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1.  Association of Genetic Loci With Glucose Levels in Childhood and Adolescence 
Diabetes  2011;60(6):1805-1812.
PMCID: PMC3114379  PMID: 21515849
2.  Genetic Markers of Adult Obesity Risk Are Associated with Greater Early Infancy Weight Gain and Growth 
PLoS Medicine  2010;7(5):e1000284.
Ken Ong and colleagues genotyped children from the ALSPAC birth cohort and showed an association between greater early infancy gains in weight and length and genetic markers for adult obesity risk.
Methods and Findings
Please see later in the article for the Editors' Summary
Editors' Summary
The proportion of overweight and obese children is increasing across the globe. In the US, the Surgeon General estimates that, compared with 1980, twice as many children and three times the number of adolescents are now overweight. Worldwide, 22 million children under five years old are considered by the World Health Organization to be overweight.
Being overweight or obese in childhood is associated with poor physical and mental health. In addition, childhood obesity is considered a major risk factor for adult obesity, which is itself a major risk factor for cancer, heart disease, diabetes, osteoarthritis, and other chronic conditions.
The most commonly used measure of whether an adult is a healthy weight is body mass index (BMI), defined as weight in kilograms/(height in metres)2. However, adult categories of obese (>30) and overweight (>25) BMI are not directly applicable to children, whose BMI naturally varies as they grow. BMI can be used to screen children for being overweight and or obese but a diagnosis requires further information.
Why Was This Study Done?
As the numbers of obese and overweight children increase, a corresponding rise in future numbers of overweight and obese adults is also expected. This in turn is expected to lead to an increasing incidence of poor health. As a result, there is great interest among health professionals in possible pathways between childhood and adult obesity. It has been proposed that certain periods in childhood may be critical for the development of obesity.
In the last few years, ten genetic variants have been found to be more common in overweight or obese adults. Eight of these have also been linked to childhood BMI and/or obesity. The authors wanted to identify the timing of childhood weight changes that may be associated with adult obesity. Knowledge of obesity risk genetic variants gave them an opportunity to do so now, without following a set of children to adulthood.
What Did the Researchers Do and Find?
The authors analysed data gathered from a subset of 7,146 singleton white European children enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC) study, which is investigating associations between genetics, lifestyle, and health outcomes for a group of children in Bristol whose due date of birth fell between April 1991 and December 1992. They used knowledge of the children's genetic makeup to find associations between an obesity risk allele score—a measure of how many of the obesity risk genetic variants a child possessed—and the children's weight, height, BMI, levels of body fat (at nine years old), and rate of weight gain, up to age 11 years.
They found that, at birth, children with a higher obesity risk allele score were not any heavier, but in the immediate postnatal period they were less likely to be in the bottom 5% of the population for weight gain (adjusted for birthweight), often termed “failure to thrive.” At six weeks of age, children with a higher obesity risk allele score tended to be longer and heavier, even allowing for weight at birth.
After six weeks of age, the obesity risk allele score was not associated with any further increase in length/height, but it was associated with a more rapid weight gain between birth and age 11 years. BMI is derived from height and weight measurements, and the association between the obesity risk allele score and BMI was weak between birth and age three-and-a-half years, but after that age the association with BMI increased rapidly. By age nine, children with a higher obesity risk allele score tended to be heavier and taller, with more fat on their bodies.
What Do These Findings Mean?
The combined obesity allele risk score is associated with higher rates of weight gain and adult obesity, and so the authors conclude that weight gain and growth even in the first few weeks after birth may be the beginning of a pathway of greater adult obesity risk.
A study that tracks a population over time can find associations but it cannot show cause and effect. In addition, only a relatively small proportion (1.7%) of the variation in BMI at nine years of age is explained by the obesity risk allele score.
The authors' method of finding associations between childhood events and adult outcomes via genetic markers of risk of disease as an adult has a significant advantage: the authors did not have to follow the children themselves to adulthood, so their findings are more likely to be relevant to current populations. Despite this, this research does not yield advice for parents how to reduce their children's obesity risk. It does suggest that “failure to thrive” in the first six weeks of life is not simply due to a lack of provision of food by the baby's caregiver but that genetic factors also contribute to early weight gain and growth.
The study looked at the combined obesity risk allele score and the authors did not attempt to identify which individual alleles have greater or weaker associations with weight gain and overweight or obesity. This would require further research based on far larger numbers of babies and children. The findings may also not be relevant to children in other types of setting because of the effects of different nutrition and lifestyles.
