Title : Plasma Olink proteomics and machine learning identifies DTD1 as a novel predictive and diagnostic inflammatory marker for treatment resistant schizophrenia
Abstract:
Treatment resistant Schizophrenia (TRS) affects approximately 30% of patients with Schizophrenia often results in increase in relapses, functional impairment, and lowers quality of life. Convergent findings show that patients with TRS suffer from pathogenetically “non-dopamine” Schizophrenia, in the development of which neuroinflammation is considered to play a significant role. In this study, we recruited a well-characterized study population of 50 schizophrenia and control subjects, which includes 30 TRS subjects (age 34 ± 10.73 years), and 20 age matching controls. The Olink platform detects biomarkers for various conditions, we utilized Olink to identify TRS-associated biomarkers. To address this, we conducted Olink-based proteomics on the blood plasma of 50 Qatari subjects, focusing on "inflammation" in TRS. Our findings revealed 61 differentially expressed proteins between TRS and healthy controls, of which 54 proteins were significantly upregulated and 6 proteins were significantly downregulated. We applied machine learning model MUVR algorithm on the normalized protein expression (NPX) dataset, and we found 6 proteins that could be a potential biomarker for TRS with an area under the curve (AUC) = 0.951 using random forest. Gene Ontology (GO) analysis of the top differentially expressed proteins (TopDE) and weighted gene co-expression analysis (WGCNA) revealed these proteins are involved in pathways associated with postsynaptic regulation and receptor endocytosis.
Audience Take Away Notes:
- This study will help the researchers to understand the pathology of treatment resistant schizophrenia, to understand the pathways that are more severely affected in TRS patients that retards the effects of any drugs except Clozapine.
