Gene- and evidence-based candidate gene selection for schizophrenia and gene feature analysis.
Gene- and evidence-based candidate gene selection for schizophrenia and gene feature analysis.
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DOI：
10.1016/j.artmed.2009.07.009
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发表时间：
2010-02
影响因子：
7.5
通讯作者：
Zhao Z
中科院分区：
文献类型：
--
作者：
Sun J;Han L;Zhao Z
精神分裂症是一种慢性精神疾病，影响全球约1%的人口。在过去的十年中，人们付出了巨大的努力，包括2400多项关联研究，以确定影响疾病易感性的基因。然而，很少有基因或标记被可靠地复制。这些信息的丰富性要求整合基因关联数据、基于证据的基因排序和大样本的后续复制。本研究的目的是发展和评估基于证据的基因排序方法，并检查精神分裂症的顶级候选基因的特征。我们提出了一种基于基因的方法，通过在每个关联研究中组合多个标记的比值比（OR），然后在多个研究中组合一个基因的OR，来选择和优先考虑候选基因。我们称之为组合-组合或法（CCOR）。CCOR类似于我们最近发表的方法，该方法首先在每个研究中选择标记物的最大OR，然后在多个研究中组合这些OR（即，选择-组合OR法（SCOR），但各研究中选择代表性OR的方法不同。通过基因本体论术语和组织中基因表达来检查排名靠前的基因的特征。我们的评估表明，SCOR方法总体上优于CCOR方法。使用SCOR，选择75个排名靠前的基因作为精神分裂症候选基因（SZGenes）。我们发现SZ基因与神经相关的功能术语有很强的相关性，并且在脑相关组织中高度表达。精神分裂症遗传学和其他复杂疾病研究的科学前景预计将在未来几年内发生巨大变化，因此，基于基因的组合OR方法可用于后续关联研究的候选基因选择和进一步的医学人工智能。这种对候选基因进行优先排序的方法可应用于其他复杂疾病，例如抑郁症、焦虑症、尼古丁依赖、酒精依赖和心血管疾病。
Schizophrenia is a chronic psychiatric disorder that affects about 1% of the population globally. A tremendous amount of effort has been expended in the past decade, including more than 2400 association studies, to identify genes influencing susceptibility to the disorder. However, few genes or markers have been reliably replicated. The wealth of this information calls for an integration of gene association data, evidence based gene ranking, and follow-up replication in large sample. The objective of this study is to develop and evaluate evidence based gene ranking methods and to examine the features of top-ranking candidate genes for schizophrenia. We proposed a gene-based approach for selecting and prioritizing candidate genes by combining odds ratios (ORs) of multiple markers in each association study and then combining ORs in multiple studies of a gene. We named it combination-combination OR method (CCOR). CCOR is similar to our recently published method, which first selects the largest OR of the markers in each study and then combines these ORs in multiple studies (i.e., selection-combination OR method, SCOR), but differs in selecting representative OR in each study. Features of top-ranking genes were examined by gene ontology terms and gene expression in tissues. Our evaluation suggested that the SCOR method overall outperforms the CCOR method. Using the SCOR, a list of 75 top-ranking genes was selected for schizophrenia candidate genes (SZGenes). We found that SZGenes had strong correlation with neuro-related functional terms and were highly expressed in brain-related tissues. The scientific landscape for schizophrenia genetics and other complex disease studies is expected to change dramatically in the next a few years, thus, the gene-based combined OR method is useful in candidate gene selection for follow-up association studies and in further artificial intelligence in medicine. This method for prioritization of candidate genes can be applied to other complex diseases such as depression, anxiety, nicotine dependence, alcohol dependence, and cardiovascular diseases.
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