Additional Information
Further information is available on the ALSPAC study
The UK National Health Service and other partners provide guidance on establishing a healthy lifestyle for children and families in their Change4Life programme
The International Obesity Taskforce is a global network of expertise and the advocacy arm of the International Association for the Study of Obesity. It works with the World Health Organization, other NGOs, and stakeholders and provides information on overweight and obesity
The Centers for Disease Control and Prevention (CDC) in the US provide guidance and tips on maintaining a healthy weight, including BMI calculators in both metric and Imperial measurements for both adults and children. They also provide BMI growth charts for boys and girls showing how healthy ranges vary for each sex at with age
The Royal College of Paediatrics and Child Health provides growth charts for weight and length/height from birth to age 4 years that are based on WHO 2006 growth standards and have been adapted for use in the UK
The CDC Web site provides information on overweight and obesity in adults and children, including definitions, causes, and data
The CDC also provide information on the role of genes in causing obesity.
The World Health Organization publishes a fact sheet on obesity, overweight and weight management, including links to childhood overweight and obesity
Wikipedia includes an article on childhood obesity (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
PMCID: PMC2876048  PMID: 20520848
3.  A Common Variant in the FTO Gene Is Associated with Body Mass Index and Predisposes to Childhood and Adult Obesity 
Science (New York, N.Y.)  2007;316(5826):889-894.
PMCID: PMC2646098  PMID: 17434869
BMJ Open  2013;3(11):e003797.
To investigate associations between modest levels of total and domain-specific (commuting, other utility, recreational) cycling and mortality from all causes, cardiovascular disease and cancer.
Population-based cohort study (European Prospective Investigation into Cancer and Nutrition study-Norfolk).
Participants were recruited from general practices in the east of England and attended health examinations between 1993 and 1997 and again between 1998 and 2000. At the first health assessment, participants reported their average weekly duration of cycling for all purposes using a simple measure of physical activity. At the second health assessment, participants reported a more detailed breakdown of their weekly cycling behaviour using the EPAQ2 physical activity questionnaire.
Adults aged 40–79 years at the first health assessment.
Primary outcome measure
All participants were followed for mortality (all-cause, cardiovascular and cancer) until March 2011.
There were 22 450 participants with complete data at the first health assessment, of whom 4398 died during follow-up; and 13 346 participants with complete data at the second health assessment, of whom 1670 died during follow-up. Preliminary analyses using exposure data from the first health assessment showed that cycling for at least 60 min/week in total was associated with a 9% reduced risk of all-cause mortality (adjusted HR 0.91, 95% CI 0.84 to 0.99). Using the more precise measures of cycling available from the second health assessment, all types of cycling were associated with greater total moderate-to-vigorous physical activity; however, there was little evidence of an association between overall or domain-specific cycling and mortality.
Cycling, in particular for utility purposes, was associated with greater moderate-to-vigorous and total physical activity. While this study provides tentative evidence that modest levels of cycling may reduce the risk of mortality, further research is required to confirm how much cycling is sufficient to induce health benefits.
PMCID: PMC3831097  PMID: 24231462
active travel; active commuting; physical activity
5.  Physical activity intensity, sedentary time, and body composition in preschoolers123 
Detailed associations between physical activity (PA) subcomponents, sedentary time, and body composition in preschoolers remain unclear.
We examined the magnitude of associations between objectively measured PA subcomponents and sedentary time with body composition in 4-y-old children.
We conducted a cross-sectional study in 398 preschool children recruited from the Southampton Women’s Survey. PA was measured by using accelerometry, and body composition was measured by using dual-energy X-ray absorptiometry. Associations between light physical activity, moderate physical activity (MPA), vigorous physical activity (VPA), and moderate-to-vigorous physical activity (MVPA) intensity; sedentary time; and body composition were analyzed by using repeated-measures linear regression with adjustment for age, sex, birth weight, maternal education, maternal BMI, smoking during pregnancy, and sleep duration. Sedentary time and PA were also mutually adjusted for one another to determine whether they were independently related to adiposity.
VPA was the only intensity of PA to exhibit strong inverse associations with both total adiposity [P < 0.001 for percentage of body fat and fat mass index (FMI)] and abdominal adiposity (P = 0.002 for trunk FMI). MVPA was inversely associated with total adiposity (P = 0.018 for percentage of body fat; P = 0.022 for FMI) but only because of the contribution of VPA, because MPA was unrelated to fatness (P ≥ 0.077). No associations were shown between the time spent sedentary and body composition (P ≥ 0.11).
In preschoolers, the time spent in VPA is strongly and independently associated with lower adiposity. In contrast, the time spent sedentary and in low-to-moderate–intensity PA was unrelated to adiposity. These results indicate that efforts to challenge pediatric obesity may benefit from prioritizing VPA.
PMCID: PMC3785144  PMID: 23553158
Diabetologia  2013;56:2367-2377.
Trial registration number NCT00237549
Electronic supplementary material
The online version of this article (doi:10.1007/s00125-013-3011-0) contains peer-reviewed but unedited supplementary material, which is available to authorised users.
