To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 = × 10−50) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 × 10−15). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 × 10−7) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 × 10−57) and GCK (rs4607517, P = 1.0 × 10−25) loci.

Context

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.

Objective

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.

Methods

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.

Results

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.

Conclusion

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.

Introduction

Obesity-susceptibility loci have been related to adiposity traits in adults and may affect body fat estimates in adolescence. There are indications that different sets of obesity-susceptibility loci influence level of and change in obesity-related traits from adolescence to adulthood.

Objectives

To investigate whether previously reported obesity-susceptible loci in adults influence adiposity traits in adolescence and change in BMI and waist circumference (WC) from adolescence into young adulthood. We also examined whether physical activity modifies the effects of these genetic loci on adiposity-related traits.

Methods

Nine obesity-susceptibility variants were genotyped in 1 643 adolescents (13–19 years old) from the HUNT study, Norway, who were followed-up into young adulthood. Lifestyle was assessed using questionnaires and anthropometric measurements were taken. The effects of genetic variants individually and combined in a genetic predisposition score (GPS) on obesity-related traits were studied cross-sectionally and longitudinally. A modifying effect of physical activity was tested.

Results

The GPS was significantly associated to BMI (B: 0.046 SD/allele [0.020, 0.073], p = 0.001) in adolescence and in young adulthood (B: 0.041 SD/allele [0.015, 0.067], p = 0.002) as it was to waist circumference (WC). The GPS was not associated to change in BMI (p = 0.762) or WC (p = 0.726). We found no significant interaction effect between the GPS and physical activity.

Conclusions

Our observations suggest that obesity-susceptibility loci established in adults affect BMI and WC already in adolescence. However, an association with change in adiposity-related traits from adolescence to adulthood could not be verified for these loci. Neither could an attenuating effect of physical activity on the association between the obesity-susceptibility genes and body fat estimates be revealed.

OBJECTIVE

To investigate whether associations of common genetic variants recently identified for fasting glucose or insulin levels in nondiabetic adults are detectable in healthy children and adolescents.

RESEARCH DESIGN AND METHODS

A total of 16 single nucleotide polymorphisms (SNPs) associated with fasting glucose were genotyped in six studies of children and adolescents of European origin, including over 6,000 boys and girls aged 9–16 years. We performed meta-analyses to test associations of individual SNPs and a weighted risk score of the 16 loci with fasting glucose.

RESULTS

Nine loci were associated with glucose levels in healthy children and adolescents, with four of these associations reported in previous studies and five reported here for the first time (GLIS3, PROX1, SLC2A2, ADCY5, and CRY2). Effect sizes were similar to those in adults, suggesting age-independent effects of these fasting glucose loci. Children and adolescents carrying glucose-raising alleles of G6PC2, MTNR1B, GCK, and GLIS3 also showed reduced β-cell function, as indicated by homeostasis model assessment of β-cell function. Analysis using a weighted risk score showed an increase [β (95% CI)] in fasting glucose level of 0.026 mmol/L (0.021–0.031) for each unit increase in the score.

CONCLUSIONS

Novel fasting glucose loci identified in genome-wide association studies of adults are associated with altered fasting glucose levels in healthy children and adolescents with effect sizes comparable to adults. In nondiabetic adults, fasting glucose changes little over time, and our results suggest that age-independent effects of fasting glucose loci contribute to long-term interindividual differences in glucose levels from childhood onwards.

