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1. Independent and combined associations between fast-food outlet exposure and genetic risk for obesity: a population-based, cross-sectional study in the UK.

Author

Burgoine T, Monsivais P, Sharp SJ, Forouhi NG, and Wareham NJ

Subjects
Adult, Body Mass Index, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Risk Factors, United Kingdom epidemiology, Fast Foods, Obesity epidemiology, Obesity genetics, Residence Characteristics
Abstract

Background: Characteristics of the built environment, such as neighbourhood fast-food outlet exposure, are increasingly recognised as risk factors for unhealthy diet and obesity. Obesity also has a genetic component, with common genetic variants explaining a substantial proportion of population-level obesity susceptibility. However, it is not known whether and to what extent associations between fast-food outlet exposure and body weight are modified by genetic predisposition to obesity., Methods: We used data from the Fenland Study, a population-based sample of 12,435 UK adults (mean age 48.6 years). We derived a genetic risk score associated with BMI (BMI-GRS) from 96 BMI-associated single nucleotide polymorphisms. Neighbourhood fast-food exposure was defined as quartiles of counts of outlets around the home address. We used multivariable regression models to estimate the associations of each exposure, independently and in combination, with measured BMI, overweight and obesity, and investigated interactions., Results: We found independent associations between BMI-GRS and risk of overweight (RR = 1.34, 95% CI 1.23-1.47) and obesity (RR = 1.73, 95% CI 1.55-1.93), and between fast-food outlet exposure and risk of obesity (highest vs lowest quartile RR = 1.58, 95% CI 1.21-2.05). There was no evidence of an interaction of fast-food outlet exposure and genetic risk on BMI (P = 0.09), risk of overweight (P = 0.51), or risk of obesity (P = 0.27). The combination of higher BMI-GRS and highest fast-food outlet exposure was associated with 2.70 (95% CI 1.99-3.66) times greater risk of obesity., Conclusions: Our study demonstrated independent associations of both genetic obesity risk and neighbourhood fast-food outlet exposure with adiposity. These important drivers of the obesity epidemic have to date been studied in isolation. Neighbourhood fast-food outlet exposure remains a potential target of policy intervention to prevent obesity and promote the public's health.

Published
2021
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2. Third-wave cognitive behaviour therapies for weight management: A systematic review and network meta-analysis.

Author

Lawlor ER, Islam N, Bates S, Griffin SJ, Hill AJ, Hughes CA, Sharp SJ, and Ahern AL

Subjects
Humans, Network Meta-Analysis, Obesity psychology, Overweight psychology, Body Weight, Cognitive Behavioral Therapy methods, Obesity therapy, Overweight therapy
Abstract

This systematic review and network meta-analysis synthesized evidence on the effects of third-wave cognitive behaviour therapies (3wCBT) on body weight, and psychological and physical health outcomes in adults with overweight or obesity. Studies that included a 3wCBT for the purposes of weight management and measured weight or body mass index (BMI) pre-intervention and ≥ 3 months post-baseline were identified through database searches (MEDLINE, CINAHL, Embase, Cochrane database [CENTRAL], PsycINFO, AMED, ASSIA, and Web of Science). Thirty-seven studies were eligible; 21 were randomized controlled trials (RCT) and included in the network meta-analyses. Risk of bias was assessed using RoB2, and evidence quality was assessed using GRADE. Random-effects pairwise meta-analysis found moderate- to high-quality evidence suggesting that 3wCBT had greater weight loss than standard behavioural treatment (SBT) at post-intervention (standardized mean difference [SMD]: -0.09, 95% confidence interval [CI]: -0.22, 0.04; N = 19; I 2 = 32%), 12 months (SMD: -0.17, 95% CI: -0.36, 0.02; N = 5; I 2 = 33%), and 24 months (SMD: -0.21, 95% CI: -0.42, 0.00; N = 2; I 2 = 0%). Network meta-analysis compared the relative effectiveness of different types of 3wCBT that were not tested in head-to-head trials up to 18 months. Acceptance and commitment therapy (ACT)-based interventions had the most consistent evidence of effectiveness. Only ACT had RCT evidence of effectiveness beyond 18 months. Meta-regression did not identify any specific intervention characteristics (dose, duration, delivery) that were associated with greater weight loss. Evidence supports the use of 3wCBT for weight management, specifically ACT. Larger trials with long-term follow-up are needed to identify who these interventions work for, their most effective components, and the most cost-effective method of delivery., (© 2020 The Authors. Obesity Reviews published by John Wiley & Sons Ltd on behalf of World Obesity Federation.)

Published
2020
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3. Human Gain-of-Function MC4R Variants Show Signaling Bias and Protect against Obesity.

Author

Lotta LA, Mokrosiński J, Mendes de Oliveira E, Li C, Sharp SJ, Luan J, Brouwers B, Ayinampudi V, Bowker N, Kerrison N, Kaimakis V, Hoult D, Stewart ID, Wheeler E, Day FR, Perry JRB, Langenberg C, Wareham NJ, and Farooqi IS

Subjects
Adult, Aged, Body Mass Index, Coronary Artery Disease complications, Coronary Artery Disease metabolism, Coronary Artery Disease pathology, Cyclic AMP metabolism, Databases, Factual, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 metabolism, Diabetes Mellitus, Type 2 pathology, Female, GTP-Binding Protein alpha Subunits, Gs metabolism, Genetic Predisposition to Disease, Genotype, Humans, Male, Middle Aged, Obesity complications, Obesity metabolism, Polymorphism, Single Nucleotide, Receptor, Melanocortin, Type 4 chemistry, Receptor, Melanocortin, Type 4 metabolism, beta-Arrestins metabolism, Gain of Function Mutation genetics, Obesity pathology, Receptor, Melanocortin, Type 4 genetics, Signal Transduction
Abstract

The melanocortin 4 receptor (MC4R) is a G protein-coupled receptor whose disruption causes obesity. We functionally characterized 61 MC4R variants identified in 0.5 million people from UK Biobank and examined their associations with body mass index (BMI) and obesity-related cardiometabolic diseases. We found that the maximal efficacy of β-arrestin recruitment to MC4R, rather than canonical Gα s -mediated cyclic adenosine-monophosphate production, explained 88% of the variance in the association of MC4R variants with BMI. While most MC4R variants caused loss of function, a subset caused gain of function; these variants were associated with significantly lower BMI and lower odds of obesity, type 2 diabetes, and coronary artery disease. Protective associations were driven by MC4R variants exhibiting signaling bias toward β-arrestin recruitment and increased mitogen-activated protein kinase pathway activation. Harnessing β-arrestin-biased MC4R signaling may represent an effective strategy for weight loss and the treatment of obesity-related cardiometabolic diseases., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2019
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4. Independent and joint associations of grip strength and adiposity with all-cause and cardiovascular disease mortality in 403,199 adults: the UK Biobank study.

Author

Kim Y, Wijndaele K, Lee DC, Sharp SJ, Wareham N, and Brage S

Subjects
Adiposity, Adult, Aged, Cardiovascular Diseases physiopathology, Cause of Death, Female, Humans, Male, Middle Aged, Obesity physiopathology, Prospective Studies, Risk, United Kingdom epidemiology, Body Mass Index, Cardiovascular Diseases mortality, Hand Strength, Muscle, Skeletal physiopathology, Obesity mortality
Abstract

Background: Higher grip strength (GS) is associated with lower mortality risk. However, whether this association is independent of adiposity is uncertain. Objective: The purpose of this study was to examine the associations between GS, adiposity, and mortality. Design: The UK Biobank study is an ongoing prospective cohort of >0.5 million UK adults aged 40-69 y. Baseline data collection (2006-2010) included measurements of GS and adiposity indicators, including body mass index (BMI; in kg/m 2 ). Age- and sex-specific GS quintiles were used. BMI was classified according to clinical cutoffs. Results: Data from 403,199 participants were included in analyses. Over a median 7.0-y of follow-up, 8287 all-cause deaths occurred. The highest GS quintile had 32% (95% CI: 26%, 38%) and 25% (95% CI: 16%, 33%) lower all-cause mortality risks for men and women, respectively, compared with the lowest GS quintile, after adjustment for confounders and BMI. Obesity class II (BMI ≥35) was associated with a greater all-cause mortality risk. The highest GS quintile and obesity class II category showed relatively higher all-cause mortality hazards (not statistically significant in men) than the highest GS quintile and the normal weight category; however, the increased risk was relatively lower than the risk for the lowest GS quintile and obesity class II category. All-cause mortality risks were generally lower for obese but stronger individuals than for nonobese but weaker individuals. Similar patterns of associations were observed for cardiovascular mortality. Conclusions: Lower grip strength and excess adiposity are both independent predictors of higher mortality risk. The higher mortality risk associated with excess adiposity is attenuated, although not completely attenuated, by greater GS. Interventions and policies should focus on improving the muscular strength of the population regardless of their degree of adiposity., (© 2017 American Society for Nutrition.)

Published
2017
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5. Integrative genomic analysis implicates limited peripheral adipose storage capacity in the pathogenesis of human insulin resistance.

Author

Lotta LA, Gulati P, Day FR, Payne F, Ongen H, van de Bunt M, Gaulton KJ, Eicher JD, Sharp SJ, Luan J, De Lucia Rolfe E, Stewart ID, Wheeler E, Willems SM, Adams C, Yaghootkar H, Forouhi NG, Khaw KT, Johnson AD, Semple RK, Frayling T, Perry JR, Dermitzakis E, McCarthy MI, Barroso I, Wareham NJ, Savage DB, Langenberg C, O'Rahilly S, and Scott RA

Subjects
Adipose Tissue metabolism, Animals, Blood Glucose analysis, Body Mass Index, Case-Control Studies, Disease Models, Animal, Female, Genome-Wide Association Study, Humans, Male, Mice, Obesity genetics, Phenotype, Adipose Tissue pathology, Cardiovascular Diseases physiopathology, Genomics methods, Insulin Resistance genetics, Metabolic Diseases physiopathology, Obesity complications
Abstract

Insulin resistance is a key mediator of obesity-related cardiometabolic disease, yet the mechanisms underlying this link remain obscure. Using an integrative genomic approach, we identify 53 genomic regions associated with insulin resistance phenotypes (higher fasting insulin levels adjusted for BMI, lower HDL cholesterol levels and higher triglyceride levels) and provide evidence that their link with higher cardiometabolic risk is underpinned by an association with lower adipose mass in peripheral compartments. Using these 53 loci, we show a polygenic contribution to familial partial lipodystrophy type 1, a severe form of insulin resistance, and highlight shared molecular mechanisms in common/mild and rare/severe insulin resistance. Population-level genetic analyses combined with experiments in cellular models implicate CCDC92, DNAH10 and L3MBTL3 as previously unrecognized molecules influencing adipocyte differentiation. Our findings support the notion that limited storage capacity of peripheral adipose tissue is an important etiological component in insulin-resistant cardiometabolic disease and highlight genes and mechanisms underpinning this link.

Published
2017
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6. Physical activity, sedentary time and gain in overall and central body fat: 7-year follow-up of the ProActive trial cohort.

Author

Golubic R, Wijndaele K, Sharp SJ, Simmons RK, Griffin SJ, Wareham NJ, Ekelund U, and Brage S

Subjects
Accelerometry, Adiposity, Adult, Cardiovascular Diseases etiology, Cardiovascular Diseases metabolism, Cohort Studies, Diabetes Mellitus, Type 2 etiology, Diabetes Mellitus, Type 2 metabolism, Evidence-Based Medicine, Female, Follow-Up Studies, Health Knowledge, Attitudes, Practice, Health Promotion, Humans, Male, Obesity complications, Obesity metabolism, Risk Factors, Time Factors, Waist Circumference, Cardiovascular Diseases prevention & control, Diabetes Mellitus, Type 2 prevention & control, Exercise, Obesity prevention & control, Sedentary Behavior, Weight Gain
Abstract

Objective: The objective of this study is to examine the independent associations of time spent in moderate-to-vigorous physical activity (MVPA) and sedentary (SED-time), with total and abdominal body fat (BF), and the bidirectionality of these associations in adults at high risk of type 2 diabetes., Design and Subjects: We measured MVPA (min per day) and SED-time (h per day) by accelerometry, and indices of total (body weight, fat mass (FM), BF% and FM index) and abdominal BF (waist circumference (WC)) using standard procedures in 231 adults (41.3 ± 6.4 years) with parental history of type 2 diabetes (ProActive UK) at baseline, 1-year and 7-year follow-up. Mixed effects models were used to quantify the independent associations (expressed as standardised β-coefficients (95% confidence interval (CI))) of MVPA and SED-time with fat indices, using data from all three time points. All models were adjusted for age, sex, intervention arm, monitor wear time, follow-up time, smoking status, socioeconomic status and MVPA/SED-time., Results: MVPA was inversely and independently associated with all indices of total BF (for example, 1 s.d. higher MVPA was associated with a reduction in FM, β = -0.09 (95% CI: -0.14, -0.04) s.d.) and abdominal BF (for example, WC: β = -0.07 (-0.12, -0.02)). Similarly, higher fat indices were independently associated with a reduction in MVPA (for example, WC: β = -0.25 (-0.36, -0.15); FM: β = -0.27 (-0.36, -0.18)). SED-time was positively and independently associated with most fat indices (for example, WC: β = 0.03 (-0.04, 0.09); FM: β = 0.10 (0.03, 0.17)). Higher values of all fat indices independently predicted longer SED-time (for example, WC: β = 0.10 (0.02, 0.18), FM: β = 0.15 (0.07, 0.22))., Conclusions: The associations of MVPA and SED-time with total and abdominal BF are bidirectional and independent among individuals at high risk for type 2 diabetes. The association between BF and MVPA is stronger than the reciprocal association, highlighting the importance of considering BF as a determinant of decreasing activity and a potential consequence. Promoting more MVPA and less SED-time may reduce total and abdominal BF.

