Quality of dietary fat and genetic risk of type 2 diabetes: individual participant data meta-analysis.

OBJECTIVE: To investigate whether the genetic burden of type 2 diabetes modifies the association between the quality of dietary fat and the incidence of type 2 diabetes. DESIGN: Individual participant data meta-analysis. DATA SOURCES: Eligible prospective cohort studies were systematically sourced from studies published between January 1970 and February 2017 through electronic searches in major medical databases (Medline, Embase, and Scopus) and discussion with investigators. REVIEW METHODS: Data from cohort studies or multicohort consortia with available genome-wide genetic data and information about the quality of dietary fat and the incidence of type 2 diabetes in participants of European descent was sought. Prospective cohorts that had accrued five or more years of follow-up were included. The type 2 diabetes genetic risk profile was characterized by a 68-variant polygenic risk score weighted by published effect sizes. Diet was recorded by using validated cohort-specific dietary assessment tools. Outcome measures were summary adjusted hazard ratios of incident type 2 diabetes for polygenic risk score, isocaloric replacement of carbohydrate (refined starch and sugars) with types of fat, and the interaction of types of fat with polygenic risk score. RESULTS: Of 102 305 participants from 15 prospective cohort studies, 20 015 type 2 diabetes cases were documented after a median follow-up of 12 years (interquartile range 9.4-14.2). The hazard ratio of type 2 diabetes per increment of 10 risk alleles in the polygenic risk score was 1.64 (95% confidence interval 1.54 to 1.75, I2=7.1%, τ2=0.003). The increase of polyunsaturated fat and total omega 6 polyunsaturated fat intake in place of carbohydrate was associated with a lower risk of type 2 diabetes, with hazard ratios of 0.90 (0.82 to 0.98, I2=18.0%, τ2=0.006; per 5% of energy) and 0.99 (0.97 to 1.00, I2=58.8%, τ2=0.001; per increment of 1 g/d), respectively. Increasing monounsaturated fat in place of carbohydrate was associated with a higher risk of type 2 diabetes (hazard ratio 1.10, 95% confidence interval 1.01 to 1.19, I2=25.9%, τ2=0.006; per 5% of energy). Evidence of small study effects was detected for the overall association of polyunsaturated fat with the risk of type 2 diabetes, but not for the omega 6 polyunsaturated fat and monounsaturated fat associations. Significant interactions between dietary fat and polygenic risk score on the risk of type 2 diabetes (P>0.05 for interaction) were not observed. CONCLUSIONS: These data indicate that genetic burden and the quality of dietary fat are each associated with the incidence of type 2 diabetes. The findings do not support tailoring recommendations on the quality of dietary fat to individual type 2 diabetes genetic risk profiles for the primary prevention of type 2 diabetes, and suggest that dietary fat is associated with the risk of type 2 diabetes across the spectrum of type 2 diabetes genetic risk.

Identification of Novel Genetic Determinants of Erythrocyte Membrane Fatty Acid Composition among Greenlanders.

Fatty acids (FAs) are involved in cellular processes important for normal body function, and perturbation of FA balance has been linked to metabolic disturbances, including type 2 diabetes. An individual's level of FAs is affected by diet, lifestyle, and genetic variation. We aimed to improve the understanding of the mechanisms and pathways involved in regulation of FA tissue levels, by identifying genetic loci associated with inter-individual differences in erythrocyte membrane FA levels. We assessed the levels of 22 FAs in the phospholipid fraction of erythrocyte membranes from 2,626 Greenlanders in relation to single nucleotide polymorphisms genotyped on the MetaboChip or imputed. We identified six independent association signals. Novel loci were identified on chromosomes 5 and 11 showing strongest association with oleic acid (rs76430747 in ACSL6, beta (SE): -0.386% (0.034), p = 1.8x10-28) and docosahexaenoic acid (rs6035106 in DTD1, 0.137% (0.025), p = 6.4x10-8), respectively. For a missense variant (rs80356779) in CPT1A, we identified a number of novel FA associations, the strongest with 11-eicosenoic acid (0.473% (0.035), p = 2.6x10-38), and for variants in FADS2 (rs174570), LPCAT3 (rs2110073), and CERS4 (rs11881630) we replicated known FA associations. Moreover, we observed metabolic implications of the ACSL6 (rs76430747) and CPT1A (rs80356779) variants, which both were associated with altered HbA1c (0.051% (0.013), p = 5.6x10-6 and -0.034% (0.016), p = 3.1x10-4, respectively). The latter variant was also associated with reduced insulin resistance (HOMA-IR, -0.193 (0.050), p = 3.8x10-6), as well as measures of smaller body size, including weight (-2.676 kg (0.523), p = 2.4x10-7), lean mass (-1.200 kg (0.271), p = 1.7x10-6), height (-0.966 cm (0.230), p = 2.0x10-5), and BMI (-0.638 kg/m2 (0.181), p = 2.8x10-4). In conclusion, we have identified novel genetic determinants of FA composition in phospholipids in erythrocyte membranes, and have shown examples of links between genetic variants associated with altered FA membrane levels and changes in metabolic traits.