Genome-wide association studies have identified SNPs reproducibly associated with type 2 diabetes (T2D). We examined the effect of genetic predisposition to T2D on insulin sensitivity and secretion using detailed phenotyping in overweight individuals with no diagnosis of T2D. Furthermore, we investigated whether this genetic predisposition modifies the responses in beta-cell function and insulin sensitivity to a 24-week dietary intervention. We genotyped 25 T2D-associated SNPs in 377 white participants from the RISCK study. Participants underwent an IVGTT prior to and following a dietary intervention that aimed to lower saturated fat intake by replacement with monounsaturated fat or carbohydrate. We composed a genetic predisposition score (T2D-GPS) by summing the T2D risk-increasing alleles of the 25 SNPs and tested for association with insulin secretion and sensitivity at baseline, and with the change in response to the dietary intervention. At baseline, a higher T2D-GPS was associated with lower acute insulin secretion (AIRg 4% lower/risk allele, P = 0.006) and lower insulin secretion for a given level of insulin sensitivity, assessed by the disposition index (DI 5% lower/risk allele, P = 0.002), but not with insulin sensitivity (Si). T2D-GPS did not modify changes in insulin secretion, insulin sensitivity or the disposition index in response to the dietary interventions to lower saturated fat. Participants genetically predisposed to T2D have an impaired ability to compensate for peripheral insulin resistance with insulin secretion at baseline, but this does not modify the response to a reduction in dietary saturated fat through iso-energetic replacement with carbohydrate or monounsaturated fat.

Electronic supplementary material

The online version of this article (doi:10.1007/s12263-012-0284-8) contains supplementary material, which is available to authorized users.

Evidence for a major role of genetic factors in the determination of body mass index (BMI) comes from studies of related individuals. Despite consistent evidence for a heritable component of BMI, estimates of BMI heritability vary widely between studies and the reasons for this remain unclear. While some variation is natural due to differences between populations and settings, study design factors may also explain some of the heterogeneity. We performed a systematic review that identified 88 independent estimates of BMI heritability from twin studies (total 140,525 twins) and 27 estimates from family studies (42,968 family members). BMI heritability estimates from twin studies ranged from 0.47 to 0.90 (5th/50th/95th centiles: 0.58/0.75/0.87) and were generally higher than those from family studies (range: 0.24–0.81; 5th/50th/95th centiles: 0.25/0.46/0.68). Meta-regression of the results from twin studies showed that BMI heritability estimates were 0.07 (P = 0.001) higher in children than in adults; estimates increased with mean age among childhood studies (+0.012/year, P = 0.002), but decreased with mean age in adult studies (−0.002/year, P = 0.002). Heritability estimates derived from AE twin models (which assume no contribution of shared environment) were 0.12 higher than those from ACE models (P < 0.001), whilst lower estimates were associated with self reported versus DNA-based determination of zygosity (−0.04, P = 0.02), and with self reported versus measured BMI (−0.05, P = 0.03). Although the observed differences in heritability according to aspects of study design are relatively small, together, the above factors explained 47% of the heterogeneity in estimates of BMI heritability from twin studies. In summary, while some variation in BMI heritability is expected due to population-level differences, study design factors explained nearly half the heterogeneity reported in twin studies. The genetic contribution to BMI appears to vary with age and may have a greater influence during childhood than adult life.

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 (Ntotal = 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.

The close correspondence between energy intake and expenditure over prolonged time periods, coupled with an apparent protection of the level of body adiposity in the face of perturbations of energy balance, has led to the idea that body fatness is regulated via mechanisms that control intake and energy expenditure. Two models have dominated the discussion of how this regulation might take place. The set point model is rooted in physiology, genetics and molecular biology, and suggests that there is an active feedback mechanism linking adipose tissue (stored energy) to intake and expenditure via a set point, presumably encoded in the brain. This model is consistent with many of the biological aspects of energy balance, but struggles to explain the many significant environmental and social influences on obesity, food intake and physical activity. More importantly, the set point model does not effectively explain the ‘obesity epidemic’ – the large increase in body weight and adiposity of a large proportion of individuals in many countries since the 1980s. An alternative model, called the settling point model, is based on the idea that there is passive feedback between the size of the body stores and aspects of expenditure. This model accommodates many of the social and environmental characteristics of energy balance, but struggles to explain some of the biological and genetic aspects. The shortcomings of these two models reflect their failure to address the gene-by-environment interactions that dominate the regulation of body weight. We discuss two additional models – the general intake model and the dual intervention point model – that address this issue and might offer better ways to understand how body fatness is controlled.

