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DOI 10.1111/cts.70216

Медицинская библиотека · Clinical and translational science · 2025

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

El Rouby Nihal, Owusu-Obeng Aniwaa, Preuss Michael H, Lee Simon, Shi Mingjian, Nadukuru Rajiv, Van Driest Sara L, Mosley Jonathan D, DelBello Melissa

СтатьяМетаанализПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

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.

Для цитирования: El Rouby Nihal, Owusu-Obeng Aniwaa, Preuss Michael H, Lee Simon, Shi Mingjian, Nadukuru Rajiv, Van Driest Sara L, Mosley Jonathan D, DelBello Melissa. Genome Wide Association Study (GWAS) Identifies Novel Genetic Loci for Second-Generation Antipsychotics (SGA)-Induced Metabolic Syndrome (MetS).. Clinical and translational science. 2025. DOI: 10.1111/cts.70216.

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