Recent Progress in the Understanding of Obesity: Contributions of Genome-Wide Association Studies.

Since 2007, discovery of genetic variants associated with general obesity and fat distribution has advanced tremendously through genome-wide association studies (GWAS). Currently, the number of robustly associated loci is 190. Even though these loci explain <3 % of the variance, they have provided us a still emerging picture of genomic localization, frequency and effect size spectra, and hints of functional implications. The translation into biological knowledge has turned out to be an immense task. However, in silico enrichment analyses of genes involved in specific pathways or expressed in specific tissues have the power to suggest biological mechanisms underlying obesity. Inspired by this, we highlight genes in five loci potentially mechanistically linked to leptin-receptor trafficking and signaling in primary cilia. The clinical application of genetic knowledge as prediction, prevention, or treatment strategies is unfortunately still far from reality. Thus, despite major advances, further research is warranted to solve one of the greatest health problems in modern society.

Discovery of coding genetic variants influencing diabetes-related serum biomarkers and their impact on risk of type 2 diabetes.

CONTEXT: Type 2 diabetes (T2D) prevalence is spiraling globally, and knowledge of its pathophysiological signatures is crucial for a better understanding and treatment of the disease. OBJECTIVE: We aimed to discover underlying coding genetic variants influencing fasting serum levels of nine biomarkers associated with T2D: adiponectin, C-reactive protein, ferritin, heat shock 70-kDa protein 1B, IGF binding protein 1 and IGF binding protein 2, IL-18, IL-2 receptor-α, and leptin. DESIGN AND PARTICIPANTS: A population-based sample of 6215 adult Danes was genotyped for 16 340 coding single-nucleotide polymorphisms and were tested for association with each biomarker. Identified loci were tested for association with T2D through a large-scale meta-analysis involving up to 17 024 T2D cases and up to 64 186 controls. RESULTS: We discovered 11 associations between single-nucleotide polymorphisms and five distinct biomarkers at a study-wide P < 3.4 × 10(-7). Nine associations were novel: IL18: BIRC6, RAD17, MARVELD2; ferritin: F5; IGF binding protein 1: SERPING1, KLKB, GCKR, CELSR2, and heat shock 70-kDa protein 1B: CFH. Three of the identified loci (CELSR2, HNF1A, and GCKR) were significantly associated with T2D, of which the association with the CELSR2 locus has not been shown previously. CONCLUSION: The identified loci influence processes related to insulin signaling, cell communication, immune function, apoptosis, DNA repair, and oxidative stress, all of which could provide a rationale for novel diabetes therapeutic strategies.

The PNPLA3 rs738409 G-allele associates with reduced fasting serum triglyceride and serum cholesterol in Danes with impaired glucose regulation.

