Metabolomic predictors for late-life depression

Abstract

<h3>Introduction</h3> Depression is a major public health problem among older adults and among the leading causes of global burden of disease and disability. Yet, current understanding of pathophysiology and optimal prevention and/or treatment of late-life depression (LLD) is limited. Advanced approaches involving methods such as metabolomics present an innovative path to identify novel biomarkers of LLD outcomes. Several known biological pathways involving tryptophan and lipid-inflammatory molecules (eicosanoids) are relevant to depression; however, there have been few systematic investigations of metabolomic predictors of long-term trajectories of LLD. <h3>Methods</h3> This is a convenience sample of ∼7000 Nurses' Health Study (NHS) participants with known metabolites and who completed depression items every four years from 1992-2016. Between 1989 and 1990, blood samples were collected and stored under standard conditions. In NHS, data on known metabolites were generated by merging the data from multiple case-control studies; however, all metabolites were profiled using liquid chromatography mass spectrometry in the same laboratory. Continuous metabolite values were transformed to probit scores to account for batch effects. We used a previously developed harmonized depressive symptom scale that was indexed to the five-item Mental Health Inventory (MHI-5, range=0-100 points). For cross-sectional analysis, we performed multivariable logistic regression models to evaluate the associations of baseline metabolite levels and likelihood of the moderate or severe depressive symptoms (MHI-5 cut-off=60); for longitudinal analysis, we used latent growth-curve analysis to identify group-based trajectories of depressive symptoms and then related baseline metabolite levels to long-term trajectories. <h3>Results</h3> The mean age of female nurses at blood draw was 57.0 (range=42.6-70.2) years. There were ∼6300 NHS participants with available data on tryptophan metabolites and ∼1300 NHS participants with available data on eicosanoids. We observed stronger signals for cross-sectional associations of higher circulating levels of tryptophan, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) with lower risk of moderate or severe depressive symptoms, adjusted for age at blood draw, fasting status, case-control status, physical activity, body mass index, diet index, alcohol use, and cigarette smoking [multivariable odds ratio (95% confidence interval): for tryptophan=0.86 (0.80-0.93), p<0.01; for EPA=0.84 (0.71-1.01), p=0.06; for DHA=0.85 (0.71-1.02), p=0.07]. From 1992-2016, we identified four depressive symptom trajectory groups: minimal depressive symptoms (63%), worsening depressive symptoms (12%), improving depressive symptoms (20%), and persistent severe depressive symptoms (5%). Additional results from multinomial models evaluating the associations between metabolites and long-term LLD trajectories will be presented. <h3>Conclusions</h3> In this sample, tryptophan and omega-3 fatty acid metabolites were significantly related to LLD outcomes; these metabolites may play a role in the pathophysiology of LLD. <h3>Funding</h3> HMS Livingston Fellowship Award