tingting Wu
- Chongqing Collaborative Innovation Center for Functional Food, Chongqing University of Education, Chongqing, China
| | - Li Chen
- School of Public Health & Institute of Child and Adolescent Health, Peking University, Beijing, China
| | - Qiuhua Yu
- Department of Critical Care Medicine, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
| | - Hangjia Zuo
- The First School of Clinical Medicine, Chongqing Medical University, Chongqing, China
| | - Xu Wang
- School of Public Health and Management, Chongqing Medical University, Chongqing, China.,Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing, China.,The Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, China
| | - Xun Lei
- School of Public Health and Management, Chongqing Medical University, Chongqing, China.,Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing, China.,The Innovation Center for Social Risk Governance in Health, Chongqing Medical University, Chongqing, China.,Research Center for Public Health Security, Chongqing Medical University, Chongqing, China
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376
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Horimoto AR, Xue D, Cai J, Lash JP, Daviglus ML, Franceschini N, Thornton TA. Genome-Wide Admixture Mapping of Estimated Glomerular Filtration Rate and Chronic Kidney Disease Identifies European and African Ancestry-of-Origin Loci in Hispanic and Latino Individuals in the United States. J Am Soc Nephrol 2022; 33:77-87. [PMID: 34670813 PMCID: PMC8763178 DOI: 10.1681/asn.2021050617] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 09/08/2021] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Admixture mapping is a powerful approach for gene mapping of complex traits that leverages the diverse genetic ancestry in populations with recent admixture, such as Hispanic or Latino individuals in the United States. These individuals have an increased risk of CKD. METHODS We performed genome-wide admixture mapping for both CKD and eGFR in a sample of 12,601 participants from the Hispanic Community Health Study/Study of Latinos, with validation in a sample of 8191 Black participants from the Women's Health Initiative (WHI). We also compared the findings with those from a conventional genome-wide association study. RESULTS Three novel ancestry-of-origin loci were identified on chromosomes 2, 14, and 15 for CKD and eGFR. The chromosome 2 locus comprises two European ancestry regions encompassing the FSHR and NRXN1 genes, with European ancestry at this locus associated with increased CKD risk. The chromosome 14 locus, found within the DLK1-DIO3 imprinted domain, was associated with lower eGFR and driven by European ancestry. The eGFR-associated locus on chromosome 15 included intronic variants of RYR3 and was within an African-specific genomic region associated with higher eGFR. The genome-wide association study failed to identify significant associations in these regions. We validated the chromosome 14 and 15 loci associated with eGFR in the WHI Black participants. CONCLUSIONS This study provides evidence of shared ancestry-specific genomic regions influencing eGFR in Hispanic or Latino individuals and Black individuals and illustrates the potential for leveraging genetic ancestry in recently admixed populations for the discovery of novel candidate loci for kidney phenotypes.
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Affiliation(s)
| | - Diane Xue
- Institute for Public Health Genetics, University of Washington, Seattle, Washington
| | - Jianwen Cai
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina
| | - James P. Lash
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - Martha L. Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, Illinois
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina
| | - Timothy A. Thornton
- Department of Biostatistics, University of Washington, Seattle, Washington
- Department of Statistics, University of Washington, Seattle, Washington
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377
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Drake I, Fryk E, Strindberg L, Lundqvist A, Rosengren AH, Groop L, Ahlqvist E, Borén J, Orho-Melander M, Jansson PA. The role of circulating galectin-1 in type 2 diabetes and chronic kidney disease: evidence from cross-sectional, longitudinal and Mendelian randomisation analyses. Diabetologia 2022; 65:128-139. [PMID: 34743218 PMCID: PMC8660752 DOI: 10.1007/s00125-021-05594-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 08/05/2021] [Indexed: 11/11/2022]
Abstract
AIMS/HYPOTHESIS Galectin-1 modulates inflammation and angiogenesis, and cross-sectional studies indicate that galectin-1 may be a uniting factor between obesity, type 2 diabetes and kidney function. We examined whether circulating galectin-1 can predict incidence of chronic kidney disease (CKD) and type 2 diabetes in a middle-aged population, and if Mendelian randomisation (MR) can provide evidence for causal direction of effects. METHODS Participants (n = 4022; 58.6% women) in the Malmö Diet and Cancer Study-Cardiovascular Cohort enrolled between 1991 and 1994 (mean age 57.6 years) were examined. eGFR was calculated at baseline and after a mean follow-up of 16.6 ± 1.5 years. Diabetes status was ascertained through registry linkage (mean follow-up of 18.4 ± 6.1 years). The associations of baseline galectin-1 with incident CKD and type 2 diabetes were assessed with Cox regression, adjusting for established risk factors. In addition, a genome-wide association study on galectin-1 was performed to identify genetic instruments for two-sample MR analyses utilising the genetic associations obtained from the Chronic Kidney Disease Genetics (CKDGen) Consortium (41,395 cases and 439,303 controls) and the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium (74,124 cases and 824,006 controls). One genome-wide significant locus in the galectin-1 gene region was identified (sentinel SNP rs7285699; p = 2.4 × 10-11). The association between galectin-1 and eGFR was also examined in individuals with newly diagnosed diabetes from the All New Diabetics In Scania (ANDIS) cohort. RESULTS Galectin-1 was strongly associated with lower eGFR at baseline (p = 2.3 × 10-89) but not with incident CKD. However, galectin-1 was associated with increased risk of type 2 diabetes (per SD increase, HR 1.12; 95% CI 1.02, 1.24). Two-sample MR analyses could not ascertain a causal effect of galectin-1 on CKD (OR 0.92; 95% CI 0.82, 1.02) or type 2 diabetes (OR 1.05; 95% CI 0.98, 1.14) in a general population. However, in individuals with type 2 diabetes from ANDIS who belonged to the severe insulin-resistant diabetes subgroup and were at high risk of diabetic nephropathy, genetically elevated galectin-1 was significantly associated with higher eGFR (p = 5.7 × 10-3). CONCLUSIONS/INTERPRETATION Galectin-1 is strongly associated with lower kidney function in cross-sectional analyses, and two-sample MR analyses suggest a causal protective effect on kidney function among individuals with type 2 diabetes at high risk of diabetic nephropathy. Future studies are needed to explore the mechanisms by which galectin-1 affects kidney function and whether it could be a useful target among individuals with type 2 diabetes for renal improvement.
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Affiliation(s)
- Isabel Drake
- Department of Clinical Sciences in Malmö, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Emanuel Fryk
- Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Lena Strindberg
- Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Annika Lundqvist
- Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anders H Rosengren
- Department of Clinical Sciences in Malmö, Lund University Diabetes Centre, Lund University, Malmö, Sweden
- Department of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Leif Groop
- Department of Clinical Sciences in Malmö, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Emma Ahlqvist
- Department of Clinical Sciences in Malmö, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Jan Borén
- Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Marju Orho-Melander
- Department of Clinical Sciences in Malmö, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Per-Anders Jansson
- Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
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378
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He L, Yu T, Zhang W, Wang B, Ma Y, Li S. Causal Associations of Obesity With Achilles Tendinopathy: A Two-Sample Mendelian Randomization Study. Front Endocrinol (Lausanne) 2022; 13:902142. [PMID: 35774146 PMCID: PMC9238354 DOI: 10.3389/fendo.2022.902142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 05/11/2022] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Achilles tendinopathy (AT) is associated with severe pain and is the cause of dysfunction and disability that are associated with significant reduction in social and economic benefits. Several potential risk factors have been proposed to be responsible for AT development; however, the results of observational epidemiological studies remain controversial, presumably because the designs of these studies are subject to residual confounding and reverse causality. Mendelian randomization (MR) can infer the causality between exposure and disease outcomes using genetic variants as instrumental variables, and identification of the causal risk factors for AT is beneficial for early intervention. Thus, we employed the MR strategy to evaluate the causal associations between previously reported risk factors (anthropometric parameters, lifestyle factors, blood biomarkers, and systemic diseases) and the risk of AT. METHODS Univariable MR was performed to screen for potential causal associations between the putative risk factors and AT. Bidirectional MR was used to infer reverse causality. Multivariable MR was conducted to investigate the body mass index (BMI)-independent causal effect of other obesity-related traits, such as the waist-hip ratio, on AT. RESULTS Univariable MR analyses with the inverse-variance weighted method indicated that the genetically predicted BMI was significantly associated with the risk of AT (P=2.0×10-3), and the odds ratios (95% confidence intervals) is 1.44 (1.14-1.81) per 1-SD increase in BMI. For the other tested risk factors, no causality with AT was identified using any of the MR methods. Bidirectional MR suggested that AT was not causally associated with BMI, and multivariable MR indicated that other anthropometric parameters included in this study were not likely to causally associate with the risk of AT after adjusting for BMI. CONCLUSIONS The causal association between BMI and AT risk suggests that weight control is a promising strategy for preventing AT and alleviating the corresponding disease burden.
