Reviews in Endocrine & Metabolic Disorders最新文献

In this thematic issue on phenotyping the obesities, prominent international experts offer an insightful and comprehensive collection of articles covering the current knowledge in the field. In order to actually capture all the polyhedral determinants of the diverse types of obesity, the granularity of the phenotypic information acquired must be expanded in the context of a personalized approach. Whilst the use of precision medicine has been successfully implemented in areas like cancer and other diseases, health care providers are more reluctant to embrace detailed phenotyping to guide diagnosis, treatment and prevention in obesity. Given its multiple complex layers, phenotyping necessarily needs to go beyond the multi-omics approach and incorporate all the diverse spheres that conform the reality of people living with obesity. Potential barriers, difficulties, roadblocks and opportunities together with their interaction in a syndemic context are analyzed. Plausible lacunae are also highlighted in addition to pointing to the need of redefining new conceptual frameworks. Therefore, this extraordinary collection of state-ofthe-art reviews provides useful information to both experienced clinicians and trainees as well as academics to steer clinical practice and research in the management of people living with obesity irrespective of practice setting or career stage.

Physical activity and exercise training programs are integral part of a comprehensive obesity management approach. In persons with overweight or obesity, exercise training, specifically aerobic (i.e. endurance) training, is associated with significant additional weight loss compared to the absence of training. However the magnitude of effect remains modest amounting to only 2-3 kg additional weight loss on average. Comparable effects have been observed for total fat loss. Exercise training, specifically aerobic training, is also associated with decreased abdominal visceral fat as assessed by imaging techniques, which is likely to benefit cardiometabolic health in persons with obesity. Based on data from controlled trials with randomization after prior weight loss, the evidence for weight maintenance with exercise training is as yet not conclusive, although retrospective analyses point to the value of relatively high-volume exercise in this regard. Resistance (i.e. muscle-strengthening) training is specifically advised for lean mass preservation during weight loss. Given the relatively limited effect of exercise training on weight loss as such, the changes in physical fitness brought about by exercise training cannot be overlooked as they provide major health benefits to persons with obesity. Aerobic, as well as combined aerobic and resistance training, increase cardiorespiratory fitness (VO_2max) while resistance training, but not aerobic training, improves muscle strength even in the absence of a significant change in muscle mass. Regarding the overall management strategy, adherence in the long term to new lifestyle habits remains a challenging issue to be addressed by further research.

Obesity is the most extended metabolic alteration worldwide increasing the risk for the development of cardiometabolic alterations such as type 2 diabetes, hypertension, and dyslipidemia. Body mass index (BMI) remains the most frequently used tool for classifying patients with obesity, but it does not accurately reflect body adiposity. In this document we review classical and new classification systems for phenotyping the obesities. Greater accuracy of and accessibility to body composition techniques at the same time as increased knowledge and use of cardiometabolic risk factors is leading to a more refined phenotyping of patients with obesity. It is time to incorporate these advances into routine clinical practice to better diagnose overweight and obesity, and to optimize the treatment of patients living with obesity.

Obesity continues to increase in prevalence globally, driven by changes in environmental factors which have accelerated the development of obesity in individuals with an underlying predisposition to weight gain. The adverse health effects and increased risk for chronic disease associated with obesity are ameliorated by weight loss, with greater benefits from larger amounts of weight reduction. Obesity is a heterogeneous condition, with the drivers, phenotype and complications differing substantially between individuals. This raises the question of whether treatments for obesity, specifically pharmacotherapy, can be targeted based on individual characteristics. This review examines the rationale and the clinical data evaluating this strategy in adults. Individualised prescribing of obesity medication has been successful in rare cases of monogenic obesity where medications have been developed to target dysfunctions in leptin/melanocortin signalling pathways but has been unsuccessful in polygenic obesity due to a lack of understanding of how the gene variants associated with body mass index affect phenotype. At present, the only factor consistently associated with longer-term efficacy of obesity pharmacotherapy is early weight loss outcome, which cannot inform choice of therapy at the time of medication initiation. The concept of matching a therapy for obesity to the characteristics of the individual is appealing but as yet unproven in randomised clinical trials. With increasing technology allowing deeper phenotyping of individuals, increased sophistication in the analysis of big data and the emergence of new treatments, it is possible that precision medicine for obesity will eventuate. For now, a personalised approach that takes into account the person's context, preferences, comorbidities and contraindications is recommended.

Individual differences in obesity, beyond being explained by metabolic and medical complications, are understood by alterations in eating behaviour which underlie psychological processes. From this psychological perspective, studies have identified several potential characteristic features at the psycho-behavioural level that could additionally explain the maintenance of chronic excess weight or the unsuccessful results of current treatments. To date, despite the growing evidence, the heterogeneity of the psychological evidence associated with obesity has made it challenging to generate consensus on whether these psycho-behavioural phenotypes can be a complement to improve outcomes of existing interventions. For this reason, this narrative review is an overview focused on summarizing studies describing the psycho-behavioural phenotypes associated with obesity. Based on the literature, three psychological constructs have emerged: reward dependence, cognitive control, and mood and emotion. We discuss the clinical implications of stratifying and identifying these psycho-behavioural profiles as potential target for interventions which may ensure a better response to treatment in individuals with obesity. Our conclusions pointed out a considerable overlap between these psycho-behavioural phenotypes suggesting bidirectional interactions between them. These findings endorse the complexity of the psycho-behavioural features associated with obesity and reinforce the need to consider them in order to improve treatment outcomes.

