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In this proposal, the investigators aim to explore the clinical subtypes and biological markers to personalize the use of antidepressants in MDD. By stratifying the subjects with (versus without) remission and treatment response, the biological markers are expected to have important prediction effects in future clinical practice.
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In this proposal, through the integration of genome, transcriptome, protein, metabolic group, microbial group and immune cell subtype of multidimensional omics data to construct the curative effect of forecast model.The investigators aim to explore the clinical subtypes and biological markers to personalize the use of antidepressants in MDD. By stratifying the subjects with (versus without) remission and treatment response, the biological markers are expected to have important prediction effects in future clinical practice.Ultimate aim is to solve the depression medication selection dilemma of "trial and error", reduce medical costs, improving depression treatment experience.
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300 participants in 2 patient groups
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huafang Li, Phd
Data sourced from clinicaltrials.gov
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