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Protein-rich diets are surging in popularity for weight loss. An increase in diet-induced thermogenesis, better preservation of fat-free mass, and enhanced satiety with greater dietary protein intakes may lead to increased energy expenditure and decreased energy intake; and thus promote a more negative energy balance that facilitates weight loss. Results from large randomized trials and meta-analyses of many smaller trials indicate that high-protein diets typically induce significantly greater amounts of weight loss than conventional low-fat or high-carbohydrate diets during the early, rapid weight loss phase (3–6 months), but differences between diets are attenuated and no longer significant during the late, slow weight loss phase (12–24 months). Gradually decreasing adherence may be responsible for this observation; in fact, dietary adherence, rather than macronutrient composition, is likely the major predictor of long-term weight loss success. Recently, some randomized trials evaluated the efficacy of high-protein (vs. normal-protein) diets consumed ad libitum during weight loss maintenance, i.e. after clinically significant weight loss. Weight regain may be smaller with high-protein diets in the short-term (3–12 months), but longer studies are needed to confirm this. Given the lack of conclusive evidence in favor of high-protein diets, or any other dietary pattern, it is reasonable to conclude that no individual nutrient is a friend or a foe when it comes to weight loss and its maintenance. Therefore, any diet that best suits one’s dietary habits and food preferences is likely to be better adhered to, and thus lead to more successful long-term weight loss.

Evidence from observational studies and randomized trials suggests that prediabetes and type 2 diabetes mellitus (T2DM) can develop in genetically susceptible individuals in parallel with weight (that is, fat) gain. Accordingly, studies show that weight loss can produce remission of T2DM in a dose-dependent manner. A weight loss of ~15 kg, achieved by calorie restriction as part of an intensive management programme, can lead to remission of T2DM in ~80% of patients with obesity and T2DM. However, long-term weight loss maintenance is challenging. Obesity and T2DM are associated with diminished glucose uptake in the brain that impairs the satiating effect of dietary carbohydrate; therefore, carbohydrate restriction might help maintain weight loss and maximize metabolic benefits. Likewise, increases in physical activity and fitness are an important contributor to T2DM remission when combined with calorie restriction and weight loss. Preliminary studies suggest that a precision dietary management approach that uses pretreatment glycaemic status to stratify patients can help optimize dietary recommendations with respect to carbohydrate, fat and dietary fibre. This approach might lead to improved weight loss maintenance and glycaemic control. Future research should focus on better understanding the individual response to dietary treatment and translating these findings into clinical practice.This Review highlights the evidence from clinical trials that diet-induced weight loss interventions can be used to treat type 2 diabetes mellitus. The composition of the diet and the importance of physical exercise programmes are discussed. Lifestyle interventions for prevention of type 2 diabetes mellitus are also considered.

The physical activity level (PAL), defined as the ratio of total daily energy expenditure to resting metabolic rate, is widely used to assess energy requirements in both clinical and research settings. PAL is often not estimated directly—via measurements of total energy expenditure and resting metabolic rate—but rather indirectly using self-reported or objectively recorded physical activity data interpreted through the metabolic equivalent of task (MET) system. However, exercise physiology research consistently shows that the conventional value of 1 MET (set at 1 kcal/kg·hour, corresponding to a resting oxygen consumption of 3.5 mL/kg·min) overestimates true resting metabolic rate by 10%–30%. This systematic bias can lead to inaccurate PAL and energy expenditure estimates when relying solely on physical activity data. To address this problem, a simple correction formula is proposed for adjusting PAL values when individual resting metabolic rate is available or can be predicted from demographic and anthropometric data.

