|Alternative Title||Exploring the relationship between infectious and inflammatory factors and three major psychiatric disorders by bioinformatics analysis|
|Place of Conferral||北京|
|Keyword||精神分裂症 心境障碍 感染及炎症因素 细胞因子 生物信息学分析|
第一部分，我们通过元分析的方法，收集了35篇流行病学调查数据，样本量15242，分析了七种感染神经系统的病原(弓形虫、单纯疱疹病毒一型(HSV-1)、单纯疱疹病毒二型(HSV-2)、 巨细胞病毒(CMV)、 人类疱疹病毒六型(HHV-6)、EB病毒(EBV)、博纳病毒(BDV))与心境障碍发病风险之间的关系，发现其中四种病原感染与心境障碍发病风险存在显著关联：弓形虫、 CMV、 HHV-6、BDV。将心境障碍分成双相情感障碍和重度抑郁障碍进行亚组分析，发现三种病原与双相情感障碍发病风险存在显著关联：弓形虫、CMV、BDV。对于重度抑郁障碍，亚组分析的三种病原弓形虫、EBV、BDV均未发现显著关联。本研究发现某些感染神经系统的病原如弓形虫、BDV可能是双相情感障碍的风险因子，而在重度抑郁障碍中并没有发现这种关联，提示某些病原感染对双相情感障碍和重度抑郁障碍的影响可能存在差异。同时之前发表的元分析亦发现弓形虫、BDV与精神分裂症的发病风险存在显著关联，也是精神分裂症的风险因子，提示双相情感障碍与精神分裂症可能共享某些感染相关的风险因素。
第二部分，我们收集精神分裂症、心境障碍的候选基因关联研究和全基因组关联研究数据 (共64个数据集，样本量41993)，对7个细胞因子基因上的13个SNPs与精神分裂症和心境障碍易感性的关联分别进行了元分析，发现IL10上1个SNP和2个单倍型 (rs1800872以及 rs1800896-rs1800871-rs1800872的单倍型A-C-A、G-C-C)与精神分裂症易感性存在显著关联；发现TNF (rs1800629)、IL1B (rs19664)以及IFNG (rs2430561)与心境情感障碍易感性存在显著关联。然后通过eQTL方法分析了这些位点与相应基因表达的影响，发现了2个可以显著影响相应基因表达的SNPs：rs19664 (IL1B)和rs1800872 (IL10)。本研究鉴定出1个与精神分裂症易感性显著关联的基因IL10，3个与心境障碍易感性显著关联的基因TNF、IL1B和IFNG，说明某些参与炎症反应的细胞因子的多态性位点可能是精神疾病的易感位点。
第三部分，我们对精神分裂症、双相情感障碍、重度抑郁障碍的全基因组关联数据和全基因组表达数据分别进行了通路分析，感染与炎症相关通路在三种精神疾病中均被鉴定出来，其中全基因组关联研究数据分析鉴定出的数目为9 (精神分裂症)、20 (双相情感障碍)、9 (重度抑郁障碍)；全基因组表达数据分析鉴定出的数目为5 (精神分裂症)、8 (双相情感障碍)、8 (重度抑郁障碍)。其中，某些病毒感染相关的通路在三种精神疾病中均被鉴定出来，白细胞介素相关的通路主要在心境障碍中被鉴定出来，干扰素相关的通路主要在重度抑郁障碍中被鉴定出来，在双相情感障碍中鉴定出可以与该疾病易感基因钙离子通道相互作用的病毒感染相关的通路。 综上所述，本论文通过生物信息学分析方法，整合临床层面、遗传层面、表达层面的证据，探究感染及炎症相关因素与主要精神疾病发病风险的关系，最终在临床层面，通过分析鉴定出与心境障碍发病风险相关的一些病原；在遗传和表达层面，鉴定出于精神分裂症和心境障碍易感性相关的细胞因子多态性位点；同时鉴定出一些感染和炎症相关的通路。最后整合所得的结果，为感染和炎症因素与精神疾病的关系提供了多层面的证据支持，为后续的研究提供了可靠候选。
|Other Abstract||Schizophrenia (SZ) and mood disorders (including bipolar disorder (BD) and major depressive disorder (MDD)) are major psychiatric disorders in adults. For these psychiatric disorders, it is believed that both environmental and genetic factors play an important role in their pathogenesis. In recent years, the relationship between psychiatric disorders and immune-related factors, especially infectious and inflammatory factors has become a hot research issue. With the enrichment of data accumulated from epidemiological research, clinical study, as well as omics research in psychiatric disorders, it has become a big challenge for researchers to identify risk factors of disease by multi-level data-mining. In this study, to explore the relationship between infectious and inflammatory factors and psychiatric disorders, considering both environmental and genetic factors of psychiatric disorders, we collected three-level data including clinical data, genetic data and expression data, then carried out researches in three parts by methods of bioinformatics analysis.|
