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全基因组关联研究精神分裂症的临床维度:精神分裂症瓦解症状的多基因效应。

Genome-wide association study of clinical dimensions of schizophrenia: polygenic effect on disorganized symptoms.

机构信息

Mental Health Service Line, Washington, DC, USA.

出版信息

Am J Psychiatry. 2012 Dec;169(12):1309-17. doi: 10.1176/appi.ajp.2012.12020218.

Abstract

OBJECTIVE

Multiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia.

METHOD

Based on the Lifetime Dimensions of Psychosis Scale ratings of 2,454 case subjects of European ancestry from the Molecular Genetics of Schizophrenia (MGS) sample, three symptom factors (positive, negative/disorganized, and mood) were identified with exploratory factor analysis. Quantitative scores for each factor from a confirmatory factor analysis were analyzed for association with 696,491 single-nucleotide polymorphisms (SNPs) using linear regression, with correction for age, sex, clinical site, and ancestry. Polygenic score analysis was carried out to determine whether case and comparison subjects in 16 Psychiatric GWAS Consortium (PGC) schizophrenia samples (excluding MGS samples) differed in scores computed by weighting their genotypes by MGS association test results for each symptom factor.

RESULTS

No genome-wide significant associations were observed between SNPs and factor scores. Most of the SNPs producing the strongest evidence for association were in or near genes involved in neurodevelopment, neuroprotection, or neurotransmission, including genes playing a role in Mendelian CNS diseases, but no statistically significant effect was observed for any defined gene pathway. Finally, polygenic scores based on MGS GWAS results for the negative/disorganized factor were significantly different between case and comparison subjects in the PGC data set; for MGS subjects, negative/disorganized factor scores were correlated with polygenic scores generated using case-control GWAS results from the other PGC samples.

CONCLUSIONS

The polygenic signal that has been observed in cross-sample analyses of schizophrenia GWAS data sets could be in part related to genetic effects on negative and disorganized symptoms (i.e., core features of chronic schizophrenia).

摘要

目的

多项证据表明,遗传因素会影响精神分裂症临床特征的变化。作者提出了精神分裂症个体维度症状评分的全基因组关联研究(GWAS)。

方法

基于来自精神分裂症分子遗传学(MGS)样本的 2454 例欧洲血统病例的生活维度精神病评定量表评分,通过探索性因子分析确定了三个症状因子(阳性、阴性/紊乱和情绪)。采用线性回归对来自验证性因子分析的每个因子的定量评分与 696491 个单核苷酸多态性(SNP)进行关联分析,校正年龄、性别、临床部位和血统。进行多基因评分分析,以确定在 16 个精神疾病 GWAS 联盟(PGC)精神分裂症样本(不包括 MGS 样本)中,通过根据每个症状因子的 MGS 关联测试结果对其基因型进行加权计算得到的评分,病例和对照组之间是否存在差异。

结果

没有观察到 SNP 与因子评分之间存在全基因组显著关联。产生最强关联证据的大多数 SNP 位于或靠近参与神经发育、神经保护或神经递质传递的基因中,包括在 Mendelian CNS 疾病中起作用的基因,但没有观察到任何定义明确的基因途径的统计学显著效应。最后,基于 MGS GWAS 对阴性/紊乱因子的结果的多基因评分在 PGC 数据集中病例和对照组之间存在显著差异;对于 MGS 患者,阴性/紊乱因子评分与使用来自其他 PGC 样本的病例对照 GWAS 结果生成的多基因评分相关。

结论

在精神分裂症 GWAS 数据集的跨样本分析中观察到的多基因信号,部分可能与对阴性和紊乱症状(即慢性精神分裂症的核心特征)的遗传影响有关。

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