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Prioritization of candidate genes for attention deficit hyperactivity disorder by computational analysis of multiple data sources

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Protein & Cell 2012年第7期3卷 526-534页

作者： suhua chang Weina zhang Lei Gao jing wang Key Laboratory of Mental Health Institute of PsychologyChinese Academy of SciencesBeijing 100101China Graduate University of the Chinese Academy of Sciences Beijing 100039China􀀍

Attention deficit hyperactivity disorder(ADHD)is a common,highly heritable psychiatric disorder charac-terized by hyperactivity,inattention and increased *** recent years,a large number of genetic studies for ADHD have been published and related ge-netic data has been accumulated *** pro-vide researchers a comprehensive ADHD genetic re-source,we previously developed the first genetic data-base for ADHD(ADHDgene).The abundant genetic data provides novel candidates for further ***,it also brings new challenge for selecting promising candidate genes for replication and verification *** this study,we surveyed the computational tools for candidate gene prioritization and selected five tools,which integrate multiple data sources for gene prioritiza-tion,to prioritize ADHD candidate genes in *** prioritization analysis resulted in 16 prioritized can-didate genes,which are mainly involved in several major neurotransmitter systems or in nervous system development *** these genes,nervous system development related genes,especially SNAP25,STX1A and the gene-gene interactions related with each of them deserve further *** results may provide new insight for further verification study and facilitate the exploration of pathogenesis mechanism of ADHD.

关键词： gene prioritization attention deficit hyper-activity disorder candidate genes multiple data sources

I-GSEA4GWAS v2： a web sewer for functional analysis of SNPs in trait-associated pathways identified from genome-wide association study

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Protein & Cell 2015年第3期6卷 221-224页

作者： Kunlin zhang(1) suhua chang(1) Liyuan Guo(1) jing wang (1) 1.Key Laboratory of Mental Health Institute of Psychology Chinese Academy of Sciences Beijing 100101 China

Dear Editor, The standard data analysis of genome-wide association study （GWAS） is based on single SNP （single nucleotide polymorphism）, thus it ignores combined effect of modest SNPs/genes. To solve this problem, pathway-based analysis （PBA） has been introduced to GWAS data analysis. PBA aims to identify biological functions and mechanisms associated with complex trait （wang et al., 2007; wang et al., 2010）. By now it has been one of the key ways to interpret GWAS data （wang et al., 2010）.

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Pathway-based analysis for genome-wide association study data of bipolar disorder provides new insights for genetic study

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Protein & Cell 2015年第12期6卷 912-915页

作者： suhua chang (1) jinglu wang (1) (2) Kunlin zhang (1) jing wang (1) 1.Key Laboratory of Mental Health Institute of Psychology Chinese Academy of Sciences Beijing 100101 China 2.University of Chinese Academy of Sciences Beijing 100049 China

Bipolar disorder （BD） is an episodic recurrent pathological mood disturbance with estimated heritability ranging from 80%-85% （Barnett and Smoller, 2009）. Although many studies have indicated that BD is a polygenic disease influenced by many genes with small effect, the pathogenesis of BD is still not well understood. According to the catalog of published genome-wide association studies （GWAS）（Welter et al., 2014）, there have been 31 BD GWASs （including bipolar disorder related symptoms and combined GWAS with other related disorders）till 01/15/2015, including the largest BD GWAS from the Psychiatric Genomics Consortium （PGC）（Sklar et al., 2011）.

关键词： association provide analysis