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Affiliation(s)
- Lijuan He
- DongFang Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Tingting Yu
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
| | - Wei Zhang
- Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
| | - Baojian Wang
- Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
| | - Yufeng Ma
- Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
- *Correspondence: Sen Li, ; Yufeng Ma,
| | - Sen Li
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
- *Correspondence: Sen Li, ; Yufeng Ma,
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379
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Ghasemi S, Becker T, Grabe HJ, Teumer A. Discovery of novel eGFR-associated multiple independent signals using a quasi-adaptive method. Front Genet 2022; 13:997302. [PMID: 36386835 PMCID: PMC9660290 DOI: 10.3389/fgene.2022.997302] [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: 07/18/2022] [Accepted: 10/13/2022] [Indexed: 11/13/2022] Open
Abstract
A decreased estimated glomerular filtration rate (eGFR) leading to chronic kidney disease is a significant public health problem. Kidney function is a heritable trait, and recent application of genome-wide association studies (GWAS) successfully identified multiple eGFR-associated genetic loci. To increase statistical power for detecting independent associations in GWAS loci, we improved our recently developed quasi-adaptive method estimating SNP-specific alpha levels for the conditional analysis, and applied it to the GWAS meta-analysis results of eGFR among 783,978 European-ancestry individuals. Among known eGFR loci, we revealed 19 new independent association signals that were subsequently replicated in the United Kingdom Biobank (n = 408,608). These associations have remained undetected by conditional analysis using the established conservative genome-wide significance level of 5 × 10-8. Functional characterization of known index SNPs and novel independent signals using colocalization of conditional eGFR association results and gene expression in cis across 51 human tissues identified two potentially causal genes across kidney tissues: TSPAN33 and TFDP2, and three candidate genes across other tissues: SLC22A2, LRP2, and CDKN1C. These colocalizations were not identified in the original GWAS. By applying our improved quasi-adaptive method, we successfully identified additional genetic variants associated with eGFR. Considering these signals in colocalization analyses can increase the precision of revealing potentially functional genes of GWAS loci.
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Affiliation(s)
- Sahar Ghasemi
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.,Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.,DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Tim Becker
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.,German Center for Neurodegenerative Diseases DZNE, Site Rostock/Greifswald, Greifswald, Germany
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.,DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
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380
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OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction. Int J Mol Sci 2021; 23:ijms23010336. [PMID: 35008760 PMCID: PMC8745343 DOI: 10.3390/ijms23010336] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 12/26/2021] [Accepted: 12/27/2021] [Indexed: 12/13/2022] Open
Abstract
Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The ‘omics’ techniques, namely genomics, proteomics, metabolomics, and transcriptomics, are excellent candidates to provide a better understanding of pathophysiologic mechanisms of disease in CKD, to improve risk stratification of patients with respect to future cardiovascular events, and to identify CKD patients who are likely to respond to a treatment. Following such a strategy, a reliable risk of future events for a particular patient may be calculated and consequently the patient would also benefit from the best available treatment based on their risk profile. Moreover, a further step forward can be represented by the aggregation of multiple omics information by combining different techniques and/or different biological samples. This has already been shown to yield additional information by revealing with more accuracy the exact individual pathway of disease.
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381
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Yoshikawa M, Asaba K, Nakayama T. Causal effect of atrial fibrillation/flutter on chronic kidney disease: A bidirectional two-sample Mendelian randomization study. PLoS One 2021; 16:e0261020. [PMID: 34898631 PMCID: PMC8668124 DOI: 10.1371/journal.pone.0261020] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Accepted: 11/22/2021] [Indexed: 11/21/2022] Open
Abstract
Chronic kidney disease (CKD) and atrial fibrillation are both major burdens on the health care system worldwide. Several observational studies have reported clinical associations between CKD and atrial fibrillation; however, causal relationships between these conditions remain to be elucidated due to possible bias by confounders and reverse causations. Here, we conducted bidirectional two-sample Mendelian randomization analyses using publicly available summary statistics of genome-wide association studies (the CKDGen consortium and the UK Biobank) to investigate causal associations between CKD and atrial fibrillation/flutter in the European population. Our study suggested a causal effect of the risk of atrial fibrillation/flutter on the decrease in serum creatinine-based estimated glomerular filtration rate (eGFR) and revealed a causal effect of the risk of atrial fibrillation/flutter on the risk of CKD (odds ratio, 9.39 per doubling odds ratio of atrial fibrillation/flutter; 95% coefficient interval, 2.39–37.0; P = 0.001), while the causal effect of the decrease in eGFR on the risk of atrial fibrillation/flutter was unlikely. However, careful interpretation and further studies are warranted, as the underlying mechanisms remain unknown. Further, our sample size was relatively small and selection bias was possible.
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Affiliation(s)
- Masahiro Yoshikawa
- Division of Laboratory Medicine, Department of Pathology and Microbiology, Nihon University School of Medicine, Tokyo, Japan
- * E-mail:
| | - Kensuke Asaba
- Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo Hospital, Tokyo, Japan
| | - Tomohiro Nakayama
- Division of Laboratory Medicine, Department of Pathology and Microbiology, Nihon University School of Medicine, Tokyo, Japan
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382
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Marini S, Georgakis MK, Anderson CD. Interactions Between Kidney Function and Cerebrovascular Disease: Vessel Pathology That Fires Together Wires Together. Front Neurol 2021; 12:785273. [PMID: 34899586 PMCID: PMC8652045 DOI: 10.3389/fneur.2021.785273] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 10/26/2021] [Indexed: 12/15/2022] Open
Abstract
The kidney and the brain, as high-flow end organs relying on autoregulatory mechanisms, have unique anatomic and physiological hemodynamic properties. Similarly, the two organs share a common pattern of microvascular dysfunction as a result of aging and exposure to vascular risk factors (e.g., hypertension, diabetes and smoking) and therefore progress in parallel into a systemic condition known as small vessel disease (SVD). Many epidemiological studies have shown that even mild renal dysfunction is robustly associated with acute and chronic forms of cerebrovascular disease. Beyond ischemic SVD, kidney impairment increases the risk of acute cerebrovascular events related to different underlying pathologies, notably large artery stroke and intracerebral hemorrhage. Other chronic cerebral manifestations of SVD are variably associated with kidney disease. Observational data have suggested the hypothesis that kidney function influences cerebrovascular disease independently and adjunctively to the effect of known vascular risk factors, which affect both renal and cerebral microvasculature. In addition to confirming this independent association, recent large-scale human genetic studies have contributed to disentangling potentially causal associations from shared genetic predisposition and resolving the uncertainty around the direction of causality between kidney and cerebrovascular disease. Accelerated atherosclerosis, impaired cerebral autoregulation, remodeling of the cerebral vasculature, chronic inflammation and endothelial dysfunction can be proposed to explain the additive mechanisms through which renal dysfunction leads to cerebral SVD and other cerebrovascular events. Genetic epidemiology also can help identify new pathological pathways which wire kidney dysfunction and cerebral vascular pathology together. The need for identifying additional pathological mechanisms underlying kidney and cerebrovascular disease is attested to by the limited effect of current therapeutic options in preventing cerebrovascular disease in patients with kidney impairment.
