151
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Zhang Y, Yang R, Dove A, Li X, Yang H, Li S, Wang J, Li WD, Zhao H, Xu W, Wang Y. Healthy lifestyle counteracts the risk effect of genetic factors on incident gout: a large population-based longitudinal study. BMC Med 2022; 20:138. [PMID: 35484537 PMCID: PMC9052486 DOI: 10.1186/s12916-022-02341-0] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 03/14/2022] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Risk genes linked to the development of gout have been identified, and lifestyle factors are related to gout risk. It remains unclear whether healthy lifestyle factors can mitigate the genetic risk of gout. Therefore, we aimed to explore whether and to what extent a healthy lifestyle can mitigate the risk of gout related to genetic factors. METHODS Within the UK Biobank, 416,481 gout-free participants (aged 37-74) were identified at baseline. Polygenic risk for gout was assessed and categorized as low (lowest tertile), middle (tertile 2), and high (highest tertile). Healthy lifestyle factors included no/moderate alcohol consumption, no smoking, physical activity, and a healthy diet. Participants were categorized into three groups according to their number of healthy lifestyle factors: unfavorable (0 or 1), intermediate (any 2), and favorable (3 or 4). Data were analyzed using Cox proportional hazard models. RESULTS Over the follow-up (median: 12.1 years), 6206 participants developed gout. Compared to low genetic risk, the hazard ratios (HRs) and 95% confidence intervals (CIs) of gout was 1.44 (1.35-1.54) for middle and 1.77 (1.66-1.89) for high genetic risk. The HRs (95% CIs) of gout were 0.63 (0.59-0.67) for a favorable lifestyle and 0.79 (0.75-0.85) for an intermediate lifestyle, compared to an unfavorable lifestyle. In joint effect analysis, compared to participants with low genetic predisposition and a favorable lifestyle, the HRs (95% CIs) of gout were 2.39 (2.12-2.70)/3.12 (2.79-3.52) in those with middle and high genetic predisposition plus unfavorable lifestyle profiles, and 1.53 (1.35-1.74)/1.98 (1.75-2.24) for those with middle and high genetic predisposition plus favorable lifestyle profiles, respectively. Moreover, compared to an unfavorable lifestyle, the HRs of gout related to a favorable lifestyle was 0.64 (95% CI, 0.56-0.73) for low genetic risk, 0.65 (95% CI, 0.58-0.72) for middle genetic risk, and 0.62 (95% CI, 0.57-0.69) for high genetic risk. There was a significant additive interaction between unfavorable lifestyle and high genetic risk on gout. CONCLUSIONS Healthy lifestyle was associated with a lower risk of gout and may attenuate the risk of gout related to genetic factors by almost a third.
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Affiliation(s)
- Yuan Zhang
- School of Public Health, Tianjin Medical University, Qixiangtai Road 22, Heping District, 300070, Tianjin, China
| | - Rongrong Yang
- School of Public Health, Tianjin Medical University, Qixiangtai Road 22, Heping District, 300070, Tianjin, China.,Public Health Science and Engineering College, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Abigail Dove
- Aging Research Center, Department of Neurobiology, Health Care Sciences and Society Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Xuerui Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Hongxi Yang
- School of Public Health, Tianjin Medical University, Qixiangtai Road 22, Heping District, 300070, Tianjin, China
| | - Shu Li
- School of Management, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Ju Wang
- School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China
| | - Wei-Dong Li
- Department of Genetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, USA
| | - Weili Xu
- Aging Research Center, Department of Neurobiology, Health Care Sciences and Society Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Yaogang Wang
- School of Public Health, Tianjin Medical University, Qixiangtai Road 22, Heping District, 300070, Tianjin, China. .,Public Health Science and Engineering College, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
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152
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Pang J, Pan X, Lin L, Li L, Yuan S, Han P, Ji X, Li H, Wang C, Chu Z, Wu H, Fan G, Du X, Ji A. Characterization of Plasma Extrachromosomal Circular DNA in Gouty Arthritis. Front Genet 2022; 13:859513. [PMID: 35464862 PMCID: PMC9019587 DOI: 10.3389/fgene.2022.859513] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 03/22/2022] [Indexed: 11/15/2022] Open
Abstract
Objective: Extrachromosomal circular DNA elements (eccDNAs) are known for their broad existence in cells and plasma, which may potentially play important roles in many biological processes. Our aim was to identify potentially functional or marked eccDNAs in gout patients. Methods: The Circle-Seq approach was applied for eccDNA detection from plasma in acute gout patients and healthy controls. Further analysis was performed on the distribution of genomic elements and eccDNA gene annotations in two groups. Results: We detected 57,216 and 109,683 eccDNAs from the acute gout and healthy control plasma, respectively. EccDNAs were mapped to the reference genome to identify diverse classes of genomic elements and there was no significant difference of eccDNAs on genomic element annotation between gout and control group. A total of 256 eccDNA-associated genes were detected as gout unique eccDNA genes, including COL1A1 and EPB42, which potentially contribute to hyperuricemia and gout, and a couple of genes involved in inflammation or immune response. Enrichment analysis showed that these eccDNA genes were highly correlated with defense response, stress response, and immune and inflammatory responses, including T cell receptor signaling pathway, Fc epsilon RI signaling pathway, and JAK-STAT signaling pathway. Conclusion: Our discovery reveals the novel potential biological roles of plasma eccDNAs in gouty arthritis.
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Affiliation(s)
- Jingyuan Pang
- Medical School, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Xiaoguang Pan
- Lars Bolund Institute of Regenerative Medicine, Qingdao-Europe Advanced Institute for Life Sciences, BGI-Qingdao, Qingdao, China
| | - Ling Lin
- Lars Bolund Institute of Regenerative Medicine, Qingdao-Europe Advanced Institute for Life Sciences, BGI-Qingdao, Qingdao, China
| | - Lei Li
- BGI-Qingdao, BGI-Shenzhen, Qingdao, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Shuai Yuan
- Emergency Department, Qingdao Third People's Hospital, Qingdao, China
| | - Peng Han
- Lars Bolund Institute of Regenerative Medicine, Qingdao-Europe Advanced Institute for Life Sciences, BGI-Qingdao, Qingdao, China
| | - Xiaopeng Ji
- Shandong Provincial Key Laboratory of Metabolic Diseases and Qingdao Key Laboratory of Gout, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Hailong Li
- Shandong Provincial Key Laboratory of Metabolic Diseases and Qingdao Key Laboratory of Gout, The Affiliated Hospital of Qingdao University, Qingdao, China.,Institute of Metabolic Diseases, Qingdao University, Qingdao, China
| | - Can Wang
- Shandong Provincial Key Laboratory of Metabolic Diseases and Qingdao Key Laboratory of Gout, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Zhaobin Chu
- BGI-Qingdao, BGI-Shenzhen, Qingdao, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Haoru Wu
- State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Nankai University, Tianjin, China
| | - Guangyi Fan
- BGI-Qingdao, BGI-Shenzhen, Qingdao, China.,BGI-Shenzhen, Shenzhen, China
| | - Xiao Du
- BGI-Qingdao, BGI-Shenzhen, Qingdao, China.,BGI-Shenzhen, Shenzhen, China
| | - Aichang Ji
- Shandong Provincial Key Laboratory of Metabolic Diseases and Qingdao Key Laboratory of Gout, The Affiliated Hospital of Qingdao University, Qingdao, China.,Institute of Metabolic Diseases, Qingdao University, Qingdao, China
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153
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Tao H, Zhong J, Mo Y, Liu W, Wang H. Exploring the Mechanism through which Phyllanthus emblica L. Extract Exerts Protective Effects against Acute Gouty Arthritis: A Network Pharmacology Study and Experimental Validation. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE : ECAM 2022; 2022:9748338. [PMID: 35449811 PMCID: PMC9017503 DOI: 10.1155/2022/9748338] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 02/23/2022] [Accepted: 03/11/2022] [Indexed: 01/05/2023]
Abstract
Increased uric acid levels and inflammatory reactions are the main factors considered responsible for the development of gouty arthritis. Phyllanthus emblica L. (PEL) has several promising pharmacological properties, including anti-inflammation and antioxidation. However, only a few studies have investigated its use for treating acute gouty arthritis (AGA), and the mechanism of action of PEL has not yet been clarified. The aim of this study was to verify the protective effects of PEL against gout and explore its underlying mechanism through network pharmacology and animal experiments. The main active components of the extract from PEL including mucic acid, mucic acid lactone, gallic acid, ethyl hexyl phthalate, and glucose were identified by UPLC-ESI-qTOF-MS. Network pharmacological analysis results revealed 13 active compounds in PEL and 85 related targets for the treatment of gout. The core mechanism of action of PEL is mainly associated with inflammation-related pathways, including the HIF-1, PI3K-Akt, TNF, and NOD-like receptor signaling pathways. Previous studies revealed that the NOD-like receptor signaling pathway, especially the NLRP3 inflammasome, plays an important role in the pathogenesis of AGA; therefore, we mainly investigated the effect of PEL on the NLRP3/ASC/caspase-1 pathway in gout rats. In the animal experiments, PEL was shown to have a satisfactory antigout effect, as it effectively reduced uric acid (UA) and xanthine oxidase (XOD) levels. In terms of inhibiting AGA-associated inflammatory reactions, our results showed that PEL significantly decreased the expression of NLRP3 and caspase-1 in ankle synoviocytes as well as the levels of downstream inflammatory factors, such as TNF-α, IL-10, and IL-1β in serum. Moreover, the results of our study show that PEL reduced MMP13 expression in the ankle synovium. Overall, the results of this study indicate that PEL exerted a therapeutic effect against AGA. Reducing uric acid levels, inhibiting inflammation, and decreasing the expression of MMP13 may be responsible for the therapeutic effect of PEL, which suggests that PEL can be further developed as a drug for the treatment of gout.
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Affiliation(s)
- Haolin Tao
- College of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou 510006, China
| | - Jingbin Zhong
- College of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou 510006, China
| | - Yingshi Mo
- College of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou 510006, China
| | - Wenbin Liu
- Guangdong Provincial Key Laboratory of Pharmaceutical Bioactive Substances, Guangdong Pharmaceutical University, Guangzhou 510006, China
| | - Hui Wang
- College of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou 510006, China
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154
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Reay WR, Kiltschewskij DJ, Geaghan MP, Atkins JR, Carr VJ, Green MJ, Cairns MJ. Genetic estimates of correlation and causality between blood-based biomarkers and psychiatric disorders. SCIENCE ADVANCES 2022; 8:eabj8969. [PMID: 35385317 PMCID: PMC8986101 DOI: 10.1126/sciadv.abj8969] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
There is a long-standing interest in exploring the relationship between blood-based biomarkers and psychiatric disorders, despite their causal role being difficult to resolve in observational studies. In this study, we leverage genome-wide association study data for a large panel of heritable serum biochemical traits to refine our understanding of causal effect in biochemical-psychiatric trait pairings. We observed widespread positive and negative genetic correlation between psychiatric disorders and biochemical traits. Causal inference was then implemented to distinguish causation from correlation, with strong evidence that C-reactive protein (CRP) exerts a causal effect on psychiatric disorders. Notably, CRP demonstrated both protective and risk-increasing effects on different disorders. Multivariable models that conditioned CRP effects on interleukin-6 signaling and body mass index supported that the CRP-schizophrenia relationship was not driven by these factors. Collectively, these data suggest that there are shared pathways that influence both biochemical traits and psychiatric illness.
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Affiliation(s)
- William R. Reay
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia
- Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Dylan J. Kiltschewskij
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia
- Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Michael P. Geaghan
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia
- Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Joshua R. Atkins
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia
| | - Vaughan J. Carr
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
- Department of Psychiatry, Monash University, Melbourne, VIC, Australia
| | - Melissa J. Green
- School of Psychiatry, University of New South Wales, Randwick, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Murray J. Cairns
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia
- Centre for Brain and Mental Health Research, Hunter Medical Research Institute, Newcastle, NSW, Australia
- Corresponding author.
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155
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Toyoda Y, Kawamura Y, Nakayama A, Morimoto K, Shimizu S, Tanahashi Y, Tamura T, Kondo T, Kato Y, Ichida K, Suzuki H, Shinomiya N, Kobayashi Y, Takada T, Matsuo H. OAT10/SLC22A13 Acts as a Renal Urate Re-Absorber: Clinico-Genetic and Functional Analyses With Pharmacological Impacts. Front Pharmacol 2022; 13:842717. [PMID: 35462902 PMCID: PMC9019507 DOI: 10.3389/fphar.2022.842717] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Accepted: 02/09/2022] [Indexed: 01/23/2023] Open
Abstract
Dysfunctional missense variant of organic anion transporter 10 (OAT10/SLC22A13), rs117371763 (c.1129C>T; p.R377C), is associated with a lower susceptibility to gout. OAT10 is a urate transporter; however, its physiological role in urate handling remains unclear. We hypothesized that OAT10 could be a renal urate re-absorber that will be a new molecular target of urate-lowering therapy like urate transporter 1 (URAT1, a physiologically-important well-known renal urate re-absorber) and aimed to examine the effect of OAT10 dysfunction on renal urate handling. For this purpose, we conducted quantitative trait locus analyses of serum urate and fractional excretion of uric acid (FEUA) using samples obtained from 4,521 Japanese males. Moreover, we performed immunohistochemical and functional analyses to assess the molecular properties of OAT10 as a renal urate transporter and evaluated its potential interaction with urate-lowering drugs. Clinico-genetic analyses revealed that carriers with the dysfunctional OAT10 variant exhibited significantly lower serum urate levels and higher FEUA values than the non-carriers, indicating that dysfunction of OAT10 increases renal urate excretion. Given the results of functional assays and immunohistochemical analysis demonstrating the expression of human OAT10 in the apical side of renal proximal tubular cells, our data indicate that OAT10 is involved in the renal urate reabsorption in renal proximal tubules from urine. Additionally, we found that renal OAT10 inhibition might be involved in the urate-lowering effect of losartan and lesinurad which exhibit uricosuric effects; indeed, losartan, an approved drug, inhibits OAT10 more strongly than URAT1. Accordingly, OAT10 can be a novel potential molecular target for urate-lowering therapy.
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Affiliation(s)
- Yu Toyoda
- Department of Pharmacy, The University of Tokyo Hospital, Tokyo, Japan
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, Saitama, Japan
| | - Yusuke Kawamura
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, Saitama, Japan
| | - Akiyoshi Nakayama
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, Saitama, Japan
| | - Keito Morimoto
- Department of Pharmacy, The University of Tokyo Hospital, Tokyo, Japan
| | - Seiko Shimizu
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, Saitama, Japan
| | - Yuki Tanahashi
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, Saitama, Japan
| | - Takashi Tamura
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Takaaki Kondo
- Program in Radiological and Medical Laboratory Sciences, Pathophysiological Laboratory Science, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Yasufumi Kato
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Kimiyoshi Ichida
- Department of Pathophysiology, Tokyo University of Pharmacy and Life Sciences, Tokyo, Japan
| | - Hiroshi Suzuki
- Department of Pharmacy, The University of Tokyo Hospital, Tokyo, Japan
| | - Nariyoshi Shinomiya
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, Saitama, Japan
| | - Yasushi Kobayashi
- Department of Anatomy and Neurobiology, National Defense Medical College, Saitama, Japan
| | - Tappei Takada
- Department of Pharmacy, The University of Tokyo Hospital, Tokyo, Japan
- *Correspondence: Tappei Takada, ; Hirotaka Matsuo,
| | - Hirotaka Matsuo
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, Saitama, Japan
- *Correspondence: Tappei Takada, ; Hirotaka Matsuo,
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156
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Chen D, Xu H, Sun L, Li Y, Wang T, Li Y. Assessing causality between osteoarthritis with urate levels and gout: a bidirectional Mendelian randomization study. Osteoarthritis Cartilage 2022; 30:551-558. [PMID: 34896305 DOI: 10.1016/j.joca.2021.12.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 11/04/2021] [Accepted: 12/02/2021] [Indexed: 02/02/2023]
Abstract
OBJECTIVES The bidirectional association between osteoarthritis (OA) and urate levels and gout, though well-documented, is inconclusive. This Mendelian randomization (MR) study aims to examine the bidirectional causality between OA and urate levels as well as gout. METHODS We used summary statistics data for serum urate levels from 288,649 CKDGen participants and gout from 69,374 Global Urate Genetics Consortium participants. The summary statistics data for OA were obtained from genome-wide association studies including up to 826,690 participants of mainly European ancestry. MR was performed using established analytical methods including the Wald ratio, inverse variance weighted (IVW), weighted median (WM) and MR-Egger. RESULTS Genetically determined urate levels [IVW odds ratio (OR) = 0.99, 95% confidence interval (CI) = 0.96, 1.02, P = 0.484] and gout (Wald ratio OR = 1.00, 95% CI = 0.98, 1.02, P = 0.908) were not associated with the risk of total OA. In site-specific OA analyses, there was no causal effect of urate levels on knee, hip, spine, thumb and hand OA, and no evidence was provided that gout increased the risk of OA at any site. In the reverse MR analyses, we found no causal effect of total OA on urate levels (IVW Beta = -0.011, 95% CI = -0.095, 0.074, P = 0.807) or gout (IVW OR = 1.05, 95% CI = 0.66, 1.68, P = 0.839). A null effect of site-specific OA was also observed. CONCLUSION Our MR study supports no bidirectional causal effect of urate levels and gout on total and site-specific OA.
