Is There an Association Between Sweetened Beverages and Adiposity?

Four mechanisms were reviewed to explain the possible association between sweetened beverages and increased overweight or obesity: excess caloric intake, glycemic index and glycemic load, lack of effect of liquid calories on satiety, and displacement of milk. The findings were inconsistent across studies. The strongest support was for the excess caloric intake hypothesis, but the findings were not conclusive. Assigning possible links between sweetened beverage consumption and adiposity requires research that compares and contrasts specific mechanisms, especially in populations at risk for obesity, while controlling for likely confounding variables.

Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.

Understanding how FI and FG levels are regulated is important because their derangement is a feature of T2D. Despite recent success from GWAS in identifying regions of the genome influencing glycemic traits, collectively these loci explain only a small proportion of trait variance. Unlocking the biological mechanisms driving these associations has been challenging because the vast majority of variants map to non-coding sequence, and the genes through which they exert their impact are largely unknown. In the current study, we sought to increase our understanding of the physiological pathways influencing both traits using exome-array genotyping in up to 33,231 non-diabetic individuals to identify coding variants and consequently genes associated with either FG or FI levels. We identified novel association signals for both traits including the receptor for GLP-1 agonists which are a widely used therapy for T2D. Furthermore, we identified coding variants at several GWAS loci which point to the genes underlying these association signals. Importantly, we found that multiple coding variants in G6PC2 result in a loss of protein function and lower fasting glucose levels.

The effect of protein and glycemic index on children's body composition: the DiOGenes randomized study

OBJECTIVE

To investigate the effect of protein and glycemic index (GI) on body composition among European children in the randomized, 6-month dietary intervention DiOGenes (diet, obesity, and genes) family-based study.

PATIENTS AND METHODS

In the study, 827 children (381 boys and 446 girls), aged 5 to 18 years, completed baseline examinations. Families with parents who lost ≥ 8% of their weight during an 8-week run-in low-calorie diet period were randomly assigned to 1 of 5 ad libitum diets: low protein (LP)/low glycemic index (LGI); LP/high GI (HGI); high protein (HP)/LGI; HP/HGI; and control diet. The target difference was 15 GI U between the LGI/HGI groups and 13 protein percentage points between the LP/HP groups. There were 658 children examined after 4 weeks. Advice on food-choice modification was provided at 6 visits during this period. No advice on weight loss was provided because the focus of the study was the ability of the diets to affect outcomes through appetite regulation. Anthropometric measurements and body composition were assessed at baseline, week 4, and week 26.

RESULTS

In the study, 465 children (58.1%) completed all assessments. The achieved differences between the GI and protein groups were 2.3 GI U and 4.9 protein percentage points, respectively. The LP/HGI group increased body fat percentage significantly more than the other groups (P = .040; partial η(2) = 0.039), and the percentage of overweight/obese children in the HP/LGI group decreased significantly during the intervention (P = .031).

CONCLUSIONS

Neither GI nor protein had an isolated effect on body composition. However, the LP/HGI combination increased body fat, whereas the HP/LGI combination was protective against obesity in this sample of children.

Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

Human genetic studies have demonstrated that quantitative human anthropometric and metabolic traits, including body mass index, waist-hip ratio, and plasma concentrations of glucose and insulin, are highly heritable, and are established risk factors for type 2 diabetes and cardiovascular diseases. Although many regions of the genome have been associated with these traits, the specific genes responsible have not yet been identified. By making use of advanced statistical “imputation” techniques applied to more than 87,000 individuals of European ancestry, and publicly available “reference panels” of more than 37 million genetic variants, we have been able to identify novel regions of the genome associated with these glycaemic and obesity-related traits and localise genes within these regions that are most likely to be causal. This improved understanding of the biological mechanisms underlying glycaemic and obesity-related traits is extremely important because it may advance drug development for downstream disease endpoints, ultimately leading to public health benefits.

The genetics underlying metabolic signatures in a brown rice diversity panel and their vital role in human nutrition

Brown rice (Oryza sativa) possesses various nutritionally dense bioactive phytochemicals exhibiting a wide range of antioxidant, anti-cancer, and anti-diabetic properties known to promote various human health benefits. However, despite the wide claims made about the importance of brown rice for human nutrition the underlying metabolic diversity has not been systematically explored. Non-targeted metabolite profiling of developing and mature seeds of a diverse genetic panel of 320 rice cultivars allowed quantification of 117 metabolites. The metabolite genome-wide association study (mGWAS) detected genetic variants influencing diverse metabolic targets in developing and mature seeds. We further interlinked genetic variants on chromosome 7 (6.06-6.43 Mb region) with complex epistatic genetic interactions impacting multi-dimensional nutritional targets, including complex carbohydrate starch quality, the glycemic index, antioxidant catechin, and rice grain color. Through this nutrigenomics approach rare gene bank accessions possessing genetic variants in bHLH and IPT5 genes were identified through haplotype enrichment. These variants were associated with a low glycemic index, higher catechin levels, elevated total flavonoid contents, and heightened antioxidant activity in the whole grain with elevated anti-cancer properties being confirmed in cancer cell lines. This multi-disciplinary nutrigenomics approach thus allowed us to discover the genetic basis of human health-conferring diversity in the metabolome of brown rice.

Evidence for a major gene affecting the transition from normoglycaemia to hyperglycaemia in Psammomys obesus

We investigated the mode of inheritance of nutritionally induced diabetes in the desert gerbil Psammomys obesus (sand rat), following transfer from low-energy (LE) to high-energy (HE) diet which induces hyperglycaemia. Psammomys selected for high or low blood glucose level were used as two parental lines. A first backcross generation (BC(1)) was formed by crossing F(1) males with females of the diabetes-prone line. The resulting 232 BC(1) progeny were assessed for blood glucose. All progeny were weaned at 3 weeks of age (week 0), and their weekly assessment of blood glucose levels proceeded until week 9 after weaning, with all progeny maintained on HE diet. At weeks 1 to 9 post weaning, a clear bimodal distribution statistically different from unimodal distribution of blood glucose was observed, normoglycaemic and hyperglycaemic at a 1:1 ratio. This ratio is expected at the first backcross generation for traits controlled by a single dominant gene. From week 0 (prior to the transfer to HE diet) till week 8, the hyperglycaemic individuals were significantly heavier (4--17%) than the normoglycaemic ones. The bimodal blood glucose distribution in BC(1) generation, with about equal frequencies in each mode, strongly suggests that a single major gene affects the transition from normo- to hyperglycaemia. The wide range of blood glucose values among the hyperglycaemic individuals (180 to 500 mg/dl) indicates that several genes and environmental factors influence the extent of hyperglycaemia. The diabetes-resistant allele appears to be dominant; the estimate for dominance ratio is 0.97.