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Affiliation(s)
- Sandro Marini
- Department of Neurology, Boston Medical Center, Boston University School of Medicine, Boston, MA, United States
| | - Marios K Georgakis
- Institute for Stroke and Dementia Research, University Hospital of LMU Munich, Munich, Germany.,McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, United States.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, United States
| | - Christopher D Anderson
- McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, United States.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, United States.,Department of Neurology, Brigham and Women's Hospital, Boston, MA, United States
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383
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Schlosser P, Tin A, Matias-Garcia PR, Thio CHL, Joehanes R, Liu H, Weihs A, Yu Z, Hoppmann A, Grundner-Culemann F, Min JL, Adeyemo AA, Agyemang C, Ärnlöv J, Aziz NA, Baccarelli A, Bochud M, Brenner H, Breteler MMB, Carmeli C, Chaker L, Chambers JC, Cole SA, Coresh J, Corre T, Correa A, Cox SR, de Klein N, Delgado GE, Domingo-Relloso A, Eckardt KU, Ekici AB, Endlich K, Evans KL, Floyd JS, Fornage M, Franke L, Fraszczyk E, Gao X, Gào X, Ghanbari M, Ghasemi S, Gieger C, Greenland P, Grove ML, Harris SE, Hemani G, Henneman P, Herder C, Horvath S, Hou L, Hurme MA, Hwang SJ, Jarvelin MR, Kardia SLR, Kasela S, Kleber ME, Koenig W, Kooner JS, Kramer H, Kronenberg F, Kühnel B, Lehtimäki T, Lind L, Liu D, Liu Y, Lloyd-Jones DM, Lohman K, Lorkowski S, Lu AT, Marioni RE, März W, McCartney DL, Meeks KAC, Milani L, Mishra PP, Nauck M, Navas-Acien A, Nowak C, Peters A, Prokisch H, Psaty BM, Raitakari OT, Ratliff SM, Reiner AP, Rosas SE, Schöttker B, Schwartz J, Sedaghat S, Smith JA, Sotoodehnia N, Stocker HR, Stringhini S, Sundström J, Swenson BR, Tellez-Plaza M, van Meurs JBJ, van Vliet-Ostaptchouk JV, Venema A, Verweij N, et alSchlosser P, Tin A, Matias-Garcia PR, Thio CHL, Joehanes R, Liu H, Weihs A, Yu Z, Hoppmann A, Grundner-Culemann F, Min JL, Adeyemo AA, Agyemang C, Ärnlöv J, Aziz NA, Baccarelli A, Bochud M, Brenner H, Breteler MMB, Carmeli C, Chaker L, Chambers JC, Cole SA, Coresh J, Corre T, Correa A, Cox SR, de Klein N, Delgado GE, Domingo-Relloso A, Eckardt KU, Ekici AB, Endlich K, Evans KL, Floyd JS, Fornage M, Franke L, Fraszczyk E, Gao X, Gào X, Ghanbari M, Ghasemi S, Gieger C, Greenland P, Grove ML, Harris SE, Hemani G, Henneman P, Herder C, Horvath S, Hou L, Hurme MA, Hwang SJ, Jarvelin MR, Kardia SLR, Kasela S, Kleber ME, Koenig W, Kooner JS, Kramer H, Kronenberg F, Kühnel B, Lehtimäki T, Lind L, Liu D, Liu Y, Lloyd-Jones DM, Lohman K, Lorkowski S, Lu AT, Marioni RE, März W, McCartney DL, Meeks KAC, Milani L, Mishra PP, Nauck M, Navas-Acien A, Nowak C, Peters A, Prokisch H, Psaty BM, Raitakari OT, Ratliff SM, Reiner AP, Rosas SE, Schöttker B, Schwartz J, Sedaghat S, Smith JA, Sotoodehnia N, Stocker HR, Stringhini S, Sundström J, Swenson BR, Tellez-Plaza M, van Meurs JBJ, van Vliet-Ostaptchouk JV, Venema A, Verweij N, Walker RM, Wielscher M, Winkelmann J, Wolffenbuttel BHR, Zhao W, Zheng Y, Loh M, Snieder H, Levy D, Waldenberger M, Susztak K, Köttgen A, Teumer A. Meta-analyses identify DNA methylation associated with kidney function and damage. Nat Commun 2021; 12:7174. [PMID: 34887417 PMCID: PMC8660832 DOI: 10.1038/s41467-021-27234-3] [Show More Authors] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 11/08/2021] [Indexed: 12/27/2022] Open
Abstract
Chronic kidney disease is a major public health burden. Elevated urinary albumin-to-creatinine ratio is a measure of kidney damage, and used to diagnose and stage chronic kidney disease. To extend the knowledge on regulatory mechanisms related to kidney function and disease, we conducted a blood-based epigenome-wide association study for estimated glomerular filtration rate (n = 33,605) and urinary albumin-to-creatinine ratio (n = 15,068) and detected 69 and seven CpG sites where DNA methylation was associated with the respective trait. The majority of these findings showed directionally consistent associations with the respective clinical outcomes chronic kidney disease and moderately increased albuminuria. Associations of DNA methylation with kidney function, such as CpGs at JAZF1, PELI1 and CHD2 were validated in kidney tissue. Methylation at PHRF1, LDB2, CSRNP1 and IRF5 indicated causal effects on kidney function. Enrichment analyses revealed pathways related to hemostasis and blood cell migration for estimated glomerular filtration rate, and immune cell activation and response for urinary albumin-to-creatinineratio-associated CpGs.
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Affiliation(s)
- Pascal Schlosser
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Adrienne Tin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, 39216, USA
| | - Pamela R Matias-Garcia
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, D-85764, Neuherberg, Bavaria, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, D-85764, Neuherberg, Bavaria, Germany
- TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Chris H L Thio
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Roby Joehanes
- Framingham Heart Study, Framingham, Massachusetts, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, US
| | - Hongbo Liu
- Department of Medicine and Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Antoine Weihs
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Zhi Yu
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Anselm Hoppmann
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Franziska Grundner-Culemann
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Josine L Min
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Charles Agyemang
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands
| | - Johan Ärnlöv
- Department of Neurobiology, Care Sciences and Society (NVS), Family Medicine and Primary Care Unit, Karolinska Institutet, Huddinge, Sweden
- School of Health and Social Studies, Dalarna University, Falun, Sweden
| | - Nasir A Aziz
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Andrea Baccarelli
- Laboratory of Environmental Precision Health, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Murielle Bochud
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Hermann Brenner
- German Cancer Research Center (DKFZ), Division of Clinical Epidemiology and Aging Research, Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Consortium, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Monique M B Breteler
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Cristian Carmeli
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
- Population Health Laboratory, University of Fribourg, Fribourg, Switzerland
| | - Layal Chaker
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - John C Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK
- Imperial College Healthcare NHS Trust, London, UK
| | | | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Tanguy Corre
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, 39216, USA
| | - Simon R Cox
- Lothian Birth Cohorts Group, Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Niek de Klein
- Department of Genetics, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Groningen, the Netherlands
| | - Graciela E Delgado
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Arce Domingo-Relloso
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Statistics and Operations Research, University of Valencia, Valencia, Spain
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Arif B Ekici
- Institute of Human Genetics, Friedrich-Alexander-UniversitätErlangen-Nürnberg, 91054, Erlangen, Germany
| | - Karlhans Endlich
- Department of Anatomy and Cell Biology, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - James S Floyd
- Department of Medicine, University of Washington, Seattle, WA, 98101, USA
- Department of Epidemiology, University of Washington, Seattle, WA, 98101, USA
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, 98101, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, Houston, TX, 77030, USA
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Lude Franke
- Department of Genetics, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Groningen, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Eliza Fraszczyk
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Xu Gao
- Laboratory of Environmental Precision Health, Mailman School of Public Health, Columbia University, New York, NY, USA
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Xīn Gào
- German Cancer Research Center (DKFZ), Division of Clinical Epidemiology and Aging Research, Heidelberg, Germany
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Sahar Ghasemi
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, D-85764, Neuherberg, Bavaria, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, D-85764, Neuherberg, Bavaria, Germany
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Megan L Grove
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Sarah E Harris
- Lothian Birth Cohorts Group, Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Peter Henneman
- Department of Clinical Genetics, Amsterdam Reproduction & Development Research Institute, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, the Netherlands
| | - Christian Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research, Munich-Neuherberg, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA
- Biostatistics, Fielding School of Public Health, UCLA, Los Angeles, CA, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Mikko A Hurme
- Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33014, Finland
| | - Shih-Jen Hwang
- Framingham Heart Study, Framingham, Massachusetts, USA
- Division of Intramural Research, Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, 90014, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Silva Kasela
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Wolfgang Koenig
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner site Munich Heart Alliance, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK
- Imperial College Healthcare NHS Trust, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Holly Kramer
- Departments of Public Health Science and Medicine, Loyola University Chicago, Maywood, IL, USA
- Edward Hines VA Medical Center, Hines, IL, USA
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Brigitte Kühnel
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, D-85764, Neuherberg, Bavaria, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, D-85764, Neuherberg, Bavaria, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Dan Liu
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Yongmei Liu
- Department of Medicine, Division of Cardiology, Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA
