Associação entre depressão na perimenopausa e níveis séricos de estradiol e hormônio folículo-estimulante

Identification of an Immune-Neuroendocrine Biomarker Panel for Detection of Depression: A Joint Effects Statistical Approach

BACKGROUND/AIMS

Less than half of depression patients are correctly diagnosed within the primary care setting. Previous proteomic studies have identified numerous immune and neuroendocrine changes in patients. However, few studies have considered the joint effects of biological molecules and their diagnostic potential. Our aim was to develop and validate a diagnostic serum biomarker panel identified through joint effects analysis of multiplex immunoassay profiling data from 1,007 clinical samples.

METHODS

In stage 1, we conducted a meta-analysis of two independent cohorts of 78 first-/recent-onset drug-naive/drug-free depression patients and 156 controls and applied the 10-fold cross-validation with least absolute shrinkage and selection operator regression to identify an optimal diagnostic prediction model (biomarker panel). In stage 2, we tested the discriminatory performance of this biomarker panel using the naturalistic Netherlands Study of Depression and Anxiety (NESDA) cohort of 468 depression patients and 305 controls.

RESULTS

An optimal panel of 33 immune-neuroendocrine biomarkers and gender was selected in the meta-analysis. Testing this biomarker-gender panel using the NESDA cohort resulted in a moderate to good performance to differentiate patients from controls (0.69 < AUC < 0.86), particularly the first-episode patients free of chronic non-psychiatric diseases or medications and following incorporation of sociodemographic covariates (0.76 < AUC < 0.92).

CONCLUSION

Despite the need for additional validation studies, we demonstrated that a blood-based biomarker-sociodemographic panel can detect depression in naturalistic healthcare settings with good discriminatory power. Further refinements of blood biomarker panels aiding in the diagnosis of depression may provide a cost-effective means to increase accuracy of clinical diagnosis within the primary care setting.

The perimenopause, depressive disorders, and hormonal variability

CONTEXT

Several investigations have postulated that the perimenopause may represent a period of increased psychiatric vulnerability, particularly for mood disorders. This review characterizes the perimenopause, including biological changes, the influence of psychosocial factors and the most common clinical manifestations. Clinic-based studies and community-based surveys addressing the prevalence of depressive symptoms in perimenopausal women are critically reviewed. We also discuss the potential greater vulnerability to mood disturbance during the perimenopause in response to hormonal variability. A therapeutic algorithm for management of depressive symptoms in middle-aged perimenopausal women is also presented. The role of estrogen in the treatment of perimenopausal depressive symptoms is particularly discussed. In addition, we review the existing data regarding the potential efficacy of estrogen as an antidepressant agent (monotherapy, augmentation strategy or prophylaxis).

DESIGN

Narrative review.