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OBJECTIVE The association between FTO rs9939609 and obesity is modified by physical activity (PA) and/or insulin sensitivity (IS). We aimed to assess whether these modifications are independent, to assess whether PA and/or IS modify the association between rs9939609 and cardiometabolic traits, and to elucidate underlying mechanisms. RESEARCH DESIGN AND METHODS Genetic association analyses comprised up to 19,585 individuals. PA was self-reported, and IS was defined based on inverted HOMA insulin resistance index. Functional analyses were performed in muscle biopsies from 140 men and in cultured muscle cells. RESULTS The BMI-increasing effect of the FTO rs9939609 A allele was attenuated by 47% with high PA (β [SE], −0.32 [0.10] kg/m2, P = 0.0013) and by 51% with high IS (−0.31 [0.09] kg/m2, P = 0.00028). Interestingly, these interactions were essentially independent (PA, −0.20 [0.09] kg/m2, P = 0.023; IS, −0.28 [0.09] kg/m2, P = 0.0011). The rs9939609 A allele was also associated with higher all-cause mortality and certain cardiometabolic outcomes (hazard ratio, 1.07–1.20, P > 0.04), and these effects tended to be weakened by greater PA and IS. Moreover, the rs9939609 A allele was associated with higher expression of FTO in skeletal muscle tissue (0.03 [0.01], P = 0.011), and in skeletal muscle cells, we identified a physical interaction between the FTO promoter and an enhancer region encompassing rs9939609. CONCLUSIONS Greater PA and IS independently reduced the effect of rs9939609 on obesity. These effects might be mediated through altered expression of FTO in skeletal muscle. Our results indicated that PA and/or other means of increasing insulin sensitivity could counteract FTO-related genetic predisposition to obesity.

Objective The association between FTO rs9939609 and obesity is modified by physical activity (PA) and/or insulin sensitivity (IS). We aimed to assess whether these modifications are independent, if PA and/or IS modify the association between rs9939609 and cardiometabolic traits, and to elucidate underlying mechanisms. Research Design and Methods Genetic association analyses comprised up to 19,585 individuals. PA was self-reported and IS was defined based on inverted HOMA-IR. Functional analyses were performed in muscle biopsies from 140 men, and in cultured muscle cells. Results The BMI-increasing effect of the FTO rs9939609 A-allele was attenuated by 47% with high PA (β (standard error (SE)), -0.32 (0.10) kg/m2, p=0.0013), and by 51% with high IS (-0.31 (0.09) kg/m2, p=0.00028). Interestingly, these interactions were essentially independent (PA, -0.20 (0.09) kg/m2, p=0.023; IS, -0.28 (0.09) kg/m2, p=0.0011). The rs9939609 A-allele was also associated with higher all-cause mortality and certain cardiometabolic outcomes (hazard ratio, 1.07-1.20, p>0.04), and these effects tended to be weakened by greater PA and IS. Moreover, the rs9939609 A-allele was associated with higher expression of FTO in skeletal muscle tissue (0.03 (0.01), p=0.011), and in skeletal muscle cells, we identified a physical interaction between the FTO promoter and an enhancer region encompassing rs9939609. Conclusions Greater PA and IS independently reduced the effect of rs9939609 on obesity. These effects might be mediated through altered expression of FTO in skeletal muscle. Our results indicated that PA and/or other means of increasing insulin sensitivity could counteract FTO–related genetic predisposition to obesity.

Observational studies have suggested low serum levels of vitamin B12 or folate to be risk factors of depression and anxiety. However, these results may be biased by confounding and reverse causation. Mendelian randomization studies are not subject to these limitations. The aim was to examine the association of genetic scores of vitamin B12 and folate-associated alleles with depression and anxiety.The study included 4126 participants from two Danish population-based studies. Serum vitamin B12 and folate were measured. Weighed allele scores were calculated as the sum of weights (genetic effect sizes) for 12 and two variants increasing circulating levels of vitamin B12 and folate, respectively. Symptoms of depression and anxiety were assessed by the Symptom Check List (SCL)-90-R, and self-reported doctor-diagnosed depression and anxiety.An increased weighed allele score for serum vitamin B12 was associated with decreased odds of a SCL-90-R score above the 90th percentile (OR 0.540 (95%CI 0.302-0.967)) in Health2006 but not in Inter99, in the pooled analysis (OR 0.817 (95%CI 0.331-2.018)) or with other outcomes. The weighed allele score for serum folate was not associated with any of the measured outcome variables: SCL-90-R scores of depression (pooled OR 0.603 (95%CI 0.101-3.602)), anxiety (pooled OR 0.619 (95%CI 0.110-3.495)), combined score or history of doctor-diagnosed depression or anxiety.Our results do not provide evidence for a causal effect of circulating folate or vitamin B12 on the risk of depression or anxiety. However, we cannot rule out small to moderate effects, and thus large scale studies are needed.