| | - Donald M Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Kurt Lohman
- Department of Medicine, Division of Cardiology, Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA
| | - Stefan Lorkowski
- Institute of Nutritional Sciences, Friedrich Schiller University Jena, Jena, Germany
- Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena, Germany
| | - Ake T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena, Germany
- Synlab Academy, SYNLAB Holding Deutschland GmbH, Mannheim and Augsburg, Augsburg, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Karlijn A C Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Matthias Nauck
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Christoph Nowak
- Department of Neurobiology, Care Sciences and Society (NVS), Family Medicine and Primary Care Unit, Karolinska Institutet, Huddinge, Sweden
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, D-85764, Neuherberg, Bavaria, Germany
- Ludwig-Maximilians Universität München, Munich, Germany
| | - Holger Prokisch
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
- Department of Computational Health, Institute of Neurogenomics, Helmholtz Zentrum München, Munich, Germany
| | - Bruce M Psaty
- Department of Medicine, University of Washington, Seattle, WA, 98101, USA
- Department of Epidemiology, University of Washington, Seattle, WA, 98101, USA
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, 98101, USA
- Department of Health Services, University of Washington, Seattle, WA, 98101, USA
| | - Olli T Raitakari
- Research centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Scott M Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, 98101, USA
| | - Sylvia E Rosas
- Joslin Diabetes Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Ben Schöttker
- German Cancer Research Center (DKFZ), Division of Clinical Epidemiology and Aging Research, Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Sanaz Sedaghat
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48104, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, 98101, USA
| | - Hannah R Stocker
- German Cancer Research Center (DKFZ), Division of Clinical Epidemiology and Aging Research, Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Silvia Stringhini
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Johan Sundström
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- The George Institute for Global Health, University of New South Wales, Sydney, Australia
| | - Brenton R Swenson
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, 98101, USA
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Maria Tellez-Plaza
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Jana V van Vliet-Ostaptchouk
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Andrea Venema
- Department of Clinical Genetics, Amsterdam Reproduction & Development Research Institute, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, the Netherlands
| | - Niek Verweij
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Groningen, the Netherlands
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Matthias Wielscher
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health, Imperial College London, London, UK
| | - Juliane Winkelmann
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Munich, Germany
- Chair Neurogenetics, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Bruce H R Wolffenbuttel
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Daniel Levy
- Framingham Heart Study, Framingham, Massachusetts, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, US
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, D-85764, Neuherberg, Bavaria, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, D-85764, Neuherberg, Bavaria, Germany
- DZHK (German Centre for Cardiovascular Research), Partner site Munich Heart Alliance, Munich, Germany
| | - Katalin Susztak
- Department of Medicine and Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Alexander Teumer
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany.
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland.
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384
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Kibler KV, Szczerba M, Lake D, Roeder AJ, Rahman M, Hogue BG, Roy Wong LY, Perlman S, Li Y, Jacobs BL. Intranasal immunization with a vaccinia virus vaccine vector expressing pre-fusion stabilized SARS-CoV-2 spike fully protected mice against lethal challenge with the heavily mutated mouse-adapted SARS2-N501Y MA30 strain of SARS-CoV-2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021. [PMID: 34909775 DOI: 10.1101/2021.07.28.454201] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
The Omicron SARS-CoV-2 variant has been designated a variant of concern because its spike protein is heavily mutated. In particular, Omicron spike is mutated at 5 positions (K417, N440, E484, Q493 and N501) that have been associated with escape from neutralizing antibodies induced by either infection with or immunization against the early Washington strain of SARS-CoV-2. The mouse-adapted strain of SARS-CoV-2, SARS2-N501Y MA30 , contains a spike that is also heavily mutated, with mutations at 4 of the 5 positions in Omicron spike associated with neutralizing antibody escape (K417, E484, Q493 and N501). In this manuscript we show that intranasal immunization with a pre-fusion stabilized Washington strain spike, expressed from a highly attenuated, replication-competent vaccinia virus construct, NYVAC-KC, fully protected mice against disease and death from SARS2-N501Y MA30 . Similarly, immunization by scarification on the skin fully protected against death, but not from mild disease. This data demonstrates that Washington strain spike, when expressed from a highly attenuated, replication-competent poxvirus, administered without parenteral injection can fully protect against the heavily mutated mouse-adapted SARS2-N501Y MA30 .
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Affiliation(s)
- Karen V Kibler
- Biodesign Center for Immunotherapy, Vaccines and Virotherapy, Arizona State University, Tempe, AZ, USA
| | - Mateusz Szczerba
- Biodesign Center for Immunotherapy, Vaccines and Virotherapy, Arizona State University, Tempe, AZ, USA
| | - Douglas Lake
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Alexa J Roeder
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Masmudur Rahman
- Biodesign Center for Immunotherapy, Vaccines and Virotherapy, Arizona State University, Tempe, AZ, USA
| | - Brenda G Hogue
- Biodesign Center for Immunotherapy, Vaccines and Virotherapy, Arizona State University, Tempe, AZ, USA
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Lok-Yin Roy Wong
- Department of Microbiology and Immunology, University of Iowa, Iowa City, Iowa, USA
| | - Stanley Perlman
- Department of Microbiology and Immunology, University of Iowa, Iowa City, Iowa, USA
- Department of Pediatrics, University of Iowa, Iowa City, Iowa, USA
| | - Yize Li
- Biodesign Center for Immunotherapy, Vaccines and Virotherapy, Arizona State University, Tempe, AZ, USA
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Bertram L Jacobs
- Biodesign Center for Immunotherapy, Vaccines and Virotherapy, Arizona State University, Tempe, AZ, USA
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
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385
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Liang Y, Luo S, Schooling CM, Au Yeung SL. Corrigendum: Genetically Predicted Fibroblast Growth Factor 23 and Major Cardiovascular Diseases, Their Risk Factors, Kidney Function, and Longevity: A Two-Sample Mendelian Randomization Study. Front Genet 2021; 12:794246. [PMID: 34858490 PMCID: PMC8632056 DOI: 10.3389/fgene.2021.794246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 10/20/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Ying Liang
- LKS Faculty of Medicine, School of Public Health, University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Shan Luo
- LKS Faculty of Medicine, School of Public Health, University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - C Mary Schooling
- LKS Faculty of Medicine, School of Public Health, University of Hong Kong, Pokfulam, Hong Kong SAR, China.,School of Public Health and Health Policy, City University of New York, New York, NY, United States
| | - Shiu Lun Au Yeung
- LKS Faculty of Medicine, School of Public Health, University of Hong Kong, Pokfulam, Hong Kong SAR, China
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386
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Ponte B, Sadler MC, Olinger E, Vollenweider P, Bochud M, Padmanabhan S, Hayward C, Kutalik Z, Devuyst O. Mendelian randomization to assess causality between uromodulin, blood pressure and chronic kidney disease. Kidney Int 2021; 100:1282-1291. [PMID: 34634361 DOI: 10.1016/j.kint.2021.08.032] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 08/02/2021] [Accepted: 08/26/2021] [Indexed: 11/24/2022]
Abstract
UMOD variants associated with higher levels of urinary uromodulin (uUMOD) increase the risk of chronic kidney disease (CKD) and hypertension. However, uUMOD levels also reflect functional kidney tubular mass in observational studies, questioning the causal link between uromodulin production and kidney damage. We used Mendelian randomization to clarify causality between uUMOD levels, kidney function and blood pressure in individuals of European descent. The link between uUMOD and estimated glomerular filtration rate (eGFR) was first investigated in a population-based cohort of 3851 individuals. In observational data, higher uUMOD associated with higher eGFR. Conversely, when using rs12917707 (an UMOD polymorphism) as an instrumental variable in one-sample Mendelian randomization, higher uUMOD strongly associated with eGFR decline. We next applied two-sample Mendelian randomization on four genome wide association study consortia to explore causal links between uUMOD and eGFR, CKD risk (567,460 individuals) and blood pressure (757,461 individuals). Higher uUMOD levels significantly associated with lower eGFR, higher odds for eGFR decline or CKD, and higher systolic or diastolic blood pressure. Each one standard deviation (SD) increase of uUMOD decreased log-transformed eGFR by -0.15 SD (95% confidence interval -0.17 to -0.13) and increased log-odds CKD by 0.13 SD (0.12 to 0.15). One SD increase of uUMOD increased systolic blood pressure by 0.06 SD (0.03 to 0.09) and diastolic blood pressure by 0.08 SD (0.05 to 0.12). The effect of uUMOD on blood pressure was mediated by eGFR, whereas the effect on eGFR was not mediated by blood pressure. Thus, our data support that genetically driven levels of uromodulin have a direct, causal and adverse effect on kidney function outcome in the general population, not mediated by blood pressure.