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Affiliation(s)
- D Chen
- School of Public Health, Hangzhou Medical College, Hangzhou, 310053, China
| | - H Xu
- School of Public Health, Hangzhou Medical College, Hangzhou, 310053, China
| | - L Sun
- Department of Orthopaedics, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Y Li
- Department of Rheumatology and Immunology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, 310014, China
| | - T Wang
- Department of Rheumatology and Immunology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, 310014, China
| | - Y Li
- School of Public Health, Hangzhou Medical College, Hangzhou, 310053, China.
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157
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Cheng Y, Li Y, Scherer N, Grundner-Culemann F, Lehtimäki T, Mishra BH, Raitakari OT, Nauck M, Eckardt KU, Sekula P, Schultheiss UT, on behalf of the GCKD investigators. Genetics of osteopontin in patients with chronic kidney disease: The German Chronic Kidney Disease study. PLoS Genet 2022; 18:e1010139. [PMID: 35385482 PMCID: PMC9015153 DOI: 10.1371/journal.pgen.1010139] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 04/18/2022] [Accepted: 03/09/2022] [Indexed: 11/18/2022] Open
Abstract
Osteopontin (OPN), encoded by SPP1, is a phosphorylated glycoprotein predominantly synthesized in kidney tissue. Increased OPN mRNA and protein expression correlates with proteinuria, reduced creatinine clearance, and kidney fibrosis in animal models of kidney disease. But its genetic underpinnings are incompletely understood. We therefore conducted a genome-wide association study (GWAS) of OPN in a European chronic kidney disease (CKD) population. Using data from participants of the German Chronic Kidney Disease (GCKD) study (N = 4,897), a GWAS (minor allele frequency [MAF]≥1%) and aggregated variant testing (AVT, MAF<1%) of ELISA-quantified serum OPN, adjusted for age, sex, estimated glomerular filtration rate (eGFR), and urinary albumin-to-creatinine ratio (UACR) was conducted. In the project, GCKD participants had a mean age of 60 years (SD 12), median eGFR of 46 mL/min/1.73m2 (p25: 37, p75: 57) and median UACR of 50 mg/g (p25: 9, p75: 383). GWAS revealed 3 loci (p<5.0E-08), two of which replicated in the population-based Young Finns Study (YFS) cohort (p<1.67E-03): rs10011284, upstream of SPP1 encoding the OPN protein and related to OPN production, and rs4253311, mapping into KLKB1 encoding prekallikrein (PK), which is processed to kallikrein (KAL) implicated through the kinin-kallikrein system (KKS) in blood pressure control, inflammation, blood coagulation, cancer, and cardiovascular disease. The SPP1 gene was also identified by AVT (p = 2.5E-8), comprising 7 splice-site and missense variants. Among others, downstream analyses revealed colocalization of the OPN association signal at SPP1 with expression in pancreas tissue, and at KLKB1 with various plasma proteins in trans, and with phenotypes (bone disorder, deep venous thrombosis) in human tissue. In summary, this GWAS of OPN levels revealed two replicated associations. The KLKB1 locus connects the function of OPN with PK, suggestive of possible further post-translation processing of OPN. Further studies are needed to elucidate the complex role of OPN within human (patho)physiology.
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Affiliation(s)
- Yurong Cheng
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Yong Li
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
| | - Nora Scherer
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
- Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Freiburg, Germany
| | - Franziska Grundner-Culemann
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, 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
| | - Binisha H. 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
| | - 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
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charité, University-Medicine, Berlin, Germany
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
| | - Ulla T. Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
- Department of Medicine IV, Nephrology and Primary Care, Faculty of Medicine and Medical Center—University of Freiburg, Freiburg, Germany
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158
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Butts B, Brown JA, Denney TS, Ballinger S, Lloyd SG, Oparil S, Sanders P, Merriman TR, Gaffo A, Singh J, Kelley EE, Calhoun DA, Dell'Italia LJ. Racial Differences in XO (Xanthine Oxidase) and Mitochondrial DNA Damage-Associated Molecular Patterns in Resistant Hypertension. Hypertension 2022; 79:775-784. [PMID: 35164526 PMCID: PMC10652275 DOI: 10.1161/hypertensionaha.121.18298] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 01/22/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND We previously reported increased plasma XO (xanthine oxidase) activity in patients with resistant hypertension. Increased XO can cause mitochondrial DNA damage and promote release of fragments called mitochondrial DNA damage-associated molecular patterns (mtDNA DAMPs). Here, we report racial differences in XO activity and mtDNA DAMPs in Black and White adults with resistant hypertension. METHODS This retrospective study includes 91 resistant hypertension patients (44% Black, 47% female) with blood pressure >140/90 mm Hg on ≥4 medications and 37 normotensive controls (30% Black, 54% female) with plasma XO activity, mtDNA DAMPs, and magnetic resonance imaging of left ventricular morphology and function. RESULTS Black-resistant hypertension patients were younger (mean age 52±10 versus 59±10 years; P=0.001), with higher XO activity and left ventricular wall thickness, and worse diastolic dysfunction than White resistant hypertension patients. Urinary sodium excretion (mg/24 hour per kg) was positively related to left ventricular end-diastolic volume (r=0.527, P=0.001) and left ventricular mass (r=0.394, P=0.02) among Black but not White resistant hypertension patients. Patients with resistant hypertension had increased mtDNA DAMPs versus controls (P<0.001), with Black mtDNA DAMPS greater than Whites (P<0.001). Transmission electron microscopy of skeletal muscle biopsies in resistant hypertension patients demonstrates mitochondria cristae lysis, myofibrillar loss, large lipid droplets, and glycogen accumulation. CONCLUSIONS These data warrant a large study to examine the role of XO and mitochondrial mtDNA DAMPs in cardiac remodeling and heart failure in Black adults with resistant hypertension.
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Affiliation(s)
- Brittany Butts
- Division of Cardiovascular Disease, University of Alabama at Birmingham (UAB) School of Medicine (SOM) (B.B., S.G.L., S.O., P.S., D.A.C., L.J.D.)
| | - Jamelle A Brown
- Center for Free Radical Biology and Department of Pathology, UAB SOM (J.A.B., S.B.)
| | - Thomas S Denney
- Department of Electrical and Computer Engineering, Auburn University (T.S.D.)
| | - Scott Ballinger
- Center for Free Radical Biology and Department of Pathology, UAB SOM (J.A.B., S.B.)
| | - Steven G Lloyd
- Division of Cardiovascular Disease, University of Alabama at Birmingham (UAB) School of Medicine (SOM) (B.B., S.G.L., S.O., P.S., D.A.C., L.J.D.)
- Birmingham Department of Veterans Affairs Health Care System (S.G.L., P.S., A.G., J.S., L.J.D.)
| | - Suzanne Oparil
- Division of Cardiovascular Disease, University of Alabama at Birmingham (UAB) School of Medicine (SOM) (B.B., S.G.L., S.O., P.S., D.A.C., L.J.D.)
| | - Paul Sanders
- Division of Cardiovascular Disease, University of Alabama at Birmingham (UAB) School of Medicine (SOM) (B.B., S.G.L., S.O., P.S., D.A.C., L.J.D.)
- Nephrology Research and Training Center and Division of Nephrology UAB SOM (P.S.)
- Birmingham Department of Veterans Affairs Health Care System (S.G.L., P.S., A.G., J.S., L.J.D.)
| | - Tony R Merriman
- Division of Clinical Immunology and Rheumatology, UAB SOM (T.R.M., A.G., J.S.)
| | - Angelo Gaffo
- Division of Clinical Immunology and Rheumatology, UAB SOM (T.R.M., A.G., J.S.)
- Birmingham Department of Veterans Affairs Health Care System (S.G.L., P.S., A.G., J.S., L.J.D.)
| | - Jasvinder Singh
- Division of Clinical Immunology and Rheumatology, UAB SOM (T.R.M., A.G., J.S.)
- Birmingham Department of Veterans Affairs Health Care System (S.G.L., P.S., A.G., J.S., L.J.D.)
| | - Eric E Kelley
- Department of Physiology and Pharmacology, West Virginia University (E.E.K.)
| | - David A Calhoun
- Division of Cardiovascular Disease, University of Alabama at Birmingham (UAB) School of Medicine (SOM) (B.B., S.G.L., S.O., P.S., D.A.C., L.J.D.)
| | - Louis J Dell'Italia
- Division of Cardiovascular Disease, University of Alabama at Birmingham (UAB) School of Medicine (SOM) (B.B., S.G.L., S.O., P.S., D.A.C., L.J.D.)
- Birmingham Department of Veterans Affairs Health Care System (S.G.L., P.S., A.G., J.S., L.J.D.)
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159
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Park JS, Kim Y, Kang J. Genome-wide meta-analysis revealed several genetic loci associated with serum uric acid levels in Korean population: an analysis of Korea Biobank data. J Hum Genet 2022; 67:231-237. [PMID: 34719683 DOI: 10.1038/s10038-021-00991-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 10/19/2021] [Accepted: 10/20/2021] [Indexed: 11/09/2022]
Abstract
The serum uric acid (SUA) level is an important determinant of gout, hypertension, metabolic syndrome, and cardiovascular disease. Although previous genome-wide studies have identified multiple genetic variants associated with SUA, most genetic analyses have focused on individuals with European ancestry; thus, understanding of the genetic architecture of SUA is currently limited for Asian populations. We conducted a genome-wide meta-analysis based on Korea Biobank data consistent with three cohorts; namely, the Korean Genome and Epidemiology Study (KoGES) Ansan and Ansung, KoGES Health Examinee, and KoGES Cardiovascular Disease Association studies. In total, 60,585 participants aged ≥40 years were included in the analysis of the three cohorts. We used logistic regression analyses to perform genome-wide association study (GWAS) adjustments for confounding variables. Subsequently, a meta-analysis was conducted by combining the analyses of the three GWASs. We identified 8,105 variants at 22 genetic loci with a P value < 5 × 10-8. Among these, six novel genetic loci associated with SUA in the Korean population were identified (rs4715517 in HCRTR2, rs145099458 in 3.2 kb 3' of MLXIPL, rs1137642 in B4GALT1, rs659107 in LOC105378410, rs7919329 in LOC107984274, and rs2240751 in MFSD12). Our meta-analysis provides insights into the genetic architecture of SUA in the Korean population. Further studies are warranted to replicate the study results and elucidate the specific role of these variants in SUA homeostasis.
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Affiliation(s)
- Jin Sung Park
- Department of Medicine, Kosin University Gospel Hospital, Kosin University College of Medicine, Busan, Republic of Korea
| | - Yunkyung Kim
- Division of Rheumatology, Department of Internal Medicine, Kosin University Gospel Hospital, Kosin University College of Medicine, Busan, Republic of Korea
| | - Jihun Kang
- Department of Family Medicine, Kosin University Gospel Hospital, Kosin University College of Medicine, Busan, Republic of Korea.
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160
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Ho LJ, Lu CH, Su RY, Lin FH, Su SC, Kuo FC, Chu NF, Hung YJ, Liu JS, Hsieh CH. Association between glucokinase regulator gene polymorphisms and serum uric acid levels in Taiwanese adolescents. Sci Rep 2022; 12:5519. [PMID: 35365700 PMCID: PMC8975867 DOI: 10.1038/s41598-022-09393-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Accepted: 03/08/2022] [Indexed: 11/20/2022] Open
Abstract
The glucokinase regulator gene (GCKR) is located on chromosome 2p23. It plays a crucial role in maintaining plasma glucose homeostasis and metabolic traits. Recently, genome-wide association studies have revealed a positive association between hyperuricemia and GCKR variants in adults. This study investigated this genetic association in Taiwanese adolescents. Data were collected from our previous cross-sectional study (Taipei Children Heart Study). The frequencies of various genotypes (CC, CT, and TT) or alleles (C and T) of the GCKR intronic single-nucleotide polymorphism (SNP) rs780094 and the coding SNP rs1260326 (Pro446Leu, a common 1403C-T transition) were compared between a total of 968 Taiwanese adolescents (473 boys, 495 girls) with hyperuricemia or normal uric acid levels on the basis of gender differences. Logistic and linear regression analyses explored the role of GCKR in abnormal uric acid (UA) levels. Boys had higher UA levels than girls (6.68 ± 1.29 and 5.23 ± 0.95 mg/dl, respectively, p < 0.001). The analysis of both SNPs in girls revealed that the T allele was more likely to appear in patients with hyperuricemia than the C allele. After adjusting for confounders, the odds ratio (OR) for hyperuricemia incidence in the TT genotype was 1.75 (95% confidence interval [CI] 1.02–3.00), which was higher than that in the C allele carriers in rs1260326 in the girl population. Similarly, the TT genotypes had a higher risk of hyperuricemia, with an OR of 2.29 (95% CI 1.11–4.73) for rs1260326 and 2.28 (95% CI 1.09–4.75) for rs780094, than the CC genotype in girl adolescents. The T (Leu446) allele of GCKR rs1260326 polymorphism is associated with higher UA levels in Taiwanese adolescent girls.
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Affiliation(s)
- Li-Ju Ho
- Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan, ROC.,Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, No. 325, Section 2, Cheng-Kung Road, Neihu District, Taipei City, 11490, Taiwan, ROC
| | - Chieh-Hua Lu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, No. 325, Section 2, Cheng-Kung Road, Neihu District, Taipei City, 11490, Taiwan, ROC
| | - Ruei-Yu Su
- Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan, ROC.,Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC.,Department of Pathology and Laboratory Medicine, Taoyuan Armed Forces General Hospital, Taoyuan, Taiwan, ROC
| | - Fu-Huang Lin
- School of Public Health, National Defense Medical Center, Taipei, Taiwan, ROC
| | - Sheng-Chiang Su
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, No. 325, Section 2, Cheng-Kung Road, Neihu District, Taipei City, 11490, Taiwan, ROC
| | - Feng-Chih Kuo
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, No. 325, Section 2, Cheng-Kung Road, Neihu District, Taipei City, 11490, Taiwan, ROC
| | - Nain-Feng Chu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, No. 325, Section 2, Cheng-Kung Road, Neihu District, Taipei City, 11490, Taiwan, ROC.,School of Public Health, National Defense Medical Center, Taipei, Taiwan, ROC
| | - Yi-Jen Hung
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, No. 325, Section 2, Cheng-Kung Road, Neihu District, Taipei City, 11490, Taiwan, ROC
| | - Jhih-Syuan Liu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, No. 325, Section 2, Cheng-Kung Road, Neihu District, Taipei City, 11490, Taiwan, ROC.
| | - Chang-Hsun Hsieh
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, No. 325, Section 2, Cheng-Kung Road, Neihu District, Taipei City, 11490, Taiwan, ROC.
