Lund University is celebrating 350 years.


Javascript is not activated in your browser. This website needs javascript activated to work properly.
You are here

Shafqat Ahmad

Genetic and Environmental Risk Factors in the Development of Obesity

Lifestyle behaviors and genetic variation have clear and distinguishable effects on obesity risk; however, the pattern of disease occurrence within and between populations that differ in their genetic and environmental underpinnings suggests obesity is caused in part by the interaction between adverse lifestyle behaviors and the genetic risk profile of an individual. This thesis aims to investigate the joint effects of genetic and environmental (specifically lifestyle) risk factors for obesity and its comorbidities using cross-sectional and longitudinal epidemiological cohorts and clinical trials. Characterizing interactions may help optimize prevention and treatment strategies by identifying risk groups of people for targeted interventions. The work in this thesis was conducted in the cross-sectional European ancestry sample of 111,421 individuals from the GLACIER, MDC, INTER99, HEALTH2006, HPFS, NHS, WGHS, InterAct, MESTSIM, TwinGene cohorts (paper I), 14,131 Pakistani adults from the PROMIS cohort (paper II), 3,541 adult from the prospective GLACIER Study (paper III) and in 5,730 participants of the DPP and Look AHEAD clinical trial (paper IV). In paper I, we reported that physical activity, assessed by the Cambridge physical activity index, diminishes the genetic risk of obesity predisposed by 12 BMIassociated genetic variants (Pinteraction=0.015). In sensitivity analyses, the interaction was only evident in the Northern American (N= 39,810) but not the European (N= 71,611) cohorts. In paper II, by employing genomewide heterogeneity of variance approach in GWAS data in PROMIS study, we identified one locus, FLJ33534 rs140133294 that associated with variance of BMI (P-value of 3.1 x 10-8). In subsequent analysis the association of this locus on BMI was found to be significant modified by smoking (Pinteraction= 0.0005). In paper III, we a genetic risk score based upon 97 BMI-associated genetic variants was significantly associated with change in BMI (β=0.014 kg/m2 per allele per 10-year follow-up, SE= 0.006, P=0.015). Three of the BMI- loci (PARK2 rs13191362, C6orf106 rs205262, C9orf93 rs4740619) were individually significantly associated with 10 year change in BMI. In paper IV, we observed that lifestyle interventions modified the response of MTIF3 rs1885988 genetic variant to weight loss. In the meta-analyzed sample of DPP and Look AHEAD, each copy of the minor Gallele at MTIF3 rs1885988 was associated with weight loss across all four years of the lifestyle interventions (P=2.4×10-3), while no association with weight loss was observed in the control arm (P= 0.11). In conclusion, this thesis work shows that gene-lifestyle interactions influence human weight maintenance on several levels, although the clinical relevance remains to be determined.

More information

Lund University Diabetes Centre, CRC, SUS Malmö, Entrance 72, House 91:12. SE-205 02 Malmö. Telephone: +46 40 39 10 00