Major depressive disorder (MDD) is a leading cause of the global disease burden with a life time prevalence of almost 15%. Genetic studies have not worked as well for MDD as for other psychiatric conditions. DNA methylation studies are a particularly promising complement. First, methylation markers may have better predictive power as methylation is directly related to gene expression. Second, methylation studies may improve disease understanding as they can account for a range of clinical disease features. For example, DNA sequence variants cannot explain the variability in age of onset or the dynamic course of MDD that is typified by exacerbations and remissions. DNA methylation studies potentially can as methylation levels show age-dependent changes and are dynamic in post-mitotic tissues in the brain. Third, the translational potential of methylation studies is profound Methylation sites are excellent modifiable targets for pharmacological interventions and as methylation is stable and can be measured cost-effectively in blood they can potentially be used in clinical settings. Our overarching goal is to identify methylation markers in existing periphera blood samples associated with clinical MDD trajectories over a six year time period. Although methylation marks in blood will not directly impact MDD, factors that affect trajectories (e.g. stress) may also affect methylation signatures in blood. As traces of these methylation changes may be preserved during cell division, indirectly our studies can also shed light on causal mechanisms. Methylation of human (non-stem cell) DNA occurs at CpG sites. As the biological knowledge is lacking to identify good candidate CpG sites, we will use next-generation sequencing to screen the >28 million CpGs in the human genome for their association with the persistence of MDD, and then replicate the top findings in independent samples using a different technology. Specifically, we will sequence 1,500 methylomes using DNA collected from the same subjects at baseline and after six years from three groups from the Netherlands Study of Depression and Anxiety: 1) controls with no MDD, 2) cases with MDD at baseline and then fully remit, and 3) cases with chronic MDD. To improve statistical power and to select the biologically most meaningful methylation markers, we will integrate other data such as genome-wide transcriptome data that is already available for these samples. Using a parallel longitudinal 3 group design, the 50 most promising sites will be replicated in 1,500 independent samples using a different technology. Successful completion of the proposed research will yield replicable methylation signatures of MDD disease trajectories with which we will start generating prediction algorithms that could eventually be used in the clinic to improve prevention, treatment, and diagnosis.
Major depressive disorder (MDD) is a leading cause of the global disease burden. Discerning the genetic basis of MDD has been difficult but DNA methylation studies represent a new and promising avenue. Successful completion of the proposed research will yield replicable methylation biomarker signatures of MDD disease trajectories that will be used to start generating prediction algorithms that could eventually be used in the clinic to improve prevention, treatment, and diagnosis.
|Aberg, Karolina A; Xie, Linying; Chan, Robin F et al. (2015) Evaluation of Methyl-Binding Domain Based Enrichment Approaches Revisited. PLoS One 10:e0132205|
|Shabalin, Andrey A; Aberg, Karolina A; van den Oord, Edwin J C G (2015) Candidate gene methylation studies are at high risk of erroneous conclusions. Epigenomics 7:13-5|