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  • Online Resource  (2)
  • Oxford University Press (OUP)  (2)
  • Delvecchio, Giuseppe  (2)
  • 1
    In: Schizophrenia Bulletin, Oxford University Press (OUP), Vol. 47, No. 4 ( 2021-07-08), p. 1141-1155
    Abstract: For several years, the role of immune system in the pathophysiology of psychosis has been well-recognized, showing differences from the onset to chronic phases. Our study aims to implement a biomarker-based classification model suitable for the clinical management of psychotic patients. A machine learning algorithm was used to classify a cohort of 362 subjects, including 160 first-episode psychosis patients (FEP), 70 patients affected by chronic psychiatric disorders (schizophrenia, bipolar disorder, and major depressive disorder) with psychosis (CRO) and 132 health controls (HC), based on mRNA transcript levels of 56 immune genes. Models distinguished between FEP, CRO, and HC and between the subgroup of drug-free FEP and HC with a mean accuracy of 80.8% and 90.4%, respectively. Interestingly, by using the feature importance method, we identified some immune gene transcripts that contribute most to the classification accuracy, possibly giving new insights on the immunopathogenesis of psychosis. Therefore, our results suggest that our classification model has a high translational potential, which may pave the way for a personalized management of psychosis.
    Type of Medium: Online Resource
    ISSN: 0586-7614 , 1745-1701
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2180196-4
    SSG: 15,3
    Location Call Number Limitation Availability
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  • 2
    In: Schizophrenia Bulletin, Oxford University Press (OUP), Vol. 46, No. Supplement_1 ( 2020-05-18), p. S290-S290
    Abstract: Disrupted communication involving large-scale neural networks is hypothesized to underlie the pathophysiology of schizophrenia, as demonstrated by impaired resting-state functional connectivity (rsFC). Seed-based functional magnetic resonance imaging (fMRI) studies in subjects at increased risk of developing psychosis have begun to identify abnormalities in rsFC, although reported findings remain mixed. The aim of this study was to conduct a meta-analysis of seed-based resting-state fMRI studies to test whether high-risk subjects show rsFC alterations relative to healthy controls within and between the default mode network (DMN), control executive network (CEN), and salience network (SN). Methods A literature search was performed to identify seed-based resting-state fMRI studies comparing subjects with genetic risk factors, psychotic-like experiences, and clinical high-risk for psychosis to healthy controls. Then, coordinates of seed regions were extracted and categorized into networks by their location within a priori templates. Activation likelihood estimate (ALE) analysis examined the reported coordinates for hypo-connectivity and hyper-connectivity with each a priori network. Results The meta-analysis included 15 studies (774 subjects at risk, 628 healthy controls) on clinical high-risk for psychosis, 6 studies (123 subjects at risk, 147 healthy controls) on psychotic-like experiences, and 5 studies (173 subjects at risk, 256 healthy controls) on genetic risk factors of developing psychosis. We found specific patterns of hypo- and hyper-connectivity within and between large-scale networks. Our results showed that subjects with high-risk for psychosis were characterized by hypo-connectivity within the SN and CEN and hyper-connectivity within the DMN and CEN. Network seeds in the DMN, CEN, and SN displayed hyper-connectivity with regions in other networks. The DMN seeds displayed hypo-connectivity with regions in the CEN, while CEN and SN seeds displayed hypo-connectivity with regions in the DMN. Discussion This meta-analysis provides evidence that subjects at risk for psychosis present distinctive abnormalities of hyper- and hypo-connectivity within and between the DMN, CEN and SN, particularly implicating network dys-connectivity as a core deficit underlying the psychopathology of psychosis in the preclinical phase. More studies are needed to investigate whether subjects at risk to develop psychosis present patterns of dysfunction between the rsFC of healthy subjects and that of patients with established psychosis.
    Type of Medium: Online Resource
    ISSN: 0586-7614 , 1745-1701
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2180196-4
    SSG: 15,3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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