Estimation of newborn risk for child or adolescent obesity:lessons from longitudinal birth cohorts

OBJECTIVES: Prevention of obesity should start as early as possible after birth. We aimed to build clinically useful equations estimating the risk of later obesity in newborns, as a first step towards focused early prevention against the global obesity epidemic. METHODS: We analyzed the lifetime Northern Finland Birth Cohort 1986 (NFBC1986) (N = 4,032) to draw predictive equations for childhood and adolescent obesity from traditional risk factors (parental BMI, birth weight, maternal gestational weight gain, behaviour and social indicators), and a genetic score built from 39 BMI/obesity-associated polymorphisms. We performed validation analyses in a retrospective cohort of 1,503 Italian children and in a prospective cohort of 1,032 U.S. children. RESULTS: In the NFBC1986, the cumulative accuracy of traditional risk factors predicting childhood obesity, adolescent obesity, and childhood obesity persistent into adolescence was good: AUROC = 0·78[0·74-0.82], 0·75[0·71-0·79] and 0·85[0·80-0·90] respectively (all p\u3c0·001). Adding the genetic score produced discrimination improvements ≤1%. The NFBC1986 equation for childhood obesity remained acceptably accurate when applied to the Italian and the U.S. cohort (AUROC = 0·70[0·63-0·77] and 0·73[0·67-0·80] respectively) and the two additional equations for childhood obesity newly drawn from the Italian and the U.S. datasets showed good accuracy in respective cohorts (AUROC = 0·74[0·69-0·79] and 0·79[0·73-0·84]) (all p\u3c0·001). The three equations for childhood obesity were converted into simple Excel risk calculators for potential clinical use. CONCLUSION: This study provides the first example of handy tools for predicting childhood obesity in newborns by means of easily recorded information, while it shows that currently known genetic variants have very little usefulness for such prediction

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.Peer reviewe

An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans.

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10(-8)), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.Please refer to the manuscript or visit the publisher's website for funding infomation

Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes

To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip involving 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two demonstrating sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of further common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signalling and cell cycle regulation, in diabetes pathogenesis

New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P <5 x 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.Peer reviewe

Type 2 diabetes-related genetic risk scores associated with variations in fasting plasma glucose and development of impaired glucose homeostasis in the prospective DESIR study

Aims/hypothesis: Genome-wide association studies have firmly established 65 independent European-derived loci associated with type 2 diabetes and 36 loci contributing to variations in fasting plasma glucose (FPG). Using individual data from the Data from an Epidemiological Study on the Insulin Resistance Syndrome (DESIR) prospective study, we evaluated the contribution of three genetic risk scores (GRS) to variations in metabolic traits, and to the incidence and prevalence of impaired fasting glycaemia (IFG) and type 2 diabetes. Methods: Three GRS (GRS-1, 65 type 2 diabetes-associated single nucleotide polymorphisms [SNPs]; GRS-2, GRS-1 combined with 24 FPG-raising SNPs; and GRS-3, FPG-raising SNPs alone) were analysed in 4,075 DESIR study participants. GRS-mediated effects on longitudinal variations in quantitative traits were assessed in 3,927 nondiabetic individuals using multivariate linear mixed models, and on the incidence and prevalence of hyperglycaemia at 9 years using Cox and logistic regression models. The contribution of each GRS to risk prediction was evaluated using the C-statistic and net reclassification improvement (NRI) analysis. Results: The two most inclusive GRS were significantly associated with increased FPG (β=0.0011 mmol/l per year per risk allele, p =8.2×10 and p =6.0×10), increased incidence of IFG and type 2 diabetes (per allele: HR 1.03, p=4.3×10 and HR 1.04, p=1.0×10), and the 9 year prevalence (OR 1.13 [95% CI 1.10, 1.17], p=1.9×10 for type 2 diabetes only; OR 1.07 [95% CI 1.05, 1.08], p=7.8×10, for IFG and type 2 diabetes). No significant interaction was found between GRS-1 or GRS-2 and potential confounding factors. Each GRS yielded a modest, but significant, improvement in overall reclassification rates (NRI 17.3%, p=6.6×10 ; NRI 17.6%, p=4.2×10; NRI 13.1%, p=1.7×10). Conclusions/ interpretation: Polygenic scores based on combined genetic information from type 2 diabetes risk and FPG variation contribute to discriminating middle-aged individuals at risk of developing type 2 diabetes in a general population

Associations between type 2 diabetes-related genetic scores and metabolic traits, in obese and normal-weight youths