High percent mammographic density adjusted for age and body mass index (BMI) is one of the strongest risk factors for breast cancer. We conducted a meta-analysis of five genome-wide association studies of percent mammographic density and report an association with rs10995190 in ZNF365 (combined P=9×6·10−10). This finding might partly explain the underlying biology of the recently discovered association between common variants in ZNF365 and breast cancer risk.

Background

Recent genome-wide association studies have identified a number of common variants associated with fasting glucose homeostasis and type 2 diabetes in populations of European origin. This is a replication study to examine whether such associations are also observed in Chinese Hans.

Methods

We genotyped nine variants in or near MADD, ADRA2A, CRY2, GLIS3, PROX1, FADS1, C2CD4B, IGF1 and IRS1 in a population-based cohort including 3,210 unrelated Chinese Hans from Beijing and Shanghai.

Results

We confirmed the associations of GLIS3-rs7034200 with fasting glucose (beta = 0.07 mmol/l, P = 0.03), beta cell function (HOMA-B) (beta = −3.03%, P = 0.009), and type 2 diabetes (OR [95%CI]  = 1.27 [1.09–1.49], P = 0.003) after adjustment for age, sex, region and BMI. The association for type 2 diabetes remained significant after adjusting for other diabetes related risk factors including family history of diabetes, lipid profile, medication information, hypertension and life style factors, while further adjustment for HOMA-B abolished the association. The A-allele of CRY2-rs11605924 was moderately associated with increased risk of combined IFG/type 2 diabetes (OR [95%CI]  = 1.15[1.01–1.30], P = 0.04). SNPs in or near MADD, ADRA2A, PROX1, FADS1, C2CD4B, IGF1, and IRS1 did not exhibit significant associations with type 2 diabetes or related glycemic traits (P≥0.10).

Conclusions

In conclusion, our results indicate the associations of GLIS3 locus with type 2 diabetes and impaired fasting glucose in Chinese Hans, partially mediated through impaired beta-cell function. In addition, we also found modest evidence for the association of CRY2-rs11605924 with combined IFG/type 2 diabetes.

To infer the causal association between childhood BMI and age at menarche, we performed a mendelian randomisation analysis using twelve established “BMI-increasing” genetic variants as an instrumental variable (IV) for higher BMI. In 8,156 women of European descent from the EPIC-Norfolk cohort, height was measured at age 39–77 years; age at menarche was self-recalled, as was body weight at age 20 years, and BMI at 20 was calculated as a proxy for childhood BMI. DNA was genotyped for twelve BMI-associated common variants (in/near FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, ETV5, MTCH2, SEC16B, FAIM2 and SH2B1), and for each individual a “BMI-increasing-allele-score” was calculated by summing the number of BMI-increasing alleles across all 12 loci. Using this BMI-increasing-allele-score as an instrumental variable for BMI, each 1 kg/m2 increase in childhood BMI was predicted to result in a 6.5% (95% CI: 4.6–8.5%) higher absolute risk of early menarche (before age 12 years). While mendelian randomisation analysis is dependent on a number of assumptions, our findings support a causal effect of BMI on early menarche and suggests that increasing prevalence of childhood obesity will lead to similar trends in the prevalence of early menarche.

Low birth weight has been associated with reduced hand grip strength, which is a marker of future physical function and disease risk. The aim of this study was to apply a twin pair approach, using both ‘individual’ data and ‘within-pair’ differences, to investigate the influence of birth weight on hand grip strength and whether this association may be mediated through fat free mass (FFM). Participants from the East Flanders Prospective Twin Survey were included if born without congenital abnormalities, birth weight >500 g and ≥22 weeks of gestation. Follow up in adulthood (age: 18–34 year), included anthropometric measures and hand grip (n = 783 individuals, n = 326 same-sex twin pairs). Birth weight was positively associated with hand grip strength (β = 2.60 kg, 95% CI 1.52, 3.67, p<0.001) and FFM (β = 4.2, 95% CI 3.16, 5.24, p<0.001), adjusted for gestational age, sex and adult age. Using ‘within-pair’ analyses, the birth weight hand grip association was significant in DZ men only (β = 5.82, 95% CI 0.67, 10.97, p = 0.028), which was attenuated following adjustment for FFM. Within-pair birth weight FFM associations were most pronounced in DZ men (β = 11.20, 95% CI 7.18, 15.22, p<0.001). Our ‘individual’ analyses show that higher birth weight is associated with greater adult hand grip strength, which is mediated through greater adult FFM. The ‘within-pair’ analyses confirm this observation and furthermore show that, particularly in men, genetic factors may in part explain this association, as birth weight differences in DZ men result in greater differences in adult strength and FFM.

