Proteomic Analysis of Plasma Markers in Patients Maintained on Antipsychotics
Comparison to Patients Off Antipsychotics and Normal Controls
Bibliographic Data
| ID | 15528017 |
|---|---|
| Authors | Rudolf Engelke (0000-0001-6773-0655, Weill Cornell Medical College in Qatar), Sami Ouanes (0000-0003-0867-060X, Hamad Medical Corporation), Suhaila Ghuloum (0000-0002-1384-4179, Hamad Medical Corporation), Rifka Chamali (Weill Cornell Medical College in Qatar), Nancy Kiwan (0000-0002-8163-6451, Weill Cornell Medical College in Qatar), Hina Sarwath (Weill Cornell Medical College in Qatar), Frank Schmidt (0000-0002-8316-7601, Weill Cornell Medical College in Qatar), Karsten Suhre (0000-0001-9638-3912, Weill Cornell Medical College in Qatar), Hassen Al-Amin (0000-0001-6358-1541, Weill Cornell Medical College in Qatar, corresponding author) |
| Year | 2022 |
| Volume | 13 |
| Publication date | 2022-04-25 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Psychiatry (JOURNAL) |
| Journal identifiers | ISSN: 1664-0640 • E-ISSN: 1664-0640 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fpsyt.2022.809071 |
| OpenAlex | W4224319523 |
| Language | EN |
| References cited | 59 |
Background Schizophrenia (SZ) and bipolar disorder (BD) share many features: overlap in mood and psychotic symptoms, common genetic predisposition, treatment with antipsychotics (APs), and similar metabolic comorbidities. The pathophysiology of both is still not well defined, and no biomarkers can be used clinically for diagnosis and management. This study aimed to assess the plasma proteomics profile of patients with SZ and BD maintained on APs compared to those who had been off APs for 6 months and to healthy controls (HCs). Methods We analyzed the data using functional enrichment, random forest modeling to identify potential biomarkers, and multivariate regression for the associations with metabolic abnormalities. Results We identified several proteins known to play roles in the differentiation of the nervous system like NTRK2, CNTN1, ROBO2, and PLXNC1, which were downregulated in AP-free SZ and BD patients but were “normalized” in those on APs. Other proteins (like NCAM1 and TNFRSF17) were “normal” in AP-free patients but downregulated in patients on APs, suggesting that these changes are related to medication's effects. We found significant enrichment of proteins involved in neuronal plasticity, mainly in SZ patients on APs. Most of the proteins associated with metabolic abnormalities were more related to APs use than having SZ or BD. The biomarkers identification showed specific and sensitive results for schizophrenia, where two proteins (PRL and MRC2) produced adequate results. Conclusions Our results confirmed the utility of blood samples to identify protein signatures and mechanisms involved in the pathophysiology and treatment of SZ and BD
Bioinformatics · Biology · Biomarker · Bipolar disorder · Gene · Mood · Mood disorders · Mood stabilizer · Pathophysiology · Proteomics · Psychiatry · Psychosis · Schizophrenia (object-oriented programming · Advanced Proteomics Techniques and Applications · Genetic Associations and Epidemiology · Medicine · Metabolism, Diabetes, and Cancer · Genetics · Internal Medicine · Oncology
| Highly cited | No |
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