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide. NAFLD begins as a relatively benign hepatic steatosis which can evolve to non-alcoholic steatohepatitis (NASH); the risk of cirrhosis and hepatocellular carcinoma (HCC) increases when fibrosis is present. NAFLD represents a complex process implicating numerous factors—genetic, metabolic, and dietary—intertwined in a multi-hit etiopathogenetic model. Recent data have highlighted the role of gut dysbiosis, which may render the bowel more permeable, leading to increased free fatty acid absorption, bacterial migration, and a parallel release of toxic bacterial products, lipopolysaccharide (LPS), and proinflammatory cytokines that initiate and sustain inflammation. Although gut dysbiosis is present in each disease stage, there is currently no single microbial signature to distinguish or predict which patients will evolve from NAFLD to NASH and HCC. Using 16S rRNA sequencing, the majority of patients with NAFLD/NASH exhibit increased numbers of Bacteroidetes and differences in the presence of Firmicutes, resulting in a decreased F/B ratio in most studies. They also present an increased proportion of species belonging to Clostridium, Anaerobacter, Streptococcus, Escherichia, and Lactobacillus, whereas Oscillibacter, Flavonifaractor, Odoribacter, and Alistipes spp. are less prominent. In comparison to healthy controls, patients with NASH show a higher abundance of Proteobacteria, Enterobacteriaceae, and Escherichia spp., while Faecalibacterium prausnitzii and Akkermansia muciniphila are diminished. Children with NAFLD/NASH have a decreased proportion of Oscillospira spp. accompanied by an elevated proportion of Dorea, Blautia, Prevotella copri, and Ruminococcus spp. Gut microbiota composition may vary between population groups and different stages of NAFLD, making any conclusive or causative claims about gut microbiota profiles in NAFLD patients challenging. Moreover, various metabolites may be involved in the pathogenesis of NAFLD, such as short-chain fatty acids, lipopolysaccharide, bile acids, choline and trimethylamine-N-oxide, and ammonia. In this review, we summarize the role of the gut microbiome and metabolites in NAFLD pathogenesis, and we discuss potential preventive and therapeutic interventions related to the gut microbiome, such as the administration of probiotics, prebiotics, synbiotics, antibiotics, and bacteriophages, as well as the contribution of bariatric surgery and fecal microbiota transplantation in the therapeutic armamentarium against NAFLD. Larger and longer-term prospective studies, including well-defined cohorts as well as a multi-omics approach, are required to better identify the associations between the gut microbiome, microbial metabolites, and NAFLD occurrence and progression.

Gut microbiome has been identified in the past decade as an important factor involved in obesity, but the magnitude of its contribution to obesity and its related comorbidities is still uncertain. Among the vast quantity of factors attributed to obesity, environmental, dietary, lifestyle, genetic, and others, the microbiome has aroused curiosity, and the scientific community has published many original articles. Most of the studies related to microbiome and obesity have been reported based on the associations between microbiota and obesity, and the in-depth study of the mechanisms related has been studied mainly in rodents and exceptionally in humans. Due to the quantity and diverse information published, the need of reviews is mandatory to recapitulate the relevant achievements. In this systematic review, we provide an overview of the current evidence on the association between intestinal microbiota and obesity. Additionally, we analyze the effects of an extreme weight loss intervention such as bariatric surgery on gut microbiota. The review is divided into 2 sections: first, the association of obesity and related metabolic disorders with different gut microbiome profiles, including metagenomics studies, and second, changes on gut microbiome after an extreme weight loss intervention such as bariatric surgery.

