Suchergebnisse

Only Vanderbilt University affiliated authors are listed on VUIR. For a full list of authors, access the version of record at https://www.nature.com/articles/s41467-019-11704-w ; 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. ; This work was supported by VA grant I01BX003360 (to A.M.H.), for the contributions of A. G., A.M.H. and D.R.V.E. This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration. Acknowledgment of VA Million Veteran Program leadership and staff contributions can be found in Supplementary Note 2. This work was supported using resources and facilities of the VA Informatics and Computing Infrastructure (VINCI), VA HSR RES 13-457. We would also like to acknowledge the grants Genetics of Cardiometabolic Diseases in the VA Population (BX-003362-01); Veterans Affairs Office of Research and Development; PIs: PS Tsao and K-M Chang and U.S. Department of Veterans Affairs IK2-CX001870 (Damrauer PI); U.S. Department of Veterans Affairs I01-BX002641(PI Tsao and Chang). This project was supported in part the by VA Clinical Science research and Development investigator-initiated grant CX000570-06(Roumie). AMH was further supported by 1I01CX000982. This publication does not represent the views of the Department of Veterans Affairs or the United States Government. The authors are grateful to members of the Chronic Kidney Disease Genetics (CKDGen) Consortium for providing summary data for replication. A full list of CKDGen consortium membership can be found in Supplementary Note 3. D.R.V.E. and T.L.E. received support from NIH/NHLBI (HL121429). J.N.H. was supported by the Vanderbilt Molecular and Genetic Epidemiology of Cancer (MAGEC) training program, funded by T32CA160056 (PI: X.O. Shu). The work of J.N.H. and A.G. is supported by K12HD043483 (PI: K.E. Hartmann). J.M.K. is supported by the Vanderbilt Genomic Medicine Training Program. The Vanderbilt Genomic Medicine Training Program is supported by an institutional training grant (T32HG008341) from the National Human Genome Research Institute of the National Institute of Health. K.S. was funded by R01DK076077, R01DK105821, and DP3DK108220. The work of A.K. was supported by KO 3598/3-1 and CRCs 1140 and 992 of the German Research Foundation. The work of M.G. was supported by DFG BO3815/4-1. The work of M.W. was supported by DFG CRC 1140 and the Else Kroener Fresenius Forschungskolleg NAKSYS, and Y. L. was supported by DFG KO 3598/4-1. C.P.C. was supported by K23AR064768 (NIAMS) and the Rheumatology Research Foundation. C.R.-C. was supported by NIH/NIDDK K01DK109019. A dataset used for the analyses described were obtained from Vanderbilt University Medical Center's BioVU which is supported by institutional funding, the 1S10RR025141-01 instrumentation award, and by the CTSA grant UL1TR000445 from NCATS/NIH. Additional funding provided by the NIH through grants P50GM115305 and U19HL065962. The authors wish to acknowledge the technical support of the VANTAGE and VANGARD core facilities, supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA068485) and Vanderbilt Vision Center (P30 EY08126).

Endometriosis is a heritable hormone-dependent gynecological disorder, associated with severe pelvic pain and reduced fertility; however, its molecular mechanisms remain largely unknown. Here we perform a meta-analysis of 11 genome-wide association case-control data sets, totalling 17,045 endometriosis cases and 191,596 controls. In addition to replicating previously reported loci, we identify five novel loci significantly associated with endometriosis risk (P<5 × 10−8), implicating genes involved in sex steroid hormone pathways (FN1, CCDC170, ESR1, SYNE1 and FSHB). Conditional analysis identified five secondary association signals, including two at the ESR1 locus, resulting in 19 independent single nucleotide polymorphisms (SNPs) robustly associated with endometriosis, which together explain up to 5.19% of variance in endometriosis. These results highlight novel variants in or near specific genes with important roles in sex steroid hormone signalling and function, and offer unique opportunities for more targeted functional research efforts. ; We acknowledge all the study participants in 11 individual endometriosis studies that provided an opportunity for the current study. We also thank many hospital directors and staff, gynaecologists, general practitioners and pathology services in Australia who provided assistance with confirmation of diagnoses. We would like to thank the research participants and employees of 23andMe for making this work possible. We thank the subjects of the Icelandic deCODE study for their participation. We thank research staff and clinicians for providing diagnostic confirmation for the OX data set. We would like to express our gratitude to the staff and members of the Biobank Japan and Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences for their outstanding assistance. The QIMR study was supported by grants from the National Health and Medical Research Council (NHMRC) of Australia (241,944, 339,462, 389,927, 389,875, 389,891, 389,892, 389,938, 443,036, 442,915, 442,981, 496,610, 496,739, 552,485, 552,498, 1,026,033 and 1,050,208), the Cooperative Research Centre for Discovery of Genes for Common Human Diseases (CRC), Cerylid Biosciences (Melbourne) and donations from N. Hawkins and S. Hawkins. Analyses of the QIMRHCS and OX GWAS were supported by the Wellcome Trust (WT084766/Z/08/Z) and makes use of WTCCC2 control data generated by the Wellcome Trust Case-Control Consortium (awards 076113 and 085475). The iPSYCH study was funded by The Lundbeck Foundation, Denmark (R102-A9118, R155-2014-1724 ), and the research has been conducted using the Danish National Biobank resource supported by the Novo Nordisk Foundation. A full list of the investigators who contributed to the generation of these data is available from http://www.wtccc.org.uk. D.R.N. was supported in part by the NHMRC Fellowship (613674) and ARC Future Fellowship (FT0991022) schemes. E.G.H. (631096) and G.W.M. (339446, 619667) were supported by the NHMRC Fellowships Scheme. S.M. is supported by an Australian Research Council Future Fellowship. A.P.M. was supported by a Wellcome Trust Senior Research Fellowship (award WT098017). N.R. was supported by funding from the Medical Research Council UK (MR/K011480/1). This study was funded by the BioBank Japan project, which is supported by the Ministry of Education, Culture, Sports, Sciences and Technology of Japanese government. ; Peer Reviewed

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files ; Endometriosis is a heritable hormone-dependent gynecological disorder, associated with severe pelvic pain and reduced fertility; however, its molecular mechanisms remain largely unknown. Here we perform a meta-analysis of 11 genome-wide association case-control data sets, totalling 17,045 endometriosis cases and 191,596 controls. In addition to replicating previously reported loci, we identify five novel loci significantly associated with endometriosis risk (P<5 × 10(-8)), implicating genes involved in sex steroid hormone pathways (FN1, CCDC170, ESR1, SYNE1 and FSHB). Conditional analysis identified five secondary association signals, including two at the ESR1 locus, resulting in 19 independent single nucleotide polymorphisms (SNPs) robustly associated with endometriosis, which together explain up to 5.19% of variance in endometriosis. These results highlight novel variants in or near specific genes with important roles in sex steroid hormone signalling and function, and offer unique opportunities for more targeted functional research efforts. ; National Health and Medical Research Council (NHMRC) of Australia Cooperative Research Centre for Discovery of Genes for Common Human Diseases (CRC), Cerylid Biosciences (Melbourne) Wellcome Trust Wellcome Trust Case-Control Consortium Lundbeck Foundation, Denmark Novo Nordisk Foundation NHMRC ARC NHMRC Fellowships Scheme Australian Research Council Wellcome Trust Senior Research Fellowship Medical Research Council UK BioBank Japan project - Ministry of Education, Culture, Sports, Sciences and Technology of Japanese government