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161
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The Relationship between Alcohol Consumption and Gout: A Mendelian Randomization Study. Genes (Basel) 2022; 13:genes13040557. [PMID: 35456363 PMCID: PMC9028689 DOI: 10.3390/genes13040557] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 03/12/2022] [Accepted: 03/16/2022] [Indexed: 01/27/2023] Open
Abstract
Gout is a disease that manifests itself after decades of following a high-purine diet, with excessive alcohol consumption assumed to be one of the main contributors to the development of the disease. This study performs a Mendelian randomization (MR) analysis to determine whether alcohol consumption causally affects the risk of developing both hyperuricemia and gout. The results indicate that genetically predicted drinks consumed per week have no causal effect on neither the risk of gout (p = 0.35), nor serum uric acid levels (p = 0.73). For MR analysis in the other direction, genetic risk of gout was significantly associated with drinks per week (p = 0.03). Furthermore, the results of the MR analysis were verified in a cohort of individuals diagnosed with hyperuricemia and gout, comprising of alcohol-consuming and alcohol-abstaining subgroups. When split by alcohol status, the serum uric acid levels failed to show a significant difference in both gout (p = 0.92) and hyperuricemia (p = 0.23) subgroups. Overall, the results suggest that increased alcohol consumption does not play a causal role in the development of gout.
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162
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Fu M, Chang TS. Phenome-Wide Association Study of Polygenic Risk Score for Alzheimer's Disease in Electronic Health Records. Front Aging Neurosci 2022; 14:800375. [PMID: 35370621 PMCID: PMC8965623 DOI: 10.3389/fnagi.2022.800375] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Accepted: 02/04/2022] [Indexed: 11/13/2022] Open
Abstract
Alzheimer's disease (AD) is the most common form of dementia and a growing public health burden in the United States. Significant progress has been made in identifying genetic risk for AD, but limited studies have investigated how AD genetic risk may be associated with other disease conditions in an unbiased fashion. In this study, we conducted a phenome-wide association study (PheWAS) by genetic ancestry groups within a large academic health system using the polygenic risk score (PRS) for AD. PRS was calculated using LDpred2 with genome-wide association study (GWAS) summary statistics. Phenotypes were extracted from electronic health record (EHR) diagnosis codes and mapped to more clinically meaningful phecodes. Logistic regression with Firth's bias correction was used for PRS phenotype analyses. Mendelian randomization was used to examine causality in significant PheWAS associations. Our results showed a strong association between AD PRS and AD phenotype in European ancestry (OR = 1.26, 95% CI: 1.13, 1.40). Among a total of 1,515 PheWAS tests within the European sample, we observed strong associations of AD PRS with AD and related phenotypes, which include mild cognitive impairment (MCI), memory loss, and dementias. We observed a phenome-wide significant association between AD PRS and gouty arthropathy (OR = 0.90, adjusted p = 0.05). Further causal inference tests with Mendelian randomization showed that gout was not causally associated with AD. We concluded that genetic predisposition of AD was negatively associated with gout, but gout was not a causal risk factor for AD. Our study evaluated AD PRS in a real-world EHR setting and provided evidence that AD PRS may help to identify individuals who are genetically at risk of AD and other related phenotypes. We identified non-neurodegenerative diseases associated with AD PRS, which is essential to understand the genetic architecture of AD and potential side effects of drugs targeting genetic risk factors of AD. Together, these findings expand our understanding of AD genetic and clinical risk factors, which provide a framework for continued research in aging with the growing number of real-world EHR linked with genetic data.
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Affiliation(s)
- Mingzhou Fu
- Movement Disorders Program, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Medical Informatics Home Area, Department of Bioinformatics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Timothy S. Chang
- Movement Disorders Program, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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163
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Sun M, Sun W, Zhao X, Li Z, Dalbeth N, Ji A, He Y, Qu H, Zheng G, Ma L, Wang J, Shi Y, Fang X, Chen H, Merriman TR, Li C. A machine learning-assisted model for renal urate underexcretion with genetic and clinical variables among Chinese men with gout. Arthritis Res Ther 2022; 24:67. [PMID: 35264217 PMCID: PMC8905745 DOI: 10.1186/s13075-022-02755-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 02/28/2022] [Indexed: 02/08/2023] Open
Abstract
OBJECTIVES The objective of this study was to develop and validate a prediction model for renal urate underexcretion (RUE) in male gout patients. METHODS Men with gout enrolled from multicenter cohorts in China were analyzed as the development and validation data sets. The RUE phenotype was defined as fractional excretion of uric acid (FEUA) <5.5%. Candidate genetic and clinical features were screened by the least absolute shrinkage and selection operator (LASSO) with 10-fold cross-validation. Machine learning algorithms (stochastic gradient descent (SGD), logistic regression, support vector machine) were performed to construct a predictive classifier of RUE. Models were assessed by the area under the receiver operating characteristic curve (AUC) and the precision-recall curve (PRC). RESULTS One thousand two hundred thirty-eight and two thousand twenty-three patients were enrolled as the development and validation cohorts, with 1220 and 754 randomly chosen patients genotyped, respectively. Rs3775948.GG of SLC2A9/GLUT9, rs504915.AA of NRXN2/URAT1, and 7 clinical features (age, hypertension, nephrolithiasis, blood glucose, serum urate, urea nitrogen, and creatinine) were generated by LASSO. Two additional SNP variants (rs2231142.GG of ABCG2 and rs11231463.GG of SLC22A9/OAT7) were selected based on their contributions to gout in the development cohort and their reported effects on renal urate handling. The optimized classifiers yielded AUCs of ~0.914 and PRCs of ~0.980 using these 11 variables. The SGD model was conducted in the validation cohort with an AUC of 0.899 and the PRC of 0.957. CONCLUSIONS A prediction model for RUE composed of four SNPs and readily accessible clinical features was established with acceptable accuracy for men with gout.
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Affiliation(s)
- Mingshu Sun
- Shandong Provincial Clinical Research Center for Immune Diseases and Gout & Shandong Provincial Key Laboratory of Metabolic Diseases, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Wenyan Sun
- Shandong Provincial Clinical Research Center for Immune Diseases and Gout & Shandong Provincial Key Laboratory of Metabolic Diseases, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xuetong Zhao
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Zhiqiang Li
- Shandong Provincial Clinical Research Center for Immune Diseases and Gout & Shandong Provincial Key Laboratory of Metabolic Diseases, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Nicola Dalbeth
- Department of Medicine, University of Auckland, Auckland, New Zealand
| | - Aichang Ji
- Shandong Provincial Clinical Research Center for Immune Diseases and Gout & Shandong Provincial Key Laboratory of Metabolic Diseases, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yuwei He
- Shandong Provincial Clinical Research Center for Immune Diseases and Gout & Shandong Provincial Key Laboratory of Metabolic Diseases, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Hongzhu Qu
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Guangmin Zheng
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Lidan Ma
- Shandong Provincial Clinical Research Center for Immune Diseases and Gout & Shandong Provincial Key Laboratory of Metabolic Diseases, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Jiayi Wang
- Department of Pharmacy, Peking University First Hospital, Beijing, China
| | - Yongyong Shi
- Shandong Provincial Clinical Research Center for Immune Diseases and Gout & Shandong Provincial Key Laboratory of Metabolic Diseases, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xiangdong Fang
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Haibing Chen
- Department of Endocrinology and Metabolism, Shanghai 10th People's Hospital, Tongji University, Shanghai, China.
| | - Tony R Merriman
- Department of Biochemistry, University of Otago, Dunedin, New Zealand. .,Department of Medicine, University of Alabama Birmingham, Birmingham, AL, USA.
| | - Changgui Li
- Shandong Provincial Clinical Research Center for Immune Diseases and Gout & Shandong Provincial Key Laboratory of Metabolic Diseases, The Affiliated Hospital of Qingdao University, Qingdao, China.
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164
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Roman YM, McClish D, Price ET, Sabo RT, Woodward OM, Mersha TB, Shah N, Armada A, Terkeltaub R. Cardiometabolic genomics and pharmacogenomics investigations in Filipino Americans: Steps towards precision health and reducing health disparities. AMERICAN HEART JOURNAL PLUS : CARDIOLOGY RESEARCH AND PRACTICE 2022; 15:100136. [PMID: 35647570 PMCID: PMC9139029 DOI: 10.1016/j.ahjo.2022.100136] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 04/18/2022] [Accepted: 04/18/2022] [Indexed: 12/26/2022]
Abstract
Background Filipino Americans (FAs) are the third-largest Asian American subgroup in the United States (US). Some studies showed that FAs experience more cardiometabolic diseases (CMDs) than other Asian subgroups and non-Hispanic Whites. The increased prevalence of CMD observed in FAs could be due to genetics and social/dietary lifestyles. While FAs are ascribed as an Asian group, they have higher burdens of CMD, and adverse social determinants of health compared to other Asian subgroups. Therefore, studies to elucidate how FAs might develop CMD and respond to medications used to manage CMD are warranted. The ultimate goals of this study are to identify potential mechanisms for reducing CMD burden in FAs and to optimize therapeutic drug selection. Collectively, these investigations could reduce the cardiovascular health disparities among FAs. Rationale and design This is a cross-sectional epidemiological design to enroll 300 self-identified Filipino age 18 yrs. or older without a history of cancer and/or organ transplant from Virginia, Washington DC, and Maryland. Once consented, a health questionnaire and disease checklist are administered to participants, and anthropometric data and other vital signs are collected. When accessible, we collect blood samples to measure basic blood biochemistry, lipids, kidney, and liver functions. We also extract DNA from the blood or saliva for genetic and pharmacogenetic analyses. CMD prevalence in FAs will be compared to the US population. Finally, we will conduct multivariate analyses to ascertain the role of genetic and non-genetic factors in developing CMD in FAs. Virginia Commonwealth University IRB approved all study materials (Protocol HM20018500). Summary This is the first community-based study to involve FAs in genomics research. The study is actively recruiting participants. Participant enrollment is ongoing. At the time of this publication, the study has enrolled 97 participants. This ongoing study is expected to inform future research to reduce cardiovascular health disparities among FAs.
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Affiliation(s)
- Youssef M. Roman
- Department of Pharmacotherapy and Outcomes Science, 410 N 12th Street, Virginia Commonwealth University, School of Pharmacy, Richmond, VA 23298, United States of America
| | - Donna McClish
- Department of Biostatistics, 830 East Main Street, One Capitol Square 740, Virginia Commonwealth University, School of Medicine, Richmond, VA 23329, United States of America
| | - Elvin T. Price
- Department of Pharmacotherapy and Outcomes Science, 410 N 12th Street, Virginia Commonwealth University, School of Pharmacy, Richmond, VA 23298, United States of America
| | - Roy T. Sabo
- Department of Biostatistics, 830 East Main Street, One Capitol Square 740, Virginia Commonwealth University, School of Medicine, Richmond, VA 23329, United States of America
| | - Owen M. Woodward
- Department of Physiology, University of Maryland School of Medicine, 685 W. Baltimore St., HSF1 580F, Baltimore, MD 21201, United States of America
| | - Tesfaye B. Mersha
- Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati, 3333 Burnet Avenue, MLC 7037, Cincinnati, OH 45229-3026, United States of America
| | - Nehal Shah
- Division of Rheumatology, Allergy, and Immunology, 1112 East Clay Street, VCU Health Sciences Research Building, Room 4-110, Virginia Commonwealth University, School of Medicine, Richmond, VA 23298-0263, United States of America
| | - Andrew Armada
- Filipino American Association of Central Virginia, 7117 Galax Road, Richmond, VA 23228, United States of America
| | - Robert Terkeltaub
- 9-SDVAHCS, Division of Rheumatology, Allergy, and Immunology, USCD School of Medicine, 9500 Gilman Drive, La Jolla, CA 92093, United States of America
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165
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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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166
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An effector index to predict target genes at GWAS loci. Hum Genet 2022; 141:1431-1447. [PMID: 35147782 DOI: 10.1007/s00439-022-02434-z] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 01/15/2022] [Indexed: 11/04/2022]
Abstract
Drug development and biological discovery require effective strategies to map existing genetic associations to causal genes. To approach this problem, we selected 12 common diseases and quantitative traits for which highly powered genome-wide association studies (GWAS) were available. For each disease or trait, we systematically curated positive control gene sets from Mendelian forms of the disease and from targets of medicines used for disease treatment. We found that these positive control genes were highly enriched in proximity of GWAS-associated single-nucleotide variants (SNVs). We then performed quantitative assessment of the contribution of commonly used genomic features, including open chromatin maps, expression quantitative trait loci (eQTL), and chromatin conformation data. Using these features, we trained and validated an Effector Index (Ei), to map target genes for these 12 common diseases and traits. Ei demonstrated high predictive performance, both with cross-validation on the training set, and an independently derived set for type 2 diabetes. Key predictive features included coding or transcript-altering SNVs, distance to gene, and open chromatin-based metrics. This work outlines a simple, understandable approach to prioritize genes at GWAS loci for functional follow-up and drug development, and provides a systematic strategy for prioritization of GWAS target genes.
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167
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Choi HK, McCormick N, Yokose C. Excess comorbidities in gout: the causal paradigm and pleiotropic approaches to care. Nat Rev Rheumatol 2022; 18:97-111. [PMID: 34921301 DOI: 10.1038/s41584-021-00725-9] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/18/2021] [Indexed: 02/07/2023]
Abstract
Gout is a common hyperuricaemic metabolic condition that leads to painful inflammatory arthritis and a high comorbidity burden, especially cardiometabolic-renal (CMR) conditions, including hypertension, myocardial infarction, stroke, obesity, hyperlipidaemia, type 2 diabetes mellitus and chronic kidney disease. Substantial advances have been made in our understanding of the excess CMR burden in gout, ranging from pathogenesis underlying excess CMR comorbidities, inferring causal relationships from Mendelian randomization studies, and potentially discovering urate crystals in coronary arteries using advanced imaging, to clinical trials and observational studies. Despite many studies finding an independent association between blood urate levels and risk of incident CMR events, Mendelian randomization studies have largely found that serum urate is not causal for CMR end points or intermediate risk factors or outcomes (such as kidney function, adiposity, metabolic syndrome, glycaemic traits or blood lipid concentrations). Although limited, randomized controlled trials to date in adults without gout support this conclusion. If imaging studies suggesting that monosodium urate crystals are deposited in coronary plaques in patients with gout are confirmed, it is possible that these crystals might have a role in the inflammatory pathogenesis of increased cardiovascular risk in patients with gout; removing monosodium urate crystals or blocking the inflammatory pathway could reduce this excess risk. Accordingly, data for CMR outcomes with these urate-lowering or anti-inflammatory therapies in patients with gout are needed. In the meantime, highly pleiotropic CMR and urate-lowering benefits of sodium-glucose cotransporter 2 (SGLT2) inhibitors and key lifestyle measures could play an important role in comorbidity care, in conjunction with effective gout care based on target serum urate concentrations according to the latest guidelines.
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Affiliation(s)
- Hyon K Choi
- Clinical Epidemiology Program, Division of Rheumatology, Allergy, and Immunology, Massachusetts General Hospital, Boston, MA, USA.
- Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
- Arthritis Research Canada, Vancouver, British Columbia, Canada.
| | - Natalie McCormick
- Clinical Epidemiology Program, Division of Rheumatology, Allergy, and Immunology, Massachusetts General Hospital, Boston, MA, USA
- Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Arthritis Research Canada, Vancouver, British Columbia, Canada
| | - Chio Yokose
- Clinical Epidemiology Program, Division of Rheumatology, Allergy, and Immunology, Massachusetts General Hospital, Boston, MA, USA
- Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
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Yuan S, Yu L, Gou W, Wang L, Sun J, Li D, Lu Y, Cai X, Yu H, Yuan C, Zheng JS, Larsson SC, Theodoratou E, Li X. Health effects of high serum calcium levels: Updated phenome-wide Mendelian randomisation investigation and review of Mendelian randomisation studies. EBioMedicine 2022; 76:103865. [PMID: 35134646 PMCID: PMC8844774 DOI: 10.1016/j.ebiom.2022.103865] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Revised: 01/18/2022] [Accepted: 01/19/2022] [Indexed: 02/08/2023] Open
Abstract
Background Calcium plays a role in a wide range of biological functions. Here we conducted a phenome-wide Mendelian randomisation (MR-PheWAS) analysis and a systematic review for MR studies to comprehensively investigate the health effects of serum calcium. Methods One-hundred and thirty genetic variants strongly associated with serum calcium levels were used as instrumental variables. A phenome-wide association analysis (PheWAS) was conducted to examine the associations of genetically predicted serum calcium with 1473 distinct phenotypes in the UK Biobank including 339,197 individuals. Observed associations in PheWAS were further tested for replication in two-sample MR replication analysis. A systematic review for MR studies on serum calcium was performed to synthesize the published evidence and compare with the current MR-PheWAS findings. Findings Higher genetically predicted calcium levels were associated with decreased risk of 5 diseases in dermatologic and musculoskeletal systems and increased risk of 17 diseases in circulatory, digestive, endocrine, genitourinary and immune systems. Eight associations were replicated in two-sample MR analysis. These included decreased risk of osteoarthritis and increased risk of coronary artery disease, myocardial infarction, coronary atherosclerosis, hyperparathyroidism, disorder of parathyroid gland, gout, and calculus of kidney and ureter with increased serum calcium. Systematic review of 25 MR studies provided supporting evidence on five out of the eight disease outcomes, while the increased risk of gout, hyperparathyroidism and disorder of parathyroid gland were novel findings. Interpretation This study found wide-ranged health effects of high serum calcium, which suggests that the benefits and adversities of strategies promoting calcium intake should be assessed. Funding ET is supported by a CRUK Career Development Fellowship (C31250/A22804). XL is supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province. SCL acknowledges research funding from the Swedish Heart Lung Foundation (Hjärt-Lungfonden, 20210351), the Swedish Research Council (Vetenskapsrådet, 2019-00977), and the Swedish Cancer Society (Cancerfonden).
