Frontiers in psychiatry · 2026
Employment-dependent associations of serum biomarkers with short- and long-term antidepressant treatment outcomes.
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Kim Jae-Min, Kang Hee-Ju, Kim Ju-Wan, Jhon Min, Lee Ju-Yeon, Kim Sung-Wan, Shin Il-Seon
Аннотация
BACKGROUND: This study investigated whether employment status moderates associations between baseline serum biomarkers and antidepressant remission at 12 weeks and 12 months.
METHODS: A prospective cohort of 1086 outpatients diagnosed with depressive disorders received stepwise antidepressant therapy using a naturalistic, flexible treatment protocol. Fourteen serum biomarkers covering immune (hsCRP, TNF-α, IL-1β, IL-6, IL-4, IL-10), metabolic (leptin, ghrelin, total cholesterol), neuroplastic (BDNF), neurotransmitter (serotonin), endocrine (cortisol), and nutritional (folate, homocysteine) domains were analyzed at baseline. Employment-dependent biomarker associations with remission (Hamilton Depression Rating Scale ≤7) at 12 weeks and 12 months were evaluated using logistic regression with biomarker-by-employment interactions and stratified analyses, adjusting for relevant covariates.
RESULTS: Higher serotonin levels significantly predicted 12-week remission exclusively among employed patients, with a significant employment interaction. At 12 months, lower leptin levels predicted remission specifically in employed patients, whereas lower TNF-α and higher BDNF levels predicted remission only in unemployed patients, each demonstrating significant employment interactions.
CONCLUSION: Baseline serum biomarkers showed employment-dependent associations with antidepressant remission outcomes, highlighting serotonin's short-term relevance and leptin, TNF-α, and BDNF as longer-term indicators. Although exploratory, these findings suggest that integrating employment status with biomarker profiles may enhance clinical decision-making by identifying patients who are more or less likely to benefit from treatment across different phases of recovery. Replication in independent cohorts is needed to establish the clinical applicability of such employment-tailored, biomarker-informed strategies.
METHODS: A prospective cohort of 1086 outpatients diagnosed with depressive disorders received stepwise antidepressant therapy using a naturalistic, flexible treatment protocol. Fourteen serum biomarkers covering immune (hsCRP, TNF-α, IL-1β, IL-6, IL-4, IL-10), metabolic (leptin, ghrelin, total cholesterol), neuroplastic (BDNF), neurotransmitter (serotonin), endocrine (cortisol), and nutritional (folate, homocysteine) domains were analyzed at baseline. Employment-dependent biomarker associations with remission (Hamilton Depression Rating Scale ≤7) at 12 weeks and 12 months were evaluated using logistic regression with biomarker-by-employment interactions and stratified analyses, adjusting for relevant covariates.
RESULTS: Higher serotonin levels significantly predicted 12-week remission exclusively among employed patients, with a significant employment interaction. At 12 months, lower leptin levels predicted remission specifically in employed patients, whereas lower TNF-α and higher BDNF levels predicted remission only in unemployed patients, each demonstrating significant employment interactions.
CONCLUSION: Baseline serum biomarkers showed employment-dependent associations with antidepressant remission outcomes, highlighting serotonin's short-term relevance and leptin, TNF-α, and BDNF as longer-term indicators. Although exploratory, these findings suggest that integrating employment status with biomarker profiles may enhance clinical decision-making by identifying patients who are more or less likely to benefit from treatment across different phases of recovery. Replication in independent cohorts is needed to establish the clinical applicability of such employment-tailored, biomarker-informed strategies.