Published
2015
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7. Prevalence and correlates of screen time in youth: an international perspective.

Author

Atkin AJ, Sharp SJ, Corder K, and van Sluijs EM

Subjects
Adolescent, Child, Child, Preschool, Educational Status, Ethnicity, Female, Global Health, Humans, Male, Mental Health, Prevalence, Risk Assessment, Risk Factors, Sex Factors, Time Factors, Adolescent Behavior ethnology, Adolescent Behavior physiology, Attitude to Computers ethnology, Child Behavior ethnology, Child Behavior physiology, Computers statistics & numerical data, Obesity epidemiology, Obesity etiology, Obesity prevention & control, Television statistics & numerical data
Abstract

Background: Screen time (including TV viewing/computer use) may be adversely associated with metabolic and mental health in children., Purpose: To describe the prevalence and sociodemographic correlates of screen time in an international sample of children aged 4-17 years., Methods: Data from the International Children's Accelerometry Database were collected between 1997-2009 and analyzed in 2013. Participants were 11,434 children (48.9% boys; mean [SD] age at first assessment, 11.7 [3.2] years). Exposures were sex, age, weight status, maternal education, and ethnicity. The outcome was self- or proxy-reported screen time <2 or >2 hours/day. Analyses were conducted initially at study level and then combined using random-effects meta-analysis., Results: Within each contributing study, at least two thirds of participants exceeded 2 hours/day of screen time. In meta-analytic models, overweight or obese children were more likely to exceed 2 hours/day of screen time than those who were non-overweight (OR=1.58, 95% CI=1.33,1.88). Girls (vs boys: 0.65; 0.54, 0.78) and participants with more highly educated mothers (vs

Published
2014
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8. Common genetic variants highlight the role of insulin resistance and body fat distribution in type 2 diabetes, independent of obesity.

Author

Scott RA, Fall T, Pasko D, Barker A, Sharp SJ, Arriola L, Balkau B, Barricarte A, Barroso I, Boeing H, Clavel-Chapelon F, Crowe FL, Dekker JM, Fagherazzi G, Ferrannini E, Forouhi NG, Franks PW, Gavrila D, Giedraitis V, Grioni S, Groop LC, Kaaks R, Key TJ, Kühn T, Lotta LA, Nilsson PM, Overvad K, Palli D, Panico S, Quirós JR, Rolandsson O, Roswall N, Sacerdote C, Sala N, Sánchez MJ, Schulze MB, Siddiq A, Slimani N, Sluijs I, Spijkerman AM, Tjonneland A, Tumino R, van der A DL, Yaghootkar H, McCarthy MI, Semple RK, Riboli E, Walker M, Ingelsson E, Frayling TM, Savage DB, Langenberg C, and Wareham NJ

Subjects
Adult, Aged, Alanine Transaminase metabolism, Body Fat Distribution, Body Mass Index, Cohort Studies, Diabetes Mellitus, Type 2 metabolism, Female, Genetic Predisposition to Disease, Genetic Variation, Glucose Clamp Technique, Glucose Tolerance Test, Humans, Insulin Secretion, Male, Middle Aged, Overweight metabolism, Polymorphism, Single Nucleotide, Waist Circumference genetics, gamma-Glutamyltransferase metabolism, Body Composition genetics, Diabetes Mellitus, Type 2 genetics, Insulin metabolism, Insulin Resistance genetics, Obesity metabolism
Abstract

We aimed to validate genetic variants as instruments for insulin resistance and secretion, to characterize their association with intermediate phenotypes, and to investigate their role in type 2 diabetes (T2D) risk among normal-weight, overweight, and obese individuals. We investigated the association of genetic scores with euglycemic-hyperinsulinemic clamp- and oral glucose tolerance test-based measures of insulin resistance and secretion and a range of metabolic measures in up to 18,565 individuals. We also studied their association with T2D risk among normal-weight, overweight, and obese individuals in up to 8,124 incident T2D cases. The insulin resistance score was associated with lower insulin sensitivity measured by M/I value (β in SDs per allele [95% CI], -0.03 [-0.04, -0.01]; P = 0.004). This score was associated with lower BMI (-0.01 [-0.01, -0.0]; P = 0.02) and gluteofemoral fat mass (-0.03 [-0.05, -0.02; P = 1.4 × 10(-6)) and with higher alanine transaminase (0.02 [0.01, 0.03]; P = 0.002) and γ-glutamyl transferase (0.02 [0.01, 0.03]; P = 0.001). While the secretion score had a stronger association with T2D in leaner individuals (Pinteraction = 0.001), we saw no difference in the association of the insulin resistance score with T2D among BMI or waist strata (Pinteraction > 0.31). While insulin resistance is often considered secondary to obesity, the association of the insulin resistance score with lower BMI and adiposity and with incident T2D even among individuals of normal weight highlights the role of insulin resistance and ectopic fat distribution in T2D, independently of body size., (© 2014 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

Published
2014
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9. Dietary protein intake and incidence of type 2 diabetes in Europe: the EPIC-InterAct Case-Cohort Study.

Author

van Nielen M, Feskens EJ, Mensink M, Sluijs I, Molina E, Amiano P, Ardanaz E, Balkau B, Beulens JW, Boeing H, Clavel-Chapelon F, Fagherazzi G, Franks PW, Halkjaer J, Huerta JM, Katzke V, Key TJ, Khaw KT, Krogh V, Kühn T, Menéndez VV, Nilsson P, Overvad K, Palli D, Panico S, Rolandsson O, Romieu I, Sacerdote C, Sánchez MJ, Schulze MB, Spijkerman AM, Tjonneland A, Tumino R, van der A DL, Würtz AM, Zamora-Ros R, Langenberg C, Sharp SJ, Forouhi NG, Riboli E, and Wareham NJ

Subjects
Adult, Animals, Cohort Studies, Europe epidemiology, Female, Follow-Up Studies, Humans, Incidence, Male, Meat, Middle Aged, Prospective Studies, Risk, Risk Factors, Diabetes Mellitus, Type 2 epidemiology, Diet, Dietary Proteins administration & dosage, Obesity complications
Abstract

Objective: The long-term association between dietary protein and type 2 diabetes incidence is uncertain. We aimed to investigate the association between total, animal, and plant protein intake and the incidence of type 2 diabetes., Research Design and Methods: The prospective European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study consists of 12,403 incident type 2 diabetes cases and a stratified subcohort of 16,154 individuals from eight European countries, with an average follow-up time of 12.0 years. Pooled country-specific hazard ratios (HRs) and 95% CI of prentice-weighted Cox regression analyses were used to estimate type 2 diabetes incidence according to protein intake., Results: After adjustment for important diabetes risk factors and dietary factors, the incidence of type 2 diabetes was higher in those with high intake of total protein (per 10 g: HR 1.06 [95% CI 1.02-1.09], P(trend) < 0.001) and animal protein (per 10 g: 1.05 [1.02-1.08], P(trend) = 0.001). Effect modification by sex (P < 0.001) and BMI among women (P < 0.001) was observed. Compared with the overall analyses, associations were stronger in women, more specifically obese women with a BMI >30 kg/m(2) (per 10 g animal protein: 1.19 [1.09-1.32]), and nonsignificant in men. Plant protein intake was not associated with type 2 diabetes (per 10 g: 1.04 [0.93-1.16], P(trend) = 0.098)., Conclusions: High total and animal protein intake was associated with a modest elevated risk of type 2 diabetes in a large cohort of European adults. In view of the rapidly increasing prevalence of type 2 diabetes, limiting iso-energetic diets high in dietary proteins, particularly from animal sources, should be considered., (© 2014 by the American Diabetes Association.)

Published
2014
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10. Prediction of measured weight from self-reported weight was not improved after stratification by body mass index.

Author

May AM, Barnes DR, Forouhi NG, Luben R, Khaw KT, Wareham NJ, Peeters PH, and Sharp SJ

Subjects
Aged, Female, Humans, Linear Models, Male, Middle Aged, Overweight, Reference Values, Reproducibility of Results, Sex Factors, Body Mass Index, Body Weight, Models, Biological, Obesity, Self Report
Abstract

Objective: Self-reported weight may underestimate measured weight. Researchers have tried to reduce the error using statistical models to predict weight from self-reported weight. We investigate whether deriving equations within separate BMI categories improves the prediction of weight compared with an equation derived regardless of an individual's BMI., Design and Methods: The analysis included self-reported and measured data from 20,536 individuals participating in the EPIC-Norfolk study. In a derivation set (n = 15,381) two approaches were used to predict weight from self-reported weight: (1) using a linear regression model with measured weight as outcome and self-reported weight and age as predictors, and (2) using the same model fit separately within 3 strata defined by BMI (< 25, 25-30, ≥ 30 kg m(-2) ). The performance of these approaches was assessed in a validation set (n = 5,155). Measured weight was compared to self-reported weight and predicted weight., Results: Self-reported weight underestimated measured weight (P < 0.0001): mean difference -1.2 ± 3.1 kg (men), -1.3 ± 2.5 kg (women). Underestimation was greater in obese participants (P < 0.0001). Predicted weight using approach 1 was not significantly different from measured weight (P < 0.05). However, in individuals with BMI < 25 kg m(-2) , weight was overestimated in men (0.90 ± 3.87 kg) and women (0.57 ± 2.06 kg), but underestimated in overweight (-0.29 ± 3.58, -0.20 ± 2.62 kg) and obese (-1.46 ± 5.05 kg, -0.73 ± 3.54 kg) men and women., Conclusions: Using separate prediction equations in strata of BMI did not further improve prediction of weight. In conclusion, predicted weight was closer to measured weight compared with self-reported weight, but using equations derived in strata of BMI did not further improve the prediction and are not recommended for prediction of weight., (Copyright © 2012 The Obesity Society.)

Published
2013
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11. Long-term risk of incident type 2 diabetes and measures of overall and regional obesity: the EPIC-InterAct case-cohort study.

Author

Langenberg C, Sharp SJ, Schulze MB, Rolandsson O, Overvad K, Forouhi NG, Spranger J, Drogan D, Huerta JM, Arriola L, de Lauzon-Guillan B, Tormo MJ, Ardanaz E, Balkau B, Beulens JW, Boeing H, Bueno-de-Mesquita HB, Clavel-Chapelon F, Crowe FL, Franks PW, Gonzalez CA, Grioni S, Halkjaer J, Hallmans G, Kaaks R, Kerrison ND, Key TJ, Khaw KT, Mattiello A, Nilsson P, Norat T, Palla L, Palli D, Panico S, Quirós JR, Romaguera D, Romieu I, Sacerdote C, Sánchez MJ, Slimani N, Sluijs I, Spijkerman AM, Teucher B, Tjonneland A, Tumino R, van der A DL, van der Schouw YT, Feskens EJ, Riboli E, and Wareham NJ

Subjects
Anthropometry, Body Mass Index, Cohort Studies, Europe epidemiology, Female, Humans, Incidence, Male, Middle Aged, Proportional Hazards Models, Risk Factors, Time Factors, Waist Circumference physiology, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 epidemiology, Obesity complications, Obesity physiopathology
Abstract

Background: Waist circumference (WC) is a simple and reliable measure of fat distribution that may add to the prediction of type 2 diabetes (T2D), but previous studies have been too small to reliably quantify the relative and absolute risk of future diabetes by WC at different levels of body mass index (BMI)., Methods and Findings: The prospective InterAct case-cohort study was conducted in 26 centres in eight European countries and consists of 12,403 incident T2D cases and a stratified subcohort of 16,154 individuals from a total cohort of 340,234 participants with 3.99 million person-years of follow-up. We used Prentice-weighted Cox regression and random effects meta-analysis methods to estimate hazard ratios for T2D. Kaplan-Meier estimates of the cumulative incidence of T2D were calculated. BMI and WC were each independently associated with T2D, with WC being a stronger risk factor in women than in men. Risk increased across groups defined by BMI and WC; compared to low normal weight individuals (BMI 18.5-22.4 kg/m(2)) with a low WC (<94/80 cm in men/women), the hazard ratio of T2D was 22.0 (95% confidence interval 14.3; 33.8) in men and 31.8 (25.2; 40.2) in women with grade 2 obesity (BMI≥35 kg/m(2)) and a high WC (>102/88 cm). Among the large group of overweight individuals, WC measurement was highly informative and facilitated the identification of a subgroup of overweight people with high WC whose 10-y T2D cumulative incidence (men, 70 per 1,000 person-years; women, 44 per 1,000 person-years) was comparable to that of the obese group (50-103 per 1,000 person-years in men and 28-74 per 1,000 person-years in women)., Conclusions: WC is independently and strongly associated with T2D, particularly in women, and should be more widely measured for risk stratification. If targeted measurement is necessary for reasons of resource scarcity, measuring WC in overweight individuals may be an effective strategy, since it identifies a high-risk subgroup of individuals who could benefit from individualised preventive action.

