Genetic and Environmental Contributions to BMI in Adolescent and Young Adult Women

The objective of this study was to determine the genetic and environmental contributions to variation in BMI over time in European‐American (EA) and African‐American (AA) adolescent and young adult women. Self‐reported BMI (kg/m²) data from 2,816 EA (1,306 twin pairs, 56.5% monozygotic (MZ)) and 404 AA (178 twin pairs, 42.7% MZ) women at baseline (T1; median age 15 years) and 3,225 EA (1,511 twin pairs, 55.3% MZ) and 539 AA (252 pairs, 43.3% MZ) women at follow‐up (T2; median age 22 years) from a Midwestern US, population‐based twin registry were used to construct biometrical genetic models. For EA women, the majority of the variance in BMI was attributable to additive genetic effects at both time points (82% for each), with the remaining variance attributable to nonshared environment. Genetic and nonshared environment correlations between adolescent and young adult BMI were 0.87 and 0.23, respectively. Among AA women, nonadditive genetic effects comprised 68% of the variance at T1 and 73% at T2, and were highly correlated (r_D = 0.94). The proportions of variance attributable to nonshared environment at T1 (29%) and T2 (25%) were more modestly correlated (r_E = 0.31). The remaining variance in AA women could be attributed to additive genetic effects. Additive vs. nonadditive genetic effects contribute differentially to BMI in AA vs. EA adolescent and young adult women. Additional research is needed to better characterize the environmental and genetic factors related to BMI in persons of different races to aid understanding of the complex determinants of body weight in individuals.     

Joint Effect of Genetic and Lifestyle Risk Factors on Type 2 Diabetes Risk among Chinese Men and Women

More than 40 genetic susceptibility loci have been reported for type 2 diabetes (T2D). Recently, the combined effect of genetic variants has been investigated by calculating a genetic risk score. We evaluated 36 genome-wide association study (GWAS) identified SNPs in 2,679 T2D cases and 3322 controls in middle-age Han Chinese. Fourteen SNPs were significantly associated with T2D in analysis adjusted for age, sex and BMI. We calculated two genetic risk scores (GRS) (GRS1 with all the 36 SNPs and GRS2 with the 14 SNPs significantly associated with T2D). The odds ratio for T2D with each GRS point (per risk allele) was 1.08 (95% CI: 1.06–1.09) for GRS1 and 1.15 (95% CI: 1.13–1.18) for GRS2. The OR for quintiles were 1.00, 1.26, 1.69, 1.95 and 2.18 (P<0.0001) for GRS1 and 1.00, 1.33, 1.60, 2.03 and 2.80 (P<0.001) for GRS2. Participants in the higher tertile of GRS1 and the higher BMI category had a higher risk of T2D compared to those on the lower tertiles of the GRS1 and of BMI (OR = 11.08; 95% CI: 7.39–16.62). We found similar results when we investigated joint effects between GRS1 and WHR terciles and exercise participation. We finally investigated the joint effect between tertiles of GRSs and a composite high risk score (no exercise participation and high BMI and WHR) on T2D risk. We found that compared to participants with low GRS1 and no high risk factors for T2D, those with high GRS1 and three high risk factors had a higher risk of T2D (OR = 13.06; 95% CI: 8.65–19.72) but the interaction factor was of marginal significance. The association was accentuated when we repeated analysis with the GRS2. In conclusion we found an association between GRS and lifestyle factors, alone and in combination, contributed to the risk of and T2D among middle age Chinese.     

Body Mass Index Genetic Risk Score and Endometrial Cancer Risk

Genome-wide association studies (GWAS) have identified common variants that predispose individuals to a higher body mass index (BMI), an independent risk factor for endometrial cancer. Composite genotype risk scores (GRS) based on the joint effect of published BMI risk loci were used to explore whether endometrial cancer shares a genetic background with obesity. Genotype and risk factor data were available on 3,376 endometrial cancer case and 3,867 control participants of European ancestry from the Epidemiology of Endometrial Cancer Consortium GWAS. A BMI GRS was calculated by summing the number of BMI risk alleles at 97 independent loci. For exploratory analyses, additional GRSs were based on subsets of risk loci within putative etiologic BMI pathways. The BMI GRS was statistically significantly associated with endometrial cancer risk (P = 0.002). For every 10 BMI risk alleles a woman had a 13% increased endometrial cancer risk (95% CI: 4%, 22%). However, after adjusting for BMI, the BMI GRS was no longer associated with risk (per 10 BMI risk alleles OR = 0.99, 95% CI: 0.91, 1.07; P = 0.78). Heterogeneity by BMI did not reach statistical significance (P = 0.06), and no effect modification was noted by age, GWAS Stage, study design or between studies (P≥0.58). In exploratory analyses, the GRS defined by variants at loci containing monogenic obesity syndrome genes was associated with reduced endometrial cancer risk independent of BMI (per BMI risk allele OR = 0.92, 95% CI: 0.88, 0.96; P = 2.1 x 10⁻⁵). Possessing a large number of BMI risk alleles does not increase endometrial cancer risk above that conferred by excess body weight among women of European descent. Thus, the GRS based on all current established BMI loci does not provide added value independent of BMI. Future studies are required to validate the unexpected observed relation between monogenic obesity syndrome genetic variants and endometrial cancer risk.     

