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Meta-Analysis
. 2025 Apr;18(4):e70216.
doi: 10.1111/cts.70216.

Genome Wide Association Study (GWAS) Identifies Novel Genetic Loci for Second-Generation Antipsychotics (SGA)-Induced Metabolic Syndrome (MetS)

Nihal El Rouby  1   2   3 , Aniwaa Owusu-Obeng  4 , Michael H Preuss  4 , Simon Lee  4 , Mingjian Shi  5 , Rajiv Nadukuru  4 , Sara L Van Driest  6   7 , Jonathan D Mosley  5   8 , Melissa DelBello  2   9
Affiliations
Meta-Analysis

Genome Wide Association Study (GWAS) Identifies Novel Genetic Loci for Second-Generation Antipsychotics (SGA)-Induced Metabolic Syndrome (MetS)

Nihal El Rouby et al. Clin Transl Sci. 2025 Apr.

Abstract

Second-generation antipsychotics (SGA) are widely used for treating psychiatric disorders; however, their use is associated with an increased risk of metabolic syndrome (MetS). To identify common genetic associations of SGA-induced metabolic syndrome (SGA-MetS), we conducted a genome-wide association study (GWAS) in a diverse patient population within the BioVU and BioMe electronic health records (EHRs)-linked biobanks. Additionally, we performed Mendelian Randomization (MR) analysis to investigate the association between the individual metabolic parameters comprising MetS (body mass index [BMI], fasting glucose, blood pressure, HDL, and triglycerides) and SGA-MetS. The meta-analysis of European ancestry GWAS from BioVU and BioMe (N = 9248) identified a genome-wide signal (rs61900075, β = -0.27, SE = 0.05, p = 1.6 × 10-8) on chromosome 11. Multiple associated variants met the suggestive level of association (p ≤ 10-5) in the PELO-ITGA1 locus on chromosome 5 and were associated among the Hispanic Ancestry within BioMe. The meta-analysis of the African Ancestry patients of BioVU and BioMe (N = 2018) identified multiple genome-wide signals that were functionally mapped to NPPC-DIS3L2 in chromosome 2. Finally, the inverse-variance weighted average MR (BMI: OR = 1.2, 95% CI: 1.1-1.4, p = 0.002) showed that genetically predicted, higher BMI was associated with an increased risk of SGA-MetS. Similar results were seen in the sensitivity analyses using the weighted median and Egger MR. This study identified novel variants for SGA-MetS and suggested a role of BMI in increasing the risk of SGA-MetS. The findings highlight the value of EHR biobanks for identifying the genetics underlying SGA-MetS. The associations in chromosome 2 and 5 will need further replication.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Association analysis plot of SGA‐MetS among European meta‐analysis of BioVU and BioMe.
FIGURE 2
FIGURE 2
Association analysis plot of SGA‐MetS among African meta‐analysis of BioVU and BioMe.
FIGURE 3
FIGURE 3
Mendelian randomization results of BMI and SGA‐MetS using weighted median, inverse‐variance weighted average, and Egger meta‐analysis.
See this image and copyright information in PMC

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