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BACKGROUND AND AIMS: Fentanyl is a highly lipophilic mu opioid receptor agonist, increasingly found in heroin and other drug supplies, that is contributing to marked increases in opioid-related overdose and may be complicating treatment of opioid use disorder (OUD). This study aimed to measure the influence of body mass index (BMI) on fentanyl withdrawal and clearance. DESIGN, SETTING, PARTICIPANTS: This secondary analysis, from a 10-day inpatient study on the safety and efficacy of sublingual dexmedetomidine for opioid withdrawal, includes participants with OUD (n = 150) recruited from three sites in New York, New Jersey and Florida, who were maintained on oral morphine (30 mg four times per day) for 5 days before starting study medication. Most participants (n = 118) tested positive for fentanyl on admission to the inpatient unit. MEASUREMENTS: Urine toxicology and opioid withdrawal symptoms [Clinical Opioid Withdrawal Scale (COWS) and Short Opiate Withdrawal Scale (SOWS)] were assessed daily. The present analysis includes data on opioid withdrawal from days 1–5 of stabilization and urine toxicology data from days 1–10. FINDINGS: Fentanyl status at admission was not significantly associated with COWS or SOWS scores after adjusting for sex, site and polysubstance use. Participants classified as overweight or obese (n = 66) had significantly higher odds of testing positive for fentanyl across days 1–10 [odds ratio (OR) = 1.65; P < 0.01] and higher SOWS maximum scores across morphine stabilization (P < 0.05) compared to those with a healthy BMI (n = 68). CONCLUSIONS: Among inpatients with opioid use disorder, fentanyl status does not appear to be statistically significantly associated with Clinical Opioid Withdrawal Scale and Short Opiate Withdrawal Scale mean and maximum scores. High body mass index status (overweight or obese) appears to be an important predictor of slower fentanyl clearance and higher Short Opiate Withdrawal Scale maximum scores across the inpatient period than lower body mass index status.

The human gut microbiota controls factors that relate to human metabolism with a reach far greater than originally expected. Microbial communities and human (or animal) hosts entertain reciprocal exchanges between various inputs that are largely controlled by the host via its genetic make-up, nutrition and lifestyle. The composition of these microbial communities is fundamental to supply metabolic capabilities beyond those encoded in the host genome, and contributes to hormone and cellular signalling that support the dynamic adaptation to changes in food availability, environment and organismal development. Poor functional exchange between the microbial communities and their human host is associated with dysbiosis, metabolic dysfunction and disease. This review examines the biology of the dynamic relationship between the reciprocal metabolic state of the microbiota-host entity in balance with its environment (i.e. in healthy states), the enzymatic and metabolic changes associated with its imbalance in three well-studied diseases states such as obesity, diabetes and atherosclerosis, and the effects of bariatric surgery and exercise.