PMCID: PMC3824356  PMID: 23959571
Diabetes screening; Health status; Intensive treatment; Patient-reported outcome measures; Primary care; Quality of life; Treatment satisfaction; Type 2 diabetes mellitus
Meta-analysis of case-control genome wide association studies (GWAS) for early onset and morbid obesity identified four variants in/near the PRL, PTER, MAF and NPC1 genes.
We aimed to validate association of these variants with obesity-related traits in population-based samples.
Genotypes and anthropometric traits were available in up to 31 083 adults from the Fenland, EPIC-Norfolk, Whitehall II, Ely and Hertfordshire studies and in 2 042 children and adolescents from the European Youth Heart Study. In each study, we tested associations of rs4712652 (near-PRL), rs10508503 (near-PTER), rs1424233 (near-MAF) and rs1805081 (NPC1), or proxy variants (r2>0.8), with the odds of being overweight and obese, as well as with BMI, percentage body fat (%BF) and waist circumference (WC). Associations were adjusted for sex, age and age2 in adults and for sex, age, age-group, country and maturity in children and adolescents. Summary statistics were combined using fixed effects meta-analysis methods.
We had 80% power to detect ORs of 1.046 to 1.092 for overweight and 1.067 to 1.136 for obesity. Variants near PRL, PTER and MAF were not associated with the odds of being overweight or obese, or with BMI, %BF or WC after meta-analysis (P > 0.15). The NPC1 variant rs1805081 showed some evidence of association with %BF (beta=0.013 SD/allele, P =0.040), but not with any of the remaining obesity-related traits (P >0.3).
Overall, these variants, which were identified in a GWAS for early onset and morbid obesity, do not seem to influence obesity-related traits in the general population.
PMCID: PMC3680864  PMID: 22430306
Obesity-susceptibility loci; genome-wide association; morbid; early-onset; anthropometric traits; children and adolescents; population-based
8.  Socio-demographic and behavioural correlates of physical activity perception in individuals with recently diagnosed diabetes: results from a cross-sectional study 
BMC Public Health  2013;13:678.
Physical activity (PA) levels in type 2 diabetes mellitus (T2DM) patients are generally low. Poor PA perception may impede healthy behaviour change in this high risk group. We describe (i) objective PA levels, (ii) the difference between objective and self-reported PA (‘PA disparity’) and the correlates of (iii) PA disparity and (iv) overestimation in recently diagnosed T2DM patients.
Cross-sectional analysis of 425 recently diagnosed T2DM patients aged 42 to 71, participating in the ADDITION-Plus study in Eastern England, UK. We define ‘PA disparity’ as the non-negative value of the difference (in mathematical terms the absolute difference) between objective and self-reported physical activity energy expenditure (PAEE in kJ · kg-1 · day-1). ‘Overestimators’ comprised those whose self-reported- exceeded objective-PAEE by 4.91 kJ · kg-1 · day-1(the equivalent of 30 minutes moderate activity per day). Multivariable linear regression examined the association between PA disparity (continuous) and socio-demographic, clinical, health behaviour, quality of life and psychological characteristics. Logistic regression examined the association between PA overestimation and individual characteristics.
Mean objective and self-reported PAEE levels ± SD were 34.4 ± 17.0 and 22.6 ± 19.4 kJ · kg-1 · day-1, respectively (difference in means =11.8; 95% CI = 9.7 to 13.9 kJ · kg-1 · day-1). Higher PA disparity was associated with male sex, younger age, lower socio-economic status and lower BMI. PA overestimators comprised 19% (n = 80), with those in routine/manual occupations more likely to be overestimators than those in managerial/professional occupations.
T2DM patients with poor physical activity perception are more likely to be male, younger, from a lower socio-economic class and to have a lower BMI. PA overestimators were more likely to be in lower socio-economic categories. Self-monitoring and targeted feedback, particularly to those in lower socio-economic categories, may improve PA perceptions and optimise interventions in T2DM patients. Our findings suggest that strategies for enabling realistic assessment of physical activity levels, through self-monitoring or feedback, warrant further investigation and may help refine and improve physical activity interventions.
PMCID: PMC3729669  PMID: 23883169
Type 2 diabetes mellitus; Physical activity; Overestimation; Awareness; Perception; Health behaviour; Lifestyle behaviour; Social correlates of health; Health promotion intervention
9.  A Prospective Study of the Association Between Quantity and Variety of Fruit and Vegetable Intake and Incident Type 2 Diabetes 
Diabetes Care  2012;35(6):1293-1300.
A greater quantity of combined F&V intake was associated with 21% lower hazard of T2D (HR 0.79 [95% CI 0.62–1.00]) comparing extreme tertiles, in adjusted analyses including variety. Separately, quantity of vegetable intake (0.76 [0.60–0.97]), but not fruit, was inversely associated with T2D in adjusted analysis. Greater variety in fruit (0.70 [0.53–0.91]), vegetable (0.77 [0.61–0.98]), and combined F&V (0.61 [0.48–0.78]) intake was associated with a lower hazard of T2D, independent of known confounders and quantity of intake comparing extreme tertiles.