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Affiliation(s)
- Belen Ponte
- Nephrology and Hypertension Service, Department of Medicine, University Hospitals of Geneva (HUG), Geneva, Switzerland.
| | - Marie C Sadler
- Department of Epidemiology and Health Systems, University Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland; Statistical Genetics Group, Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Eric Olinger
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology, University of Zurich, Zürich, Switzerland
| | - Peter Vollenweider
- Department of Internal Medicine, University Hospital of Lausanne (CHUV), Lausanne, Switzerland
| | - Murielle Bochud
- Department of Epidemiology and Health Systems, University Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland
| | - Sandosh Padmanabhan
- Department of Health and Social Care, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, Scotland
| | - Caroline Hayward
- Biomedical Genomics Section, Medical Research Council (MRC) Human Genetics Unit, Institute of Genetics and Molecular Medicine (IGMM), University of Edinburgh, Edinburgh, Scotland
| | - Zoltán Kutalik
- Department of Epidemiology and Health Systems, University Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland; Statistical Genetics Group, Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Olivier Devuyst
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology, University of Zurich, Zürich, Switzerland.
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387
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Turner M, Staplin N. UMOD-ulating CKD risk: untangling the relationship between urinary uromodulin, blood pressure, and kidney disease. Kidney Int 2021; 100:1168-1170. [PMID: 34802557 DOI: 10.1016/j.kint.2021.09.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 09/24/2021] [Indexed: 11/23/2022]
Abstract
A new Mendelian randomization study finds evidence that genetically predicted higher levels of urinary uromodulin are associated with lower kidney function and higher blood pressure. Bidirectional and multivariable Mendelian randomization suggests the association with higher blood pressure appears to be partially through decreased kidney function, but blood pressure does not appear to mediate the association of uromodulin with low kidney function. We describe the methods used for the bidirectional and multivariable Mendelian randomization analyses and examine the validity of the assumptions and implications of the results.
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Affiliation(s)
- Michael Turner
- Medical Research Council Population Health Research Unit, Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Natalie Staplin
- Medical Research Council Population Health Research Unit, Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Oxford Kidney Unit, Churchill Hospital, Oxford, UK.
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388
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Yang Y, Bartz TM, Brown MR, Guo X, Zilhao NR, Trompet S, Weiss S, Yao J, Brody JA, Defilippi CR, Hoogeveen RC, Lin HJ, Gudnason V, Ballantyne CM, Dorr M, Jukema JW, Petersmann A, Psaty BM, Rotter JI, Boerwinkle E, Fornage M, Jun G, Yu B. Identification of Functional Genetic Determinants of Cardiac Troponin T and I in a Multiethnic Population and Causal Associations With Atrial Fibrillation. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2021; 14:e003460. [PMID: 34732054 PMCID: PMC8692416 DOI: 10.1161/circgen.121.003460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 10/26/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND Elevated cardiac troponin levels in blood are associated with increased risk of cardiovascular diseases and mortality. Cardiac troponin levels are heritable, but their genetic architecture remains elusive. METHODS We conducted a transethnic genome-wide association analysis on high-sensitivity cTnT (cardiac troponin T; hs-cTnT) and high-sensitivity cTnI (cardiac troponin I; hs-cTnI) levels in 24 617 and 14 336 participants free of coronary heart disease and heart failure from 6 population-based cohorts, followed by a series of bioinformatic analyses to decipher the genetic architecture of hs-cTnT and hs-cTnI. RESULTS We identified 4 genome-wide significant loci for hs-cTnT including a novel locus rs3737882 in PPFIA4 and 3 previously reported loci at NCOA2, TRAM1, and BCL2. One known locus at VCL was replicated for hs-cTnI. One copy of C allele for rs3737882 was associated with a 6% increase in hs-cTnT levels (minor allele frequency, 0.18; P=2.80×10-9). We observed pleiotropic loci located at BAG3 and ANO5. The proportions of variances explained by single-nucleotide polymorphisms were 10.15% and 7.74% for hs-cTnT and hs-cTnI, respectively. Single-nucleotide polymorphisms were colocalized with BCL2 expression in heart tissues and hs-cTnT and with ANO5 expression in artery, heart tissues, and whole blood and both troponins. Mendelian randomization analyses showed that genetically increased hs-cTnT and hs-cTnI levels were associated with higher odds of atrial fibrillation (odds ratio, 1.38 [95% CI, 1.25-1.54] for hs-cTnT and 1.21 [95% CI, 1.06-1.37] for hs-cTnI). CONCLUSIONS We identified a novel genetic locus associated with hs-cTnT in a multiethnic population and found that genetically regulated troponin levels were associated with atrial fibrillation.
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Affiliation(s)
- Yunju Yang
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, Houston, Texas, USA
| | - Traci M. Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Michael R. Brown
- Department of Epidemiology, Human Genetics & Environmental Sciences and Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, 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, California, USA
| | | | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center and Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics; Department of Functional Genomics; University Medicine and University of Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - 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, California, USA
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA
| | | | - Ron C. Hoogeveen
- Division of Atherosclerosis and Vascular Medicine, Department of Medicine, Baylor College of Medicine, Houston, Texas, 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, California, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Christie M. Ballantyne
- Division of Atherosclerosis and Vascular Medicine, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
- Center for Cardiovascular Disease Prevention, Methodist DeBakey Heart Center, Houston, TX, USA
| | - Marcus Dorr
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B - Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, University Medicine Greifswald, Greifswald, Germany
| | - J. Wouter Jukema
- Department of Cardiology and Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden and the Netherlands Heart Institute, Utrecht, the Netherlands
| | - Astrid Petersmann
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald and Institute of Clinical Chemistry and Laboratory Medicine, Universitätsmedizin Oldenburg, Oldenburg, Germany
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Epidemiology, and Department of Health Services, University of Washington, Seattle, Washington, 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, California, USA
| | - Eric Boerwinkle
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, Houston, Texas, USA
- Department of Epidemiology, Human Genetics & Environmental Sciences and Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Myriam Fornage
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, Houston, Texas, USA
- Department of Epidemiology, Human Genetics & Environmental Sciences and Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Goo Jun
- Department of Epidemiology, Human Genetics & Environmental Sciences and Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics & Environmental Sciences and Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
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389
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Dhande IS, Braun MC, Doris PA. Emerging Insights Into Chronic Renal Disease Pathogenesis in Hypertension From Human and Animal Genomic Studies. Hypertension 2021; 78:1689-1700. [PMID: 34757770 PMCID: PMC8577298 DOI: 10.1161/hypertensionaha.121.18112] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
The pathogenic links between elevated blood pressure and chronic kidney disease remain obscure. This article examines progress in population genetics and in animal models of hypertension and chronic kidney disease. It also provides a critique of the application of genome-wide association studies to understanding the heritability of renal function. Emerging themes identified indicate that heritable risk of chronic kidney disease in hypertension can arise from genetic variation in (1) glomerular and tubular protein handling mechanisms; (2) autoregulatory capacity of the renal vasculature; and (3) innate and adaptive immune mechanisms. Increased prevalence of hypertension-associated chronic kidney disease that occurs with aging may reflect amplification of heritable risks by normal aging processes affecting immunity and autoregulation.