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Affiliation(s)
- Shuai Yuan
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Lili Yu
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wanglong Gou
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Lijuan Wang
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jing Sun
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Doudou Li
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ying Lu
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaxia Cai
- Department of Nutrition and Food Hygiene, Beijing Key Laboratory of Environmental Toxicology, School of Public Health, Capital Medical University, Beijing, China
| | - Huanling Yu
- Department of Nutrition and Food Hygiene, Beijing Key Laboratory of Environmental Toxicology, School of Public Health, Capital Medical University, Beijing, China
| | - Changzheng Yuan
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, USA
| | - Ju-Sheng Zheng
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Evropi Theodoratou
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK; Cancer Research UK Edinburgh Centre, Medical Research Council Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Xue Li
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK.
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169
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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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170
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Qiu K, Zeng T, Liao Y, Min J, Zhang N, Peng M, Kong W, Chen LL. Identification of Inflammation-Related Biomarker Pro-ADM for Male Patients With Gout by Comprehensive Analysis. Front Immunol 2022; 12:798719. [PMID: 35116032 PMCID: PMC8803656 DOI: 10.3389/fimmu.2021.798719] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 12/28/2021] [Indexed: 11/22/2022] Open
Abstract
Objective Gout is a local inflammatory disease caused by the deposition of monosodium urate (MSU) crystals in joints or adjacent tissues. When some gout occurs without hyperuricemia, or its clinical symptoms and signs are not typical, the diagnosis of gout will be delayed, so there is an urgent need to find a new biomarker to predict and diagnose of gout flare. Our research attempts to find the key genes and potential molecular mechanisms of gout through bioinformatics analysis, and collected general data and blood biochemical samples of patients with gout and healthy, then analyzed and compared the expression of factors regulated by key genes. Method GSE160170 were downloaded from GEO database for analysis. The data were normalized to identify the differentially expressed genes (DEGs), then GO and KEGG enrichment analysis were applied. Protein-protein interaction (PPI) networks and hub genes between DEGs were identified. Then collect general information and blood samples from male patients with acute gout, hyperuricemia and healthy. ELISA method was used to detect pro-ADM levels of different groups, and the data was input into SPSS statistical software for analysis. Result We identified 266 DEGs (179 up-regulated and 87 down-regulated) between gout patients and healthy controls. GO analysis results show that DEGs are mostly enriched in inflammatory response, growth factor activity, cytokine activity, chemokine activity, S100 protein binding and CXCR chemokine receptor binding. KEGG pathway analysis showed that DEGs are mainly related to Chemokine signaling pathway and Cytokine-cytokine receptor interaction. ADM, CXCR1, CXCR6, CXCL3, CCL3, CCL18, CCL3L3, CCL4L1, CD69, CD83, AREG, EREG, B7RP1, HBEGF, NAMPT and S100B are the most important hub genes in the PPI network. We found that the expression of pro-ADM in the gout group and hyperuricemia group was higher than that in the healthy group, and the difference was statistically significant. Conclusion In this study, a series of bioinformatics analyses were performed on DEGs to identify key genes and pathways related to gout. Through clinical verification, we found that pro-ADM can be used as an inflammation-related biomarker for acute attacks of gout, providing new ideas for the diagnosis and treatment of gout.
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Affiliation(s)
- Kangli Qiu
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Wuhan, China
| | - Tianshu Zeng
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Wuhan, China
| | - Yunfei Liao
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Wuhan, China
| | - Jie Min
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Wuhan, China
| | - Nan Zhang
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Wuhan, China
| | - Miaomiao Peng
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Wuhan, China
| | - Wen Kong
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Wuhan, China
| | - Lu-lu Chen
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Wuhan, China
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171
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Chang SJ, Toyoda Y, Kawamura Y, Nakamura T, Nakatochi M, Nakayama A, Liao WT, Shimizu S, Takada T, Takeuchi K, Wakai K, Shi Y, Shinomiya N, Chen CJ, Li C, Okada Y, Ichida K, Matsuo H. A meta-analysis of genome-wide association studies using Japanese and Taiwanese has revealed novel loci associated with gout susceptibility. Hum Cell 2022; 35:767-770. [PMID: 35032298 PMCID: PMC8866370 DOI: 10.1007/s13577-021-00665-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 12/21/2021] [Indexed: 11/25/2022]
Affiliation(s)
- Shun-Jen Chang
- Department of Kinesiology, Health and Leisure Studies, National University of Kaohsiung, Kaohsiung, Taiwan
| | - Yu Toyoda
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Yusuke Kawamura
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Takahiro Nakamura
- Laboratory for Mathematics, National Defense Medical College, Saitama, Japan
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Akiyoshi Nakayama
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Wei-Ting Liao
- Department of Biotechnology, College of Life Science, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Seiko Shimizu
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Tappei Takada
- Department of Pharmacy, The University of Tokyo Hospital, Tokyo, Japan
| | - Kenji Takeuchi
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
- Affiliated Hospital of Qingdao University and Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, China
| | - Nariyoshi Shinomiya
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Chung-Jen Chen
- Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Changgui Li
- Department of Endocrinology and Metabolism, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Osaka, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Osaka, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kimiyoshi Ichida
- Department of Pathophysiology, Tokyo University of Pharmacy and Life Sciences, Tokyo, Japan
| | - Hirotaka Matsuo
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan.
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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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173
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He H, Pan L, Du J, Jin Y, Jia P, Shan G. Body mass index was linked with multi-cardiometabolic abnormalities in Chinese children and adolescents: a community-based survey. BMC Pediatr 2022; 22:33. [PMID: 35012488 PMCID: PMC8744239 DOI: 10.1186/s12887-021-03092-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 12/22/2021] [Indexed: 11/15/2022] Open
Abstract
Background Evidence on how body mass index (BMI) influence cardiometabolic health remains sparse in Chinese children and adolescents, especially in south China. We aim to investigate the effect of overweight and/or obesity on high blood pressure (HBP), dyslipidemia, elevated serum uric acid (SUA) and their clustering among children and adolescents in an island in South China. Methods Using multi-stage cluster sampling method, 1577 children and adolescents aged 7–18 in Hainan province, south China, participated in the survey. The association between body mass index and cardiometabolic indexes were explored. Overweight and obesity were classified according to criteria of World Health Organization for children and adolescents aged 5 to 19. Restricted cubic spline models were used to examine the possible non-linear association between BMI and cardiometabolic profiles. Multivariable logistic regression models were fitted to examine the effect size of BMI on cardiometabolic disorders including HBP, elevated SUA and dyslipidemia. Comorbidity of at least two cardiometabolic abnormalities (HBP, dyslipidemia, elevated SUA) was defined as clustering of cardiometabolic risk factors. Results Comparing with normal weight and underweight subjects, overweight/obese youths had higher levels of BP, SUA, triglyceride, low-density lipoprotein but lower level of high-density lipoprotein. Overweight/obese youth had higher risk of dyslipidemia (OR:2.89, 95%CI: 1.65–5.06), HBP (OR:2.813, 95%CI: 1.20–6.59) and elevated SUA (OR: 2.493, 95%CI: 1.45–4.27), respectively, than their counterparts. The sex-, age-adjusted prevalence of abnormalities clustering was 32.61% (95% CI: 20.95% to 46.92%) in overweight/obesity group, much higher than in the under/normal weight group (8.85%, 95%CI: 7.44% to 10.48%). Conclusion Excess adiposity increased the risk of elevated serum uric acid, serum lipids, blood pressure and their clustering among children and adolescents in south China.
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Affiliation(s)
- Huijing He
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences; School of Basic Medicine, Peking Union Medical College, 5 Dongdansantiao, Dongcheng District, Beijing, 100005, China
| | - Li Pan
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences; School of Basic Medicine, Peking Union Medical College, 5 Dongdansantiao, Dongcheng District, Beijing, 100005, China
| | - Jianwei Du
- Hainan Provincial Center for Disease Control and Prevention, Haikou, 570203, China
| | - Yuming Jin
- Hainan Provincial Center for Disease Control and Prevention, Haikou, 570203, China
| | - Pengben Jia
- Hainan Provincial Center for Disease Control and Prevention, Haikou, 570203, China
| | - Guangliang Shan
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences; School of Basic Medicine, Peking Union Medical College, 5 Dongdansantiao, Dongcheng District, Beijing, 100005, China.
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Zhang X, Hou G, Li F, Zheng X, Nie Q, Song G. SLC2A9 rs1014290 Polymorphism is Associated with Prediabetes and Type 2 Diabetes. Int J Endocrinol 2022; 2022:4947684. [PMID: 36545489 PMCID: PMC9763018 DOI: 10.1155/2022/4947684] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 11/17/2022] [Accepted: 11/29/2022] [Indexed: 12/15/2022] Open
Abstract
PURPOSE To investigate the association of the A/G rs1014290 polymorphism in SLC2A9 with type 2 diabetes (T2DM) and prediabetes mellitus (pre-DM). Patients and Methods. We enrolled 1058 patients who attended the Hebei General Hospital, Shijiazhuang, Hebei Province, China. The patients underwent general testing and oral glucose tolerance tests and were divided into three groups: 352 patients newly diagnosed with T2DM, 358 patients with pre-DM, and 348 healthy controls. The single nucleotide polymorphism (SNP) was detected by ligase detection reactions. The χ 2 test, one-way ANOVA, and binary logistic regression analysis were used to analyze the results. RESULTS In the T2DM group, the GG genotype frequency at the rs1014290 locus was significantly lower (14.8%) than it was in the healthy controls. Furthermore, the GG genotype group was associated with a reduced risk of T2DM in unadjusted and confounder-adjusted models compared with the risk in the AA genotype group. The G allele in the SLC2A9 rs1014290 locus decreased susceptibility to T2DM. In the pre-DM group, the GG and AG genotype groups had no significant correlation with the risk of pre-DM in any of the models. In the T2DM group, the uric acid level was significantly lower in the GG genotype group. In the T2DM and pre-DM groups, the HOMA-β levels were significantly higher in the GA (P < 0.001) and GG (P < 0.001) genotype groups than it was in the AA genotype group, and HOMA-IR was significantly lower in the GA (P < 0.001) and GG (P < 0.001) genotype groups than it was in the AA genotype group. CONCLUSION The A/G (rs1014290) SNP in SLC2A9 is closely related to the occurrence and development of diabetes.
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Affiliation(s)
- Xuemei Zhang
- Department of Rheumatism and Immunology, Hebei General Hospital, 348 Heping West Road, Shijiazhuang, Hebei 050000, China
| | - Guangsen Hou
- Department of Geriatric, Affiliated Hospital of Hebei Engineering University, 81 Congtai Road, Handan, Hebei 056000, China
| | - Fang Li
- Department of Rheumatism and Immunology, Hebei General Hospital, 348 Heping West Road, Shijiazhuang, Hebei 050000, China
| | - Xiao Zheng
- Department of Rheumatism and Immunology, Hebei General Hospital, 348 Heping West Road, Shijiazhuang, Hebei 050000, China
| | - Qian Nie
- Physical Examination Center, Hebei General Hospital, 348 Heping West Road, Shijiazhuang, Hebei 050000, China
| | - Guangyao Song
- Hebei Key Laboratory of Metabolic Diseases, Hebei General Hospital, 348 Heping West Road, Shijiazhuang, Hebei 050000, China
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175
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Lv Z, Cui J, Zhang J. Associations between serum urate and telomere length and inflammation markers: Evidence from UK Biobank cohort. Front Immunol 2022; 13:1065739. [PMID: 36591268 PMCID: PMC9797991 DOI: 10.3389/fimmu.2022.1065739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 11/28/2022] [Indexed: 12/23/2022] Open
Abstract
Objective Hyperuricemia and gout have become gradually more common. The effect of serum urate on organism aging and systematic inflammation is not determined. This study aims to evaluate whether serum urate is causally associated with cellular aging markers and serum inflammation markers. Methods A Mendelian randomization study was performed on summary-level data from the largest published genome-wide association studies. Single nucleotide polymorphisms with a genome-wide significance level were selected as instrumental variables for leukocyte telomere length (LTL), and serum soluble makers of inflammation (CRP, IL-6, TNF-α, and IGF-1). Standard inverse variance weighted (IVW) method was used as the primary statistical method. The weighted median, MR-Egger regression, and MR-PRESSO methods were used for sensitivity analysis. Results An inverse causal association of genetically predicted serum urate levels and LTL was found using IVW method (OR: 0.96, 95%CI 0.95, 0.97; β=-0.040; SE=0.0072; P=4.37×10-8). The association was also supported by MR results using MR-Egger method and weighted median method. The MR-PRESSO analysis and leave-one-out sensitivity analysis supported the robustness of the combined results. In terms of other aging-related serum biomarkers, there was no evidence supporting a causal effect of serum urate on CRP, IL-6, TNF-α, or IGF-1 levels. Conclusions Serum urate levels are negatively associated with telomere length but are not associated with serum soluble indicators of inflammation. Telomere length may be a critical marker that reflects urate-related organismal aging and may be a mechanism in the age-related pathologies and mortality caused by hyperuricemia.
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Affiliation(s)
- Zhengtao Lv
- Department of Orthopedics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiarui Cui
- School of Rehabilitation and Health Preservation, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- *Correspondence: Jiarui Cui, ; Jiaming Zhang,
| | - Jiaming Zhang
- Department of Orthopedics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- *Correspondence: Jiarui Cui, ; Jiaming Zhang,
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176
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Gao Y, Xu B, Yang Y, Zhang M, Yu T, Zhang Q, Sun J, Liu R. Association Between Serum Uric Acid and Carotid Intima-Media Thickness in Different Fasting Blood Glucose Patterns: A Case-Control Study. Front Endocrinol (Lausanne) 2022; 13:899241. [PMID: 35712254 PMCID: PMC9197240 DOI: 10.3389/fendo.2022.899241] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 04/07/2022] [Indexed: 12/03/2022] Open
Abstract
Our objective was to analyze the correlation between serum uric acid (SUA) levels and carotid intima-media thickness (CIMT) and explore the relationship between SUA and carotid atherosclerosis in different glucose metabolism patterns. A total of 614 patients were enrolled in this case-control study, including 406 in the normouricemia group and 208 in the hyperuricemia group. The two groups were each divided into three groups according to fasting blood glucose (FBG) level: normal, impaired fasting glucose (IFG), and diabetes mellitus (DM). CIMT and the CIMT thickening rate in the hyperuricemia group were significantly higher than those in the normouricemia group: 0.17 (0.11-0.24) cm vs. 0.12 (0.08-0.15) cm and 73.56% vs. 51.97% (p < 0.001). Pearson's correlation analysis showed that age, systolic blood pressure (SBP), diastolic blood pressure, FBG, triglyceride, SUA, creatinine, and blood urea nitrogen were positively correlated with CIMT, whereas high-density lipoprotein cholesterol and total cholesterol were negatively correlated with CIMT. Multiple linear regression analysis showed that age, SUA, FBG, and SBP were independent factors that affected CIMT. Furthermore, age and SBP were independent factors in the normouricemia group, and FBG was an independent factor that affected CIMT in the hyperuricemia group (p < 0.05). In the hyperuricemia group, CIMT in the DM group was significantly higher than that in the normal group [0.20 (0.14-0.25)cm vs. 0.15 (0.1-0.25); p < 0.05], and the CIMT thickening rate in the DM group was significantly higher than those in the IFG and normal groups (90.38% vs. 78.38%, 90.38% vs. 65.81%; p < 0.05). The ROC curve analysis showed that uric acid combined with age, SBP, and FBG had the highest area under the curve (AUC) for predicting CIMT thickening [0.855 (95% confidence interval (CI): 0.804-0.906)], followed by uric acid combined with FBG [AUC: 0.767 (95% CI: 0.726-0.808)]. In conclusion, SUA was closely associated with an increase in CIMT in patients with specific FBG metabolic patterns and may be an independent risk factor for carotid atherosclerosis. SUA, especially in combination with other factors (such as age, SBP, FBG), may serve as a specific model to help predict the incidence of CIMT thickening. Clinical Trial Registration: http://www.chictr.org.cn, identifier ChiCTR2000039124.
