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Lona-Durazo F, Omachi K, Fermin D, Eichinger F, Troost JP, Lin MH, Dinsmore IR, Mirshahi T, Chang AR, Miner JH, Paterson AD, Barua M, Gagliano Taliun SA. Association of Genetically Predicted Skipping of COL4A4 Exon 27 with Hematuria and Albuminuria. J Am Soc Nephrol 2025; 36:48-59. [PMID: 39190490 PMCID: PMC11671039 DOI: 10.1681/asn.0000000000000480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Accepted: 08/22/2024] [Indexed: 08/29/2024] Open
Abstract
Key Points Using transcriptome-wide association studies, we identified an association between splicing out of exon 27 of COL4A4 and hematuria. We confirmed the presence of COL4A4 exon 27 splicing in an independent cohort. Functional assays revealed that the COL4A4 transcript with exon 27 spliced out affects collagen IV trimer assembly and secretion. Background Hematuria is an established sign of glomerular disease and can be associated with kidney failure, but there has been limited scientific study of this trait. Methods Here, we combined genetic data from the UK Biobank with predicted gene expression and splicing from Genotype Tissue Expression kidney cortex samples (n =65) in a transcriptome-wide association study to identify additional potential biological mechanisms influencing hematuria. Results The transcriptome-wide association study using kidney cortex identified significant associations for five genes in expression and three significant splicing events. Notably, we identified an association between the skipping of COL4A4 exon 27, which is genetically predicted by intronic rs11898094 (minor allele frequency 13%), and hematuria. Association between this variant was also found with urinary albumin excretion. We found independent evidence supporting the same variant predicting this skipping event in glomeruli-derived mRNA transcriptomics data (n =245) from the Nephrotic Syndrome Study Network. The functional significance of loss of exon 27 was demonstrated using the split NanoLuc-based α 3α 4α 5(IV) heterotrimer assay, in which type IV collagen heterotrimer formation was quantified by luminescence. The causal splicing variant for this skipping event is yet to be identified. Conclusions In summary, by integrating multiple data types, we identified a potential splicing event associated with hematuria and albuminuria.
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Affiliation(s)
- Frida Lona-Durazo
- Montreal Heart Institute, Montreal, Quebec, Canada
- Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada
| | - Kohei Omachi
- Division of Nephrology, Washington University School of Medicine, St. Louis, Missouri
- Department of Molecular Medicine, Graduate School of Pharmaceutical Sciences, Kumamoto University, Kumamoto, Japan
| | - Damian Fermin
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Felix Eichinger
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Jonathan P. Troost
- Michigan Institute for Clinical and Health Research, University of Michigan, Ann Arbor, Michigan
| | - Meei-Hua Lin
- Division of Nephrology, Washington University School of Medicine, St. Louis, Missouri
| | - Ian R. Dinsmore
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | - Tooraj Mirshahi
- Department of Genomic Health, Geisinger, Danville, Pennsylvania
| | - Alexander R. Chang
- Department of Population Health Sciences, Center for Kidney Health Research, Geisinger, Danville, Pennsylvania
- Department of Nephrology, Geisinger, Danville, Pennsylvania
| | - Jeffrey H. Miner
- Division of Nephrology, Washington University School of Medicine, St. Louis, Missouri
| | - Andrew D. Paterson
- Divisions of Epidemiology and Biostatistics, Dalla Lana School of Public Health, Toronto, Ontario, Canada
- Genetics and Genome Biology, Research Institute at The Hospital for Sick Children, Toronto, Ontario, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Moumita Barua
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
- Division of Nephrology, University Health Network, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Toronto General Hospital Research Institute, Toronto, Ontario, Canada
| | - Sarah A. Gagliano Taliun
- Montreal Heart Institute, Montreal, Quebec, Canada
- Department of Medicine, Université de Montréal, Montreal, Quebec, Canada
- Department of Neurosciences, Université de Montréal, Montreal, Quebec, Canada
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Chen HL, Chiang HY, Chang DR, Cheng CF, Wang CCN, Lu TP, Lee CY, Chattopadhyay A, Lin YT, Lin CC, Yu PT, Huang CF, Lin CH, Yeh HC, Ting IW, Tsai HK, Chuang EY, Tin A, Tsai FJ, Kuo CC. Discovery and prioritization of genetic determinants of kidney function in 297,355 individuals from Taiwan and Japan. Nat Commun 2024; 15:9317. [PMID: 39472450 PMCID: PMC11522641 DOI: 10.1038/s41467-024-53516-7] [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: 05/30/2023] [Accepted: 10/12/2024] [Indexed: 11/02/2024] Open
Abstract
Current genome-wide association studies (GWAS) for kidney function lack ancestral diversity, limiting the applicability to broader populations. The East-Asian population is especially under-represented, despite having the highest global burden of end-stage kidney disease. We conducted a meta-analysis of multiple GWASs (n = 244,952) on estimated glomerular filtration rate and a replication dataset (n = 27,058) from Taiwan and Japan. This study identified 111 lead SNPs in 97 genomic risk loci. Functional enrichment analyses revealed that variants associated with F12 gene and a missense mutation in ABCG2 may contribute to chronic kidney disease (CKD) through influencing inflammation, coagulation, and urate metabolism pathways. In independent cohorts from Taiwan (n = 25,345) and the United Kingdom (n = 260,245), polygenic risk scores (PRSs) for CKD significantly stratified the risk of CKD (p < 0.0001). Further research is required to evaluate the clinical effectiveness of PRSCKD in the early prevention of kidney disease.
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Affiliation(s)
- Hung-Lin Chen
- Big Data Center, China Medical University Hospital, China Medical University, Taichung, Taiwan
- Department of Biomedical Informatics, College of Medicine, China Medical University, Taichung, Taiwan
| | - Hsiu-Yin Chiang
- Big Data Center, China Medical University Hospital, China Medical University, Taichung, Taiwan
- Department of Biomedical Informatics, College of Medicine, China Medical University, Taichung, Taiwan
| | - David Ray Chang
- Division of Nephrology, Department of Internal Medicine, China Medical University Hospital, China Medical University, Taichung, Taiwan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Chi-Fung Cheng
- Big Data Center, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Charles C N Wang
- Department of Bioinformatics and Medical Engineering, Asia University, Taichung, Taiwan
| | - Tzu-Pin Lu
- Institute of Health Data Analytics and Statistics, Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Chien-Yueh Lee
- Master Program in Artificial Intelligence, Innovation Frontier Institute of Research for Science and Technology, National Taipei University of Technology, Taipei, Taiwan
- Department of Electrical Engineering, National Taipei University of Technology, Taipei, Taiwan
| | - Amrita Chattopadhyay
- Big Data Center, China Medical University Hospital, China Medical University, Taichung, Taiwan
- Institute of Epidemiology and Preventive Medicine, Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Yu-Ting Lin
- Big Data Center, China Medical University Hospital, China Medical University, Taichung, Taiwan
- Department of Biomedical Informatics, College of Medicine, China Medical University, Taichung, Taiwan
| | - Che-Chen Lin
- Big Data Center, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Pei-Tzu Yu
- Big Data Center, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Chien-Fong Huang
- Big Data Center, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Chieh-Hua Lin
- Big Data Center, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Hung-Chieh Yeh
- Division of Nephrology, Department of Internal Medicine, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - I-Wen Ting
- Division of Nephrology, Department of Internal Medicine, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Huai-Kuang Tsai
- Institute of Information Science, Academia Sinica, Taipei, Taiwan
| | - Eric Y Chuang
- Biomedical Technology and Device Research Laboratories, Industrial Technology Research Institute, Hsinchu, Taiwan
- Department of Electrical Engineering, College of Electrical Engineering and Computer Science, National Taiwan University, Taipei, Taiwan
- Graduate Institute of Biomedical Electronics and Bioinformatics, College of Electrical Engineering and Computer Science, National Taiwan University, Taipei, Taiwan
| | - Adrienne Tin
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - Fuu-Jen Tsai
- School of Chinese Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan.
- Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan.
- Division of Medical Genetics, China Medical University Children's Hospital, Taichung, Taiwan.
- Department of Medical Laboratory Science & Biotechnology, Asia University, Taichung, Taiwan.
| | - Chin-Chi Kuo
- Big Data Center, China Medical University Hospital, China Medical University, Taichung, Taiwan.
- Department of Biomedical Informatics, College of Medicine, China Medical University, Taichung, Taiwan.
- Division of Nephrology, Department of Internal Medicine, China Medical University Hospital, China Medical University, Taichung, Taiwan.
- Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan.
- College of Medicine, China Medical University, Taichung, Taiwan.
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Xiao H, Li L, Yang M, Zhang X, Zhou J, Zeng J, Zhou Y, Lan X, Liu J, Lin Y, Zhong Y, Zhang X, Wang L, Cao Z, Liu P, Mei H, Cai M, Cai X, Tao Y, Zhu Y, Yu C, Hu L, Wang Y, Huang Y, Su F, Gao Y, Zhou R, Xu X, Yang H, Wang J, Zhu H, Zhou A, Jin X. Genetic analyses of 104 phenotypes in 20,900 Chinese pregnant women reveal pregnancy-specific discoveries. CELL GENOMICS 2024; 4:100633. [PMID: 39389017 PMCID: PMC11602630 DOI: 10.1016/j.xgen.2024.100633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 12/14/2023] [Accepted: 07/22/2024] [Indexed: 10/12/2024]
Abstract
Monitoring biochemical phenotypes during pregnancy is vital for maternal and fetal health, allowing early detection and management of pregnancy-related conditions to ensure safety for both. Here, we conducted a genetic analysis of 104 pregnancy phenotypes in 20,900 Chinese women. The genome-wide association study (GWAS) identified a total of 410 trait-locus associations, with 71.71% reported previously. Among the 116 novel hits for 45 phenotypes, 83 were successfully replicated. Among them, 31 were defined as potentially pregnancy-specific associations, including creatine and HELLPAR and neutrophils and ESR1, with subsequent analysis revealing enrichments in estrogen-related pathways and female reproductive tissues. The partitioning heritability underscored the significant roles of fetal blood, embryoid bodies, and female reproductive organs in pregnancy hematology and birth outcomes. Pathway analysis confirmed the intricate interplay of hormone and immune regulation, metabolism, and cell cycle during pregnancy. This study contributes to the understanding of genetic influences on pregnancy phenotypes and their implications for maternal health.