Published
2012
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12. Physical activity attenuates the influence of FTO variants on obesity risk: a meta-analysis of 218,166 adults and 19,268 children.

Author

Kilpeläinen TO, Qi L, Brage S, Sharp SJ, Sonestedt E, Demerath E, Ahmad T, Mora S, Kaakinen M, Sandholt CH, Holzapfel C, Autenrieth CS, Hyppönen E, Cauchi S, He M, Kutalik Z, Kumari M, Stančáková A, Meidtner K, Balkau B, Tan JT, Mangino M, Timpson NJ, Song Y, Zillikens MC, Jablonski KA, Garcia ME, Johansson S, Bragg-Gresham JL, Wu Y, van Vliet-Ostaptchouk JV, Onland-Moret NC, Zimmermann E, Rivera NV, Tanaka T, Stringham HM, Silbernagel G, Kanoni S, Feitosa MF, Snitker S, Ruiz JR, Metter J, Larrad MT, Atalay M, Hakanen M, Amin N, Cavalcanti-Proença C, Grøntved A, Hallmans G, Jansson JO, Kuusisto J, Kähönen M, Lutsey PL, Nolan JJ, Palla L, Pedersen O, Pérusse L, Renström F, Scott RA, Shungin D, Sovio U, Tammelin TH, Rönnemaa T, Lakka TA, Uusitupa M, Rios MS, Ferrucci L, Bouchard C, Meirhaeghe A, Fu M, Walker M, Borecki IB, Dedoussis GV, Fritsche A, Ohlsson C, Boehnke M, Bandinelli S, van Duijn CM, Ebrahim S, Lawlor DA, Gudnason V, Harris TB, Sørensen TI, Mohlke KL, Hofman A, Uitterlinden AG, Tuomilehto J, Lehtimäki T, Raitakari O, Isomaa B, Njølstad PR, Florez JC, Liu S, Ness A, Spector TD, Tai ES, Froguel P, Boeing H, Laakso M, Marmot M, Bergmann S, Power C, Khaw KT, Chasman D, Ridker P, Hansen T, Monda KL, Illig T, Järvelin MR, Wareham NJ, Hu FB, Groop LC, Orho-Melander M, Ekelund U, Franks PW, and Loos RJ

Subjects
Adipose Tissue metabolism, Adolescent, Adult, Aged, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Child, Female, Genotype, Humans, Male, Obesity metabolism, Obesity physiopathology, Risk Factors, Genetic Predisposition to Disease, Motor Activity, Obesity genetics, Polymorphism, Single Nucleotide, Proteins genetics
Abstract

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.

Published
2011
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13. The aetiology of symptomatic gallstones quantification of the effects of obesity, alcohol and serum lipids on risk. Epidemiological and biomarker data from a UK prospective cohort study (EPIC-Norfolk).

Author

Banim PJ, Luben RN, Bulluck H, Sharp SJ, Wareham NJ, Khaw KT, and Hart AR

Subjects
Adult, Aged, Alcohol Drinking epidemiology, Anthropometry methods, Biomarkers blood, Body Mass Index, England epidemiology, Epidemiologic Methods, Female, Gallstones blood, Gallstones epidemiology, Humans, Lipoproteins, HDL blood, Male, Middle Aged, Obesity epidemiology, Triglycerides blood, Waist Circumference, Alcohol Drinking adverse effects, Gallstones etiology, Lipids blood, Obesity complications
Abstract

Objective: The development of gallstones is influenced by obesity and alcohol. This study aimed to precisely quantify these risks and investigate whether the aetiological mechanism may involve serum lipids, for the first time using a European prospective cohort study., Methods: The European Prospective Investigation into Cancer-Norfolk, recruited 25 639 men and women, aged 40 to 74 years, between 1993 and 1997. At enrolment weight, height and alcohol intake were recorded and nonfasting blood samples taken to measure serum triglycerides, cholesterol, high-density lipoproteins and low-density lipoproteins. The cohort was monitored for 14 years for symptomatic gallstones. Cox regression estimated sex-specific hazard ratios (HRs) for symptomatic gallstones adjusted for covariates., Results: Symptomatic gallstones developed in 296 people (67.9% women). For each additional unit of BMI, the HR in men was 1.08 [95% confidence interval (CI)=1.02-1.14]; in women the HR was 1.08 (95% CI=1.06-1.11). Every unit of alcohol consumed per week decreased risk in men by 3% (HR=0.97, 95% CI=0.95-0.99) with no effect in women. Serum triglycerides increased risk in men (highest vs. lowest quarter HR=2.02, 95% CI=1.03-3.98) and women (HR=2.43, 95% CI=1.52-3.90). Increased high-density lipoprotein was associated with a decreased risk in men (highest vs. lowest quarter HR=0.22, 95% CI=0.09-0.52) and women (HR=0.55, 95% CI=0.36-0.85). No effects were found for serum cholesterol and low-density lipoprotein., Conclusion: Obesity and alcohol influence gallstone formation, possibly in part through their effects on serum lipids. Reducing obesity may prevent gallstones in the population, as 38% of incident cases of gallstones were associated with a BMI of more than 25.

Published
2011
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14. Genetic susceptibility to obesity and related traits in childhood and adolescence: influence of loci identified by genome-wide association studies.

Author

den Hoed M, Ekelund U, Brage S, Grontved A, Zhao JH, Sharp SJ, Ong KK, Wareham NJ, and Loos RJ

Subjects
Adolescent, Adult, Child, Chromosome Mapping, Female, Genetic Variation, Humans, Male, Polymorphism, Single Nucleotide, Skinfold Thickness, Waist Circumference, White People genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Obesity genetics
Abstract

Objective: Large-scale genome-wide association (GWA) studies have thus far identified 16 loci incontrovertibly associated with obesity-related traits in adults. We examined associations of variants in these loci with anthropometric traits in children and adolescents., Research Design and Methods: Seventeen variants representing 16 obesity susceptibility loci were genotyped in 1,252 children (mean ± SD age 9.7 ± 0.4 years) and 790 adolescents (15.5 ± 0.5 years) from the European Youth Heart Study (EYHS). We tested for association of individual variants and a genetic predisposition score (GPS-17), calculated by summing the number of effect alleles, with anthropometric traits. For 13 variants, summary statistics for associations with BMI were meta-analyzed with previously reported data (N(total) = 13,071 children and adolescents)., Results: In EYHS, 15 variants showed associations or trends with anthropometric traits that were directionally consistent with earlier reports in adults. The meta-analysis showed directionally consistent associations with BMI for all 13 variants, of which 9 were significant (0.033-0.098 SD/allele; P < 0.05). The near-TMEM18 variant had the strongest effect (0.098 SD/allele P = 8.5 × 10(-11)). Effect sizes for BMI tended to be more pronounced in children and adolescents than reported earlier in adults for variants in or near SEC16B, TMEM18, and KCTD15, (0.028-0.035 SD/allele higher) and less pronounced for rs925946 in BDNF (0.028 SD/allele lower). Each additional effect allele in the GPS-17 was associated with an increase of 0.034 SD in BMI (P = 3.6 × 10(-5)), 0.039 SD, in sum of skinfolds (P = 1.7 × 10(-7)), and 0.022 SD in waist circumference (P = 1.7 × 10(-4)), which is comparable with reported results in adults (0.039 SD/allele for BMI and 0.033 SD/allele for waist circumference)., Conclusions: Most obesity susceptibility loci identified by GWA studies in adults are already associated with anthropometric traits in children/adolescents. Whereas the association of some variants may differ with age, the cumulative effect size is similar.

Published
2010
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15. Genetic markers of adult obesity risk are associated with greater early infancy weight gain and growth.

Author

Elks CE, Loos RJ, Sharp SJ, Langenberg C, Ring SM, Timpson NJ, Ness AR, Davey Smith G, Dunger DB, Wareham NJ, and Ong KK

Subjects
Birth Weight, Body Mass Index, Child, Child, Preschool, Failure to Thrive genetics, Female, Genetic Predisposition to Disease, Genotype, Humans, Infant, Infant, Newborn, Linear Models, Longitudinal Studies, Male, Risk Factors, Alleles, Body Height genetics, Genetic Markers, Growth genetics, Obesity genetics, Weight Gain genetics
Abstract

Background: Genome-wide studies have identified several common genetic variants that are robustly associated with adult obesity risk. Exploration of these genotype associations in children may provide insights into the timing of weight changes leading to adult obesity., Methods and Findings: Children from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort were genotyped for ten genetic variants previously associated with adult BMI. Eight variants that showed individual associations with childhood BMI (in/near: FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, and ETV5) were used to derive an "obesity-risk-allele score" comprising the total number of risk alleles (range: 2-15 alleles) in each child with complete genotype data (n = 7,146). Repeated measurements of weight, length/height, and body mass index from birth to age 11 years were expressed as standard deviation scores (SDS). Early infancy was defined as birth to age 6 weeks, and early infancy failure to thrive was defined as weight gain between below the 5th centile, adjusted for birth weight. The obesity-risk-allele score showed little association with birth weight (regression coefficient: 0.01 SDS per allele; 95% CI 0.00-0.02), but had an apparently much larger positive effect on early infancy weight gain (0.119 SDS/allele/year; 0.023-0.216) than on subsequent childhood weight gain (0.004 SDS/allele/year; 0.004-0.005). The obesity-risk-allele score was also positively associated with early infancy length gain (0.158 SDS/allele/year; 0.032-0.284) and with reduced risk of early infancy failure to thrive (odds ratio = 0.92 per allele; 0.86-0.98; p = 0.009)., Conclusions: The use of robust genetic markers identified greater early infancy gains in weight and length as being on the pathway to adult obesity risk in a contemporary birth cohort.

Published
2010
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16. Supporting Weight Management during COVID-19 (SWiM-C): A randomised controlled trial of a web-based, ACT-based, guided self-help intervention

Author

Mueller, Julia, Richards, R, Jones, RA, Whittle, F, Woolston, J, Stubbings, M, Sharp, SJ, Griffin, SJ, Bostock, J, Hughes, CA, Hill, AJ, Ahern, AL, Mueller, Julia [0000-0002-4939-7112], Jones, Beckie [0000-0003-2197-1175], Whittle, Fiona [0000-0001-5461-521X], Sharp, Stephen [0000-0003-2375-1440], Griffin, Simon [0000-0002-2157-4797], Ahern, Amy [0000-0001-5069-4758], and Apollo - University of Cambridge Repository

Subjects
Adult, Internet, COVID-19, Humans, Obesity, Acceptance and Commitment Therapy, Overweight, Weight Gain, Pandemics
Abstract

Introduction: Adults with overweight and obesity are vulnerable to weight gain and mental health deterioration during the COVID-19 pandemic. We developed a web-based, guided self-help intervention based on Acceptance and Commitment Therapy (ACT) that aims to support adults with overweight and obesity to prevent weight gain by helping them to manage their eating behaviours, be more physically active and protect their emotional wellbeing (“SWiM-C”). SWiM-C is a guided self-help programme using non-specialist guides to enhance scalability and population reach while minimising cost. This study evaluated the effect of SWiM-C on bodyweight, eating behaviour, physical activity and mental wellbeing in adults with overweight and obesity over 4 months during the COVID-19 pandemic in the UK. Methods: We randomised adults (BMI≥25kg/m2) to SWiM-C or to a wait-list standard advice group. Participants completed outcome assessments online at baseline and 4 months. The primary outcome was self-measured weight; secondary outcomes were eating behaviour, physical activity, experiential avoidance/psychological flexibility, depression, anxiety, stress, and wellbeing. We estimated differences between study groups in change in outcomes from baseline to 4 months using linear regression, adjusted for outcome at baseline and the randomisation stratifiers (BMI, sex). The trial was pre-registered (ISRCTN12107048). Results: 486 participants were assessed for eligibility; 388 participants were randomised (196 standard advice, 192 SWiM-C) and 324 were analysed. The adjusted difference in weight between SWiM-C and standard advice was -0.60kg (-1.67 to 0.47, p=0.27). SWiM-C led to improvements in uncontrolled eating (-3.61 [-5.94 to -1.28]), cognitive restraint (5.28 [2.81 to 7.75]), experiential avoidance (-3.39 [-5.55 to -1.23]), and wellbeing (0.13 [0.07 to 0.18]). Conclusions: SWiM-C improved several psychological determinants of successful weight management and had a protective effect on wellbeing during the pandemic. However, differences in weight and some other outcomes were compatible with no effect of the intervention, suggesting further refinement of the intervention is needed.

