Authors
Xiaoyu Tong, Kanhao Zhao, Gregory A Fonzo, Hua Xie, Nancy B Carlisle, Corey J Keller, Desmond J Oathes, Yvette Sheline, Charles B Nemeroff, Madhukar Trivedi, Amit Etkin, Yu Zhang
Published in
Nature. Mental health. Volume 4. Issue 1. Pages 85-101. Epub Dec 12, 2025.
Abstract
Major depressive disorder (MDD) is a prevalent condition that profoundly impairs quality of life across diverse populations. Despite widespread use, current antidepressant and psychotherapeutic treatments exhibit limited efficacy and unsatisfactory response rates. Progress in developing effective therapies is hampered by the insufficiently understood heterogeneity of MDD and its elusive underlying mechanisms. Here, to address these challenges, we develop a novel machine learning framework that identifies structure-function covariation through target-oriented fusion of structural and functional connectivity, which robustly predicts individual-level antidepressant response (sertraline, R 2 = 0.31; placebo, R 2 = 0.22). Validation in an independent escitalopram-medicated MDD cohort confirms the biomarker's generalizability (P = 0.01) and suggests an overlap of psychopharmacological signatures across selective serotonin reuptake inhibitors. Our models highlight the right precuneus as a common key region for both sertraline and placebo responses, with the right middle frontal gyrus and left fusiform gyrus specific to sertraline and the left inferior and middle frontal gyri to placebo. We also find that structural connectivity is more predictive of sertraline response, while functional connectivity better predicts placebo response. The framework further decomposes the overall predictive patterns into three constitutive network constellations (default-mode regulatory, affective and sensory processing), which exhibit distinct generalizable structure-function covariation and treatment-specific association with personality traits and behavioral/cognitive profiles. These findings provide unique insights to the structure-function covariation in patients with MDD, its association to the heterogeneity in antidepressant response and the dissection of the intricate MDD neuropsychopharmacology, paving the way for precision medicine and development of more targeted antidepressant therapeutics. Clinicaltrials.gov registration: Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC), NCT01407094.
PMID:
42460432
Bibliographic data and abstract were imported from PubMed on 16 Jul 2026.
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