Precision medicine for psychotic disorders: objective assessment, risk prediction, and pharmacogenomics.

Psychosis occurs inside the brain, but may have external manifestations (peripheral molecular biomarkers, behaviors) that can be objectively and quantitatively measured. Blood biomarkers that track core psychotic manifestations such as hallucinations and delusions could provide a window into the biology of psychosis, as well as help with diagnosis and treatment. We endeavored to identify objective blood gene expression biomarkers for hallucinations and delusions, using a stepwise discovery, prioritization, validation, and testing in independent cohorts design. We were successful in identifying biomarkers that were predictive of high hallucinations and of high delusions states, and of future psychiatric hospitalizations related to them, more so when personalized by gender and diagnosis. Top biomarkers for hallucinations that survived discovery, prioritization, validation and testing include PPP3CB, DLG1, ENPP2, ZEB2, and RTN4. Top biomarkers for delusions include AUTS2, MACROD2, NR4A2, PDE4D, PDP1, and RORA. The top biological pathways uncovered by our work are glutamatergic synapse for hallucinations, as well as Rap1 signaling for delusions. Some of the biomarkers are targets of existing drugs, of potential utility in pharmacogenomics approaches (matching patients to medications, monitoring response to treatment). The top biomarkers gene expression signatures through bioinformatic analyses suggested a prioritization of existing medications such as clozapine and risperidone, as well as of lithium, fluoxetine, valproate, and the nutraceuticals omega-3 fatty acids and magnesium. Finally, we provide an example of how a personalized laboratory report for doctors would look. Overall, our work provides advances for the improved diagnosis and treatment for schizophrenia and other psychotic disorders.

Diabetes mellitus and predisposition to athletic pedal fracture.

The purpose of this project was to study the epidemiology of pedal fractures among diabetic athletes and to determine whether diabetic athletes have a higher prevalence of pedal fractures than athletes from the general population. Questionnaire results were obtained from 120 athletes, 60 with diabetes mellitus and 60 without the disease. Subjects answered questions regarding gender, age, duration of disease (if present), presence of Type I or Type II diabetes, daily activity level, types of physical activity, and the admission or denial of athletically induced pedal fracture, including which bones were affected. Statistical significance was achieved with the following parameters: the presence of diabetes and increased prevalence of fracture (p < 0.025) maleness and diabetes and increased prevalence of fracture (p < 0.05), duration of diabetes greater than 25 years and increased prevalence of fracture (p < 0.005), control subjects greater than 30 years of age and increased prevalence of fracture (p = 0.007), moderate correlation between diabetes and prevalence of multiple fractures (r = 0.55, p < 0.025), and moderate correlation between daily activity level and prevalence of fracture among control subjects (r = 0.73, p < 0.05). The most frequently fractured bone was the fifth metatarsal. Until now the literature available on the topic has been sparse, confusing and inconclusive; the results of this study was enable individuals with diabetes to be informed of the risks of pedal fracture associated with active lifestyles.