Work Package 5
Integrative analyses of genetic, epigenetic, and environmental vulnerability factors of affective disorders
Prof. Dr. Marcella Rietschel1, PD Dr. Stephanie Witt1, Prof. Dr. Markus M. Nöthen2, Prof. Dr. Axel Krug³
1University of Heidelberg, Central Institute of Mental Health (ZI) Mannheim 2University of Bonn, Institute of Human Genetics and Department of Genomics, Life & Brain Centre 3University of Marburg, Department of Psychiatry and Psychotherapy
Twin, family and epidemiologic studies provide robust evidence for an important contribution of genetic factors to the etiology and pathophysiology of affective disorders. The estimates of heritability are high and range between 40 and 70% for major depressive disorder and up to 80% for bipolar disorder, respectively. Recent molecular genetic studies have identified a number of susceptibility genes in both disorders, and our group has contributed substantially to these findings. The aim of this workpackage is to identify how genetic, epigenetic, and environmental factors impact on the etiology of affective disorders. This will be achieved by genotyping the MACS probands (N=2500) and correlating these factors with each other, with categorical diagnoses, and with subphenotypes. The latter will be assessed in the MACS with magnetic resonance imaging (MRI, WP1), studies of miRNA profiles and of mitochondrial function (WP3, WP4), among others. A focus will be on the effects of two novel, yet well established, risk genes, i.e. CACNA1C and NCAN. In addition, systematic approaches will be added: to ensure state-of-the-art coverage of all variants known to be of importance to psychiatric disorders, subjects will be genotyped with the PsychChip, a genome-wide array enriched with 50.000 variants specific for psychiatric disorders, and genome-wide methylation will be conducted in extreme groups. For the statistical analyses, a convergent approach will be applied in collaboration with WP6. This will comprise single marker, multimarker-, polygenic score based-, and pathway analytical methods, and will take into account environmental factors. The results of our analyses will provide data concerning diagnosis-specific factors, as well as factors which are of relevance across diagnostic boundaries.