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      Mapping eGFR loci to the renal transcriptome and phenome in the VA Million Veteran Program

      research-article
      1 , 2 , 1 , 3 , 4 , 1 , 3 , 5 , 5 , 1 , 6 , 1 , 6 , 7 , 7 , 1 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 10 , 7 , 19 , 20 , 21 , 11 , 22 , 19 , 13 , 14 , 23 , 24 , 25 , 26 , 27 , 11 , 28 , 29 , 30 , 31 , 19 , 32 , 5 , 1 , 6 , , 1 , 7 ,
      Nature Communications
      Nature Publishing Group UK
      Chronic kidney disease, Kidney, Gene expression

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          Abstract

          Chronic kidney disease (CKD), defined by low estimated glomerular filtration rate (eGFR), contributes to global morbidity and mortality. Here we conduct a transethnic Genome-Wide Association Study of eGFR in 280,722 participants of the Million Veteran Program (MVP), with replication in 765,289 participants from the Chronic Kidney Disease Genetics (CKDGen) Consortium. We identify 82 previously unreported variants, confirm 54 loci, and report interesting findings including association of the sickle cell allele of betaglobin among non-Hispanic blacks. Our transcriptome-wide association study of kidney function in healthy kidney tissue identifies 36 previously unreported and nine known genes, and maps gene expression to renal cell types. In a Phenome-Wide Association Study in 192,868 MVP participants using a weighted genetic score we detect associations with CKD stages and complications and kidney stones. This investigation reinterprets the genetic architecture of kidney function to identify the gene, tissue, and anatomical context of renal homeostasis and the clinical consequences of dysregulation.

          Abstract

          Persistently low levels of estimated glomerular filtration rate (eGFR) are a biomarker of chronic kidney disease. Here, the authors reinterpret the genetic architecture of kidney function across ancestries, to identify not only genes, but the tissue and anatomical contexts of renal homeostasis.

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          Most cited references47

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          Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics

          Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes.
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            An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

            To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10−8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action–associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.
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              Connecting genetic risk to disease end points through the human blood plasma proteome

              Genome-wide association studies (GWAS) with intermediate phenotypes, like changes in metabolite and protein levels, provide functional evidence to map disease associations and translate them into clinical applications. However, although hundreds of genetic variants have been associated with complex disorders, the underlying molecular pathways often remain elusive. Associations with intermediate traits are key in establishing functional links between GWAS-identified risk-variants and disease end points. Here we describe a GWAS using a highly multiplexed aptamer-based affinity proteomics platform. We quantify 539 associations between protein levels and gene variants (pQTLs) in a German cohort and replicate over half of them in an Arab and Asian cohort. Fifty-five of the replicated pQTLs are located in trans. Our associations overlap with 57 genetic risk loci for 42 unique disease end points. We integrate this information into a genome-proteome network and provide an interactive web-tool for interrogations. Our results provide a basis for novel approaches to pharmaceutical and diagnostic applications.
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                Author and article information

