Leveraging genetics to improve Body Mass Index increase prediction in the first-episode of psychosis

Background Individuals with a first episode of psychosis (FEP) show rapid weight gain during the first months of treatment, which is associated with reduction in psychiatric and physical health. Although genetics is assumed to be a significant contributor to this weight gain, its exact role is unknown. Methods Reference GWAS from BMI and SCZ were obtained to evaluate the pleiotropic landscape between both traits using the pleioFDR software. In parallel, we gathered a population-based FEP cohort of 381 individuals and BMI Polygenic risk-scores (PRS) were evaluated on a sample of 224 individuals. Subsequently, the PRSs obtained from both BMI and the variants shared between the two traits were incorporated into risk models that included demographic and clinical variable to predict BMI increase (ΔBMI) on an independent sample of 157 patients. Results BMI PRS significantly improved the prediction of absolute BMI and ΔBMI during the first 12 months after the onset of psychotic symptoms. This improvement, was mainly explained by shared variants between SCZ and BMI. In contrast, absolute BMI was predicted mainly by non-shared variants. Conclusions We validated, for the first time, that genetic factors play a key in the determination of both BMI and ΔBMI in FEP. This finding has important clinical implications in identifying individuals who require specific treatment strategies. Improved risk classification may help prevent associated adverse metabolic events, and reduce overtreatment and costs for both individuals and the healthcare system. It also highlights the importance of studying genetic pleiotropy in the context of medically important comorbidities.