Published
2022

17. Physical activity, sedentary time and gain in overall and central body fat: 7-year follow-up of the ProActive trial cohort

Author

Golubic, R, Wijndaele, K, Sharp, SJ, Simmons, RK, Griffin, SJ, Wareham, NJ, Ekelund, U, Brage, S, ProActive Study Group, Wijndaele, Katrien [0000-0003-2199-7981], Sharp, Stephen [0000-0003-2375-1440], Simmons, Rebecca [0000-0002-7726-8529], Griffin, Simon [0000-0002-2157-4797], Wareham, Nicholas [0000-0003-1422-2993], Brage, Soren [0000-0002-1265-7355], and Apollo - University of Cambridge Repository

Subjects
Adult, Male, Health Knowledge, Attitudes, Practice, Evidence-Based Medicine, Time Factors, Health Promotion, Weight Gain, Cohort Studies, Diabetes Mellitus, Type 2, Cardiovascular Diseases, Risk Factors, Accelerometry, Humans, Female, Obesity, Sedentary Behavior, Waist Circumference, Exercise, Adiposity, Follow-Up Studies
Abstract

OBJECTIVE: The objective of this study is to examine the independent associations of time spent in moderate-to-vigorous physical activity (MVPA) and sedentary (SED-time), with total and abdominal body fat (BF), and the bidirectionality of these associations in adults at high risk of type 2 diabetes. DESIGN AND SUBJECTS: We measured MVPA (min per day) and SED-time (h per day) by accelerometry, and indices of total (body weight, fat mass (FM), BF% and FM index) and abdominal BF (waist circumference (WC)) using standard procedures in 231 adults (41.3 ± 6.4 years) with parental history of type 2 diabetes (ProActive UK) at baseline, 1-year and 7-year follow-up. Mixed effects models were used to quantify the independent associations (expressed as standardised β-coefficients (95% confidence interval (CI))) of MVPA and SED-time with fat indices, using data from all three time points. All models were adjusted for age, sex, intervention arm, monitor wear time, follow-up time, smoking status, socioeconomic status and MVPA/SED-time. RESULTS: MVPA was inversely and independently associated with all indices of total BF (for example, 1 s.d. higher MVPA was associated with a reduction in FM, β = -0.09 (95% CI: -0.14, -0.04) s.d.) and abdominal BF (for example, WC: β = -0.07 (-0.12, -0.02)). Similarly, higher fat indices were independently associated with a reduction in MVPA (for example, WC: β = -0.25 (-0.36, -0.15); FM: β = -0.27 (-0.36, -0.18)). SED-time was positively and independently associated with most fat indices (for example, WC: β = 0.03 (-0.04, 0.09); FM: β = 0.10 (0.03, 0.17)). Higher values of all fat indices independently predicted longer SED-time (for example, WC: β = 0.10 (0.02, 0.18), FM: β = 0.15 (0.07, 0.22)). CONCLUSIONS: The associations of MVPA and SED-time with total and abdominal BF are bidirectional and independent among individuals at high risk for type 2 diabetes. The association between BF and MVPA is stronger than the reciprocal association, highlighting the importance of considering BF as a determinant of decreasing activity and a potential consequence. Promoting more MVPA and less SED-time may reduce total and abdominal BF.

Published
2015

18. The Association between Dietary Energy Density and Type 2 Diabetes in Europe: Results from the EPIC-InterAct Study

Author

InterAct Consortium, Saskia W van den Berg, Daphne L van der A, Annemieke M W Spijkerman, Geertruida J van Woudenbergh, Mariken J Tijhuis, Pilar Amiano, Eva Ardanaz, Joline W J Beulens, Heiner Boeing, Françoise Clavel-Chapelon, Francesca L Crowe, Blandine de Lauzon-Guillain, Guy Fagherazzi, Paul W Franks, Heinz Freisling, Carlos Gonzalez, Sara Grioni, Jytte Halkjaer, José María Huerta, Inge Huybrechts, Rudolf Kaaks, Kay Tee Khaw, Giovanna Masala, Peter M Nilsson, Kim Overvad, Salvatore Panico, J Ramón Quirós, Olov Rolandsson, Carlotta Sacerdote, María-José Sánchez, Matthias B Schulze, Nadia Slimani, Ellen A Struijk, Anne Tjonneland, Rosario Tumino, Stephen J Sharp, Claudia Langenberg, Nita G Forouhi, Edith J M Feskens, Elio Riboli, Nicholas J Wareham, The InterAct Consortium, [van den Berg,SW, van der A,DL, Spijkerman,AMW, Tijhuis,MJ] Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands. [van Woudenbergh,GJ, Feskens,EJM] Division of Human Nutrition - Section Nutrition and Epidemiology, Wageningen University, Wageningen, The Netherlands. [Amiano,P] Instituto BIO-Donostia, Basque Government, Donostia, Spain. [Amiano,P, Ardanaz,E, Huerta,JM, Sánchez,M] Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública), Madrid, Spain. [Amiano,P] Public Health Division of Gipuzkoa, San Sebastian, Spain. [Ardanaz,E] Navarre Public Health Institute (ISPN), Pamplona, Spain. [Beulens,JWJ, Struijk,EA] Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands. [Boeing,H] Department of Epidemiology, German Institute of Human Nutrition, Potsdam-Rehbruecke, Germany. [Clavel-Chapelon,F, Fagherazzi,G] Nutrition, Hormones and Women’s Health, Institut National de la Santé et de la Recherche Médicale (INSERM) and Center for Research in Epidemiology and Population Health (CESP), Villejuif, France. [Clavel-Chapelon,F, de Lauzon-Guillain,B, Fagherazzi,G] University Paris Sud, Villejuif, France. [Crowe,FL] Cancer Epidemiology Unit, University of Oxford, Oxford, United Kingdom. [de Lauzon- Guillain,B] Institut National de la Santé et de la Recherche Médicale (INSERM) and Center for Research in Epidemiology and Population Health (CESP), Villejuif, France. [Franks,PW] Department of Clinical Sciences, Skane University Hospital, Lund University, Malmö, Sweden. [Rolandsson,O] Department of Public Health and Clinical Medicine, Umea University, Umea, Sweden. [Freisling,H, Huybrechts,I] International Agency for Research on Cancer, Lyon, France. [Gonzalez,C] Unit Nutrition, Environment and Cancer, Department of Epidemiology, Catalan Institute of Oncology, Barcelona, Spain. [Grioni,S] Nutritional Epidemiology Unit, Milan, Italy. [Halkjaer,J, Tjonneland,A] Danish Cancer Society Research Center, Copenhagen, Denmark. [Huerta,JM] Department of Epidemiology, Murcia Regional Health Authority, Murcia, Spain. [Kaaks,R] Division of Cancer Epidemiology, German Cancer Research Centre (DKFZ), Heidelberg, Germany. [Khaw,KT] Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. [Masala,G] Molecular and Nutritional Epidemiology Unit, Cancer Research and Prevention Institute, Florence, Italy. [Nilsson,PM] Department of Clinical Sciences Medicine, University Hospital Scania, Lund University, Malmö, Sweden. [Overvad,K] Department of Cardiology, Aalborg Hospital, Aarhus University Hospital, Aalborg, Denmark. [Overvad,K] Department of Epidemiology, School of Public Health, Aarhus, Denmark. [Panico,S] Department of Clinical and Experimental Medicine, Federico II University, Naples, Italy. [Quirós,JR] Asturias Health & Health Care Council, Oviedo, Spain. [Sacerdote,C] Human Genetic Foundation (HuGeF), Torino, Italy. Center for Cancer Prevention, Torino, Italy. [Sánchez,MJ] Andalusian School of Public Health, Granada, Spain. [Schulze,MB] Department of Molecular Epidemiology, German Institute of Human Nutrition, Potsdam-Rehbruecke, Germany. [Slimani,N] Dietary Exposure Assessment Group (DEX), International Agency for Research on Cancer, Lyon, France. [Tumino,R] Cancer Registry and Histopathology Unit, Ragusa, Italy. Aire Onlus, Ragusa, Spain. [Sharp,SJ, Langenberg,C, Forouhi,NG, Wareham,NJ] MRC Epidemiology Unit, Cambridge, United Kingdom. [Riboli,E] Department of Epidemiology and Biostatistics, Imperial College London, London, UK., The EPIC-InterAct Study received funding from the European Union (Integrated project LSHM-CT-2006-037197 in the Framework Programme 6 of the European Community). DLvdA: Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands, AMWS: Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands, EA: Health Research Fund (FIS) of the Spanish Ministry of Health, Navarre Regional Government and CIBER Epidemiologı´a y Salud Pu´ blica (CIBERESP)., JWJB: Verification of diabetes cases in EPIC-NL was additionally funded by NL Agency grant IGE05012 and an Incentive Grant from the Board of the UMC Utrecht., FLC: Cancer Research UK, PWF: Swedish Research Council, Novo Nordisk, Swedish Diabetes Association, Swedish Heart- Lung Foundation, JH: Danish Cancer Society, JMH: Health Research Fund of the Spanish Ministry of Health, Murcia Regional Government (Nu 6236), RK: German Cancer Aid, German Ministry of Research (BMBF), KTK: Medical Research Council UK, Cancer Research UK, PN: Swedish Research Council, KO: Danish Cancer Society, SP: Compagnia di San Paolo, JRQ: Asturias Regional Government, OR: The Vasterboten County Council, AT: Danish Cancer Society, RT: AIRE-ONLUS Ragusa, AVIS-Ragusa, Sicilian Regional Government, ER: ER was supported in this work by the Imperial College Biomedical Research Centre. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript., Epidemiology and Data Science, ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias, APH - Health Behaviors & Chronic Diseases, van den Berg, Sw, van der A., Dl, Spijkerman, Am, van Woudenbergh, Gj, Tijhuis, Mj, Amiano, P, Ardanaz, E, Beulens, Jw, Boeing, H, Clavel Chapelon, F, Crowe, Fl, de Lauzon Guillain, B, Fagherazzi, G, Franks, Pw, Freisling, H, Gonzalez, C, Grioni, S, Halkjaer, J, Huerta, Jm, Huybrechts, I, Kaaks, R, Khaw, Kt, Masala, G, Nilsson, Pm, Overvad, K, Panico, Salvatore, Quir?s, Jr, Rolandsson, O, Sacerdote, C, S?nchez, Mj, Schulze, Mb, Slimani, N, Struijk, Ea, Tjonneland, A, Tumino, R, Sharp, Sj, Langenberg, C, Forouhi, Ng, Feskens, Ej, Riboli, E, Wareham, Nj, and Interact, Consortium

Subjects
Gerontology, Anatomy and Physiology, endocrine system diseases, Nutrition and Disease, Epidemiology, lcsh:Medicine, Type 2 diabetes, Diabetes Mellitus Tipo 2, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Probability::Risk::Risk Factors [Medical Subject Headings], Cohort Studies, Impaired glucose tolerance, Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::Humans [Medical Subject Headings], MELLITUS, Endocrinology, Risk Factors, Voeding en Ziekte, Medicine and Health Sciences, Longitudinal Studies, lcsh:Science, Prospective cohort study, risk, METABOLIC SYNDROME, RISK, Multidisciplinary, Estudios de casos y controles, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Epidemiologic Study Characteristics as Topic::Epidemiologic Studies::Case-Control Studies [Medical Subject Headings], weight change, Ingestión de energía, WOMEN, Geographicals::Geographic Locations::Europe [Medical Subject Headings], Phenomena and Processes::Physiological Phenomena::Nutritional Physiological Phenomena::Diet::Energy Intake [Medical Subject Headings], Humanos, Europe, us adults, Endokrinologi och diabetes, Observational Studies, Medicine, Science & Technology - Other Topics, Diseases::Nutritional and Metabolic Diseases::Metabolic Diseases::Glucose Metabolism Disorders::Diabetes Mellitus::Diabetes Mellitus, Type 2 [Medical Subject Headings], impaired glucose-tolerance, LIFE-STYLE, Dieta, women, Europa, Research Article, WEIGHT CHANGE, Factores de riesgo, life-style, Clinical Research Design, united-states, UNITED-STATES, Endocrine System, Phenomena and Processes::Physiological Phenomena::Nutritional Physiological Phenomena::Diet [Medical Subject Headings], Endocrinology and Diabetes, metabolic syndrome, IMPAIRED GLUCOSE-TOLERANCE, US ADULTS, Environmental health, Glycemic load, glycemic load, medicine, GLYCEMIC LOAD, Humans, Obesity, Biology, Nutrition, VLAG, Diabetic Endocrinology, Science & Technology, Population Biology, business.industry, MULTIDISCIPLINARY SCIENCES, lcsh:R, Weight change, Case-control study, Diabetes Mellitus Type 2, medicine.disease, Diet, Diabetes Mellitus, Type 2, Case-Control Studies, Other Clinical Medicine, lcsh:Q, Metabolic syndrome, Energy Intake, business, mellitus
Abstract

