Abstract
Currently, the clinical diagnosis of schizophrenia relies solely on self-reporting and clinical interview, and likely comprises heterogeneous biological subsets. Such subsets may be defined by an underlying biology leading to solid biomarkers. A transgenic rat model modestly overexpressing the full-length, non-mutant Disrupted-in-Schizophrenia 1 (DISC1) protein (tgDISC1 rat) was generated that defines such a subset, inspired by our previous identification of insoluble DISC1 protein in post mortem brains from patients with chronic mental illness. Besides specific phenotypes such as DISC1protein pathology, abnormal dopamine homeostasis, and changes in neuroanatomy and behavior, this animal model also shows subtle disturbances in overarching signaling pathways relevant for schizophrenia. In a reverse-translational approach, assuming that both the animal model and a patient subset share common disturbed signaling pathways, we identified differentially expressed transcripts from peripheral blood mononuclear cells of tgDISC1 rats that revealed an interconnected set of dysregulated genes, led by decreased expression of regulator of G-protein signaling 1 (RGS1), chemokine (C-C) ligand 4 (CCL4), and other immune-related transcripts enriched in T-cell and macrophage signaling and converging in one module after weighted gene correlation network analysis. Testing expression of this gene network in two independent cohorts of patients with schizophrenia versus healthy controls (n = 16/50 and n = 54/45) demonstrated similar expression changes. The two top markers RGS1 and CCL4 defined a subset of 27% of patients with 97% specificity. Thus, analogous aberrant signaling pathways can be identified by a blood test in an animal model and a corresponding schizophrenia patient subset, suggesting that in this animal model tailored pharmacotherapies for this patient subset could be achieved.
Dokumententyp: | Zeitschriftenartikel |
---|---|
Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
ISSN: | 2158-3188 |
Sprache: | Englisch |
Dokumenten ID: | 79919 |
Datum der Veröffentlichung auf Open Access LMU: | 15. Dez. 2021, 14:50 |
Letzte Änderungen: | 15. Dez. 2021, 14:50 |