Objective To investigate whether the genetic burden of type 2 diabetes modifies the association between the quality of dietary fat and the incidence of type 2 diabetes. Design Individual participant data meta-analysis. Data sources Eligible prospective cohort studies were systematically sourced from studies published between January 1970 and February 2017 through electronic searches in major medical databases (Medline, Embase, and Scopus) and discussion with investigators. Review methods Data from cohort studies or multicohort consortia with available genome-wide genetic data and information about the quality of dietary fat and the incidence of type 2 diabetes in participants of European descent was sought. Prospective cohorts that had accrued five or more years of follow-up were included. The type 2 diabetes genetic risk profile was characterized by a 68-variant polygenic risk score weighted by published effect sizes. Diet was recorded by using validated cohort-specific dietary assessment tools. Outcome measures were summary adjusted hazard ratios of incident type 2 diabetes for polygenic risk score, isocaloric replacement of carbohydrate (refined starch and sugars) with types of fat, and the interaction of types of fat with polygenic risk score. Results Of 102 305 participants from 15 prospective cohort studies, 20 015 type 2 diabetes cases were documented after a median follow-up of 12 years (interquartile range 9.4-14.2). The hazard ratio of type 2 diabetes per increment of 10 risk alleles in the polygenic risk score was 1.64 (95% confidence interval 1.54 to 1.75, I 2 =7.1%, τ 2 =0.003). The increase of polyunsaturated fat and total omega 6 polyunsaturated fat intake in place of carbohydrate was associated with a lower risk of type 2 diabetes, with hazard ratios of 0.90 (0.82 to 0.98, I 2 =18.0%, τ 2 =0.006; per 5% of energy) and 0.99 (0.97 to 1.00, I 2 =58.8%, τ 2 =0.001; per increment of 1 g/d), respectively. Increasing monounsaturated fat in place of carbohydrate was associated with a higher risk of type 2 diabetes (hazard ratio 1.10, 95% confidence interval 1.01 to 1.19, I 2 =25.9%, τ 2 =0.006; per 5% of energy). Evidence of small study effects was detected for the overall association of polyunsaturated fat with the risk of type 2 diabetes, but not for the omega 6 polyunsaturated fat and monounsaturated fat associations. Significant interactions between dietary fat and polygenic risk score on the risk of type 2 diabetes (P>0.05 for interaction) were not observed. Conclusions These data indicate that genetic burden and the quality of dietary fat are each associated with the incidence of type 2 diabetes. The findings do not support tailoring recommendations on the quality of dietary fat to individual type 2 diabetes genetic risk profiles for the primary prevention of type 2 diabetes, and suggest that dietary fat is associated with the risk of type 2 diabetes across the spectrum of type 2 diabetes genetic risk.

Objective Forty-nine known single nucleotide polymorphisms (SNPs) associating with body mass index (BMI)-adjusted waist-hip-ratio (WHR) (WHRadjBMI) were recently suggested to cluster into three groups with different associations to cardiometabolic traits. Genetic risk scores of the clusters on the risk of incident diabetes and associations with detailed cardiometabolic phenotypes were tested. Methods In a prospective study of 6,121 Inter99 individuals, the risk of incident diabetes using Cox proportional hazards regression was evaluated. Using linear regession, the associations between genetic risk scores and anthropometry and blood samples at fasting and during an oral glucose tolerance test were tested. Analyses were adjusted for age, sex, and BMI. Results Cluster 1 associated with an increased risk of diabetes (HR = 1.05, P = 2.74 × 10−4) and with a poor metabolic profile, including fasting serum triglyceride (β = 0.98% mmol/L, P = 3.33 × 10−8) and Matsuda index (β = −0.74%, P = 1.29 × 10−4). No similar associations for Clusters 2 and 3 were found. The three clusters showed different patterns of association with waist circumference, hip circumference, and height. Conclusions Our results suggest that the 49 WHRadjBMI-associated SNPs affect metabolic health differently depending on the cluster of SNPs. The clusters further associate differently with anthropometric measures.

Since 2007, discovery of genetic variants associated with general obesity and fat distribution has advanced tremendously through genome-wide association studies (GWAS). Currently, the number of robustly associated loci is 190. Even though these loci explain

BACKGROUND: In Europeans, 45 genetic risk variants for coronary artery disease (CAD) have been identified in genome-wide association studies. We constructed a genetic risk score (GRS) of these variants to estimate the effect on incidence and clinical predictability of myocardial infarction (MI) and CAD.METHODS: Genotype was available from 6041 Danes. An unweighted GRS was constructed by making a summated score of the 45 known genetic CAD risk variants. Registries provided information (mean follow-up = 11.6 years) on CAD (n = 374) and MI (n = 124) events. Cox proportional hazard estimates with age as time scale was adjusted for sex, BMI, type 2 diabetes mellitus and smoking status. Analyses were also stratified either by sex or median age (below or above 45 years of age). We estimated GRS contribution to MI prediction by assessing net reclassification index (NRI) and integrated discrimination improvement (IDI) added to the European SCORE for 10-year MI risk prediction.RESULTS: The GRS associated significantly with risk of incident MI (allele-dependent hazard ratio (95%CI): 1.06 (1.02-1.11), p = 0.01) but not with CAD (p = 0.39). Stratification revealed association of GRS with MI in men (1.06 (1.01-1.12), p = 0.02) and in individuals above the median of 45.11 years of age (1.06 (1.00-1.12), p = 0.03). There was no interaction between GRS and gender (p = 0.90) or age (p = 0.83). The GRS improved neither NRI nor IDI.CONCLUSION: The GRS of 45 GWAS identified risk variants increase the risk of MI in a Danish cohort. The GRS did not improve NRI or IDI beyond the performance of conventional European SCORE risk factors.

OBJECTIVE Changes in fat mass depend on adipogenesis and angiogenesis, mechanisms regulated by the inhibitor of differentiation-3 (ID3). Id3 knockout mice showed attenuated increases in BMI and visceral fat mass. We hypothesized that the ID3 missense variant (rs11574-A) would lead to an attenuated increase over time in fat mass, BMI, waist circumference (WC), and waist-hip ratio (WHR) in humans. METHODS The genotyped study populations included the Obesity Research Group - Genetics (ORGGEN) cohort, a cohort of men with obesity (N = 716) and of randomly selected men (N = 826) from the Danish draft register who were examined at mean ages of 20 and 46 years, and the Inter99 (N = 6,116) and Health2006 (N = 2,761) cohorts, two population-based samples of middle-aged people, followed up after 5 years. RESULTS In meta-analyses of all data, no association was found between rs11574-A and changes in BMI, WC, WHR, or fat mass. We found an association between rs11574-A and cross-sectional BMI (N = 10,359, β: -0.16 kg/m2 per allele, 95% CI: -0.30 to -0.01, P = 0.033) and fat mass (N = 4,188, β: -0.52 kg/m2 per allele, 95% CI: -1.03 to -0.01, P = 0.046). CONCLUSIONS No consistent impact of the genetic variant on changes in fat mass, BMI, or fat distribution was found in three Danish cohorts.

