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Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci ( P  < 5 × 10 −8 ), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis. A genome-wide association study and Metabochip meta-analysis of body mass index (BMI) detects 97 BMI-associated loci, of which 56 were novel, and many loci have effects on other metabolic phenotypes; pathway analyses implicate the central nervous system in obesity susceptibility and new pathways such as those related to synaptic function, energy metabolism, lipid biology and adipogenesis. Genetic correlates of obesity In the second of two Articles in this issue from the GIANT Consortium, Elizabeth Speliotes and collegues conducted a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), commonly used to define obesity and assess adiposity, to find 97 BMI-associated loci, of which 56 were novel. Many of these loci have significant effects on other metabolic phenotypes. The 97 loci account for about 2.7% of BMI variation, and genome-wide estimates suggest common variation accounts for more than 20% of BMI variation. Pathway analyses implicate the central nervous system in obesity susceptibility including synaptic function, glutamate signaling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

A large-scale epigenome-wide association study identifies changes in DNA methylation associated with body mass index in blood and adipose tissue, and correlates DNA methylation sites with high risk of incident type 2 diabetes. Body fat and diabetes risk Obesity is a major risk factor for type 2 diabetes and related metabolic disorders. Genetic association studies have identified genomic loci associated with obesity, and recent studies have also suggested associations with DNA methylation. These authors report an epigenome-wide association study for body mass index (BMI), identifying an association with DNA methylation at 187 loci in blood and adipose tissue. They find that these methylation changes are secondary to adiposity and are also associated with an increased risk of developing type 2 diabetes, independent of conventional risk factors. Approximately 1.5 billion people worldwide are overweight or affected by obesity, and are at risk of developing type 2 diabetes, cardiovascular disease and related metabolic and inflammatory disturbances 1 , 2 . Although the mechanisms linking adiposity to associated clinical conditions are poorly understood, recent studies suggest that adiposity may influence DNA methylation 3 , 4 , 5 , 6 , a key regulator of gene expression and molecular phenotype 7 . Here we use epigenome-wide association to show that body mass index (BMI; a key measure of adiposity) is associated with widespread changes in DNA methylation (187 genetic loci with P  < 1 × 10 −7 , range P  = 9.2 × 10 −8 to 6.0 × 10 −46 ; n  = 10,261 samples). Genetic association analyses demonstrate that the alterations in DNA methylation are predominantly the consequence of adiposity, rather than the cause. We find that methylation loci are enriched for functional genomic features in multiple tissues ( P  < 0.05), and show that sentinel methylation markers identify gene expression signatures at 38 loci ( P  < 9.0 × 10 −6 , range P  = 5.5 × 10 −6 to 6.1 × 10 −35 , n  = 1,785 samples). The methylation loci identify genes involved in lipid and lipoprotein metabolism, substrate transport and inflammatory pathways. Finally, we show that the disturbances in DNA methylation predict future development of type 2 diabetes (relative risk per 1 standard deviation increase in methylation risk score: 2.3 (2.07–2.56); P  = 1.1 × 10 −54 ). Our results provide new insights into the biologic pathways influenced by adiposity, and may enable development of new strategies for prediction and prevention of type 2 diabetes and other adverse clinical consequences of obesity.

Visceral adipose tissue (VAT)—fat stored around the internal organs—has been suggested as an independent risk factor for cardiovascular and metabolic disease 1 – 3 , as well as all-cause, cardiovascular-specific and cancer-specific mortality 4 , 5 . Yet, the contribution of genetics to VAT, as well as its disease-related effects, are largely unexplored due to the requirement for advanced imaging technologies to accurately measure VAT. Here, we develop sex-stratified, nonlinear prediction models (coefficient of determination = 0.76; typical 95% confidence interval (CI) = 0.74–0.78) for VAT mass using the UK Biobank cohort. We performed a genome-wide association study for predicted VAT mass and identified 102 novel visceral adiposity loci. Predicted VAT mass was associated with increased risk of hypertension, heart attack/angina, type 2 diabetes and hyperlipidemia, and Mendelian randomization analysis showed visceral fat to be a causal risk factor for all four diseases. In particular, a large difference in causal effect between the sexes was found for type 2 diabetes, with an odds ratio of 7.34 (95% CI = 4.48–12.0) in females and an odds ratio of 2.50 (95% CI = 1.98–3.14) in males. Our findings bolster the role of visceral adiposity as a potentially independent risk factor, in particular for type 2 diabetes in Caucasian females. Independent validation in other cohorts is necessary to determine whether the findings can translate to other ethnicities, or outside the UK. Analysis of the UK Biobank reveals new genetic loci associated with estimated visceral adipose tissue (VAT) mass, and suggests that VAT is potentially an independent risk factor for various cardiovascular and metabolic diseases, such as hypertension and type 2 diabetes.