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Affiliation(s)
- Isha S. Dhande
- Center for Human Genetics, Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas HSC, Houston (I.S.D., P.A.D.)
| | - Michael C. Braun
- Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston (M.C.B.)
| | - Peter A. Doris
- Center for Human Genetics, Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas HSC, Houston (I.S.D., P.A.D.)
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390
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Yu Z, Jin J, Tin A, Köttgen A, Yu B, Chen J, Surapaneni A, Zhou L, Ballantyne CM, Hoogeveen RC, Arking DE, Chatterjee N, Grams ME, Coresh J. Polygenic Risk Scores for Kidney Function and Their Associations with Circulating Proteome, and Incident Kidney Diseases. J Am Soc Nephrol 2021; 32:3161-3173. [PMID: 34548389 PMCID: PMC8638405 DOI: 10.1681/asn.2020111599] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 08/29/2021] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) have revealed numerous loci for kidney function (eGFR). The relationship between polygenic predictors of eGFR, risk of incident adverse kidney outcomes, and the plasma proteome is not known. METHODS We developed a genome-wide polygenic risk score (PRS) for eGFR by applying the LDpred algorithm to summary statistics generated from a multiethnic meta-analysis of CKDGen Consortium GWAS ( n =765,348) and UK Biobank GWAS (90% of the cohort; n =451,508), followed by best-parameter selection using the remaining 10% of UK Biobank data ( n =45,158). We then tested the association of the PRS in the Atherosclerosis Risk in Communities (ARIC) study ( n =8866) with incident CKD, ESKD, kidney failure, and AKI. We also examined associations between the PRS and 4877 plasma proteins measured at middle age and older adulthood and evaluated mediation of PRS associations by eGFR. RESULTS The developed PRS showed a significant association with all outcomes. Hazard ratios per 1 SD lower PRS ranged from 1.06 (95% CI, 1.01 to 1.11) to 1.33 (95% CI, 1.28 to 1.37). The PRS was significantly associated with 132 proteins at both time points. The strongest associations were with cystatin C, collagen α -1(XV) chain, and desmocollin-2. Most proteins were higher at lower kidney function, except for five proteins, including testican-2. Most correlations of the genetic PRS with proteins were mediated by eGFR. CONCLUSIONS A PRS for eGFR is now sufficiently strong to capture risk for a spectrum of incident kidney diseases and broadly influences the plasma proteome, primarily mediated by eGFR.
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Affiliation(s)
- Zhi Yu
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts,Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Jin Jin
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Adrienne Tin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland,Division of Nephrology, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
| | - Anna Köttgen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland,Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Centre–University of Freiburg, Freiburg, Germany
| | - Bing Yu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas
| | - Jingsha Chen
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland
| | - Aditya Surapaneni
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland
| | - Linda Zhou
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland
| | | | - Ron C. Hoogeveen
- Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Dan E. Arking
- McKusick-Nathans Department of Genetic Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland,Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Morgan E. Grams
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland,Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland,Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland,Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland,Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
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391
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Claussnitzer M, Susztak K. Gaining insight into metabolic diseases from human genetic discoveries. Trends Genet 2021; 37:1081-1094. [PMID: 34315631 PMCID: PMC8578350 DOI: 10.1016/j.tig.2021.07.005] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 06/29/2021] [Accepted: 07/05/2021] [Indexed: 12/30/2022]
Abstract
Human large-scale genetic association studies have identified sequence variations at thousands of genetic risk loci that are more common in patients with diverse metabolic disease compared with healthy controls. While these genetic associations have been replicated in multiple large cohorts and sometimes can explain up to 50% of heritability, the molecular and cellular mechanisms affected by common genetic variation associated with metabolic disease remains mostly unknown. A variety of new genome-wide data types, in conjunction with novel biostatistical and computational analytical methodologies and foundational experimental technologies, are paving the way for a principled approach to systematic variant-to-function (V2F) studies for metabolic diseases, turning associated regions into causal variants, cell types and states of action, effector genes, and cellular and physiological mechanisms. Identification of new target genes and cellular programs for metabolic risk loci will improve mechanistic understanding of disease biology and identification of novel therapeutic strategies.
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Affiliation(s)
- Melina Claussnitzer
- Beth Israel Deaconess Medical Center, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Katalin Susztak
- Department of Medicine and Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA.
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392
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Zhang K, Hocker JD, Miller M, Hou X, Chiou J, Poirion OB, Qiu Y, Li YE, Gaulton KJ, Wang A, Preissl S, Ren B. A single-cell atlas of chromatin accessibility in the human genome. Cell 2021; 184:5985-6001.e19. [PMID: 34774128 PMCID: PMC8664161 DOI: 10.1016/j.cell.2021.10.024] [Citation(s) in RCA: 259] [Impact Index Per Article: 64.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 07/30/2021] [Accepted: 10/21/2021] [Indexed: 12/12/2022]
Abstract
Current catalogs of regulatory sequences in the human genome are still incomplete and lack cell type resolution. To profile the activity of gene regulatory elements in diverse cell types and tissues in the human body, we applied single-cell chromatin accessibility assays to 30 adult human tissue types from multiple donors. We integrated these datasets with previous single-cell chromatin accessibility data from 15 fetal tissue types to reveal the status of open chromatin for ∼1.2 million candidate cis-regulatory elements (cCREs) in 222 distinct cell types comprised of >1.3 million nuclei. We used these chromatin accessibility maps to delineate cell-type-specificity of fetal and adult human cCREs and to systematically interpret the noncoding variants associated with complex human traits and diseases. This rich resource provides a foundation for the analysis of gene regulatory programs in human cell types across tissues, life stages, and organ systems.
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Affiliation(s)
- Kai Zhang
- Ludwig Institute for Cancer Research, La Jolla, CA, USA; Department of Cellular and Molecular Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - James D Hocker
- Ludwig Institute for Cancer Research, La Jolla, CA, USA; Medical Scientist Training Program, University of California San Diego, La Jolla, CA, USA; Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Michael Miller
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Xiaomeng Hou
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Joshua Chiou
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA; Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Olivier B Poirion
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Yunjiang Qiu
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
| | - Yang E Li
- Ludwig Institute for Cancer Research, La Jolla, CA, USA; Department of Cellular and Molecular Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Kyle J Gaulton
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Allen Wang
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Bing Ren
- Ludwig Institute for Cancer Research, La Jolla, CA, USA; Center for Epigenomics, University of California San Diego, La Jolla, CA, USA; Department of Cellular and Molecular Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
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393
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Park S, Lee S, Kim Y, Cho S, Kim K, Kim YC, Han SS, Lee H, Lee JP, Lee S, Choi EK, Joo KW, Lim CS, Kim YS, Kim DK. Causal effects of atrial fibrillation on brain white and gray matter volume: a Mendelian randomization study. BMC Med 2021; 19:274. [PMID: 34814924 PMCID: PMC8611907 DOI: 10.1186/s12916-021-02152-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 10/04/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Atrial fibrillation (AF) and brain volume loss are prevalent in older individuals. We aimed to assess the causal effect of atrial fibrillation on brain volume phenotypes by Mendelian randomization (MR) analysis. METHODS The genetic instrument for AF was constructed from a previous genome-wide association study (GWAS) meta-analysis (15,993 AF patients and 113,719 controls of European ancestry). The outcome summary statistics for head-size-normalized white or gray matter volume measured by magnetic resonance imaging were provided by a previous GWAS of 33,224 white British participants in the UK Biobank. Two-sample MR by the inverse variance-weighted method was performed, supported by pleiotropy-robust MR sensitivity analysis. The causal estimates for the effect of AF on ischemic stroke were also investigated in a dataset that included the findings from the MEGASTROKE study (34,217 stroke patients and 406,111 controls of European ancestry). The direct effects of AF on brain volume phenotypes adjusted for the mediating effect of ischemic stroke were studied by multivariable MR. RESULTS A higher genetic predisposition for AF was significantly associated with lower grey matter volume [beta -0.040, standard error (SE) 0.017, P=0.017], supported by pleiotropy-robust MR sensitivity analysis. Significant causal estimates were identified for the effect of AF on ischemic stroke (beta 0.188, SE 0.026, P=1.03E-12). The total effect of AF on lower brain grey matter volume was attenuated by adjusting for the effect of ischemic stroke (direct effects, beta -0.022, SE 0.033, P=0.528), suggesting that ischemic stroke is a mediator of the identified causal pathway. The causal estimates were nonsignificant for effects on brain white matter volume as an outcome. CONCLUSIONS This study identified that genetic predisposition for AF is significantly associated with lower gray matter volume but not white matter volume. The results indicated that the identified total effect of AF on gray matter volume may be mediated by ischemic stroke.
