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

Prof. Dr. Marcella Rietschel¹, PD Dr. Stephanie Witt¹, Prof. Dr. Markus M. Nöthen²

¹University of Heidelberg, Central Institute of Mental Health (ZI) Mannheim
²University of Bonn, Institute of Human Genetics and Department of Genomics, Life & Brain Centre 

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 Work Package 5 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 Work Package 3 and Work Package 6.
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, Work Package 5 seeks to identify such correlations in the complete sample and most extensively together with Work Package 6 in a subsample of 300 individuals (100 MDD-, 100 BD-patients, 100 healthy subjects) which will also be analyzed intensely by Work Package 1, Work Package 3, and Work Package 4. 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 lifeevents. 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 Work Package 6. This includes multimarker, polygenic and pathway analyses to identify yet undetected genotypephenotype 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 Work Package 1, Work Package 3, Work Package 4 and Work Package 6 for further analyses. The results of our analyses will elucidate disease-specific factors, as well as factors which are of relevance across diagnostic boundaries.