Depression & PerimenopauseThe Immunobiological Mechanisms of Depression in Perimenopause

This project aims to identify immunobiological mechanisms underlying the development of depression during the perimenopause. During the perimenopause, the risk for recurrence of depression is increased 13-fold among women who previously had depression. Moreover, perimenopause overlaps with the age span exhibiting the highest suicide rate for women. The perimenopause can last for several years and starts when estrogen and progesterone levels begin to fluctuate, gradually declining. Sex hormones are powerful modulators of the immune response and the investigators therefore propose that changes in lymphocytes play a central role in depression during this time. Notably, our previous work has demonstrated deficient regulatory T-cell responses in women with post- partum depression and identified a specific pro-inflammatory profile that predicts depression during pregnancy. Importantly, our new pilot data derived from women with severe depression in the perimenopausal age span reveals alterations in tryptophan metabolites that control T- cell responses as well as in the methylation of genes involved in T-cell fate and chromatin remodeling. Taken together, these data support the hypothesis that the perimenopausal hormonal shifts induce a pro-inflammatory state, regulated by chromatin modifications in T-cells, that triggers depression in vulnerable women.

To test this hypothesis, the investigators will enroll 180 perimenopausal women aged 40-55, approximately half with depression and half without a diagnosis of depression. All participants will complete psychiatric assessments and provide blood samples to measure sex hormones, inflammation and immune cell changes. Women with depression will be reassessed approximately eight weeks later to identify blood markers that change as depressive symptoms improve.

This project seeks to improve understanding of the biological mechanisms of depression during perimenopause and aid the development of predictive biomarkers and more effective treatments.