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Background:: Recent cross-sectional genome-wide scans have reported associations of 97 independent loci with body mass index (BMI). In 3541 middle-aged adult participants from the GLACIER Study, we tested whether these loci are associated with 10-year changes in BMI and other cardiometabolic traits (fasting and 2-h glucose, triglycerides, total cholesterol, and systolic and diastolic blood pressures). Methods:: A BMI-specific genetic risk score (GRS) was calculated by summing the BMI-associated effect alleles at each locus. Trait-specific cardiometabolic GRSs comprised only the loci that show nominal association (P?0.10) with the respective trait in the original cross-sectional study. In longitudinal genetic association analyses, the second visit trait measure (assessed ~10 years after baseline) was used as the dependent variable and the models were adjusted for the baseline measure of the outcome trait, age, age2, fasting time (for glucose and lipid traits), sex, follow-up time and population substructure. Results:: The BMI-specific GRS was associated with increased BMI at follow-up (ß=0.014?kg?m-2per allele per 10-year follow-up, s.e.=0.006, P=0.019) as were three loci (PARK2rs13191362, P=0.005; C6orf106rs205262, P=0.043; and C9orf93rs4740619, P=0.01). Although not withstanding Bonferroni correction, a handful of single-nucleotide polymorphisms was nominally associated with changes in blood pressure, glucose and lipid levels. Conclusions:: Collectively, established BMI-associated loci convey modest but statistically significant time-dependent associations with long-term changes in BMI, suggesting a role for effect modification by factors that change with time in this population.

Background/Objective:Genome-wide-association studies have identified numerous body mass index (BMI)-associated variants, but it is unclear how these relate to weight gain in adults at different ages.Methods:We examined the association of a genetic risk score (GRS), consisting of 31 BMI-associated variants, with an annual weight change (AWC) and a substantial weight gain (SWG) of 10% by comparing self-reported weight at 20 years (y) with baseline weight (mean: 58 y; s.d.: 8 y) in 21407 participants from the Malmö Diet and Cancer Study (MDCS), and comparing baseline weight to weight at follow-up (mean: 73 y; s.d.: 6 y) among 2673 participants. Association between GRS and AWG and SWG was replicated in 4327 GLACIER (Gene x Lifestyle interactions And Complex traits Involved in Elevated disease Risk) participants (mean: 45 y; s.d.: 7 y) with 10 y follow-up. Cohort-specific results were pooled by fixed-effect meta-analyses.Results:In MDCS, the GRS was associated with increased AWC (β: 0.003; s.e: 0.01; P: 7 × 10−8) and increased odds for SWG (odds ratio (OR) 1.01 (95% confidence interval (CI): 1.00, 1.02); P: 0.013) per risk-allele from age 20y, but unexpectedly with decreased AWC (β: −0.006; s.e: 0.002; P: 0.009) and decreased odds for SWG OR 0.96 (95% CI: 0.93, 0.98); P: 0.001) between baseline and follow-up. Effect estimates from age 20 y to baseline differed significantly from those from baseline to follow-up (P: 0.0002 for AWC and P: 0.0001 for SWG). Similar to MDCS, the GRS was associated with decreased odds for SWG OR 0.98 (95% CI: 0.96, 1.00); P: 0.029) from baseline to follow-up in GLACIER. In meta-analyses (n=7000), the GRS was associated with decreased AWC (β: −0.005; s.e.m. 0.002; P: 0.002) and decreased odds for SWG OR 0.97 (95% CI: 0.96, 0.99); P: 0.001) per risk-allele.Conclusions:Our results provide convincing evidence for a paradoxical inversed relationship between a high number of BMI-associated risk-alleles and less weight gain during and after middle-age, in contrast to the expected increased weight gain seen in younger age.

Background:: Obesity is a complex disease caused by the interplay of genetic and lifestyle factors, but identification of gene–lifestyle interactions in obesity has remained challenging. Few large-scale studies have reported use of genome-wide approaches to investigate gene–lifestyle interactions in obesity. Methods:: In the Pakistan Risk of Myocardial Infraction Study, a cross-sectional study based in Pakistan, we calculated body mass index (BMI) variance estimates (square of the residual of inverse-normal transformed BMI z-score) in 14?131 participants and conducted genome-wide heterogeneity of variance analyses (GWHVA) for this outcome. All analyses were adjusted for age, age2, sex and genetic ancestry. Results:: The GWHVA analyses identified an intronic variant, rs140133294, in the FLJ33544gene in association with BMI variance (P-value=3.1 × 10-8). In explicit tests of gene × lifestyle interaction, smoking was found to significantly modify the effect of rs140133294 on BMI (Pinteraction=0.0005), whereby the minor allele (T) was associated with lower BMI in current smokers, while positively associated with BMI in never smokers. Analyses of ENCODE data at the FLJ33534locus revealed features indicative of open chromatin and high confidence DNA-binding motifs for several transcription factors, providing suggestive biological support for a mechanism of interaction. Conclusions:: In summary, we have identified a novel interaction between smoking and variation at the FLJ33534locus in relation to BMI in people from Pakistan.