OBJECTIVE

The goal of this study was to investigate whether the effects of common genetic variants associated with fasting glucose in adults are detectable in healthy children.

RESEARCH DESIGN AND METHODS

Single nucleotide polymorphisms in MTNR1B (rs10830963), G6PC2 (rs560887), and GCK (rs4607517) were genotyped in 2,025 healthy European children aged 9–11 and 14–16 years. Associations with fasting glucose, insulin, homeostasis model assessment (HOMA)-insulin resistance (IR) and HOMA-B were investigated along with those observed for type 2 diabetes variants available in this study (CDKN2A/B, IGF2BP2, CDKAL1, SLC30A8, HHEX-IDE, and Chr 11p12).

RESULTS

Strongest associations were observed for G6PC2 and MTNR1B, with mean fasting glucose levels (95% CI) being 0.084 (0.06–0.11) mmol/l, P = 7.9 × 10−11 and 0.069 (0.04–0.09) mmol/l, P = 1.9 × 10−7 higher per risk allele copy, respectively. A similar but weaker trend was observed for GCK (0.028 [−0.006 to 0.06] mmol/l, P = 0.11). All three variants were associated with lower β-cell function (HOMA-B P = 9.38 × 10−5, 0.004, and 0.04, respectively). SLC30A8 (rs13266634) was the only type 2 diabetes variant associated with higher fasting glucose (0.033 mmol/l [0.01–0.06], P = 0.01). Calculating a genetic predisposition score adding the number of risk alleles of G6PC2, MTNR1B, GCK, and SLC30A8 showed that glucose levels were successively higher in children carrying a greater number of risk alleles (P = 7.1 × 10−17), with mean levels of 5.34 versus 4.91 mmol/l comparing children with seven alleles (0.6% of all children) to those with none (0.5%). No associations were found for fasting insulin or HOMA-IR with any of the variants.

CONCLUSIONS

The effects of common polymorphisms influencing fasting glucose are apparent in healthy children, whereas the presence of multiple risk alleles amounts to a difference of >1 SD of fasting glucose.

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.

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.

Please see later in the article for the Editors' Summary

Editors' Summary

Background

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

Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000284.

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)

Background

Common variants in PCSK1 have been reported to be associated with obesity in populations of European origin. We aimed to replicate this association in Chinese.

Methodology/Principal Findings

Two PCSK1 variants rs6234 and rs6235 (in strong LD with each other, r2 = 0.98) were genotyped in a population-based cohort of 3,210 Chinese Hans. The rs6234 was used for further association analyses with obesity and related traits. We found no significant association of rs6234 with obesity, overweight, BMI, waist circumference, or body fat percentage (P>0.05) in all participants. However, the rs6234 G-allele showed a significant association with increased risk of combined phenotype of obesity and overweight (OR 1.21[1.03–1.43], P = 0.0193) and a trend toward association with obesity (OR 1.25[0.98–1.61], P = 0.08) in men, but not in women (P≥0.29). Consistently, the rs6234 G-allele showed significant association with increased BMI (P = 0.0043), waist circumference (P = 0.008) and body fat percentage (P = 0.0131) only in men, not in women (P≥0.24). Interestingly, the rs6234 G-allele was significantly associated with increased HOMA-B (P = 0.0059) and decreased HOMA-S (P = 0.0349) in all participants.