Aims/hypothesisLifestyle modification and weight loss are cornerstones of type 2 diabetes management. However, carbohydrate restriction may have weight-independent beneficial effects on glycaemic control. This has been difficult to demonstrate because low-carbohydrate diets readily decrease body weight. We hypothesised that carbohydrate restriction enhances the beneficial metabolic effects of weight loss in type 2 diabetes.MethodsThis open-label, parallel RCT included adults with type 2 diabetes, HbA1c 48–97 mmol/mol (6.5–11%), BMI >25 kg/m2, eGFR >30 ml min−1 [1.73 m]−2 and glucose-lowering therapy restricted to metformin or dipeptidyl peptidase-4 inhibitors. Participants were randomised by a third party and assigned to 6 weeks of energy restriction (all foods were provided) aiming at ~6% weight loss with either a carbohydrate-reduced high-protein diet (CRHP, percentage of total energy intake [E%]: CH30/P30/F40) or a conventional diabetes diet (CD, E%: CH50/P17/F33). Fasting blood samples, continuous glucose monitoring and magnetic resonance spectroscopy were used to assess glycaemic control, lipid metabolism and intrahepatic fat. Change in HbA1c was the primary outcome; changes in circulating and intrahepatic triacylglycerol were secondary outcomes. Data were collected at Copenhagen University Hospital (Bispebjerg and Herlev).ResultsSeventy-two adults (CD 36, CRHP 36, all white, 38 male sex) with type 2 diabetes (mean duration 8 years, mean HbA1c 57 mmol/mol [7.4%]) and mean BMI of 33 kg/m2 were enrolled, of which 67 (CD 33, CRHP 34) completed the study. Body weight decreased by 5.8 kg (5.9%) in both groups after 6 weeks. Compared with the CD diet, the CRHP diet further reduced HbA1c (mean [95% CI] −1.9 [−3.5, −0.3] mmol/mol [−0.18 (−0.32, −0.03)%], p = 0.018) and diurnal mean glucose (mean [95% CI] −0.8 [−1.2, −0.4] mmol/l, p < 0.001), stabilised glucose excursions by reducing glucose CV (mean [95% CI] −4.1 [−5.9, −2.2]%, p < 0.001), and augmented the reductions in fasting triacylglycerol concentration (by mean [95% CI] −18 [−29, −6]%, p < 0.01) and liver fat content (by mean [95% CI] −26 [−45, 0]%, p = 0.051). However, pancreatic fat content was decreased to a lesser extent by the CRHP than the CD diet (mean [95% CI] 33 [7, 65]%, p = 0.010). Fasting glucose, insulin, HOMA2-IR and cholesterol concentrations (total, LDL and HDL) were reduced significantly and similarly by both diets.Conclusions/interpretationModerate carbohydrate restriction for 6 weeks modestly improved glycaemic control, and decreased circulating and intrahepatic triacylglycerol levels beyond the effects of weight loss itself compared with a CD diet in individuals with type 2 diabetes. Concurrent differences in protein and fat intakes, and the quality of dietary macronutrients, may have contributed to these results and should be explored in future studies.Trial registrationClinicalTrials.gov NCT03814694.FundingThe study was funded by Arla Foods amba, The Danish Dairy Research Foundation, and Copenhagen University Hospital Bispebjerg Frederiksberg.

Visceral adipose tissue (VAT) is an important risk factor for obesity-related metabolic disorders. Therefore, a reduction in VAT has become a key goal in obesity management. However, VAT is correlated with intrahepatic triglyceride (IHTG) content, so it is possible that IHTG, not VAT, is a better marker of metabolic disease. We determined the independent association of IHTG and VAT to metabolic function, by evaluating groups of obese subjects, who differed in IHTG content (high or normal) but matched on VAT volume or differed in VAT volume (high or low) but matched on IHTG content. Stable isotope tracer techniques and the euglycemic-hyperinsulinemic clamp procedure were used to assess insulin sensitivity and very-low-density lipoprotein-triglyceride (VLDL-TG) secretion rate. Tissue biopsies were obtained to evaluate cellular factors involved in ectopic triglyceride accumulation. Hepatic, adipose tissue and muscle insulin sensitivity were 41, 13, and 36% lower (P < 0.01), whereas VLDL-triglyceride secretion rate was almost double (P < 0.001), in subjects with higher than normal IHTG content, matched on VAT. No differences in insulin sensitivity or VLDL-TG secretion were observed between subjects with different VAT volumes, matched on IHTG content. Adipose tissue CD36 expression was lower (P < 0.05), whereas skeletal muscle CD36 expression was higher (P < 0.05), in subjects with higher than normal IHTG. These data demonstrate that IHTG, not VAT, is a better marker of the metabolic derangements associated with obesity. Furthermore, alterations in tissue fatty acid transport could be involved in the pathogenesis of ectopic triglyceride accumulation by redirecting plasma fatty acid uptake from adipose tissue toward other tissues.

