Major depressive disorder (MDD) is a common mental health condition characterized by substantial clinical heterogeneity and variability in treatment response. Current diagnosis and treatment selection for MDD mainly rely on clinical assessments, and reliable biological markers that can support diagnosis, predict antidepressant treatment response, guide personalized treatment, and improve understanding of disease mechanisms remain limited.
The goal of this prospective observational cohort study is to develop and optimize multi-omics-based models for MDD diagnosis and antidepressant treatment response prediction using longitudinal clinical characteristics and biological data collected from an independent prospective cohort. The study also aims to evaluate the generalizability and predictive performance of existing multi-omics-based models in this independent cohort of participants aged 14-45 years.
The main questions it aims to answer are:
Can integrated clinical and multi-omics features identify biomarkers and develop predictive models for MDD diagnosis and antidepressant treatment response? Can existing multi-omics-based models for MDD diagnosis and treatment response prediction be replicated and validated in an independent prospective cohort?
Participants with MDD and healthy controls will undergo standardized clinical assessments, longitudinal follow-up, and biological sample collection for multi-omics profiling. Clinical and multi-omics data will be integrated to identify biomarkers, develop and validate predictive models for MDD diagnosis, antidepressant treatment response, and long-term outcomes, and explore biological pathways and potential therapeutic targets associated with MDD.
The study is expected to improve understanding of the biological heterogeneity of MDD and contribute to the development of objective approaches for diagnosis, treatment response prediction, personalized care, and future therapeutic discovery.
Participants aged 14-45 years.
Participants are able to understand the study procedures and provide written informed consent. For participants younger than 18 years, both the participant and their legal guardian must provide consent.
Meet DSM-5 criteria for major depressive disorder (single or recurrent episode).
Have a baseline Montgomery-Åsberg Depression Rating Scale (MADRS) score ≥24 and 17-item Hamilton Depression Rating Scale (HAMD-17) score ≥18.
Current or lifetime diagnosis of other major psychiatric disorders, including schizophrenia spectrum disorders, schizoaffective disorder, or bipolar disorder.
Substance use disorder within 12 months prior to screening.
Depression secondary to medical or neurological conditions.
Regular antidepressant treatment within 2 weeks prior to enrollment.
This study enrolls participants aged 14-45 years from outpatient and inpatient psychiatric settings, comprising two cohorts: participants meeting DSM-5 criteria for major depressive disorder (MDD) and demographically matched healthy controls (HCs) without current or lifetime major psychiatric disorders. MDD participants are recruited during an active depressive episode with baseline Montgomery-Åsberg Depression Rating Scale (MADRS) score ≥24 and 17-item Hamilton Depression Rating Scale (HAMD-17) score ≥18. HC participants are frequency-matched to the MDD cohort by age and sex distribution.
Cohort
Prospective
Not listed
Change in Montgomery-Åsberg Depression Rating Scale (MADRS) Total Score From Baseline to Week 8
The primary outcome is the change in Montgomery-Åsberg Depression Rating Scale (MADRS) total score from baseline to Week 8 after antidepressant treatment. The MADRS is a clinician-rated scale assessing depressive symptom severity. The total score ranges from 0 to 60, with higher scores indicating greater depressive symptom severity (worse outcome). Change in MADRS total score from baseline to Week 8 will be assessed as the primary clinical endpoint.
Antidepressant Treatment Response Rate Based on Montgomery-Åsberg Depression Rating Scale (MADRS) at Week 8
Treatment response is defined as a ≥50% reduction from baseline in Montgomery-Åsberg Depression Rating Scale (MADRS) total score at Week 8. The MADRS score ranges from 0 to 60, with higher scores indicating greater depressive symptom severity (worse outcome). The outcome measure is the percentage of participants achieving treatment response.
17-item Hamilton Depression Rating Scale (HAMD-17)-Defined Treatment Response at Week 8
Treatment response is defined as a ≥50% reduction from baseline in 17-item Hamilton Depression Rating Scale (HAMD-17) total score at Week 8. The HAMD-17 total score ranges from 0 to 52, with higher scores indicating greater depressive symptom severity (worse outcome). The outcome measure is the percentage of participants achieving treatment response.
