Person:

Franks, Paul

Background: Bicycling to work may be a viable approach for achieving physical activity that provides cardiovascular health benefits. In this study we investigated the relationship of bicycling to work with incidence of obesity, hypertension, hypertriglyceridemia, and impaired glucose tolerance across a decade of follow‐up in middle‐aged men and women. Methods and Results: We followed 23 732 Swedish men and women with a mean age of 43.5 years at baseline who attended a health examination twice during a 10‐year period (1990–2011). In multivariable adjusted models we calculated the odds of incident obesity, hypertension, hypertriglyceridemia, and impaired glucose tolerance, comparing individuals who commuted to work by bicycle with those who used passive modes of transportation. We also examined the relationship of change in commuting mode with incidence of these clinical risk factors. Cycling to work at baseline was associated with lower odds of incident obesity (odds ratio [OR]=0.85, 95% CI 0.73–0.99), hypertension (OR=0.87, 95% CI 0.79–0.95), hypertriglyceridemia (OR=0.85, 95% CI 0.76–0.94), and impaired glucose tolerance (OR=0.88, 95% CI 0.80–0.96) compared with passive travel after adjusting for putative confounding factors. Participants who maintained or began bicycling to work during follow‐up had lower odds of obesity (OR=0.61, 95% CI 0.50–0.73), hypertension (OR=0.89, 95% CI 0.80–0.98), hypertriglyceridemia (OR=0.80, 95% CI 0.70–0.90), and impaired glucose tolerance (OR=0.82, 95% CI 0.74–0.91) compared with participants not cycling to work at both times points or who switched from cycling to other modes of transport during follow‐up. Conclusions: These data suggest that commuting by bicycle to work is an important strategy for primordial prevention of clinical cardiovascular risk factors among middle‐aged men and women.

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

Background: Multiple genetic variants have been reliably associated with obesity-related traits in Europeans, but little is known about their associations and interactions with lifestyle factors in South Asians. Methods: In 16,157 Pakistani adults (8232 controls; 7925 diagnosed with myocardial infarction [MI]) enrolled in the PROMIS Study, we tested whether: a) BMI-associated loci, individually or in aggregate (as a genetic risk score - GRS), are associated with BMI; b) physical activity and smoking modify the association of these loci with BMI. Analyses were adjusted for age, age2, sex, MI (yes/no), and population substructure. Results: Of 95 SNPs studied here, 73 showed directionally consistent effects on BMI as reported in Europeans. Each additional BMI-raising allele of the GRS was associated with 0.04 (SE = 0.01) kg/m2 higher BMI (P = 4.5 × 10−14). We observed nominal evidence of interactions of CLIP1 rs11583200 (Pinteraction = 0.014), CADM2 rs13078960 (Pinteraction = 0.037) and GALNT10 rs7715256 (Pinteraction = 0.048) with physical activity, and PTBP2 rs11165643 (Pinteraction = 0.045), HIP1 rs1167827 (Pinteraction = 0.015), C6orf106 rs205262 (Pinteraction = 0.032) and GRID1 rs7899106 (Pinteraction = 0.043) with smoking on BMI. Conclusions: Most BMI-associated loci have directionally consistent effects on BMI in Pakistanis and Europeans. There were suggestive interactions of established BMI-related SNPs with smoking or physical activity. Electronic supplementary material The online version of this article (doi:10.1186/s12881-015-0259-x) contains supplementary material, which is available to authorized users.

Aims/hypothesis We compared the ability of genetic (established type 2 diabetes, fasting glucose, 2 h glucose and obesity variants) and modifiable lifestyle (diet, physical activity, smoking, alcohol and education) risk factors to predict incident type 2 diabetes and obesity in a population-based prospective cohort of 3,444 Swedish adults studied sequentially at baseline and 10 years later. Methods: Multivariable logistic regression analyses were used to assess the predictive ability of genetic and lifestyle risk factors on incident obesity and type 2 diabetes by calculating the AUC. Results: The predictive accuracy of lifestyle risk factors was similar to that yielded by genetic information for incident type 2 diabetes (AUC 75% and 74%, respectively) and obesity (AUC 68% and 73%, respectively) in models adjusted for age, age2 and sex. The addition of genetic information to the lifestyle model significantly improved the prediction of type 2 diabetes (AUC 80%; p = 0.0003) and obesity (AUC 79%; p < 0.0001) and resulted in a net reclassification improvement of 58% for type 2 diabetes and 64% for obesity. Conclusions/interpretation These findings illustrate that lifestyle and genetic information separately provide a similarly high degree of long-range predictive accuracy for obesity and type 2 diabetes. Electronic supplementary material The online version of this article (doi:10.1007/s00125-015-3818-y) contains peer-reviewed but unedited supplementary material, which is available to authorised users.