BACKGROUND Associations between dairy intake and body mass index (BMI) have been inconsistently observed in epidemiological studies, and the causal relationship remains ill defined. METHODS We performed Mendelian randomization (MR) analysis using an established dairy intake-associated genetic polymorphism located upstream of the lactase gene (LCT-13910 C/T, rs4988235) as an instrumental variable (IV). Linear regression models were fitted to analyze associations between (a) dairy intake and BMI, (b) rs4988235 and dairy intake, and (c) rs4988235 and BMI in each study. The causal effect of dairy intake on BMI was quantified by IV estimators among 184802 participants from 25 studies. RESULTS Higher dairy intake was associated with higher BMI (β = 0.03 kg/m2 per serving/day; 95% CI, 0.00–0.06; P = 0.04), whereas the LCT genotype with 1 or 2 T allele was significantly associated with 0.20 (95% CI, 0.14–0.25) serving/day higher dairy intake (P = 3.15 × 10−12) and 0.12 (95% CI, 0.06–0.17) kg/m2 higher BMI (P = 2.11 × 10−5). MR analysis showed that the genetically determined higher dairy intake was significantly associated with higher BMI (β = 0.60 kg/m2 per serving/day; 95% CI, 0.27–0.92; P = 3.0 × 10−4). CONCLUSIONS The present study provides strong evidence to support a causal effect of higher dairy intake on increased BMI among adults.

During the past 7 years, genome-wide association studies have shed light on the contribution of common genomic variants to the genetic architecture of type 2 diabetes, obesity and related intermediate phenotypes. The discoveries have firmly established more than 175 genomic loci associated with these phenotypes. Despite the tight correlation between type 2 diabetes and obesity, these conditions do not appear to share a common genetic background, since they have few genetic risk loci in common. The recent genetic discoveries do however highlight specific details of the interplay between the pathogenesis of type 2 diabetes, insulin resistance and obesity. The focus is currently shifting towards investigations of data from targeted array-based genotyping and exome and genome sequencing to study the individual and combined effect of low-frequency and rare variants in metabolic disease. Here we review recent progress as regards the concepts, methodologies and derived outcomes of studies of the genetics of type 2 diabetes and obesity, and discuss avenues to be investigated in the future within this research field.

The mechanistic link between the FTO locus and risk of obesity has remained elusive. However, a new study presents compelling evidence suggesting that the browning of white adipocytes into beige adipocytes (together with regulation of thermogenesis), might be an important and potentially modifiable pathway for development of obesity therapeutics.

Meta-analyses have suggested an effect of MTHFR C677T genotype (rs1801133), a proxy for blood total homocysteine, on cardiovascular disease (CVD) in populations with low population dietary folate. The aim was to examine the association and effect modification by serum folate and vitamin B12 levels between MTHFR and CVD-related outcomes in a general population with no mandatory folic acid fortification policy. The study population included 13,748 adults retrieved from pooling of four population-based studies conducted in Denmark. MTHFR genotype, serum folate (measured in approximately 9,356 individuals), and serum vitamin B12 (9,215 individuals), hypertension, and dyslipidemia were measured at baseline, and participants were followed for a mean of 10.5-11.7 years in central registries for diagnoses of stroke (623 incidents), ischaemic heart disease (IHD) (835 incidents), and all-cause mortality (1,272 incidents). The MTHFR genotype (TT vs. CC/CT) was not associated with hypertension [OR (95 % CI) 1.09 (0.95-1.25)], dyslipidemia [OR (95 % CI) 0.97 (0.84-1.11)], stroke [HR (95 % CI) 0.92 (0.69-1.23)], and all-cause mortality [HR (95 % CI) 0.94 (0.77-1.14)], either overall, or in participants with low serum folate or B12 status (P values for interactions 0.15-0.94). Individuals with the MTHFR TT genotype had a higher risk of IHD (HR (95 % CI) 1.38 (1.11-1.71)), but this association was not modified by folate status (P value for interaction 0.45). Our results do not support a causal relationship between homocysteine and CVD. However, we cannot exclude a direct causal effect of MTHFR C677T genotype on IHD. Purpose: Meta-analyses have suggested an effect of MTHFR C677T genotype (rs1801133), a proxy for blood total homocysteine, on cardiovascular disease (CVD) in populations with low population dietary folate. The aim was to examine the association and effect modification by serum folate and vitamin B12 levels between MTHFR and CVD-related outcomes in a general population with no mandatory folic acid fortification policy.Methods: The study population included 13,748 adults retrieved from pooling of four population-based studies conducted in Denmark. MTHFR genotype, serum folate (measured in approximately 9,356 individuals), and serum vitamin B12 (9,215 individuals), hypertension, and dyslipidemia were measured at baseline, and participants were followed for a mean of 10.5–11.7 years in central registries for diagnoses of stroke (623 incidents), ischaemic heart disease (IHD) (835 incidents), and all-cause mortality (1,272 incidents).Results: The MTHFR genotype (TT vs. CC/CT) was not associated with hypertension [OR (95 % CI) 1.09 (0.95–1.25)], dyslipidemia [OR (95 % CI) 0.97 (0.84–1.11)], stroke [HR (95 % CI) 0.92 (0.69–1.23)], and all-cause mortality [HR (95 % CI) 0.94 (0.77–1.14)], either overall, or in participants with low serum folate or B12 status (P values for interactions 0.15–0.94). Individuals with the MTHFR TT genotype had a higher risk of IHD (HR (95 % CI) 1.38 (1.11–1.71)), but this association was not modified by folate status (P value for interaction 0.45).Conclusions: Our results do not support a causal relationship between homocysteine and CVD. However, we cannot exclude a direct causal effect of MTHFR C677T genotype on IHD.