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Affiliation(s)
- Yuanyuan Gao
- Department of VIP Unit, China-Japan Union Hospital of Jilin University, Changchun, China
- Department of Endocrinology, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Baofeng Xu
- Department of Stroke Center, First Hospital of Jilin University, Changchun, China
| | - Yanyan Yang
- Department of Ultrasound, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Mei Zhang
- Department of VIP Unit, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Tian Yu
- Department of VIP Unit, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Qiujuan Zhang
- Department of VIP Unit, China-Japan Union Hospital of Jilin University, Changchun, China
| | - Jianwei Sun
- Department of Neurosurgery, Weifang People’s Hospital, Weifang, China
| | - Rui Liu
- Department of VIP Unit, China-Japan Union Hospital of Jilin University, Changchun, China
- *Correspondence: Rui Liu,
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177
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Li LM, Jiang BG, Sun LL. HNF1A:From Monogenic Diabetes to Type 2 Diabetes and Gestational Diabetes Mellitus. Front Endocrinol (Lausanne) 2022; 13:829565. [PMID: 35299962 PMCID: PMC8921476 DOI: 10.3389/fendo.2022.829565] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 02/03/2022] [Indexed: 12/12/2022] Open
Abstract
Diabetes, a disease characterized by hyperglycemia, has a serious impact on the lives and families of patients as well as on society. Diabetes is a group of highly heterogeneous metabolic diseases that can be classified as type 1 diabetes (T1D), type 2 diabetes (T2D), gestational diabetes mellitus (GDM), or other according to the etiology. The clinical manifestations are more or less similar among the different types of diabetes, and each type is highly heterogeneous due to different pathogenic factors. Therefore, distinguishing between various types of diabetes and defining their subtypes are major challenges hindering the precise treatment of the disease. T2D is the main type of diabetes in humans as well as the most heterogeneous. Fortunately, some studies have shown that variants of certain genes involved in monogenic diabetes also increase the risk of T2D. We hope this finding will enable breakthroughs regarding the pathogenesis of T2D and facilitate personalized treatment of the disease by exploring the function of the signal genes involved. Hepatocyte nuclear factor 1 homeobox A (HNF1α) is widely expressed in pancreatic β cells, the liver, the intestines, and other organs. HNF1α is highly polymorphic, but lacks a mutation hot spot. Mutations can be found at any site of the gene. Some single nucleotide polymorphisms (SNPs) cause maturity-onset diabetes of the young type 3 (MODY3) while some others do not cause MODY3 but increase the susceptibility to T2D or GDM. The phenotypes of MODY3 caused by different SNPs also differ. MODY3 is among the most common types of MODY, which is a form of monogenic diabetes mellitus caused by a single gene mutation. Both T2D and GDM are multifactorial diseases caused by both genetic and environmental factors. Different types of diabetes mellitus have different clinical phenotypes and treatments. This review focuses on HNF1α gene polymorphisms, HNF1A-MODY3, HNF1A-associated T2D and GDM, and the related pathogenesis and treatment methods. We hope this review will provide a valuable reference for the precise and individualized treatment of diabetes caused by abnormal HNF1α by summarizing the clinical heterogeneity of blood glucose abnormalities caused by HNF1α mutation.
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Affiliation(s)
- Li-Mei Li
- Research Center for Translational Medicine, Key Laboratory of Arrhythmias of the Ministry of Education of China, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Bei-Ge Jiang
- Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, China
- *Correspondence: Bei-Ge Jiang, ; Liang-Liang Sun,
| | - Liang-Liang Sun
- Department of Endocrinology and Metabolism, Changzheng Hospital, Naval Medical University, Shanghai, China
- *Correspondence: Bei-Ge Jiang, ; Liang-Liang Sun,
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178
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Kononov S, Mal G, Azarova I, Klyosova E, Bykanova M, Churnosov M, Polonikov A. Pharmacogenetic loci for rosuvastatin are associated with intima-media thickness change and coronary artery disease risk. Pharmacogenomics 2022; 23:15-34. [PMID: 34905955 DOI: 10.2217/pgs-2021-0097] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Accepted: 11/09/2021] [Indexed: 11/21/2022] Open
Abstract
Aim: Polymorphisms at LPA, LDLR, APOE, APOC1, MYLIP and ABCG2 are attractive targets for assessment of their impact on lipid-lowering therapy with rosuvastatin. The present study investigated whether polymorphisms at these genes are associated with the risk of coronary artery disease (CAD) development, and reduction of atherogenic lipids and carotid intima-media thickness (CIMT) in CAD patients, taking rosuvastatin. Materials & methods: 190 CAD patients and 1697 subjects were enrolled in pharmacogenetic and genetic association study, respectively. SNP genotyping was done using the MassARRAY-4 system. Results:MYLIP rs6924995, rs3757354, APOC1 rs445925, LDLR rs6511720, APOE rs7412, ABCG2 rs2199936, rs1481012 variants were significantly associated with CAD susceptibility (p = 0.016, 0.0003, <0.0001, <0.0001, 0.013, 0.016, 0.0035, respectively), as well as with CIMT regression (except ABCG2 variants; p = 0.05, 0.039, 0.039, 0.016, 0.0065), and changes in plasma lipids during rosuvastatin therapy. Conclusion: The studied polymorphisms possess pleiotropic effects on plasma lipids and CIMT, CAD susceptibility, and determine lipid-lowering response to rosuvastatin.
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Affiliation(s)
- Stanislav Kononov
- Department of Internal Medicine N 2, Kursk State Medical University, 14 Pirogova St., Kursk 305035, Russian Federation
| | - Galina Mal
- Department of Pharmacology, Kursk State Medical University, 3 Karl Marx St., Kursk 305041, Russian Federation
| | - Iuliia Azarova
- Department of Biological Chemistry, Kursk State Medical University, 3 Karl Marx St., Kursk 305041, Russian Federation
- Laboratory of Biochemical Genetics & Metabolomics, Research Institute for Genetic & Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya St., Kursk 305041, Russian Federation
| | - Elena Klyosova
- Laboratory of Biochemical Genetics & Metabolomics, Research Institute for Genetic & Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya St., Kursk 305041, Russian Federation
- Department of Biology, Medical Genetics & Ecology, Kursk State Medical University, 3 Karl Marx St., Kursk 305041, Russian Federation
| | - Marina Bykanova
- Department of Biology, Medical Genetics & Ecology, Kursk State Medical University, 3 Karl Marx St., Kursk 305041, Russian Federation
- Laboratory of Genomic Research, Research Institute for Genetic & Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya St., Kursk 305041, Russian Federation
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State University, 85 Pobeda St., Belgorod 308015, Russian Federation
| | - Alexey Polonikov
- Department of Biology, Medical Genetics & Ecology, Kursk State Medical University, 3 Karl Marx St., Kursk 305041, Russian Federation
- Laboratory of Statistical Genetics & Bioinformatics, Research Institute for Genetic & Molecular Epidemiology, Kursk State Medical University, 18 Yamskaya St., Kursk 305041, Russian Federation
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179
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Lorenzo JPP, Sollano MHMZ, Salido EO, Li-Yu J, Tankeh-Torres SA, Wulansari Manuaba IAR, Rahman MM, Paul BJ, Mok MY, De Silva M, Padhan P, Lim AL, Marcial M, Vicera JJ, Haq SA, Salman S, Liyanage CK, Keen HI, Yew Kuang C, Wei JCC, Hellmi RY, Chan CE, Louthrenoo W. 2021 Asia-Pacific League of Associations for Rheumatology clinical practice guideline for treatment of gout. Int J Rheum Dis 2021; 25:7-20. [PMID: 34931463 DOI: 10.1111/1756-185x.14266] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 11/30/2021] [Accepted: 12/03/2021] [Indexed: 01/08/2023]
Abstract
BACKGROUND Gout is the most prevalent inflammatory arthritis in the Asia-Pacific region and worldwide. This clinical practice guideline (CPG) aims to provide recommendations based on systematically obtained evidence and values and preferences tailored to the unique needs of patients with gout and hyperuricemia in Asia, Australasia, and the Middle East. The target users of these guidelines are general practitioners and specialists, including rheumatologists, in these regions. METHODS Relevant clinical questions were formulated by the Steering Committee. Systematic reviews of evidence were done, and certainty of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation methodology. A multi-sectoral consensus panel formulated the final recommendations. RESULTS The Asia-Pacific League of Associations for Rheumatology Task Force developed this CPG for treatment of gout with 3 overarching principles and 22 recommendation statements that covered the treatment of asymptomatic hyperuricemia (2 statements), treatment of acute gout (4 statements), prophylaxis against gout flare when initiating urate-lowering therapy (3 statements), urate-lowering therapy (3 statements), treatment of chronic tophaceous gout (2 statements), treatment of complicated gout and non-responders (2 statements), treatment of gout with moderate to severe renal impairment (1 statement), and non-pharmacologic interventions (5 statements). CONCLUSION Recommendations for clinically relevant scenarios in the management of gout were formulated to guide physicians in administering individualized care.
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Affiliation(s)
| | | | - Evelyn O Salido
- College of Medicine, University of the Philippines Manila, Manila, Philippines
| | - Julie Li-Yu
- University of Santo Tomas, Manila, Philippines
| | | | | | | | | | - Mo Yin Mok
- Department of Biomedical Sciences, City University of Hong Kong, Kowloon, Hong Kong
| | | | - Prasanta Padhan
- Department of Clinical Immunology and Rheumatology, Kalinga Institute of Medical Sciences, KIIT University, Bhubaneswar, India
| | | | | | | | - Syed Atiqul Haq
- Department of Rheumatology, Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh
| | - Sami Salman
- Department of Medicine, College of Medicine, University of Baghdad, Baghdad, Iraq
| | - Chiranthi K Liyanage
- Department of Pharmacology, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka
| | - Helen I Keen
- University of Western and Perth, Perth, WA, Australia.,Murdoch University, Perth, WA, Australia
| | - Cheng Yew Kuang
- Farrer Park Medical Center, Singapore, Singapore.,Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | | | - Rakhma Yanti Hellmi
- Rheumatology Division, Dr Kariadi General Hospital Medical Center, Diponegoro University, Semarang, Indonesia
| | | | - Worawit Louthrenoo
- Division of Rheumatology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
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180
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Tin A, Schlosser P, Matias-Garcia PR, Thio CHL, Joehanes R, Liu H, Yu Z, Weihs A, Hoppmann A, Grundner-Culemann F, Min JL, Kuhns VLH, Adeyemo AA, Agyemang C, Ärnlöv J, Aziz NA, Baccarelli A, Bochud M, Brenner H, Bressler J, Breteler MMB, Carmeli C, Chaker L, Coresh J, Corre T, Correa A, Cox SR, Delgado GE, Eckardt KU, Ekici AB, Endlich K, Floyd JS, Fraszczyk E, Gao X, Gào X, Gelber AC, 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, Kardia SLR, Kasela S, Kleber ME, Koenig W, Kooner JS, Kronenberg F, Kühnel B, Ladd-Acosta C, Lehtimäki T, Lind L, Liu D, Lloyd-Jones DM, Lorkowski S, Lu AT, Marioni RE, März W, McCartney DL, Meeks KAC, Milani L, Mishra PP, Nauck M, Nowak C, Peters A, Prokisch H, Psaty BM, Raitakari OT, Ratliff SM, Reiner AP, Schöttker B, Schwartz J, Sedaghat S, Smith JA, Sotoodehnia N, Stocker HR, Stringhini S, Sundström J, Swenson BR, van Meurs JBJ, van Vliet-Ostaptchouk JV, Venema A, Völker U, Winkelmann J, Wolffenbuttel BHR, Zhao W, Zheng Y, Loh M, Snieder H, Waldenberger M, Levy D, Akilesh S, Woodward OM, et alTin A, Schlosser P, Matias-Garcia PR, Thio CHL, Joehanes R, Liu H, Yu Z, Weihs A, Hoppmann A, Grundner-Culemann F, Min JL, Kuhns VLH, Adeyemo AA, Agyemang C, Ärnlöv J, Aziz NA, Baccarelli A, Bochud M, Brenner H, Bressler J, Breteler MMB, Carmeli C, Chaker L, Coresh J, Corre T, Correa A, Cox SR, Delgado GE, Eckardt KU, Ekici AB, Endlich K, Floyd JS, Fraszczyk E, Gao X, Gào X, Gelber AC, 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, Kardia SLR, Kasela S, Kleber ME, Koenig W, Kooner JS, Kronenberg F, Kühnel B, Ladd-Acosta C, Lehtimäki T, Lind L, Liu D, Lloyd-Jones DM, Lorkowski S, Lu AT, Marioni RE, März W, McCartney DL, Meeks KAC, Milani L, Mishra PP, Nauck M, Nowak C, Peters A, Prokisch H, Psaty BM, Raitakari OT, Ratliff SM, Reiner AP, Schöttker B, Schwartz J, Sedaghat S, Smith JA, Sotoodehnia N, Stocker HR, Stringhini S, Sundström J, Swenson BR, van Meurs JBJ, van Vliet-Ostaptchouk JV, Venema A, Völker U, Winkelmann J, Wolffenbuttel BHR, Zhao W, Zheng Y, Loh M, Snieder H, Waldenberger M, Levy D, Akilesh S, Woodward OM, Susztak K, Teumer A, Köttgen A. Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus. Nat Commun 2021; 12:7173. [PMID: 34887389 PMCID: PMC8660809 DOI: 10.1038/s41467-021-27198-4] [Show More Authors] [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: 03/17/2021] [Accepted: 11/08/2021] [Indexed: 12/25/2022] Open
Abstract
Elevated serum urate levels, a complex trait and major risk factor for incident gout, are correlated with cardiometabolic traits via incompletely understood mechanisms. DNA methylation in whole blood captures genetic and environmental influences and is assessed in transethnic meta-analysis of epigenome-wide association studies (EWAS) of serum urate (discovery, n = 12,474, replication, n = 5522). The 100 replicated, epigenome-wide significant (p < 1.1E-7) CpGs explain 11.6% of the serum urate variance. At SLC2A9, the serum urate locus with the largest effect in genome-wide association studies (GWAS), five CpGs are associated with SLC2A9 gene expression. Four CpGs at SLC2A9 have significant causal effects on serum urate levels and/or gout, and two of these partly mediate the effects of urate-associated GWAS variants. In other genes, including SLC7A11 and PHGDH, 17 urate-associated CpGs are associated with conditions defining metabolic syndrome, suggesting that these CpGs may represent a blood DNA methylation signature of cardiometabolic risk factors. This study demonstrates that EWAS can provide new insights into GWAS loci and the correlation of serum urate with other complex traits.
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Affiliation(s)
- Adrienne Tin
- Department of Medicine, University of Mississippi Medical Center, Jackson, 39216, MS, USA.
