MedStar Authors catalog › Details for: Meta-analysis of genome-wide linkage scans for renal function traits. [Review]
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Meta-analysis of genome-wide linkage scans for renal function traits. [Review]

by Umans, Jason G.
Citation: Nephrology Dialysis Transplantation. 27(2):647-56, 2012 Feb..Journal: Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.ISSN: 0931-0509.Full author list: Rao M; Mottl AK; Cole SA; Umans JG; Freedman BI; Bowden DW; Langefeld CD; Fox CS; Yang Q; Cupples A; Iyengar SK; Hunt SC; Trikalinos TA.UI/PMID: 21622988.Subject(s): Female | *Genetic Linkage | *Genetic Predisposition to Disease/ep [Epidemiology] | *Genome-Wide Association Study/mt [Methods] | Glomerular Filtration Rate/ge [Genetics] | Humans | Kidney Failure, Chronic/di [Diagnosis] | Kidney Failure, Chronic/ep [Epidemiology] | *Kidney Failure, Chronic/ge [Genetics] | Male | Sensitivity and SpecificityInstitution(s): MedStar Health Research InstituteActivity type: Journal Article.Medline article type(s): Journal Article | Meta-Analysis | Research Support, N.I.H., Extramural | Research Support, Non-U.S. Gov't | ReviewOnline resources: Click here to access online Digital Object Identifier: http://dx.doi.org/10.1093/ndt/gfr255 (Click here) Abbreviated citation: Nephrol Dial Transplant. 27(2):647-56, 2012 Feb.Local Holdings: Available online from MWHC library: 1996 - present, Available in print through MWHC library: 1999 - 2006.Abstract: BACKGROUND: Several genome scans have explored the linkage of chronic kidney disease phenotypes to chromosomic regions with disparate results. Genome scan meta-analysis (GSMA) is a quantitative method to synthesize linkage results from independent studies and assess their concordance.Abstract: METHODS: We searched PubMed to identify genome linkage analyses of renal function traits in humans, such as estimated glomerular filtration rate (GFR), albuminuria, serum creatinine concentration and creatinine clearance. We contacted authors for numerical data and extracted information from individual studies. We applied the GSMA nonparametric approach to combine results across 14 linkage studies for GFR, 11 linkage studies for albumin creatinine ratio, 11 linkage studies for serum creatinine and 4 linkage studies for creatinine clearance.Abstract: RESULTS: No chromosomal region reached genome-wide statistical significance in the main analysis which included all scans under each phenotype; however, regions on Chromosomes 7, 10 and 16 reached suggestive significance for linkage to two or more phenotypes. Subgroup analyses by disease status or ethnicity did not yield additional information.Abstract: CONCLUSIONS: While heterogeneity across populations, methodologies and study designs likely explain this lack of agreement, it is possible that linkage scan methodologies lack the resolution for investigating complex traits. Combining family-based linkage studies with genome-wide association studies may be a powerful approach to detect private mutations contributing to complex renal phenotypes.

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