Comparison of body mass index and waist circumference as predictors of cardiometabolic health in a population of young Canadian adults

<p>Abstract</p> <p>Background</p> <p>This study aimed to investigate whether waist circumference (WC) or body mass index (BMI) is a better predictor of blood lipid concentrations among young men and women from different ethnocultural groups.</p> <p>Methods</p> <p>Participants were 1181 healthy men (n = 358) and women (n = 823) aged 20-29 years taken from the cross-sectional Toronto Nutrigenomics and Health Study. Analyses were conducted separately for men and women, and for Caucasian and East Asian ethnocultural groups. Serum triglycerides (TG) and total to HDL cholesterol ratio (TC:HDL cholesterol) were used as outcomes. Associations between the adiposity and blood lipid measures were examined using partial correlations and odds ratios derived from logistic regression models.</p> <p>Results</p> <p>WC had a stronger association with serum lipid concentrations than BMI. WC was significantly related to TG and TC:HDL cholesterol after adjusting for BMI and covariates among men and women (P ≤ 0.01). However, after adjusting for WC and covariates, BMI was not significantly associated with the two serum lipid measures. WC was a better predictor of TG and TC:HDL among all sex and ethnocultural subgroups except among East Asian women where little difference between the two measures was observed.</p> <p>Conclusions</p> <p>WC is a stronger predictor of cardiometabolic health when compared with BMI among young adults, especially among men.</p

GWAS identifies an NAT2 acetylator status tag single nucleotide polymorphism to be a major locus for skin fluorescence

Aims/hypothesis Skin fluorescence (SF) is a non-invasive marker of AGEs and is associated with the long-term complications of diabetes. SF increases with age and is also greater among individuals with diabetes. A familial correlation of SF suggests that genetics may play a role. We therefore performed parallel genome-wide association studies of SF in two cohorts. Methods Cohort 1 included 1,082 participants, 35–67 years of age with type 1 diabetes. Cohort 2 included 8,721 participants without diabetes, aged 18–90 years. Results rs1495741 was significantly associated with SF in Cohort 1 (p \u3c 6 × 10−10), which is known to tag theNAT2 acetylator phenotype. The fast acetylator genotype was associated with lower SF, explaining up to 15% of the variance. In Cohort 2, the top signal associated with SF (p = 8.3 × 10−42) was rs4921914, also in NAT2, 440 bases upstream of rs1495741 (linkage disequilibrium r 2 = 1.0 for rs4921914 with rs1495741). We replicated these results in two additional cohorts, one with and one without type 1 diabetes. Finally, to understand which compounds are contributing to the NAT2–SF signal, we examined 11 compounds assayed from skin biopsies (n = 198): the fast acetylator genotype was associated with lower levels of the AGEs hydroimidazolones of glyoxal (p = 0.017). Conclusions/interpretation We identified a robust association between NAT2 and SF in people with and without diabetes. Our findings provide proof of principle that genetic variation contributes to interindividual SF and thatNAT2 acetylation status plays a major role

Caffeine Consumption Contributes to Skin Intrinsic Fluorescence in Type 1 Diabetes.

Background: A variant (rs1495741) in the gene for the N-acetyltransferase 2 (NAT2) protein is associated with skin intrinsic fluorescence (SIF), a noninvasive measure of advanced glycation end products and other fluorophores in the skin. Because NAT2 is involved in caffeine metabolism, we aimed to determine whether caffeine consumption is associated with SIF and whether rs1495741 is associated with SIF independently of caffeine. Materials and Methods: SIF was measured in 1,181 participants with type 1 diabetes from the Epidemiology of Diabetes Interventions and Complications study. Two measures of SIF were used: SIF1, using a 375-nm excitation light-emitting diode (LED), and SIF14 (456-nm LED). Food frequency questionnaires were used to estimate mean caffeine intake. To establish replication, we examined a second type 1 diabetes cohort. Results: Higher caffeine intake was significantly associated with higher SIF1LED 375 nm[0.6, 0.2] (P=2×10−32) and SIF14LED 456 nm[0.4, 0.8] (P=7×10−31) and accounted for 4% of the variance in each after adjusting for covariates. When analyzed together, caffeine intake and rs1495741 both remained highly significantly associated with SIF1LED 375 nm[0.6, 0.2] and SIF14LED 456 nm[0.4, 0.8]. Mean caffeinated coffee intake was also positively associated with SIF1LED 375 nm[0.6, 0.2] (P=9×10−12) and SIF14LED 456 nm[0.4, 0.8] (P=4×10−12), but no association was observed for decaffeinated coffee intake. Finally, caffeine was also positively associated with SIF1LED 375 nm[0.6, 0.2] and SIF14LED 456 nm[0.4, 0.8] (P\u3c0.0001) in the replication cohort. Conclusions: Caffeine contributes to SIF. The effect of rs1495741 on SIF appears to be partially independent of caffeine consumption. Because SIF and coffee intake are each associated with cardiovascular disease, our findings suggest that accounting for coffee and/or caffeine intake may improve risk prediction models for SIF and cardiovascular disease in individuals with diabetes