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Affiliation(s)
- Han Xiao
- Institute of Maternal and Child Health, Wuhan Children's Hospital (Wuhan Maternal and Child Health Care Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430010, China
| | - Linxuan Li
- BGI Research, Shenzhen 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Meng Yang
- Institute of Maternal and Child Health, Wuhan Children's Hospital (Wuhan Maternal and Child Health Care Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430010, China
| | - Xinyi Zhang
- BGI Research, Shenzhen 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jieqiong Zhou
- Department of Obstetrics, Wuhan Children's Hospital (Wuhan Maternal and Child Health Care Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430010, China
| | - Jingyu Zeng
- BGI Research, Shenzhen 518083, China; College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yan Zhou
- Department of Obstetrics, Wuhan Children's Hospital (Wuhan Maternal and Child Health Care Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430010, China
| | - Xianmei Lan
- BGI Research, Shenzhen 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiuying Liu
- Department of Obstetrics, Wuhan Children's Hospital (Wuhan Maternal and Child Health Care Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430010, China
| | - Ying Lin
- BGI Research, Shenzhen 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuanyuan Zhong
- Department of Obstetrics, Wuhan Children's Hospital (Wuhan Maternal and Child Health Care Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430010, China
| | - Xiaoqian Zhang
- BGI Research, Shenzhen 518083, China; College of Computer Science and Technology, Guizhou University, Guiyang 550025, China
| | - Lin Wang
- BGI Research, Shenzhen 518083, China
| | - Zhongqiang Cao
- Institute of Maternal and Child Health, Wuhan Children's Hospital (Wuhan Maternal and Child Health Care Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430010, China
| | | | - Hong Mei
- Institute of Maternal and Child Health, Wuhan Children's Hospital (Wuhan Maternal and Child Health Care Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430010, China
| | | | - Xiaonan Cai
- Institute of Maternal and Child Health, Wuhan Children's Hospital (Wuhan Maternal and Child Health Care Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430010, China
| | - Ye Tao
- BGI Research, Shenzhen 518083, China
| | - Yunqing Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China; Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing 100191, China
| | - Liqin Hu
- Institute of Maternal and Child Health, Wuhan Children's Hospital (Wuhan Maternal and Child Health Care Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430010, China
| | - Yu Wang
- BGI Research, Shenzhen 518083, China
| | - Yushan Huang
- BGI Research, Shenzhen 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | | | - Ya Gao
- BGI Research, Shenzhen 518083, China
| | | | - Xun Xu
- BGI Research, Shenzhen 518083, China; Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen 518120, China
| | - Huanming Yang
- BGI Research, Shenzhen 518083, China; Guangdong Provincial Academician Workstation of BGI Synthetic Genomics, BGI, Shenzhen 518120, China; James D. Watson Institute of Genome Sciences, Hangzhou 310058, China
| | | | - Huanhuan Zhu
- BGI Research, Shenzhen 518083, China; BGI Research, Wuhan 430074, China.
| | - Aifen Zhou
- Institute of Maternal and Child Health, Wuhan Children's Hospital (Wuhan Maternal and Child Health Care Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430010, China; Department of Obstetrics, Wuhan Children's Hospital (Wuhan Maternal and Child Health Care Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430010, China.
| | - Xin Jin
- BGI Research, Shenzhen 518083, China; BGI Research, Wuhan 430074, China; The Innovation Centre of Ministry of Education for Development and Diseases, School of Medicine, South China University of Technology, Guangzhou 510006, China; Shanxi Medical University-BGI Collaborative Center for Future Medicine, Shanxi Medical University, Taiyuan 030001, China; Shenzhen Key Laboratory of Transomics Biotechnologies, BGI Research, Shenzhen 518083, China.
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4
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Cañadas-Garre M, Baños-Jaime B, Maqueda JJ, Smyth LJ, Cappa R, Skelly R, Hill C, Brennan EP, Doyle R, Godson C, Maxwell AP, McKnight AJ. Genetic variants affecting mitochondrial function provide further insights for kidney disease. BMC Genomics 2024; 25:576. [PMID: 38858654 PMCID: PMC11163707 DOI: 10.1186/s12864-024-10449-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 05/24/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND Chronic kidney disease (CKD) is a complex disorder that has become a high prevalence global health problem, with diabetes being its predominant pathophysiologic driver. Autosomal genetic variation only explains some of the predisposition to kidney disease. Variations in the mitochondrial genome (mtDNA) and nuclear-encoded mitochondrial genes (NEMG) are implicated in susceptibility to kidney disease and CKD progression, but they have not been thoroughly explored. Our aim was to investigate the association of variation in both mtDNA and NEMG with CKD (and related traits), with a particular focus on diabetes. METHODS We used the UK Biobank (UKB) and UK-ROI, an independent collection of individuals with type 1 diabetes mellitus (T1DM) patients. RESULTS Fourteen mitochondrial variants were associated with estimated glomerular filtration rate (eGFR) in UKB. Mitochondrial variants and haplogroups U, H and J were associated with eGFR and serum variables. Mitochondrial haplogroup H was associated with all the serum variables regardless of the presence of diabetes. Mitochondrial haplogroup X was associated with end-stage kidney disease (ESKD) in UKB. We confirmed the influence of several known NEMG on kidney disease and function and found novel associations for SLC39A13, CFL1, ACP2 or ATP5G1 with serum variables and kidney damage, and for SLC4A1, NUP210 and MYH14 with ESKD. The G allele of TBC1D32-rs113987180 was associated with higher risk of ESKD in patients with diabetes (OR:9.879; CI95%:4.440-21.980; P = 2.0E-08). In UK-ROI, AGXT2-rs71615838 and SURF1-rs183853102 were associated with diabetic nephropathies, and TFB1M-rs869120 with eGFR. CONCLUSIONS We identified novel variants both in mtDNA and NEMG which may explain some of the missing heritability for CKD and kidney phenotypes. We confirmed the role of MT-ND5 and mitochondrial haplogroup H on renal disease (serum variables), and identified the MT-ND5-rs41535848G variant, along with mitochondrial haplogroup X, associated with higher risk of ESKD. Despite most of the associations were independent of diabetes, we also showed potential roles for NEMG in T1DM.
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Affiliation(s)
- Marisa Cañadas-Garre
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK.
- Genomic Oncology Area, Centre for Genomics and Oncological Research: Pfizer, GENYO, University of Granada-Andalusian Regional Government, PTS Granada. Avenida de La Ilustración 114, 18016, Granada, Spain.
- Hematology Department, Hospital Universitario Virgen de Las Nieves, Avenida de Las Fuerzas Armadas 2, 18014, Granada, Spain.
- Instituto de Investigación Biosanitaria de Granada (Ibs.GRANADA), Avda. de Madrid, 15, 18012, Granada, Spain.
| | - Blanca Baños-Jaime
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
- Instituto de Investigaciones Químicas (IIQ), Centro de Investigaciones Científicas Isla de La Cartuja (cicCartuja), Consejo Superior de Investigaciones Científicas (CSIC), Universidad de Sevilla, Avda. Américo Vespucio 49, 41092, Seville, Spain
| | - Joaquín J Maqueda
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
- Experimental Oncology Laboratory, IRCCS Rizzoli Orthopaedic Institute, 40136, Bologna, Italy
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, 40126, Bologna, Italy
| | - Laura J Smyth
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
| | - Ruaidhri Cappa
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
| | - Ryan Skelly
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
| | - Claire Hill
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
| | - Eoin P Brennan
- UCD Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
- School of Medicine, University College Dublin, Dublin, D04 V1W8, Ireland
| | - Ross Doyle
- UCD Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
- School of Medicine, University College Dublin, Dublin, D04 V1W8, Ireland
- Mater Misericordiae University Hospital, Eccles St, Dublin, D07 R2WY, Ireland
| | - Catherine Godson
- UCD Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
- School of Medicine, University College Dublin, Dublin, D04 V1W8, Ireland
| | - Alexander P Maxwell
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
- Regional Nephrology Unit, Belfast City Hospital, Level 11Lisburn Road, Belfast, BT9 7AB, UK
| | - Amy Jayne McKnight
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
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Betzler AC, Brunner C. The Role of the Transcriptional Coactivator BOB.1/OBF.1 in Adaptive Immunity. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1459:53-77. [PMID: 39017839 DOI: 10.1007/978-3-031-62731-6_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/18/2024]
Abstract
BOB.1/OBF.1 is a transcriptional coactivator involved in octamer-dependent transcription. Thereby, BOB.1/OBF.1 is involved in the transcriptional regulation of genes important for lymphocyte physiology. BOB.1/OBF.1-deficient mice reveal multiple B- and T-cell developmental defects. The most prominent defect of these mice is the complete absence of germinal centers (GCs) resulting in severely impaired T-cell-dependent immune responses. In humans, BOB.1/OBF.1 is associated with several autoimmune and inflammatory diseases but also linked to liquid and solid tumors. Although its role for B-cell development is relatively well understood, its exact role for the GC reaction and T-cell biology has long been unclear. Here, the contribution of BOB.1/OBF.1 for B-cell maturation is summarized, and recent findings regarding its function in GC B- as well as in various T-cell populations are discussed. Finally, a detailed perspective on how BOB.1/OBF.1 contributes to different pathologies is provided.
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Affiliation(s)
- Annika C Betzler
- Department of Oto-Rhino-Larnygology, Ulm University Medical Center, Ulm, Germany
- Core Facility Immune Monitoring, Ulm University, Ulm, Germany
| | - Cornelia Brunner
- Department of Oto-Rhino-Larnygology, Ulm University Medical Center, Ulm, Germany.
- Core Facility Immune Monitoring, Ulm University, Ulm, Germany.