BACKGROUND AND AIM: Non-alcoholic fatty liver disease (NAFLD) is a common condition, associated with hepatic insulin resistance and the metabolic syndrome including hyperglycaemia and dyslipidemia. We aimed at studying the potential impact of the NAFLD-associated PNPLA3 rs738409 G-allele on NAFLD-related metabolic traits in hyperglycaemic individuals. METHODS: The rs738409 variant was genotyped in the population-based Inter99 cohort examined by an oral glucose-tolerance test, and a combined study-sample consisting of 192 twins (96 twin pairs) and a sub-set of the Inter99 population (n = 63) examined by a hyperinsulinemic euglycemic clamp (n(total) = 255). In Inter99, we analyzed associations of rs738409 with components of the WHO-defined metabolic syndrome (n = 5,847) and traits related to metabolic disease (n = 5,663). In the combined study sample we elucidated whether the rs738409 G-allele altered hepatic or peripheral insulin sensitivity. Study populations were divided into individuals with normal glucose-tolerance (NGT) and with impaired glucose regulation (IGR). RESULTS: The case-control study showed no associations with components of the metabolic syndrome or the metabolic syndrome. Among 1,357 IGR individuals, the rs738409 G-allele associated with decreased fasting serum triglyceride levels (per allele effect(ß) = -9.9% [-14.4%;-4.0% (95% CI)], p = 5.1×10(-5)) and fasting total cholesterol (ß = -0.2 mmol/l [-0.3;-0.01 mmol/l(95% CI)], p = 1.5×10(-4)). Meta-analyses showed no impact on hepatic or peripheral insulin resistance in carriers of the rs738409 G-allele. CONCLUSION: Our findings suggest that the G-allele of PNPLA3 rs738409 associates with reduced fasting levels of cholesterol and triglyceride in individuals with IGR.

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

BACKGROUND: The FTO gene harbors the strongest known susceptibility locus for obesity. While many individual studies have suggested that physical activity (PA) may attenuate the effect of FTO on obesity risk, other studies have not been able to confirm this interaction. To confirm or refute unambiguously whether PA attenuates the association of FTO with obesity risk, we meta-analyzed data from 45 studies of adults (n = 218,166) and nine studies of children and adolescents (n = 19,268). METHODS AND FINDINGS: All studies identified to have data on the FTO rs9939609 variant (or any proxy [r(2)>0.8]) and PA were invited to participate, regardless of ethnicity or age of the participants. PA was standardized by categorizing it into a dichotomous variable (physically inactive versus active) in each study. Overall, 25% of adults and 13% of children were categorized as inactive. Interaction analyses were performed within each study by including the FTO×PA interaction term in an additive model, adjusting for age and sex. Subsequently, random effects meta-analysis was used to pool the interaction terms. In adults, the minor (A-) allele of rs9939609 increased the odds of obesity by 1.23-fold/allele (95% CI 1.20-1.26), but PA attenuated this effect (p(interaction)  = 0.001). More specifically, the minor allele of rs9939609 increased the odds of obesity less in the physically active group (odds ratio  = 1.22/allele, 95% CI 1.19-1.25) than in the inactive group (odds ratio  = 1.30/allele, 95% CI 1.24-1.36). No such interaction was found in children and adolescents. CONCLUSIONS: The association of the FTO risk allele with the odds of obesity is attenuated by 27% in physically active adults, highlighting the importance of PA in particular in those genetically predisposed to obesity.

Studies of metabolic phenotypic correlates of 15 obesity associated gene variants.

AIMS: Genome-wide association studies have identified novel BMI/obesity associated susceptibility loci. The purpose of this study is to determine associations with overweight, obesity, morbid obesity and/or general adiposity in a Danish population. Moreover, we want to investigate if these loci associate with type 2 diabetes and to elucidate potential underlying metabolic mechanisms. METHODS: 15 gene variants in 14 loci including TMEM18 (rs7561317), SH2B1 (rs7498665), KCTD15 (rs29941), NEGR1 (rs2568958), ETV5 (rs7647305), BDNF (rs4923461, rs925946), SEC16B (rs10913469), FAIM2 (rs7138803), GNPDA2 (rs10938397), MTCH2 (rs10838738), BAT2 (rs2260000), NPC1 (rs1805081), MAF (rs1424233), and PTER (rs10508503) were genotyped in 18,014 middle-aged Danes. RESULTS: Five of the 15 gene variants associated with overweight, obesity and/or morbid obesity. Per allele ORs ranged from 1.15-1.20 for overweight, 1.10-1.25 for obesity, and 1.41-1.46 for morbid obesity. Five of the 15 variants moreover associated with increased measures of adiposity. BDNF rs4923461 displayed a borderline BMI-dependent protective effect on type 2 diabetes (0.87 (0.78-0.96, p = 0.008)), whereas SH2B1 rs7498665 associated with nominally BMI-independent increased risk of type 2 diabetes (1.16 (1.07-1.27, p = 7.8×10(-4))). CONCLUSIONS: Associations with overweight and/or obesity and measures of obesity were confirmed for seven out of the 15 gene variants. The obesity risk allele of BDNF rs4923461 protected against type 2 diabetes, which could suggest neuronal and peripheral distinctive ways of actions for the protein. SH2B1 rs7498665 associated with type 2 diabetes independently of BMI.

