Schizophrenia (SCZ) is increasingly recognized as a multi-system disorder characterized by peripheral immunometabolic dysregulation. To investigate system-level blood-brain integration, we analyzed peripheral blood transcriptomics, resting-state fMRI (fALFF), and cognitive data from two cohorts (Discovery: 43 SCZ, 60 HCs; Validation: 41 SCZ, 29 HCs). Seven robust peripheral blood gene co-expression modules associated with SCZ were identified, enriched for immune and metabolic pathways.
These modules showed reproducible disease associations in independent blood cohorts. Widespread alterations in functional coupling between these gene modules and intrinsic brain activity (fALFF) were observed in SCZ, characterized by a network-specific reconfiguration with an inverse pattern of correlation changes between limbic and frontoparietal/default mode networks. This dysregulated coupling pattern was highly reproducible across cohorts.
We further identified putative core disease-associated module-network pairs: a downregulated metabolic module coupled with frontoparietal/default mode regions, and an upregulated ribosomal module coupled with limbic regions. Integration of these multimodal features yielded a proof-of-concept improvement in SCZ diagnostic classification (AUCs: 0.71–0.77 in an independent temporal but local validation cohort). Correlation and mediation analyses suggested that brain functional activity in these coupled regions may mediate the relationship between peripheral gene expression and cognitive impairment.
Collectively, these findings reveal distinct, reproducible dysregulation of peripheral-central functional coupling in SCZ, offering a multi-scale framework for understanding its pathophysiology and highlighting the potential of trans-scale features as candidate biomarkers for diagnosis and mechanistic insight. This is a preview of subscription content, access via your institution Receive 12 print issues and online access Prices may be subject to local taxes which are calculated during checkout Data used in the present study can be accessed upon request from the corresponding authors. The GEO data used in the current study is available at https://www.ncbi.nlm.nih.gov/geo/ (GSE18312, GSE38485, GSE21138, GSE12649, GSE53987).
Other tools and methods used in the analysis are described in the Methods section with references. McCutcheon RA, Pillinger T, Varvari I, Halstead S, Ayinde OO, Crossley NA, et al. Integrate: international guidelines for the algorithmic treatment of schizophrenia.
Lancet Psychiat. 2025;12:384–94. https://doi.org/10.1016/S2215-0366(25)00031-8 McCutcheon RA, Reis MT, Howes OD. Schizophrenia-an overview. Jama Psychiat. 2020;77:201–10. https://doi.org/10.1001/jamapsychiatry.2019.3360 Benjamin K, Chen Q, Jaffe AE, Stolz JM, Collado-Torres L, Huuki-Myers LA, et al.
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