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Affiliation(s)
- Sehoon Park
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
- Department of Internal Medicine, Armed Forces Capital Hospital, Gyeonggi-do, Seongnam, Korea
| | - Soojin Lee
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, 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, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
| | - Kwangsoo Kim
- Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul, Korea
| | - Yong Chul Kim
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
| | - Seung Seok Han
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Kidney Research Institute, Seoul National University, Seoul, Korea
| | - Hajeong Lee
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
| | - Jung Pyo Lee
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Kidney Research Institute, Seoul National University, Seoul, Korea
- Department of Internal Medicine, Seoul National University Boramae Medical Center, Seoul, Korea
| | - Soryoung Lee
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
| | - Eue-Keun Choi
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
| | - Kwon Wook Joo
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
- Kidney Research Institute, Seoul National University, Seoul, Korea
| | - Chun Soo Lim
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, 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, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
- Kidney Research Institute, Seoul National University, Seoul, Korea
| | - Dong Ki Kim
- Department of Internal Medicine, Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Gyeonggi-do, Uijeongbu, Korea.
- Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
- Kidney Research Institute, Seoul National University, Seoul, Korea.
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394
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Wu Z, Zhang C. Role of the cytoskeleton in steroidogenesis. Endocr Metab Immune Disord Drug Targets 2021; 22:549-557. [PMID: 34802411 DOI: 10.2174/1871530321666211119143653] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 08/25/2021] [Accepted: 10/20/2021] [Indexed: 11/22/2022]
Abstract
Steroidogenesis in the adrenal cortex or gonads is a complicated process, modulated by various elements either at the tissue or molecular level. The substrate-cholesterol is first delivered to the outer membrane of mitochondria, undergoing a series of enzymatic reactions along with the material exchange between the mitochondria and the ER (endoplasmic reticulum) and ultimately yield various steroids: aldosterone, cortisol, testosterone and estrone. Several valves are set to adjust the amount of production to the needs. e.g. StAR(steroidogenic acute regulator) is in charge of the rate-limiting step-traffic of cholesterol from outer membrane to inner membrane of mitochondria. And the "needs" is partly reflected by trophic signals like ACTH、LH and downstream pathways-- intracellular cAMP pathway, which represents the endocrinal regulation of steroid synthesis, too. The coordinated activities of these related factors are all associated with another crucial cellular constituent-the cytoskeleton, which plays a crucial role in the cellular architecture and substrate trafficking. Though considerable studies have been performed regarding steroid synthesis, details about the upstream signaling pathways and mechanisms of the regulation by cytoskeleton network still remain unclear. The metabolism and interplays of the pivotal cellular organelles with cytoskeleton are worth exploring as well. In this review, we summarize research of different time span, describing the roles of specific cytoskeleton elements in steroidogenesis and related signaling pathways involved in the steroid synthesis. In addition, we discussed the inner cytoskeletal network involved in steroidogenic processes such as mitochondrial movement, organelle interactions and cholesterol trafficking.
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Affiliation(s)
- Zaichao Wu
- Joint Program of Nanchang University and Queen Mary University of London, School of Medicine, Nanchang University, Nanchang, Jiangxi. China
| | - Chunping Zhang
- Department of Cell Biology, School of Medicine, Nanchang University, Nanchang, Jiangxi. China
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395
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Warmerdam R, Lanting P, Lifelines Cohort Study, Deelen P, Franke L. Idéfix: identifying accidental sample mix-ups in biobanks using polygenic scores. Bioinformatics 2021; 38:1059-1066. [PMID: 34792549 PMCID: PMC8796367 DOI: 10.1093/bioinformatics/btab783] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 10/07/2021] [Accepted: 11/15/2021] [Indexed: 02/03/2023] Open
Abstract
MOTIVATION Identifying sample mix-ups in biobanks is essential to allow the repurposing of genetic data for clinical pharmacogenetics. Pharmacogenetic advice based on the genetic information of another individual is potentially harmful. Existing methods for identifying mix-ups are limited to datasets in which additional omics data (e.g. gene expression) is available. Cohorts lacking such data can only use sex, which can reveal only half of the mix-ups. Here, we describe Idéfix, a method for the identification of accidental sample mix-ups in biobanks using polygenic scores. RESULTS In the Lifelines population-based biobank, we calculated polygenic scores (PGSs) for 25 traits for 32 786 participants. We then applied Idéfix to compare the actual phenotypes to PGSs, and to use the relative discordance that is expected for mix-ups, compared to correct samples. In a simulation, using induced mix-ups, Idéfix reaches an AUC of 0.90 using 25 polygenic scores and sex. This is a substantial improvement over using only sex, which has an AUC of 0.75. Subsequent simulations present Idéfix's potential in varying datasets with more powerful PGSs. This suggests its performance will likely improve when more highly powered GWASs for commonly measured traits will become available. Idéfix can be used to identify a set of high-quality participants for whom it is very unlikely that they reflect sample mix-ups, and for these participants we can use genetic data for clinical purposes, such as pharmacogenetic profiles. For instance, in Lifelines, we can select 34.4% of participants, reducing the sample mix-up rate from 0.15% to 0.01%. AVAILABILITYAND IMPLEMENTATION Idéfix is freely available at https://github.com/molgenis/systemsgenetics/wiki/Idefix. The individual-level data that support the findings were obtained from the Lifelines biobank under project application number ov16_0365. Data is made available upon reasonable request submitted to the LifeLines Research office (research@lifelines.nl, https://www.lifelines.nl/researcher/how-to-apply/apply-here). SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Robert Warmerdam
- Department of Genetics, University Medical Center Groningen, University of Groningen, 9700AB Groningen, The Netherlands
| | - Pauline Lanting
- Department of Genetics, University Medical Center Groningen, University of Groningen, 9700AB Groningen, The Netherlands
| | | | - Patrick Deelen
- Department of Genetics, University Medical Center Groningen, University of Groningen, 9700AB Groningen, The Netherlands,Department of Genetics, University Medical Center Utrecht, 3508GA Utrecht, The Netherlands
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396
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Karhunen V, Bakker MK, Ruigrok YM, Gill D, Larsson SC. Modifiable Risk Factors for Intracranial Aneurysm and Aneurysmal Subarachnoid Hemorrhage: A Mendelian Randomization Study. J Am Heart Assoc 2021; 10:e022277. [PMID: 34729997 PMCID: PMC8751955 DOI: 10.1161/jaha.121.022277] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Background The aim of this study was to assess the associations of modifiable lifestyle factors (smoking, coffee consumption, sleep, and physical activity) and cardiometabolic factors (body mass index, glycemic traits, type 2 diabetes, systolic and diastolic blood pressure, lipids, and inflammation and kidney function markers) with risks of any (ruptured or unruptured) intracranial aneurysm and aneurysmal subarachnoid hemorrhage using Mendelian randomization. Methods and Results Summary statistical data for the genetic associations with the modifiable risk factors and the outcomes were obtained from meta‐analyses of genome‐wide association studies. The inverse‐variance weighted method was used as the main Mendelian randomization analysis, with additional sensitivity analyses conducted using methods more robust to horizontal pleiotropy. Genetic predisposition to smoking, insomnia, and higher blood pressure was associated with an increased risk of both intracranial aneurysm and aneurysmal subarachnoid hemorrhage. For intracranial aneurysm, the odds ratios were 3.20 (95% CI, 1.93–5.29) per SD increase in smoking index, 1.24 (95% CI, 1.10–1.40) per unit increase in log‐odds of insomnia, and 2.92 (95% CI, 2.49–3.43) per 10 mm Hg increase in diastolic blood pressure. In addition, there was weak evidence for associations of genetically predicted decreased physical activity, higher triglyceride levels, higher body mass index, and lower low‐density lipoprotein cholesterol levels with higher risk of intracranial aneurysm and aneurysmal subarachnoid hemorrhage, with 95% CI overlapping the null for at least 1 of the outcomes. All results were consistent in sensitivity analyses. Conclusions This Mendelian randomization study suggests that smoking, insomnia, and high blood pressure are major risk factors for intracranial aneurysm and aneurysmal subarachnoid hemorrhage.