Studies of association between LPIN1 variants and common metabolic phenotypes among 17,538 Danes.

OBJECTIVE: Lipin-1, encoded by LPIN1, is expressed in the major metabolically active tissues. Decreased expression of lipin-1 in adipose tissue correlates with increased insulin resistance, and tagging of the LPIN1 locus has shown that rs33997857, rs6744682, and rs6708316 associate with metabolic phenotypes, specifically body mass index (BMI) and fasting serum lipid levels, both on the individual single-nucleotide polymorphism level and with a three-marker haplotype. Our aim was to validate the reported findings in the Danish population. DESIGN: In the present study, variants were analyzed in LPIN1 using case-control studies, haplotype analyses, and quantitative trait analyses in a population of 17,538 Danes. METHODS: The three LPIN1 variants were genotyped in 17,538 Danes from four study populations of middle-aged people. This provided us with a statistical power >99% to replicate previous findings. Variants were analyzed individually and in haplotype combinations in studies of quantitative metabolic traits and in case-control studies. RESULTS: None of the three variants were associated with the examined quantitative traits including BMI, waist circumference, blood pressure, fasting serum lipid concentrations, or plasma glucose or serum insulin concentrations in the fasting state and following an oral glucose tolerance test. Haplotypes were tested for association with quantitative traits; however, only nominal association with blood pressure (P=0.04) and waist circumference (P=0.04) was observed. In case-control studies, no association was found for individual variants or the three-marker haplotype. CONCLUSION: LPIN1 rs33997857, rs6744682, and rs6708316 did not associate with type 2 diabetes, obesity, or related quantitative metabolic phenotypes in the Danish population examined.

Combined analyses of 20 common obesity susceptibility variants.

OBJECTIVE: Genome-wide association studies and linkage studies have identified 20 validated genetic variants associated with obesity and/or related phenotypes. The variants are common, and they individually exhibit small-to-modest effect sizes. RESEARCH DESIGN AND METHODS: In this study we investigate the combined effect of these variants and their ability to discriminate between normal weight and overweight/obese individuals. We applied receiver operating characteristics (ROC) curves, and estimated the area under the ROC curve (AUC) as a measure of the discriminatory ability. The analyses were performed cross-sectionally in the population-based Inter99 cohort where 1,725 normal weight, 1,519 overweight, and 681 obese individuals were successfully genotyped for all 20 variants. RESULTS: When combining all variants, the 10% of the study participants who carried more than 22 risk-alleles showed a significant increase in probability of being both overweight with an odds ratio of 2.00 (1.47-2.72), P = 4.0 x 10(-5), and obese with an OR of 2.62 (1.76-3.92), P = 6.4 x 10(-7), compared with the 10% of the study participants who carried less than 14 risk-alleles. Discrimination ability for overweight and obesity, using the 20 single nucleotide polymorphisms (SNPs), was determined to AUCs of 0.53 and 0.58, respectively. When combining SNP data with conventional nongenetic risk factors of obesity, the discrimination ability increased to 0.64 for overweight and 0.69 for obesity. The latter is significantly higher (P < 0.001) than for the nongenetic factors alone (AUC = 0.67). CONCLUSIONS: The discriminative value of the 20 validated common obesity variants is at present time sparse and too weak for clinical utility, however, they add to increase the discrimination ability of conventional nongenetic risk factors.