Blood concentrations of triglycerides are influenced by genetic factors as well as a number of environmental factors, including adiposity and glucose homeostasis. The aim was to investigate the association between a serum triglyceride weighted genetic risk score (wGRS) and changes in fasting serum triglyceride level over 5 years and to test whether the effect of the wGRS was modified by 5 year changes of adiposity, insulin resistance, and lifestyle factors. A total of 3,474 nondiabetic individuals from the Danish Inter99 cohort participated in both the baseline and 5 year follow-up physical examinations and had information on the wGRS comprising 39 genetic variants. In a linear regression model adjusted for age, sex, and baseline serum triglyceride, the wGRS was associated with increased serum triglyceride levels over 5 years [per allele effect = 1.3% (1.0.1.6%); P = 1.0 ∼ 10 -17]. This triglyceride-increasing effect of the wGRS interacted with changes in insulin resistance (P interaction= 1.5 ∼ 10 -6). This interaction indicated that the effect of the wGRS was stronger in individuals who became more insulin resistant over 5 years. In conclusion, our findings suggest that increased genetic risk load is associated with a larger increase in fasting serum triglyceride levels in nondiabetic individuals during 5 years of follow-up. This effect of the wGRS is accentuated by increasing insulin resistance.

OBJECTIVE Genome-wide association studies and linkage studies have identified 20 validated genetic variants associated with obesity and/or related phenotypes. The variants are common, and they individually exhibit small-to-modest effect sizes. RESEARCH DESIGN AND METHODS In this study we investigate the combined effect of these variants and their ability to discriminate between normal weight and overweight/obese individuals. We applied receiver operating characteristics (ROC) curves, and estimated the area under the ROC curve (AUC) as a measure of the discriminatory ability. The analyses were performed cross-sectionally in the population-based Inter99 cohort where 1,725 normal weight, 1,519 overweight, and 681 obese individuals were successfully genotyped for all 20 variants. RESULTS When combining all variants, the 10% of the study participants who carried more than 22 risk-alleles showed a significant increase in probability of being both overweight with an odds ratio of 2.00 (1.47–2.72), P = 4.0 × 10−5, and obese with an OR of 2.62 (1.76–3.92), P = 6.4 × 10−7, compared with the 10% of the study participants who carried less than 14 risk-alleles. Discrimination ability for overweight and obesity, using the 20 single nucleotide polymorphisms (SNPs), was determined to AUCs of 0.53 and 0.58, respectively. When combining SNP data with conventional nongenetic risk factors of obesity, the discrimination ability increased to 0.64 for overweight and 0.69 for obesity. The latter is significantly higher (P < 0.001) than for the nongenetic factors alone (AUC = 0.67). CONCLUSIONS The discriminative value of the 20 validated common obesity variants is at present time sparse and too weak for clinical utility, however, they add to increase the discrimination ability of conventional nongenetic risk factors.

Forty-nine known single nucleotide polymorphisms (SNPs) associating with body mass index (BMI)-adjusted waist-hip-ratio (WHR) (WHRadjBMI) were recently suggested to cluster into three groups with different associations to cardiometabolic traits. Genetic risk scores of the clusters on the risk of incident diabetes and associations with detailed cardiometabolic phenotypes were tested.In a prospective study of 6,121 Inter99 individuals, the risk of incident diabetes using Cox proportional hazards regression was evaluated. Using linear regession, the associations between genetic risk scores and anthropometry and blood samples at fasting and during an oral glucose tolerance test were tested. Analyses were adjusted for age, sex, and BMI.Cluster 1 associated with an increased risk of diabetes (HR = 1.05, P = 2.74 × 10(-) (4) ) and with a poor metabolic profile, including fasting serum triglyceride (β = 0.98% mmol/L, P = 3.33 × 10(-) (8) ) and Matsuda index (β = -0.74%, P = 1.29 × 10(-) (4) ). No similar associations for Clusters 2 and 3 were found. The three clusters showed different patterns of association with waist circumference, hip circumference, and height.Our results suggest that the 49 WHRadjBMI-associated SNPs affect metabolic health differently depending on the cluster of SNPs. The clusters further associate differently with anthropometric measures.

The decade anniversary for genome-wide association studies (GWAS) is approaching, and this experimental approach has commenced a deeper understanding of the genetics underlying complex diseases. In obesity genetics the GIANT (Genetic Investigation of ANthropometric Traits) consortium has played a crucial role, recently with two comprehensive meta-analyses, one focusing on general obesity, analyzing body-mass index (BMI) and the other on fat distribution, focusing on waist-hip ratio adjusted for BMI. With the in silico methods applied in these two studies as the pivot, this review looks into some of the biological knowledge, beginning to emerge from the intricate genomic background behind the genetic determinants of human adiposity. These include synaptic dysfunction, where GWAS pinpoint potential new mechanisms in pathways already known to be linked with obesity.

Context: Type 2 diabetes (T2D) prevalence is spiraling globally, and knowledge of its pathophysiological signatures is crucial for a better understanding and treatment of the disease. Objective: We aimed to discover underlying coding genetic variants influencing fasting serum levels of nine biomarkers associated with T2D: adiponectin, C-reactive protein, ferritin, heat shock 70-kDa protein 1B, IGF binding protein 1 and IGF binding protein 2, IL-18, IL-2 receptor-α, and leptin. Design and Participants: A population-based sample of 6215 adult Danes was genotyped for 16 340 coding single-nucleotide polymorphisms and were tested for association with each biomarker. Identified loci were tested for association with T2D through a large-scale meta-analysis involving up to 17 024 T2D cases and up to 64 186 controls. Results: We discovered 11 associations between single-nucleotide polymorphisms and five distinct biomarkers at a study-wide P < 3.4 × 10−7. Nine associations were novel: IL18: BIRC6, RAD17, MARVELD2; ferritin: F5; IGF binding protein 1: SERPING1, KLKB, GCKR, CELSR2, and heat shock 70-kDa protein 1B: CFH. Three of the identified loci (CELSR2, HNF1A, and GCKR) were significantly associated with T2D, of which the association with the CELSR2 locus has not been shown previously. Conclusion: The identified loci influence processes related to insulin signaling, cell communication, immune function, apoptosis, DNA repair, and oxidative stress, all of which could provide a rationale for novel diabetes therapeutic strategies.