Abstract Background The incidence of thyroid cancer is rising, and relatively little is known about modifiable risk factors for the condition. Observational studies have suggested a link between adiposity and thyroid cancer; however, these are subject to confounding and reverse causality. Here, we used data from the UK Biobank and Mendelian randomization approaches to investigate whether adiposity causes benign nodular thyroid disease and differentiated thyroid cancer. Methods We analyzed data from 379 708 unrelated participants of European ancestry in the UK Biobank and identified 1812 participants with benign nodular thyroid disease and 425 with differentiated thyroid carcinoma. We tested observational associations with measures of adiposity and type 2 diabetes mellitus. One and 2-sample Mendelian randomization approaches were used to investigate causal relationships. Results Observationally, there were positive associations between higher body mass index (odds ratio [OR], 1.15; 95% confidence interval [CI], 1.08-1.22), higher waist-hip ratio (OR, 1.16; 95% CI, 1.09-1.23), and benign nodular thyroid disease, but not thyroid cancer. Mendelian randomization did not support a causal link for obesity with benign nodular thyroid disease or thyroid cancer, although it did provide some evidence that individuals in the highest quartile for genetic liability of type 2 diabetes had higher odds of thyroid cancer than those in the lowest quartile (OR, 1.45; CI, 1.11-1.90). Conclusions Contrary to the findings of observational studies, our results do not confirm a causal role for obesity in benign nodular thyroid disease or thyroid cancer. They do, however, suggest a link between type 2 diabetes and thyroid cancer.

A randomized, parallel controlled, open-label clinical trial was conducted to evaluate the effect of a botanic compound berberine (BBR) on NAFLD. A randomized, parallel controlled, open-label clinical trial was conducted in three medical centers (NIH Registration number: NCT00633282). A total of 184 eligible patients with NAFLD were enrolled and randomly received (i) lifestyle intervention (LSI), (ii) LSI plus pioglitazone (PGZ) 15mg qd, and (iii) LSI plus BBR 0.5g tid, respectively, for 16 weeks. Hepatic fat content (HFC), serum glucose and lipid profiles, liver enzymes and serum and urine BBR concentrations were assessed before and after treatment. We also analyzed hepatic BBR content and expression of genes related to glucose and lipid metabolism in an animal model of NAFLD treated with BBR. As compared with LSI, BBR treatment plus LSI resulted in a significant reduction of HFC (52.7% vs 36.4%, p = 0.008), paralleled with better improvement in body weight, HOMA-IR, and serum lipid profiles (all p<0.05). BBR was more effective than PGZ 15mg qd in reducing body weight and improving lipid profile. BBR-related adverse events were mild and mainly occurred in digestive system. Serum and urine BBR concentrations were 6.99ng/ml and 79.2ng/ml, respectively, in the BBR-treated subjects. Animal experiments showed that BBR located favorably in the liver and altered hepatic metabolism-related gene expression. BBR ameliorates NAFLD and related metabolic disorders. The therapeutic effect of BBR on NAFLD may involve a direct regulation of hepatic lipid metabolism. ClinicalTrials.gov NCT00633282.

Mendelian randomization (MR) has been used to estimate the causal effect of body mass index (BMI) on particular traits thought to be affected by BMI. However, BMI may also be a modifiable, causal risk factor for outcomes where there is no prior reason to suggest that a causal effect exists. We performed a MR phenome-wide association study (MR-pheWAS) to search for the causal effects of BMI in UK Biobank (n = 334 968), using the PHESANT open-source phenome scan tool. A subset of identified associations were followed up with a formal two-stage instrumental variable analysis in UK Biobank, to estimate the causal effect of BMI on these phenotypes. Of the 22 922 tests performed, our MR-pheWAS identified 587 associations below a stringent P value threshold corresponding to a 5% estimated false discovery rate. These included many previously identified causal effects, for instance, an adverse effect of higher BMI on risk of diabetes and hypertension. We also identified several novel effects, including protective effects of higher BMI on a set of psychosocial traits, identified initially in our preliminary MR-pheWAS in circa 115,000 UK Biobank participants and replicated in a different subset of circa 223,000 UK Biobank participants. Our comprehensive MR-pheWAS identified potential causal effects of BMI on a large and diverse set of phenotypes. This included both previously identified causal effects, and novel effects such as a protective effect of higher BMI on feelings of nervousness.

Recent studies have revealed the critical role of several microRNAs (miRNAs) in energy homeostasis and metabolic processes and suggest that circulating miRNAs can be used as early predictors of weight loss in the design of precision nutrition. Thus, the aim of this study was to investigate circulating adiposity‐related miRNAs as biomarkers of the response to two specific weight loss dietary treatments. The expression of 86 miRNAs was investigated in plasma of 78 subjects with obesity randomized to two different diets [moderately high‐protein diet (n = 38) and low‐fat diet (n = 40)] and in 25 eutrophic controls (BMI ≤ 25 kg/m2). Bioinformatic analyses were performed to explore the target genes and biological pathways regulated by the dysregulated miRNAs. As results, 26 miRNAs were found differently expressed in eutrophic and volunteers with obesity. Moreover, 7 miRNAs (miR‐130a‐3p, miR‐142‐5p, miR‐144‐5p, miR‐15a‐5p, miR‐22‐3p, miR‐221‐3p and miR‐29c‐3p) were differentially expressed between responders and non‐responders to a low‐fat diet. Furthermore, after adjustment for basal glucose levels, 1‐SD increase in miR‐22‐3p expression was associated with reduction in the risk of non‐response to low‐fat diet [OR = 0.181, 95% CI (0.084‐0.947), P = .043]. Bioinformatic analyses evidenced that these 7 miRNAs regulate the expression of genes participating in important metabolic pathways. Conclusively, 7 circulating miRNAs related to adiposity could be used for predicting the response to a low‐fat diet intervention prescribed to lose weight.

