Notes

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Most individuals with obesity or overweight have difficulty maintaining weight loss. The weight-reduced state induces changes in many physiological processes that appear to drive weight regain. Here, we review the use of cell biology, genetics, and imaging techniques that are being used to begin understanding why weight regain is the normal response to dieting. As with obesity itself, weight regain has both genetic and environmental drivers. Genetic drivers for "thinness" and "obesity" largely overlap, but there is evidence for specific genetic loci that are different for each of these weight states. There is only limited information regarding the genetics of weight regain. Currently, most genetic loci related to weight point to the central nervous system as the organ responsible for determining the weight set point. Neuroimaging tools have proved useful in studying the contribution of the central nervous system to the weight-reduced state in humans. Neuroimaging technologies fall into three broad categories functional, connectivity, and structural neuroimaging. Connectivity and structural imaging techniques offer unique opportunities for testing mechanistic hypotheses about changes in brain function or tissue structure in the weight-reduced state.Preventing regain of lost weight is the most difficult challenge in the treatment of obesity. The National Institute of Diabetes and Digestive and Kidney Diseases convened a workshop, "The Physiology of the Weight-Reduced State," on June 3 to 4, 2019, in order to explore the physiologic mechanisms of appetitive and metabolic adaptation that take place in the weight-reduced state and counter an individual's efforts to maintain reduced weight following weight loss.Mounting evidence suggests that obesity, parameters of metabolic syndrome, and asthma are significantly associated. Interestingly, these conditions are also associated with microbiome dysbiosis, notably in the airway microbiome for patients with asthma and in the gut microbiome for patients with obesity and/or metabolic syndrome. Considering that improvements in asthma control, lung function, and airway hyperresponsiveness are often reported after bariatric surgery, this review investigated the potential role of bacterial gut and airway microbiome changes after bariatric surgery in ameliorating asthma symptoms. Rapid and persistent gut microbiota alterations were reported following surgery, some of which can be sustained for years. The gut microbiome is thought to modulate airway cellular responses via short-chain fatty acids and inflammatory mediators, such that increased propionate and butyrate levels following surgery may aid in reducing asthma symptoms. In addition, increased prevalence of Akkermansia muciniphila after Roux-en-Y gastric bypass and sleeve gastrectomy may confer protection against airway hyperreactivity and inflammation. Metabolic syndrome parameters also improved following bariatric surgery, and whether weight-loss-independent metabolic changes affect airway processes and asthma pathobiology merits further research. Fulfilling knowledge gaps outlined in this review could facilitate the development of new therapeutic options for patients with obesity and asthma.
Little is known about the predictors of response to obesity interventions.

In 450 participants with obesity, body composition, resting energy expenditure, satiety, satiation, eating behavior, affect, and physical activity were measured by validated studies and questionnaires. These variables were used to classify obesity phenotypes. Subsequently, in a 12-month, pragmatic, real-world trial performed in a weight management center, 312 patients were randomly assigned to phenotype-guided treatment or non-phenotype-guided treatment with antiobesity medications phentermine, phentermine/topiramate, bupropion/naltrexone, lorcaserin, and liraglutide. click here The primary outcome was weight loss at 12 months.

Four phenotypes of obesity were identified in 383 of 450 participants (85%) hungry brain (abnormal satiation), emotional hunger (hedonic eating), hungry gut (abnormal satiety), and slow burn (decreased metabolic rate). In 15% of participants, no phenotype was identified. Two or more phenotypes were identified in 27% of patients. In the pragmatic clinical trial, the phenotype-guided approach was associated with 1.75-fold greater weight loss after 12 months with mean weight loss of 15.9% compared with 9.0% in the non-phenotype-guided group (difference -6.9% [95% CI -9.4% to -4.5%], P < 0.001), and the proportion of patients who lost >10% at 12 months was 79% in the phenotype-guided group compared with 34% with non-phenotype-guided treatment group.

Biological and behavioral phenotypes elucidate human obesity heterogeneity and can be targeted pharmacologically to enhance weight loss.
Biological and behavioral phenotypes elucidate human obesity heterogeneity and can be targeted pharmacologically to enhance weight loss.
Self-monitoring is critical for weight management, but little is known about lapses in the use of digital self-monitoring. The objectives of this study were to examine whether lapses in self-weighing and wearing activity trackers are associated with weight and activity outcomes and to identify objective predictors of lapses.

Participants (N = 160, BMI = 25.5 ± 3.3 kg/m
, 33.1 ± 4.6 years old) were drawn from a sample of young adults in the Study of Novel Approaches to Prevention-Extension (SNAP-E) weight gain prevention trial. Analyses evaluated associations between weighing and tracker lapses and changes in weight and steps/day during the first 90 days after receiving a smart scale and activity tracker.

On average, participants self-weighed 49.6% of days and wore activity trackers 75.2% of days. Every 1-day increase in a weighing lapse was associated with a 0.06-lb gain. Lapses in tracker wear were not associated with changes in steps/day or weight between wear days. Weight gain predicted a higher likelihood of starting a lapse in weighing and tracker wear, whereas lower steps predicted a higher likelihood of a tracker lapse.

Weight gain may discourage adherence to self-monitoring. Future research could examine just-in-time supports to anticipate and reduce the frequency or length of self-monitoring lapses.
Weight gain may discourage adherence to self-monitoring. Future research could examine just-in-time supports to anticipate and reduce the frequency or length of self-monitoring lapses.
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