AIMS/HYPOTHESIS: Elevated serum ferritin levels are associated with an increased risk of type 2 diabetes, but the nature of this association remains elusive. The aim of this study was to test the hypothesis that an elevated fasting serum ferritin level is associated with an increased risk of type 2 diabetes due to its association with impaired beta cell function and decreased insulin sensitivity.METHODS: We investigated 6,392 individuals from the Danish general population. Surrogate measures of beta cell function and insulin sensitivity were calculated for approximately 6,100 individuals based on OGTT examinations.RESULTS: The ORs for type 2 diabetes were 4.2 (95% CI 2.4, 7.2) for the highest vs the lowest quintile of serum ferritin, and 17 (95% CI 8.9, 33) for serum ferritin levels ≥97.5th percentile vs CONCLUSIONS/INTERPRETATION: Elevated fasting serum ferritin levels are associated with surrogate measures of both impaired beta cell function and decreased insulin sensitivity. Menopause seems to modify the association with insulin sensitivity.

Background— There are several well-established lifestyle factors influencing dyslipidemia and currently; 157 genetic susceptibility loci have been reported to be associated with serum lipid levels at genome-wide statistical significance. However, the interplay between lifestyle risk factors and these susceptibility loci has not been fully elucidated. We tested whether genetic risk scores (GRS) of lipid-associated single nucleotide polymorphisms associate with fasting serum lipid traits and whether the effects are modulated by lifestyle factors or estimates of metabolic health. Methods and Results— The single nucleotide polymorphisms were genotyped in 2 Danish cohorts: inter99 (n=5961) for discovery analyses and Health2006 (n=2565) for replication. On the basis of published effect sizes of single nucleotide polymorphisms associated with circulating fasting levels of total cholesterol, low-density lipoprotein-cholesterol, high-density lipoprotein-cholesterol, or triglyceride, 4 weighted GRS were constructed. In a cross-sectional design, we investigated whether the effect of these weighted GRSs on lipid levels were modulated by diet, alcohol consumption, physical activity, and smoking or the individual metabolic health status as estimated from body mass index, waist circumference, and insulin resistance assessed using homeostasis model assessment of insulin resistance. All 4 lipid weighted GRSs associated strongly with their respective trait (from P =3.3×10 –69 to P =1.1×10 –123 ). We found interactions between the triglyceride weighted GRS and body mass index and waist circumference on fasting triglyceride levels in Inter99 and replicated these findings in Health2006 ( P interaction =9.8×10 –5 and 2.0×10 –5 , respectively, in combined analysis). Conclusions— Our findings suggest that individuals who are obese may be more susceptible to the cumulative genetic burden of triglyceride single nucleotide polymorphisms. Therefore, it is suggested that especially these genetically at-risk individuals may benefit more from targeted interventions aiming at obesity prevention.

Summary The liking and selective ingestion of palatable foods—including sweets—is biologically controlled, and dysfunction of this regulation may promote unhealthy eating, obesity, and disease. The hepatokine fibroblast growth factor 21 (FGF21) reduces sweet consumption in rodents and primates, whereas knockout of Fgf21 increases sugar consumption in mice. To investigate the relevance of these findings in humans, we genotyped variants in the FGF21 locus in participants from the Danish Inter99 cohort (n = 6,514) and examined their relationship with a detailed range of food and ingestive behaviors. This revealed statistically significant associations between FGF21 rs838133 and increased consumption of candy, as well as nominal associations with increased alcohol intake and daily smoking. Moreover, in a separate clinical study, plasma FGF21 levels increased acutely after oral sucrose ingestion and were elevated in fasted sweet-disliking individuals. These data suggest the liver may secrete hormones that influence eating behavior.

Objective: Genome-wide association studies have identified genetic variants associating with BMI, however, it is un-clarified whether the same variants also influence body weight fluctuations. Methods: Among 3,982 adult individuals that attended both a baseline and a five-year follow-up examination in the Danish Inter99 intervention study, a genetic risk score (GRS) was constructed based on 30 BMI variants to address whether it is associated with body weight changes. Moreover, it was examined whether the effect of lifestyle changes was modulated by the GRS. Results: The GRS associated strongly with baseline body weight, with a per risk allele increase of 0.45 (0.33-0.58) kg (P = 52.7 x 10(-12)), corresponding to a body weight difference of 3.41 (2.21-4.60) kg comparing the highest (>= 30 risk alleles) and lowest ( Objective Genome-wide association studies have identified genetic variants associating with BMI, however, it is un-clarified whether the same variants also influence body weight fluctuations. Methods Among 3,982 adult individuals that attended both a baseline and a five-year follow-up examination in the Danish Inter99 intervention study, a genetic risk score (GRS) was constructed based on 30 BMI variants to address whether it is associated with body weight changes. Moreover, it was examined whether the effect of lifestyle changes was modulated by the GRS. Results The GRS associated strongly with baseline body weight, with a per risk allele increase of 0.45 (0.33-0.58) kg (P = 2.7 × 10 -12), corresponding to a body weight difference of 3.41 (2.21-4.60) kg comparing the highest (≥ 30 risk alleles) and lowest (≤ 26 risk alleles) risk allele tertile. No association was observed with changes in body weight during the five years. Changes in lifestyle, including physical activity, diet and smoking habits associated strongly with body weight changes, however, no interactions with the GRS was observed. Conclusion The GRS associated with body weight cross-sectionally, but not with changes over a five-year period. Body weight changes were influenced by lifestyle changes, however, independently of the GRS.

More than 40 genetic risk variants for type 2 diabetes have been validated. We aimed to test whether a genetic risk score associates with the incidence of type 2 diabetes and with 5-year changes in glycemic traits and whether the effects were modulated by changes in BMI and lifestyle. The Inter99 study population was genotyped for 46 variants, and a genetic risk score was constructed. During a median follow-up of 11 years, 327 of 5,850 individuals developed diabetes. Physical examinations and oral glucose tolerance tests were performed at baseline and after 5 years (n = 3,727). The risk of incident type 2 diabetes was increased with a hazard ratio of 1.06 (95% CI 1.03–1.08) per risk allele. While the population in general had improved glucose regulation during the 5-year follow-up period, each additional allele in the genetic risk score was associated with a relative increase in fasting, 30-min, and 120-min plasma glucose values and a relative decrease in measures of β-cell function over the 5-year period, whereas indices of insulin sensitivity were unaffected. The effect of the genetic risk score on 5-year changes in fasting plasma glucose was stronger in individuals who increased their BMI. In conclusion, a genetic risk score based on 46 variants associated strongly with incident type 2 diabetes and 5-year changes in plasma glucose and β-cell function. Individuals who gain weight may be more susceptible to the cumulative impact of type 2 diabetes risk variants on fasting plasma glucose.

