# Deciphering the molecular tapestry of schizophrenia: integrating transcriptomics, neuroimaging, and clinical data for precision medicine

## TL;DR

This study combines blood gene data, brain imaging, and clinical symptoms to uncover molecular patterns in schizophrenia, offering new insights for precision medicine.

## Contribution

The study identifies shared genes linking brain function and clinical symptoms in schizophrenia through a multi-omics approach.

## Key findings

- 994 differentially expressed genes were identified, mostly downregulated, with enrichment in neuronal development and inflammation pathways.
- Six genes (GRK2, KLF3, TAOK2, ARFGAP45, AP1M1, GPAT2) were found to link brain function and clinical symptoms in schizophrenia.
- A multi-omics strategy revealed cross-modal relationships between gene expression, neuroimaging, and clinical features.

## Abstract

This study employed a multi-omics approach to investigate the molecular and functional underpinnings of schizophrenia by integrating blood transcriptomic profiles, neuroimaging-derived brain phenotypes, and clinical symptomatology. RNA sequencing of blood samples from 43 patients with schizophrenia and 60 healthy controls identified 994 differentially expressed genes (DEGs), the vast majority of which were downregulated (n = 921, |FC| > 1.5, P < 0.05), with enrichment in pathways related to neuronal development and inflammation. Concurrent neuroimaging analyses revealed altered functional activation in key brain regions, including the prefrontal and anterior cingulate cortices. A Partial Least Squares correlation analysis demonstrated significant cross-modal relationships among gene expression, neuroimaging patterns, and clinical presentation. Furthermore, we identified six genes—GRK2, KLF3, TAOK2, ARFGAP45, AP1M1, and GPAT2—that were shared across gene sets associated with both brain function and clinical symptoms, suggesting a common transcriptional basis for these features of schizophrenia. Collectively, these findings provide novel insights into the integrated molecular and functional changes in schizophrenia, highlighting the value of a comprehensive multi-omics strategy to decipher its pathophysiology and potentially inform improved diagnostic and therapeutic strategies.