                Contributors
                todd.l.edwards@vanderbilt.edu
                adriana.hung@vanderbilt.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                26 August 2019
                26 August 2019
                2019
                : 10
                : 3842
                Affiliations
                [1 ]ISNI 0000 0001 2264 7217, GRID grid.152326.1, Biomedical Laboratory Research and Development, , Tennessee Valley Healthcare System (626)/Vanderbilt University, ; Nashville, TN USA
                [2 ]ISNI 0000 0004 1936 9916, GRID grid.412807.8, Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, , Vanderbilt University Medical Center, ; Nashville, TN USA
                [3 ]ISNI 0000 0004 1936 9916, GRID grid.412807.8, Department of Obstetrics & Gynecology, Vanderbilt Genetics Institute, Vanderbilt Epidemiology Center, , Vanderbilt University Medical Center, ; Nashville, TN USA
                [4 ]ISNI 0000 0004 1936 9916, GRID grid.412807.8, Department of Biomedical Informatics, , Vanderbilt University Medical Center, ; Nashville, TN USA
                [5 ]ISNI 0000 0004 1936 8972, GRID grid.25879.31, Department of Medicine, Renal Electrolyte and Hypertension Division, , University of Pennsylvania, ; Philadelphia, PA USA
                [6 ]ISNI 0000 0004 1936 9916, GRID grid.412807.8, Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, , Vanderbilt University Medical Center, ; Nashville, TN USA
                [7 ]ISNI 0000 0004 1936 9916, GRID grid.412807.8, Division of Nephrology and Hypertension, Department of Medicine, , Vanderbilt University Medical Center, ; Nashville, TN USA
                [8 ]ISNI 0000 0004 1936 9916, GRID grid.412807.8, Divisions of Rheumatology and Clinical Pharmacology, Department of Medicine, , Vanderbilt University Medical Center, ; Nashville, TN USA
                [9 ]Veteran Affairs Administration Tennessee Valley VA Health Care System Geriatric Research Education Clinical Center (GRECC), Nashville, TN USA
                [10 ]ISNI 0000 0004 1936 9916, GRID grid.412807.8, Department of Medicine, , Vanderbilt University Medical Center, ; Nashville, TN USA
                [11 ]ISNI 0000 0004 4657 1992, GRID grid.410370.1, VA Boston Health Care System, ; Boston, MA USA
                [12 ]ISNI 000000041936754X, GRID grid.38142.3c, Center for Genomic Medicine, Massachusetts General Hospital, , Harvard Medical School, ; Boston, MA USA
                [13 ]GRID grid.66859.34, Program in Medical and Population Genetics, , Broad Institute of Harvard and MIT, ; Cambridge, MA USA
                [14 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Surgery, Massachusetts General Hospital, , Harvard Medical School, ; Boston, MA USA
                [15 ]ISNI 0000 0004 0420 350X, GRID grid.410355.6, Department of Surgery, , Corporal Michael Crescenz VA Medical Center, ; Philadelphia, PA USA
                [16 ]ISNI 0000 0004 1936 8972, GRID grid.25879.31, Department of Surgery, Perelman School of Medicine, , University of Pennsylvania, ; Philadelphia, PA USA
                [17 ]ISNI 0000 0000 9555 3716, GRID grid.280807.5, VA Salt Lake City Health Care System, ; Salt Lake City, UT USA
                [18 ]ISNI 0000 0001 2193 0096, GRID grid.223827.e, University of Utah School of Medicine, ; Salt Lake City, UT USA
                [19 ]Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Centre—University of Freiburg, Freiburg, Germany
                [20 ]ISNI 0000 0001 2190 5763, GRID grid.7727.5, Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, , University of Regensburg, ; Regensburg, Germany
                [21 ]ISNI 0000 0000 9194 7179, GRID grid.411941.8, Department of Nephrology, , University Hospital Regensburg, ; Regensburg, Germany
                [22 ]ISNI 0000 0001 2193 0096, GRID grid.223827.e, Division of Nephrology, Department of Internal Medicine, , University of Utah School of Medicine, ; Salt Lake City, UT USA
                [23 ]ISNI 0000 0004 4657 1992, GRID grid.410370.1, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), , VA Boston Healthcare System, ; Boston, MA USA
                [24 ]ISNI 0000 0004 0419 4084, GRID grid.414026.5, Atlanta VA Medical Center, ; Atlanta, GA USA
                [25 ]Emory Clinical Cardiovascular Research Institute, Atlanta, GA USA
                [26 ]ISNI 0000 0004 0419 2556, GRID grid.280747.e, VA Palo Alto Health Care System, ; Palo Alto, CA USA
                [27 ]ISNI 0000000419368956, GRID grid.168010.e, Department of Medicine, Stanford University School of Medicine, ; Stanford, CA USA
                [28 ]ISNI 000000041936754X, GRID grid.38142.3c, Section of Cardiology and Department of Medicine, Brigham and Women’s Hospital, , Harvard Medical School, ; Boston, MA USA
                [29 ]ISNI 0000 0004 0420 4721, GRID grid.413847.d, Nephrology Section, , Memphis VA Medical Center, ; Memphis, TN USA
                [30 ]ISNI 0000 0004 0386 9246, GRID grid.267301.1, Division of Nephrology, , University of Tennessee Health Science Center, ; Memphis, TN USA
                [31 ]Institute for Biomedicine, Eurac Research, Bolzano, Italy
                [32 ]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Department of Epidemiology, , Johns Hopkins Bloomberg School of Public Health, ; Baltimore, MD USA
                Author information
                http://orcid.org/0000-0001-7479-0920
                http://orcid.org/0000-0002-7786-4670
                http://orcid.org/0000-0002-5728-912X
                http://orcid.org/0000-0002-4636-5780
                http://orcid.org/0000-0002-4898-3865
                http://orcid.org/0000-0003-3420-5082
                http://orcid.org/0000-0002-9103-5860
                http://orcid.org/0000-0002-3839-0281
                http://orcid.org/0000-0003-2651-8791
                http://orcid.org/0000-0002-4119-0109
                http://orcid.org/0000-0002-4671-3714
                http://orcid.org/0000-0002-1005-3726
                http://orcid.org/0000-0003-4318-6119
                http://orcid.org/0000-0002-3203-1608
                Article
                11704
                10.1038/s41467-019-11704-w
                6710266
                31451708
                34e8dbd6-dad0-467d-8365-7ea805c82cbb
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 15 January 2019
                : 23 July 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/100009633, U.S. Department of Health & Human Services | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD);
                Award ID: K12 HD043483
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000062, U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases);
                Award ID: K01DK109019
                Award ID: R01DK076077
                Award ID: R01DK105821
                Award ID: DP3DK108220
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft (German Research Foundation);
                Award ID: DFG CRC 1140
                Award ID: DFG BO-3815/4-1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100003042, Else Kröner-Fresenius-Stiftung (Else Kroner-Fresenius Foundation);
                Award ID: NAKSYS
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000738, U.S. Department of Veterans Affairs (Department of Veterans Affairs);
                Award ID: I01-BX002641
                Award Recipient :
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                © The Author(s) 2019

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                chronic kidney disease,kidney,gene expression
                Uncategorized
                chronic kidney disease, kidney, gene expression

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