Journal Article; Research Support, Non-U.S. Gov't; BACKGROUND Observational studies implicate higher dietary energy density (DED) as a potential risk factor for weight gain and obesity. It has been hypothesized that DED may also be associated with risk of type 2 diabetes (T2D), but limited evidence exists. Therefore, we investigated the association between DED and risk of T2D in a large prospective study with heterogeneity of dietary intake. METHODOLOGY/PRINCIPAL FINDINGS A case-cohort study was nested within the European Prospective Investigation into Cancer (EPIC) study of 340,234 participants contributing 3.99 million person years of follow-up, identifying 12,403 incident diabetes cases and a random subcohort of 16,835 individuals from 8 European countries. DED was calculated as energy (kcal) from foods (except beverages) divided by the weight (gram) of foods estimated from dietary questionnaires. Prentice-weighted Cox proportional hazard regression models were fitted by country. Risk estimates were pooled by random effects meta-analysis and heterogeneity was evaluated. Estimated mean (sd) DED was 1.5 (0.3) kcal/g among cases and subcohort members, varying across countries (range 1.4-1.7 kcal/g). After adjustment for age, sex, smoking, physical activity, alcohol intake, energy intake from beverages and misreporting of dietary intake, no association was observed between DED and T2D (HR 1.02 (95% CI: 0.93-1.13), which was consistent across countries (I(2) = 2.9%). CONCLUSIONS/SIGNIFICANCE In this large European case-cohort study no association between DED of solid and semi-solid foods and risk of T2D was observed. However, despite the fact that there currently is no conclusive evidence for an association between DED and T2DM risk, choosing low energy dense foods should be promoted as they support current WHO recommendations to prevent chronic diseases. Yes

Published
2013
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19. Long-term risk of incident type 2 Diabetes and measures of overall and regional obesity: The EPIC-InterAct Case-Cohort Study

Author

Nicola D. Kerrison, Olov Rolandsson, Joachim Spranger, Nicholas J. Wareham, Kay-Tee Khaw, Luigi Palla, Carlos González, Heiner Boeing, Nita G. Forouhi, Ivonne Sluijs, María José Tormo, Joline W.J. Beulens, Kim Overvad, Matthias B. Schulze, Isabelle Romieu, Beverley Balkau, Francesca L. Crowe, Domenico Palli, María José Sánchez, J. Ramón Quirós, Claudia Langenberg, Yvonne T. van der Schouw, Dora Romaguera, Nadia Slimani, Paul W. Franks, Rosario Tumino, Eva Ardanaz, Göran Hallmans, Stephen J. Sharp, José María Huerta, Anne Tjønneland, Birgit Teucher, H. Bas Bueno-de-Mesquita, Salvatore Panico, Edith J. M. Feskens, Teresa Norat, L. van der A. Daphne, Carlotta Sacerdote, Elio Riboli, Annemieke M.W. Spijkerman, Blandine de Lauzon-Guillan, Peter M. Nilsson, Dagmar Drogan, Timothy J. Key, Sara Grioni, Rudolf Kaaks, Jytte Halkjær, Larraitz Arriola, Amalia Mattiello, Françoise Clavel-Chapelon, The InterAct Consortium, [Langenberg,C, Sharp,SJ, Forouhi,NG, Kerrison,ND, Palla,L, Wareham,NJ] MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, United Kingdom. [Schulze,MB] Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Arthur-Scheunert-Allee, Nuthetal, Germany. [Rolandsson,O, Hallmans,G] Department of Public Health and Clinical Medicine, Umea University, Norrlands Universitetsjukhus, Umea, Sweden. [Overvad,K] Department of Epidemiology, School of Public Health, Aarhus C, Denmark. [Spranger.J] Charité-Universitatsmedizin Berlin, Department of Endocrinology, Diabetes and Nutrition, Berlin, Germany. [Drogan,D, Boeing,H] Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany.[Arriola,L, Tormo,MJ] Department of Epidemiology, Murcia Regional Health Council, Murcia, Spain. [Huerta,JM, Arriola,L, Tormo,MJ, Ardanaz,E, Sánchez,MJ] Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pu´ blica), Madrid, Spain . [Arriola,L] Public Health Division of Gipuzkoa, Basque Government, San Sebastian, Spain. Instituto BIO-Donostia, Hospital Donostia, Donostia, Basque Country. [Lauzon-Guillan,B, Balkau,B] INSERM, CESP Centre for Research in Epidemiology and Population Health, U1018: Epidemiology of Diabetes, Obesity and Chronic Kidney Disease over the Lifecourse, Villejuif Cedex, France. University Paris, Villejuif Cedex, France. [Ardanaz,E] Navarre Public Health Institute, Pamplona, Navarra, Spain. [Beulens,JWJ, Sluijs,I, Schouw,T] Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. [Bueno-de-Mesquita,HB] National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands. [Clavel-Chapelon,F] INSERM, CESP Centre for Research in Epidemiology and Population Health,U1018: Nutrition, Hormones and Women’s Health, IGR, Villejuif Cedex, France. [Crowe,FL, Key,TJ] Cancer Epidemiology Unit, Nuffield Department of Clinical Medicine, University of Oxford,Richard Doll Building, Roosevelt Drive, Oxford, United Kingdom. [Grioni,S] Fondazione IRCCS Istituto Nazionale Tumori Milan, Milan, Italy. [Halkjaer,J, Tjonneland,A] Danish Cancer Society Research Center, Copenhagen, Denmark. [Kerrison,ND, Teucher,B] German Cancer Research Centre, Heidelberg, Germany. [Khaw,KT] Department of Public Health and Primary Care, University of Cambridge Addenbrooke’s Hospital, Cambridge, United Kingdom. [Mattiello,A] Department of Clinical and Experimental Medicine Federico II University, Naples, Italy. [Nilsson,P, Panico,S] University of Lund, Department of Clinical Sciences Medicine, University Hospital Scania, Malmo, Sweden. [Norat,T, Romaguera,D, Riboli,E] Department of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, United Kingdom. [Palli,D] Molecular and Nutritional Epidemiology Unit, ISPO Ponte Nuovo, Florence, Italy. [Quirós, JR] Public Health Directorate, Oviedo, Spain. [Romieu,I, Slimani,N] International Agency for Research on Cancer, Lyon Cedex, France. [Sacerdote,C] Center for Cancer Prevention (CPO-Piemonte), Torino, Italy. Human Genetics Foundation (HuGeF), Torino, Italy. [Sánchez,MJ] Andalusian School of Public Health, Granada, Spain. [Spijkerman,AMW, A Daphne,L] National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands. [Tumino,R] Cancer Registry and Histopathology Unit, ‘‘Civile - M.P. Arezzo’’ Hospital, Dante Ragusa, Italy. [Feskens,EJM] Division of Human Nutrition - Section Nutrition and Epidemiology, University of Wageningen, Wageningen, The Netherlands. [Franks,PW] Department of Clinical Sciences, Clinical Research Center, Ska°ne University Hospital, Lund University, Malmö , Sweden. [Bueno-de-Mesquita,HB] Department of Gastroenterology and Hepatology, University Medical Centre, Utrecht, The Netherlands., Funding: EU Integrated Project LSHM-CT-2006-037197. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. InterAct investigators acknowledge funding from the following agencies: KO: Danish Cancer Society, JS: ‘Heisenberg-Professorship (SP716/2-1), clinical research group (KFO218/1), and a research group (Molecular Nutrition to JS) support of the Bundesministerium fu¨ r Bildung und Forschung (BMBF), MJT: Health Research Fund (FIS) of the Spanish Ministry of Health, the CIBER en Epidemiologı´a y Salud Pu´ blica (CIBERESP), Spain, Murcia Regional Government (Nu 6236), JWJB, HBBdM, IS, AMWS, DLvdA, YTvdS: Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands, verification of diabetes cases was additionally funded by NL Agency grant IGE05012 and an Incentive Grant from the Board of the UMC Utrecht, FLC: Cancer Research UK, PWF: Swedish Research Council, Novo Nordisk, Swedish Diabetes Association, Swedish Heart-Lung Foundation, GH: The county of Va¨sterbotten, RK: German Cancer Aid, Federal Ministry of Education and Research, TJK: Cancer Research UK, KK: Medical Research Council UK, Cancer Research UK, PN: Swedish Research Council, JRQ: Asturias Regional Government, BT: German Cancer Aid, Federal Ministry of Education and Research, AT: Danish Cancer Society, RT: AIRE-ONLUS Ragusa, AVIS-Ragusa, Sicilian Regional Government., Epidemiology and Data Science, ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias, APH - Health Behaviors & Chronic Diseases, Langenberg, C, Sharp, Sj, Schulze, Mb, Rolandsson, O, Overvad, K, Forouhi, Ng, Spranger, J, Drogan, D, Huerta, Jm, Arriola, L, de Lauzon Guillan, B, Tormo, Mj, Ardanaz, E, Balkau, B, Beulens, Jw, Boeing, H, Bueno de Mesquita, Hb, Clavel Chapelon, F, Crowe, Fl, Franks, Pw, Gonzalez, Ca, Grioni, S, Halkjaer, J, Hallmans, G, Kaaks, R, Kerrison, Nd, Key, Tj, Khaw, Kt, Mattiello, A, Nilsson, P, Norat, T, Palla, L, Palli, D, Panico, Salvatore, Quir?s, Jr, Romaguera, D, Romieu, I, Sacerdote, C, S?nchez, Mj, Slimani, N, Sluijs, I, Spijkerman, Am, Teucher, B, Tjonneland, A, Tumino, R, van der A., Dl, van der Schouw, Yt, Feskens, Ej, Riboli, E, Wareham, Nj, and Interact, Consortium

Subjects
Male, Gerontology, Índice de Masa Corporal, Time Factors, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Models, Statistical::Proportional Hazards Models [Medical Subject Headings], Nutrition and Disease, Epidemiology, Phenomena and Processes::Physical Phenomena::Time::Time Factors [Medical Subject Headings], Analytical, Diagnostic and Therapeutic Techniques and Equipment::Diagnosis::Diagnostic Techniques and Procedures::Physical Examination::Anthropometry [Medical Subject Headings], body-mass index, Diabetes Mellitus Tipo 2, Named Groups::Persons::Age Groups::Adult::Middle Aged [Medical Subject Headings], Overweight, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Statistics as Topic::Probability::Risk::Risk Factors [Medical Subject Headings], Body Mass Index, Cohort Studies, Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::Humans [Medical Subject Headings], Endocrinology, prevention, Risk Factors, Voeding en Ziekte, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Diagnosis::Diagnostic Techniques and Procedures::Physical Examination::Body Constitution::Body Weights and Measures::Body Size::Waist Circumference [Medical Subject Headings], Cumulative incidence, Longitudinal Studies, Prospective Studies, Nutrition and Dietetics, Anthropometry, Incidence, primary-care, Hazard ratio, Absolute risk reduction, Geographicals::Geographic Locations::Europe [Medical Subject Headings], General Medicine, Middle Aged, waist circumference, Europe, Näringslära, nutrition, Cohort, Medicine, Diseases::Nutritional and Metabolic Diseases::Metabolic Diseases::Glucose Metabolism Disorders::Diabetes Mellitus::Diabetes Mellitus, Type 2 [Medical Subject Headings], Female, medicine.symptom, Life Sciences & Biomedicine, Research Article, Cohort study, Clinical Research Design, abdominal adiposity, Check Tags::Male [Medical Subject Headings], Analytical, Diagnostic and Therapeutic Techniques and Equipment::Diagnosis::Diagnostic Techniques and Procedures::Physical Examination::Body Constitution::Body Weights and Measures::Body Mass Index [Medical Subject Headings], Endocrinology and Diabetes, Medicine, General & Internal, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Data Collection::Vital Statistics::Morbidity::Incidence [Medical Subject Headings], General & Internal Medicine, medicine, Humans, cancer, Obesity, Risk factor, Proportional Hazards Models, VLAG, Diabetic Endocrinology, Science & Technology, business.industry, association, nutritional and metabolic diseases, Diabetes Mellitus Type 2, Diseases::Nutritional and Metabolic Diseases::Nutrition Disorders::Overnutrition::Obesity [Medical Subject Headings], Diabetes Mellitus, Type 2, Antropometría, Check Tags::Female [Medical Subject Headings], Other Clinical Medicine, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Epidemiologic Study Characteristics as Topic::Epidemiologic Studies::Cohort Studies [Medical Subject Headings], Meta-Analyses, participants, business, Estudios de Cohortes, Body mass index, Demography, mellitus
Abstract

