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Background: Antidepressants are among the most prescribed medications in the United States. The aim of this study was to explore the prevalence of antidepressant prescriptions and investigate sex differences and age-sex interactions in adults enrolled in the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT) study. Materials and Methods: We conducted a retrospective analysis of the RIGHT study. Using electronic prescriptions, we assessed 12-month prevalence of antidepressant treatment. Sex differences and age-sex interactions were evaluated using multivariable logistic regression and flexible recursive smoothing splines. Results: The sample consisted of 11,087 participants (60% women). Antidepressant prescription prevalence was 22.24% (27.96% women, 13.58% men). After adjusting for age and enrollment year, women had significantly greater odds of antidepressant prescription (odds ratio = 2.29; 95% confidence interval = 2.07, 2.54). Furthermore, selective serotonin reuptake inhibitors (SSRIs) had a significant age-sex interaction. While SSRI prescriptions in men showed a sustained decrease with age, there was no such decline for women until after reaching ∼50 years of age. There are important limitations to consider in this study. Electronic prescription data were cross-sectional; information on treatment duration or adherence was not collected; this cohort is not nationally representative; and enrollment occurred over a broad period, introducing confounding by changes in temporal prescribing practices. Conclusions: Underscored by the significant interaction between age and sex on odds of SSRI prescription, our results warrant age to be incorporated as a mediator when investigating sex differences in mental illness, especially mood disorders and their treatment. [ABSTRACT FROM AUTHOR]

• Bipolar disorder is a chronic illness requiring lifelong psychotropic treatment. • Treatment typically involves switching or adding medications from different classes. • Illness trajectory differs among individuals, complicating staging or risk appraisal. • Markers of disease complexity were associated with pharmacotherapy exposure. • Higher polygenic risk for schizophrenia or anxiety predicted pharmacotherapy exposure. Individuals with bipolar disorder (BD) require chronic pharmacotherapy, typically including medication switches or polypharmacy due to persisting symptoms or intolerable side effects. Here, we quantified pharmacotherapy exposure (PE) of Mayo Clinic BD Biobank participants using the number of cross-sectional (at enrollment) and lifetime BD-specific medications and medication classes, to understand the relationship between PE and markers of disease severity or treatment failure, psychiatric comorbidities, and polygenic risk scores (PRS) for six major psychiatric disorders. Being female (p < 0.05), older (p < 0.01), having history of suicide attempts (p < 0.0001), and comorbid attention-deficit/hyperactivity disorder (p < 0.05) or generalized anxiety disorder (p < 0.05) were uniformly associated with higher PE. Lifetime exposure to unique medication classes among participants with BD-I was significantly lower than for those with schizoaffective disorder (estimate = -2.1, p < 0.0001) while significantly higher than for those with BD-II (estimate = 0.5, p < 0.01). Further, higher PRS for schizophrenia (SCZ) and anxiety resulted in greater lifetime medication counts (p < 0.01), both driven by antipsychotic (p < 0.001) and anxiolytic use (p < 0.05). Our results provide initial evidence of the utility of PE as a measure of disease complexity or treatment resistance, and that PE may be predicted by higher genetic risk for SCZ and anxiety. [ABSTRACT FROM AUTHOR]