Dataset Information

Assessment of a Bidirectional Association Between Major Depressive Disorder and Alopecia Areata.

ABSTRACT:

Importance

Alopecia areata (AA) is an autoimmune disease characterized by hair loss that can impose a substantial psychological burden on patients, including major depressive disorder (MDD), yet many patients report mental health symptoms prior to the onset of AA. As such, there may be an association between MDD and AA that acts in both directions.

Objective

To assess the bidirectional association between MDD and AA.

Design, setting, and participants

This population-based retrospective cohort study included patients 10 to 90 years of age registered with The Health Improvement Network in general practices in the United Kingdom between January 1, 1986, and May 16, 2012. Statistical analysis was conducted from August 17, 2017, to April 23, 2018. To assess the risk of AA, the following 2 cohorts were defined: patients with an incident diagnosis of MDD (exposure) and a reference general population cohort. To assess the risk of MDD, the following 2 cohorts were defined: patients with an incident diagnosis of AA (exposure) and a reference general population cohort. Person-time was partitioned into unexposed and exposed time in the exposure cohorts.

Main outcomes and measures

In the analysis of the risk of AA, development of incident AA during follow-up was considered the main outcome measure. In the analysis of the risk of MDD, development of incident MDD during follow-up was considered the primary outcome measure.

Results

In the analysis of the risk of AA, 405 339 patients who developed MDD (263 916 women and 141 423 men; median age, 36.7 years [interquartile range, 26.6-50.5 years]) and 5 738 596 patients who did not develop MDD (2 912 201 women and 2 826 395 men; median age, 35.8 years [interquartile range, 25.3-52.6 years]) were followed up for 26 years. After adjustment for covariates, MDD was found to increase the risk of subsequently developing AA by 90% (hazard ratio, 1.90; 95% CI, 1.67-2.15; P < .001). Antidepressants demonstrated a protective effect on the risk of AA (hazard ratio, 0.57; 95% CI, 0.53-0.62; P < .001). In the analysis of the risk of MDD, 6861 patients who developed AA (3846 women and 3015 men; median age, 31.5 years [interquartile range, 18.2 years]) and 6 137 342 patients who did not develop AA (3 172 371 women and 2 964 971 men; median age, 35.9 years [interquartile range, 27.0 years]) were followed up for 26 years. After adjustment for covariates, AA was found to increase the risk of subsequently developing MDD by 34% (hazard ratio, 1.34; 95% CI, 1.23-1.46; P < .001).

Conclusions and relevance

These temporal analyses suggest that, while patients with AA are at risk for subsequently developing MDD, having MDD also appears to be a significant risk factor for development of AA, with antidepressant use confounding this risk.

SUBMITTER: Vallerand IA

PROVIDER: S-EPMC6459092 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD. In total, 33 MDD patients and 34 healthy controls were analyzed using basal gene expression in whole blood, and gene expression from whole blood that was stimulated with LPS for 5-6 h, using microarrays. Patients were arbitrarily selected from all patients to serve as primary cohort (nMDD = 21 (MDD01-MDD21); nControls = 21 (Con01-Con21)), or replication cohort (nMDD = 12 (MDD22-MDD35); nControls = 13 (Con22-Con37)) using microarrays. This submission does not include Samples CON21_LPS or CON30_LPS.

Project description:AIMS/HYPOTHESIS:Observational studies have shown a bidirectional association between major depressive disorder (MDD) and cardiometabolic diseases. We conducted a two-sample bidirectional Mendelian randomisation (MR) study to assess the causal associations of MDD with type 2 diabetes, coronary artery disease (CAD) and heart failure and vice versa. METHODS:We extracted summary-level data for MDD, type 2 diabetes, CAD and heart failure from corresponding published large genome-wide association studies of individuals mainly of European-descent. In total, 96 SNPs for MDD, 202 SNPs for type 2 diabetes, 44 SNPs for CAD and 12 SNPs for heart failure were proposed as instrumental variables at the genome-wide significance level (p?<?5?×?10-8). The random-effects inverse-variance weighted method was used for the main analyses. RESULTS:Genetic liability to MDD was significantly associated with type 2 diabetes and CAD at the Bonferroni-corrected significance level. The ORs of type 2 diabetes and CAD were respectively 1.26 (95% CI 1.10, 1.43; p?=?6?×?10-4) and 1.16 (95% CI 1.05, 1.29; p?=?0.0047) per one-unit increase in loge odds of MDD. There was a suggestive association between MDD and heart failure (OR 1.11 [95% CI 1.01, 1.21]; p?=?0.033). We found limited evidence supporting causal effects of cardiometabolic diseases on MDD risk in the reverse MR analyses. CONCLUSIONS/INTERPRETATION:The present study strengthened the evidence that MDD is a potential risk factor for type 2 diabetes and CAD. Whether MDD is causally related to heart failure needs further study. DATA AVAILABILITY:All data included in this study were uploaded as supplements and are also publicly available through published GWASs and open GWAS datasets (UK Biobank, 23andMe and Psychiatric Genomics: https://datashare.is.ed.ac.uk/handle/10283/3203; DIAGRAM: http://diagram-consortium.org/downloads.html; CARDIoGRAMplusCD4: www.cardiogramplusc4d.org/; HERMES: http://www.kp4cd.org/datasets/mi). Graphical abstract.