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Bechmann LE, Emanuelsson F, Nordestgaard BG, Benn M. Genetic variation in solute carrier family 5 member 2 mimicking sodium-glucose co-transporter 2-inhibition and risk of cardiovascular disease and all-cause mortality: reduced risk not explained by lower plasma glucose. Cardiovasc Res 2023; 119:2482-2493. [PMID: 37516996 DOI: 10.1093/cvr/cvad122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 04/20/2023] [Accepted: 05/23/2023] [Indexed: 08/01/2023] Open
Abstract
AIMS Treatment with sodium-glucose co-transporter 2 (SGLT2)-inhibitors reduces the risk of cardiovascular disease and mortality, but the mechanism is unclear. We hypothesized that a functional genetic variant in solute carrier family 5 member 2 (SLC5A2), known to be associated with familial renal glucosuria, would mimic pharmacological SGLT2-inhibition, and thus provide an opportunity to examine potential mediators of the effects on lower risk of cardiovascular disease and mortality. METHODS AND RESULTS We examined 112 712 individuals from the Copenhagen City Heart Study and Copenhagen General Population Study (CCHS + CGPS), 488 687 from the UK Biobank, and 342 499 from FinnGen, genotyped for SLC5A2 rs61742739, c.1961A > G; p.(Asn654Ser). The 2.0% heterozygotes and 0.01% homozygotes were pooled as carriers and compared with the 98% non-carriers. First, we examined the risk of cardiovascular disease and mortality; second, whether carrying the variant was associated with potential mediators of the effect; and third, whether identified potential mediators could explain the observed reduced risk of cardiovascular disease and mortality. In the CCHS + CGPS, carriers vs. non-carries had a 31% lower risk of heart failure, 21% lower risk of myocardial infarction, 16% lower risk of ischaemic heart disease, and 22% lower risk of all-cause mortality. Corresponding values in meta-analyses of the three studies combined were lower risk by 10%, 6%, 6%, and 10%, respectively. The SLC5A2 rs61742739 variant was not associated with a risk of ischaemic stroke or cardiovascular mortality. Of the lower risks observed in CCHS + CGPS, lower plasma glucose mediated 2.0%(P = 0.004) on heart failure, 3.1%(P = 0.09) on myocardial infarction, 4.1%(P = 0.02) on ischaemic heart disease, and 6.0%(P = 0.39) on all-cause mortality; corresponding values in the UK Biobank were 2.9%(P = 0.70), 1.5%(P = 0.77), 4.1%(P = 0.23), and 3.1%(P = 0.21), respectively. CONCLUSION A functional genetic variant in SLC5A2, mimicking SGLT2-inhibition, was associated with a lower risk of heart failure, myocardial infarction, ischaemic heart disease, and all-cause mortality. These effects were at most minimally mediated through lower plasma glucose.
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Affiliation(s)
- Louise E Bechmann
- Department of Clinical Biochemistry, Copenhagen University Hospital-Rigshospitalet, Blegdamsvej 9, DK-2100 Copenhagen, Denmark
- Faculty of Health and Medical Sciences, Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark
| | - Frida Emanuelsson
- Department of Clinical Biochemistry, Copenhagen University Hospital-Rigshospitalet, Blegdamsvej 9, DK-2100 Copenhagen, Denmark
- Faculty of Health and Medical Sciences, Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark
| | - Børge G Nordestgaard
- Faculty of Health and Medical Sciences, Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark
- Department of Clinical Biochemistry, Copenhagen University Hospital-Herlev and Gentofte, Borgmester Ib Juuls Vej 1, DK-2730 Herlev, Denmark
- The Copenhagen General Population Study, Copenhagen University Hospital-Herlev and Gentofte, Borgmester Ib Juuls Vej 1, DK-2730 Herlev, Denmark
- The Copenhagen City Heart Study, Frederiksberg and Bispebjerg Hospital, Copenhagen University Hospital, Nordre Fasanvej 57, DK-2000 Frederiksberg, Denmark
| | - Marianne Benn
- Department of Clinical Biochemistry, Copenhagen University Hospital-Rigshospitalet, Blegdamsvej 9, DK-2100 Copenhagen, Denmark
- Faculty of Health and Medical Sciences, Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark
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Gagliano Taliun SA, Dinsmore IR, Mirshahi T, Chang AR, Paterson AD, Barua M. GWAS for the composite traits of hematuria and albuminuria. Sci Rep 2023; 13:18084. [PMID: 37872228 PMCID: PMC10593773 DOI: 10.1038/s41598-023-45102-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 10/16/2023] [Indexed: 10/25/2023] Open
Abstract
Our GWAS of hematuria in the UK Biobank identified 6 loci, some of which overlap with loci for albuminuria suggesting pleiotropy. Since clinical syndromes are often defined by combinations of traits, generating a combined phenotype can improve power to detect loci influencing multiple characteristics. Thus the composite trait of hematuria and albuminuria was chosen to enrich for glomerular pathologies. Cases had both hematuria defined by ICD codes and albuminuria defined as uACR > 3 mg/mmol. Controls had neither an ICD code for hematuria nor an uACR > 3 mg/mmol. 2429 cases and 343,509 controls from the UK Biobank were included. eGFR was lower in cases compared to controls, with the exception of the comparison in females using CKD-EPI after age adjustment. Variants at 4 loci met genome-wide significance with the following nearest genes: COL4A4, TRIM27, ETV1 and CUBN. TRIM27 is part of the extended MHC locus. All loci with the exception of ETV1 were replicated in the Geisinger MyCode cohort. The previous GWAS of hematuria reported COL4A3-COL4A4 variants and HLA-B*0801 within MHC, which is in linkage disequilibrium with the TRIM27 variant (D' = 0.59). TRIM27 is highly expressed in the tubules. Additional loci included a coding sequence variant in CUBN (p.Ala2914Val, MAF = 0.014 (A), p = 3.29E-8, OR = 2.09, 95% CI = 1.61-2.72). Overall, GWAS for the composite trait of hematuria and albuminuria identified 4 loci, 2 of which were not previously identified in a GWAS of hematuria.
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Affiliation(s)
- Sarah A Gagliano Taliun
- Department of Medicine and Department of Neurosciences, Université de Montréal, Montréal, QC, Canada
- Montréal Heart Institute, Montréal, QC, Canada
| | - Ian R Dinsmore
- Department of Genomic Health, Geisinger, Danville, PA, USA
| | | | - Alexander R Chang
- Department of Population Health Sciences, Center for Kidney Health Research, Geisinger, Danville, PA, USA
- Department of Nephrology, Geisinger, Danville, PA, USA
| | - Andrew D Paterson
- Divisions of Epidemiology and Biostatistics, Dalla Lana School of Public Health, Toronto, ON, Canada.
- Genetics and Genome Biology, Research Institute at the Hospital for Sick Children, Toronto, ON, Canada.
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada.
| | - Moumita Barua
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada.
- Division of Nephrology, University Health Network, Toronto, ON, Canada.
- Department of Medicine, University of Toronto, Toronto, ON, Canada.
- Toronto General Hospital Research Institute, 8NU-855, 200 Elizabeth Street, Toronto, ON, M5G2C4, Canada.
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8
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Solanki KV, Hu Y, Moore BS, Abedi V, Avula V, Mirshahi T, Strande NT, Bucaloiu ID, Chang AR. The Phenotypic Spectrum of COL4A3 Heterozygotes. Kidney Int Rep 2023; 8:2088-2099. [PMID: 37849993 PMCID: PMC10577321 DOI: 10.1016/j.ekir.2023.07.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 07/17/2023] [Indexed: 10/19/2023] Open
Abstract
Introduction The penetrance and phenotypic spectrum of autosomal dominant Alport Syndrome (ADAS), affecting 1 in 106, remains understudied. Methods Using data from 174,418 participants in the Geisinger MyCode/DiscovEHR study, an unselected health system-based cohort with whole exome sequencing, we identified 403 participants who were heterozygous for likely pathogenic COL4A3 variants. Phenotypic data was evaluated using International Classification of Diseases (ICD) codes, laboratory data, and chart review. To evaluate the phenotypic spectrum of genetically-determined ADAS, we matched COL4A3 heterozygotes 1:5 to nonheterozygotes using propensity scores by demographics, hypertension, diabetes, and nephrolithiasis. Results COL4A3 heterozygotes were at significantly increased risks of hematuria, decreased estimated glomerular filtration rate (eGFR), albuminuria, and kidney failure (P < 0.05 for all comparisons) but not bilateral sensorineural hearing loss (P = 0.9). Phenotypic severity was more severe for collagenous domain glycine missense variants than protein truncating variants (PTVs). For example, patients with Gly695Arg (n = 161) had markedly increased risk of dipstick hematuria (odds ratio [OR] 9.50; 95% confidence interval [CI]: 6.32, 14.28) and kidney failure (OR 7.02; 95% CI: 3.48, 14.16) whereas those with PTVs (n = 119) had moderately increased risks of dipstick hematuria (OR 1.64; 95% CI: 1.03, 2.59) and kidney failure (OR 3.44; 95% CI: 1.28, 9.22). Less than a third of patients had albuminuria screening completed, and fewer than 1 of 3 were taking inhibitors of the renin-angiotensin-aldosterone system. Conclusion This study demonstrates a wide spectrum of phenotypic severity in ADAS due to COL4A3 with phenotypic variability by genotype. Future studies are needed to evaluate the impact of earlier diagnosis, appropriate evaluation, and treatment of ADAS.