Context: Young-onset obesity is strongly associated with the early development of type 2 diabetes (T2D). Genetic risk scores (GRSs) related to T2D might help predicting the early impairment of glucose homeostasis in obese youths. Objective: Our objective was to investigate the contributions of four GRSs (associated with: T2D [GRS-T2D], beta-cell function [GRS-β], insulin resistance [GRS-IR], and body mass index) to the variation of traits derived from oral glucose tolerance test (OGTT) in obese and normal-weight children and young adults. Design: This was a cross-sectional association study. Patients: A total of 1076 obese children/adolescents (age = 11.4 ± 2.8 years) and 1265 normalweight young volunteers (age = 21.1 ± 4.4 years) of European ancestry were recruited from pediatric obesity clinics and general population, respectively. Intervention: Standard OGTT was the intervention in this study. Main Outcome Measures: Associations between GRSs and OGTT-derived traits including fasting glucose and insulin, insulinogenic index, insulin sensitivity index, disposition index (DI) and associations between GRSs and pre-diabetic conditions were measured. Results: GRS-β significantly associated with fasting glucose (β = 0.019; P = 3.5 × 10) and DI (β =-0.031; P = 8.9 × 10-4, last quartile 18%lower than first) in obese children, and nominally associated with fasting glucose (β = 0.009; P = 0.017) and DI (β =-0.030; P = 1.1 × 10-3, last quartile 11%lower than first) in normal-weight youths. GRS-T2D showed weaker contribution to fasting glucose and DI compared to GRS-β, in both obese and normal-weight youths. GRS associated with insulin resistance and GRS associated with body mass index did not associate with any traits. None of the GRSs associated with prediabetes, which affected only 4%of participants overall. Conclusion: Single nucleotide polymorphisms identified by genome-wide association studies to influence beta-cell function were associated with fasting glucose and indices of insulin secretion in youths, especially in obese children. (J Clin Endocrinol Metab 101: 4244-4250, 2016)

Endocannabinoid receptor 1 gene variations increase risk for obesity and modulate body mass index in European populations.

The therapeutic effects of cannabinoid receptor blockade on obesity-associated phenotypes underline the importance of the endocannabinoid pathway on the energy balance. Using a staged-approach, we examined the contribution of the endocannabinoid receptor 1 gene (CNR1) on obesity and body mass index (BMI) in the European population. With the input of CNR1 exons and 3' and 5' regions sequencing and HapMap database, we selected and genotyped 26 tagging single-nucleotide polymorphisms (SNPs) in 1932 obese cases and 1173 non-obese controls of French European origin. Variants that showed significant associations (P 0.5) with these two SNPs in the initial case-control study, identified two better associated SNPs (rs6454674 and rs10485170). Our study of 5750 subjects shows that CNR1 variations increase the risk for obesity and modulate BMI in our European population. As CB1 is a drug target for obesity, a pharmacogenetic analysis of the endocannabinoid blockade obesity treatment may be of interest to identify best responders

Common variants near BDNF and SH2B1 show nominal evidence of association with snacking behavior in European populations

We investigated the effect of 24 obesity-predisposing single nucleotide polymorphisms (SNPs), separately and in combination, on snacking behavior in three European populations. The 24 SNPs were genotyped in 7,502 subjects (1,868 snackers and 5,634 non-snackers). We tested the hypothesis that obesity risk variants or a genetic risk score increases snacking using a logistic regression adjusted for sex, age, and body mass index. The obesity genetic risk score was not associated with snacking (odds ratio (OR) = 1.00 [0.98–1.02], P value = 0.48). The obesity risk variants of two SNPs (rs925946 and rs7498665) close to the BDNF and SH2B1 genes showed nominal evidence of association with increased snacking (OR = 1.09 [1.01–1.17], P value = 0.0348 and OR = 1.11 [1.04–1.19], P value = 0.00703, respectively) but did not survive Bonferroni corrections for multiple testing. The associations of rs925946 and rs7498665 obesity risk variants with increased BMI (β = 0.180 [0.022–0.339], P value = 0.0258 and β = 0.166 [0.019–0.313], P value = 0.0271, respectively) were slightly attenuated after adjusting for snacking (β = 0.151 [−0.006 to 0.309], P value = 0.0591 and β = 0.152 [0.006–0.297], P value = 0.0413). Our data suggest that genetic predisposition to obesity does not significantly contribute to snacking behavior. The nominal associations of rs925946 and rs7498665 obesity risk variants near the BDNF and SH2B1 genes with increased snacking deserve further investigation