Gene–lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13–0.31], P = 1.63 × 10−6). All SNPs were associated with 2-h glucose (β = 0.06–0.12 mmol/allele, P ≤ 1.53 × 10−7), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene–lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.

BACKGROUND AND AIM: Non-alcoholic fatty liver disease (NAFLD) is a common condition, associated with hepatic insulin resistance and the metabolic syndrome including hyperglycaemia and dyslipidemia. We aimed at studying the potential impact of the NAFLD-associated PNPLA3 rs738409 G-allele on NAFLD-related metabolic traits in hyperglycaemic individuals.METHODS: The rs738409 variant was genotyped in the population-based Inter99 cohort examined by an oral glucose-tolerance test, and a combined study-sample consisting of 192 twins (96 twin pairs) and a sub-set of the Inter99 population (n = 63) examined by a hyperinsulinemic euglycemic clamp (n(total) = 255). In Inter99, we analyzed associations of rs738409 with components of the WHO-defined metabolic syndrome (n = 5,847) and traits related to metabolic disease (n = 5,663). In the combined study sample we elucidated whether the rs738409 G-allele altered hepatic or peripheral insulin sensitivity. Study populations were divided into individuals with normal glucose-tolerance (NGT) and with impaired glucose regulation (IGR).RESULTS: The case-control study showed no associations with components of the metabolic syndrome or the metabolic syndrome. Among 1,357 IGR individuals, the rs738409 G-allele associated with decreased fasting serum triglyceride levels (per allele effect(β) = -9.9% [-14.4%;-4.0% (95% CI)], p = 5.1×10(-5)) and fasting total cholesterol (β = -0.2 mmol/l [-0.3;-0.01 mmol/l(95% CI)], p = 1.5×10(-4)). Meta-analyses showed no impact on hepatic or peripheral insulin resistance in carriers of the rs738409 G-allele.CONCLUSION: Our findings suggest that the G-allele of PNPLA3 rs738409 associates with reduced fasting levels of cholesterol and triglyceride in individuals with IGR.

Ruth Loos and colleagues report findings from a meta-analysis of multiple studies examining the extent to which physical activity attenuates effects of a specific gene variant, FTO, on obesity in adults and children. They report a fairly substantial attenuation by physical activity on the effects of this genetic variant on the risk of obesity in adults., Background The FTO gene harbors the strongest known susceptibility locus for obesity. While many individual studies have suggested that physical activity (PA) may attenuate the effect of FTO on obesity risk, other studies have not been able to confirm this interaction. To confirm or refute unambiguously whether PA attenuates the association of FTO with obesity risk, we meta-analyzed data from 45 studies of adults (n = 218,166) and nine studies of children and adolescents (n = 19,268). Methods and Findings All studies identified to have data on the FTO rs9939609 variant (or any proxy [r 2>0.8]) and PA were invited to participate, regardless of ethnicity or age of the participants. PA was standardized by categorizing it into a dichotomous variable (physically inactive versus active) in each study. Overall, 25% of adults and 13% of children were categorized as inactive. Interaction analyses were performed within each study by including the FTO×PA interaction term in an additive model, adjusting for age and sex. Subsequently, random effects meta-analysis was used to pool the interaction terms. In adults, the minor (A−) allele of rs9939609 increased the odds of obesity by 1.23-fold/allele (95% CI 1.20–1.26), but PA attenuated this effect (p interaction = 0.001). More specifically, the minor allele of rs9939609 increased the odds of obesity less in the physically active group (odds ratio = 1.22/allele, 95% CI 1.19–1.25) than in the inactive group (odds ratio = 1.30/allele, 95% CI 1.24–1.36). No such interaction was found in children and adolescents. Conclusions The association of the FTO risk allele with the odds of obesity is attenuated by 27% in physically active adults, highlighting the importance of PA in particular in those genetically predisposed to obesity. Please see later in the article for the Editors' Summary, Editors’ Summary Background Two in three Americans are overweight, of whom half are obese, and the trend towards increasing obesity is now seen across developed and developing countries. There has long been interest in understanding the impact of genes and environment when it comes to apportioning responsibility for obesity. Carrying a change in the FTO gene is common (found in three-quarters of Europeans and North Americans) and is associated with a 20%–30% increased risk of obesity. Some overweight or obese individuals may feel that the dice are loaded and there is little point in fighting the fat; it has been reported that those made aware of their genetic susceptibility to obesity may still choose a poor diet. A similar fatalism may occur when overweight and obese people consider physical activity. But disentangling the influence of physical activity on those genetically susceptible to obesity from other factors that might impact weight is not straightforward, as it requires large sample sizes, could be subject to publication bias, and may rely on less than ideal self-reporting methods. Why Was This Study Done? The public health ramifications of understanding the interaction between genetic susceptibility to obesity and physical activity are considerable. Tackling the rising prevalence of obesity will inevitably include interventions principally aimed at changing dietary intake and/or increasing physical activity, but the evidence for these with regards to those genetically susceptible has been lacking to date. The authors of this paper set out to explore the interaction between the commonest genetic susceptibility trait and physical activity using a rigorous meta-analysis of a large number of studies. What Did the Researchers Do and Find? The authors were concerned that a meta-analysis of published studies would be limited both by the data available to them and by possible bias. Instead of this more widely used approach, they took the literature search as their starting point, identified other studies through their collaborators’ network, and then undertook a meta-analysis of all available studies using a new and standardized analysis plan. This entailed an extremely large number of authors mining their data afresh to extract the relevant data points to enable such a meta-analysis. Physical activity was identified in the original studies in many different ways, including by self-report or by using an external measure of activity or heart rate. In order to perform the meta-analysis, participants were labeled as physically active or inactive in each study. For studies that had used a continuous scale, the authors decided that the bottom 20% of the participants were inactive (10% for children and adolescents). Using data from over 218,000 adults, the authors found that carrying a copy of the susceptibility gene increased the odds of obesity by 1.23-fold. But the size of this influence was 27% less in the genetically susceptible adults who were physically active (1.22-fold) compared to those who were physically inactive (1.30-fold). In a smaller study of about 19,000 children, no such effect of physical activity was seen. What Do these Findings Mean? This study demonstrates that people who carry the susceptibility gene for obesity can benefit from physical activity. This should inform health care professionals and the wider public that the view of genetically determined obesity not being amenable to exercise is incorrect and should be challenged. Dissemination, implementation, and ensuring uptake of effective physical activity programs remains a challenge and deserves further consideration. That the researchers treated “physically active” as a yes/no category, and how they categorized individuals, could be criticized, but this was done for pragmatic reasons, as a variety of means of assessing physical activity were used across the studies. It is unlikely that the findings would have changed if the authors had used a different method of defining physically active. Most of the studies included in the meta-analysis looked at one time point only; information about the influence of physical activity on weight changes over time in genetically susceptible individuals is only beginning to emerge. Additional Information Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001116. This study is further discussed in a PLoS Medicine Perspective by Lennert Veerman The US Centers for Disease Control and Prevention provides obesity-related statistics, details of prevention programs, and an overview on public health strategy in the United States A more worldwide view is given by the World Health Organization The UK National Health Service website gives information on physical activity guidelines for different age groups, while similar information can also be found from US sources