Conclusion/Significance

In this study, we found modest evidence for association of the PCSK1 rs6234 with BMI and overweight in men only but not in women, which suggested that PCSK1 rs6234 might not be an important contributor to obesity in Chinese Hans. However, further studies with larger sample sizes are needed to draw a firm conclusion.

OBJECTIVE

To investigate whether variation in the melatonin receptor 1B gene (MTNR1B), recently identified as a common genetic determinant of fasting glucose levels in healthy, diabetes free individuals is associated with measures of beta-cell function and whole-body insulin sensitivity.

RESEARCH DESIGN AND METHODS

A total of 1,276 healthy individuals of European ancestry were studied at 19 centres of the RISC study. Whole-body insulin sensitivity (M/I) was assessed by hyperinsulinaemic-euglycemic clamp and indices of beta-cell function were derived from a 75-g oral glucose tolerance test (including 30-min insulin response and glucose sensitivity). We studied rs10830963 in MTNR1B using additive genetic models, adjusting for age, sex, and recruitment centre.

RESULTS

The minor (G) allele of rs10830963 in MTNR1B (frequency 0.30 in HapMap CEU; 0.29 in RISC participants) was associated with higher levels of fasting plasma glucose (standardized beta (95% CI) 0.17 (0.085; 0.25) per G allele; p=5.8×10e-5), consistent with recent observations. In addition, the G-allele was significantly associated with lower early insulin response (−0.19 (−0.28; −0.10); p=1.7×10e-5), as well as with decreased beta-cell glucose sensitivity (−0.11 (−0.20; −0.027); p=0.010). No associations were observed with clamp assessed insulin sensitivity (p=0.15) or different measures of body size (all p-values >0.7).

CONCLUSIONS

Genetic variation in MTNR1B is associated with defective early insulin response and decreased beta-cell glucose sensitivity, which may contribute to the higher glucose levels of non-diabetic individuals carrying the minor G allele of rs10830963 in MTNR1B.

To identify novel genetic loci associated with fasting glucose concentrations, we examined the leading association signals in 10 genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding the melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G-allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95%CI 0.06–0.08) mmol/L in fasting glucose levels (P=3.2×10−50) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P=1.1×10−15). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05–1.12), per G allele P=3.3×10−7) in a meta-analysis of thirteen case-control studies totalling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P=1.1×10−57) and GCK (rs4607517, P=1.0×10−25) loci.

The adipocyte-derived protein adiponectin is highly heritable and inversely associated with risk of type 2 diabetes mellitus (T2D) and coronary heart disease (CHD). We meta-analyzed 3 genome-wide association studies for circulating adiponectin levels (n = 8,531) and sought validation of the lead single nucleotide polymorphisms (SNPs) in 5 additional cohorts (n = 6,202). Five SNPs were genome-wide significant in their relationship with adiponectin (P≤5×10−8). We then tested whether these 5 SNPs were associated with risk of T2D and CHD using a Bonferroni-corrected threshold of P≤0.011 to declare statistical significance for these disease associations. SNPs at the adiponectin-encoding ADIPOQ locus demonstrated the strongest associations with adiponectin levels (P-combined = 9.2×10−19 for lead SNP, rs266717, n = 14,733). A novel variant in the ARL15 (ADP-ribosylation factor-like 15) gene was associated with lower circulating levels of adiponectin (rs4311394-G, P-combined = 2.9×10−8, n = 14,733). This same risk allele at ARL15 was also associated with a higher risk of CHD (odds ratio [OR] = 1.12, P = 8.5×10−6, n = 22,421) more nominally, an increased risk of T2D (OR = 1.11, P = 3.2×10−3, n = 10,128), and several metabolic traits. Expression studies in humans indicated that ARL15 is well-expressed in skeletal muscle. These findings identify a novel protein, ARL15, which influences circulating adiponectin levels and may impact upon CHD risk.

