ArticleBMC psychiatry2025
Disrupted genes and pathways in schizophrenia: a robust analysis of the brain and blood.
Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Increased RHOA expression in peripheral blood mononuclear cells of patients with acute schizophrenia.Molecular biology reports · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundSchizophrenia (SCZ) is a neuropsychiatric disorder that is not yet fully understood, characterized by behavioral, emotional, and cognitive dysfunctions. In this study, we analyzed publicly available gene-expression data to identify SCZ-associated genes and pathways, offering deeper insights into its biological basis.
methodsThe data collection aimed to retrieve gene expression databases featuring samples from the brain's prefrontal cortex and blood. After performing exclusion criteria and quality checks, 17 datasets were retrieved from six different sources: Brain biopsy (n = 6), whole blood (n = 2), peripheral blood mononuclear cells (n = 2), leukocytes (n = 1), lymphocytes (n = 1) and isolated neurons (n = 5). We used four brain datasets as the discovery set for the initial analysis. Differentially expressed genes (DEGs) were identified by comparing SCZ patients with controls and were subsequently used in enrichment analysis. Finally, we applied feature selection to pinpoint the most informative DEGs for SCZ and evaluated their accuracy using data from other tissues.
resultsThis analytical approach identified 532 DEGs. Feature selection revealed three genes-HUWE1, PTGDS, and RPL31-that effectively discriminated SCZ from control samples. The 3-gene model's performance was validated in other datasets, presenting accuracy (> 72%) in brain tissue, whole blood, PMBCs and leukocytes. Furthermore, the enrichment analysis revealed a potential linkage with neurodegenerative biological pathways.
conclusionThese insights open new avenues for exploring key genes for SCZ, which can lead to new therapeutic targets or tools for diagnosis, potentially transforming the management of SCZ and enhancing patient care.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.