Title: Early metabolic dysfunction and psychosis: Producing a clinically useful metabolic risk calculator (Psy-MetRiC) for use in people presenting with first-episode psychosis
Funder: Department of Health and Social Care

Abstract: Background In the U.K., around 0.8% of the population have chronic psychotic illness (1), with a shortened life-expectancy of around 20 years (2). The most significant contributor to the excess mortality is physical comorbidity including dysglycaemia, which is up to 30% more prevalent than in the general population, even at the first-episode of psychosis (FEP) (3), with an excess yearly societal cost in the U.K. of around 0.7bn (4). Recently, evidence suggests that even after controlling for anthropomorphic and social factors, markers of metabolic dysfunction are 2-3x higher in both young persons prior to the onset of clinical psychosis (5), and in FEP (6, 7), which usually occurs in young people (Aim: To develop and validate a metabolic risk algorithm for young people presenting with FEP (Psy-MetRiC).Objectives 1) To identify and compare metabolic risk algorithms in the general and psychiatric populations, to help inform the development of Psy-MetRiC. 2) To delineate trajectories of metabolic development in childhood and adolescence in people who subsequently develop psychosis using prospective birth cohort data. To examine whether low-grade systemic inflammation mediates and/or moderates the association between abnormal metabolic development and risk of psychosis. 3) To develop and validate a metabolic risk calculator (Psy-MetRiC) for young people presenting with FEP, and to assess its acceptability amongst service users and healthcare workers.Methods I will perform a systematic review of current metabolic risk algorithms that have been developed for the psychiatric and general populations. Then, I will use repeated measures latent class analysis to delineate pathways of metabolic development and dysfunction in those who develop psychosis, using a large birth cohort. The results from these two steps will inform the development of a clinically useful risk calculator for people presenting with FEP, which I will validate using other large birth cohorts. I will assess acceptability by holding focus groups of service users and healthcare workers.Perceived Impacts Psy-MetRiC can be used by clinicians of Early Intervention in Psychosis teams, who look after young people presenting with FEP, to allow individualised treatment considering metabolic risk. This may reduce the known physical comorbidity in psychosis, at the most effective time to do so. A future prospective trial may seek to test this. Secondly, the project will provide a greater understanding of the complex interplay between body and mind in psychosis. The findings may provide impetus for future trials of targeted interventions such as anti-glycaemic or anti-inflammatory medication to the subgroup of patients implicated.

Lay abstract: People with psychosis, who make up around 0.5-0.8% of the U.K. population, are up to 50% more likely to have physical illnesses such as obesity, heart disease and diabetes than the general population, and they die up to 20 years sooner compared with the general population, partly because of physical comorbidity. Whilst the routinely used blood tests for diabetes may not pick up problems in young people presenting for the first time with psychosis (termed first-episode psychosis'), more recent research has demonstrated that more complicated in-depth tests for problems with blood sugars are 2-3x higher than they should be, in those presenting with first-episode psychosis. These tests are known as the most significant early predictors of future physical health problems like obesity and type 2 diabetes, but may be difficult to measure in routine psychiatric clinics.Early signs of metabolic dysfunction are therefore currently going missed, but if doctors were better able to recognise this early metabolic risk, they may be able to act early to prevent life-long, life-shortening physical illnesses such as obesity and type 2 diabetes. They might do this with careful selection of antipsychotics, some of which can cause diabetes/obesity themselves, or by referring to specialist diabetes doctors, and by encouraging a healthy lifestyle.I therefore plan to develop a metabolic risk prediction calculator called Psy-MetRiC' for young people who are experiencing their first-episode of psychosis. It will be designed for use by doctors when they see people first presenting with psychosis. Metabolic risk calculators have been developed for other patient groups and for the general population, but there isn't one for young people with psychosis who, based upon recent research, may have significantly altered metabolic function compared with the general population, and who may be prescribed medication that could further deteriorate their metabolic function, such as antipsychotics. Therefore, there is clear and crucial need for a tailor-made risk prediction calculator for this patient group. I have discussed my proposal at length with the McPin Foundation (a large, national mental-health patient-voice organisation), who have provided strongly positive feedback that this proposal is important, and who have pledged their support to the project. When I finish the project, the validated calculator will be put onto a website, and will be available for use by doctors in their clinics.First, I will rigorously search the literature to see how other metabolic risk calculators have been developed and validated. I will then use a large patient database to go right back and see how metabolic function and dysfunction develops longitudinally in young people who later develop psychosis, using statistical techniques. Using the previously designed calculators as a starting point, as well as the findings from my new analysis of metabolic development, and information gained from focus groups, I will develop the calculator using statistical techniques, and will use data from a large patient database to validate it.Throughout the process, I will hold focus groups to see what people think of Psy-MetRiC. I will include healthcare workers to help ensure the prediction measures I use in the calculator are useful in day-to-day clinical practice, and will also utilise an agreed collaboration with the McPin Foundation where I can learn in more detail the ideas, concerns and expectations of the calculator amongst service-users. I will adapt and revise my work based upon the ideas, concerns and expectations I discover. I will include updates in the McPin Foundation newsletters, and hold dissemination events in the local community. I will write the findings up for peer-reviewed publication, as well as presenting them at departmental, national and international conferences.

Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;2.3 PSYCHOLOGICAL, SOCIAL AND ECONOMIC FACTORS
Health categories: MENTAL HEALTH