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Affiliation(s)
- Kaushal V Solanki
- Center for Kidney Health Research, Geisinger, Danville, Pennsylvania, USA
| | - Yirui Hu
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania, USA
| | - Bryn S Moore
- Department of Genomic Health, Geisinger, Danville, Pennsylvania, USA
| | - Vida Abedi
- Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania, USA; Road, Tarrytown, New York, USA
| | - Venkatesh Avula
- Department of Genomic Health, Geisinger, Danville, Pennsylvania, USA
| | - Tooraj Mirshahi
- Department of Genomic Health, Geisinger, Danville, Pennsylvania, USA
| | - Natasha T Strande
- Department of Genomic Health, Geisinger, Danville, Pennsylvania, USA
- Autism and Developmental Medicine Institute, Geisinger, Danville, Pennsylvania, USA
| | - Ion D Bucaloiu
- Department of Nephrology, Geisinger, Danville, Pennsylvania, USA
| | - Alexander R Chang
- Center for Kidney Health Research, Geisinger, Danville, Pennsylvania, USA
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania, USA
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9
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Lagou V, Jiang L, Ulrich A, Zudina L, González KSG, Balkhiyarova Z, Faggian A, Maina JG, Chen S, Todorov PV, Sharapov S, David A, Marullo L, Mägi R, Rujan RM, Ahlqvist E, Thorleifsson G, Gao Η, Εvangelou Ε, Benyamin B, Scott RA, Isaacs A, Zhao JH, Willems SM, Johnson T, Gieger C, Grallert H, Meisinger C, Müller-Nurasyid M, Strawbridge RJ, Goel A, Rybin D, Albrecht E, Jackson AU, Stringham HM, Corrêa IR, Farber-Eger E, Steinthorsdottir V, Uitterlinden AG, Munroe PB, Brown MJ, Schmidberger J, Holmen O, Thorand B, Hveem K, Wilsgaard T, Mohlke KL, Wang Z, Shmeliov A, den Hoed M, Loos RJF, Kratzer W, Haenle M, Koenig W, Boehm BO, Tan TM, Tomas A, Salem V, Barroso I, Tuomilehto J, Boehnke M, Florez JC, Hamsten A, Watkins H, Njølstad I, Wichmann HE, Caulfield MJ, Khaw KT, van Duijn CM, Hofman A, Wareham NJ, Langenberg C, Whitfield JB, Martin NG, Montgomery G, Scapoli C, Tzoulaki I, Elliott P, Thorsteinsdottir U, Stefansson K, Brittain EL, McCarthy MI, Froguel P, Sexton PM, Wootten D, Groop L, Dupuis J, Meigs JB, Deganutti G, Demirkan A, Pers TH, Reynolds CA, Aulchenko YS, Kaakinen MA, Jones B, Prokopenko I. GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification. Nat Genet 2023; 55:1448-1461. [PMID: 37679419 PMCID: PMC10484788 DOI: 10.1038/s41588-023-01462-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Accepted: 06/27/2023] [Indexed: 09/09/2023]
Abstract
Conventional measurements of fasting and postprandial blood glucose levels investigated in genome-wide association studies (GWAS) cannot capture the effects of DNA variability on 'around the clock' glucoregulatory processes. Here we show that GWAS meta-analysis of glucose measurements under nonstandardized conditions (random glucose (RG)) in 476,326 individuals of diverse ancestries and without diabetes enables locus discovery and innovative pathophysiological observations. We discovered 120 RG loci represented by 150 distinct signals, including 13 with sex-dimorphic effects, two cross-ancestry and seven rare frequency signals. Of these, 44 loci are new for glycemic traits. Regulatory, glycosylation and metagenomic annotations highlight ileum and colon tissues, indicating an underappreciated role of the gastrointestinal tract in controlling blood glucose. Functional follow-up and molecular dynamics simulations of lower frequency coding variants in glucagon-like peptide-1 receptor (GLP1R), a type 2 diabetes treatment target, reveal that optimal selection of GLP-1R agonist therapy will benefit from tailored genetic stratification. We also provide evidence from Mendelian randomization that lung function is modulated by blood glucose and that pulmonary dysfunction is a diabetes complication. Our investigation yields new insights into the biology of glucose regulation, diabetes complications and pathways for treatment stratification.
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Affiliation(s)
- Vasiliki Lagou
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Human Genetics, Wellcome Sanger Institute, Hinxton, UK
- VIB-KU Leuven Center for Brain and Disease Research, Leuven, Belgium
| | - Longda Jiang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Anna Ulrich
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
| | - Liudmila Zudina
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
| | - Karla Sofia Gutiérrez González
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Molecular Diagnostics, Clinical Laboratory, Clinica Biblica Hospital, San José, Costa Rica
| | - Zhanna Balkhiyarova
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK
| | - Alessia Faggian
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
- Laboratory for Artificial Biology, Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy
| | - Jared G Maina
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
- UMR 8199-EGID, Institut Pasteur de Lille, CNRS, University of Lille, Lille, France
| | - Shiqian Chen
- Section of Endocrinology and Investigative Medicine, Imperial College London, London, UK
| | - Petar V Todorov
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Sodbo Sharapov
- Laboratory of Glycogenomics, Institute of Cytology and Genetics SD RAS, Novosibirsk, Russia
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
| | - Alessia David
- Centre for Bioinformatics and System Biology, Department of Life Sciences, Imperial College London, London, UK
| | - Letizia Marullo
- Department of Evolutionary Biology, Genetic Section, University of Ferrara, Ferrara, Italy
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Roxana-Maria Rujan
- Centre for Sports, Exercise and Life Sciences, Coventry University, Conventry, UK
| | - Emma Ahlqvist
- Lund University Diabetes Centre, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | | | - Ηe Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Εvangelos Εvangelou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Beben Benyamin
- Australian Centre for Precision Health, University of South Australia, Adelaide, South Australia, Australia
- Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Robert A Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Aaron Isaacs
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- CARIM School for Cardiovascular Diseases and Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands
- Department of Physiology, Maastricht University, Maastricht, the Netherlands
| | - Jing Hua Zhao
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Sara M Willems
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Toby Johnson
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Christa Meisinger
- Epidemiology, Faculty of Medicine, University of Augsburg, Augsburg, Germany
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- IBE, Faculty of Medicine, LMU Munich, Munich, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Department of Medicine I, University Hospital Grosshadern, Ludwig-Maximilians-University, Munich, Germany
| | - Rona J Strawbridge
- Cardiovascular Medicine Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska University Hospital Solna, Stockholm, Sweden
- School of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Anuj Goel
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Denis Rybin
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Eva Albrecht
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | | | - Eric Farber-Eger
- Vanderbilt Institute for Clinical and Translational Research and Vanderbilt Translational and Clinical Cardiovascular Research Center, Nashville, TN, USA
| | | | - André G Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Patricia B Munroe
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Morris J Brown
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Julian Schmidberger
- Department of Internal Medicine I, Ulm University Medical Centre, Ulm, Germany
| | - Oddgeir Holmen
- Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Kristian Hveem
- K G Jebsen Centre for Genetic Epdiemiology, Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway
| | - Tom Wilsgaard
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
- Department of Clinical Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Aleksey Shmeliov
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
| | - Marcel den Hoed
- The Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Ruth J F Loos
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Wolfgang Kratzer
- Department of Internal Medicine I, Ulm University Medical Centre, Ulm, Germany
| | - Mark Haenle
- Department of Internal Medicine I, Ulm University Medical Centre, Ulm, Germany
| | - Wolfgang Koenig
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Bernhard O Boehm
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore and Department of Endocrinology, Tan Tock Seng Hospital, Singapore City, Singapore
| | - Tricia M Tan
- Section of Endocrinology and Investigative Medicine, Imperial College London, London, UK
| | - Alejandra Tomas
- Section of Cell Biology and Functional Genomics, Imperial College London, London, UK
| | - Victoria Salem
- Department of Bioengineering, Imperial College London, South Kensington Campus, London, UK
| | - Inês Barroso
- Exeter Centre of Excellence for Diabetes Research (EXCEED), University of Exeter Medical School, Exeter, UK
| | - Jaakko Tuomilehto
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Diabetes Research Unit, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Jose C Florez
- Center for Genomic Medicine and Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Anders Hamsten
- Cardiovascular Medicine Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Hugh Watkins
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Inger Njølstad
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
- Department of Clinical Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
| | - H-Erich Wichmann
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Mark J Caulfield
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Kay-Tee Khaw
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Centre for Medical Systems Biology, Leiden, the Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Netherlands Consortium for Healthy Ageing, the Hague, the Netherlands
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Computational Medicine, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - John B Whitfield
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Grant Montgomery
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, Queensland, Australia
| | - Chiara Scapoli
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, Imperial College London, London, UK
- National Institute for Health Research Imperial College London Biomedical Research Centre, Imperial College London, London, UK
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Evan L Brittain
- Vanderbilt University Medical Center and the Vanderbilt Translational and Clinical Cardiovascular Research Center, Nashville, TN, USA
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Genentech, South San Francisco, CA, USA
| | - Philippe Froguel
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- UMR 8199-EGID, Institut Pasteur de Lille, CNRS, University of Lille, Lille, France
| | - Patrick M Sexton
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
- ARC Centre for Cryo-Electron Microscopy of Membrane Proteins, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
| | - Denise Wootten
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
- ARC Centre for Cryo-Electron Microscopy of Membrane Proteins, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
| | - Leif Groop
- Lund University Diabetes Centre, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Finnish Institute for Molecular Medicine (FIMM), Helsinki University, Helsinki, Finland
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada
| | - James B Meigs
- Programs in Metabolism and Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Giuseppe Deganutti
- Centre for Sports, Exercise and Life Sciences, Coventry University, Conventry, UK
| | - Ayse Demirkan
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK
- Department of Genetics, University Medical Center Groningen, Groningen, the Netherlands
| | - Tune H Pers
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Christopher A Reynolds
- Centre for Sports, Exercise and Life Sciences, Coventry University, Conventry, UK
- School of Life Sciences, University of Essex, Colchester, UK
| | - Yurii S Aulchenko
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Laboratory of Glycogenomics, Institute of Cytology and Genetics SD RAS, Novosibirsk, Russia
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
| | - Marika A Kaakinen
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK.
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK.
| | - Ben Jones
- Section of Endocrinology and Investigative Medicine, Imperial College London, London, UK.
| | - Inga Prokopenko
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK.
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK.
- UMR 8199-EGID, Institut Pasteur de Lille, CNRS, University of Lille, Lille, France.
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10
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Bocher O, Willer CJ, Zeggini E. Unravelling the genetic architecture of human complex traits through whole genome sequencing. Nat Commun 2023; 14:3520. [PMID: 37316478 DOI: 10.1038/s41467-023-39259-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 06/06/2023] [Indexed: 06/16/2023] Open
Affiliation(s)
- Ozvan Bocher
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Cristen J Willer
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Computational Medicine and Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany.
- Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, Ismaninger Str. 22, 81675, Munich, Germany.
