对耐药性精神分裂症进行全基因组关联分析,以发现变体并进行多基因评估。

IF 3.8 3区 医学 Q2 GENETICS & HEREDITY
Hasan Çağın Lenk, Elise Koch, Kevin S O'Connell, Robert Løvsletten Smith, Ibrahim A Akkouh, Srdjan Djurovic, Ole A Andreassen, Espen Molden
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引用次数: 0

摘要

背景:耐药性精神分裂症(TRS)的广义定义是对适当治疗的反应不足,与疾病负担的大幅增加有关。氯氮平是唯一获准用于治疗 TRS 的药物,与其他药物相比,它对总体症状的临床疗效更佳,是非典型抗精神病药物的雏形。利培酮是另一种非典型抗精神病药物,具有更明显的多巴胺2拮抗作用,常用于治疗精神分裂症。在此,我们对接受氯氮平(TRS)与利培酮(非 TRS)治疗的患者进行了一项全基因组关联研究,并调查了精神分裂症的单基因变异和/或多基因风险评分是否与 TRS 状态相关。我们假设,接受氯氮平与利培酮治疗的患者可能会表现出不同的神经生物学表型,这些表型与这两种药物的药理学特征相匹配,并且可以用遗传差异来解释。研究对象(n = 1286)是在 2005 年至 2022 年期间从常规治疗药物监测(TDM)服务中招募的。曾检测到氯氮平与利培酮的血清浓度(无氯氮平的TDM史)分别定义为TRS组(n = 478)和非TRS组(n = 808):我们发现TRS与LINC00523基因中的一个常见变异存在提示性关联,其显著性略低于全基因组阈值(rs79229764 C > T, OR = 4.89; p = 1.8 × 10-7)。精神分裂症的多基因风险评分与 TRS 显著相关(OR = 1.4,p = 2.1 × 10-6)。在精神分裂症供体(n = 214;CommonMind Consortium)的大量死后脑样本中,基因表达分析表明,rs79229764变异等位基因可能参与了GPR88和PUDP的调控,而GPR88和PUDP分别在纹状体神经传递和智力障碍中发挥作用:我们报告了rs79229764位点与TRS的提示性遗传关联,并表明精神分裂症的遗传责任与TRS呈正相关。这些结果为今后的后续研究提供了一个候选位点,以阐明 TRS 的分子基础。我们的研究结果进一步证明了单变异和多基因关联分析对预测 TRS 的价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genome-wide association analysis of treatment resistant schizophrenia for variant discovery and polygenic assessment.

Background: Treatment resistant schizophrenia (TRS) is broadly defined as inadequate response to adequate treatment and is associated with a substantial increase in disease burden. Clozapine is the only approved treatment for TRS, showing superior clinical effect on overall symptomatology compared to other drugs, and is the prototype of atypical antipsychotics. Risperidone, another atypical antipsychotic with a more distinctive dopamine 2 antagonism, is commonly used in treatment of schizophrenia. Here, we conducted a genome-wide association study on patients treated with clozapine (TRS) vs. risperidone (non-TRS) and investigated whether single variants and/or polygenic risk score for schizophrenia are associated with TRS status. We hypothesized that patients who are treated with clozapine and risperidone might exhibit distinct neurobiological phenotypes that match pharmacological profiles of these drugs and can be explained by genetic differences. The study population (n = 1286) was recruited from a routine therapeutic drug monitoring (TDM) service between 2005 and 2022. History of a detectable serum concentration of clozapine and risperidone (without TDM history of clozapine) defined the TRS (n = 478) and non-TRS (n = 808) group, respectively.

Results: We identified a suggestive association between TRS and a common variant within the LINC00523 gene with a significance just below the genome-wide threshold (rs79229764 C > T, OR = 4.89; p = 1.8 × 10-7). Polygenic risk score for schizophrenia was significantly associated with TRS (OR = 1.4, p = 2.1 × 10-6). In a large post-mortem brain sample from schizophrenia donors (n = 214; CommonMind Consortium), gene expression analysis indicated that the rs79229764 variant allele might be involved in the regulation of GPR88 and PUDP, which plays a role in striatal neurotransmission and intellectual disability, respectively.

Conclusions: We report a suggestive genetic association at the rs79229764 locus with TRS and show that genetic liability for schizophrenia is positively associated with TRS. These results suggest a candidate locus for future follow-up studies to elucidate the molecular underpinnings of TRS. Our findings further demonstrate the value of both single variant and polygenic association analyses for TRS prediction.

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来源期刊
Human Genomics
Human Genomics GENETICS & HEREDITY-
CiteScore
6.00
自引率
2.20%
发文量
55
审稿时长
11 weeks
期刊介绍: Human Genomics is a peer-reviewed, open access, online journal that focuses on the application of genomic analysis in all aspects of human health and disease, as well as genomic analysis of drug efficacy and safety, and comparative genomics. Topics covered by the journal include, but are not limited to: pharmacogenomics, genome-wide association studies, genome-wide sequencing, exome sequencing, next-generation deep-sequencing, functional genomics, epigenomics, translational genomics, expression profiling, proteomics, bioinformatics, animal models, statistical genetics, genetic epidemiology, human population genetics and comparative genomics.
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