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Pascal Schlosser
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Pamela R Matias-Garcia
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, 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, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Hongbo Liu
- Department of Medicine and Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, 19104, PA, USA
| | - 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
| | - Antoine Weihs
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - 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
| | - Jan Bressler
- 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, 77030, TX, USA
| | - 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
| | - 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, 39216, MS, USA
| | - Simon R Cox
- Lothian Birth Cohorts Group, Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Graciela E Delgado
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - 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
| | - James S Floyd
- Department of Medicine, University of Washington, Seattle, 98101, WA, USA
- Department of Epidemiology, University of Washington, Seattle, 98101, WA, USA
- Cardiovascular Health Research Unit, University of Washington, Seattle, 98101, WA, USA
| | - 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
| | - Allan C Gelber
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - 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, Neuherberg, D-85764, Bavaria, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, 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, 77030, TX, 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
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, 90095, CA, 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, MA, USA
- Division of Intramural Research, Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, 48109, MI, 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
- National Heart and Lung Institute, 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
| | - 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, Neuherberg, D-85764, Bavaria, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany
| | - Christine Ladd-Acosta
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - 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
| | - Donald M Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 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, 90095, CA, 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, 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
| | - 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, Neuherberg, D-85764, 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, 98101, WA, USA
- Department of Epidemiology, University of Washington, Seattle, 98101, WA, USA
- Cardiovascular Health Research Unit, University of Washington, Seattle, 98101, WA, USA
- Department of Health Services, University of Washington, Seattle, 98101, WA, 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, 48109, MI, USA
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, 98101, WA, 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, MN, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, 48109, MI, 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, 98101, WA, 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, NSW, Australia
| | - Brenton R Swenson
- Cardiovascular Health Research Unit, University of Washington, Seattle, 98101, WA, USA
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - 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
| | - Uwe Völker
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - 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, 48109, MI, 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
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany
- DZHK (German Centre for Cardiovascular Research), Partner site Munich Heart Alliance, Munich, Germany
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Shreeram Akilesh
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Owen M Woodward
- Department of Physiology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Katalin Susztak
- Department of Medicine and Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, 19104, PA, 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
| | - Anna Köttgen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
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181
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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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182
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Herman MA, Birnbaum MJ. Molecular aspects of fructose metabolism and metabolic disease. Cell Metab 2021; 33:2329-2354. [PMID: 34619074 PMCID: PMC8665132 DOI: 10.1016/j.cmet.2021.09.010] [Citation(s) in RCA: 153] [Impact Index Per Article: 38.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 09/02/2021] [Accepted: 09/13/2021] [Indexed: 02/06/2023]
Abstract
Excessive sugar consumption is increasingly considered as a contributor to the emerging epidemics of obesity and the associated cardiometabolic disease. Sugar is added to the diet in the form of sucrose or high-fructose corn syrup, both of which comprise nearly equal amounts of glucose and fructose. The unique aspects of fructose metabolism and properties of fructose-derived metabolites allow for fructose to serve as a physiological signal of normal dietary sugar consumption. However, when fructose is consumed in excess, these unique properties may contribute to the pathogenesis of cardiometabolic disease. Here, we review the biochemistry, genetics, and physiology of fructose metabolism and consider mechanisms by which excessive fructose consumption may contribute to metabolic disease. Lastly, we consider new therapeutic options for the treatment of metabolic disease based upon this knowledge.
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Affiliation(s)
- Mark A Herman
- Division of Endocrinology, Metabolism, and Nutrition, Duke University, Durham, NC, USA; Duke Molecular Physiology Institute, Duke University, Durham, NC, USA; Department of Pharmacology and Cancer Biology, Duke University, Durham, NC, USA.
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183
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McCormick N, Yokose C, Lu N, Joshi AD, Curhan GC, Choi HK. Impact of adiposity on risk of female gout among those genetically predisposed: sex-specific prospective cohort study findings over >32 years. Ann Rheum Dis 2021; 81:556-563. [PMID: 34857519 DOI: 10.1136/annrheumdis-2021-221635] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 11/09/2021] [Indexed: 12/22/2022]
Abstract
OBJECTIVES To evaluate the joint (combined) association of excess adiposity and genetic predisposition with the risk of incident female gout, and compare to their male counterparts; and determine the proportion attributable to body mass index (BMI) only, genetic risk score (GRS) only, and to their interaction. METHODS We prospectively investigated potential gene-BMI interactions in 18 244 women from the Nurses' Health Study and compared with 10 888 men from the Health Professionals Follow-Up Study. GRS for hyperuricaemia was derived from 114 common urate-associated single nucleotide polymorphisms. RESULTS Multivariable relative risk (RR) for female gout was 1.49 (95% CI 1.42 to 1.56) per 5 kg/m2 increment of BMI and 1.43 (1.35 to 1.52) per SD increment in the GRS. For their joint association of BMI and GRS, RR was 2.18 (2.03 to 2.36), more than the sum of each individual factor, indicating significant interaction on an additive scale (p for interaction <0.001). The attributable proportions of joint effect for female gout were 42% (37% to 46%) to adiposity, 37% (32% to 42%) to genetic predisposition and 22% (16% to 28%) to their interaction. Additive interaction among men was smaller although still significant (p interaction 0.002, p for heterogeneity 0.04 between women and men), and attributable proportion of joint effect was 14% (6% to 22%). CONCLUSIONS While excess adiposity and genetic predisposition both are strongly associated with a higher risk of gout, the excess risk of both combined was higher than the sum of each, particularly among women.
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Affiliation(s)
- Natalie McCormick
- Division of Rheumatology, Allergy and Immunology, Massachusetts General Hospital, Boston, Massachusetts, USA .,Arthritis Research Canada, Vancouver, British Columbia, Canada.,Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Chio Yokose
- Medicine, Harvard Medical School, Boston, Massachusetts, USA.,Rheumatology Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Na Lu
- Arthritis Research Canada, Vancouver, British Columbia, Canada.,Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Amit D Joshi
- Medicine, Harvard Medical School, Boston, Massachusetts, USA.,Clinical Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Gary C Curhan
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.,Division of Renal Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Hyon K Choi
- Arthritis Research Canada, Vancouver, British Columbia, Canada .,Division of Rheumatology, Allergy and Immunology, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
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184
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Abstract
Circulation of urate levels is determined by the balance between urate production and excretion, homeostasis regulated by the function of urate transporters in key epithelial tissues and cell types. Our understanding of these physiological processes and identification of the genes encoding the urate transporters has advanced significantly, leading to a greater ability to predict risk for urate-associated diseases and identify new therapeutics that directly target urate transport. Here, we review the identified urate transporters and their organization and function in the renal tubule, the intestinal enterocytes, and other important cell types to provide a fuller understanding of the complicated process of urate homeostasis and its role in human diseases. Furthermore, we review the genetic tools that provide an unbiased catalyst for transporter identification as well as discuss the role of transporters in determining the observed significant gender differences in urate-associated disease risk.
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Affiliation(s)
| | - Owen M Woodward
- Department of Physiology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
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185
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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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186
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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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187
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Ji A, Shaukat A, Takei R, Bixley M, Cadzow M, Topless RK, Major TJ, Phipps-Green A, Merriman ME, Hindmarsh JH, Stamp LK, Dalbeth N, Li C, Merriman TR. Aotearoa New Zealand Māori and Pacific Population-amplified Gout Risk Variants: CLNK Is a Separate Risk Gene at the SLC2A9 Locus. J Rheumatol 2021; 48:1736-1744. [PMID: 34210831 DOI: 10.3899/jrheum.201684] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/11/2021] [Indexed: 11/22/2022]
Abstract
OBJECTIVE The Māori and Pacific (Polynesian) population of Aotearoa New Zealand has a high prevalence of gout. Our aim was to identify potentially functional missense genetic variants in candidate inflammatory genes amplified in frequency that may underlie the increased prevalence of gout in Polynesian populations. METHODS A list of 712 inflammatory disease-related genes was generated. An in silico targeted exome set was extracted from whole genome sequencing data in people with gout of various ancestral groups (Polynesian, European, East Asian; n = 55, 780, 135, respectively) to identify Polynesian-amplified common missense variants (minor allele frequency > 0.05). Candidate functional variants were tested for association with gout by multivariable-adjusted regression analysis in 2528 individuals of Polynesian ancestry. RESULTS We identified 26 variants common in the Polynesian population and uncommon in the European and East Asian populations. Three of the 26 population-amplified variants were nominally associated with the risk of gout (rs1635712 [KIAA0319], ORmeta = 1.28, Pmeta = 0.03; rs16869924 [CLNK], ORmeta = 1.37, Pmeta = 0.002; rs2070025 [fibrinogen A alpha chain (FGA)], ORmeta = 1.34, Pmeta = 0.02). The CLNK variant, within the established SLC2A9 gout locus, was genetically independent of the association signal at SLC2A9. CONCLUSION We provide nominal evidence for the existence of population-amplified genetic variants conferring risk of gout in Polynesian populations. Polymorphisms in CLNK have previously been associated with gout in other populations, supporting our evidence for the association of this gene with gout.
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Affiliation(s)
- Aichang Ji
- A. Ji, PhD, Research Fellow, C. Li, PhD, Professor, Shandong Provincial Key Laboratory of Metabolic Diseases, the Affiliated Hospital of Qingdao University, Qingdao, China
| | - Amara Shaukat
- A. Shaukat, MSc, Doctoral Student, M. Bixley, MSc, Assistant Research Fellow, M. Cadzow, PhD, Research Fellow, R.K. Topless, BSc, Assistant Research Fellow, T.J. Major, PhD, Research Fellow, A. Phipps-Green, MSc, Assistant Research Fellow, M.E. Merriman, BSc, Research Assistant, Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Riku Takei
- R. Takei, MSc, Scientist, Division of Clinical Immunology and Rheumatology, University of Alabama at Birmingham, Birmingham, USA
| | - Matthew Bixley
- A. Shaukat, MSc, Doctoral Student, M. Bixley, MSc, Assistant Research Fellow, M. Cadzow, PhD, Research Fellow, R.K. Topless, BSc, Assistant Research Fellow, T.J. Major, PhD, Research Fellow, A. Phipps-Green, MSc, Assistant Research Fellow, M.E. Merriman, BSc, Research Assistant, Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Murray Cadzow
- A. Shaukat, MSc, Doctoral Student, M. Bixley, MSc, Assistant Research Fellow, M. Cadzow, PhD, Research Fellow, R.K. Topless, BSc, Assistant Research Fellow, T.J. Major, PhD, Research Fellow, A. Phipps-Green, MSc, Assistant Research Fellow, M.E. Merriman, BSc, Research Assistant, Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Ruth K Topless
- A. Shaukat, MSc, Doctoral Student, M. Bixley, MSc, Assistant Research Fellow, M. Cadzow, PhD, Research Fellow, R.K. Topless, BSc, Assistant Research Fellow, T.J. Major, PhD, Research Fellow, A. Phipps-Green, MSc, Assistant Research Fellow, M.E. Merriman, BSc, Research Assistant, Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Tanya J Major
- A. Shaukat, MSc, Doctoral Student, M. Bixley, MSc, Assistant Research Fellow, M. Cadzow, PhD, Research Fellow, R.K. Topless, BSc, Assistant Research Fellow, T.J. Major, PhD, Research Fellow, A. Phipps-Green, MSc, Assistant Research Fellow, M.E. Merriman, BSc, Research Assistant, Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Amanda Phipps-Green
- A. Shaukat, MSc, Doctoral Student, M. Bixley, MSc, Assistant Research Fellow, M. Cadzow, PhD, Research Fellow, R.K. Topless, BSc, Assistant Research Fellow, T.J. Major, PhD, Research Fellow, A. Phipps-Green, MSc, Assistant Research Fellow, M.E. Merriman, BSc, Research Assistant, Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Marilyn E Merriman
- A. Shaukat, MSc, Doctoral Student, M. Bixley, MSc, Assistant Research Fellow, M. Cadzow, PhD, Research Fellow, R.K. Topless, BSc, Assistant Research Fellow, T.J. Major, PhD, Research Fellow, A. Phipps-Green, MSc, Assistant Research Fellow, M.E. Merriman, BSc, Research Assistant, Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Jennie Harré Hindmarsh
- J. Harré Hindmarsh, PhD, Research Coordinator, Ngāti Porou Hauora Charitable Trust, Te Puia Springs, Tairāwhiti East Coast, New Zealand
| | - Lisa K Stamp
- L.K. Stamp, PhD, Professor, Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Nicola Dalbeth
- N. Dalbeth, MD, Professor, Department of Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Changgui Li
- A. Ji, PhD, Research Fellow, C. Li, PhD, Professor, Shandong Provincial Key Laboratory of Metabolic Diseases, the Affiliated Hospital of Qingdao University, Qingdao, China
| | - Tony R Merriman
- T.R. Merriman, BSc, Research Assistant, Shandong Provincial Key Laboratory of Metabolic Diseases, the Affiliated Hospital of Qingdao University, Qingdao, China, Department of Biochemistry, University of Otago, Dunedin, New Zealand, and Division of Clinical Immunology and Rheumatology, University of Alabama at Birmingham, Birmingham, USA. A. Ji and A. Shaukat contributed equally to this work.
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Kukal S, Guin D, Rawat C, Bora S, Mishra MK, Sharma P, Paul PR, Kanojia N, Grewal GK, Kukreti S, Saso L, Kukreti R. Multidrug efflux transporter ABCG2: expression and regulation. Cell Mol Life Sci 2021; 78:6887-6939. [PMID: 34586444 PMCID: PMC11072723 DOI: 10.1007/s00018-021-03901-y] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 06/24/2021] [Accepted: 07/15/2021] [Indexed: 12/15/2022]
Abstract
The adenosine triphosphate (ATP)-binding cassette efflux transporter G2 (ABCG2) was originally discovered in a multidrug-resistant breast cancer cell line. Studies in the past have expanded the understanding of its role in physiology, disease pathology and drug resistance. With a widely distributed expression across different cell types, ABCG2 plays a central role in ATP-dependent efflux of a vast range of endogenous and exogenous molecules, thereby maintaining cellular homeostasis and providing tissue protection against xenobiotic insults. However, ABCG2 expression is subjected to alterations under various pathophysiological conditions such as inflammation, infection, tissue injury, disease pathology and in response to xenobiotics and endobiotics. These changes may interfere with the bioavailability of therapeutic substrate drugs conferring drug resistance and in certain cases worsen the pathophysiological state aggravating its severity. Considering the crucial role of ABCG2 in normal physiology, therapeutic interventions directly targeting the transporter function may produce serious side effects. Therefore, modulation of transporter regulation instead of inhibiting the transporter itself will allow subtle changes in ABCG2 activity. This requires a thorough comprehension of diverse factors and complex signaling pathways (Kinases, Wnt/β-catenin, Sonic hedgehog) operating at multiple regulatory levels dictating ABCG2 expression and activity. This review features a background on the physiological role of transporter, factors that modulate ABCG2 levels and highlights various signaling pathways, molecular mechanisms and genetic polymorphisms in ABCG2 regulation. This understanding will aid in identifying potential molecular targets for therapeutic interventions to overcome ABCG2-mediated multidrug resistance (MDR) and to manage ABCG2-related pathophysiology.