Montgomery-Åsberg Depression Rating Scale (MADRS)-Defined Antidepressant Treatment Remission at Week 8
Remission is defined as a total score ≤10 on the Montgomery-Åsberg Depression Rating Scale (MADRS) at Week 8. The MADRS score ranges from 0 to 60, with higher scores indicating greater depressive symptom severity (worse outcome). The outcome measure is the percentage of participants achieving remission.
17-item Hamilton Depression Rating Scale (HAMD-17)-Defined Antidepressant Treatment Remission at Week 8
Remission is defined as a total score ≤7 on the 17-item Hamilton Depression Rating Scale (HAMD-17) at Week 8. The HAMD-17 score ranges from 0 to 52, with higher scores indicating greater depressive symptom severity (worse outcome). The outcome measure is the percentage of participants achieving remission.
Area Under the Receiver Operating Characteristic Curve (AUROC) of Multi-Omics-Based Models for Discriminating Major Depressive Disorder From Healthy Controls
A multivariable model integrating clinical characteristics and multi-omics data, including immune profiling (CyTOF and cytokine profiling), genomics, epigenomics, bulk transcriptomics, single-cell transcriptomics, proteomics, metabolomics, and microbiome profiling, will be developed to discriminate participants with major depressive disorder from healthy controls. Model discrimination performance will be primarily assessed by the area under the receiver operating characteristic curve (AUROC). Sensitivity, specificity, and predictive accuracy will be reported as supportive metrics.
Area Under the Receiver Operating Characteristic Curve (AUROC) of Multi-Omics-Based Models for Predicting MADRS-Defined Antidepressant Treatment Response at Week 8
A multivariable model integrating baseline clinical characteristics and multi-omics data, including immune profiling (CyTOF and cytokine profiling), genomics, epigenomics, bulk transcriptomics, single-cell transcriptomics, proteomics, metabolomics, and microbiome profiling, will be developed to predict antidepressant treatment response at Week 8. Treatment response will be defined as a ≥50% reduction from baseline in Montgomery-Åsberg Depression Rating Scale (MADRS) total score at Week 8. Model predictive performance will be primarily assessed by the area under the receiver operating characteristic curve (AUROC), with internal validation performed using bootstrap resampling. Calibration, sensitivity, specificity, and predictive accuracy will be reported as supportive metrics.
Area Under the Receiver Operating Characteristic Curve (AUROC) of Multi-Omics-Based Models Integrating Baseline Profiles and Week 4 Molecular Changes for Predicting MADRS-Defined Antidepressant Treatment Response at Week 8
A longitudinal multivariable model integrating baseline clinical characteristics, baseline multi-omics profiles, and multi-omics changes from baseline to Week 4 will be developed to predict MADRS-defined antidepressant treatment response at Week 8. Treatment response will be defined as a ≥50% reduction from baseline in Montgomery-Åsberg Depression Rating Scale (MADRS) total score at Week 8. Multi-omics data will include immune profiling (CyTOF and cytokine profiling), genomics, epigenomics, bulk transcriptomics, single-cell transcriptomics, proteomics, metabolomics, and microbiome profiling. Model predictive performance will be primarily assessed by the area under the receiver operating characteristic curve (AUROC), with internal validation performed using bootstrap resampling. Calibration, sensitivity, specificity, and predictive accuracy will be reported as supportive metrics.
Number of Significantly Altered Multi-Omics Features From Baseline to Week 8 of Antidepressant Treatment
Longitudinal changes in multi-omics profiles from baseline to Week 8 will be analyzed to identify molecular features significantly altered following antidepressant treatment. Multi-omics analyses will include immune profiling (CyTOF and cytokine profiling), genomics, epigenomics, bulk transcriptomics, single-cell transcriptomics, proteomics, metabolomics, and microbiome profiling. Statistically significant features will be identified based on predefined statistical thresholds, and the number of significantly altered features will be reported.
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Shanghai Mental Health Center
Lead sponsor
LinGang Laboratory
Collaborator
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