The burden of depression in men is high. Current diagnostic criteria may not fully capture men's experience with depression. Descriptions of the heterogeneity in depression among men are lacking. The purpose of the study was to characterize latent subtypes of major depression and changes in these subtypes among men receiving citalopram in Level 1 of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial. Latent transition analysis was applied to data from 387 men who completed baseline and Week 12 study visits in Level 1 of STAR*D. Items from the self-report version of the Quick Inventory of Depressive Symptomatology were used as indicators of latent depression subtypes. Four statuses were identified at baseline and Week 12. Baseline statuses were Mild (10% of men), Moderate (53%), Severe with Psychomotor Slowing (20%), and Severe with Psychomotor Agitation (17%). At Week 12, the statuses were Symptom Resolution (41%), Mild (36%), Moderate (18%), and Severe with Psychomotor Slowing (5%). Men in the Mild status were most likely to transition to Symptom Resolution (probability = 69%). Men in the Severe with Agitation status were least likely to transition to Symptom Resolution (probability = 0%). This work highlights the need to not focus solely on summary rating scores but to also consider patterns of symptoms when treating depression.

Over the last decade there has been a great effort to annotate noncoding regions of the genome, particularly those that regulate gene expression. These regulatory elements contain binding sites for transcription factors (TF), which interact with one another and transcriptional machinery to initiate, enhance, or repress gene expression. The Encyclopedia of DNA Elements (ENCODE) consortium has generated thousands of epigenomic datasets, such as DNase-seq and ChIP-seq experiments, with the goal of defining such regions. By integrating these assays, we developed the Registry of candidate Regulatory Elements (cREs), a collection of putative regulatory regions across human and mouse. In total, we identified over 1.3M human and 400k mouse cREs each annotated with cell-type specific signatures (e.g. promoter-like, enhancer-like) in over 400 human and 100 mouse biosamples. We then demonstrated the biological utility of these regions by analyzing cell type enrichments for genetic variants reported by genome wide association studies (GWAS). To search and visualize these cREs, we developed the online database SCREEN (search candidate regulatory elements by ENCODE). After defining cREs, we next sought to determine their potential gene targets. To compare target gene prediction methods, we developed a comprehensive benchmark of enhancer-gene links by curating ChIA-PET, Hi-C and eQTL datasets. We then used this benchmark to evaluate unsupervised linking approaches such as the correlation of epigenomic signal. We determined that these methods have low overall performance and do not outperform simply selecting the closest gene. We then developed a supervised Random Forest model which had notably better performance than unsupervised methods. We demonstrated that this model can be applied across cell types and can be used to predict target genes for GWAS associated variants. Finally, we used the registry of cREs to annotate variants associated with psychiatric disorders. We found that these "psych SNPs" are enriched in cREs active in brain tissue and likely target genes involved in neural development pathways. We also demonstrated that psych SNPs overlap binding sites for TFs involved in neural and immune pathways. Finally, by identifying psych SNPs with allele imbalance in chromatin accessibility, we highlighted specific cases of psych SNPs altering TF binding motifs resulting in the disruption of TF binding. Overall, we demonstrated our collection of putative regulatory regions, the Registry of cREs, can be used to understand the potential biological function of noncoding variation and develop hypotheses for future testing.

OBJECTIVE: To examine whether cerebrovascular risk, executive function, and processing speed are associated with acute treatment outcome of psychotic depression in older adults. METHODS: The authors analyzed data from 142 persons aged 60 years or older with major depression with psychotic features who participated in a 12-week randomized controlled trial (RCT) comparing olanzapine plus sertraline with olanzapine plus placebo. The independent variables were baseline cerebrovascular risk (Framingham Stroke Risk Score), baseline executive function (Stroop interference score and the initiation/perseveration subscale of the Mattis Dementia Rating Scale), and baseline processing speed (color and word reading components of the Stroop). The outcome variable was change in severity of depression, measured by the 17-item Hamilton Depression Rating Scale total score, during the course of the RCT. RESULTS: Greater baseline cerebrovascular risk was significantly associated with less improvement in depression severity over time, after controlling for pertinent covariates. Neither executive function nor processing speed predicted outcome. CONCLUSION: This study suggests an association of cerebrovascular risk, but not executive function or processing speed, with treatment outcome of major depression with psychotic features in older adults.