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This systematic review evaluates how different antidepressant classes affect insulin resistance, a metabolic complication common in depression. Tricyclic antidepressants (nortriptyline, amitriptyline, imipramine) worsen insulin sensitivity, while SSRIs and SNRIs appear metabolically neutral; bupropion and agomelatine show potential metabolic benefits in diabetic patients.
This study tested a machine learning model combining 34 serum and urine biomarkers to objectively diagnose major depressive disorder in 160 patients and 120 controls. The biomarker diagnostic model achieved good internal discrimination (AUC 0.81) but showed moderate performance in internal-external validation (AUC 0.62-0.72), suggesting potential clinical utility pending further validation.
A longitudinal fMRI study tracked 48 patients with major depressive disorder over 8 weeks to identify neural biomarkers of treatment response, finding differential amygdala-supplementary motor area connectivity patterns between those who remitted versus those who did not respond to antidepressants. While baseline connectivity correlated with treatment outcomes and normalized with successful treatment, the findings require replication as they did not survive multiple comparisons correction.
This systematic scoping review synthesized evidence from 46 studies (2014–2024) on associations between hormonal contraceptive use and psychiatric outcomes. Meta-analysis found small but statistically significant increases in depressive symptoms with progestin-only methods (RR=1.24) and inconsistent evidence for anxiety and suicidality, with high heterogeneity across studies highlighting the need for individual risk assessment.
Research demonstrates that using personalized fMRI resting-state scans to target transcranial magnetic stimulation (TMS) increases depression response rates to 80%, compared to 60% with standard scalp-based targeting. The accelerated protocol offers potential faster treatment timelines (one week) for patients with treatment-resistant depression.
