Otowa Takeshi, Maher Brion S, Aggen Steven H, McClay Joseph L, van den Oord Edwin J, Hettema John M
Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America; Department of Neuropsychiatry, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.
Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
PLoS One. 2014 Nov 12;9(11):e112559. doi: 10.1371/journal.pone.0112559. eCollection 2014.
Anxiety disorders (ADs) are common mental disorders caused by a combination of genetic and environmental factors. Since ADs are highly comorbid with each other, partially due to shared genetic basis, studying AD phenotypes in a coordinated manner may be a powerful strategy for identifying potential genetic loci for ADs. To detect these loci, we performed genome-wide association studies (GWAS) of ADs. In addition, as a complementary approach to single-locus analysis, we also conducted gene- and pathway-based analyses. GWAS data were derived from the control sample of the Molecular Genetics of Schizophrenia (MGS) project (2,540 European American and 849 African American subjects) genotyped on the Affymetrix GeneChip 6.0 array. We applied two phenotypic approaches: (1) categorical case-control comparisons (CC) based upon psychiatric diagnoses, and (2) quantitative phenotypic factor scores (FS) derived from a multivariate analysis combining information across the clinical phenotypes. Linear and logistic models were used to analyse the association with ADs using FS and CC traits, respectively. At the single locus level, no genome-wide significant association was found. A trans-population gene-based meta-analysis across both ethnic subsamples using FS identified three genes (MFAP3L on 4q32.3, NDUFAB1 and PALB2 on 16p12) with genome-wide significance (false discovery rate (FDR] <5%). At the pathway level, several terms such as transcription regulation, cytokine binding, and developmental process were significantly enriched in ADs (FDR <5%). Our approaches studying ADs as quantitative traits and utilizing the full GWAS data may be useful in identifying susceptibility genes and pathways for ADs.
焦虑症（ADs）是由遗传和环境因素共同作用引起的常见精神障碍。由于焦虑症之间存在高度共病现象，部分原因是共享遗传基础，以协调的方式研究焦虑症表型可能是识别焦虑症潜在基因位点的有效策略。为了检测这些位点，我们对焦虑症进行了全基因组关联研究（GWAS）。此外，作为单基因座分析的补充方法，我们还进行了基于基因和通路的分析。GWAS数据来自精神分裂症分子遗传学（MGS）项目的对照样本（2540名欧裔美国人和849名非裔美国人受试者），这些样本在Affymetrix GeneChip 6.0芯片上进行了基因分型。我们应用了两种表型方法：（1）基于精神科诊断的分类病例对照比较（CC），以及（2）从结合临床表型信息的多变量分析中得出的定量表型因子得分（FS）。分别使用线性模型和逻辑模型来分析FS和CC性状与焦虑症的关联。在单基因座水平上，未发现全基因组显著关联。使用FS对两个种族亚样本进行的跨群体基于基因的荟萃分析确定了三个具有全基因组显著性的基因（4q32.3上的MFAP3L、16p12上的NDUFAB1和PALB2）（错误发现率（FDR）<5%）。在通路水平上，转录调控、细胞因子结合和发育过程等几个术语在焦虑症中显著富集（FDR<5%）。我们将焦虑症作为定量性状进行研究并利用完整GWAS数据的方法可能有助于识别焦虑症的易感基因和通路。