Author Summary

Through a meta-analysis of genome-wide association studies of 14,733 individuals, we identified common base-pair variants in the genome which influence circulating adiponectin levels. Since adiponectin is an adipocyte-derived circulating protein which has been inversely associated with risk of obesity-related diseases such as type 2 diabetes (T2D) and coronary heart disease (CHD), we next sought to understand if the identified variants influencing adiponectin levels also influence risk of T2D, CHD, and several metabolic traits. In addition to confirming that variation at the ADIPOQ locus influences adiponectin levels, our analyses point to a variant in the ARL15 (ADP-ribosylation factor-like 15) locus which decreases adiponectin levels and increases risk of CHD and T2D. Further, this same variant was associated with increased fasting insulin levels and glycated hemoglobin. While the function of ARL15 is not known, we provide insight into the tissue specificity of ARL15 expression. These results thus provide novel insights into the physiology of the adiponectin pathway and obesity-related diseases.

The timing of associations between common genetic variants for weight or body mass index (BMI) across the life course may provide insights into the aetiology of obesity. We genotyped variants in FTO (rs9939609) and near MC4R (rs17782313) in 1240 men and 1239 women born in 1946 and participating in the MRC 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 years. Hierarchical mixed models were used to test whether genetic associations with weight or BMI standard deviation scores (SDS) changed with age during childhood and adolescence (2–20 years) or adulthood (20–53 years). The association between FTO rs9939609 and BMI SDS strengthened during childhood and adolescence (rate of change: 0.007 SDS/A-allele/year; 95% CI: 0.003–0.010, P < 0.001), reached a peak strength at age 20 years (0.13 SDS/A-allele, 0.08–0.19), and then weakened during adulthood (−0.003 SDS/A-allele/year, −0.005 to −0.001, P = 0.001). MC4R rs17782313 showed stronger associations with weight than BMI; its association with weight strengthened during childhood and adolescence (0.005 SDS/C-allele/year; 0.001–0.008, P = 0.006), peaked at age 20 years (0.13 SDS/C-allele, 0.07–0.18), and weakened during adulthood (−0.002 SDS/C-allele/year, −0.004 to 0.000, P = 0.05). In conclusion, genetic variants in FTO and MC4R showed similar biphasic changes in their associations with BMI and weight, respectively, strengthening during childhood up to age 20 years and then weakening with increasing adult age. Studies of the aetiology of obesity spanning different age groups may identify age-specific determinants of weight gain.

The INSIG2 rs7566605 polymorphism was identified for obesity (BMI≥30 kg/m2) in one of the first genome-wide association studies, but replications were inconsistent. We collected statistics from 34 studies (n = 74,345), including general population (GP) studies, population-based studies with subjects selected for conditions related to a better health status (‘healthy population’, HP), and obesity studies (OB). We tested five hypotheses to explore potential sources of heterogeneity. The meta-analysis of 27 studies on Caucasian adults (n = 66,213) combining the different study designs did not support overall association of the CC-genotype with obesity, yielding an odds ratio (OR) of 1.05 (p-value = 0.27). The I2 measure of 41% (p-value = 0.015) indicated between-study heterogeneity. Restricting to GP studies resulted in a declined I2 measure of 11% (p-value = 0.33) and an OR of 1.10 (p-value = 0.015). Regarding the five hypotheses, our data showed (a) some difference between GP and HP studies (p-value = 0.012) and (b) an association in extreme comparisons (BMI≥32.5, 35.0, 37.5, 40.0 kg/m2 versus BMI<25 kg/m2) yielding ORs of 1.16, 1.18, 1.22, or 1.27 (p-values 0.001 to 0.003), which was also underscored by significantly increased CC-genotype frequencies across BMI categories (10.4% to 12.5%, p-value for trend = 0.0002). We did not find evidence for differential ORs (c) among studies with higher than average obesity prevalence compared to lower, (d) among studies with BMI assessment after the year 2000 compared to those before, or (e) among studies from older populations compared to younger. Analysis of non-Caucasian adults (n = 4889) or children (n = 3243) yielded ORs of 1.01 (p-value = 0.94) or 1.15 (p-value = 0.22), respectively. There was no evidence for overall association of the rs7566605 polymorphism with obesity. Our data suggested an association with extreme degrees of obesity, and consequently heterogeneous effects from different study designs may mask an underlying association when unaccounted for. The importance of study design might be under-recognized in gene discovery and association replication so far.

