Shared Biologic Pathways Between Alzheimer Disease and Major Depression: A Systematic Review of MicroRNA Expression Studies.

OBJECTIVE: The clinical-epidemiological relationship between major depressive disorder (MDD) and Alzheimer disease (AD) suggests that they may share common neurobiologic abnormalities. METHODS: The authors conducted a systematic review and identified microRNAs abnormally expressed in both AD and MDD. The pattern of microRNA regulation in each disorder and the genes regulated by each microRNA and the biologic processes and pathways regulated by these genes were identified. RESULTS: Seventy-four microRNAs were abnormally expressed in AD and 30 in MDD; 7 were common for both disorders (hsa-let-7f-5p, hsa-miR-664a-3p, hsa-miR-361-5p, hsa-let-7g-5p, hsa-let-7d-5p, hsa-miR-191-5p, hsa-miR-26b-5p). These microRNAs interact with 45 validated genes, and the main biologic pathways and processes regulated by them were proteostasis control, maintenance of genomic integrity, regulation of transcriptional activity, immune-inflammatory control, and neurotrophic support. CONCLUSION: The current results suggest that the maintenance of genomic integrity, proteostasis control, immune-inflammatory regulation, and neurotrophic support are key neurobiologic links between these conditions. A comprehensive hypothetical model for the interaction between MDD, aging, and the development of AD is provided.

Predictors of incidence of clinically significant depressive symptoms in the elderly: 10-year follow-up study of the Bambui cohort study of aging.

OBJECTIVE: We aim to evaluate the incidence rate and predictors of clinically significant depressive symptoms (CSDS) over 10 years of follow-up from a population-based cohort study (the Bambui Cohort Study of Aging). METHODS: We calculated the predictors of incidence of CSDS over 10 years of follow-up by the Cox proportional regression analysis. Depressive symptoms were evaluated by GHQ-12 and scores of five or higher indicated CSDS. RESULTS: The annualized incidence rate of clinically significant depressive symptoms was 46 per 1000 person-year. In the multivariate analysis, the main predictors of CSDS were cognitive impairment (HR = 1,69 CI95% [1,20 - 2.37], p = 0.002), diabetes (HR = 1.59 CI95% [1.14 - 2.20], p = 0.006), use of 2 to 4 (HR = 1,95 CI95% [1.21 - 3.15], p = 0.006) and of 5 or more medications in the last 90 days (HR = 2.19 CI95% [1.31 - 3.66], p = 0.003) and higher baseline depressive symptoms (HR = 2.12 CI95% [1.61 - 2.78], p < 0.001). CONCLUSION: These results highlight the importance of higher depressive symptoms, cognitive impairment and endocrine-metabolic disorders to the development of depressive symptoms in older adults. These findings provide a framework for the development of interventions to prevent the emergence of clinically significant depressive symptoms in the elderly.