PMCID: PMC3357245  PMID: 22474042
10.  The association of the mitochondrial DNA OriB variant (16184–16193 polycytosine tract) with type 2 diabetes in Europid populations 
Diabetologia  2013;56:1907-1913.
The association between the mitochondrial DNA 16181–16193 polycytosine variant (known as the OriB variant as it maps to the OriB origin of replication) and type 2 diabetes has not been reliably characterised, with studies reporting conflicting results. We report a systematic review of published literature in Europid populations, new data from the Norfolk Diabetes Case–Control Study and a meta-analysis to help quantify this association.
We performed a systematic review identifying all the studies of the OriB variant and type 2 diabetes in Europid populations published before January 2013. We typed the OriB variant by pyrosequencing and sequencing in the Norfolk Diabetes Case–Control Study, which comprised 5,574 type 2 diabetes cases and 6,950 population-based controls.
Overall, the meta-analysis included eight published studies plus the current new results, with a total of 11,794 type 2 diabetes cases and 14,465 controls. In the Norfolk Diabetes Case–Control Study, the OR for type 2 diabetes for the OriB variant was 1.09 (95% CI 0.96, 1.24). In a combined analysis, the relative risk for type 2 diabetes for the OriB variant in Europid populations was 1.10 (95% CI 1.01, 1.20; p = 0.03)
Results from this systematic review and meta-analysis suggest that the mitochondrial DNA OriB variant is modestly associated with an increased risk of type 2 diabetes in Europid populations, with an effect size comparable with that of recently identified variants from genome-wide association studies.
Electronic supplementary material
The online version of this article (doi:10.1007/s00125-013-2945-6) contains peer-reviewed but unedited supplementary material, which is available to authorised users.
PMCID: PMC3737432  PMID: 23702607
Europid populations; Meta-analysis; Mitochondrial DNA; OriB variant; Pyrosequencing; Systematic review; Type 2 diabetes
11.  Intrahepatic Lipid Content and Insulin Resistance Are More Strongly Associated with Impaired NEFA Suppression after Oral Glucose Loading Than with Fasting NEFA Levels in Healthy Older Individuals 
Introduction. The mechanisms underlying the association between insulin resistance and intrahepatic lipid (IHL) accumulation are not completely understood. We sought to determine whether this association was explained by differences in fasting non-esterified fatty acid (NEFA) levels and/or NEFA suppression after oral glucose loading. Materials and Methods. We performed a cross-sectional analysis of 70 healthy participants in the Hertfordshire Physical Activity Trial (39 males, age 71.3 ± 2.4 years) who underwent oral glucose tolerance testing with glucose, insulin, and NEFA levels measured over two hours. IHL was quantified with magnetic resonance spectroscopy. Insulin sensitivity was measured with the oral glucose insulin sensitivity (OGIS) model, the leptin: adiponectin ratio (LAR), and the homeostasis model assessment (HOMA). Results. Measures of insulin sensitivity were not associated with fasting NEFA levels, but OGIS was strongly associated with NEFA suppression at 30 minutes and strongly inversely associated with IHL. Moreover, LAR was strongly inversely associated with NEFA suppression and strongly associated with IHL. This latter association (beta = 1.11 [1.01, 1.21], P = 0.026) was explained by reduced NEFA suppression (P = 0.24 after adjustment). Conclusions. Impaired postprandial NEFA suppression, but not fasting NEFA, contributes to the strong and well-established association between whole body insulin resistance and liver fat accumulation.
PMCID: PMC3659510  PMID: 23737780
To investigate the relationship of body weight and its changes over time with physical activity.
Population-based prospective cohort study (Norfolk cohort of the European Prospective Investigation into Cancer and Nutrition, EPIC-Norfolk, United Kingdom)
25639 men and women aged 39-79 years at baseline. Physical activity was self-reported. Weight and height were measured by standard clinical procedures at baseline and self-reported at 18-month and 10-y follow-ups (calibrated against clinical measures). Main outcome measure was physical activity at the 10-y follow-up
Body weight and physical activity were inversely associated in cross-sectional analyses. In longitudinal analyses, an increase in weight was associated with higher risk of being inactive 10 years later, after adjusting for baseline activity, 18-month activity, sex, baseline age, prevalent diseases, socioeconomic status, education, smoking, total daily energy intake, and alcohol intake. Compared with stable weight, a gain in weight of >2 kg/y during short-, medium- and long-term was consistently and significantly associated with greater likelihood of physical inactivity after 10 y, with the most pronounced effect for long-term weight gain, OR=1.89 (95% CI: 1.30-2.70) in fully adjusted analysis. Weight gain of 0.5-2 kg/y over long term was substantially associated with physical inactivity after full adjustment, OR=1.26 (95% CI: 1.11-1.41).
