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Fluctuating hormone levels during the menstrual cycle and major reproductive cycle stages have been linked to mood changes, mental health conditions, and an increased likelihood of psychotic episodes. This knowledge could potentially be used for the predictive modeling of exacerbations and mood deterioration through the collection and analysis of data from wearables and apps. A literature search for a narrative review has been conducted using selected keywords in Pubmed, Embase and Google Scholar. Based on published data, it can be seen that hormonal changes affect the severity of symptoms in several mental health conditions, including depression, PMDD, PTSD, bipolar disorder and schizophrenia. The influence of FSH, LH, testosterone, and other hormone precursors has also been investigated, but there is less information available regarding their impact. E2 levels have been measured as a treatment–response biomarker and have demonstrated significant predictive ability for treatment responder groups. On the other hand, FSH has been demonstrated to be helpful in predicting treatment non-responder groups in schizophrenia. Monitoring reproductive hormones in combination with wearables or digital solutions has the potential to predict mood changes more effectively. Precise and frequent hormone measurements might prove to be more effective than relying on absolute threshold levels. Further research is needed to validate the utility and precision of hormone use in the field of mental health.
Wieczorek et al. (Thu,) studied this question.