Association of type 2 diabetes susceptibility loci with one-year weight loss in the look AHEAD clinical trial

The importance of lifestyle intervention for the prevention and treatment of type 2 diabetes (T2D) has been underscored by the limited benefit of pharmacologic therapies. We sought to determine whether genetic variants that contribute to T2D risk modify the response of weight and waist circumference to an intensive lifestyle intervention (ILI) in patients with obesity and T2D. Look AHEAD (Action for Health in Diabetes) is a randomized clinical trial comparing an ILI with a control condition on the risk of cardiovascular disease in overweight adults with T2D. We analyzed 28 single-nucleotide polymorphisms (SNPs) at/near 17 T2D-susceptibility genes in 3,903 consented participants. We genetically characterized the cohort by assessing whether T2D-susceptibility loci were overrepresented compared with a nondiabetic community-based cohort (N = 1,016). We evaluated the association of individual variants and a composite genetic risk score (GRS) with anthropometric traits at baseline and after 1-year of intervention. Look AHEAD subjects carried more T2D-susceptibility alleles than the control population. At baseline, TCF7L2 risk alleles and the highest GRS were associated with lower BMI and waist circumference. Nominally significant genotype-by-intervention interactions were detected for 1-year change in waist circumference with JAZF1, MTNR1B, and IRS1, and BMI with JAZF1. Highest GRS was associated with a greater reduction in waist circumference at year 1, although the variance in change attributable to the GRS was small. This study shows that the genetic burden associated with T2D risk does not undermine the effect of lifestyle intervention and suggests the existence of additional genomic regions, distinct from the T2D-susceptibility loci, which may enhance or mitigate weight loss.     

Genome-wide association study of the plasma triglyceride response to an n-3 polyunsaturated fatty acid supplementation

Studies have shown a large interindividual variability in plasma TG response to long-chain n-3 PUFA supplementation, which may likely be attributable to genetic variability within the populations studied. The objective is to compare the frequency of SNPs in a genome-wide association study between responders (reduction in plasma TG levels ≥0.01 mM) and nonresponders (increase in plasma TG of ≥0 mM) to supplementation. Genomic DNA from 141 subjects who completed a 2-week run-in period followed by 6-week supplementation with 5 g of fish oil daily (1.9–2.2 g EPA and 1.1 g DHA daily) were genotyped on Illumina HumanOmni-5-QuadBeadChip. Thirteen loci had frequency differences between responders and nonresponders (P < 1 × 10⁻⁵), including SNPs in or near IQCJ-SCHIP1, MYB, NELL1, NXPH1, PHF17, and SLIT2 genes. A genetic risk score (GRS) was constructed by summing the number of risk alleles. This GRS explained 21.53% of the variation in TG response to n-3 PUFA supplementation when adjusted for age, sex, and BMI (P = 0.0002). Using Fish Oil Intervention and Genotype as a replication cohort, the GRS was able to explain 2% of variation in TG response when adjusted. In conclusion, subjects who decrease their plasma TG levels following n-3 PUFA supplementation may have a different genetic profile than individuals who do not respond.     

Genetic susceptibility to obesity and diet intakes: association and interaction analyses in the Malmö Diet and Cancer Study

Gene–environment interactions need to be studied to better understand the obesity. We aimed at determining whether genetic susceptibility to obesity associates with diet intake levels and whether diet intakes modify the genetic susceptibility. In 29,480 subjects of the population-based Malmö Diet and Cancer Study (MDCS), we first assessed association between 16 genome-wide association studies identified obesity-related single-nucleotide polymorphisms (SNPs) with body mass index (BMI) and associated traits. We then conducted association analyses between a genetic risk score (GRS) comprising of 13 replicated SNPs and the individual SNPs, and relative dietary intakes of fat, carbohydrates, protein, fiber and total energy intake, as well as interaction analyses on BMI and associated traits among 26,107 nondiabetic MDCS participants. GRS associated strongly with increased BMI (P = 3.6 × 10^?34), fat mass (P = 6.3 × 10^?28) and fat-free mass (P = 1.3 × 10^?24). Higher GRS associated with lower total energy intake (P = 0.001) and higher intake of fiber (P = 2.3 × 10^?4). No significant interactions were observed between GRS and the studied dietary intakes on BMI or related traits. Of the individual SNPs, after correcting for multiple comparisons, NEGR1 rs2815752 associated with diet intakes and BDNF rs4923461 showed interaction with protein intake on BMI. In conclusion, our study does not provide evidence for a major role for macronutrient-, fiber- or total energy intake levels in modifying genetic susceptibility to obesity measured as GRS. However, our data suggest that the number of risk alleles as well as some of the individual obesity loci may have a role in regulation of food and energy intake and that some individual loci may interact with diet.     