Weight gain (during short-, medium- and long-term) is a significant determinant of future physical inactivity independent of baseline weight and activity. Compared with maintaining weight, moderate (0.5-2 kg/y) and large weight gain (>2 kg/y) significantly predict future inactivity; a potentially vicious cycle including further weight gain, obesity and complications associated with a sedentary lifestyle. Based on current predictions of obesity trends, we estimate that the prevalence of inactivity in England would exceed 60% in year 2020.
PMCID: PMC3635037  PMID: 22531093
physical activity; obesity; weight gain; cohort study; epidemiology
13.  Meta-analysis and imputation refines the association of 15q25 with smoking quantity 
Nature genetics  2010;42(5):436-440.
PMCID: PMC3612983  PMID: 20418889
14.  The EPIC-Norfolk Eye Study: rationale, methods and a cross-sectional analysis of visual impairment in a population-based cohort 
BMJ Open  2013;3(3):e002684.
To summarise the methods of the European Prospective Investigation of Cancer (EPIC)-Norfolk Eye Study, and to present data on the prevalence of visual impairment and associations with visual impairment in the participants.
A population-based cross-sectional study nested within an on-going prospective cohort study (EPIC).
East England population (the city of Norwich and its surrounding small towns and rural areas).
A total of 8623 participants aged 48–92 years attended the Eye Study and underwent assessment of visual acuity, autorefraction, biometry, tonometry, corneal biomechanical measures, scanning laser polarimetry, confocal scanning laser ophthalmoscopy, fundal photography and automated perimetry.
Outcome measures
Visual impairment was defined according to the WHO classification and the UK driving standard, and was based on presenting visual acuity. Summary measures of other ophthalmic measurements are also presented.
The prevalence (95% CI) of WHO-defined moderate-to-severe visual impairment and blindness was 0.74% (0.55% to 0.92%). The prevalence (95% CI) of presenting visual acuity worse than the UK driving standard was 5.87% (5.38% to 6.37%). Older age was significantly associated with visual impairment or blindness (p<0.001). Presenting visual acuity worse than UK driving standard was associated with older age (p<0.001), female sex (p=0.005) and lower educational level (p=0.022).
The prevalence of blindness and visual impairment in this selected population was low. Visual impairment was more likely in older participants, women and those with a lower educational level.
PMCID: PMC3612817  PMID: 23516272
15.  Seropositivity and Higher Immunoglobulin G Antibody Levels Against Cytomegalovirus Are Associated With Mortality in the Population-Based European Prospective Investigation of Cancer–Norfolk Cohort 
After adjustment for a range of possible confounders, cytomegalovirus seropositivity and cytomegalovirus immunoglobulin G antibody levels were associated with all-cause mortality in the EPIC-Norfolk population-based cohort study.
Background. The relationship between cytomegalovirus (CMV) infection and mortality among immunocompetent individuals is uncertain. We aimed to examine whether seropositivity for CMV and the level of CMV immunoglobulin G (IgG) antibody are associated with all-cause and cause-specific mortality.
Methods. We used data from a random sample of 13 090 participants aged 40–79 years at recruitment in 1993–1997 to the European Prospective Investigation of Cancer–Norfolk population-based cohort study. We measured baseline IgG antibody levels against CMV. Death certificates were obtained for all participants who died before 31 March 2011. Codes for the underlying cause of death were used to investigate cause-specific mortality.
Results. A total of 2514 deaths occurred during a mean follow-up of 14.3 years (SD, 3.3 years). Compared to seronegative participants (age- and sex-adjusted mortality rate, 12.4 [95% confidence interval {CI}, 11.3–13.2] per 1000 person-years at risk), rates increased across thirds of IgG antibody levels (score test of trend P < .0001). CMV seropositivity (prevalence 59%) was associated with increased all-cause mortality (age- and sex-adjusted hazard ratio [HR], 1.16 [95% CI, 1.07–1.26]), similarly in men and women (P for interaction = .52). The association persisted after additionally adjusting for measures of socioeconomic status and possible confounders. Cause-specific analyses suggested that increased mortality from cardiovascular disease (HR, 1.06 [95% CI, .91–1.24]), cancer (HR, 1.13 [95% CI, .98–1.31]), and other causes (HR, 1.23 [95% CI, 1.04–1.47) all appeared to contribute to the overall associations.
Conclusions. Seropositivity and higher IgG antibody levels against CMV are associated with increased mortality and after adjustment for a range of potential confounders in the general population.
PMCID: PMC3634310  PMID: 23442763
cytomegalovirus; cancer; mortality; cohort study; cardiovascular disease
16.  An Ensemble Learning Approach Jointly Modeling Main and Interaction Effects in Genetic Association Studies 
Genetic epidemiology  2008;32(4):285-300.