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Affiliation(s)
- Samiksha Kukal
- Genomics and Molecular Medicine Unit, Institute of Genomics and Integrative Biology (IGIB), Council of Scientific and Industrial Research (CSIR), Mall Road, Delhi, 110007, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Debleena Guin
- Genomics and Molecular Medicine Unit, Institute of Genomics and Integrative Biology (IGIB), Council of Scientific and Industrial Research (CSIR), Mall Road, Delhi, 110007, India
- Department of Biotechnology, Delhi Technological University, Shahbad Daulatpur, Main Bawana Road, Delhi, 110042, India
| | - Chitra Rawat
- Genomics and Molecular Medicine Unit, Institute of Genomics and Integrative Biology (IGIB), Council of Scientific and Industrial Research (CSIR), Mall Road, Delhi, 110007, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Shivangi Bora
- Genomics and Molecular Medicine Unit, Institute of Genomics and Integrative Biology (IGIB), Council of Scientific and Industrial Research (CSIR), Mall Road, Delhi, 110007, India
- Department of Biotechnology, Delhi Technological University, Shahbad Daulatpur, Main Bawana Road, Delhi, 110042, India
| | - Manish Kumar Mishra
- Genomics and Molecular Medicine Unit, Institute of Genomics and Integrative Biology (IGIB), Council of Scientific and Industrial Research (CSIR), Mall Road, Delhi, 110007, India
- Department of Biotechnology, Delhi Technological University, Shahbad Daulatpur, Main Bawana Road, Delhi, 110042, India
| | - Priya Sharma
- Genomics and Molecular Medicine Unit, Institute of Genomics and Integrative Biology (IGIB), Council of Scientific and Industrial Research (CSIR), Mall Road, Delhi, 110007, India
| | - Priyanka Rani Paul
- Genomics and Molecular Medicine Unit, Institute of Genomics and Integrative Biology (IGIB), Council of Scientific and Industrial Research (CSIR), Mall Road, Delhi, 110007, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Neha Kanojia
- Genomics and Molecular Medicine Unit, Institute of Genomics and Integrative Biology (IGIB), Council of Scientific and Industrial Research (CSIR), Mall Road, Delhi, 110007, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Gurpreet Kaur Grewal
- Department of Biotechnology, Kanya Maha Vidyalaya, Jalandhar, Punjab, 144004, India
| | - Shrikant Kukreti
- Nucleic Acids Research Lab, Department of Chemistry, University of Delhi (North Campus), Delhi, 110007, India
| | - Luciano Saso
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, P. le Aldo Moro 5, 00185, Rome, Italy
| | - Ritushree Kukreti
- Genomics and Molecular Medicine Unit, Institute of Genomics and Integrative Biology (IGIB), Council of Scientific and Industrial Research (CSIR), Mall Road, Delhi, 110007, India.
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
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189
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Ogura M, Toyoda Y, Sakiyama M, Kawamura Y, Nakayama A, Yamanashi Y, Takada T, Shimizu S, Higashino T, Nakajima M, Naito M, Hishida A, Kawai S, Okada R, Sasaki M, Ayaori M, Suzuki H, Takata K, Ikewaki K, Harada-Shiba M, Shinomiya N, Matsuo H. Increase of serum uric acid levels associated with APOE ε2 haplotype: a clinico-genetic investigation and in vivo approach. Hum Cell 2021; 34:1727-1733. [PMID: 34532841 PMCID: PMC8490264 DOI: 10.1007/s13577-021-00609-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 09/02/2021] [Indexed: 10/30/2022]
Abstract
Elevated serum uric acid (SUA)-hyperuricemia-is caused by overproduction of urate or by its decreased renal and/or intestinal excretion. This disease, which is increasing in prevalence worldwide, is associated with both gout and metabolic diseases. Several studies have reported relationships between apolipoprotein E (APOE) haplotypes and SUA levels in humans; however, their results remain inconsistent. This prompted us to investigate the relationship between APOE polymorphisms and SUA levels. Our subjects were 5,272 Japanese men, premenopausal women, and postmenopausal women. Multiple linear regression analyses revealed the ε2 haplotype of APOE to be independently associated with higher SUA in men (N = 1,726) and postmenopausal women (N = 1,753), but not in premenopausal women (N = 1,793). In contrast, the ε4 haplotype was little related to SUA levels in each group. Moreover, to examine the effect of Apoe deficiency on SUA levels, we conducted animal experiments using Apoe knockout mice, which mimics ε2/ε2 carriers. We found that SUA levels in Apoe knockout mice were significantly higher than those in wild-type mice, which is consistent with the SUA-raising effect of the ε2 haplotype observed in our clinico-genetic analyses. Further analyses suggested that renal rather than intestinal underexcretion of urate could be involved in Apoe deficiency-related SUA increase. In conclusion, we successfully demonstrated that the ε2 haplotype, but not the ε4 haplotype, increases SUA levels. These findings will improve our understanding of genetic factors affecting SUA levels.
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Affiliation(s)
- Masatsune Ogura
- Department of Metabolism and Endocrinology, Eastern Chiba Medical Center, 3-6-2 Okayamadai, Togane, Chiba, 283-8686, Japan.
- Department of General Medical Science, Chiba University Graduate School of Medicine, 1-8-1 Inohana, Chuo-ku, Chiba, Chiba, 260-8670, Japan.
- Department of Molecular Innovation in Lipidology, National Cerebral and Cardiovascular Center Research Institute, 6-1 Kishibe-shinmachi, Suita, Osaka, 564-8565, Japan.
| | - Yu Toyoda
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Masayuki Sakiyama
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
- Department of Dermatology, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Yusuke Kawamura
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Akiyoshi Nakayama
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Yoshihide Yamanashi
- Department of Pharmacy, Faculty of Medicine, The University of Tokyo Hospital, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Tappei Takada
- Department of Pharmacy, Faculty of Medicine, The University of Tokyo Hospital, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Seiko Shimizu
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Toshihide Higashino
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Mayuko Nakajima
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Mariko Naito
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, 466-8550, Japan
- Department of Oral Epidemiology, Hiroshima University Graduate School of Biomedical and Health Sciences, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8553, Japan
| | - Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, 466-8550, Japan
| | - Sayo Kawai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, 466-8550, Japan
- Department of Public Health, Aichi Medical University School of Medicine, 1-1 Yazako-karimata, Nagakute, Aichi, 480-1195, Japan
| | - Rieko Okada
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, 466-8550, Japan
| | - Makoto Sasaki
- Division of Anti-Aging and Vascular Medicine, Department of Internal Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Makoto Ayaori
- Division of Anti-Aging and Vascular Medicine, Department of Internal Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Hiroshi Suzuki
- Department of Pharmacy, Faculty of Medicine, The University of Tokyo Hospital, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Koki Takata
- Takata Clinic, 10-15 Wakakusa-cho, Higashi-ku, Hiroshima, Hiroshima, 732-0053, Japan
| | - Katsunori Ikewaki
- Division of Anti-Aging and Vascular Medicine, Department of Internal Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Mariko Harada-Shiba
- Department of Molecular Innovation in Lipidology, National Cerebral and Cardiovascular Center Research Institute, 6-1 Kishibe-shinmachi, Suita, Osaka, 564-8565, Japan
| | - Nariyoshi Shinomiya
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Hirotaka Matsuo
- Department of Integrative Physiology and Bio-Nano Medicine, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan.
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McCormick N, O’Connor MJ, Yokose C, Merriman TR, Mount DB, Leong A, Choi HK. Assessing the Causal Relationships Between Insulin Resistance and Hyperuricemia and Gout Using Bidirectional Mendelian Randomization. Arthritis Rheumatol 2021; 73:2096-2104. [PMID: 33982892 PMCID: PMC8568618 DOI: 10.1002/art.41779] [Citation(s) in RCA: 84] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 04/16/2021] [Indexed: 11/10/2022]
Abstract
OBJECTIVE Hyperuricemia is closely associated with insulin resistance syndrome (and its many cardiometabolic sequelae); however, whether they are causally related has long been debated. We undertook this study to investigate the potential causal nature and direction between insulin resistance and hyperuricemia, along with gout, by using bidirectional Mendelian randomization (MR) analyses. METHODS We used genome-wide association data (n = 288,649 for serum urate [SU] concentration; n = 763,813 for gout risk; n = 153,525 for fasting insulin) to select genetic instruments for 2-sample MR analyses, using multiple MR methods to address potential pleiotropic associations. We then used individual-level, electronic medical record-linked data from the UK Biobank (n = 360,453 persons of European ancestry) to replicate our analyses via single-sample MR analysis. RESULTS Genetically determined SU levels, whether inferred from a polygenic score or strong individual loci, were not associated with fasting insulin concentrations. In contrast, genetically determined fasting insulin concentrations were positively associated with SU levels (0.37 mg/dl per log-unit increase in fasting insulin [95% confidence interval (95% CI) 0.15, 0.58]; P = 0.001). This persisted in outlier-corrected (β = 0.56 mg/dl [95% CI 0.45, 0.67]) and multivariable MR analyses adjusted for BMI (β = 0.69 mg/dl [95% CI 0.53, 0.85]) (P < 0.001 for both). Polygenic scores for fasting insulin were also positively associated with SU level among individuals in the UK Biobank (P < 0.001). Findings for gout risk were bidirectionally consistent with those for SU level. CONCLUSION These findings provide evidence to clarify core questions about the close association between hyperuricemia and insulin resistance syndrome: hyperinsulinemia leads to hyperuricemia but not the other way around. Reducing insulin resistance could lower the SU level and gout risk, whereas lowering the SU level (e.g., allopurinol treatment) is unlikely to mitigate insulin resistance and its cardiometabolic sequelae.
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Affiliation(s)
- Natalie McCormick
- Clinical Epidemiology Program, Division of Rheumatology, Allergy, and Immunology, Massachusetts General Hospital Boston MA USA
- The Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston MA
- Department of Medicine, Harvard Medical School, Boston MA USA
- Arthritis Research Canada, Richmond BC Canada
| | - Mark J. O’Connor
- Endocrine Division, Massachusetts General Hospital, Boston MA USA
| | - Chio Yokose
- Clinical Epidemiology Program, Division of Rheumatology, Allergy, and Immunology, Massachusetts General Hospital Boston MA USA
- The Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston MA
- Department of Medicine, Harvard Medical School, Boston MA USA
| | - Tony R. Merriman
- Biochemistry Department, University of Otago, Dunedin, New Zealand
- Division of Rheumatology and Clinical Immunology, University of Alabama, Birmingham AL
| | - David B. Mount
- Department of Medicine, Harvard Medical School, Boston MA USA
- Brigham and Women’s Hospital and VA Boston Healthcare System, Harvard Medical School, Boston MA USA
| | - Aaron Leong
- Department of Medicine, Harvard Medical School, Boston MA USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston MA USA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge MA USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston MA USA
| | - Hyon K. Choi
- Clinical Epidemiology Program, Division of Rheumatology, Allergy, and Immunology, Massachusetts General Hospital Boston MA USA
- The Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston MA
- Department of Medicine, Harvard Medical School, Boston MA USA
- Arthritis Research Canada, Richmond BC Canada
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191
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The genetic basis of urate control and gout: Insights into molecular pathogenesis from follow-up study of genome-wide association study loci. Best Pract Res Clin Rheumatol 2021; 35:101721. [PMID: 34732286 DOI: 10.1016/j.berh.2021.101721] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
This review focuses on the post-genome-wide association study (GWAS) era in gout, i.e., the translation of GWAS genetic association signals into biologically informative knowledge. Analytical and experimental follow-up of individual loci, based on the identification of causal genetic variants, reveals molecular pathogenic pathways. We summarize in detail the largest GWAS in urate to date, then we review follow-up studies and molecular insights from ABCG2, HNF4A, PDZK1, MAF, GCKR, ALDH2, ALDH16A1, SLC22A12, SLC2A9, ABCC4, and SLC22A13, including the role of insulin signaling. One common factor in these pathways is the importance of transcriptional control, including the HNF4α transcription factor. The new molecular knowledge reveals new targets for intervention to manage urate levels and prevent gout.
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Goldberg A, Garcia-Arroyo F, Sasai F, Rodriguez-Iturbe B, Sanchez-Lozada LG, Lanaspa MA, Johnson RJ. Mini Review: Reappraisal of Uric Acid in Chronic Kidney Disease. Am J Nephrol 2021; 52:837-844. [PMID: 34673651 DOI: 10.1159/000519491] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Accepted: 09/06/2021] [Indexed: 12/16/2022]
Abstract
Hyperuricemia predicts the development of chronic kidney disease (CKD) and metabolic complications, but whether it has a causal role has been controversial. This is especially true given the 2 recently conducted randomized controlled trials that failed to show a benefit of lowering uric acid in type 1 diabetes-associated CKD and subjects with stage 3-4 CKD. While these studies suggest that use of urate-lowering drugs in unselected patients is unlikely to slow the progression of CKD, there are subsets of subjects with CKD where reducing uric acid synthesis may be beneficial. This may be the case in patients with gout, hyperuricemia (especially associated with increased production), and urate crystalluria. Here, we discuss the evidence and propose that future clinical trials targeting these specific subgroups should be performed.
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Affiliation(s)
- Avi Goldberg
- Clalit Health Services, Hebrew University of Jerusalem, Jerusalem, Israel
| | | | - Fumihiko Sasai
- Division of Renal Diseases and Hypertension, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | | | | | - Miguel A Lanaspa
- Division of Renal Diseases and Hypertension, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Richard J Johnson
- Division of Renal Diseases and Hypertension, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
- Rocky Mountain VA Medical Center, Aurora, Colorado, USA
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193
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Wolyncewicz B, Major TJ, Delahunt B, Thunders M. The epigenome: key to understanding and predicting gout flares. Pathology 2021; 53:824-829. [PMID: 34657735 DOI: 10.1016/j.pathol.2021.09.001] [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: 07/19/2021] [Revised: 09/16/2021] [Accepted: 09/21/2021] [Indexed: 11/26/2022]
Abstract
Gout is a form of arthritis, resulting from an inflammatory reaction to the deposition of monosodium urate (MSU) crystals in the synovial fluid of the joint space. It is characterised by periods of acute inflammation in the affected joint, or joints (known as gout flares), separated by asymptomatic periods. There seems to be substantial overlap between environmental triggers of gout flares and common environmental modifiers (diet, pharmaceuticals, and stress) of epigenetic markers (DNA methylation, histone modifications, and ncRNA). Very few studies have looked at whether environment is influencing gout through epigenetic mechanisms. The pathogenesis of gouty inflammation is well understood but understanding the variation of response to hyperuricaemia in terms of gout flare initiation is less well known. In this review, we will examine the potential of epigenomics in understanding how gout flares may occur, both in terms of development of hyperuricaemia and the inflammatory response. Looking at the epigenome and its intersection with lifestyle could help identify new targets and strategies for effective management of gout flares.
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Affiliation(s)
- Ben Wolyncewicz
- Otago Medical School, Division of Health Sciences, University of Otago, Dunedin, New Zealand
| | - Tanya J Major
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Brett Delahunt
- Department of Pathology and Molecular Medicine, Wellington School of Medicine and Health Sciences, University of Otago, Wellington, New Zealand
| | - Michelle Thunders
- Department of Pathology and Molecular Medicine, Wellington School of Medicine and Health Sciences, University of Otago, Wellington, New Zealand.
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194
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Droździk M, Oswald S, Droździk A. Impact of kidney dysfunction on hepatic and intestinal drug transporters. Biomed Pharmacother 2021; 143:112125. [PMID: 34474348 DOI: 10.1016/j.biopha.2021.112125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 08/11/2021] [Accepted: 08/24/2021] [Indexed: 12/16/2022] Open
Abstract
Emerging information suggests that pathology of the kidney may not only affect expression and function of membrane transporters in the organ, but also in the gastrointestinal tract and the liver. Transporter dysfunction may cause effects on handling of drug as well as endogenous compounds with subsequent clinical consequences. A literature search was conducted on Ovid and PubMed databases to select relevant in vitro, animal and human studies that have reported expression, protein abundance and function of the gastrointestinal and liver localized ABC transporters and SLC carriers in kidney dysfunction or uremia states. The altered function of drug transporters in the liver and intestines in kidney failure subjects may provide compensatory activity in handling endogenous compounds (e.g. uremic toxins), which is expected to affect drug pharmacokinetics and local drug actions.
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Affiliation(s)
- Marek Droździk
- Department of Pharmacology, Faculty of Medicine and Dentistry, Pomeranian Medical University, Powstancow Wlkp 72, 70-111 Szczecin, Poland.
| | - Stefan Oswald
- Institute of Pharmacology and Toxicology, Faculty of Medicine, Rostock University Medical Center, 18057 Rostock, Germany.
| | - Agnieszka Droździk
- Department of Integrated Dentistry, Faculty of Medicine and Dentistry, Pomeranian Medical University, Powstancow Wlkp 72, 70-111 Szczecin, Poland.
