Neuroimmune transcriptome changes in patient brains of psychiatric and neurological disorders.
Level 4 - case-series / case-control
Cross-sectional postmortem case-control transcriptomic study across multiple disease cohorts
PubMed 36424395 · doi:10.1038/s41380-022-01854-7
What was done
Curated 1,275 immune-related genes (IRGs) and analyzed their expression profiles across microarray and RNA-sequencing datasets from 2,467 postmortem human brains. The dataset comprised neurotypical controls and patients diagnosed with six brain disorders: schizophrenia, bipolar disorder, autism spectrum disorder, major depressive disorder, Alzheimer's disease, and Parkinson's disease. A core set of 865 IRGs present across all datasets was evaluated for differential expression, innate immune pathways, co-expression networks with neuronal systems, tissue/sex/cell-type specificity, and overlap with genome-wide association study (GWAS) risk loci.
What was found
More than 60% of the analyzed IRGs exhibited significantly altered expression in at least one of the six disorders. Differentially expressed IRGs shared across conditions were predominantly enriched for innate immunity functions. Co-expression network analyses demonstrated functional interactions between neuroimmune and neuronal transcript systems across disorders. Only a small fraction of the differentially expressed immune genes overlapped with established GWAS risk variants. Specific effect sizes, fold changes, and p-values were not provided in the abstract.
Why it matters
This study provides a broad cross-disorder comparison of neuroimmune dysregulation in the human brain, showing that innate immune pathway alterations are widespread across both psychiatric and neurodegenerative illnesses despite limited direct genetic liability in the same genes.
Limits
Analysis relies on postmortem brain tissue, which is inherently subject to confounding by cause of death, agonal state, postmortem interval, and lifetime medication exposure. Transcriptomic changes reflect cross-sectional correlations rather than directional causality. The abstract does not report specific quantitative effect sizes or dataset-specific sample breakdowns.
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