Obesity is a complex, multifactorial and chronic disease. Bariatric surgery is a safe and effective treatment intervention for obesity and obesity-related diseases. However, weight loss after surgery can be highly heterogeneous and is not entirely predictable, particularly in the long-term after intervention. In this review, we present and discuss the available data on patient-related and procedure-related factors that were previously appointed as putative predictors of bariatric surgery outcomes. In addition, we present a critical appraisal of the available evidence on which factors could be taken into account when recommending and deciding which bariatric procedure to perform. Several patient-related features were identified as having a potential impact on weight loss after bariatric surgery, including age, gender, anthropometrics, obesity co-morbidities, eating behavior, genetic background, circulating biomarkers (microRNAs, metabolites and hormones), psychological and socioeconomic factors. However, none of these factors are sufficiently robust to be used as predictive factors. Overall, there is no doubt that before we long for precision medicine, there is the unmet need for a better understanding of the socio-biological drivers of weight gain, weight loss failure and weight-regain after bariatric interventions. Machine learning models targeting preoperative factors and effectiveness measurements of specific bariatric surgery interventions, would enable a more precise identification of the causal links between determinants of weight gain and weight loss. Artificial intelligence algorithms to be used in clinical practice to predict the response to bariatric surgery interventions could then be created, which would ultimately allow to move forward into precision medicine in bariatric surgery prescription.

Obesity has reached epidemic proportion worldwide and in all ages. Available evidence points to a multifactorial pathogenesis involving gene predisposition and environmental factors. Gut microbiota plays a critical role as a major interface between external factors, i.e., diet, lifestyle, toxic chemicals, and internal mechanisms regulating energy and metabolic homeostasis, fat production and storage. A shift in microbiota composition is linked with overweight and obesity, with pathogenic mechanisms involving bacterial products and metabolites (mainly endocannabinoid-related mediators, short-chain fatty acids, bile acids, catabolites of tryptophan, lipopolysaccharides) and subsequent alterations in gut barrier, altered metabolic homeostasis, insulin resistance and chronic, low-grade inflammation. Although animal studies point to the links between an "obesogenic" microbiota and the development of different obesity phenotypes, the translational value of these results in humans is still limited by the heterogeneity among studies, the high variation of gut microbiota over time and the lack of robust longitudinal studies adequately considering inter-individual confounders. Nevertheless, available evidence underscores the existence of several genera predisposing to obesity or, conversely, to lean and metabolically health phenotype (e.g., Akkermansia muciniphila, species from genera Faecalibacterium, Alistipes, Roseburia). Further longitudinal studies using metagenomics, transcriptomics, proteomics, and metabolomics with exact characterization of confounders are needed in this field. Results must confirm that distinct genera and specific microbial-derived metabolites represent effective and precision interventions against overweight and obesity in the long-term.

Bariatric surgery (BS) is the most effective long-term treatment for severe obesity. This review summarizes the main nutritional deficiencies before and after BS, as well as current dietary and supplementation recommendations to avoid them. Likewise, we have reviewed all those aspects that in recent years have been shown to be related to postoperative weight loss (WL) and its subsequent maintenance, such as hormonal changes, dietary patterns, changes in food preference, adherence to recommendations and follow-up, genetic factors and microbiota, among others. Despite all the knowledge, nutritional deficiencies and weight regain after BS are frequent. It is essential to continue studying in this field in order to establish more precise recommendations according to the individual characteristics of patients. It is also a major objective to understand more deeply the role of the factors involved in WL and its maintenance. This will allow the development of precision treatments and nutrition for patients with obesity, optimizing their benefit after BS.

Obesity epidemic reached the dimensions of a real global health crisis with more than one billion people worldwide living with obesity. Multiple obesity-related mechanisms cause structural, functional, humoral, and hemodynamic alterations with cardiovascular (CV) deleterious effects. A correct assessment of the cardiovascular risk in people with obesity is critical for reducing mortality and preserving quality of life. The correct identification of the obesity status remains difficult as recent evidence suggest that different phenotypes of obesity exist, each one associated with different degrees of CV risk. Diagnosis of obesity cannot depend only on anthropometric parameters but should include a precise assessment of the metabolic status. Recently, the World Heart Federation and World Obesity Federation provided an action plan for management of obesity-related CV risk and mortality, stressing for the instauration of comprehensive structured programs encompassing multidisciplinary teams. In this review we aim at providing an updated summary regarding the different obesity phenotypes, their specific effects on CV risk and differences in clinical management.

Obesity is a heterogenous disease accompanied by a broad spectrum of cardiometabolic risk profiles. Traditional paradigms for dietary weight management do not address biological heterogeneity between individuals and have catastrophically failed to combat the global pandemic of obesity-related diseases. Nutritional strategies that extend beyond basic weight management to instead target patient-specific pathophysiology are warranted. In this narrative review, we provide an overview of the tissue-level pathophysiological processes that drive patient heterogeneity to shape distinct cardiometabolic phenotypes in obesity. Specifically, we discuss how divergent physiology and postprandial phenotypes can reveal key metabolic defects within adipose, liver, or skeletal muscle, as well as the integrative involvement of the gut microbiome and the innate immune system. Finally, we highlight potential precision nutritional approaches to target these pathways and discuss recent translational evidence concerning the efficacy of such tailored dietary interventions for different obesity phenotypes, to optimise cardiometabolic benefits.