Principal Investigator: Professor Bernie Devlin
Department: University of PittsburghTags: 54406, co-morbidity, genetics/genotyping, mental health, psychosis, risk prediction, SNP
We want to understand why psychiatric disorders and various other diseases, such as metabolic diseases, co-occur. For instance, previous studies have documented that individuals with schizophrenia and other psychotic disorders develop type 2 diabetes mellitus (T2D) more often than individuals without such diagnoses. Because their immediate family members also are at an increased risk to develop T2D than the general public, the cause of T2D could be genetic in nature, made worse by antipsychotic medications taken by people to dampen their symptoms, as well as unhealthy lifestyle choices, such as inactivity or poor diet.
In this study, we propose to estimate the risk for metabolic diseases, like T2D, in psychiatric phenotypes considering both genetic and environmental factors. Furthermore, we will develop a Risk Estimator that considers all of these risk factors. The Risk Estimator will take the form of a score that is generated by examining the unique genetic make-up of each individual who does or does not have metabolic disease. Covariates, such as age, sex, and other metabolic features will be included to adjust the estimate of risk. Additionally, we will identify rare, damaging genetic variants, present in some subjects, that map onto metabolic pathways of interest because these could add further information. Ideally, the Risk Estimator would accurately predict who is at a higher risk of developing metabolic disorders, especially in the context of a psychiatric disorder. If it were sufficiently predictive, this score might prove useful for mitigating effects of metabolic disease by altering the choice psychiatric medications, some of which present greater risk for metabolic disturbance than others; or result in recommendations for lifestyle changes for subjects at high risk for metabolic disease.