Complex diseases are presumed to be the results of interactions of several genes and environmental factors, with each gene only having a small effect on the disease. Thus, the methods that can account for gene-gene interactions to search for a set of marker loci in different genes or across genome and to analyze these loci jointly are critical. In this article, we propose an ensemble learning approach (ELA) to detect a set of loci whose main and interaction effects jointly have a significant association with the trait. In the ELA, we first search for “base learners” and then combine the effects of the base learners by a linear model. Each base learner represents a main effect or an interaction effect. The result of the ELA is easy to interpret. When the ELA is applied to analyze a data set, we can get a final model, an overall P-value of the association test between the set of loci involved in the final model and the trait, and an importance measure for each base learner and each marker involved in the final model. The final model is a linear combination of some base learners. We know which base learner represents a main effect and which one represents an interaction effect. The importance measure of each base learner or marker can tell us the relative importance of the base learner or marker in the final model. We used intensive simulation studies as well as a real data set to evaluate the performance of the ELA. Our simulation studies demonstrated that the ELA is more powerful than the single-marker test in all the simulation scenarios. The ELA also outperformed the other three existing multi-locus methods in almost all cases. In an application to a large-scale case-control study for Type 2 diabetes, the ELA identified 11 single nucleotide polymorphisms that have a significant multi-locus effect (P-value = 0.01), while none of the single nucleotide polymorphisms showed significant marginal effects and none of the two-locus combinations showed significant two-locus interaction effects.
PMCID: PMC3572743  PMID: 18205210
epistasis; association study; complex disease; Type 2 diabetes
17.  Associations between the Pubertal Timing-Related Variant in LIN28B and BMI Vary Across the Life Course 
The common C allele of rs314276 in LIN28B has been robustly associated with earlier age at menarche in girls and associated with earlier timing of other pubertal traits in both sexes.
Our objective was to explore the associations between rs314276, as a marker of earlier pubertal timing, and body mass index (BMI), weight, and height across the life course.
The rs314276 in LIN28B was genotyped in 1242 men and 1209 women born in 1946 and participating in the Medical Research Council National Survey of Health and Development. Birth weight was recorded, and height and weight were measured or self-reported repeatedly at 11 time points between ages 2 and 53 yr. Polynomial mixed models were used to test whether additive genetic associations with SD scores (SDS) for BMI and height changed with age between 0 and 53 yr.
Longitudinal analyses revealed age-dependent associations between rs314276 genotype and BMI (P < 0.001 for genotype-by-age2 interaction) and body weight (P < 0.001 for genotype-by-age2 interaction) in women, but not in men. In women only, the C allele at rs314276 was associated with higher BMI SDS from ages 15–43 yr. In contrast, C allele associations with shorter height SDS were apparent in both men and women and did not vary with age.
A common genetic variant in LIN28B that confers earlier puberty was associated with a prolonged increase in BMI during adolescence and early to mid-adulthood in women only. Such genetic associations may provide insights into the direct effects of pubertal timing on obesity risk.
PMCID: PMC3504301  PMID: 20962026
Lancet  2012;380(9855):1741-1748.
The increasing prevalence of type 2 diabetes poses a major public health challenge. Population-based screening and early treatment for type 2 diabetes could reduce this growing burden. However, uncertainty persists around the benefits of screening for type 2 diabetes. We assessed the effect of a population-based stepwise screening programme on mortality.
In a pragmatic parallel group, cluster-randomised trial, 33 general practices in eastern England were randomly assigned by the method of minimisation in an unbalanced design to: screening followed by intensive multifactorial treatment for people diagnosed with diabetes (n=15); screening plus routine care of diabetes according to national guidelines (n=13); and a no-screening control group (n=5). The study population consisted of 20 184 individuals aged 40–69 years (mean 58 years), at high risk of prevalent undiagnosed diabetes, on the basis of a previously validated risk score. In screening practices, individuals were invited to a stepwise programme including random capillary blood glucose and glycated haemoglobin (HbA1c) tests, a fasting capillary blood glucose test, and a confirmatory oral glucose tolerance test. The primary outcome was all-cause mortality. All participants were flagged for mortality surveillance by the England and Wales Office of National Statistics. Analysis was by intention-to-screen and compared all-cause mortality rates between screening and control groups. This study is registered, number ISRCTN86769081.
Of 16 047 high-risk individuals in screening practices, 15 089 (94%) were invited for screening during 2001–06, 11 737 (73%) attended, and 466 (3%) were diagnosed with diabetes. 4137 control individuals were followed up. During 184 057 person-years of follow up (median duration 9·6 years [IQR 8·9–9·9]), there were 1532 deaths in the screening practices and 377 in control practices (mortality hazard ratio [HR] 1·06, 95% CI 0·90–1·25). We noted no significant reduction in cardiovascular (HR 1·02, 95% CI 0·75–1·38), cancer (1·08, 0·90–1·30), or diabetes-related mortality (1·26, 0·75–2·10) associated with invitation to screening.