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11
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Solanki KV, Hu Y, Moore BS, Abedi V, Avula V, Mirshahi T, Strande NT, Bucaloiu ID, Chang AR. The Phenotypic Spectrum of COL4A3 Heterozygotes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.11.23288298. [PMID: 37163122 PMCID: PMC10168410 DOI: 10.1101/2023.04.11.23288298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Most data on Alport Syndrome (AS) due to COL4A3 are limited to families with autosomal recessive AS or severe manifestations such as focal segmental glomerulosclerosis (FSGS). Using data from 174,418 participants in the Geisinger MyCode/DiscovEHR study, an unselected health system-based cohort with whole exome sequencing, we identified 403 participants (0.2%) who were heterozygous for likely pathogenic COL4A3 variants. Phenotypic data was evaluated using International Classification of Diseases (ICD) codes, laboratory data, and chart review. To evaluate the phenotypic spectrum of genetically-determined autosomal dominant AS, we matched COL4A3 heterozygotes 1:5 to non-heterozygotes using propensity scores by demographics, hypertension, diabetes, and nephrolithiasis. COL4A3 heterozygotes were at significantly increased risks of hematuria, decreased estimated glomerular filtration rate (eGFR), albuminuria, and end-stage kidney disease (ESKD) (p<0.05 for all comparisons) but not bilateral sensorineural hearing loss (p=0.9). Phenotypic severity tended to be more severe among patients with glycine missense variants located within the collagenous domain. For example, patients with Gly695Arg (n=161) had markedly increased risk of dipstick hematuria (OR 9.47, 95% CI: 6.30, 14.22) and ESKD diagnosis (OR 7.01, 95% CI: 3.48, 14.12) whereas those with PTVs (n=119) had moderately increased risks of dipstick hematuria (OR 1.63, 95% CI: 1.03, 2.58) and ESKD diagnosis (OR 3.43, 95% CI: 1.28, 9.19). Less than a third of patients had albuminuria screening completed, and fewer than 1/3 were taking inhibitors of the renin-angiotensin-aldosterone system (RAASi). Future studies are needed to evaluate the impact of earlier diagnosis, appropriate evaluation, and treatment of ADAS.
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Affiliation(s)
| | - Yirui Hu
- Department of Population Health Sciences, Geisinger, Danville, PA
| | - Bryn S Moore
- Department of Genomic Health, Geisinger, Danville, PA
| | - Vida Abedi
- Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, Hershey, PA
| | | | | | - Natasha T Strande
- Department of Genomic Health, Geisinger, Danville, PA
- Autism and Developmental Medicine Institute, Geisinger, Danville, PA
| | | | - Alexander R Chang
- Center for Kidney Health Research, Geisinger, Danville, PA
- Department of Population Health Sciences, Geisinger, Danville, PA
- Regeneron Genetics Center, Sawmill Road, Tarrytown, NY
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12
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Wagner CA, Unwin R, Lopez-Garcia SC, Kleta R, Bockenhauer D, Walsh S. The pathophysiology of distal renal tubular acidosis. Nat Rev Nephrol 2023; 19:384-400. [PMID: 37016093 DOI: 10.1038/s41581-023-00699-9] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/27/2023] [Indexed: 04/06/2023]
Abstract
The kidneys have a central role in the control of acid-base homeostasis owing to bicarbonate reabsorption and production of ammonia and ammonium in the proximal tubule and active acid secretion along the collecting duct. Impaired acid excretion by the collecting duct system causes distal renal tubular acidosis (dRTA), which is characterized by the failure to acidify urine below pH 5.5. This defect originates from reduced function of acid-secretory type A intercalated cells. Inherited forms of dRTA are caused by variants in SLC4A1, ATP6V1B1, ATP6V0A4, FOXI1, WDR72 and probably in other genes that are yet to be discovered. Inheritance of dRTA follows autosomal-dominant and -recessive patterns. Acquired forms of dRTA are caused by various types of autoimmune diseases or adverse effects of some drugs. Incomplete dRTA is frequently found in patients with and without kidney stone disease. These patients fail to appropriately acidify their urine when challenged, suggesting that incomplete dRTA may represent an intermediate state in the spectrum of the ability to excrete acids. Unrecognized or insufficiently treated dRTA can cause rickets and failure to thrive in children, osteomalacia in adults, nephrolithiasis and nephrocalcinosis. Electrolyte disorders are also often present and poorly controlled dRTA can increase the risk of developing chronic kidney disease.
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Affiliation(s)
- Carsten A Wagner
- Institute of Physiology, University of Zurich, Zurich, Switzerland.
- Department of Renal Medicine, Royal Free Hospital, University College London, London, UK.
| | - Robert Unwin
- Department of Renal Medicine, Royal Free Hospital, University College London, London, UK
| | - Sergio C Lopez-Garcia
- Department of Renal Medicine, Royal Free Hospital, University College London, London, UK
- Department of Paediatric Nephrology, Great Ormond Street Hospital for Children, NHS Foundation Trust, London, UK
| | - Robert Kleta
- Department of Renal Medicine, Royal Free Hospital, University College London, London, UK
| | - Detlef Bockenhauer
- Department of Renal Medicine, Royal Free Hospital, University College London, London, UK
- Department of Paediatric Nephrology, Great Ormond Street Hospital for Children, NHS Foundation Trust, London, UK
| | - Stephen Walsh
- Department of Renal Medicine, Royal Free Hospital, University College London, London, UK
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13
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Groen In 't Woud S, Rood IM, Steenbergen E, Willemsen B, Dijkman HB, van Geel M, Schoots J, Wetzels JFM, Lugtenberg D, Deegens JKJ, Bongers EMHF. Kidney Disease Associated With Mono-allelic COL4A3 and COL4A4 Variants: A Case Series of 17 Families. Kidney Med 2023; 5:100607. [PMID: 36925663 PMCID: PMC10011433 DOI: 10.1016/j.xkme.2023.100607] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Rationale & Objective Mono-allelic variants in COL4A3 and COL4A4 (COL4A3/COL4A4) have been identified in a spectrum of glomerular basement membrane nephropathies, including thin basement membrane nephropathy and autosomal dominant Alport syndrome. With the increasing use of next generation sequencing, mono-allelic COL4A3/COL4A4 variants are detected more frequently, but phenotypic heterogeneity impedes counseling. We aimed to investigate the phenotypic spectrum, kidney biopsy results, and segregation patterns of patients with mono-allelic COL4A3/COL4A4 variants identified by whole exome sequencing. Study Design Case series. Setting & Participants We evaluated clinical and pathologic characteristics of 17 Dutch index patients with mono-allelic variants in COL4A3/COL4A4 detected by diagnostic whole exome sequencing and 25 affected family members with variants confirmed by Sanger sequencing. Results Eight different mono-allelic COL4A3/COL4A4 variants were identified across members of 11 families, comprising 7 glycine substituted missense variants and 1 frameshift variant. All index patients had microscopic hematuria at clinical presentation (median age 43 years) and 14 had (micro)albuminuria/proteinuria. All family members showed co-segregation of the variant with at least hematuria. At end of follow-up of all 42 individuals (median age 54 years), 16/42 patients had kidney function impairment, of whom 6 had kidney failure. Reports of kidney biopsies of 14 patients described thin basement membrane nephropathy, focal segmental glomerulosclerosis, minimal change lesions, and Alport syndrome. Electron microscopy images of 7 patients showed a significantly thinner glomerular basement membrane compared with images of patients with idiopathic focal segmental glomerulosclerosis and other hereditary glomerular diseases. No genotype-phenotype correlations could be established. Limitations Retrospective design, ascertainment bias toward severe kidney phenotypes, and familial hematuria. Conclusions This study confirms the wide phenotypic spectrum associated with mono-allelic COL4A3/COL4A4 variants, extending from isolated microscopic hematuria to kidney failure with high intra- and interfamilial variability.
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Affiliation(s)
- Sander Groen In 't Woud
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.,Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Ilse M Rood
- Department of Nephrology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Eric Steenbergen
- Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Brigith Willemsen
- Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Henry B Dijkman
- Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Michel van Geel
- Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Jeroen Schoots
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jack F M Wetzels
- Department of Nephrology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Dorien Lugtenberg
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jeroen K J Deegens
- Department of Nephrology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Ernie M H F Bongers
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
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Gregorio VD, Caparali B, Shojaei A, Ricardo S, Barua M. Alport Syndrome: Clinical Spectrum and Therapeutic Advances. Kidney Med 2023; 5:100631. [PMID: 37122389 PMCID: PMC10131117 DOI: 10.1016/j.xkme.2023.100631] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2023] Open
Abstract
Alport syndrome is a hereditary disorder characterized by kidney disease, ocular abnormalities, and sensorineural hearing loss. Work in understanding the cause of Alport syndrome and the molecular composition of the glomerular basement membrane ultimately led to the identification of COL4A3, COL4A4 (both on chromosome 2q36), and COL4A5 (chromosome Xq22), encoding the α3, α4, and α5 chains of type IV collagen, as the responsible genes. Subsequent studies suggested that autosomal recessive Alport syndrome and males with X-linked Alport syndrome have more severe disease, whereas autosomal dominant Alport syndrome and females with X-linked Alport syndrome have more variability. Variant type is also influential-protein-truncating variants in autosomal recessive Alport syndrome or males with X-linked Alport syndrome often present with severe symptoms, characterized by kidney failure, extrarenal manifestations, and lack of the α3-α4-α5(IV) network. By contrast, mild-moderate forms from missense variants display α3-α4-α5(IV) in the glomerular basement membrane and are associated with protracted kidney involvement without extrarenal manifestations. Regardless of type, therapeutic intervention for kidney involvement is focused on early initiation of angiotensin-converting enzyme inhibitors. There are several therapies under investigation including sodium/glucose cotransporter 2 inhibitors, aminoglycoside analogs, endothelin type A antagonists, lipid-modifying drugs, and hydroxychloroquine, although targeting the underlying defect through gene therapy remains in preclinical stages.
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15
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Blair DR, Hoffmann TJ, Shieh JT. Common genetic variation associated with Mendelian disease severity revealed through cryptic phenotype analysis. Nat Commun 2022; 13:3675. [PMID: 35760791 PMCID: PMC9237040 DOI: 10.1038/s41467-022-31030-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 05/30/2022] [Indexed: 11/09/2022] Open
Abstract
Clinical heterogeneity is common in Mendelian disease, but small sample sizes make it difficult to identify specific contributing factors. However, if a disease represents the severely affected extreme of a spectrum of phenotypic variation, then modifier effects may be apparent within a larger subset of the population. Analyses that take advantage of this full spectrum could have substantially increased power. To test this, we developed cryptic phenotype analysis, a model-based approach that infers quantitative traits that capture disease-related phenotypic variability using qualitative symptom data. By applying this approach to 50 Mendelian diseases in two cohorts, we identify traits that reliably quantify disease severity. We then conduct genome-wide association analyses for five of the inferred cryptic phenotypes, uncovering common variation that is predictive of Mendelian disease-related diagnoses and outcomes. Overall, this study highlights the utility of computationally-derived phenotypes and biobank-scale cohorts for investigating the complex genetic architecture of Mendelian diseases.
