| 1. |
- Dickens, Alex M., et al.
(författare)
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Links between central CB1-receptor availability and peripheral endocannabinoids in patients with first episode psychosis
- 2020
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Ingår i: NPJ schizophrenia. - : Nature Partner Journals. - 2334-265X. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- There is an established, link between psychosis and metabolic abnormalities, such as altered glucose metabolism and dyslipidemia, which often precede the initiation of antipsychotic treatment. It is known that obesity-associated metabolic disorders are promoted by activation of specific cannabinoid targets (endocannabinoid system (ECS)). Our recent data suggest that there is a change in the circulating lipidome at the onset of first episode psychosis (FEP). With the aim of characterizing the involvement of the central and peripheral ECSs, and their mutual associations; here, we performed a combined neuroimaging and metabolomic study in patients with FEP and healthy controls (HC). Regional brain cannabinoid receptor type 1 (CB1R) availability was quantified in two, independent samples of patients with FEP (n = 20 and n = 8) and HC (n = 20 and n = 10), by applying three-dimensional positron emission tomography, using two radiotracers, [11C]MePPEP and [18F]FMPEP-d2. Ten endogenous cannabinoids or related metabolites were quantified in serum, drawn from these individuals during the same imaging session. Circulating levels of arachidonic acid and oleoylethanolamide (OEA) were reduced in FEP individuals, but not in those who were predominantly medication free. In HC, there was an inverse association between levels of circulating arachidonoyl glycerol, anandamide, OEA, and palmitoyl ethanolamide, and CB1R availability in the posterior cingulate cortex. This phenomenon was, however, not observed in FEP patients. Our data thus provide evidence of cross talk, and dysregulation between peripheral endocannabinoids and central CB1R availability in FEP.
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| 2. |
- Frank, Elisabeth, et al.
(författare)
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Platform for systems medicine research and diagnostic applications in psychotic disorders - The METSY project
- 2018
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Ingår i: European psychiatry. - : Elsevier. - 0924-9338 .- 1778-3585. ; 50, s. 40-46
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 3. |
- Lamichhane, Santosh, et al.
(författare)
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Association Between Circulating Lipids and Future Weight Gain in Individuals With an At-Risk Mental State and in First-Episode Psychosis
- 2021
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Ingår i: Schizophrenia Bulletin. - : Oxford University Press. - 0586-7614 .- 1745-1701. ; 47:1, s. 160-169
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Tidskriftsartikel (refereegranskat)abstract
- Patients with schizophrenia have a lower than average life span, largely due to the increased prevalence of cardiometabolic comorbidities. There is an unmet public health need to identify individuals with psychotic disorders who have a high risk of rapid weight gain and who are at risk of developing metabolic complications. Here, we applied mass spectrometry-based lipidomics in a prospective study comprising 48 healthy controls (CTR), 44 first-episode psychosis (FEP) patients, and 22 individuals at clinical high risk (CHR) for psychosis, from 2 study centers (Turku, Finland and London, UK). Baseline serum samples were analyzed using lipidomics, and body mass index (BMI) was assessed at baseline and after 12 months. We found that baseline triacylglycerols (TGs) with low double-bond counts and carbon numbers were positively associated with the change in BMI at follow-up. In addition, a molecular signature comprised of 2 TGs (TG[48:0] and TG[45:0]) was predictive of weight gain in individuals with a psychotic disorder, with an area under the receiver operating characteristic curve (AUROC) of 0.74 (95% CI: 0.60-0.85). When independently tested in the CHR group, this molecular signature predicted said weight change with AUROC = 0.73 (95% CI: 0.61-0.83). We conclude that molecular lipids may serve as a predictor of weight gain in psychotic disorders in at-risk individuals and may thus provide a useful marker for identifying individuals who are most prone to developing cardiometabolic comorbidities.
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