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Published on: June 15, 2011
Genetic susceptibility of cardiometabolic outcomes in schizophrenia spectrum disorders
Chenxu Zhao1, Bochao Lin2, Elnaz Naderi1
1Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
Abstract:
Patients with schizophrenia spectrum disorders (SSDs) have a higher risk for post-diagnostic cardiometabolic comorbidities. While antipsychotic use partly explains this, the contribution of genetic susceptibility remains unclear. We investigated the relationships between cardiometabolic-related polygenic risk scores (PRSes) with cardiometabolic outcomes using data from 671 patients with SSDs in the Dutch Genetic Risk and Outcome of Psychosis study. Seven PRSes were calculated for body mass index (BMI), high- and low-density lipoprotein cholesterol (HDL, LDL), triglycerides, glucose, systolic (SBP) and diastolic blood pressure (DBP) using summary statistics from most recent genome-wide association studies. Four linear regression models assessed the cross-sectional associations between PRSes and cardiometabolic outcomes including BMI, HDL, LDL, triglycerides, glycated hemoglobin, SBP, DBP, and a composite metabolic score. Model #1 included baseline factors (age, sex, and population substructure); #2 included model 1 with a single-trait PRS; #3 included model 1 with all PRSes of designated traits; and #4 included model 1 and a composite PRS score. All seven cardiometabolic PRSes were significantly associated with their corresponding outcomes. Significant cross-trait associations were observed including PRSBMI with lower HDL (explained variance (R2) = 2.33%), higher DBP (R2 = 3.35%), and higher SBP (R2 = 2.29%); PRSHDL with higher HDL(R2 = 2.05%) and LDL levels(R2 = 2.31%); PRSDBP with higher SBP(R2 = 1.75%), and PRSSBP with higher DBP(R2 = 2.94%). The current study suggests that genetic susceptibility contributes modestly but significantly to poor cardiometabolic outcomes. Shared genetic susceptibility may underpin the frequent co-occurrence of cardiometabolic morbidities in SSDs, supporting the potential utility of PRSes in identifying high-risk patients for early intervention in practice.
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