In this large UK sample, screening for type 2 diabetes in patients at increased risk was not associated with a reduction in all-cause, cardiovascular, or diabetes-related mortality within 10 years. The benefits of screening might be smaller than expected and restricted to individuals with detectable disease.
Wellcome Trust; UK Medical Research Council; National Health Service research and development support; UK National Institute for Health Research; University of Aarhus, Denmark; Bio-Rad.
PMCID: PMC3607818  PMID: 23040422
19.  Epidemiological Study Designs to Investigate Gene–Behavior Interactions in the Context of Human Obesity 
Obesity (Silver Spring, Md.)  2008;16(Suppl 3):S66-S71.
The epidemiology of obesity suggests that, for the majority of individuals, the disorder arises from an interaction between genetic predisposition and lifestyle behaviors such as dietary intake and physical activity. Unravelling the molecular basis of such interactions is complex but is becoming a realistic proposition as evidence emerges from whole genome association studies of genetic variants that are definitively associated with obesity. A range of possible study designs is available for investigating gene–lifestyle interaction, and the strengths and weaknesses of each approach are discussed in this article. Given the likely small main effect of common genetic variants and the difficulties in demonstrating associations of lifestyle factors with future risk of obesity, we would favor an analytical approach based on the clear specification of prior probabilities to reduce the likelihood of false discovery. Mixed approaches combining data from large-scale observational studies with smaller intervention trials may be ideal. In designing new studies to investigate these issues, a key choice is how precisely to quantify the important, but difficult to measure lifestyle behaviors. It is clear from power calculations that an approach based on enhancing precision of measurement of diet and physical activity is critical.
The high heritability of obesity coupled with the rapid increase in prevalence suggests that a combination of genetic and behavioral factors is critical to the etiology of obesity (1). It is easy to propose such a model for the development of obesity, but it is altogether much harder to identify the molecular mechanisms that underlie such a model. In this article, we review overall strategies and possible epidemiological study designs for investigating how genetic and behavioral risk factors combine to lead to excess weight gain.
PMCID: PMC2703295  PMID: 19037217
20.  Mammographic breast density and breast cancer: evidence of a shared genetic basis 
Cancer research  2012;72(6):1478-1484.
Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3628 breast cancer cases and 5190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of SNPs were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case-control status as the outcome. This analysis was repeated using ten different cut-offs for the most significant density SNPs (1-10% representing 5,222-50,899 SNPs). Permutation analysis was also performed across all 10 cut-offs. The association between risk score and breast cancer was significant for all cut-offs from 3-10% of top density SNPs, being most significant for the 6% (2-sided P=0.002) to 10% (P=0.001) cut-offs (overall permutation P=0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR= 1.31 (95%CI 1.08-1.59)] compared to women in the bottom 10%. Together, our results demonstrate that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants.
PMCID: PMC3378688  PMID: 22266113
breast cancer; mammographic density; SNPs; polygenic; Mendelian Randomisation
Diabetes care  2012;35(6):1293-1300.
The association between quantity of fruit and vegetable intake and risk of type 2 diabetes (T2D) is not clear, and the relationship with variety of intake is unknown. The current study examined the association of both quantity and variety of fruit and vegetable intake and risk of T2D.
Research Design and Methods
We examined the 11-year incidence of T2D in relation to quantity and variety of fruit, vegetables and combined fruit and vegetable intake in a case-cohort study of 3,704 participants (n=653 T2D cases) nested within the European Prospective Investigation into Cancer and Nutrition-Norfolk Study, who completed 7-day prospective food diaries. Variety of intake was derived from the total number of different items consumed in a one week period. Multivariable Prentice-weighted Cox regression was used to estimate hazard ratios (HR) and 95% CI.
Greater quantity of combined fruit and vegetable intake was associated with 21% lower hazard of T2D (HR 0.79; 0.62-1.00) comparing extreme tertiles, in adjusted analyses including variety. Separately, quantity of vegetable intake (HR 0.76; 0.60-0.97), but not fruit, was inversely associated with T2D in adjusted analysis. Greater variety in fruit (HR 0.70; 0.53-0.91), vegetable (HR 0.77; 0.61-0.98), and combined fruit and vegetable (HR 0.61; 0.48-0.78) intake was associated with a lower hazard of T2D, independent of known confounders and quantity of intake comparing extreme tertiles.
These findings suggest that a diet characterised by greater quantity of vegetable and greater variety of both fruit and vegetable intake is associated with a reduced risk of T2D.
PMCID: PMC3357245  PMID: 22474042
22.  Associations of Common Genetic Variants With Age-Related Changes in Fasting and Postload Glucose 
Diabetes  2011;60(5):1617-1623.
In the general, nondiabetic population, fasting glucose increases only slightly over time, whereas 2-h postload glucose shows a much steeper age-related rise. The reasons underlying these different age trajectories are unknown. We investigated whether common genetic variants associated with fasting and 2-h glucose contribute to age-related changes of these traits.
