Patients with severe mental illness have increased mortality, often linked to cardio-metabolic disease. Non-alcoholic fatty liver disease (NAFLD) incidence is higher in patients with schizophrenia and is exacerbated with antipsychotic treatment. NAFLD is associated with obesity and insulin resistance, both of which are induced by several antipsychotic medications. NAFLD is considered an independent risk factor for cardiovascular disease, the leading cause of death for patients with severe mental illness. Although the clinical literature clearly defines increased risk of NAFLD with antipsychotic therapy, the underlying mechanisms are not understood. Given the complexity of the disorder as well as the complex pharmacology associated with atypical antipsychotic (AA) medications, we chose to use a proteomic approach in healthy mice treated with a low dose of risperidone (RIS) or olanzapine (OLAN) for 28 days to determine effects on development of NAFLD and to identify pathways impacted by AA medications, while removing confounding intrinsic effects of mental illness. Both AA drugs caused development of steatosis in comparison with vehicle controls (p < 0.01) and affected multiple pathways relating to energy metabolism, NAFLD, and immune function. AA-associated alteration in autonomic function appears to be a unifying theme in the regulation of hepatic pathology.

Research examining homelessness in rural areas has been sparse. The current study aims to expand conceptions of rural homelessness by mapping community-level risk factors related to housing insecurity. Geographic information systems (GIS) techniques were used to map the distribution of select community-level risk indicators in the State of Maine. Three methodological choices related to this process are demonstrated: (1) selection and distribution of housing insecurity risk indicators; (2) use of location quotients; and (3) use of spatial lags. After examining and mapping selected risk factors against the location of homeless service supports, four areas in Maine were identified as communities of concern for housing insecurity. Better understanding the extent and location of areas of high need that are resource poor can help service and funding agencies to plan for the more efficient and effective distribution of homeless prevention and mitigation services. Implications for research in rural areas are discussed.

ObjectivesPsychotic-spectrum disorders emerge during adolescence and early adulthood, which corresponds with the peak period for substance use initiation. Clinical and epidemiological data provide support that substance use is associated with psychotic symptom onset and severity. Experience-sampling methodology (ESM) data may provide additional insight into dynamic associations between substance use and psychotic symptoms. This is one of the first efforts to characterize substance use frequency and dynamic associations with psychotic symptoms and negative affect from ESM data in both clinical high risk (CHR) and early psychosis (EP) individuals.MethodsUsing ESM, 33 individuals, including 17 with CHR and 16 EP (age range: 15–24), provided information on substance use, negative affect, and psychotic symptoms 6 times a day across a 21-day data collection window. Psychotic symptoms and negative affect included multi-item variables rated on a seven-point Likert Scale. Participants reported recent substance use for 4 drug classes (nicotine, cannabis, depressants, stimulants) via a yes/no item. Descriptive information included data on substance use frequency, and momentary negative affect and psychotic symptoms. Exploratory analyses included multi-level and person-level dynamic structural equation models, which assessed contemporaneous and lagged associations between substance use and symptoms.ResultsTwenty-seven individuals (82%) reported recurrent substance use including stimulants (n = 12, 46%), nicotine (n = 9, 27%), cannabis (n = 6, 18%), and depressants (n = 4, 12%). Individuals with any recurrent substance use indicated usage at 47.7% of answered prompts; stimulants at 23.6%; nicotine at 74.2%; cannabis at 39.1%; and depressants at 20.1%. A multi-level dynamic structural equation model reflected that substance use (any class) was associated with lagged negative affect (β = −0.02, CI: −0.06, &lt; -0.00) but no significant contemporaneous or lagged associations between substance use and psychotic symptoms. Person-level models suggest potentially meaningful inter-individual variability.ConclusionsCHR and EP individuals use a range of substances that may both reflect and influence other experiences in daily life experiences. Data reflected moderate to high rates of recurrent substance use with more consistent use within nicotine and cannabis classes. ESM data have the potential to increase our understanding of the dynamic relationships between substance use and symptoms and to inform treatment for individuals in early course psychosis.

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