New approach methodologies (NAMs) for preclinical and translational evaluation of mRNA-lipid nanoparticle (LNP) therapeutics.

Bipolar disorder (BD) is a severe mood disorder with a lifetime prevalence of ~1–2% of the world population [], representing a major cause of disability globally [, ]. It typically emerges during adolescence or early adulthood, with a median age of onset around 20 years; early identification is essential to improve prognosis and quality of life [, ]. Delayed diagnosis is associated with poorer treatment response, increased suicide risk, and higher healthcare costs [–]. Approximately 60% of BD patients initially present with depressive symptoms, often resulting in misdiagnosis as major depressive disorder (MDD) for several years []. Diagnostic delays of 6–10 years have been consistently reported [, ], during which patients remain on suboptimal or potentially deleterious treatments, particularly antidepressant monotherapy without mood stabilizers, which can trigger manic episodes and worsen outcomes [, , ]. Multiple research approaches have attempted to identify predictors of BD conversion among MDD patients. Population-based registry studies from Sweden [], Denmark [], Taiwan [], and Korea [] have identified demographic factors, psychiatric comorbidities, and healthcare utilization patterns as candidate predictors, while electronic health record (EHR) studies using traditional regression [] and machine learning [] have achieved moderate predictive accuracy in diverse healthcare systems. Smaller cohorts have also highlighted childhood trauma, substance use, and specific depressive features as potential risk factors [–]. Systematic reviews and meta-analyses have synthesized these heterogeneous findings. Kessing et al. examined 31 longitudinal cohorts of patients with unipolar depression and, in 11 cohorts using survival analyses, including register-based samples, reported decreasing annual conversion rates over time without consistent clinical predictors, largely attributed to methodological differences []. In contrast, Ratheesh et al. analyzed 56 predominantly prospective clinical MDD cohorts and identified three robust predictors of conversion: family history of BD, younger age of onset, and psychotic features []. Salazar de Pablo et al. found that ~15% of children and adolescents with depressive disorders later developed BD, with younger age, recruitment from specialized clinics, and hospitalization associated with increased risk []. However, in the EarlyBipolife study, family history alone had limited prognostic value for conversion to BD [].