A collaborative re-analysis of data from the InterAct case-control study conducted by Claudia Langenberg and colleagues has established that waist circumference is associated with risk of type 2 diabetes, independently of body mass index., Background Waist circumference (WC) is a simple and reliable measure of fat distribution that may add to the prediction of type 2 diabetes (T2D), but previous studies have been too small to reliably quantify the relative and absolute risk of future diabetes by WC at different levels of body mass index (BMI). Methods and Findings The prospective InterAct case-cohort study was conducted in 26 centres in eight European countries and consists of 12,403 incident T2D cases and a stratified subcohort of 16,154 individuals from a total cohort of 340,234 participants with 3.99 million person-years of follow-up. We used Prentice-weighted Cox regression and random effects meta-analysis methods to estimate hazard ratios for T2D. Kaplan-Meier estimates of the cumulative incidence of T2D were calculated. BMI and WC were each independently associated with T2D, with WC being a stronger risk factor in women than in men. Risk increased across groups defined by BMI and WC; compared to low normal weight individuals (BMI 18.5–22.4 kg/m2) with a low WC (102/88 cm). Among the large group of overweight individuals, WC measurement was highly informative and facilitated the identification of a subgroup of overweight people with high WC whose 10-y T2D cumulative incidence (men, 70 per 1,000 person-years; women, 44 per 1,000 person-years) was comparable to that of the obese group (50–103 per 1,000 person-years in men and 28–74 per 1,000 person-years in women). Conclusions WC is independently and strongly associated with T2D, particularly in women, and should be more widely measured for risk stratification. If targeted measurement is necessary for reasons of resource scarcity, measuring WC in overweight individuals may be an effective strategy, since it identifies a high-risk subgroup of individuals who could benefit from individualised preventive action. Please see later in the article for the Editors' Summary, Editors' Summary Background Worldwide, more than 350 million people have diabetes, and this number is increasing rapidly. Diabetes is characterized by dangerous levels of glucose (sugar) in the blood. Blood sugar levels are usually controlled by insulin, a hormone that the pancreas releases after meals (digestion of food produces glucose). In people with type 2 diabetes (the commonest form of diabetes), blood sugar control fails because the fat and muscle cells that normally respond to insulin by removing sugar from the blood become insulin resistant. Type 2 diabetes can be controlled with diet and exercise, and with drugs that help the pancreas make more insulin or that make cells more sensitive to insulin. The long-term complications of diabetes, which include an increased risk of heart disease and stroke, reduce the life expectancy of people with diabetes by about 10 years compared to people without diabetes. Why Was This Study Done? A high body mass index (BMI, a measure of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) is a strong predictor of type 2 diabetes. Although the risk of diabetes is greatest in obese people (who have a BMI of greater than 30 kg/m2), many of the people who develop diabetes are overweight—they have a BMI of 25–30 kg/m2. Healthy eating and exercise reduce the incidence of diabetes in high-risk individuals, but it is difficult and expensive to provide all overweight and obese people with individual lifestyle advice. Ideally, a way is needed to distinguish between people with high and low risk of developing diabetes at different levels of BMI. Waist circumference is a measure of fat distribution that has the potential to quantify diabetes risk among people with different BMIs because it estimates the amount of fat around the abdominal organs, which also predicts diabetes development. In this case-cohort study, the researchers use data from the InterAct study (which is investigating how genetics and lifestyle interact to affect diabetes risk) to estimate the long-term risk of type 2 diabetes associated with BMI and waist circumference. A case-cohort study measures exposure to potential risk factors in a group (cohort) of people and compares the occurrence of these risk factors in people who later develop the disease and in a randomly chosen subcohort. What Did the Researchers Do and Find? The researchers estimated the association of BMI and waist circumference with type 2 diabetes from baseline measurements of the weight, height, and waist circumference of 12,403 people who subsequently developed type 2 diabetes and a subcohort of 16,154 participants enrolled in the European Prospective Investigation into Cancer and Nutrition (EPIC). Both risk factors were independently associated with type 2 diabetes risk, but waist circumference was a stronger risk factor in women than in men. Obese men (BMI greater than 35 kg/m2) with a high waist circumference (greater than 102 cm) were 22 times more likely to develop diabetes than men with a low normal weight (BMI 18.5–22.4 kg/m2) and a low waist circumference (less than 94 cm); obese women with a waist circumference of more than 88 cm were 31.8 times more likely to develop type 2 diabetes than women with a low normal weight and waist circumference (less than 80 cm). Importantly, among overweight people, waist circumference measurements identified a subgroup of overweight people (those with a high waist circumference) whose 10-year cumulative incidence of type 2 diabetes was similar to that of obese people. What Do These Findings Mean? These findings indicate that, among people of European descent, waist circumference is independently and strongly associated with type 2 diabetes, particularly among women. Additional studies are needed to confirm this association in other ethnic groups. Targeted measurement of waist circumference in overweight individuals (who now account for a third of the US and UK adult population) could be an effective strategy for the prevention of diabetes because it would allow the identification of a high-risk subgroup of people who might benefit from individualized lifestyle advice. Additional Information Please access these web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001230. The US National Diabetes Information Clearinghouse provides information about diabetes for patients, health care professionals, and the general public, including detailed information on diabetes prevention (in English and Spanish) The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (including some information in Spanish) The UK National Health Service Choices website provides information for patients and carers about type 2 diabetes, about the prevention of type 2 diabetes, and about obesity; it also includes peoples stories about diabetes and about obesity The charity Diabetes UK also provides detailed information for patients and carers, including information on healthy lifestyles for people with diabetes, and has a further selection of stories from people with diabetes; the charity Healthtalkonline has interviews with people about their experiences of diabetes More information on the InterAct study is available MedlinePlus provides links to further resources and advice about diabetes and diabetes prevention and about obesity (in English and Spanish)

Published
2012
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20. Common genetic variants highlight the role of insulin resistance and body fat distribution in type 2 diabetes, independent of obesity

Author

Núria Sala, Nina Roswall, Tilman Kühn, Larraitz Arriola, Dorota Pasko, Elio Riboli, Mark I. McCarthy, Afshan Siddiq, María José Sánchez, Luca A. Lotta, Francesca L. Crowe, Timothy J. Key, Peter M. Nilsson, Anne Tjønneland, Inês Barroso, Guy Fagherazzi, Nita G. Forouhi, Carlotta Sacerdote, Kim Overvad, Aurelio Barricarte, Nicholas J. Wareham, Sara Grioni, Tove Fall, Françoise Clavel-Chapelon, Olov Rolandsson, Heiner Boeing, Jacqueline M. Dekker, Mark Walker, Adam Barker, Vilmantas Giedraitis, Daphne L. van der A, Claudia Langenberg, Diana Gavrila, David B. Savage, Ele Ferrannini, Matthias B. Schulze, Hanieh Yaghootkar, Nadia Slimani, Paul W. Franks, Erik Ingelsson, Annemieke M.W. Spijkerman, Robert A. Scott, Ivonne Sluijs, Rosario Tumino, Stephen J. Sharp, Salvatore Panico, Robert K. Semple, Beverley Balkau, Leif Groop, Domenico Palli, Timothy M. Frayling, J. Ramón Quirós, Rudolf Kaaks, Scott, Ra, Fall, T, Pasko, D, Barker, A, Sharp, Sj, Arriola, L, Balkau, B, Barricarte, A, Barroso, I, Boeing, H, Clavel Chapelon, F, Crowe, Fl, Dekker, Jm, Fagherazzi, G, Ferrannini, E, Forouhi, Ng, Franks, Pw, Gavrila, D, Giedraitis, V, Grioni, S, Groop, Lc, Kaaks, R, Key, Tj, K?hn, T, Lotta, La, Nilsson, Pm, Overvad, K, Palli, D, Panico, Salvatore, Quir?s, Jr, Rolandsson, O, Roswall, N, Sacerdote, C, Sala, N, S?nchez, Mj, Schulze, Mb, Siddiq, A, Slimani, N, Sluijs, I, Spijkerman, Am, Tjonneland, A, Tumino, R, van der A., Dl, Yaghootkar, H, Mccarthy, Mi, Semple, Rk, Riboli, E, Walker, M, Ingelsson, E, Frayling, Tm, Savage, Db, Langenberg, C, Wareham, Nj, The RISC The study group InterAct, Consortium, Epidemiology and Data Science, and EMGO - Lifestyle, overweight and diabetes

Subjects
Adult, Male, medicine.medical_specialty, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Type 2 diabetes, Overweight, Polymorphism, Single Nucleotide, Article, Body Mass Index, Cohort Studies, Insulin resistance, Diabetes mellitus, Internal medicine, Insulin Secretion, Internal Medicine, medicine, Body Fat Distribution, Humans, Insulin, Genetic Predisposition to Disease, Obesity, Aged, 2. Zero hunger, Glucose tolerance test, medicine.diagnostic_test, business.industry, nutritional and metabolic diseases, Genetic Variation, Alanine Transaminase, gamma-Glutamyltransferase, Glucose clamp technique, Glucose Tolerance Test, Middle Aged, medicine.disease, Endocrinology, Diabetes Mellitus, Type 2, Body Composition, Glucose Clamp Technique, Female, medicine.symptom, Insulin Resistance, Waist Circumference, business
Abstract

We aimed to validate genetic variants as instruments for insulin resistance and secretion, to characterize their association with intermediate phenotypes, and to investigate their role in type 2 diabetes (T2D) risk among normal-weight, overweight, and obese individuals. We investigated the association of genetic scores with euglycemic-hyperinsulinemic clamp– and oral glucose tolerance test–based measures of insulin resistance and secretion and a range of metabolic measures in up to 18,565 individuals. We also studied their association with T2D risk among normal-weight, overweight, and obese individuals in up to 8,124 incident T2D cases. The insulin resistance score was associated with lower insulin sensitivity measured by M/I value (β in SDs per allele [95% CI], −0.03 [−0.04, −0.01]; P = 0.004). This score was associated with lower BMI (−0.01 [−0.01, −0.0]; P = 0.02) and gluteofemoral fat mass (−0.03 [−0.05, −0.02; P = 1.4 × 10−6) and with higher alanine transaminase (0.02 [0.01, 0.03]; P = 0.002) and γ-glutamyl transferase (0.02 [0.01, 0.03]; P = 0.001). While the secretion score had a stronger association with T2D in leaner individuals (Pinteraction = 0.001), we saw no difference in the association of the insulin resistance score with T2D among BMI or waist strata (Pinteraction > 0.31). While insulin resistance is often considered secondary to obesity, the association of the insulin resistance score with lower BMI and adiposity and with incident T2D even among individuals of normal weight highlights the role of insulin resistance and ectopic fat distribution in T2D, independently of body size.

Published
2016
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21. Genome-wide association for abdominal subcutaneous and visceral adipose reveals a novel locus for visceral fat in women

