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Platform for systems medicine research and diagnostic applications in psychotic disorders - The METSY project
Biomax Informatics AB, Planegg, Germany.
Biomax Informatics AB, Planegg, Germany.
VTT Technical Research Centre of Finland Ltd., Tampere, Finland.
Steno Diabetes Center Copenhagen, Gentofte, Denmark.
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2018 (English)In: European psychiatry, ISSN 0924-9338, E-ISSN 1778-3585, Vol. 50, p. 40-46Article in journal (Refereed) Published
Abstract [en]

Psychotic disorders are associated with metabolic abnormalities including alterations in glucose and lipid metabolism. A major challenge in the treatment of psychosis is to identify patients with vulnerable metabolic profiles who may be at risk of developing cardiometabolic co-morbidities. It is established that both central and peripheral metabolic organs use lipids to control energy balance and regulate peripheral insulin sensitivity. The endocannabinoid system, implicated in the regulation of glucose and lipid metabolism, has been shown to be dysregulated in psychosis. It is currently unclear how these endocannabinoid abnormalities relate to metabolic changes in psychosis. Here we review recent research in the field of metabolic co-morbidities in psychotic disorders as well as the methods to study them and potential links to the endocannabinoid system. We also describe the bioinformatics platforms developed in the EU project METSY for the investigations of the biological etiology in patients at risk of psychosis and in first episode psychosis patients. The METSY project was established with the aim to identify and evaluate multi-modal peripheral and neuroimaging markers that may be able to predict the onset and prognosis of psychiatric and metabolic symptoms in patients at risk of developing psychosis and first episode psychosis patients. Given the intrinsic complexity and widespread role of lipid metabolism, a systems biology approach which combines molecular, structural and functional neuroimaging methods with detailed metabolic characterisation and multi-variate network analysis is essential in order to identify how lipid dysregulation may contribute to psychotic disorders. A decision support system, integrating clinical, neuropsychological and neuroimaging data, was also developed in order to aid clinical decision making in psychosis. Knowledge of common and specific mechanisms may aid the etiopathogenic understanding of psychotic and metabolic disorders, facilitate early disease detection, aid treatment selection and elucidate new targets for pharmacological treatments.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 50, p. 40-46
Keywords [en]
Bioinformatics, Biomarkers, Decision support systems, Endocannabinoid system, Lipid metabolism, Metabolomics, Psychoses, Schizophrenia
National Category
Psychiatry
Identifiers
URN: urn:nbn:se:oru:diva-64483DOI: 10.1016/j.eurpsy.2017.12.001ISI: 000430263900007PubMedID: 29361398Scopus ID: 2-s2.0-85040608354OAI: oai:DiVA.org:oru-64483DiVA, id: diva2:1177073
Funder
EU, FP7, Seventh Framework Programme, 602478Available from: 2018-01-24 Created: 2018-01-24 Last updated: 2018-08-20Bibliographically approved

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Hyötyläinen, TuuliaOresic, Matej

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