4.1 Article

Genome-wide association with bone mass and geometry 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-S14

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资金

  1. NCRR NIH HHS [1S10RR163736-01A1] Funding Source: Medline
  2. NHLBI NIH HHS [N01HC25195, N01-HC-25195] Funding Source: Medline
  3. NIAMS NIH HHS [R01 AR041398-15, R01 AR041398, R01 AR050066] Funding Source: Medline
  4. NIA NIH HHS [R01 AR/AG 41398] Funding Source: Medline
  5. DIVISION OF EPIDEMIOLOGY AND CLINICAL APPLICATIONS [N01HC025195] Funding Source: NIH RePORTER
  6. NATIONAL INSTITUTE OF ARTHRITIS AND MUSCULOSKELETAL AND SKIN DISEASES [R01AR050066, R01AR041398] Funding Source: NIH RePORTER

向作者/读者索取更多资源

Background: Osteoporosis is characterized by low bone mass and compromised bone structure, heritable traits that contribute to fracture risk. There have been no genome-wide association and linkage studies for these traits using high-density genotyping platforms. Methods: We used the Affymetrix 100K SNP GeneChip marker set in the Framingham Heart Study ( FHS) to examine genetic associations with ten primary quantitative traits: bone mineral density ( BMD), calcaneal ultrasound, and geometric indices of the hip. To test associations with multivariable-adjusted residual trait values, we used additive generalized estimating equation ( GEE) and family-based association tests ( FBAT) models within each sex as well as sexes combined. We evaluated 70,987 autosomal SNPs with genotypic call rates >= 80%, HWE p >= 0.001, and MAF >= 10% in up to 1141 phenotyped individuals ( 495 men and 646 women, mean age 62.5 yrs). Variance component linkage analysis was performed using 11,200 markers. Results: Heritability estimates for all bone phenotypes were 30-66%. LOD scores >= 3.0 were found on chromosomes 15 ( 1.5 LOD confidence interval: 51,336,679-58,934,236 bp) and 22 ( 35,890,398-48,603,847 bp) for femoral shaft section modulus. The ten primary phenotypes had 12 associations with 100K SNPs in GEE models at p < 0.000001 and 2 associations in FBAT models at p < 0.000001. The 25 most significant p-values for GEE and FBAT were all less than 3.5 x 10(-6) and 2.5 x 10(-5), respectively. Of the 40 top SNPs with the greatest numbers of significantly associated BMD traits ( including femoral neck, trochanter, and lumbar spine), one half to two-thirds were in or near genes that have not previously been studied for osteoporosis. Notably, pleiotropic associations between BMD and bone geometric traits were uncommon. Evidence for association ( FBAT or GEE p < 0.05) was observed for several SNPs in candidate genes for osteoporosis, such as rs1801133 in MTHFR; rs1884052 and rs3778099 in ESR1; rs4988300 in LRP5; rs2189480 in VDR; rs2075555 in COLIA1; rs10519297 and rs2008691 in CYP19, as well as SNPs in PPARG ( rs10510418 and rs2938392) and ANKH ( rs2454873 and rs379016). All GEE, FBAT and linkage results are provided as an open-access results resource at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007. Conclusion: The FHS 100K SNP project offers an unbiased genome-wide strategy to identify new candidate loci and to replicate previously suggested candidate genes for osteoporosis.

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