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Affiliation(s)
- Ville Karhunen
- Department of Epidemiology and Biostatistics School of Public Health Imperial College London London United Kingdom.,Research Unit of Mathematical Sciences University of Oulu Finland.,Center for Life Course Health Research University of Oulu Finland
| | - Mark K Bakker
- Department of Neurology and Neurosurgery University Medical Center Utrecht Brain CenterUtrecht University Utrecht the Netherlands
| | - Ynte M Ruigrok
- Department of Neurology and Neurosurgery University Medical Center Utrecht Brain CenterUtrecht University Utrecht the Netherlands
| | - Dipender Gill
- Department of Epidemiology and Biostatistics School of Public Health Imperial College London London United Kingdom.,Clinical Pharmacology and Therapeutics Section Institute of Medical and Biomedical Education and Institute for Infection and Immunity St George's, University of London London United Kingdom.,Clinical Pharmacology Group, Pharmacy and Medicines Directorate St George's University Hospitals NHS Foundation Trust London United Kingdom.,Novo Nordisk Research Centre Oxford Oxford United Kingdom
| | - Susanna C Larsson
- Unit of Medical Epidemiology Department of Surgical Sciences Uppsala University Uppsala Sweden.,Unit of Cardiovascular and Nutritional Epidemiology Institute of Environmental Medicine Karolinska Institutet Stockholm Sweden
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397
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Richard EL, McEvoy LK, Cao SY, Oren E, Alcaraz JE, LaCroix AZ, Salem RM. Biomarkers of kidney function and cognitive ability: A Mendelian randomization study. J Neurol Sci 2021; 430:118071. [PMID: 34534883 PMCID: PMC8635776 DOI: 10.1016/j.jns.2021.118071] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 08/28/2021] [Accepted: 09/04/2021] [Indexed: 02/04/2023]
Abstract
BACKGROUND Estimated glomerular filtration rate (eGFR), albuminuria and serum uric acid (SUA) are markers of kidney function that have been associated with cognitive ability. However, whether these associations are causal is unclear. METHODS We performed one-sample Mendelian randomization (MR) to estimate the effects of kidney function markers on cognitive performance using data from the UK Biobank. Polygenic scores for SUA, urine albumin to creatinine ratio (ACR), estimated glomerular filtration rate based on serum creatinine (eGFRcre) and serum cystatin C (eGFRcys) were used as instrumental variables, and cognitive function outcomes included tests of verbal-numeric reasoning, reaction time, visual memory, and numeric memory. RESULTS We found no evidence of a causal effect of genetically determined SUA, eGFRcre or eGFRcys on cognitive function outcomes. There was no association between a polygenic score for ACR and verbal-numeric reasoning or numeric memory. However, there was suggestive evidence of a relationship between genetically increased ACR and slower reaction time and worse visual memory. ACR was no longer significantly associated with visual memory in analyses using an unweighted polygenic score and in analyses stratified by sex and age category. Pleiotropy adjusted estimates were directionally consistent with those of the principal analysis but overlapped with the null. CONCLUSIONS This MR study does not support causal effects of SUA, eGFRcre or eGFRcys on cognitive performance. Genetically increased ACR was associated with slower processing speed and visual memory, but results need confirmation in independent samples.
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Affiliation(s)
- Erin L Richard
- Department of Family Medicine and Public Health, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA; Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA.
| | - Linda K McEvoy
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA; Department of Radiology, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA
| | - Steven Y Cao
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA
| | - Eyal Oren
- Graduate School of Public Health, San Diego State University, 5500 Campanile Dr, San Diego, CA, USA
| | - John E Alcaraz
- Graduate School of Public Health, San Diego State University, 5500 Campanile Dr, San Diego, CA, USA
| | - Andrea Z LaCroix
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA
| | - Rany M Salem
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, USA
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398
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Kondratyev NV, Alfimova MV, Golov AK, Golimbet VE. Bench Research Informed by GWAS Results. Cells 2021; 10:3184. [PMID: 34831407 PMCID: PMC8623533 DOI: 10.3390/cells10113184] [Citation(s) in RCA: 5] [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: 09/23/2021] [Revised: 11/11/2021] [Accepted: 11/11/2021] [Indexed: 12/15/2022] Open
Abstract
Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually 'highly polygenic'. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise 'wet biologists' with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.
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Affiliation(s)
| | | | - Arkadiy K. Golov
- Mental Health Research Center, 115522 Moscow, Russia; (M.V.A.); (A.K.G.); (V.E.G.)
- Institute of Gene Biology, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Vera E. Golimbet
- Mental Health Research Center, 115522 Moscow, Russia; (M.V.A.); (A.K.G.); (V.E.G.)
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399
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Zhao JV, Schooling CM. Using genetics to understand the role of kidney function in COVID-19: a mendelian randomization study. BMC Nephrol 2021; 22:381. [PMID: 34774005 PMCID: PMC8590376 DOI: 10.1186/s12882-021-02586-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 10/28/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Kidney dysfunction occurs in severe COVID-19, and is a predictor of COVID-19 mortality. Whether kidney dysfunction causes severe COVID-19, and hence is a target of intervention, or whether it is a symptom, is unclear because conventional observational studies are open to confounding. To obtain unconfounded estimates, we used Mendelian randomization to examine the role of kidney function in severe COVID-19. METHODS We used genome-wide significant, uncorrelated genetic variants to predict kidney function, in terms of estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR), and then assessed whether people with genetically instrumented higher eGFR or lower UACR, an indication of better kidney function, had a lower risk of severe COVID-19 (8779 cases, 1,001,875 controls), using the largest available cohorts with extensive genotyping. For comprehensiveness, we also examined their role in COVID-19 hospitalization (24,274 cases, 2,061,529 controls) and all COVID-19 (1,12,612 cases, 2,474,079 controls). RESULTS Genetically instrumented higher eGFR was associated with lower risk of severe COVID-19 (odds ratio (OR) 0.90, 95% confidence interval (CI) 0.83, 0.98) but not related to COVID-19 hospitalization or infection. Genetically instrumented UACR was not related to COVID-19. CONCLUSIONS Kidney function appears to be one of the key targets for severe COVID-19 treatment. Use of available medications to improve kidney function, such as antihypertensives, might be beneficial for COVID-19 treatment, with relevance to drug repositioning.
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Affiliation(s)
- Jie V Zhao
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 1/F, Patrick Manson Building, 7 Sassoon Road, Hong Kong, SAR, China.
| | - C Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 1/F, Patrick Manson Building, 7 Sassoon Road, Hong Kong, SAR, China
- City University of New York, School of Public Health and Health policy, New York, NY, USA
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400
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Xu K, Kiryluk K. Mapping GWAS loci to kidney genes and cell types. Kidney Int 2021; 101:447-450. [PMID: 34774560 DOI: 10.1016/j.kint.2021.10.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 10/21/2021] [Indexed: 11/29/2022]
Affiliation(s)
- Katherine Xu
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, New York, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, New York, USA.
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