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Sheng X, Guan Y, Ma Z, Wu J, Liu H, Qiu C, Vitale S, Miao Z, Seasock MJ, Palmer M, Shin MK, Duffin KL, Pullen SS, Edwards TL, Hellwege JN, Hung AM, Li M, Voight BF, Coffman TM, Brown CD, Susztak K. Mapping the genetic architecture of human traits to cell types in the kidney identifies mechanisms of disease and potential treatments. Nat Genet 2021; 53:1322-1333. [PMID: 34385711 PMCID: PMC9338440 DOI: 10.1038/s41588-021-00909-9] [Citation(s) in RCA: 106] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 06/30/2021] [Indexed: 02/07/2023]
Abstract
The functional interpretation of genome-wide association studies (GWAS) is challenging due to the cell-type-dependent influences of genetic variants. Here, we generated comprehensive maps of expression quantitative trait loci (eQTLs) for 659 microdissected human kidney samples and identified cell-type-eQTLs by mapping interactions between cell type abundances and genotypes. By partitioning heritability using stratified linkage disequilibrium score regression to integrate GWAS with single-cell RNA sequencing and single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing data, we prioritized proximal tubules for kidney function and endothelial cells and distal tubule segments for blood pressure pathogenesis. Bayesian colocalization analysis nominated more than 200 genes for kidney function and hypertension. Our study clarifies the mechanism of commonly used antihypertensive and renal-protective drugs and identifies drug repurposing opportunities for kidney disease.
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Affiliation(s)
- Xin Sheng
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Yuting Guan
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ziyuan Ma
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Junnan Wu
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Hongbo Liu
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Chengxiang Qiu
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Steven Vitale
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Zhen Miao
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew J Seasock
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew Palmer
- Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | | | - Kevin L Duffin
- Eli Lilly and Company Lilly Corporate Center, Indianapolis, IN, USA
| | - Steven S Pullen
- Department of Cardiometabolic Diseases Research, Boehringer Ingelheim Pharmaceuticals, Ridgefield, CT, USA
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jacklyn N Hellwege
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Adriana M Hung
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Mingyao Li
- Department of Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Benjamin F Voight
- Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Thomas M Coffman
- Cardiovascular and Metabolic Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore
| | | | - Katalin Susztak
- Department of Medicine, Renal Electrolyte and Hypertension Division, University of Pennsylvania, Philadelphia, PA, USA.
- Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA.
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196
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Sandoval-Plata G, Morgan K, Abhishek A. Variants in urate transporters, ADH1B, GCKR and MEPE genes associate with transition from asymptomatic hyperuricaemia to gout: results of the first gout versus asymptomatic hyperuricaemia GWAS in Caucasians using data from the UK Biobank. Ann Rheum Dis 2021; 80:1220-1226. [PMID: 33832965 DOI: 10.1136/annrheumdis-2020-219796] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 12/16/2022]
Abstract
OBJECTIVES To perform a genome-wide association study (GWAS) of gout cases versus asymptomatic hyperuricaemia (AH) controls, and gout cases versus normouricaemia controls, and to generate a polygenic risk score (PRS) to determine gout-case versus AH-control status. METHODS Gout cases and AH controls (serum urate (SU) ≥6.0 mg/dL) from the UK Biobank were divided into discovery (4934 cases, 56 948 controls) and replication (2115 cases, 24 406 controls) cohorts. GWAS was conducted and PRS generated using summary statistics in discovery cohort as the base dataset and the replication cohort as the target dataset. The predictive ability of the model was evaluated. GWAS were performed to identify variants associated with gout compared with normouricaemic controls using SU <6.0 mg/dL and <7.0 mg/dL thresholds, respectively. RESULTS Thirteen independent single nucleotide polymorphisms (SNPs) in ABCG2, SLC2A9, SLC22A11, GCKR, MEPE, PPM1K-DT, LOC105377323 and ADH1B reached genome-wide significance and replicated as predictors of AH to gout transition. Twelve of 13 associations were novel for this transition, and rs1229984 (ADH1B) was identified as GWAS locus for gout for the first time. The best PRS model was generated from association data of 17 SNPs; and had predictive ability of 58.5% that increased to 69.2% on including demographic factors. Two novel SNPs rs760077(MTX1) and rs3800307(PRSS16) achieved GWAS significance for association with gout compared with normouricaemic controls using both SU thresholds. CONCLUSION The association of urate transporters with gout supports the central role of hyperuricaemia in its pathogenesis. Larger GWAS are required to identify if variants in inflammatory pathways contribute to progression from AH to gout.
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Affiliation(s)
- Gabriela Sandoval-Plata
- Academic Rheumatology, University of Nottingham, Nottingham, UK
- Nottingham Biomedical Research Centre, NIHR, Nottingham, UK
- Human Genetics, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Kevin Morgan
- Human Genetics, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Abhishek Abhishek
- Academic Rheumatology, University of Nottingham, Nottingham, UK
- Nottingham Biomedical Research Centre, NIHR, Nottingham, UK
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197
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Murdoch R, Barry MJ, Choi HK, Hernandez D, Johnsen B, Labrador M, Reid S, Singh JA, Terkeltaub R, Vázquez Mellado J, Dalbeth N. Gout, Hyperuricaemia and Crystal-Associated Disease Network (G-CAN) common language definition of gout. RMD Open 2021; 7:rmdopen-2021-001623. [PMID: 33903281 PMCID: PMC8076916 DOI: 10.1136/rmdopen-2021-001623] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 03/23/2021] [Accepted: 04/02/2021] [Indexed: 12/27/2022] Open
Abstract
Objective To develop a Gout, Hyperuricaemia and Crystal-Associated Disease Network (G-CAN) common language definition of gout, with the goal of increasing public understanding and awareness, and ensure consistent and understandable messages about gout. Methods A G-CAN working group that included patients, physicians and nongovernmental organisation (NGO) representatives was formed to develop a common language definition of gout for use with the public, media, healthcare providers and stakeholders. A literature search and interviews with patients, healthcare workers and stakeholders informed development of the definition. Following consultation with G-CAN members and partners, the definition was endorsed by the G-CAN board. Results The G-CAN common language definition of gout describes the epidemiology, pathophysiology, symptoms and impact, risk factors, comorbidities, management and healthcare and workforce considerations. Detailed information is provided to support the content of the definition. After the publication of the English-language version, the definition will be available for translation into other languages by G-CAN members. Conclusion G-CAN has developed a concise and easily understandable statement describing gout in language that can be used in conversations with the lay public, media, NGOs, funders, healthcare providers and other stakeholders.
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Affiliation(s)
- Rachel Murdoch
- Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - Michael J Barry
- Department of Primary Care, Harvard Medical School, Boston, Massachusetts, USA
| | - Hyon K Choi
- Division of Rheumatology Allergy and Immunology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | - Brianne Johnsen
- Division of Rheumatology Allergy and Immunology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Manuel Labrador
- Department of Rheumatology, Hospital General de México, Ciudad de Mexico, Mexico
| | - Susan Reid
- Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - Jasvinder A Singh
- Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA.,Medicine Service, Birmingham VA Medical Center, Birmingham, Alabama, USA
| | - Robert Terkeltaub
- Department of Rheumatology, University of California San Diego, La Jolla, California, USA
| | | | - Nicola Dalbeth
- Department of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
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198
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Mandal AK, Leask MP, Estiverne C, Choi HK, Merriman TR, Mount DB. Genetic and Physiological Effects of Insulin on Human Urate Homeostasis. Front Physiol 2021; 12:713710. [PMID: 34408667 PMCID: PMC8366499 DOI: 10.3389/fphys.2021.713710] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 07/02/2021] [Indexed: 12/19/2022] Open
Abstract
Insulin and hyperinsulinemia reduce renal fractional excretion of urate (FeU) and play a key role in the genesis of hyperuricemia and gout, via uncharacterized mechanisms. To explore this association further we studied the effects of genetic variation in insulin-associated pathways on serum urate (SU) levels and the physiological effects of insulin on urate transporters. We found that urate-associated variants in the human insulin (INS), insulin receptor (INSR), and insulin receptor substrate-1 (IRS1) loci associate with the expression of the insulin-like growth factor 2, IRS1, INSR, and ZNF358 genes; additionally, we found genetic interaction between SLC2A9 and the three loci, most evident in women. We also found that insulin stimulates the expression of GLUT9 and increases [14C]-urate uptake in human proximal tubular cells (PTC-05) and HEK293T cells, transport activity that was effectively abrogated by uricosurics or inhibitors of protein tyrosine kinase (PTK), PI3 kinase, MEK/ERK, or p38 MAPK. Heterologous expression of individual urate transporters in Xenopus oocytes revealed that the [14C]-urate transport activities of GLUT9a, GLUT9b, OAT10, OAT3, OAT1, NPT1 and ABCG2 are directly activated by insulin signaling, through PI3 kinase (PI3K)/Akt, MEK/ERK and/or p38 MAPK. Given that the high-capacity urate transporter GLUT9a is the exclusive basolateral exit pathway for reabsorbed urate from the renal proximal tubule into the blood, that insulin stimulates both GLUT9 expression and urate transport activity more than other urate transporters, and that SLC2A9 shows genetic interaction with urate-associated insulin-signaling loci, we postulate that the anti-uricosuric effect of insulin is primarily due to the enhanced expression and activation of GLUT9.
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Affiliation(s)
- Asim K. Mandal
- Renal Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Megan P. Leask
- Biochemistry Department, University of Otago, Dunedin, New Zealand
- Division of Rheumatology and Clinical Immunology, University of Alabama, Birmingham, AL, United States
| | - Christopher Estiverne
- Renal Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Hyon K. Choi
- Division of Rheumatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Tony R. Merriman
- Biochemistry Department, University of Otago, Dunedin, New Zealand
- Division of Rheumatology and Clinical Immunology, University of Alabama, Birmingham, AL, United States
| | - David B. Mount
- Renal Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Renal Division, VA Boston Healthcare System, Harvard Medical School, Boston, MA, United States
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199
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Badii M, Gaal OI, Cleophas MC, Klück V, Davar R, Habibi E, Keating ST, Novakovic B, Helsen MM, Dalbeth N, Stamp LK, Macartney-Coxson D, Phipps-Green AJ, Stunnenberg HG, Dinarello CA, Merriman TR, Netea MG, Crişan TO, Joosten LAB. Urate-induced epigenetic modifications in myeloid cells. Arthritis Res Ther 2021; 23:202. [PMID: 34321071 PMCID: PMC8317351 DOI: 10.1186/s13075-021-02580-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 07/12/2021] [Indexed: 01/02/2023] Open
Abstract
OBJECTIVES Hyperuricemia is a metabolic condition central to gout pathogenesis. Urate exposure primes human monocytes towards a higher capacity to produce and release IL-1β. In this study, we assessed the epigenetic processes associated to urate-mediated hyper-responsiveness. METHODS Freshly isolated human peripheral blood mononuclear cells or enriched monocytes were pre-treated with solubilized urate and stimulated with LPS with or without monosodium urate (MSU) crystals. Cytokine production was determined by ELISA. Histone epigenetic marks were assessed by sequencing immunoprecipitated chromatin. Mice were injected intraarticularly with MSU crystals and palmitate after inhibition of uricase and urate administration in the presence or absence of methylthioadenosine. DNA methylation was assessed by methylation array in whole blood of 76 participants with normouricemia or hyperuricemia. RESULTS High concentrations of urate enhanced the inflammatory response in vitro in human cells and in vivo in mice, and broad-spectrum methylation inhibitors reversed this effect. Assessment of histone 3 lysine 4 trimethylation (H3K4me3) and histone 3 lysine 27 acetylation (H3K27ac) revealed differences in urate-primed monocytes compared to controls. Differentially methylated regions (e.g. HLA-G, IFITM3, PRKAB2) were found in people with hyperuricemia compared to normouricemia in genes relevant for inflammatory cytokine signaling. CONCLUSION Urate alters the epigenetic landscape in selected human monocytes or whole blood of people with hyperuricemia compared to normouricemia. Both histone modifications and DNA methylation show differences depending on urate exposure. Subject to replication and validation, epigenetic changes in myeloid cells may be a therapeutic target in gout.
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Affiliation(s)
- M Badii
- Department of Medical Genetics, Iuliu Hațieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
- Department of Internal Medicine and Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Center, Geert Grooteplein 8, 6525 GA, Nijmegen, The Netherlands
| | - O I Gaal
- Department of Medical Genetics, Iuliu Hațieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
- Department of Internal Medicine and Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Center, Geert Grooteplein 8, 6525 GA, Nijmegen, The Netherlands
| | - M C Cleophas
- Department of Internal Medicine and Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Center, Geert Grooteplein 8, 6525 GA, Nijmegen, The Netherlands
| | - V Klück
- Department of Internal Medicine and Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Center, Geert Grooteplein 8, 6525 GA, Nijmegen, The Netherlands
| | - R Davar
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen, The Netherlands
| | - E Habibi
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen, The Netherlands
| | - S T Keating
- Department of Internal Medicine and Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Center, Geert Grooteplein 8, 6525 GA, Nijmegen, The Netherlands
| | - B Novakovic
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen, The Netherlands
| | - M M Helsen
- Department of Rheumatology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - N Dalbeth
- Department of Medicine, University of Auckland, Auckland, New Zealand
| | - L K Stamp
- Department of Medicine, University of Otago Christchurch, Christchurch, New Zealand
| | - D Macartney-Coxson
- Human Genomics, Institute of Environmental Science and Research (ESR), Wellington, New Zealand
| | - A J Phipps-Green
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - H G Stunnenberg
- Department of Molecular Biology, Faculty of Science, Radboud University, Nijmegen, The Netherlands
| | - C A Dinarello
- Department of Internal Medicine and Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Center, Geert Grooteplein 8, 6525 GA, Nijmegen, The Netherlands
- Department of Medicine, University of Colorado Denver, Aurora, CO, 80045, USA
| | - T R Merriman
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
- Division of Clinical Immunology and Rheumatology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - M G Netea
- Department of Internal Medicine and Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Center, Geert Grooteplein 8, 6525 GA, Nijmegen, The Netherlands
- Human Genomics Laboratory, University of Medicine and Pharmacy of Craiova, Craiova, Romania
| | - T O Crişan
- Department of Medical Genetics, Iuliu Hațieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania
- Department of Internal Medicine and Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Center, Geert Grooteplein 8, 6525 GA, Nijmegen, The Netherlands
| | - L A B Joosten
- Department of Medical Genetics, Iuliu Hațieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.
- Department of Internal Medicine and Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University Medical Center, Geert Grooteplein 8, 6525 GA, Nijmegen, The Netherlands.
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200
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Stanzick KJ, Li Y, Schlosser P, Gorski M, Wuttke M, Thomas LF, Rasheed H, Rowan BX, Graham SE, Vanderweff BR, Patil SB, Robinson-Cohen C, Gaziano JM, O'Donnell CJ, Willer CJ, Hallan S, Åsvold BO, Gessner A, Hung AM, Pattaro C, Köttgen A, Stark KJ, Heid IM, Winkler TW. Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals. Nat Commun 2021; 12:4350. [PMID: 34272381 PMCID: PMC8285412 DOI: 10.1038/s41467-021-24491-0] [Citation(s) in RCA: 173] [Impact Index Per Article: 43.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 06/21/2021] [Indexed: 12/24/2022] Open
Abstract
Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 loci (n = 460,826 and 852,678, respectively). Our customizable tool for Gene PrioritiSation reveals 23 compelling genes including mechanistic insights and enables navigation through genes and variants likely relevant for kidney function in human to help select targets for experimental follow-up.
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Affiliation(s)
- Kira J Stanzick
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Yong Li
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Mathias Gorski
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Laurent F Thomas
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- BioCore - Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
| | - Humaira Rasheed
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Bryce X Rowan
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Veteran's Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
| | - Sarah E Graham
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
| | - Brett R Vanderweff
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Snehal B Patil
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Cassiane Robinson-Cohen
- Department of Veteran's Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
- Vanderbilt University Medical Center, Division of Nephrology and Hypertension, Vanderbilt Center for Kidney Disease and Integrated Program for Acute Kidney Injury Research, and Vanderbilt Precision Nephrology Program Nashville, Nashville, TN, USA
| | - John M Gaziano
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, USA
- Department of Internal Medicine, Harvard Medical School, Boston, MA, USA
| | | | - Cristen J Willer
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Stein Hallan
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Nephrology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Bjørn Olav Åsvold
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Andre Gessner
- Institute of Clinical Microbiology and Hygiene, University Hospital Regensburg, Regensburg, Germany
| | - Adriana M Hung
- Department of Veteran's Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
- Vanderbilt University Medical Center, Division of Nephrology and Hypertension, Vanderbilt Center for Kidney Disease and Integrated Program for Acute Kidney Injury Research, and Vanderbilt Precision Nephrology Program Nashville, Nashville, TN, USA
| | - Cristian Pattaro
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Klaus J Stark
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.
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