精神分裂症資料作全基因相關性分析─ 病患分群、基因型設算及罕見變異基因型檢定

Abstract

精神分裂症是一種複雜的疾病，它主要會受到基因遺傳及環境因素的影響。我們從dbGaP 取得case-control 資料做全基因相關性研究，其中包含了1521 位精神分裂症患者和2332 位一般人。由於我們認為精神分裂症的不同症狀是由不同致病基因所導致，我們利用regression extension of latent class analysis (RLCA) 與症狀評分量表做全基因相關性研究，將精神分裂症分成數種症狀。我們藉由引入HapMap 3 對未觀察到的基因型做設算。最後我們對每一個SNP 作相關性檢定並找出顯著與精神分裂症相關之SNP。另外，我們使用cumulative minor-allele test (CMAT) 對罕見變異基因型作檢定。

Schizophrenia is a complex disease caused by both genetic inheritance and environment factors. We use the case-control genome-wide association study (GWAS) with 1521 cases and 2332 controls from the database of Genotypes and Phenotypes (dbGaP) to test SNP association with schizophrenia. Since different symptoms of schizophrenia may be caused by different genes, we use the regression extension of latent class analysis (RLCA) to classify patients based on their responses to the Diagnostic Interview for Genetic Studies (DIGS) measures, and perform GWAS separately for each individual patient subgroup. We extract untyped and missing genotypes by imputation and with HapMap 3 as the reference panel. Then we perform single SNP test of association to find significant SNPs and apply the cumulative minor-allele test (CMAT) to test association between schizophrenia and rare SNPs.