In the first part, we investigated the association between infectious agents and risk of mood disorders by meta-analysis. Thirty-five studies with a total of 15242 participants covering seven infectious agents including T.gondii, HSV-1, HSV-2, CMV, HHV-6, EBV, BDV were analyzed. Among them, T.gondii, CMV, HHV-6 and BDV were found to be significantly associated with risk of mood disorders. In subgroup analyses, significant higher prevalence of T.gondii, CMV and BDV was observed in BD patients than controls, while no significant association was observed among any investigated infectious agents (T.gondii, EBV and BDV) with MDD, which showed different effect of T.gondii and BDV infection on disease risk between BD and MDD. Meanwhile, previous meta-analyses also demonstrated that T.gondii and BDV was significantly associated with SZ, suggesting that BD and SZ might share some infectious factors. In the second part, we first performed a meta-analysis to investigate the association of cytokine polymorphisms with SZ and mood disorders, then conducted expression quantitative trait loci (eQTL) to detect functional effects of the risk cytokine polymorphisms. Data from 64 studies with a total of 41993 participants were available for meta-analysis. After correction, rs1800872 and two haplotypes of rs1800896 - rs1800871 - rs1800872 in IL10 showed significant associations with SZ; while rs1800629 in TNF , rs19664 in IL1B and rs2430561 in IFNG showed significant associations with mood disorders. Results of eQTL analyses showed that rs19664 and rs1800872 was significantly associated expression level of IL1B and IL10 respectively. This study supported the involvement of infection and inflammation related cytokines in the pathogenesis of major psychiatric disorders on both genetic and expression level.
In the third part, we performed pathway based analyses (PBA) using data from both GWAS and expression microarray on SZ, BD and MDD. Infection and inflammation related pathways were identified to be significantly associated in all three disorders. In GWAS PBA, the number of such significant pathways was 9 (SZ), 20 (BD) and 9 (MDD), while in PBA of expression data, that number was which 5 (SZ), 8 (BD) and 8 (MDD) respectively. Among these significant pathways, virus infection related pathways were identified in all three disorders, while interleukin related pathways were mainly identified in mood disorders. Besides, interferon related pathways were mainly identified in MDD; while in BD, a viral infection related pathway, which was involved with interaction between cytokines and calcium channel gene ( a previously identified BD susceptibility gene) was identified. In summary, in this study, to explore the relationship between infectious and inflammatory factors and psychiatric disorders, we collected three-level data and carried out researches in three parts by methods of bioinformatics analysis. Analysis based on clinical data identified infectious agents significantly associated with mood disorders, while analysis based on genetic and expression data identified cytokine polymorphisms significantly associated with SZ and mood disorders, as well as infection and inflammation related pathways. Combining results from different levels, our study provided multi-level evidence supporting the relationship between infectious and inflammatory factors and three psychiatric disorders, which might facilitate further research on pathogenesis of major psychiatric disorders.
|高蕾. 基于生物信息学方法探究感染及炎症 相关因素与三种常见精神疾病的关系[D]. 北京. 中国科学院研究生院,2014.|
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