Background/Objectives: The location and distribution of excess fat, rather than overall adiposity, are stronger predictors of cardiometabolic risk and are commonly assessed using the waist-to-hip ratio (WHR). Fat distribution in women has a heritable component, yet the genetic factors that influence it remain poorly understood. We aim to assess the association between obesity-related polymorphisms with WHR and cardiometabolic risk in overweight and obese women. Methods: A cohort study was conducted in 512 women (56.1 ± 6.4 years; body mass index (BMI) ≥ 25 kg/m2). WHR was calculated, and participants were classified into android (WHR > 0.85) or gynoid (WHR ≤ 0.85) obesity groups. We genotyped 15 SNPs previously associated with obesity using TaqMan real-time PCR. Different genetic models (dominant, recessive, and allelic) were analysed, and bivariate and multivariate analyses were performed to compare the fat distribution groups. Results: Of the 15 SNPs studied, only 3 presented a significant association with WHR > 0.85. PSRC1 rs599839 in a dominant model (AA + GA vs. GG) with OR = 3.18 (p = 0.041), SLC30A8 rs1326634 in a recessive model (CC vs. TC + TT) (OR = 2.38; p = 0.004), both showing increased susceptibility to central obesity. KIF6 rs20455 offers protection in a recessive model (CC vs. TC + TT) with an OR of 0.47 (p = 0.043). After adjusted multivariate analysis, only SLC30A8 and diabetes remained independently associated with an increased risk of android obesity (OR = 2.50; p = 0.003 and OR = 3.63; p = 0.004, respectively). Conclusions: The SLC30A8 variant was significantly associated with android fat distribution and high cardiometabolic risk in overweight/obese women. Identifying genetic factors that influence fat distribution may help specify targeted lifestyle changes or pharmacological interventions to reduce risk.

Population studies suggest that atopic dermatitis (AD) is associated with an increased risk of obesity, however a causal relationship between these two conditions remains to be established. We therefore use Mendelian randomization (MR) to evaluate whether obesity and AD are causally interlinked. We used summary statistics extracted from genome wide association studies of Body Mass Index (BMI) and AD. MR analysis was performed in both directions to establish the direction of causality between BMI and AD. We find that genetically determined increase in adiposity is associated with increased risk of AD (odds ratio of AD 1.08 [95% CI 1.01 to 1.14; p = 0.015] per unit increase in BMI). Conversely, genetically determined increased risk of AD is not associated with a higher BMI (change in BMI attributable to AD based on genetic information: 0.00; 95% CI − 0.02 to 0.02; p = 0.862). There was no evidence for confounding of these genetic analyses by horizontal pleiotropy. Our results indicate that the association of AD with obesity is likely to reflect a causal role for adiposity in the development of AD. Our findings enhance understanding of the etiology of AD, and the basis for experimental studies to evaluate the mechanistic pathways by which adiposity promotes AD.

Background/objectivesGut microbiome regulates host energy metabolism and adiposity. A recent study identified a genome-wide significant variant in the lactase (LCT) gene that determines gut-microbiome abundance. We investigated whether the LCT variant influenced long-term changes in adiposity among overweight and obese individuals.Subjects/methodsWe included 583 whites with LCT variant rs4988235 (G allele as Bifidobacterium-abundance-increasing allele) who were randomly assigned to one of four weight-loss diets varying in macronutrient contents. Two-year changes in adiposity measures were assessed according to the LCT genotype and weight-loss diets.ResultsWe observed a significant interaction between the LCT genotype and dietary protein intake on changes in whole body total fat mass %, trunk fat %, superficial adipose tissue mass (SAT), visceral adipose tissue mass (VAT), and total adipose tissue mass (TAT) (Pinteraction < 0.05 for all). In response to high-protein diet, carrying the G allele of LCT variant rs4988235 was associated with greater reduction of whole body total fat mass % (β [SE] –0.9 [0.43], P = 0.04), trunk fat % (–1.06 [0.58], P = 0.07), SAT (–0.89 [0.42], P = 0.04), VAT (–0.63 [0.27], P = 0.03), and TAT (–1.69 [0.76], P = 0.03). Conversely, increasing numbers of the G allele tended to be related to less reduction of these outcomes in response to low-protein diet.ConclusionsLong-term improvement of body fat composition and distribution was significantly influenced by the Bifidobacterium-related LCT genotype and dietary protein intake. Overweight and obese individuals with the G allele of LCT variant rs4988235 may benefit improving adiposity by eating a low-calorie, high-protein diet.