Integrative analyses of genetic, epigenetic, transcriptomic, and environmental vulnerability factors of affective disorders

情感障碍的遗传、表观遗传、转录组和环境脆弱性因素的综合分析

• 批准号: 250995792
• 负责人: Professor Dr. Markus M. Nöthen
• 金额: --
• 依托单位: Institut für Humangenetik
• 依托单位国家: 德国
• 项目类别: Research Units
• 财政年份: 2014
• 资助国家: 德国
• 起止时间: 2013-12-31 至 2019-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/250995792?language=en
• 关键词: Integrative; analyses; genetic; epigenetic; transcriptomic

The contribution of genetic factors to major depressive disorder (MDD) and bipolar disorder (BD) is well established, with heritability estimates ranging between 40 and 70% (MDD) and up to 80% (BD), respectively. Molecular genetic candidate and genome-wide association studies (GWAS) have identified a number of susceptibility genes contributing to their etiology including CACNA1C and NCAN, and our group has contributed substantially to these findings.The aim of WP5 is to identify how genetic and environmental factors impact on the etiology of affective disorders, by using genetic, epigenetic and transcriptomic methods. So far, we performed systematic genome-wide genotyping of the first 1.000 MACS for which DNA was available. The obtained genotype data was imputed and genotype information for several genes, including NCAN and CACNA1C, was provided to WP1 and WP6 for further analyses. In addition, in-depth bisulfite sequencing analysis of CACNA1C and NCAN was performed. The genome-wide methylation analysis was completed for 66 individuals from two sub-groups with genetic or environmental risk as well as from a control group. The analysis revealed patterns of differential methylation in pathways which have previously been implicated in BD. Using our large BD GWAS data, we performed additional bioinformatics analyses including a genome-wide analysis of microRNA coding genes in collaboration with WP3 and WP6. While so far most epigenetic and gene expression studies have concentrated on comparison between categorical diagnosis and neglected course of disorder, severity, and effect of medication, in the second funding period, WP5 seeks to identify such correlations in the complete sample and most extensively together with WP6 in a subsample of 300 individuals (100 MDD-, 100 BD-patients, 100 healthy subjects) which will also be analyzed intensely by WP1, WP3, and WP4. Epigenome-wide methylation and expression profiles will be assessed in this subsample at baseline and follow-up. Longitudinal analyses of the methylation and expression profiles will be performed in relation to the course of illness or the occurrence of life-events. The genome-wide genotype dataset will be completed for all 2.500 MACS. This dataset will allow us to further analyze the impact of the cumulative effect of variation on subphenotypes. Using data from different platforms, we will perform integrative analyses of the genetic, epigenetic and expression data in collaboration with WP6. This includes multimarker, polygenic and pathway analyses to identify yet undetected genotype-phenotype and GxE effects. The data will be used particularly for in-depth analysis of genes which are interaction partners or in pathways of the two risk genes CACNA1C and NCAN. The generated data will be provided to WP1, WP3, WP4 and WP6 for further analyses. The results of our analyses will elucidate disease-specific factors, as well as factors which are of relevance across diagnostic boundaries.

遗传因素对严重抑郁障碍(MDD)和双相情感障碍(BD)的贡献是公认的，遗传力估计分别在40%到70%(MDD)和高达80%(BD)之间。分子遗传学候选和全基因组关联研究(Gwas)已经确定了一些导致情感障碍病因的易感基因，包括CACNA1C和NCAN，我们的团队对这些发现做出了重大贡献。WP5的目的是通过使用遗传学、表观遗传学和转录转录的方法来确定遗传和环境因素如何影响情感障碍的病因。到目前为止，我们对第一批可获得DNA的1.000个Mac进行了系统的全基因组基因分型。获得的基因数据被输入，并将包括NCAN和CACNA1C在内的几个基因的基因信息提供给WP1和WP6进行进一步分析。此外，对CACNA1C和NCAN进行了深入的亚硫酸氢盐测序分析。来自两个有遗传或环境风险的亚组的66个个体以及来自对照组的66个个体完成了全基因组甲基化分析。分析揭示了以前被认为与BD有关的通路中的差异甲基化模式。使用我们的大型BD Gwas数据，我们进行了额外的生物信息学分析，包括与WP3和WP6合作对microRNA编码基因进行全基因组分析。虽然到目前为止，大多数表观遗传学和基因表达研究都集中在明确诊断和被忽视的疾病病程、严重程度和药物效果之间的比较，但在第二个资助期，WP5试图在整个样本中确定这种相关性，最广泛的是与WP6一起在300个个体(100名MDD患者、100名BD患者、100名健康受试者)中进行分析，WP1、WP3和WP4也将对其进行深入分析。表观基因组范围的甲基化和表达谱将在基线和后续的这一亚样本中进行评估。甲基化和表达谱的纵向分析将与病程或生活事件的发生有关。将完成所有2.500个Mac的全基因组基因数据集。这一数据集将使我们能够进一步分析变异累积效应对亚型的影响。利用来自不同平台的数据，我们将与WP6合作对遗传、表观遗传和表达数据进行综合分析。这包括多标记、多基因和通径分析，以确定尚未检测到的基因型-表型和GxE效应。这些数据将特别用于深入分析两个风险基因CACNA1C和NCAN的相互作用伙伴或途径中的基因。生成的数据将提供给WP1、WP3、WP4和WP6作进一步分析。我们的分析结果将阐明疾病特有的因素，以及跨诊断界限相关的因素。