Journal Digest

Combining data from demographic information with data from neuropsychological and neuroimaging tests could help to better predict adolescents at risk of initiating alcohol use by age 18 than can be done with demographic information alone, according to a study published in AJP Advance.

The study involved 137 substance-naïve adolescents aged 12 to 14. All participants received neuropsychological testing at baseline to evaluate the neurocognitive function; structural magnetic resonance imaging (sMRI) and functional magnetic resonance imaging (fMRI) were used to assess brain structure. To measure substance use, the Customary Drinking and Drug Use Record was administered to patients at the start of the study and again every six months by telephone interview until the end of the trial.

By age 18, 70 adolescents (51 percent) initiated moderate to heavy alcohol use and 67 remained nonusers. The combined data model was found to be 74 percent accurate in predicting such outcomes compared with an accuracy rate of 62 percent in the demographic model.

The study also identified 34 predictors that contributed to alcohol use by age 18, including being male, higher socioeconomic status, early dating, more externalizing behaviors, worse executive functioning, thinner cortices, and less brain activation in diffusely distributed regions of the brain.

“The results provide evidence that multimodal neuroimaging data, as well as neuropsychological testing, can be used to generate predictions of future behaviors with significantly better accuracy than demographic information alone,” the authors wrote. “Understanding neurocognitive factors that predate substance use initiation is crucial to specifying the consequences of substance use on brain development, as well as identifying at-risk youth and potential targets of preventive efforts.”

A primate study published in the Proceedings of the National Academy of Science suggests a novel compound that targets two types of pain receptors may offer relief without the risk of dependency.

Rhesus monkeys administered BU08028, a ligand with mixed mu opioid peptide/nociception-orphanin FQ peptide receptor activity (MOP/NOP), experienced relief from a “noxious stimulus” for up to 48 hours. Doses of the compound 10 times to 30 times higher than that necessary for pain relief did not cause respiratory depression or adverse cardiovascular events—side effects that can typically lead to overdose death when opioids are misused.

Additional analysis involving drug self-administration suggested that the animals found BU08028 to be less rewarding than cocaine and other opioid agonists such as remifentanil and buprenorphine.

“To our knowledge, the present study provides the first functional evidence in nonhuman primates that BU08028 with mixed MOP/NOP agonist activities is an effective and safe analgesic without apparent abuse liability or other opioid-associated side effects,” wrote the study authors from Wake Forest University School of Medicine. “Because monkey models provide the most phylogenetically appropriate evaluation of opioid receptor functions and drug effects, these findings provide a translational bridge for such ligands as effective analgesics without safety and abuse liability concerns.”

There is limited research on how to best match medically complex patients who have serious mental illness with the right treatments. A study published in Psychiatric Services in Advance describes how consideration of psychosocial variables such as a patient’s social support, self-efficacy, and attitude regarding possible treatment outcomes could help to guide care for patients with serious mental illness and diabetes.

Researchers from the Case Western University School of Medicine analyzed baseline data from 200 individuals with serious mental illness (including schizophrenia, schizoaffective disorder, bipolar disorder, or major depression) and comorbid diabetes involved in a study comparing a self-management intervention versus treatment as usual. As part of the trial, participants were asked questions about their symptoms as well as their perception of social support, perception of their ability to manage their conditions, and outcome expectancy related to treatment.

The analysis revealed two conceptually distinct subgroups of patients within the study. Patients with the most severe depression had “less confidence that they could manage both their psychiatric illness and diabetes, had lower expectations for treatment, and had lower perceived social support. This group scored significantly worse on measures of psychiatric symptom severity, general functioning, and diabetes control compared with the other group,” according to the authors.

“Consideration of all of these factors can personalize care for specific challenges and strengths among patients with comorbid serious mental illness and diabetes and may inform treatment approaches that can advance care for this vulnerable group of individuals,” the researchers concluded. ■