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Affiliation(s)
- David R Blair
- Division of Medical Genetics, Department of Pediatrics, Benioff Children's Hospital, San Francisco, CA, USA.
| | - Thomas J Hoffmann
- Institute for Human Genetics, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Joseph T Shieh
- Division of Medical Genetics, Department of Pediatrics, Benioff Children's Hospital, San Francisco, CA, USA.
- Institute for Human Genetics, San Francisco, CA, USA.
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16
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Genetics in chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference. Kidney Int 2022; 101:1126-1141. [PMID: 35460632 PMCID: PMC9922534 DOI: 10.1016/j.kint.2022.03.019] [Citation(s) in RCA: 80] [Impact Index Per Article: 26.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 03/16/2022] [Accepted: 03/29/2022] [Indexed: 01/19/2023]
Abstract
Numerous genes for monogenic kidney diseases with classical patterns of inheritance, as well as genes for complex kidney diseases that manifest in combination with environmental factors, have been discovered. Genetic findings are increasingly used to inform clinical management of nephropathies, and have led to improved diagnostics, disease surveillance, choice of therapy, and family counseling. All of these steps rely on accurate interpretation of genetic data, which can be outpaced by current rates of data collection. In March of 2021, Kidney Diseases: Improving Global Outcomes (KDIGO) held a Controversies Conference on "Genetics in Chronic Kidney Disease (CKD)" to review the current state of understanding of monogenic and complex (polygenic) kidney diseases, processes for applying genetic findings in clinical medicine, and use of genomics for defining and stratifying CKD. Given the important contribution of genetic variants to CKD, practitioners with CKD patients are advised to "think genetic," which specifically involves obtaining a family history, collecting detailed information on age of CKD onset, performing clinical examination for extrarenal symptoms, and considering genetic testing. To improve the use of genetics in nephrology, meeting participants advised developing an advanced training or subspecialty track for nephrologists, crafting guidelines for testing and treatment, and educating patients, students, and practitioners. Key areas of future research, including clinical interpretation of genome variation, electronic phenotyping, global representation, kidney-specific molecular data, polygenic scores, translational epidemiology, and open data resources, were also identified.
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17
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Gagliano Taliun SA, Sulem P, Sveinbjornsson G, Gudbjartsson DF, Stefansson K, Paterson AD, Barua M. GWAS of Hematuria. Clin J Am Soc Nephrol 2022; 17:672-683. [PMID: 35474271 PMCID: PMC9269584 DOI: 10.2215/cjn.13711021] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 03/21/2022] [Indexed: 01/25/2023]
Abstract
BACKGROUND AND OBJECTIVES Glomerular hematuria has varied causes but can have a genetic basis, including Alport syndrome and IgA nephropathy. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS We used summary statistics to identify genetic variants associated with hematuria in White British UK Biobank participants. Individuals with glomerular hematuria were enriched by excluding participants with genitourinary conditions. A strongly associated locus on chromosome 2 (COL4A4-COL4A3) was identified. The region was reimputed using the Trans-Omics for Precision Medicine Program followed by sequential rounds of regional conditional analysis, conditioning on previous genetic signals. Similarly, we applied conditional analysis to identify independent variants in the MHC region on chromosome 6 using imputed HLA haplotypes. RESULTS In total, 16,866 hematuria cases and 391,420 controls were included. Cases had higher urinary albumin-creatinine compared with controls (women: 13.01 mg/g [8.05-21.33] versus 12.12 mg/g [7.61-19.29]; P<0.001; men: 8.85 mg/g [5.66-16.19] versus 7.52 mg/g [5.04-12.39]; P<0.001) and lower eGFR (women: 88±14 versus 90±13 ml/min per 1.72 m2; P<0.001; men: 87±15 versus 90±13 ml/min per 1.72 m2; P<0.001), supporting enrichment of glomerular hematuria. Variants at six loci (PDPN, COL4A4-COL4A3, HLA-B, SORL1, PLLP, and TGFB1) met genome-wide significance (P<5E-8). At chromosome 2, COL4A4 p.Ser969X (rs35138315; minor allele frequency=0.00035; P<7.95E-35; odds ratio, 87.3; 95% confidence interval, 47.9 to 159.0) had the most significant association, and two variants in the locus remained associated with hematuria after conditioning for this variant: COL4A3 p.Gly695Arg (rs200287952; minor allele frequency=0.00021; P<2.16E-7; odds ratio, 45.5; 95% confidence interval, 11.8 to 168.0) and a common COL4A4 intron 25 variant (not previously reported; rs58261427; minor allele frequency=0.214; P<2.00E-9; odds ratio, 1.09; 95% confidence interval, 1.06 to 1.12). Of the HLA haplotypes, HLA-B (*0801; minor allele frequency=0.14; P<4.41E-24; odds ratio, 0.84; 95% confidence interval, 0.82 to 0.88) displayed the most statistically significant association. For remaining loci, we identified three novel associations, which were replicated in the deCODE dataset for dipstick hematuria (nearest genes: PDPN, SORL1, and PLLP). CONCLUSIONS Our study identifies six loci associated with hematuria, including independent variants in COL4A4-COL4A3 and HLA-B. Additionally, three novel loci are reported, including an association with an intronic variant in PDPN expressed in the podocyte. PODCAST This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_04_26_CJN13711021.mp3.
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Affiliation(s)
- Sarah A. Gagliano Taliun
- Department of Medicine, Université de Montréal, Montreal, Quebec, Canada,Department of Neurosciences, Université de Montréal, Montreal, Quebec, Canada,Research Centre, Montréal Heart Institute, Montreal, Quebec, Canada
| | | | | | | | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Andrew D. Paterson
- Division of Epidemiology, Dalla Lana School of Public Health, Toronto, Ontario, Canada,Division of Biostatistics, Dalla Lana School of Public Health, Toronto, Ontario, Canada,Genetics and Genome Biology, Research Institute at The Hospital for Sick Children, Toronto, Ontario, Canada,Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Moumita Barua
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada,Division of Nephrology, University Health Network, Toronto, Ontario, Canada,Department of Medicine, University of Toronto, Toronto, Ontario, Canada,Toronto General Hospital Research Institute, Toronto, Ontario, Canada
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18
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Joseph CB, Mariniello M, Yoshifuji A, Schiano G, Lake J, Marten J, Richmond A, Huffman JE, Campbell A, Harris SE, Troyanov S, Cocca M, Robino A, Thériault S, Eckardt KU, Wuttke M, Cheng Y, Corre T, Kolcic I, Black C, Bruat V, Concas MP, Sala C, Aeschbacher S, Schaefer F, Bergmann S, Campbell H, Olden M, Polasek O, Porteous DJ, Deary IJ, Madore F, Awadalla P, Girotto G, Ulivi S, Conen D, Wuehl E, Olinger E, Wilson JF, Bochud M, Köttgen A, Hayward C, Devuyst O. Meta-GWAS Reveals Novel Genetic Variants Associated with Urinary Excretion of Uromodulin. J Am Soc Nephrol 2022; 33:511-529. [PMID: 35228297 PMCID: PMC8975067 DOI: 10.1681/asn.2021040491] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 12/27/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Uromodulin, the most abundant protein excreted in normal urine, plays major roles in kidney physiology and disease. The mechanisms regulating the urinary excretion of uromodulin remain essentially unknown. METHODS We conducted a meta-analysis of genome-wide association studies for raw (uUMOD) and indexed to creatinine (uUCR) urinary levels of uromodulin in 29,315 individuals of European ancestry from 13 cohorts. We tested the distribution of candidate genes in kidney segments and investigated the effects of keratin-40 (KRT40) on uromodulin processing. RESULTS Two genome-wide significant signals were identified for uUMOD: a novel locus (P 1.24E-08) over the KRT40 gene coding for KRT40, a type 1 keratin expressed in the kidney, and the UMOD-PDILT locus (P 2.17E-88), with two independent sets of single nucleotide polymorphisms spread over UMOD and PDILT. Two genome-wide significant signals for uUCR were identified at the UMOD-PDILT locus and at the novel WDR72 locus previously associated with kidney function. The effect sizes for rs8067385, the index single nucleotide polymorphism in the KRT40 locus, were similar for both uUMOD and uUCR. KRT40 colocalized with uromodulin and modulating its expression in thick ascending limb (TAL) cells affected uromodulin processing and excretion. CONCLUSIONS Common variants in KRT40, WDR72, UMOD, and PDILT associate with the levels of uromodulin in urine. The expression of KRT40 affects uromodulin processing in TAL cells. These results, although limited by lack of replication, provide insights into the biology of uromodulin, the role of keratins in the kidney, and the influence of the UMOD-PDILT locus on kidney function.