Author Summary

A polymorphism of the INSIG2 gene was identified as being associated with obesity in one of the first genome-wide association studies. However, this association has since then been highly debated upon inconsistent subsequent reports. We collected association information from 34 studies including a total of 74,000 participants. In a meta-analysis of the 27 studies including 66,000 Caucasian adults, we found no overall association of this polymorphism rs7566605 with obesity, comparing subjects with a body-mass-index (BMI)≥30 kg/m2 with normal BMI subjects (BMI<30 kg/m2). Our data suggested an association of this polymorphism with extreme obesity (e.g., BMI≥37.5 kg/m2) compared to normal controls. Such an association with extreme obesity might induce heterogeneous effects from different study designs depending on the proportion of extreme obesity included by the design. However, further studies would be required to substantiate this finding. The importance of study design might be under-recognized in gene discovery and association replication so far.

The protein encoded by the PPARGC1A gene is expressed at high levels in metabolically active tissues and is involved in the control of oxidative stress via reactive oxygen species detoxification. Several recent reports suggest that the PPARGC1A Gly482Ser (rs8192678) missense polymorphism may relate inversely with blood pressure. We used conventional meta-analysis methods to assess the association between Gly482Ser and systolic (SBP) or diastolic blood pressures (DBP) or hypertension in 13,949 individuals from 17 studies, of which 6,042 were previously unpublished observations. The studies comprised cohorts of white European, Asian, and American Indian adults, and adolescents from South America. Stratified analyses were conducted to control for population stratification. Pooled genotype frequencies were 0.47 (Gly482Gly), 0.42 (Gly482Ser), and 0.11 (Ser482Ser). We found no evidence of association between Gly482Ser and SBP [Gly482Gly: mean = 131.0 mmHg, 95% confidence interval (CI) = 130.5–131.5 mmHg; Gly482Ser mean = 133.1 mmHg, 95% CI = 132.6–133.6 mmHg; Ser482Ser: mean = 133.5 mmHg, 95% CI = 132.5–134.5 mmHg; P = 0.409] or DBP (Gly482Gly: mean = 80.3 mmHg, 95% CI = 80.0–80.6 mmHg; Gly482Ser mean = 81.5 mmHg, 95% CI = 81.2–81.8 mmHg; Ser482Ser: mean = 82.1 mmHg, 95% CI = 81.5–82.7 mmHg; P = 0.651). Contrary to previous reports, we did not observe significant effect modification by sex (SBP, P = 0.966; DBP, P = 0.715). We were also unable to confirm the previously reported association between the Ser482 allele and hypertension [odds ratio: 0.97, 95% CI = 0.87–1.08, P = 0.585]. These results were materially unchanged when analyses were focused on whites only. However, statistical evidence of gene-age interaction was apparent for DBP [Gly482Gly: 73.5 (72.8, 74.2), Gly482Ser: 77.0 (76.2, 77.8), Ser482Ser: 79.1 (77.4, 80.9), P = 4.20 × 10−12] and SBP [Gly482Gly: 121.4 (120.4, 122.5), Gly482Ser: 125.9 (124.6, 127.1), Ser482Ser: 129.2 (126.5, 131.9), P = 7.20 × 10−12] in individuals <50 yr (n = 2,511); these genetic effects were absent in those older than 50 yr (n = 5,088) (SBP, P = 0.41; DBP, P = 0.51). Our findings suggest that the PPARGC1A Ser482 allele may be associated with higher blood pressure, but this is only apparent in younger adults.

