Journal Article

Meta-analysis of genome-wide linkage scans for renal function traits

Madhumathi Rao, Amy K. Mottl, Shelley A. Cole, Jason G. Umans, Barry I. Freedman, Donald W. Bowden, Carl D. Langefeld, Caroline S. Fox, Qiong Yang, Adrienne Cupples, Sudha K. Iyengar, Steven C. Hunt and Thomas A. Trikalinos

in Nephrology Dialysis Transplantation

Published on behalf of European Renal Association - European Dialysis and Transplant Assoc

Volume 27, issue 2, pages 647-656
Published in print February 2012 | ISSN: 0931-0509
Published online May 2011 | e-ISSN: 1460-2385 | DOI: http://dx.doi.org/10.1093/ndt/gfr255
Meta-analysis of genome-wide linkage scans for renal function traits

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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.

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.

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.

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.

Keywords: albuminuria; chronic kidney disease; glomerular filtration rate; linkage scans; meta-analysis

Journal Article.  5374 words.  Illustrated.

Subjects: Nephrology

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