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Association of genetic risk scores with body mass index in Swiss psychiatric cohorts
Saigi-Morgui, N., Vandenberghe, F., Delacrétaz, A., Quteineh, L., Gholamrezaee , M., Aubry, J.-M., von Gunten, A., Kutalik, Z., Conus, P., & Eap, C. B. (2016). Association of genetic risk scores with body mass index in Swiss psychiatric cohorts. Pharmacogenetics and Genomics, 26(5), 208-217. https://doi.org/10.1097/FPC.0000000000000210
Objective Weight gain is associated with psychiatric disorders and/or with psychotropic drug treatments. We analyzed in three psychiatric cohorts under psychotropic treatment the association of weighted genetic risk scores (w-GRSs) with BMI by integrating BMI-related polymorphisms from the candidate-gene approach and Genome-Wide Association Studies (GWAS).Materials and methods w-GRS of 32 polymorphisms associated previously with BMI in general population GWAS and 20 polymorphisms associated with antipsychotics-induced weight gain were investigated in three independent psychiatric samples.Results w-GRS of 32 polymorphisms were significantly associated with BMI in the psychiatric sample 1 (n=425) and were replicated in another sample (n=177). Those at the percentile 95 (p95) of the score had 2.26 and 2.99 kg/m(2) higher predicted BMI compared with individuals at the percentile 5 (p5) in sample 1 and in sample 3 (P=0.009 and 0.04, respectively). When combining all samples together (n=750), a significant difference of 1.89 kg/m(2) predicted BMI was found between p95 and p5 individuals at 12 months of treatment. Stronger associations were found among men (difference: 2.91k g/m(2) of predicted BMI between p95 and p5, P=0.0002), whereas no association was found among women. w-GRS of 20 polymorphisms was not associated with BMI. The w-GRS of 52 polymorphisms and the clinical variables (age, sex, treatment) explained 1.99 and 3.15%, respectively, of BMI variability.Conclusion The present study replicated in psychiatric cohorts previously identified BMI risk variants obtained in GWAS analyses from population-based samples. Sex-specific analysis should be considered in further analysis. (C) 2016 Wolters Kluwer Health, Inc. All rights reserved.