AIMS/HYPOTHESIS: Genome-wide association studies have identified novel WHR and BMI susceptibility loci. The aim of this study was to elucidate if any of these loci had an effect on quantitative measures of glucose homeostasis, including estimates of insulin release and insulin sensitivity in an epidemiological setting.METHODS: By applying an additive genetic model, 14 WHR-associated gene variants and 18 BMI-associated variants were investigated for their relationships with glucose-related metabolic traits in treatment-naive individuals from the population-based Inter99 study sample (n = 6,039).RESULTS: Of the variants associated with BMI, the QPCTL rs2287019 C allele was associated with an increased insulinogenic index of 7.4% per risk allele (p = 4.0 × 10⁻⁷) and increased disposition index of 5.6% (p = 6.4 × 10⁻⁵). The LRP1B rs2890652 C allele was associated with insulin resistance, showing a 3.3% increase (p = 0.0011) using the HOMA-insulin resistance (HOMA-IR) index and a 2.2% reduction (p = 0.0014) with the Matsuda index. Of the variants associated with WHR, LYPLAL1/SLC30A10 rs4846567 G allele carriers showed a 5.2% lower HOMA-IR (p = 0.00086) in women, indicating improved insulin sensitivity. Female carriers of the VEGFA rs6905288 A allele were insulin resistant, with a 3.7% increase in HOMA-IR (p = 0.00036) and 4.0% decrease in Matsuda index (p = 2 × 10⁻⁴).CONCLUSIONS: Our correlative findings from analysing single-locus data suggest that some variation in validated BMI and WHR loci are associated with either increased or decreased insulin sensitivity and thereby potentially with metabolically healthy or metabolically unhealthy subsets of obesity. The results call for testing in larger study samples and for further physiological exploration of the possible metabolic implications of these loci.

Background A genome-wide association study (GWAS) using metabolite concentrations as proxies for enzymatic activity, suggested that two variants: rs2014355 in the gene encoding short-chain acyl-coenzyme A dehydrogenase (ACADS) and rs11161510 in the gene encoding medium-chain acyl-coenzyme A dehydrogenase (ACADM) impair fatty acid β-oxidation. Chronic exposure to fatty acids due to an impaired β-oxidation may down-regulate the glucose-stimulated insulin release and result in an increased risk of type 2 diabetes (T2D). We aimed to investigate whether the two variants associate with altered insulin release following an oral glucose load or with T2D. Methods The variants were genotyped using KASPar® PCR SNP genotyping system and investigated for associations with estimates of insulin release and insulin sensitivity following an oral glucose tolerance test (OGTT) in a random sample of middle-aged Danish individuals (n ACADS = 4,324; n ACADM = 4,337). The T2D-case-control study involved a total of ~8,300 Danish individuals (n ACADS = 8,313; n ACADM = 8,344). Results In glucose-tolerant individuals the minor C-allele of rs2014355 of ACADS associated with reduced measures of serum insulin at 30 min following an oral glucose load (per allele effect (β) = -3.8% (-6.3%;-1.3%), P = 0.003), reduced incremental area under the insulin curve (β = -3.6% (-6.3%;-0.9%), P = 0.009), reduced acute insulin response (β = -2.2% (-4.2%;0.2%), P = 0.03), and with increased insulin sensitivity ISIMatsuda (β = 2.9% (0.5%;5.2%), P = 0.02). The C-allele did not associate with two other measures of insulin sensitivity or with a derived disposition index. The C-allele was not associated with T2D in the case-control analysis (OR 1.07, 95% CI 0.96-1.18, P = 0.21). rs11161510 of ACADM did not associate with any indices of glucose-stimulated insulin release or with T2D. Conclusions In glucose-tolerant individuals the minor C-allele of rs2014355 of ACADS was associated with reduced measures of glucose-stimulated insulin release during an OGTT, a finding which in part may be mediated through an impaired β-oxidation of fatty acids.

Obesity is globaLy prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined aSociations betwEn body maS index and ĝ̂1/42.8 miLion SNPs in up to 123,865 individuals with targeted foLow up of 42 SNPs in up to 125,931 aDitional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci aSociated with body maS index (P < 5-10-8), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly aSociated loci may provide new insights into human body weight regulation. © 2010 Nature America, Inc. All rights reserved.

