The way to her heart? Response to romantic cues is dependent on hunger state and dieting history: An fMRI pilot study

A randomized, double-blind, placebo-controlled study of a GHSR blocker in people with alcohol use disorder

BACKGROUNDStudies have demonstrated the role of ghrelin in alcohol-related behaviors and consumption. Blockade of the growth hormone secretagogue receptor (GHSR), which is the ghrelin receptor, has been shown to decrease alcohol drinking and reward-related behaviors across several animal models. We previously conducted a human study testing a GHSR inverse agonist/competitive antagonist, PF-5190457, in individuals who are heavy drinkers and showed its safety when coadministered with alcohol. Here, we conducted a phase IIa experimental medicine study in patients with alcohol use disorder (AUD) to investigate the effects of PF-5190457 on alcohol- and food-related outcomes.METHODSForty-two individuals with AUD (n = 29 completers) participated in a randomized, double-blind, placebo-controlled study where they received PF-5190457 100mg b.i.d. (or placebo) in 2 counterbalanced, within-subject stages. Participants completed an alcohol cue-reactivity (CR) experiment in a bar-like laboratory and a virtual food choice experiment in a cafeteria-like virtual reality (VR) environment. A subset of participants (n = 12) performed a CR task during a brain functional MRI (fMRI) experiment.RESULTSPF-5190457 did not reduce cue-elicited alcohol craving. PF-5190457 reduced virtual calories selected (P = 0.04) in the VR environment. PF-5190457 did not influence neural activation during CR task in the fMRI experiment.CONCLUSIONThis study provides human evidence of the role of GHSR blockade in behaviors related to food selection and highlights the need for future investigations into targeting the ghrelin system in AUD.TRIAL REGISTRATIONClinicalTrials.gov (accession no. NCT02707055).FUNDINGNIDA and NIAAA ZIA-DA000635; National Center for Advancing Translational Sciences UH2/UH3-TR000963.

Double jeopardy: Comorbid obesity and cigarette smoking are linked to neurobiological alterations in inhibitory control during smoking cue exposure

Obesity and cigarette smoking are two of the leading preventable causes of death in the United States. Research suggests that overlapping pathophysiology may contribute to obesity and nicotine use disorder (NUD), yet no studies have investigated the effect of obesity on neural response to reward stimuli in NUD. This study used arterial spin-labeled perfusion functional magnetic resonance imaging (fMRI) to examine neural responses during exposure to smoking versus nonsmoking cues in 79 treatment-seeking participants with NUD, 26 with normal weight, 28 with overweight, and 25 with obesity. Given that deficits in behavioral inhibitory control have been associated with both obesity and NUD, participants completed an affect-congruent Go/NoGo task to assess the effect of body mass index (BMI) on this construct in NUD. Analyses revealed that BMI was negatively associated with activation in the right dorsolateral prefrontal cortex (dlPFC) in response to smoking cues, with significantly reduced response in smokers with overweight and smokers with obesity compared with normal-weight smokers. In addition, greater commission errors on the Go/NoGo task were correlated with reduced neural response to smoking cues in the right dlPFC only among those with obesity. Together, these findings provide evidence that obesity in treatment-seeking NUDs is related to neurobiological alterations in inhibitory control over cue-potentiated behaviors, suggesting that smoking cessation may be more difficult in individuals with comorbid NUD and obesity than in those without, requiring treatment strategies tailored to meet their unique needs.

The effect of preprocessing pipelines in subject classification and detection of abnormal resting state functional network connectivity using group ICA

Resting state functional network connectivity (rsFNC) derived from functional magnetic resonance (fMRI) imaging is emerging as a possible biomarker to identify several brain disorders. Recently it has been pointed out that methods used to preprocess head motion variance might not fully remove all unwanted effects in the data. Proposed processing pipelines locate the treatment of head motion effects either close to the beginning or as one of the final steps. In this work, we assess several preprocessing pipelines applied in group independent component analysis (gICA) methods to study the rsFNC of the brain. The evaluation method utilizes patient/control classification performance based on linear support vector machines and leave-one-out cross validation. In addition, we explored group tests and correlation with severity measures in the patient population. We also tested the effect of removing high frequencies via filtering. Two real data cohorts were used: one consisting of 48 mTBI and one composed of 21 smokers, both with their corresponding matched controls. A simulation procedure was designed to test the classification power of each pipeline. Results show that data preprocessing can change the classification performance. In real data, regressing motion variance before gICA produced clearer group differences and stronger correlation with nicotine dependence.