Author

Amelie Bonnefond, Nancy Heard-Costa, Eleftheria Zeggini, Anna Gloyn, LAURA CRISPONI, Eco De Geus, Michael Weedon, Torben Jørgensen, Jaakko Kaprio, Iva Miljkovic, Amanda Bennett, Yurii Aulchenko, Michael Stumvoll, Andrew Hattersley, Christian Dina, Sophie Visvikis-Siest, Udo Seedorf, Vilmundur Gudnason, Michael Marmot, Mika Kivimaki, Mary Feitosa, Danielle Posthuma, Claudia Langenberg, Stavroula Kanoni, Cyrus Cooper, Meena Kumari, Peter Kovacs, Debbie A Lawlor, Inga Prokopenko, Rafn Benediktsson, Stephen Kritchevsky, Philippe Froguel, Cornelia Van Duijn, Nita Forouhi, Anne B. Newman, Ko Willems van Dijk, John Carr, Reedik Mägi, Sutapa Mukherjee, Lyle John Palmer, Francois Pattou, L. Adrienne Cupples, Paul Franks, Paul Elliott, Albert Vernon Smith, MANUELA UDA, Kirsten Ohm Kyvik, Manuel Serrano Ríos, Richard Bergman, Gonneke Willemsen, Cecilia Lindgren, Igor Rudan, Human genetics, NCA - Attention & Cognition, EMGO - Lifestyle, overweight and diabetes, Institute for Molecular Medicine Finland, Research Group Ripatti Samuli, Hjelt Institute (-2014), Department of Public Health, Biostatistics Helsinki, Complex Disease Genetics, Genetic Epidemiology, Biological Psychology, Functional Genomics, Neuroscience Campus Amsterdam - Attention & Cognition, EMGO+ - Lifestyle, Overweight and Diabetes, GIANT Consortium, MAGIC Consortium, GLGC Consortium, Dupuis, J., Langenberg, C., Prokopenko, I., Saxena, R., Soranzo, N., Jackson, AU., Wheeler, E., Glazer, NL., Bouatia-Naji, N., Gloyn, AL., Lindgren, CM., Mägi, R., Morris, AP., Randall, J., Johnson, T., Elliott, P., Rybin, D., Thorleifsson, G., Steinthorsdottir, V., Henneman, P., Grallert, H., Dehghan, A., Hottenga, JJ., Franklin, CS., Navarro, P., Song, K., Goel, A., Perry, JR., Egan, JM., Lajunen, T., Grarup, N., Sparsø, T., Doney, A., Voight, BF., Stringham, HM., Li, M., Kanoni, S., Shrader, P., Cavalcanti-Proença, C., Kumari, M., Qi, L., Timpson, NJ., Gieger, C., Zabena, C., Rocheleau, G., Ingelsson, E., An, P., O'Connell, J., Luan£££Jian'an£££ J., Elliott, A., McCarroll, SA., Payne, F., Roccasecca, RM., Pattou, F., Sethupathy, P., Ardlie, K., Ariyurek, Y., Balkau, B., Barter, P., Beilby, JP., Ben-Shlomo, Y., Benediktsson, R., Bennett, AJ., Bergmann, S., Bochud, M., Boerwinkle, E., Bonnefond, A., Bonnycastle, LL., Borch-Johnsen, K., Böttcher, Y., Brunner, E., Bumpstead, SJ., Charpentier, G., Chen, YD., Chines, P., Clarke, R., Coin, LJ., Cooper, MN., Cornelis, M., Crawford, G., Crisponi, L., Day, IN., de Geus EJ., Delplanque, J., Dina, C., Erdos, MR., Fedson, AC., Fischer-Rosinsky, A., Forouhi, NG., Fox, CS., Frants, R., Franzosi, MG., Galan, P., Goodarzi, MO., Graessler, J., Groves, CJ., Grundy, S., Gwilliam, R., Gyllensten, U., Hadjadj, S., Hallmans, G., Hammond, N., Han, X., Hartikainen, AL., Hassanali, N., Hayward, C., Heath, SC., Hercberg, S., Herder, C., Hicks, AA., Hillman, DR., Hingorani, AD., Hofman, A., Hui, J., Hung, J., Isomaa, B., Johnson, PR., Jørgensen, T., Jula, A., Kaakinen, M., Kaprio, J., Kesaniemi, YA., Kivimaki, M., Knight, B., Koskinen, S., Kovacs, P., Kyvik, KO., Lathrop, GM., Lawlor, DA., Le Bacquer, O., Lecoeur, C., Li, Y., Lyssenko, V., Mahley, R., Mangino, M., Manning, AK., Martínez-Larrad£££María Teresa£££ MT., McAteer, JB., McCulloch, LJ., McPherson, R., Meisinger, C., Melzer, D., Meyre, D., Mitchell, BD., Morken, MA., Mukherjee, S., Naitza, S., Narisu, N., Neville, MJ., Oostra, BA., Orrù, M., Pakyz, R., Palmer, CN., Paolisso, G., Pattaro, C., Pearson, D., Peden, JF., Pedersen, NL., Perola, M., Pfeiffer, AF., Pichler, I., Polasek, O., Posthuma, D., Potter, SC., Pouta, A., Province, MA., Psaty, BM., Rathmann, W., Rayner, NW., Rice, K., Ripatti, S., Rivadeneira, F., Roden, M., Rolandsson, O., Sandbaek, A., Sandhu, M., Sanna, S., Sayer, AA., Scheet, P., Scott, LJ., Seedorf, U., Sharp, SJ., Shields, B., Sigurðsson, G., Sijbrands, EJ., Silveira, A., Simpson, L., Singleton, A., Smith, NL., Sovio, U., Swift, A., Syddall, H., Syvänen, AC., Tanaka, T., Thorand, B., Tichet, J., Tönjes, A., Tuomi, T., Uitterlinden, AG., van Dijk KW., van Hoek, M., Varma, D., Visvikis-Siest, S., Vitart, V., Vogelzangs, N., Waeber, G., Wagner, PJ., Walley, A., Walters, GB., Ward, KL., Watkins, H., Weedon, MN., Wild, SH., Willemsen, G., Witteman, JC., Yarnell, JW., Zeggini, E., Zelenika, D., Zethelius, B., Zhai, G., Zhao, JH., Zillikens, MC., Borecki, IB., Loos, RJ., Meneton, P., Magnusson, PK., Nathan, DM., Williams, GH., Hattersley, AT., Silander, K., Salomaa, V., Smith, GD., Bornstein, SR., Schwarz, P., Spranger, J., Karpe, F., Shuldiner, AR., Cooper, C., Dedoussis, GV., Serrano-Ríos, M., Morris, AD., Lind, L., Palmer, LJ., Hu, FB., Franks, PW., Ebrahim, S., Marmot, M., Kao, WH., Pankow, JS., Sampson, MJ., Kuusisto, J., Laakso, M., Hansen, T., Pedersen, O., Pramstaller, PP., Wichmann, HE., Illig, T., Rudan, I., Wright, AF., Stumvoll, M., Campbell, H., Wilson, JF., Hamsten, A., Bergman, RN., Buchanan, TA., Collins, FS., Mohlke, KL., Tuomilehto, J., Valle, TT., Altshuler, D., Rotter, JI., Siscovick, DS., Penninx, BW., Boomsma, ID., Deloukas, P., Spector, TD., Frayling, TM., Ferrucci, L., Kong, A., Thorsteinsdottir, U., Stefansson, K., van Duijn CM., Aulchenko, YS., Cao, A., Scuteri, A., Schlessinger, D., Uda, M., Ruokonen, A., Jarvelin, MR., Waterworth, DM., Vollenweider, P., Peltonen, L., Mooser, V., Abecasis, RG., Wareham, NJ., Sladek, R., Froguel, P., Watanabe, RM., Meigs, JB., Groop, L., Boehnke, M., McCarthy, MI., Florez, JC., Barroso£££Inês£££ I., Feitosa, Mary [0000-0002-0933-2410], Heard-Costa, Nancy [0000-0001-9730-0306], Newman, Anne B [0000-0002-0106-1150], Miljkovic, Iva [0000-0002-3155-9777], Kritchevsky, Stephen B [0000-0003-3336-6781], Carr, J Jeffrey [0000-0002-4398-8237], Gudnason, Vilmunder [0000-0001-5696-0084], Cupples, L Adrienne [0000-0003-0273-7965], Apollo - University of Cambridge Repository, and Medical Research Council (MRC)

Subjects
Male, Netherlands Twin Register (NTR), Cancer Research, Adipose tissue, Genome-wide association study, QH426-470, FTO gene, Body Mass Index, 0302 clinical medicine, Genetics (clinical), TISSUE DISTRIBUTION, GENE-EXPRESSION, 2. Zero hunger, ATHEROSCLEROSIS MESA, 0303 health sciences, INSULIN-RESISTANCE, Sex Characteristics, MAGIC Consortium, Adult, Aged, Cytokines/genetics, European Continental Ancestry Group, Female, Genome-Wide Association Study, HapMap Project, Humans, Intra-Abdominal Fat, Lysophospholipase/genetics, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Proteins/genetics, Subcutaneous Fat, Abdominal, 3142 Public health care science, environmental and occupational health, CARDIOVASCULAR-DISEASE, OBESITY, Cytokines, Medicine, Lysophospholipase, Research Article, medicine.medical_specialty, Waist, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, 030209 endocrinology & metabolism, HIP RATIO, Biology, White People, GLGC Consortium, 03 medical and health sciences, Insulin resistance, Internal medicine, GIANT Consortium, medicine, Genetics, CORONARY-HEART-DISEASE, ddc:610, Molecular Biology, PERICARDIAL FAT, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, 0604 Genetics, Proteins, nutritional and metabolic diseases, medicine.disease, Obesity, Endocrinology, RISK-FACTORS, Body mass index, Developmental Biology
Abstract

Body fat distribution, particularly centralized obesity, is associated with metabolic risk above and beyond total adiposity. We performed genome-wide association of abdominal adipose depots quantified using computed tomography (CT) to uncover novel loci for body fat distribution among participants of European ancestry. Subcutaneous and visceral fat were quantified in 5,560 women and 4,997 men from 4 population-based studies. Genome-wide genotyping was performed using standard arrays and imputed to ∼2.5 million Hapmap SNPs. Each study performed a genome-wide association analysis of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), VAT adjusted for body mass index, and VAT/SAT ratio (a metric of the propensity to store fat viscerally as compared to subcutaneously) in the overall sample and in women and men separately. A weighted z-score meta-analysis was conducted. For the VAT/SAT ratio, our most significant p-value was rs11118316 at LYPLAL1 gene (p = 3.1×10E-09), previously identified in association with waist–hip ratio. For SAT, the most significant SNP was in the FTO gene (p = 5.9×10E-08). Given the known gender differences in body fat distribution, we performed sex-specific analyses. Our most significant finding was for VAT in women, rs1659258 near THNSL2 (p = 1.6×10-08), but not men (p = 0.75). Validation of this SNP in the GIANT consortium data demonstrated a similar sex-specific pattern, with observed significance in women (p = 0.006) but not men (p = 0.24) for BMI and waist circumference (p = 0.04 [women], p = 0.49 [men]). Finally, we interrogated our data for the 14 recently published loci for body fat distribution (measured by waist–hip ratio adjusted for BMI); associations were observed at 7 of these loci. In contrast, we observed associations at only 7/32 loci previously identified in association with BMI; the majority of overlap was observed with SAT. Genome-wide association for visceral and subcutaneous fat revealed a SNP for VAT in women. More refined phenotypes for body composition and fat distribution can detect new loci not previously uncovered in large-scale GWAS of anthropometric traits., Author Summary Body fat distribution, particularly centralized obesity, is associated with metabolic risk above and beyond total adiposity. We performed genome-wide association of abdominal adipose depots quantified using computed tomography (CT) to uncover novel loci for body fat distribution among participants of European ancestry. We quantified subcutaneous and visceral fat in more than 10,000 women and men who also had genome-wide association data available. Given the known gender differences in body fat distribution, we performed sex-specific analyses. Our most significant finding was for VAT in women, near the THNSL2 gene. These findings were not observed in men. We also interrogated our data for the 14 recently published loci for body fat distribution (measured by waist–hip ratio adjusted for BMI); associations were observed for 7 of these loci, most notably for VAT/SAT ratio. We conclude that genome-wide association for visceral and subcutaneous fat revealed a SNP for VAT in women. More refined phenotypes for body composition and fat distribution can detect new loci not uncovered in large-scale GWAS of anthropometric traits.

Published
2012
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22. Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals

