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This article is part of the supplement: The Framingham Heart Study 100,000 single nucleotide polymorphisms resource

Open Access Research

A genome-wide association for kidney function and endocrine-related traits in the NHLBI's Framingham Heart Study

Shih-Jen Hwang1, Qiong Yang3, James B Meigs2, Elizabeth N Pearce4 and Caroline S Fox15*

Author Affiliations

1 National Heart Lung and Blood Institutes, Bethesda, MD, USA

2 Massachusetts General Hospital and Harvard Medical School , Boston, MA, USA

3 Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA

4 Boston University School of Medicine, Boston, MA, USA

5 Department of Endocrinology, Diabetes, and Hypertension, the Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA

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BMC Medical Genetics 2007, 8(Suppl 1):S10  doi:10.1186/1471-2350-8-S1-S10

Published: 19 September 2007

Abstract

Background

Glomerular filtration rate (GFR) and urinary albumin excretion (UAE) are markers of kidney function that are known to be heritable. Many endocrine conditions have strong familial components. We tested for association between the Affymetrix GeneChip Human Mapping 100K single nucleotide polymorphism (SNP) set and measures of kidney function and endocrine traits.

Methods

Genotype information on the Affymetrix GeneChip Human Mapping 100K SNP set was available on 1345 participants. Serum creatinine and cystatin-C (cysC; n = 981) were measured at the seventh examination cycle (1998–2001); GFR (n = 1010) was estimated via the Modification of Diet in Renal Disease (MDRD) equation; UAE was measured on spot urine samples during the sixth examination cycle (1995–1998) and was indexed to urinary creatinine (n = 822). Thyroid stimulating hormone (TSH) was measured at the third and fourth examination cycles (1981–1984; 1984–1987) and mean value of the measurements were used (n = 810). Age-sex-adjusted and multivariable-adjusted residuals for these measurements were used in association with genotype data using generalized estimating equations (GEE) and family-based association tests (FBAT) models. We presented the results for association tests using additive allele model. We evaluated associations with 70,987 SNPs on autosomes with minor allele frequencies of at least 0.10, Hardy-Weinberg Equilibrium p-value ≥ 0.001, and call rates of at least 80%.

Results

The top SNPs associated with these traits using the GEE method were rs2839235 with GFR (p-value 1.6*10-05), rs1158167 with cysC (p-value 8.5*10-09), rs1712790 with UAE (p-value 1.9*10-06), and rs6977660 with TSH (p-value 3.7*10-06), respectively. The top SNPs associated with these traits using the FBAT method were rs6434804 with GFR(p-value 2.4*10-5), rs563754 with cysC (p-value 4.7*10-5), rs1243400 with UAE (p-value 4.8*10-6), and rs4128956 with TSH (p-value 3.6*10-5), respectively. Detailed association test results can be found at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite. Four SNPs in or near the CST3 gene were highly associated with cysC levels (p-value 8.5*10-09 to 0.007).

Conclusion

Kidney function traits and TSH are associated with SNPs on the Affymetrix GeneChip Human Mapping 100K SNP set. These data will serve as a valuable resource for replication as more SNPs associated with kidney function and endocrine traits are identified.