2026 ECNP Congress

PS02-2191

Peripheral blood RNA-seq analysis in bipolar and schizophrenia spectrum disorders: modest influence of antipsychotic treatment

Yosra Bejaoui — S. Ghuloum, T. John, G. Thareja, T. Habib, K. Suhre, H. Al-Amin · Weill Cornell Medicine-Qatar, Psychiatry Department, Doha, Qatar

2026 ECNP Congress

Introduction:Schizophrenia spectrum disorder (SSD) and bipolar disorder (BP) are chronic mental health conditions. They present as clinical disturbances in thinking, emotional regulation, and behavior, creating a significant burden on individual health and social life, and leading to premature mortality and morbidity [1]. Antipsychotics (APs) remain the foundation of pharmacological management, yet their contribution to the peripheral transcriptomic alterations repeatedly observed in these patients remains poorly characterized and confounds biomarker discovery. Since brain tissue is inaccessible in living patients, peripheral blood has been widely used as a surrogate tissue for transcriptomic studies to identify biomarkers for mental illness [2].

Aim: In this study, we aimed to (i) characterize peripheral blood transcriptomic signatures of BP and SSD in a Qatar-based cohort; (ii) identify disease-related changes attributed to APs treatment; and (iii) identify shared and disorder-specific molecular pathways and network modules.

Method:We conducted a cross-sectional peripheral blood RNA sequencing (RNA-seq) study of 64 patients with BP and SSD, stratified by APs treatment status (mental disorder without APs [MD] and mental disorder with APs [MD+APs]), and 92 healthy controls (HC). Differential expression was analyzed using DESeq2. Functional enrichment was performed with Metascape. Weighted gene co-expression network analysis (WGCNA) identified disease-associated modules, which were tested for correlation with clinical and metabolic traits. Protein–protein interaction (PPI) network analysis and cross-study comparisons with external BP and SSD transcriptomic datasets were conducted to evaluate reproducibility.

Results:Principal component analysis revealed a separation between unaffected and affected individuals and showed that samples from individuals receiving antipsychotic treatment had greater transcriptional variability than those not on treatment. Patients showed distinct blood transcriptomic profiles compared to controls, with a core set of 1,278 differentially expressed genes shared between individuals with mental illness, both on and off antipsychotics. Direct comparison between MD and MD+APs identified only 4 DEGs (CYRIA, TSIX, FRS2, XIST), indicating a modest transcriptomic effect of APs. Shared DEGs were enriched in immune activation, RNA and protein homeostasis, metabolic regulation, sphingolipid signalling, and insulin pathway processes. WGCNA module M1 was strongly upregulated in patients and showed no correlation with metabolic traits. SSD-specific DEGs were enriched in hexose catabolism, pyruvate and folate metabolism, and telomere maintenance, while BP-specific DEGs clustered around immune and sphingolipid-related metabolic pathways. SPON2 emerged as the single gene consistently differentially expressed across all SSD datasets and two independent external studies, whereas OGT was the only replicated BP gene, highlighting substantial inter-study heterogeneity [3]. Clinically, LDL cholesterol was higher in MD+APs compared with MD; diastolic blood pressure was elevated in both MD and MD+APs vs. HC, and systolic blood pressure was elevated only in MD+APs vs. HC however features, including BMI, waist circumference, fasting glucose, HbA1c, triglycerides, and HDL, showed no significant differences between the MD and MD + APs groups and healthy controls. This may be due to the high prevalence of metabolic syndrome components in our study population.

Conclusion:This is the first peripheral transcriptomic study of BP/SSD in a Qatar-based cohort. We identified a robust disease-associated signature largely independent of APs treatment, while APs exposure contributed only modestly at the transcriptomic.

References

  1. Arias, D., Saxena, S., and Verguet, S. (2022). Quantifying the global burden of mental disorders and their economic value. EClinicalMedicine 54, 101675. doi:10.1016/j.eclinm. 2022.101675
  2. Sullivan, P.F., Fan, C., Perou, C.M., 2006. Evaluating the comparability of gene expression in blood and brain. Am. J. Med. Genet. B 141B (3), 261–268.
  3. Hess, J.L., et al., 2016. Transcriptome-wide mega-analyses reveal joint dysregulation of immunologic genes and transcription regulators in brain and blood in schizophrenia. Schizophr. Res. 176 (2-3), 114–124.