A genome-wide association analysis of a broad psychosis phenotype identifies three loci for further investigation.
A genome-wide association analysis of a broad psychosis phenotype identifies three loci for further investigation.
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DOI：
10.1016/j.biopsych.2013.03.033
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发表时间：
2014-03-01
影响因子：
10.6
通讯作者：
Spencer, Chris C. A.
中科院分区：
文献类型：
--
作者：
Bramon, Elvira;Pirinen, Matti;Strange, Amy;Lin, Kuang;Freeman, Colin;Bellenguez, Celine;Su, Zhan;Band, Gavin;Pearson, Richard;Vukcevic, Damjan;Langford, Cordelia;Deloukas, Panos;Hunt, Sarah;Gray, Emma;Dronov, Serge;Potter, Simon C.;Tashakkori-Ghanbaria, Avazeh;Edkins, Sarah;Bumpstead, Suzannah J.;Arranz, Maria J.;Bakker, Steven;Bender, Stephan;Bruggeman, Richard;Cahn, Wiepke;Chandler, David;Collier, David A.;Crespo-Facorro, Benedicto;Dazzan, Paola;de Haan, Lieuwe;di Forti, Marta;Dragovic, Milan;Giegling, Ina;Hall, Jeremy;Iyegbe, Conrad;Jablensky, Assen;Kahn, Rene S.;Kalaydjieva, Luba;Kravariti, Eugenia;Lawrie, Stephen;Lins-Zen, Don H.;Mata, Ignacio;McDonald, Colm;McIntosh, Andrew;Myin-Germeys, Inez;Ophoff, Roel A.;Pariante, Carmine M.;Paunio, Tiina;Picchioni, Marco;Ripke, Stephan;Rujescu, Dan;Sauer, Heinrich;Shaikh, Madiha;Sussmann, Jessika;Suvisaari, Jaana;Tosato, Sarah;Toulopoulou, Timothea;Van Os, Jim;Walshe, Muriel;Weisbrod, Matthias;Whalley, Heather;Wiersma, Durk;Blackwell, Jenefer M.;Brown, Matthew A.;Casas, Juan P.;Corvin, Aiden;Duncanson, Audrey;Jankowski, Janusz A. Z.;Markus, Hugh S.;Mathew, Christopher G.;Palmer, Colin N. A.;Plomin, Robert;Rautanen, Anna;Sawcer, Stephen J.;Trembath, Richard C.;Wood, Nicholas W.;Barroso, Ines;Peltonen, Leena;Lewis, Cathryn M.;Murray, Robin M.;Donnelly, Peter;Powell, John;Spencer, Chris C. A.
关键词：
全基因组关联研究（GWAS）已经确定了几个与精神分裂症和/或双相情感障碍相关的基因座。我们将精神病作为一种广泛的综合征而不是特定的诊断类别进行了GWAS。1239例精神分裂症、情感性精神障碍或精神病性双相情感障碍患者、857名未患病亲属和2739名健康对照者采用Affysse6.0单核苷酸多态性（SNP）阵列进行基因分型。使用UNPHASED对695，193个SNP进行了分析，该分析结合了家庭和无关个体的信息。我们试图使用来自精神病GWAS联盟和Schizophrenia-GENE-plus队列（10，352名精神分裂症患者和24，474名对照）的非重叠样本的现有数据复制在23个基因组区域中发现的信号。在我们的数据中，没有单个SNP显示出与精神病相关的令人信服的证据。然而，我们观察到一种趋势，即在以前与精神分裂症相关的基因座上与相同的风险等位基因相关（单侧p = 0.003）。多基因评分分析发现，精神病学GWAS联盟的与精神分裂症相关的SNP组显著预测了我们样本中的疾病状态（p = 5 × 10-14），并解释了约2%的表型方差。虽然狭义定义的表型有其优势，我们相信新的基因座也可以通过广泛的表型荟萃分析发现。我们引入的新的统计方法来模拟研究之间的效应量异质性，这将有助于未来的GWAS结合相关表型的联合收割机关联证据。应用这些方法，我们强调三个位点，值得进一步调查。我们发现，在我们的数据中，传达精神分裂症风险的SNP也可以预测疾病状态。
Genome-wide association studies (GWAS) have identified several loci associated with schizophrenia and/or bipolar disorder. We performed a GWAS of psychosis as a broad syndrome rather than within specific diagnostic categories. 1239 cases with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder; 857 of their unaffected relatives, and 2739 healthy controls were genotyped with the Affymetrix 6.0 single nucleotide polymorphism (SNP) array. Analyses of 695,193 SNPs were conducted using UNPHASED, which combines information across families and unrelated individuals. We attempted to replicate signals found in 23 genomic regions using existing data on nonoverlapping samples from the Psychiatric GWAS Consortium and Schizophrenia-GENE-plus cohorts (10,352 schizophrenia patients and 24,474 controls). No individual SNP showed compelling evidence for association with psychosis in our data. However, we observed a trend for association with same risk alleles at loci previously associated with schizophrenia (one-sided p = .003). A polygenic score analysis found that the Psychiatric GWAS Consortium’s panel of SNPs associated with schizophrenia significantly predicted disease status in our sample (p = 5 × 10–14) and explained approximately 2% of the phenotypic variance. Although narrowly defined phenotypes have their advantages, we believe new loci may also be discovered through meta-analysis across broad phenotypes. The novel statistical methodology we introduced to model effect size heterogeneity between studies should help future GWAS that combine association evidence from related phenotypes. Applying these approaches, we highlight three loci that warrant further investigation. We found that SNPs conveying risk for schizophrenia are also predictive of disease status in our data.
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通讯作者：
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