Optimizing perimenopausal mental health by integrating precision biomarkers, digital health interventions, and psychosocial care.

Abstract

This study addressed the critical need for an integrated, personalized approach to perimenopausal mental health, addressing both biological and psychosocial factors. Current research highlighted the influence of hormonal fluctuations, genetic predispositions, and lifestyle factors in shaping perimenopausal mental health outcomes. This transitional period is marked by significant hormonal fluctuations contributing to heightened anxiety, depression, and sleep disturbances, affecting the women's quality of life. Traditional pharmacological treatments, including selective serotonin reuptake inhibitors and hormone replacement therapy, have limitations due to variable efficacy and side effects, emphasizing the need for precision medicine. Advancements in pharmacogenomics and metabolomics provide new avenues for individualized treatments, with genetic markers (e.g., Solute carrier organic anion transporter family member 1B1, estrogen receptor 1/estrogen receptor 2, and tachykinin receptor 3) guiding hormone therapy responses. Emerging digital health technologies, such as artificial intelligence-driven diagnostics, wearable monitoring, and telehealth platforms, offer scalable, real-time mental health support, though regulatory and clinical validation challenges remain. Furthermore, integrative treatment models combining hormone-based therapy with non-pharmacological interventions demonstrate significant efficacy in alleviating perimenopausal symptoms. Future directions should prioritize the clinical validation and ethical implementation of digital health solutions, ensuring safety, efficacy, and user accessibility. A multidisciplinary, patient-centric model, incorporating genetics, endocrinology, digital health, and psychosocial interventions, is essential for optimizing perimenopausal mental health outcomes.