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Affiliation(s)
- Christina B Joseph
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
| | - Marta Mariniello
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Ayumi Yoshifuji
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Guglielmo Schiano
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Jennifer Lake
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Jonathan Marten
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
| | - Anne Richmond
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
| | - Jennifer E Huffman
- Center for Population Genomics,VA Boston Healthcare System, Jamaica Plain, Massachusetts
- The Framingham Heart Study, Framingham, Massachusetts
| | - Archie Campbell
- Centre for Genomic & Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Stephan Troyanov
- Division of Nephrology, Hôpital du Sacre-Coeur de Montreal, Montreal, Canada
| | - Massimiliano Cocca
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
| | - Antonietta Robino
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
| | - Sébastien Thériault
- Department of Molecular Biology, Medical Biochemistry and Pathology, Laval University, Quebec City, Canada
- Population Health Research Institute, McMaster University, Hamilton, Canada
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charite Universitätsmedizin Berlin, Berlin, Germany
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Yurong Cheng
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Tanguy Corre
- Center for Primary Care and Public Health (Unisante), University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ivana Kolcic
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - Corrinda Black
- Aberdeen Centre for Health Data Science, School of Medicine, Medical Science and Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - Vanessa Bruat
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Maria Pina Concas
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
| | - Cinzia Sala
- Genetics of Common Disorders Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Franz Schaefer
- Division of Pediatric Nephrology, Center for Pediatrics and Adolescent Medicine, University Hospital Heidelberg, Heidelberg, Germany
| | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Harry Campbell
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Matthias Olden
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Ozren Polasek
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - David J Porteous
- Centre for Genomic & Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Francois Madore
- Division of Nephrology, Hôpital du Sacre-Coeur de Montreal, Montreal, Canada
| | - Philip Awadalla
- Division of Nephrology, Hôpital du Sacre-Coeur de Montreal, Montreal, Canada
| | - Giorgia Girotto
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149, Trieste, Italy
| | - Sheila Ulivi
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
| | - David Conen
- Population Health Research Institute, McMaster University, Hamilton, Canada
| | - Elke Wuehl
- Cardiology Division, University Hospital Basel, Basel, Switzerland
| | - Eric Olinger
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
- Translational and Clinical Research Institute, Newcastle upon Tyne, Newcastle, United Kingdom
| | - James F Wilson
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Murielle Bochud
- Center for Primary Care and Public Health (Unisante), University of Lausanne, Lausanne, Switzerland
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Genomic & Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Olivier Devuyst
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
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19
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First genome-wide association study investigating blood pressure and renal traits in domestic cats. Sci Rep 2022; 12:1899. [PMID: 35115544 PMCID: PMC8813908 DOI: 10.1038/s41598-022-05494-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 12/28/2021] [Indexed: 11/08/2022] Open
Abstract
Hypertension (HTN) and chronic kidney disease (CKD) are common in ageing cats. In humans, blood pressure (BP) and renal function are complex heritable traits. We performed the first feline genome-wide association study (GWAS) of quantitative traits systolic BP and creatinine and binary outcomes HTN and CKD, testing 1022 domestic cats with a discovery, replication and meta-analysis design. No variants reached experimental significance level in the discovery stage for any phenotype. Follow up of the top 9 variants for creatinine and 5 for systolic BP, one SNP reached experimental-wide significance for association with creatinine in the combined meta-analysis (chrD1.10258177; P = 1.34 × 10–6). Exploratory genetic risk score (GRS) analyses were performed. Within the discovery sample, GRS of top SNPs from the BP and creatinine GWAS show strong association with HTN and CKD but did not validate in independent replication samples. A GRS including SNPs corresponding to human CKD genes was not significant in an independent subset of cats. Gene-set enrichment and pathway-based analysis (GSEA) was performed for both quantitative phenotypes, with 30 enriched pathways with creatinine. Our results support the utility of GWASs and GSEA for genetic discovery of complex traits in cats, with the caveat of our findings requiring validation.
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Barua M, Paterson AD. Population-based studies reveal an additive role of type IV collagen variants in hematuria and albuminuria. Pediatr Nephrol 2022; 37:253-262. [PMID: 33635378 DOI: 10.1007/s00467-021-04934-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 10/31/2020] [Accepted: 01/07/2021] [Indexed: 02/08/2023]
Abstract
Specific variants in genes that encode the α3α4α5 chains of type IV collagen cause Alport syndrome (AS), which encompass a clinical spectrum from isolated hematuria to multisystem disease affecting sight, hearing and kidney function. The commonest form is X-linked Alport syndrome (XLAS; COL4A5) with autosomal AS (COL4A3 and COL4A4) comprising a minority of cases. While historic data estimates the frequency of AS at 1:5000-10,000, recent population-based genetic studies suggest the prevalence is considerably higher. Genome-wide association studies (GWAS) have been performed in the Icelandic (deCODE) and UK (UK Biobank) populations, demonstrating an association of type IV collagen gene variants with AS relevant kidney traits. In the Icelandic population, 1 in 600 carries a 2.5-kb COL4A3 coding deletion or a COL4A3 missense variant (rs200287952[A], Gly695Arg), both of which are strongly associated with hematuria and albuminuria (P values = 1.9 × 10-5 to 2.5 × 10-20). In the UK Biobank, COL4A4 rs35138315 (Ser969X; carrier frequency 0.13%) is strongly associated with both hematuria and albuminuria (P = 1.5 × 10-73). Thus, the frequency for autosomal AS is 5-16 times higher than the historic prevalence of all forms of the disorder. Furthermore, COL4A4 rs3518315 (Ser969X) is also a reported founder mutation in families with autosomal dominant focal and segmental glomerulosclerosis and autosomal recessive forms of AS. This supports an additive mode of inheritance for specific variants, wherein a number of copies of a mutation influence disease severity in a cumulative fashion. These studies did not include the X chromosome, excluding analysis of COL4A5, which represents an area for future study.
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Affiliation(s)
- Moumita Barua
- Division of Nephrology, Toronto General Hospital, 200 Elizabeth Street, 8NU-855, Toronto, ON, M5G 2C4, Canada. .,Department of Medicine, University of Toronto, Toronto, Canada. .,Toronto General Hospital Research Institute, University Health Network, Toronto, Canada. .,Institute of Medical Sciences, University of Toronto, Toronto, Canada.
| | - Andrew D Paterson
- Institute of Medical Sciences, University of Toronto, Toronto, Canada.,Divisions of Epidemiology and Biostatistics, Dalla Lana School of Public Health, Toronto, Canada.,Genetics and Genome Biology, Research Institute at Hospital for Sick Children, Toronto, Canada
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21
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22
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Long-read sequencing of 3,622 Icelanders provides insight into the role of structural variants in human diseases and other traits. Nat Genet 2021; 53:779-786. [PMID: 33972781 DOI: 10.1038/s41588-021-00865-4] [Citation(s) in RCA: 150] [Impact Index Per Article: 37.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 04/05/2021] [Indexed: 01/05/2023]
Abstract
Long-read sequencing (LRS) promises to improve the characterization of structural variants (SVs). We generated LRS data from 3,622 Icelanders and identified a median of 22,636 SVs per individual (a median of 13,353 insertions and 9,474 deletions). We discovered a set of 133,886 reliably genotyped SV alleles and imputed them into 166,281 individuals to explore their effects on diseases and other traits. We discovered an association of a rare deletion in PCSK9 with lower low-density lipoprotein (LDL) cholesterol levels, compared to the population average. We also discovered an association of a multiallelic SV in ACAN with height; we found 11 alleles that differed in the number of a 57-bp-motif repeat and observed a linear relationship between the number of repeats carried and height. These results show that SVs can be accurately characterized at the population scale using LRS data in a genome-wide non-targeted approach and demonstrate how SVs impact phenotypes.
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23
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Yeremenko N, Danger R, Baeten D, Tomilin A, Brouard S. Transcriptional regulator BOB.1: Molecular mechanisms and emerging role in chronic inflammation and autoimmunity. Autoimmun Rev 2021; 20:102833. [PMID: 33864944 DOI: 10.1016/j.autrev.2021.102833] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 01/28/2021] [Indexed: 11/19/2022]
Abstract
Lymphocytes constitute an essential and potent effector compartment of the immune system. Therefore, their development and functions must be strictly regulated to avoid inappropriate immune responses, such as autoimmune reactions. Several lines of evidence from genetics (e.g. association with multiple sclerosis and primary biliary cirrhosis), human expression studies (e.g. increased expression in target tissues and draining lymph nodes of patients with autoimmune diseases), animal models (e.g. loss of functional protein protects animals from the development of collagen-induced arthritis, experimental autoimmune encephalomyelitis, type 1 diabetes, bleomycin-induced fibrosis) strongly support a causal link between the aberrant expression of the lymphocyte-restricted transcriptional regulator BOB.1 and the development of autoimmune diseases. In this review, we summarize the current knowledge of unusual structural and functional plasticity of BOB.1, stringent regulation of its expression, and the pivotal role that BOB.1 plays in shaping B- and T-cell responses. We discuss recent developments highlighting the significant contribution of BOB.1 to the pathogenesis of autoimmune diseases and how to leverage our knowledge to target this regulator to treat autoimmune tissue inflammation.
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Affiliation(s)
- Nataliya Yeremenko
- CHU Nantes, Université de Nantes, Inserm, Centre de Recherche en Transplantation et Immunologie, UMR 1064, ITUN, Nantes, France; Amsterdam Rheumatology and Immunology Center, Department of Clinical Immunology and Rheumatology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands; Department of Experimental Immunology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.
| | - Richard Danger
- CHU Nantes, Université de Nantes, Inserm, Centre de Recherche en Transplantation et Immunologie, UMR 1064, ITUN, Nantes, France
| | - Dominique Baeten
- Amsterdam Rheumatology and Immunology Center, Department of Clinical Immunology and Rheumatology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands; Department of Experimental Immunology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Alexey Tomilin
- Institute of Cytology, Russian Academy of Sciences, St-Petersburg, Russian Federation
| | - Sophie Brouard
- CHU Nantes, Université de Nantes, Inserm, Centre de Recherche en Transplantation et Immunologie, UMR 1064, ITUN, Nantes, France
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24
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Genetic insights into rapid kidney function decline. Kidney Int 2021; 99:805-808. [PMID: 33745545 DOI: 10.1016/j.kint.2020.11.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 11/24/2020] [Indexed: 11/20/2022]
Abstract
Gorski et al. report a meta-GWAS of rapid kidney function decline in 42 longitudinal studies from the CKDGen Consortium and UK Biobank, amounting to more than 270'000 individuals with two eGFRcrea measurements. They identified genome-wide significant variants associated with two indexes of rapid kidney function decline, involving genes with a high potential for causality. These data increase our understanding of kidney function and risk of disease.
