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High S100B Levels Predict Antidepressant Response in Patients With Major Depression Even When Considering
Ricard Navinés1, Giovanni Oriolo1,2, Igor Horrillo3
1Department of Psychiatry and Psychology, Hospital Clinic, Instituto de Investigaciones Biomédicas August Pi i Sunyer (IDIBAPS), Barcelona; Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Barcelona, Spain.
Background:
The relationship between antidepressant response and glial, inflammatory, and metabolic markers is poorly understood in depression. This study assessed the ability of biological markers to predict antidepressant response in major depressive disorder (MDD).
Methods:
We included 31 MDD outpatients treated with escitalopram or sertraline for 8 consecutive weeks. The Montgomery-Åsberg Depression Rating Scale (MADRS) was administered at baseline and at week 4 and 8 of treatment. Concomitantly, blood samples were collected for the determination of serum S100B, C-reactive protein (CRP), and high-density lipoprotein cholesterol (HDL)-C levels. Treatment response was defined as ≥50% improvement in the MADRS score from baseline to either week 4 or 8. Variables associated with treatment response were included in a linear regression model as predictors of treatment response.
Results:
Twenty-seven patients (87%) completed 8 weeks of treatment; 74% and 63% were responders at week 4 and 8, respectively. High S100B and low HDL-C levels at baseline were associated with better treatment response at both time points. Low CRP levels were correlated with better response at week 4. Multivariate analysis showed that high baseline S100B levels and low baseline HDL-C levels were good predictors of treatment response at week 4 (R2 = 0.457, P = .001), while S100B was at week 8 (R2 = 0.239, P = .011). Importantly, baseline S100B and HDL-C levels were not associated with depression severity and did not change over time with clinical improvement.
Conclusions:
Serum S100B levels appear to be a useful biomarker of antidepressant response in MDD even when considering inflammatory and metabolic markers.
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