Polygenic risk scores analyses of psychiatric and metabolic traits with antipsychotic-induced weight gain in schizophrenia: an exploratory study

IF 2.9 3区 医学 Q2 GENETICS & HEREDITY
Kazunari Yoshida, Victoria S. Marshe, Samar S. M. Elsheikh, Malgorzata Maciukiewicz, Arun K. Tiwari, Eva J. Brandl, Jeffrey A. Lieberman, Herbert Y. Meltzer, James L. Kennedy, Daniel J. Müller
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引用次数: 0

Abstract

Given the polygenic nature of antipsychotic-induced weight gain (AIWG), we investigated whether polygenic risk scores (PRS) for various psychiatric and metabolic traits were associated with AIWG. We included individuals with schizophrenia (SCZ) of European ancestry from two cohorts (N = 151, age = 40.3 ± 11.8 and N = 138, age = 36.5 ± 10.8). We investigated associations of AIWG defined as binary and continuous variables with PRS calculated from genome-wide association studies of body mass index (BMI), coronary artery disease (CAD), fasting glucose, fasting insulin, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), triglycerides, type 1 and 2 diabetes mellitus, and SCZ, using regression models. We observed nominal associations (uncorrected p < 0.05) between PRSs for BMI, CAD, and LDL-C, type 1 diabetes, and SCZ with AIWG. While results became non-significant after correction for multiple testing, these preliminary results suggest that PRS analyses might contribute to identifying risk factors of AIWG and might help to elucidate mechanisms at play in AIWG.

Abstract Image

Abstract Image

精神分裂症患者抗精神病药物引起的体重增加的精神和代谢特征的多因素风险评分分析:一项探索性研究。
鉴于抗精神病药物诱导的体重增加(AIWG)的多基因性质,我们研究了各种精神和代谢特征的多基因风险评分(PRS)是否与AIWG相关。我们纳入了来自两个队列(N = 151,年龄 = 40.3 ± 11.8和N = 138岁 = 36.5 ± 10.8)。我们使用回归模型研究了定义为二元和连续变量的AIWG与PRS的相关性,PRS是根据体重指数(BMI)、冠状动脉疾病(CAD)、空腹血糖、空腹胰岛素、高密度脂蛋白胆固醇、低密度脂蛋白胆甾醇(LDL-C)、甘油三酯、1型和2型糖尿病以及SCZ的全基因组关联研究计算的。我们观察到名义关联(未校正的p
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来源期刊
Pharmacogenomics Journal
Pharmacogenomics Journal 医学-药学
CiteScore
7.20
自引率
0.00%
发文量
35
审稿时长
6-12 weeks
期刊介绍: The Pharmacogenomics Journal is a print and electronic journal, which is dedicated to the rapid publication of original research on pharmacogenomics and its clinical applications. Key areas of coverage include: Personalized medicine Effects of genetic variability on drug toxicity and efficacy Identification and functional characterization of polymorphisms relevant to drug action Pharmacodynamic and pharmacokinetic variations and drug efficacy Integration of new developments in the genome project and proteomics into clinical medicine, pharmacology, and therapeutics Clinical applications of genomic science Identification of novel genomic targets for drug development Potential benefits of pharmacogenomics.
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