Purpose of ReviewIndividuals with metabolically unhealthy normal weight (MUNW) have an adverse cardiometabolic risk factor profile in the absence of excess body weight, and increased risk for diabetes and heart disease. We critically review some physiological traits and lifestyle characteristics of the MUNW phenotype.Recent FindingsThe prevalence of MUNW varies considerably around the world and among ethnicities, partly because of different definitions; on average, this phenotype affects about ~ 30% of normal weight persons globally. Most studies have recruited MUNW subjects who, although within the normal weight range, are significantly “more obese” than their metabolically healthy lean peers (greater body mass index or total body fat); hence one cannot ascertain whether observed differences are true traits of the MUNW phenotype of simply secondary to greater relative adiposity within the normal range. Carefully matched studies have indicated that MUNW can exist in the absence of excess total body fat. These subjects have a preferential accumulation of fat in the upper body (abdominal subcutaneous and visceral adipose tissues) and the liver, but not skeletal muscle; perhaps surprisingly, this predominantly “android” fat distribution does not translate into increased waist circumference. The MUNW phenotype is associated with lower aerobic fitness and muscle mass and strength, but whether this is simply due to inadequate regular physical activity is not entirely clear. Likewise, no consistent associations have been found between any dietary factors and the development of MUNW phenotype, but diet-induced modest weight loss facilitates its resolution.SummaryDelineating the mechanisms leading to metabolic dysfunction in the absence of increased body weight and body fat will likely reveal important targets for improving metabolic health and eventually for reducing the burden of cardiometabolic disease, not only in individuals with normal body weight but also in people with obesity.

Insulin is an important regulator of glucose, lipid, and protein metabolism. It suppresses hepatic glucose and triglyceride production, inhibits adipose tissue lipolysis and whole-body and muscle proteolysis, and stimulates glucose uptake in muscle. In this review we discuss what is currently known about the control of substrate metabolism by insulin in men and women. The data available so far indicate that women are more sensitive to insulin with regards to glucose metabolism (both in the liver and in muscle), whereas there are no differences between men and women in insulin action on lipolysis. Potential differences exist in the regulation of plasma triglyceride concentration and protein metabolism by insulin and in changes in insulin action in response to stimuli (e.g., weight loss and exercise) that are known to alter insulin sensitivity. However, these areas have not been studied comprehensively enough to draw firm conclusions.

Gestational diabetes mellitus (GDM) adversely affects offspring glucose homeostasis and risk of developing obesity. Here, we examined the association between glycemia in pregnant women with overweight or obesity without GDM and offspring metabolic health. Maternal fasting glucose concentrations and glucose 2-h after an oral glucose tolerance test (OGTT) were measured in 208 women with a pre-pregnancy body mass index (BMI) of 28–45 kg/m 2 without GDM. Offspring outcomes were collected at birth, 3, and 5 years of age. Linear mixed models with time as fixed factor and subject ID as random effects were used for analysis. No associations were found between maternal fasting or 2-h glucose concentrations with offspring glucose and insulin concentrations from birth to 5 years of age. However, maternal fasting glucose in GW 28 and 36, and 2-h OGTT glucose in GW 28 were positively associated with C-peptide concentration at birth. Maternal fasting glucose concentrations in GW 28 and 36 were positively associated with weight-for-length, and maternal fasting glucose in GW 36 was associated with BMI z-score at birth. In summary, blood glucose in pregnant women with overweight or obesity is positively associated with offspring C-peptide concentration, weight-for-length, and BMI z-score at birth, even in the absence of GDM.