ObjectiveLipin-1, encoded byLPIN1, is expressed in the major metabolically active tissues. Decreased expression of lipin-1 in adipose tissue correlates with increased insulin resistance, and tagging of theLPIN1locus has shown that rs33997857, rs6744682, and rs6708316 associate with metabolic phenotypes, specifically body mass index (BMI) and fasting serum lipid levels, both on the individual single-nucleotide polymorphism level and with a three-marker haplotype. Our aim was to validate the reported findings in the Danish population.DesignIn the present study, variants were analyzed inLPIN1using case–control studies, haplotype analyses, and quantitative trait analyses in a population of 17 538 Danes.MethodsThe threeLPIN1variants were genotyped in 17 538 Danes from four study populations of middle-aged people. This provided us with a statistical power >99% to replicate previous findings. Variants were analyzed individually and in haplotype combinations in studies of quantitative metabolic traits and in case–control studies.ResultsNone of the three variants were associated with the examined quantitative traits including BMI, waist circumference, blood pressure, fasting serum lipid concentrations, or plasma glucose or serum insulin concentrations in the fasting state and following an oral glucose tolerance test. Haplotypes were tested for association with quantitative traits; however, only nominal association with blood pressure (P=0.04) and waist circumference (P=0.04) was observed. In case–control studies, no association was found for individual variants or the three-marker haplotype.ConclusionLPIN1rs33997857, rs6744682, and rs6708316 did not associate with type 2 diabetes, obesity, or related quantitative metabolic phenotypes in the Danish population examined.

BACKGROUND Several obesity risk alleles affecting adult adiposity have been identified by the recent wave of genome wide association studies. We aimed to examine the potential effect of these variants on fetal body composition by investigating the variants in relation to birth weight and ponderal index of the newborn. METHODOLOGY/PRINCIPAL FINDINGS Midwife records from the Danish State Archives provided information on mother's age, parity, as well as birth weight, birth length and prematurity of the newborn in 4,744 individuals of the population-based Inter99 study. Twenty-four risk alleles showing genome-wide associations with adult BMI and/or waist circumference were genotyped. None of the 24 risk variants tested showed an association with birth weight or ponderal index after correction for multiple testing. Birth weight was divided into three categories low (≤10(th) percentile), normal (10(th)-90(th) percentile) and high birth weight (≥90th percentile) to allow for non-linear associations. There was no difference in the number of risk alleles between the groups (p = 0.57). No interactions between each risk allele and birth weight in the prediction of adult BMI were observed. An obesity risk score was created by summing up risk alleles. The risk score did not associate with fetal body composition. Moreover there was no interaction between the risk score and birth weight/ponderal index in the prediction of adult BMI. CONCLUSION 24 common variants associated with adult adiposity did not affect or interact with birth weight among Danes suggesting that the effects of these variants predominantly arise in the post-natal life.

Obesity and related complications are major health burdens. Almost 700 million adults are currently obese globally and the prevalence is predicted to rise towards 2030. The sudden change of lifestyle with physical inactivity and excessive calorie intake undoubtedly have a major part of the epidemic development; however, some individuals seem to be more prone to be affected by an unhealthy lifestyle than others. Hence, genetic predisposition also has an essential role in determining disease susceptibility and response to lifestyle factors. Since the introduction of genome-wide association studies (GWAS), the success of identifying obesity susceptibility variants have increased, and a total of 32 variants have been identified associating genome-wide significantly with body mass index (BMI) and 18 with measures of fat distribution during four overall obesity GWAS waves. However, the immediate success of the GWAS approach has eased off, but the proportion of explained variance for BMI by the identified obesity variants remains low. This review suggests and discusses new initiatives to take GWAS of obesity to the next level, including gene-environment interactions as modulating/masking factors, low-frequent or rare variants and ways to address such analyses, and finally reflections about the applicability of epigenetic modifications when elucidating the genetic background of obesity.

Aims: Genome-wide association studies have identified novel BMI/obesity associated susceptibility loci. The purpose of this study is to determine associations with overweight, obesity, morbid obesity and/or general adiposity in a Danish population. Moreover, we want to investigate if these loci associate with type 2 diabetes and to elucidate potential underlying metabolic mechanisms. Methods: 15 gene variants in 14 loci including TMEM18 (rs7561317), SH2B1 (rs7498665), KCTD15 (rs29941), NEGR1 (rs2568958), ETV5 (rs7647305), BDNF (rs4923461, rs925946), SEC16B (rs10913469), FAIM2 (rs7138803), GNPDA2 (rs10938397), MTCH2 (rs10838738), BAT2 (rs2260000), NPC1 (rs1805081), MAF (rs1424233), and PTER (rs10508503) were genotyped in 18,014 middle-aged Danes. Results: Five of the 15 gene variants associated with overweight, obesity and/or morbid obesity. Per allele ORs ranged from 1.15-1.20 for overweight, 1.10-1.25 for obesity, and 1.41-1.46 for morbid obesity. Five of the 15 variants moreover associated with increased measures of adiposity. BDNF rs4923461 displayed a borderline BMI-dependent protective effect on type 2 diabetes (0.87 (0.78-0.96, p = 0.008)), whereas SH2B1 rs7498665 associated with nominally BMI-independent increased risk of type 2 diabetes (1.16 (1.07-1.27, p = 7.8x10(-4))). Conclusions: Associations with overweight and/or obesity and measures of obesity were confirmed for seven out of the 15 gene variants. The obesity risk allele of BDNF rs4923461 protected against type 2 diabetes, which could suggest neuronal and peripheral distinctive ways of actions for the protein. SH2B1 rs7498665 associated with type 2 diabetes independently of BMI.

Lower serum vitamin B12 levels have been related to adverse metabolic health profiles, including adiposity. We used a Mendelian randomization design to test whether this relation might be causal. We included two Danish population-based studies (ntotal = 9311). Linear regression was used to test for associations between (1) serum vitamin B12 levels and body mass index (BMI), (2) genetic variants and serum vitamin B12 levels, and (3) genetic variants and BMI. The effect of a genetically determined decrease in serum vitamin B12 on BMI was estimated by instrumental variable regression. Decreased serum vitamin B12 associated with increased BMI (P