Cited 35 times since 2014 (3.4 per year) source: EuropePMC PLoS genetics, Volume 10, Issue 12, 4 1 2014, Pages e1004799 Stratification by smoking status reveals an association of CHRNA5-A3-B4 genotype with body mass index in never smokers. Taylor AE, Morris RW, Fluharty ME, Bjorngaard JH, Åsvold BO, Gabrielsen ME, Campbell A, Marioni R, Kumari M, Hällfors J, Männistö S, Marques-Vidal P, Kaakinen M, Cavadino A, Postmus I, Husemoen LL, Skaaby T, Ahluwalia TS, Treur JL, Willemsen G, Dale C, Wannamethee SG, Lahti J, Palotie A, Räikkönen K, Kisialiou A, McConnachie A, Padmanabhan S, Wong A, Dalgård C, Paternoster L, Ben-Shlomo Y, Tyrrell J, Horwood J, Fergusson DM, Kennedy MA, Frayling T, Nohr EA, Christiansen L, Ohm Kyvik K, Kuh D, Watt G, Eriksson J, Whincup PH, Vink JM, Boomsma DI, Davey Smith G, Lawlor D, Linneberg A, Ford I, Jukema JW, Power C, Hyppönen E, Jarvelin MR, Preisig M, Borodulin K, Kaprio J, Kivimaki M, Smith BH, Hayward C, Romundstad PR, Sørensen TI, Munafò MR, Sattar N
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 = 2.00 × 10(-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 = 6.38 × 10(-5)). An interaction test confirmed that these estimates differed from each other (P = 4.95 × 10(-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.
