aceSerum Protein Glycopatterns as Biomarkers for Machine Learning Diagnosis of Major Depressive Disorder
The diagnosis of major depressive disorder (MDD) currently relies on subjective clinical assessment, underscoring the need for objective biomarkers. Glycosylation, a common post-translational modification, is involved in neuroinflammation and immune regulation, both implicated in MDD pathogenesis. This study aimed to identify serum protein glycopatterns as biomarkers for MDD diagnosis and severity stratification. Serum samples from 150 individuals, including healthy volunteers (HV, n = 38), mild-to-moderate MDD…
In a 150-person study, an AI model using blood sugar-protein patterns told healthy people from mild-to-moderate and severe depression with 95.3% accuracy in cross-validation.
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- Peer-reviewedGlycobiology2026-09-21
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Truvace Impact Record TRV-2026-1164, v3: “Serum Protein Glycopatterns as Biomarkers for Machine Learning Diagnosis of Major Depressive Disorder.” Truvace, 2026-11-05. /record/TRV-2026-1164 (accessed on the day you copy it). sha256 a2b655a88d5b69b1…
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