中国精神分裂症患者抗精神病药物诱导的脂质和BMI变化的药物遗传学研究:全基因组关联研究。

IF 6.2 1区 医学 Q1 PSYCHIATRY
Kenneth Chi-Yin Wong, Perry Bok-Man Leung, Benedict Ka-Wa Lee, Zoe Zi-Yu Zheng, Emily Man-Wah Tsang, Meng-Hui Liu, Kelly Wing-Kwan Lee, Shi-Tao Rao, Pak-Chung Sham, Simon Sai-Yu Lui, Hon-Cheong So
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引用次数: 0

摘要

第二代抗精神病药物(SGAs)被广泛用于治疗精神分裂症(SCZ),但它们经常引起代谢副作用,如血脂异常和肥胖。我们进行了全基因组关联研究(GWASs),以确定与sga诱导的中国SCZ患者脂质和BMI变化相关的遗传变异。接受SGAs治疗的中国SCZ纵向队列随访时间长达18.7年(平均5.7年,SD = 3.3年)。我们分析了患者的基因型(N = 669)、脂质谱和BMI,使用了19 316份处方记录和每个结果的3 917至7 596项代谢测量。采用线性混合模型评估7种SGAs对每位患者代谢变化的随机影响,然后进行GWAS和基因集分析,并进行Bonferroni和FDR校正。5个snp在多次检测校正前的p值达到-08:rs6532055 (ABCG2)与奥氮平诱导的LDL变化相关,rs2644520(接近SORCS1)与阿立哌唑诱导的甘油三酯变化相关,rs115843863(接近UPP2)与氯氮平诱导的HDL变化相关,rs2514895(接近KIRREL3)与帕利培酮诱导的LDL变化相关,rs188405603(接近kirrel9)与喹硫平诱导的甘油三酯变化相关。对于160个GWAS分析,这5个snp通过了FDR校正0.2,但未通过bonferroni校正的全基因组显著性阈值(p值-10)。基于基因的分析显示Bonferroni校正后的6个全基因组显著基因(p值-6):ABCG2, APOA5, ZPR1, GCNT4, MAST2和CRTAC1。四组基因与sga诱导的代谢副作用显著相关。总之,该药物遗传学GWAS鉴定了几种可能与sga诱导的代谢副作用相关的遗传变异,可能为个性化治疗策略提供信息,以最大限度地降低SCZ患者的代谢风险。考虑到我们有限的样本量,需要进一步的重复实验来证实这些发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Pharmacogenetic study of antipsychotic-induced lipid and BMI changes in Chinese schizophrenia patients: A Genome-Wide Association Study.

Pharmacogenetic study of antipsychotic-induced lipid and BMI changes in Chinese schizophrenia patients: A Genome-Wide Association Study.

Pharmacogenetic study of antipsychotic-induced lipid and BMI changes in Chinese schizophrenia patients: A Genome-Wide Association Study.

Second-generation antipsychotics (SGAs) are widely used to treat schizophrenia (SCZ), but they often induce metabolic side effects like dyslipidemia and obesity. We conducted genome-wide association studies (GWASs) to identify genetic variants associated with SGA-induced lipid and BMI changes in Chinese SCZ patients. A longitudinal cohort of Chinese SCZ receiving SGAs was followed for up to 18.7 years (mean = 5.7 years, SD = 3.3 years). We analysed the patients' genotypes (N = 669), lipid profiles, and BMI using 19 316 prescription records and 3 917 to 7 596 metabolic measurements per outcome. Linear mixed models were employed to evaluate seven SGAs' random effects on metabolic changes for each patient, followed by GWAS and gene set analyses with Bonferroni and FDR correction. Five SNPs achieved p-value < 5 × 10-08 before multiple testing correction: rs6532055 (ABCG2) linked to olanzapine-induced LDL changes, rs2644520 (near SORCS1) linked to aripiprazole-induced triglyceride changes, rs115843863 (near UPP2) linked to clozapine-induced HDL changes, rs2514895 (near KIRREL3) linked to paliperidone-induced LDL changes, and rs188405603 (SLC2A9) linked to quetiapine-induced triglyceride changes. These five SNPs passed FDR correction at 0.2 but not Bonferroni-corrected genome-wide significance threshold (p-value < 3.125 × 10-10) for 160 GWAS analyses. Gene-based analysis revealed six genome-wide significant genes after Bonferroni correction (p-value < 2.73 × 10-6): ABCG2, APOA5, ZPR1, GCNT4, MAST2, and CRTAC1. Four gene sets were significantly associated with SGA-induced metabolic side effects. In summary, this pharmacogenetic GWAS identified several genetic variants potentially associated with SGA-induced metabolic side effects, potentially informing personalized treatment strategies to minimize metabolic risk in SCZ patients. Given our limited sample size, further replications are required to confirm the findings.

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来源期刊
CiteScore
11.50
自引率
2.90%
发文量
484
审稿时长
23 weeks
期刊介绍: Psychiatry has suffered tremendously by the limited translational pipeline. Nobel laureate Julius Axelrod''s discovery in 1961 of monoamine reuptake by pre-synaptic neurons still forms the basis of contemporary antidepressant treatment. There is a grievous gap between the explosion of knowledge in neuroscience and conceptually novel treatments for our patients. Translational Psychiatry bridges this gap by fostering and highlighting the pathway from discovery to clinical applications, healthcare and global health. We view translation broadly as the full spectrum of work that marks the pathway from discovery to global health, inclusive. The steps of translation that are within the scope of Translational Psychiatry include (i) fundamental discovery, (ii) bench to bedside, (iii) bedside to clinical applications (clinical trials), (iv) translation to policy and health care guidelines, (v) assessment of health policy and usage, and (vi) global health. All areas of medical research, including — but not restricted to — molecular biology, genetics, pharmacology, imaging and epidemiology are welcome as they contribute to enhance the field of translational psychiatry.
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