We studied 5,196 nondiabetic participants of the Whitehall II cohort (aged 40–78 years) attending up to four 5-yearly oral glucose tolerance tests. A genetic score was calculated separately for fasting and 2-h glucose, including 16 and 5 single nucleotide polymorphisms, respectively. Longitudinal modeling with age centered at 55 years was used to study the effects of each genotype and genetic score on fasting and 2-h glucose and their interactions with age, adjusting for sex and time-varying BMI.
The fasting glucose genetic score was significantly associated with fasting glucose with a 0.029 mmol/L (95% CI 0.023–0.034) difference (P = 2.76 × 10−21) per genetic score point, an association that remained constant over time (age interaction P = 0.17). Two-hour glucose levels differed by 0.076 mmol/L (0.047–0.105) per genetic score point (P = 3.1 × 10−7); notably, this effect became stronger with increasing age by 0.006 mmol/L (0.003–0.009) per genetic score point per year (age interaction P = 3.0 × 10−5), resulting in diverging age trajectories by genetic score.
Common genetic variants contribute to the age-related rise of 2-h glucose levels, whereas associations of variants for fasting glucose are constant over time, in line with stable age trajectories of fasting glucose.
PMCID: PMC3292338  PMID: 21441441
Methods and Results
PMCID: PMC3319296  PMID: 20829508
Angplt4; E40K; T266M; cardiovascular disease; LPL
24.  Incidence of Type 2 Diabetes Using Proposed HbA1c Diagnostic Criteria in the European Prospective Investigation of Cancer–Norfolk Cohort 
Diabetes Care  2011;34(4):950-956.
To evaluate the incidence and relative risk of type 2 diabetes defined by the newly proposed HbA1c diagnostic criteria in groups categorized by different baseline HbA1c levels.
Using data from the European Prospective Investigation of Cancer (EPIC)-Norfolk cohort with repeat HbA1c measurements, we estimated the prevalence of known and previously undiagnosed diabetes at baseline (baseline HbA1c ≥6.5%) and the incidence of diabetes over 3 years. We also examined the incidence and corresponding odds ratios (ORs) by different levels of baseline HbA1c. Incident diabetes was defined clinically (self-report at follow-up, prescribed diabetes medication, or inclusion on a diabetes register) or biochemically (HbA1c ≥6.5% at the second health assessment), or both.
The overall prevalence of diabetes was 4.7%; 41% of prevalent cases were previously undiagnosed. Among 5,735 participants without diabetes at baseline (identified clinically or using HbA1c criteria, or both), 72 developed diabetes over 3 years (1.3% [95% CI 1.0–1.5]), of which 49% were identified using the HbA1c criteria. In 6% of the total population, the baseline HbA1c was 6.0–6.4%; 36% of incident cases arose in this group. The incidence of diabetes in this group was 15 times higher than in those with a baseline HbA1c of <5.0% (OR 15.5 [95% CI 7.2–33.3]).
The cumulative incidence of diabetes defined using a newly proposed HbA1c threshold in this middle-aged British cohort was 1.3% over 3 years. Targeting interventions to individuals with an HbA1c of 6.0–6.4% might represent a feasible preventive strategy, although complementary population-based preventive strategies are also needed to reduce the growing burden of diabetes.
PMCID: PMC3064056  PMID: 20622160
Background: Longitudinal growth associations with genetic variants identified for adult BMI may provide insights into the timing of obesity susceptibility.
Objective: The objective was to explore associations of known BMI loci with measures of body size from birth to adulthood.
Design: A total of 2537 individuals from a longitudinal British birth cohort were genotyped for 11 genetic variants robustly associated with adult BMI (in/near FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, ETV5, SEC16B, SH2B1, and MTCH2). We derived an obesity-risk-allele score, comprising the sum of BMI-increasing alleles in each individual, and examined this for an association with birth weight and repeated measures of weight, height, and BMI SD scores (SDS) at 11 time points between ages 2 and 53 y.
Results: The obesity-risk-allele score showed borderline significant association with birth weight (0.019 SDS/allele; P = 0.05) and was more clearly associated with higher weight and BMI at all time points between ages 2 and 53 y; the strongest associations with weight occurred at ages 11 and 20 y (both 0.056 SDS/allele). In longitudinal analyses, the score was positively associated with weight gain only between birth and 11 y (0.003 SDS/allele per year; 95% CI: 0.001, 0.004; P = 0.001). The risk-allele score was associated with taller height at 7 y (0.031 SDS/allele; P = 0.002) and greater height gains between 2 and 7 y (0.007 SDS/allele per year; P < 0.001), but not with adult height (P = 0.5).
Conclusions: The combined effect of adult obesity susceptibility variants on weight gain was confined to childhood. These variants conferred a faster tempo of height growth that was evident before the pubertal years.
PMCID: PMC3325838  PMID: 22456663

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