RESUMEN
BACKGROUND: Research suggests that Alopecia areata (AA) and Major Depressive Disorder (MDD) show substantial comorbidity. To date, no study has investigated the hypothesis that this is attributable to shared genetic aetiology. OBJECTIVES: To investigate AA-MDD comorbidity on the epidemiological and molecular genetic levels. METHODS: First, epidemiological analyses were performed using data from a cohort of adult German health insurance beneficiaries (n = 1.855 million) to determine the population-based prevalence of AA-MDD comorbidity. Second, analyses were performed to determine the prevalence of MDD in a clinical AA case-control sample with data on psychiatric phenotypes, stratifying for demographic factors to identify possible contributing factors to AA-MDD comorbidity. Third, the genetic overlap between AA and MDD was investigated using a polygenic risk score (PRS) approach and linkage disequilibrium score (LDSC) regression. For PRS, summary statistics from a large MDD GWAS meta-analysis (PGC-MD2) were used as the training sample, while a Central European AA cohort, including the above-mentioned AA patients, and an independent replication US-AA cohort were used as target samples. LDSC was performed using summary statistics of PGC-MD2 and the largest AA meta-analysis to date. RESULTS: High levels of AA-MDD comorbidity were reported in the population-based (MDD in 24% of AA patients), and clinical samples (MDD in 44% of AA patients). MDD-PRS explained a modest proportion of variance in AA case-control status (R2 = 1%). This signal was limited to the major histocompatibility complex (MHC) region on chromosome 6. LDSC regression (excluding MHC) revealed no significant genetic correlation between AA and MDD. CONCLUSIONS: As in previous research, AA patients showed an increased prevalence of MDD. The present analyses suggest that genetic overlap may be confined to the MHC region, which is implicated in immune function. More detailed investigation is required to refine understanding of how the MHC is involved in the development of AA and MDD comorbidity.
RESUMEN
Although the currently available antidepressants are well established in the treatment of the major depressive disorder (MDD), there is strong variability in the response of individual patients. Reliable predictors to guide treatment decisions before or in an early stage of treatment are needed. DNA-methylation has been proven a useful biomarker in different clinical conditions, but its importance for mechanisms of antidepressant response has not yet been determined. 80 MDD patients were selected out of >500 participants from the Early Medication Change (EMC) cohort with available genetic material based on their antidepressant response after four weeks and stratified into clear responders and age- and sex-matched non-responders (N = 40, each). Early improvement after two weeks was analyzed as a secondary outcome. DNA-methylation was determined using the Illumina EPIC BeadChip. Epigenome-wide association studies were performed and differentially methylated regions (DMRs) identified using the comb-p algorithm. Enrichment was tested for hallmark gene-sets and in genome-wide association studies of depression and antidepressant response. No epigenome-wide significant differentially methylated positions were found for treatment response or early improvement. Twenty DMRs were associated with response; the strongest in an enhancer region in SORBS2, which has been related to cardiovascular diseases and type II diabetes. Another DMR was located in CYP2C18, a gene previously linked to antidepressant response. Results pointed towards differential methylation in genes associated with cardiac function, neuroticism, and depression. Linking differential methylation to antidepressant treatment response is an emerging topic and represents a step towards personalized medicine, potentially facilitating the prediction of patients' response before treatment.