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25
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Liu XZ, Zhang H. The Effect of Sodium Glucose Cotransporter 2 Inhibitors From a Human Genetic Perspective. Front Genet 2021; 12:658012. [PMID: 33815487 PMCID: PMC8017288 DOI: 10.3389/fgene.2021.658012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Accepted: 02/26/2021] [Indexed: 11/19/2022] Open
Affiliation(s)
- Xing-zi Liu
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education of China, Beijing, China
| | - Hong Zhang
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education of China, Beijing, China
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26
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Abstract
Kidney stone disease (nephrolithiasis) is a common problem that can be associated with alterations in urinary solute composition including hypercalciuria. Studies suggest that the prevalence of monogenic kidney stone disorders, including renal tubular acidosis with deafness, Bartter syndrome, primary hyperoxaluria and cystinuria, in patients attending kidney stone clinics is ∼15%. However, for the majority of individuals, nephrolithiasis has a multifactorial aetiology involving genetic and environmental factors. Nonetheless, the genetic influence on stone formation in these idiopathic stone formers remains considerable and twin studies estimate a heritability of >45% for nephrolithiasis and >50% for hypercalciuria. The contribution of polygenic influences from multiple loci have been investigated by genome-wide association and candidate gene studies, which indicate that a number of genes and molecular pathways contribute to the risk of stone formation. Genetic approaches, studying both monogenic and polygenic factors in nephrolithiasis, have revealed that the following have important roles in the aetiology of kidney stones: transporters and channels; ions, protons and amino acids; the calcium-sensing receptor (a G protein-coupled receptor) signalling pathway; and the metabolic pathways for vitamin D, oxalate, cysteine, purines and uric acid. These advances, which have increased our understanding of the pathogenesis of nephrolithiasis, will hopefully facilitate the future development of targeted therapies for precision medicine approaches in patients with nephrolithiasis.
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Affiliation(s)
- Sarah A Howles
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK.,Academic Endocrine Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Rajesh V Thakker
- Academic Endocrine Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
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27
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Abstract
Acid-base balance is critical for normal life. Acute and chronic disturbances impact cellular energy metabolism, endocrine signaling, ion channel activity, neuronal activity, and cardiovascular functions such as cardiac contractility and vascular blood flow. Maintenance and adaptation of acid-base homeostasis are mostly controlled by respiration and kidney. The kidney contributes to acid-base balance by reabsorbing filtered bicarbonate, regenerating bicarbonate through ammoniagenesis and generation of protons, and by excreting acid. This review focuses on acid-base disorders caused by renal processes, both inherited and acquired. Distinct rare inherited monogenic diseases affecting acid-base handling in the proximal tubule and collecting duct have been identified. In the proximal tubule, mutations of solute carrier 4A4 (SLC4A4) (electrogenic Na+/HCO3--cotransporter Na+/bicarbonate cotransporter e1 [NBCe1]) and other genes such as CLCN5 (Cl-/H+-antiporter), SLC2A2 (GLUT2 glucose transporter), or EHHADH (enoyl-CoA, hydratase/3-hydroxyacyl CoA dehydrogenase) causing more generalized proximal tubule dysfunction can cause proximal renal tubular acidosis resulting from bicarbonate wasting and reduced ammoniagenesis. Mutations in adenosine triphosphate ATP6V1 (B1 H+-ATPase subunit), ATPV0A4 (a4 H+-ATPase subunit), SLC4A1 (anion exchanger 1), and FOXI1 (forkhead transcription factor) cause distal renal tubular acidosis type I. Carbonic anhydrase II mutations affect several nephron segments and give rise to a mixed proximal and distal phenotype. Finally, mutations in genes affecting aldosterone synthesis, signaling, or downstream targets can lead to hyperkalemic variants of renal tubular acidosis (type IV). More common forms of renal acidosis are found in patients with advanced stages of chronic kidney disease and are owing, at least in part, to a reduced capacity for ammoniagenesis.
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Affiliation(s)
- Carsten A Wagner
- Institute of Physiology, University of Zurich, Zurich, Switzerland; National Center for Competence in Research Kidney, Switzerland.
| | - Pedro H Imenez Silva
- Institute of Physiology, University of Zurich, Zurich, Switzerland; National Center for Competence in Research Kidney, Switzerland
| | - Soline Bourgeois
- Institute of Physiology, University of Zurich, Zurich, Switzerland; National Center for Competence in Research Kidney, Switzerland
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28
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Abstract
PURPOSE OF REVIEW Megalin is well known for its role in the reabsorption of proteins from the ultrafiltrate. Recent studies suggest that megalin also reabsorbs renin and angiotensinogen. Indeed, without megalin urinary renin and angiotensinogen levels massively increase, and even prorenin becomes detectable in urine. RECENT FINDINGS Intriguingly, megalin might also contribute to renal angiotensin production, as evidenced from studies in megalin knockout mice. This review discusses these topics critically, concluding that urinary renin-angiotensin system components reflect diminished reabsorption rather than release from renal tissue sites and that alterations in renal renin levels or megalin-dependent signaling need to be ruled out before concluding that angiotensin production at renal tissue sites is truly megalin dependent. Future studies should evaluate megalin-mediated renin/angiotensinogen transcytosis (allowing interstitial angiotensin generation), and determine whether megalin prefers prorenin over renin, thus explaining why urine normally contains no prorenin.
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Affiliation(s)
- Yuan Sun
- Department of Internal Medicine, Division of Pharmacology and Vascular Medicine, Erasmus MC, room EE1418b, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands
- Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, Shenzhen, China
- Translational Medicine Collaborative Innovation Center, The Second Clinical Medical College (Shenzhen People's Hospital) of Jinan University, Shenzhen, China
| | - Xifeng Lu
- Department of Physiology, Shenzhen University Health Science Center, Shenzhen University, Shenzhen, China
| | - A H Jan Danser
- Department of Internal Medicine, Division of Pharmacology and Vascular Medicine, Erasmus MC, room EE1418b, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands.
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29
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Eggertsson HP, Kristmundsdottir S, Beyter D, Jonsson H, Skuladottir A, Hardarson MT, Gudbjartsson DF, Stefansson K, Halldorsson BV, Melsted P. GraphTyper2 enables population-scale genotyping of structural variation using pangenome graphs. Nat Commun 2019; 10:5402. [PMID: 31776332 PMCID: PMC6881350 DOI: 10.1038/s41467-019-13341-9] [Citation(s) in RCA: 97] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Accepted: 10/30/2019] [Indexed: 12/31/2022] Open
Abstract
Analysis of sequence diversity in the human genome is fundamental for genetic studies. Structural variants (SVs) are frequently omitted in sequence analysis studies, although each has a relatively large impact on the genome. Here, we present GraphTyper2, which uses pangenome graphs to genotype SVs and small variants using short-reads. Comparison to the syndip benchmark dataset shows that our SV genotyping is sensitive and variant segregation in families demonstrates the accuracy of our approach. We demonstrate that incorporating public assembly data into our pipeline greatly improves sensitivity, particularly for large insertions. We validate 6,812 SVs on average per genome using long-read data of 41 Icelanders. We show that GraphTyper2 can simultaneously genotype tens of thousands of whole-genomes by characterizing 60 million small variants and half a million SVs in 49,962 Icelanders, including 80 thousand SVs with high-confidence.
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Affiliation(s)
- Hannes P Eggertsson
- deCODE genetics/Amgen Inc., Sturlugata 8, Reykjavik, Iceland.
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland.
| | - Snaedis Kristmundsdottir
- deCODE genetics/Amgen Inc., Sturlugata 8, Reykjavik, Iceland
- School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
| | - Doruk Beyter
- deCODE genetics/Amgen Inc., Sturlugata 8, Reykjavik, Iceland
| | - Hakon Jonsson
- deCODE genetics/Amgen Inc., Sturlugata 8, Reykjavik, Iceland
| | | | | | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Sturlugata 8, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen Inc., Sturlugata 8, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Bjarni V Halldorsson
- deCODE genetics/Amgen Inc., Sturlugata 8, Reykjavik, Iceland.
- School of Science and Engineering, Reykjavik University, Reykjavik, Iceland.
| | - Pall Melsted
- deCODE genetics/Amgen Inc., Sturlugata 8, Reykjavik, Iceland.
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland.
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30
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Howles SA, Wiberg A, Goldsworthy M, Bayliss AL, Gluck AK, Ng M, Grout E, Tanikawa C, Kamatani Y, Terao C, Takahashi A, Kubo M, Matsuda K, Thakker RV, Turney BW, Furniss D. Genetic variants of calcium and vitamin D metabolism in kidney stone disease. Nat Commun 2019; 10:5175. [PMID: 31729369 PMCID: PMC6858460 DOI: 10.1038/s41467-019-13145-x] [Citation(s) in RCA: 87] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Accepted: 10/16/2019] [Indexed: 01/18/2023] Open
Abstract
Kidney stone disease (nephrolithiasis) is a major clinical and economic health burden with a heritability of ~45–60%. We present genome-wide association studies in British and Japanese populations and a trans-ethnic meta-analysis that include 12,123 cases and 417,378 controls, and identify 20 nephrolithiasis-associated loci, seven of which are previously unreported. A CYP24A1 locus is predicted to affect vitamin D metabolism and five loci, DGKD, DGKH, WDR72, GPIC1, and BCR, are predicted to influence calcium-sensing receptor (CaSR) signaling. In a validation cohort of only nephrolithiasis patients, the CYP24A1-associated locus correlates with serum calcium concentration and a number of nephrolithiasis episodes while the DGKD-associated locus correlates with urinary calcium excretion. In vitro, DGKD knockdown impairs CaSR-signal transduction, an effect rectified with the calcimimetic cinacalcet. Our findings indicate that studies of genotype-guided precision-medicine approaches, including withholding vitamin D supplementation and targeting vitamin D activation or CaSR-signaling pathways in patients with recurrent kidney stones, are warranted. Kidney stones form in the presence of overabundance of crystal-forming substances such as Ca2+ and oxalate. Here, the authors report genome-wide association analyses for kidney stone disease, report seven previously unknown loci and find that some of these loci also associate with Ca2+ concentration and excretion.
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Affiliation(s)
- Sarah A Howles
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK. .,Academic Endocrine Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
| | - Akira Wiberg
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Michelle Goldsworthy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK.,Academic Endocrine Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Asha L Bayliss
- Academic Endocrine Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Anna K Gluck
- Academic Endocrine Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Michael Ng
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Emily Grout
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Chizu Tanikawa
- Laboratory of Genome Technology, Human Genome Centre, University of Tokyo, Tokyo, Japan
| | - Yoichiro Kamatani
- RIKEN Centre for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Chikashi Terao
- RIKEN Centre for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Atsushi Takahashi
- RIKEN Centre for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Michiaki Kubo
- RIKEN Centre for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Koichi Matsuda
- Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, University of Tokyo, Tokyo, Japan
| | - Rajesh V Thakker
- Academic Endocrine Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Benjamin W Turney
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Dominic Furniss
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
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