4.6 Article

Stratification by Smoking Status Reveals an Association of CHRNA5-A3-B4 Genotype with Body Mass Index in Never Smokers

期刊

PLOS GENETICS
卷 10, 期 12, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pgen.1004799

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资金

  1. Medical Research Council [MR/J01351X/1]
  2. British Heart Foundation [RG/13/16/30528, PG/13/66/30442] Funding Source: researchfish
  3. Chief Scientist Office [CZD/16/6/4] Funding Source: researchfish
  4. Economic and Social Research Council [ES/K005774/1, ES/G007489/1, ES/J023299/1] Funding Source: researchfish
  5. Medical Research Council [MR/K023195/1, MR/K023195/1B, G1001799, MC_UU_12013/1, MC_PC_15018, MC_UU_12013/6, MR/K013351/1, MR/J01351X/1, MC_UU_12019/1] Funding Source: researchfish
  6. ESRC [ES/J023299/1, ES/K005774/1] Funding Source: UKRI
  7. MRC [MC_UU_12013/1, MR/K013351/1, MC_UU_12013/6, G1001799, MC_UU_12019/1, MR/J01351X/1] Funding Source: UKRI

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We previously used a single nucleotide polymorphism (SNP) in the CHRNA5-A3-B4 gene cluster associated with heaviness of smoking within smokers to confirm the causal effect of smoking in reducing body mass index (BMI) in a Mendelian randomisation analysis. While seeking to extend these findings in a larger sample we found that this SNP is associated with 0.74% lower body mass index (BMI) per minor allele in current smokers (95% CI -0.97 to -0.51, P = 2.00x10(-10)), but also unexpectedly found that it was associated with 0.35% higher BMI in never smokers (95% CI + 0.18 to + 0.52, P = 6.38x10(-5)). An interaction test confirmed that these estimates differed from each other (P = 4.95x10(-13)). This difference in effects suggests the variant influences BMI both via pathways unrelated to smoking, and via the weight-reducing effects of smoking. It would therefore be essentially undetectable in an unstratified genome-wide association study of BMI, given the opposite association with BMI in never and current smokers. This demonstrates that novel associations may be obscured by hidden population sub-structure. Stratification on well-characterized environmental factors known to impact on health outcomes may therefore reveal novel genetic associations.

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