4.1 Article

Genome-wide association with diabetes-related traits in the Framingham Heart Study

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BMC MEDICAL GENETICS
卷 8, 期 -, 页码 -

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BIOMED CENTRAL LTD
DOI: 10.1186/1471-2350-8-S1-S16

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  1. DIVISION OF EPIDEMIOLOGY AND CLINICAL APPLICATIONS [N01HC025195] Funding Source: NIH RePORTER
  2. NATIONAL CENTER FOR RESEARCH RESOURCES [M01RR001066] Funding Source: NIH RePORTER
  3. NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES [K23DK065978] Funding Source: NIH RePORTER
  4. NCRR NIH HHS [M01 RR001066, M01-RR-01066] Funding Source: Medline
  5. NHLBI NIH HHS [N01HC25195, N01-HC-25195] Funding Source: Medline
  6. NIDDK NIH HHS [K23 DK065978, K23 DK65978-03] Funding Source: Medline

向作者/读者索取更多资源

Background: Susceptibility to type 2 diabetes may be conferred by genetic variants having modest effects on risk. Genome-wide fixed marker arrays offer a novel approach to detect these variants. Methods: We used the Affymetrix 100K SNP array in 1,087 Framingham Offspring Study family members to examine genetic associations with three diabetes-related quantitative glucose traits ( fasting plasma glucose ( FPG), hemoglobin A1c, 28-yr time-averaged FPG ( tFPG)), three insulin traits ( fasting insulin, HOMA-insulin resistance, and 0-120 min insulin sensitivity index); and with risk for diabetes. We used additive generalized estimating equations ( GEE) and family-based association test ( FBAT) models to test associations of SNP genotypes with sex-age-age(2)-adjusted residual trait values, and Cox survival models to test incident diabetes. Results: We found 415 SNPs associated ( at p < 0.001) with at least one of the six quantitative traits in GEE, 242 in FBAT ( 18 overlapped with GEE for 639 non-overlapping SNPs), and 128 associated with incident diabetes ( 31 overlapped with the 639) giving 736 non-overlapping SNPs. Of these 736 SNPs, 439 were within 60 kb of a known gene. Additionally, 53 SNPs ( of which 42 had r(2) < 0.80 with each other) had p < 0.01 for incident diabetes AND ( all 3 glucose traits OR all 3 insulin traits, OR 2 glucose traits and 2 insulin traits); of these, 36 overlapped with the 736 other SNPs. Of 100K SNPs, one ( rs7100927) was in moderate LD ( r(2) = 0.50) with TCF7L2 ( rs7903146), and was associated with risk of diabetes ( Cox p-value 0.007, additive hazard ratio for diabetes = 1.56) and with tFPG ( GEE p-value 0.03). There were no common ( MAF > 1%) 100K SNPs in LD ( r2 > 0.05) with ABCC8 A1369S ( rs757110), KCNJ11 E23K ( rs5219), or SNPs in CAPN10 or HNFa. PPARG P12A ( rs1801282) was not significantly associated with diabetes or related traits. Conclusion: Framingham 100K SNP data is a resource for association tests of known and novel genes with diabetes and related traits posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007. Framingham 100K data replicate the TCF7L2 association with diabetes.

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