OBJECTIVE— Genome-wide association studies have identified common variants in CDKAL1, CDKN2A/B, IGF2BP2, SLC30A8, HHEX/IDE, EXT2, and LOC387761 loci that significantly increase the risk of type 2 diabetes. We aimed to replicate these observations in a population-based cohort of Chinese Hans and examine the associations of these variants with type 2 diabetes and diabetes-related phenotypes.

RESEARCH DESIGN AND METHODS— We genotyped 17 single nucleotide polymorhisms (SNPs) in 3,210 unrelated Chinese Hans, including 424 participants with type 2 diabetes, 878 with impaired fasting glucose (IFG), and 1,908 with normal fasting glucose.

RESULTS— We confirmed the associations between type 2 diabetes and variants near CDKAL1 (odds ratio 1.49 [95% CI 1.27–1.75]; P = 8.91 × 10−7) and CDKN2A/B (1.31 [1.12–1.54]; P = 1.0 × 10−3). We observed significant association of SNPs in IGF2BP2 (1.17 [1.03–1.32]; P = 0.014) and SLC30A8 (1.12 [1.01–1.25]; P = 0.033) with combined IFG/type 2 diabetes. The SNPs in CDKAL1, IGF2BP2, and SLC30A8 were also associated with impaired β-cell function estimated by homeostasis model assessment of β-cell function. When combined, each additional risk allele from CDKAL1-rs9465871, CDKN2A/B-rs10811661, IGF2BP2-rs4402960, and SLC30A8-rs13266634 increased the risk for type 2 diabetes by 1.24-fold (P = 2.85 × 10−7) or for combined IFG/type 2 diabetes by 1.21-fold (P = 6.31 × 10−11). None of the SNPs in EXT2 or LOC387761 exhibited significant association with type 2 diabetes or IFG. Significant association was observed between the HHEX/IDE SNPs and type 2 diabetes in individuals from Shanghai only (P < 0.013) but not in those from Beijing (P > 0.33).

CONCLUSIONS— Our results indicate that in Chinese Hans, common variants in CDKAL1, CDKN2A/B, IGF2BP2, and SLC30A8 loci independently or additively contribute to type 2 diabetes risk, likely mediated through β-cell dysfunction.

OBJECTIVE— Loss of lipin 1 activity causes lipodystrophy and insulin resistance in the fld mouse, and LPIN1 expression and common genetic variation were recently suggested to influence adiposity and insulin sensitivity in humans. We aimed to conduct a comprehensive association study to clarify the influence of common LPIN1 variation on adiposity and insulin sensitivity in U.K. populations and to examine the role of LPIN1 mutations in insulin resistance syndromes.

RESEARCH DESIGN AND METHOD— Twenty-two single nucleotide polymorphisms tagging common LPIN1 variation were genotyped in Medical Research Council (MRC) Ely (n = 1,709) and Hertfordshire (n = 2,901) population-based cohorts. LPIN1 exons, exon/intron boundaries, and 3′ untranslated region were sequenced in 158 patients with idiopathic severe insulin resistance (including 23 lipodystrophic patients) and 48 control subjects.

RESULTS— We found no association between LPIN1 single nucleotide polymorphisms and fasting insulin but report a nominal association between rs13412852 and BMI (P = 0.042) in a meta-analysis of 8,504 samples from in-house and publicly available studies. Three rare nonsynonymous variants (A353T, R552K, and G582R) were detected in severely insulin-resistant patients. However, these did not cosegregate with disease in affected families, and Lipin1 protein expression and phosphorylation in patients with variants were indistinguishable from those in control subjects.

CONCLUSIONS— Our data do not support a major effect of common LPIN1 variation on metabolic traits and suggest that mutations in LPIN1 are not a common cause of lipodystrophy in humans. The nominal associations with BMI and other metabolic traits in U.K. cohorts require replication in larger cohorts.

Herbert et al. (Reports, 14 April 2006, p. 279) found that the rs7566605 genetic variant, located upstream of the INSIG2 gene, was consistently associated with increased body mass index. However, we found no evidence of association between rs7566605 and body mass index in two large ethnically homogeneous population-based cohorts. On the contrary, an opposite tendency was observed.