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Proposed by the EPA section on Neuroimaging -One of the major limitations of current therapeutic management of psychoses is the lack of predictive, personalised medicine tools that could inform clinicians’ as choice of treatment for individual patients, aiming to improve functional outcomes while preventing adverse metabolic side effects (e.g., weight gain, metabolic syndrome, diabetes). In current clinical practice, poor efficacy or adverse side effects of treatments can present months after commencement of treatment. Even if therapy is adjusted, it might already be too late for the patient to fully recover from such comorbidity. Therefore, prompt identification of a patient’s risk profile is essential for selecting an optimal preventative therapeutic strategy. In a personalised medicine approach to disease treatment and prevention of comorbidities, a patient would first undergo a comprehensive screening by a range of diagnostic tools, which would predict the patient’s mental, functional and somatic outcomes given various lines of treatment, and thus help identify the optimal treatment strategy. Recent research using molecular profiling approaches (such as metabolomics) and neuroimaging suggests that such prediction of patient outcomes, even in individuals at clinical high risk for psychosis, may be feasible. The aim of this Symposium is to cover recent advances in the domain of outcome prediction, with specific focus on use of high-dimensional and multi-modal data such as from ‘omics’ and neuroimaging.
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S0026 - Predicting One-year Outcomes in First-episode Psychosis
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The outcome of first-episode psychosis (FEP) varies and may be predicted by several baseline measures. In the Helsinki Early Psychosis Study, young adults with FEP (n=97) from the Helsinki area in Finland were broadly assessed as soon as possible after first psychiatric contact for psychosis. Age- and gender-matched population controls were also assessed (n=62). The participants were followed up via appointments and medical records. We present both published and unpublished results on predictors of 12-month clinical, functional, and metabolic outcomes. More severe cognitive deficits at the beginning of treatment predicted several outcomes such as occupational status and functional level – beyond baseline positive and affective symptom levels, but not when negative symptoms were accounted for. More severe baseline obsessive-compulsive symptoms were predictive of a lower rate of remission, whereas a higher level of anxiety symptoms predicted better functional outcome, when the severity of positive symptoms was adjusted for. Adverse childhood experiences measuring cumulating psychosocial stress did not predict occupational status or functional level when positive and negative symptoms and neurocognition were controlled for, whereas in controls having experienced school bullying was associated with lower functioning. Insulin resistance in early psychosis appeared as an early marker of increased vulnerability to weight gain and abdominal obesity in young adults with FEP. Further, increased waist circumference predicted worsening low-grade inflammation, increasing further the cardiovascular risk. In sum, we have found different types of prognostic markers in FEP. Identifying the individuals at risk of less favorable outcomes could affect treatment choices in FEP.
S0027 - Machine Learning Approaches in the Context of Psychiatric Neuroimaging: Any Impact on Diagnosis and Outcome?
, S0028 - Molecular Lipids in Prediction of Psychosis and the Associated Cardiometabolic Co-morbidities
, ABSTRACT
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Lipid metabolism has been an area of increased interest in psychosis research, not only due to its link to metabolic comorbidities, but also due to its putative role in the pathophysiology of psychosis.
Lipid disturbances are observed already in the period preceding the onset of psychosis. For example, we performed mass spectrometry based lipidomics in a cohort of individuals at clinical high risk for psychosis (the EU-GEI study) and found that the individuals who transitioned to psychosis within a 2-year follow-up period displayed decreased levels of ether phospholipids. This finding may be of direct (patho)physiological relevance, as ether phospholipids (particularly plasmalogens, a major subgroup of ether phospholipids) are highly enriched in the brain, are supplied to the brain by the liver, have many structural and functional roles, and may act as endogenous antioxidants.
Accumulating evidence also suggests that lipid disturbances play a crucial role in the development of metabolic comorbidities associated with psychotic disorders. Our lipidomic studies have shown that psychotic patients who rapidly gain weight during follow-up have elevated triglycerides (TGs) with low double bond count and carbon number at baseline. These TGs are known to be associated with non-alcoholic fatty liver disease (NAFLD) and with increased risk of type 2 diabetes.
In conclusion, although the mechanisms linking dysregulation of lipid metabolism with the pathophysiology of psychosis are currently poorly understood, findings by us and others suggest that metabolic abnormalities are evident in people who are vulnerable to psychosis, and to the associated metabolic comorbidities.
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