Author

Seppo Koskinen, Christian Herder, Daniel I. Chasman, Andrew R. Wood, Jonna L. Grimsby, J.F. Wilson, Day Inm., Massimo Mangino, Gonneke Willemsen, Robert W. Mahley, Cristian Pattaro, Nicole L. Glazer, T.B. Harris, Irene Pichler, M S Sandhu, D. van Heemst, Christine Proença, Martha Ganser, Robert A. Hegele, Richa Saxena, Eleftheria Zeggini, Markku Laakso, Peter Kraft, Judith B. Borja, Karen L. Mohlke, J B Richards, de Geus Ejc., Robert Sladek, Cristen J. Willer, Samy Hadjadj, S.M. Boekholdt, Gina M. Peloso, Kijoung Song, Sutapa Mukherjee, Gudmar Thorleifsson, Winston Hide, Mark I. McCarthy, Ruth E. Pakyz, Marian Beekman, Ayellet V. Segrè, Inga Prokopenko, Ping An, George Dedoussis, Danielle Posthuma, Jeanette Erdmann, Simon J. Griffin, Nilesh J. Samani, Inke R. König, Frank B. Hu, Lokki M-L., David M. Evans, Xiaohui Li, Valgerdur Steinthorsdottir, Aimo Ruokonen, A Pouta, Kerrin S. Small, Cecilia M. Lindgren, O Le Bacquer, Xijing Han, Florian Kronenberg, E Katsareli, Christian Dina, S. Gabriel, Jochen Spranger, James S. Pankow, M. Kloppenburg, Penninx Bwjh., Torben Hansen, Josh Smith, Jennie Hui, Gordon H. Williams, Mark Seielstad, Ingrid B. Borecki, Weihua Zhang, Peter P. Pramstaller, Stephen J. Sharp, Neil R. Robertson, Zee Ryl., Mike Sampson, Angela Silveira, C.M. van Duijn, Anders Hamsten, Peter Shrader, Denis Rybin, Chen Y-Di., Gunnar Sigurdsson, Michael Stumvoll, Russel Tracy, Mark O. Goodarzi, Göran Hallmans, Michael R. Erdos, Valeriya Lyssenko, Juha Saharinen, Sven Bergmann, Jeffrey R. O'Connell, Debbie A Lawlor, Thomas Meitinger, Yvonne Böttcher, Jérôme Delplanque, Sarah G. Buxbaum, Silvia Naitza, Shah Ebrahim, Graham A. Hitman, Angelo Scuteri, Aroon D. Hingorani, Heribert Schunkert, François Pattou, Claudia Lamina, A L Elliott, Sekar Kathiresan, Dawn M. Waterworth, Jennifer A. Brody, Thomas Quertermous, Leena Peltonen, Josephine M. Egan, Daniel J. Rader, J F Peden, Yarnell Jwg., Daniel S. Pearson, Pfeiffer Afh., P S Chines, N Vogelzangs, Susan Redline, Alka M. Kanaya, T B Harris, J. V. van Vliet-Ostaptchouk, Ghislain Rocheleau, Rune R. Frants, Olga D. Carlson, James G. Wilson, Melissa Garcia, Ong Rt-H., Mark J. Caulfield, Tanya M. Teslovich, Loo B-M., Beatrice Knight, Andreas Ziegler, Claudia Langenberg, Yoon Shin Cho, Paul M. Ridker, Mark J. Rieder, Praveen Sethupathy, Bert Bravenboer, J. Viikari, Matt Neville, Ioannis M. Stylianou, Andrew Walley, Jarvelin M-R., Jarred B. McAteer, Ronald M. Krauss, Augustine Kong, Oluf Pedersen, Mark J. Daly, Andrew P. Morris, Anna F. Dominiczak, Stéphane Cauchi, Michael Boehnke, Christopher J. O'Donnell, Barbara Thorand, Peter M. Nilsson, Aaron Isaacs, Deborah A. Nickerson, Roza Blagieva, Mary F. Feitosa, Nicholas J. Wareham, Robert Roberts, J S Kooner, K W van Dijk, Tiinamaija Tuomi, Paul Scheet, Lynda M. Rose, Albert V. Smith, Rafn Benediktsson, Chiara Sabatti, Candace Guiducci, Lee M. Kaplan, Aki S. Havulinna, Toby Johnson, Samuli Ripatti, Erik Ingelsson, Mario A. Morken, Carl G. P. Platou, Anke Tönjes, Qi Sun, Narisu Narisu, S J Bumpstead, Jose M. Ordovas, Alan B. Feranil, L Groop, P Chines, Sara M. Willems, Perry Jrb., Matthew A. Allison, Jan Scott, Cécile Lecoeur, Kastelein Jjp., Herman A. Taylor, Anyuan Cao, Christopher J. Groves, Lincoln D. Stein, Laura J. Scott, John Beilby, Kristin G. Ardlie, Christopher S. Franklin, Yoav Ben-Shlomo, B M Shields, N J Timpson, Marco Orrù, Amélie Bonnefond, Kiran Musunuru, Murielle Bochud, Udo Seedorf, Yongmei Liu, Guillaume Lettre, Lee J-Y., Alan R. Shuldiner, Ryan P. Welch, David J. Hunter, John Whitfield, Klaus Strassburger, Khaw K-T., Hartikainen A-L., Gunnar Sigurðsson, Lu Qi, Richard N. Bergman, G M Lathrop, Sigrid W. Fouchier, T van Herpt, David S. Siscovick, Igor Rudan, Richard M. Watanabe, Themistocles L. Assimes, Nicholas G. Martin, Ozren Polasek, Dhiraj Varma, K Kim, Oliver Hofmann, Nicholas D. Hastie, S Bumpstead, Jose C. Florez, Fernando Rivadeneira, Katharine R. Owen, Braxton D. Mitchell, Alisa K. Manning, Abbas Dehghan, Bruce Bartholow Duncan, Cisca Wijmenga, Timo T. Valle, Jaakko Kaprio, Mika Kivimäki, B Shields, Laila Simpson, Tim D. Spector, Paul W. Franks, Guangju Zhai, María Teresa Martínez-Larrad, Janssens Acjw., Kim L. Ward, Inês Barroso, Xiuqing Guo, Rosa Maria Roccasecca, Zari Dastani, Reijo Laaksonen, Wilmar Igl, Vincent Mooser, Niels Grarup, Cornelia Huth, Christian Gieger, Fabio Marroni, Jaakko Tuomilehto, Doney Asf., Andrew C. Edmondson, Christian Fuchsberger, Meena Kumari, David M. Nathan, Reedik Mägi, Solomon K. Musani, U de Faire, Knut Borch-Johnsen, Masahiro Koseki, Giuseppe Paolisso, Norman Klopp, Caroline S. Fox, Nelson B. Freimer, Mika Kähönen, Peter Henneman, Diana Zelenika, K Willems-Vandijk, Steven A. McCarroll, Paul Elliott, Wichmann H-E., J. C. Bis, Nita G. Forouhi, Antti Jula, Witteman Jcm., Fredrik Karpe, Joseph Hung, Antje Fischer-Rosinsky, Eric J. Brunner, Elena Gonzalez, Soumya Raychaudhuri, Jian'an Luan, Josée Dupuis, Joshua C. Randall, Taesung Park, Francis S. Collins, Lori L. Bonnycastle, Andrew A. Hicks, Peter Kovacs, Thomas Illig, Maja Barbalić, David Couper, Jaspal S. Kooner, Damien C. Croteau-Chonka, Gavin Lucas, P J Wagner, Young-Jin Kim, Yurii S. Aulchenko, Aurelian Bidulescu, Ingrid Meulenbelt, Pilar Galan, Iris M. Heid, Michael N. Weedon, Serena Sanna, Sarah H. Wild, Hivert M-F., Patricia B. Munroe, Johan G. Eriksson, Teresa Ferreira, Robert A. Scott, A. Sandbaek, Kenneth Rice, Veronique Vitart, Xin Yuan, Leslie A. Lange, Hilma Holm, Jorge R. Kizer, Timothy M. Frayling, Marika Kaakinen, Liu C-T., Petersen A-K., Peter Schwarz, G B Walters, Palmer Cna., Jean Tichet, Bernhard Paulweber, Ying Wu, Alyson Hall, Christopher T. Johansen, David Masson, Martin Ladouceur, Christie M. Ballantyne, Tai E-S., Robert Luben, Guillaume Charpentier, Angela Döring, Philip J. Barter, Ruth McPherson, Benjamin F. Voight, Wolfgang Rathmann, Mark Walker, Markus Perola, M. A. Province, Veikko Salomaa, James B. Meigs, George Davey Smith, Robert Clarke, Gerard Waeber, Stefania Bandinelli, Sally L. Ricketts, Kaisa Silander, Loos Rjf., Amanda J. Bennett, John C. Chambers, Marilyn C. Cornelis, L A Cupples, Andrew T. Hattersley, M Sandhu, Marju Orho-Melander, C M van Duijn, Olli T. Raitakari, David Meyre, Ida Surakka, Jouke-Jan Hottenga, Uh H-W., Kari Stefansson, David Melzer, P E Slagboom, Kristian Midthjell, Robert K. Semple, James P. Pirruccello, Aloysius G Lieverse, Åsa Johansson, Michael Roden, Felicity Payne, Eric J.G. Sijbrands, N P Burtt, David R. Hillman, Michael Marmot, Todd Green, Eric E. Schadt, Sijbrands Ejg., Tien Yin Wong, Coin Ljm., K B Boström, Olov Rolandsson, A D Morris, David Altshuler, Harald Grallert, L C Groop, Alan F. Wright, Karen Kapur, Xueling Sim, Philippe Froguel, K O Kyvik, T. Lauritzen, Linda S. 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Hveem, K, Laakso, M, Morris, Ad, Palmer, Cn, Rudan, I, Sijbrands, E, Stein, Ld, Tuomilehto, J, Uitterlinden, A, Walker, M, Watanabe, Rm, Abecasis, Gr, Boehm, Bo, Campbell, H, Daly, Mj, Hattersley, At, Pedersen, O, Barroso, I, Groop, L, Sladek, R, Thorsteinsdottir, U, Wilson, Jf, Illig, T, Froguel, P, van Duijn, Cm, Stefansson, K, Altshuler, D, Boehnke, M, Mccarthy, Mi, Soranzo, N, Wheeler, E, Glazer, Nl, Bouatia Naji, N, Mägi, R, Randall, J, Elliott, P, Rybin, D, Dehghan, A, Hottenga, Jj, Song, K, Goel, A, Lajunen, T, Cavalcanti Proença, C, Kumari, M, Timpson, Nj, Zabena, C, Ingelsson, E, An, P, O'Connell, J, Luan, J, Elliott, A, Roccasecca, Rm, Pattou, F, Sethupathy, P, Ariyurek, Y, Barter, P, Beilby, Jp, Ben Shlomo, Y, Bergmann, S, Bochud, M, Bonnefond, A, Borch Johnsen, K, Böttcher, Y, Brunner, E, Bumpstead, Sj, Chen, Yd, Clarke, R, Coin, Lj, Cooper, Mn, Crisponi, L, Day, In, de Geus, Ej, Delplanque, J, Fedson, Ac, Fischer Rosinsky, A, Forouhi, Ng, Franzosi, Mg, Galan, P, Goodarzi, 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Strachan, Dp, Reilly, Mp, Samani, Nj, Schunkert, H, Cupples, La, Ridker, Pm, Rader, Dj, Kathiresan, S., Medical Research Council (MRC), Perry, John [0000-0001-6483-3771], Wareham, Nicholas [0000-0003-1422-2993], Langenberg, Claudia [0000-0002-5017-7344], Semple, Robert [0000-0001-6539-3069], Griffin, Simon [0000-0002-2157-4797], Barroso, Ines [0000-0001-5800-4520], Soranzo, Nicole [0000-0003-1095-3852], Wheeler, Eleanor [0000-0002-8616-6444], Luan, Jian'an [0000-0003-3137-6337], Forouhi, Nita [0000-0002-5041-248X], Sharp, Stephen [0000-0003-2375-1440], Sovio, Ulla [0000-0002-0799-1105], Zhao, Jing Hua [0000-0003-4930-3582], Luben, Robert [0000-0002-5088-6343], Khaw, Kay-Tee [0000-0002-8802-2903], Sandhu, Manjinder [0000-0002-2725-142X], Apollo - University of Cambridge Repository, Biological Psychology, Functional Genomics, Neuroscience Campus Amsterdam - Attention & Cognition, EMGO+ - Lifestyle, Overweight and Diabetes, Other departments, Experimental Vascular Medicine, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, Cardiology, Human genetics, Psychiatry, NCA - Attention & Cognition, EMGO - Lifestyle, overweight and diabetes, Lääketieteen yksikkö - School of Medicine, University of Tampere, Institute for Molecular Medicine Finland, Hjelt Institute (-2014), Clinicum, Department of General Practice and Primary Health Care, Department of Public Health, Haartman Institute (-2014), Transplantation Laboratory, Biostatistics Helsinki, Quantitative Genetics, Complex Disease Genetics, Genetic Epidemiology, DIAGRAM+ Consortium, MAGIC Consortium, GLGC Investigators, MuTHER Consortium, DIAGRAM Consortium, GIANT Consortium, Global B Pgen Consortium, Procardis Consortium, MAGIC investigators, GLGC Consortium, Olson, J., Kronmal, R., Robbins, J., Chaves, PH., Burke, G., Kuller, LH., Tracy, R., Gottdiener, J., Prineas, R., Becker, JT., Enright, P., Klein, R., and O'Leary, DH.

Subjects
Netherlands Twin Register (NTR), Male, Insulin Resistance/genetics, VARIANTS, 0302 clinical medicine, POPULATION, African Americans, blood/genetics, 0303 health sciences, education.field_of_study, Adiponectin/blood, Adiponectin/genetics, Asian Continental Ancestry Group, Cholesterol, HDL/genetics, Diabetes Mellitus, Type 2/genetics, European Continental Ancestry Group, Female, Gene Expression, Genetic Predisposition to Disease, Genome-Wide Association Study, Glucose Tolerance Test, Humans, Metabolic Networks and Pathways, Polymorphism, Single Nucleotide, Waist-Hip Ratio, Global B Pgen Consortium, MAGIC investigators, 3. Good health, Cholesterol, Medicine, Adiponectin, Type 2, medicine.medical_specialty, HDL, Biolääketieteet - Biomedicine, Single-nucleotide polymorphism, DIAGRAM Consortium, White People, Molecular Genetics, GLGC Consortium, 03 medical and health sciences, Asian People, SDG 3 - Good Health and Well-being, GIANT Consortium, Diabetes Mellitus, Genetics, DIAGRAM+ Consortium, GENOME-WIDE ASSOCIATION, Polymorphism, education, Biology, Molecular Biology, Ecology, Evolution, Behavior and Systematics, 0604 Genetics, Science & Technology, GLGC Investigators, nutritional and metabolic diseases, ta3121, medicine.disease, Obesity, Black or African American, blood/genetics, African Americans, Asian Continental Ancestry Group, Cholesterol, genetics, Diabetes Mellitus, genetics, European Continental Ancestry Group, Female, Gene Expression, Genetic Predisposition to Disease, Genome-Wide Association Study, Glucose Tolerance Test, Humans, Insulin Resistance, genetics, Male, Metabolic Networks and Pathways, Polymorphism, Single Nucleotide, Waist-Hip Ratio, Endocrinology, Diabetes Mellitus, Type 2, Developmental Biology, Type 2/genetics, Cancer Research, Type 2 diabetes, QH426-470, 030204 cardiovascular system & hematology, LIPID CONCENTRATIONS, GENETICS & HEREDITY, Genetics (clinical), RISK, 2. Zero hunger, INSULIN-RESISTANCE, Glucose tolerance test, medicine.diagnostic_test, MAGIC Consortium, Single Nucleotide, ADIPOSE-TISSUE, CORONARY-ARTERY-DISEASE, Life Sciences & Biomedicine, Research Article, Clinical Research Design, GENETIC-BASIS, Population, Insulin resistance, Internal medicine, Diabetes mellitus, medicine, ddc:610, 030304 developmental biology, RECEPTOR, Cholesterol, HDL, Human Genetics, HDL/genetics, 3121 General medicine, internal medicine and other clinical medicine, MuTHER Consortium, 3111 Biomedicine, Procardis Consortium, Insulin Resistance
Abstract

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10−8–1.2×10−43). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p, Author Summary Serum adiponectin levels are highly heritable and are inversely correlated with the risk of type 2 diabetes (T2D), coronary artery disease, stroke, and several metabolic traits. To identify common genetic variants associated with adiponectin levels and risk of T2D and metabolic traits, we conducted a meta-analysis of genome-wide association studies of 45,891 multi-ethnic individuals. In addition to confirming that variants at the ADIPOQ and CDH13 loci influence adiponectin levels, our analyses revealed that 10 new loci also affecting circulating adiponectin levels. We demonstrated that expression levels of several genes in these candidate regions are associated with serum adiponectin levels. Using a powerful novel method to assess the contribution of the identified variants with other traits using summary-level results from large-scale GWAS consortia, we provide evidence that the risk alleles for adiponectin are associated with deleterious changes in T2D risk and metabolic syndrome traits (triglycerides, HDL, post-prandial glucose, insulin, and waist-to-hip ratio), demonstrating that the identified loci, taken together, impact upon metabolic disease.

Published
2012
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