Genetic Determinants of Carbohydrate Consumption

Background: There are a number of biological pathways that affect our ingestive behaviours, including energy homeostasis, food reward, and taste. Given that carbohydrates such as sugars, provide energy and a sweet taste, examining candidate genes in each pathway may help explain differences in carbohydrate consumption behaviours. Objective: To determine whether variations in genes encoding a glucose transporter (GLUT2), a dopamine receptor (DRD2), and sweet taste receptor (TAS1R2) are associated with differences in sugar consumption in two distinct populations. Methods: Population 1 included diabetes-free young adults where dietary intake was assessed using a one month 196-item food frequency questionnaire (FFQ). Population 2 consisted of individuals with type 2 diabetes. Dietary intake was assessed using 3-day food records administered 2 weeks apart; food record 1 (FR1) and 2 (FR2). Subjects were genotyped for the Thr110Ile variation in GLUT2 (n1=587; n2=100), the C957T variation in DRD2 (n1=313; n2=100), and the Ser9Cys and Ile191Val variations in TAS1R2 (n1=1037; n2=100) using real-time PCR. Results: In comparison to individuals homozygous for the GLUT2 Thr allele, consumption of sugars was higher among Ile carriers in population 1 (133 ± 5 vs 118 ± 3 g/d, p=0.006) and population 2 on two separate food records (FR1: 112 ± 9 vs 87 ± 5 g/d, p=0.02; FR2: 105 ± 8 vs 78 ± 4 g/d, p=0.002). For the C957T variation in population 1, we detected a significant DRD2xSex interaction with the consumption of sucrose decreasing with each T allele among men (p=0.03) and a heterosis mode of inheritance among women where heterozygotes consumed the most (p=0.01). For TAS1R2, we detected a significant TAS1R2xBMI interaction and among overweight individuals, carriers of the Val allele consumed less sugars than those with the Ile/Ile genotype (103 ± 6 vs122 ± 6 g/d, p=0.01). In population 2, carriers of the Val allele consumed less sugars than individuals with the Ile/Ile genotype (83 ± 6 vs 99 ± 6 g/d, p=0.04) on FR2. Conclusions: Our findings demonstrate that genetic variation in GLUT2, DRD2 and TAS1R2 affect habitual sugar consumption and suggest that selection of dietary sugars can be influenced by different biological pathways.Ph

Caffeine Consumption Contributes to Skin Intrinsic Fluorescence in Type 1 Diabetes

Background: A variant (rs1495741) in the gene for the N-acetyltransferase 2 (NAT2) protein is associated with skin intrinsic fluorescence (SIF), a noninvasive measure of advanced glycation end products and other fluorophores in the skin. Because NAT2 is involved in caffeine metabolism, we aimed to determine whether caffeine consumption is associated with SIF and whether rs1495741 is associated with SIF independently of caffeine. Materials and Methods: SIF was measured in 1,181 participants with type 1 diabetes from the Epidemiology of Diabetes Interventions and Complications study. Two measures of SIF were used: SIF1, using a 375-nm excitation light-emitting diode (LED), and SIF14 (456-nm LED). Food frequency questionnaires were used to estimate mean caffeine intake. To establish replication, we examined a second type 1 diabetes cohort. Results: Higher caffeine intake was significantly associated with higher SIF1LED 375nm[0.6,0.2] (P=2×10-32) and SIF14LED 456nm[0.4,0.8] (P=7×10-31) and accounted for 4% of the variance in each after adjusting for covariates. When analyzed together, caffeine intake and rs1495741 both remained highly significantly associated with SIF1LED 375nm[0.6,0.2] and SIF14LED 456nm[0.4,0.8]. Mean caffeinated coffee intake was also positively associated with SIF1LED 375nm[0.6,0.2] (P=9×10-12) and SIF14LED 456nm[0.4,0.8] (P=4×10-12), but no association was observed for decaffeinated coffee intake. Finally, caffeine was also positively associated with SIF1LED 375nm[0.6,0.2] and SIF14LED 456nm[0.4,0.8] (P\u3c0.0001) in the replication cohort. Conclusions: Caffeine contributes to SIF. The effect of rs1495741 on SIF appears to be partially independent of caffeine consumption. Because SIF and coffee intake are each associated with cardiovascular disease, our findings suggest that accounting for coffee and/or caffeine intake may improve risk prediction models for SIF and cardiovascular disease in individuals with diabetes