Adiposity significantly modifies genetic risk for dyslipidemia

Recent genome-wide association studies have identified multiple loci robustly associated with plasma lipids, which also contribute to extreme lipid phenotypes. However, these common genetic variants explain <12% of variation in lipid traits. Adiposity is also an important determinant of plasma lipoproteins, particularly plasma TGs and HDL cholesterol (HDLc) concentrations. Thus, interactions between genes and clinical phenotypes may contribute to this unexplained heritability. We have applied a weighted genetic risk score (GRS) for both plasma TGs and HDLc in two large cohorts at the extremes of BMI. Both BMI and GRS were strongly associated with these lipid traits. A significant interaction between obese/lean status and GRS was noted for each of TG (P_Interaction = 2.87 × 10⁻⁴) and HDLc (P_Interaction = 1.05 × 10⁻³). These interactions were largely driven by SNPs tagging APOA5, glucokinase receptor (GCKR), and LPL for TG, and cholesteryl ester transfer protein (CETP), GalNAc-transferase (GALNT2), endothelial lipase (LIPG), and phospholipid transfer protein (PLTP) for HDLc. In contrast, the GRS_{LDL cholesterol} × adiposity interaction was not significant. Sexual dimorphism was evident for the GRS_HDL on HDLc in obese (P_Interaction = 0.016) but not lean subjects. SNP by BMI interactions may provide biological insight into specific genetic associations and missing heritability.     

Fine Mapping of the Body Fat QTL on Human Chromosome 1q43

IntroductionEvidence for linkage and association of obesity-related quantitative traits to chromosome 1q43 has been reported in the Quebec Family Study (QFS) and in populations of Caribbean Hispanic ancestries yet no specific candidate locus has been replicated to date.MethodsUsing a set of 1,902 single nucleotide polymorphisms (SNPs) genotyped in 525 African American (AA) and 391 European American (EA) women enrolled in the NIEHS uterine fibroid study (NIEHS-UFS), we generated a fine association map for the body mass index (BMI) across a 2.3 megabase-long interval delimited by RGS7 (regulator of G-protein signaling 7) and PLD5 (Phospholipase D, member 5). Multivariable-adjusted linear regression models were fitted to the data to evaluate the association in race-stratified analyses and meta-analysis.ResultsThe strongest associations were observed in a recessive genetic model and peaked in the 3’ end of RGS7 at intronic rs261802 variant in the AA group (p = 1.0 x 10⁻⁴) and in meta-analysis of AA and EA samples (p = 9.0 x 10⁻⁵). In the EA group, moderate associations peaked at rs6429264 (p = 2.0 x 10⁻³) in the 2 Kb upstream sequence of RGS7. In the reference populations for the European ancestry in the 1,000 genomes project, rs6429264 occurs in strong linkage disequilibrium (D’ = 0.94) with rs1341467, the strongest candidate SNP for total body fat in QFS that failed genotyping in the present study. Additionally we report moderate associations at the 3’ end of PLD5 in meta-analysis (3.2 x 10⁻⁴ ≤ p ≤ 5.8 x 10⁻⁴).ConclusionWe report replication data suggesting that RGS7, a gene abundantly expressed in the brain, might be a putative body fat QTL on human chromosome 1q43. Future genetic and functional studies are required to substantiate our observations and to potentially link them to the neurobehavioral phenotypes associated with the RGS7 region.     

Obesity and the relation between joint exposure to ambient air pollutants and incident type 2 diabetes: A cohort study in UK Biobank

BackgroundAir pollution has been related to incidence of type 2 diabetes (T2D). We assessed the joint association of various air pollutants with the risk of T2D and examined potential modification by obesity status and genetic susceptibility on the relationship.Methods and findingsA total of 449,006 participants from UK Biobank free of T2D at baseline were included. Of all the study population, 90.9% were white and 45.7% were male. The participants had a mean age of 56.6 (SD 8.1) years old and a mean body mass index (BMI) of 27.4 (SD 4.8) kg/m². Ambient air pollutants, including particulate matter (PM) with diameters ≤2.5 μm (PM_2.5), between 2.5 μm and 10 μm (PM_2.5–10), nitrogen dioxide (NO₂), and nitric oxide (NO) were measured. An air pollution score was created to assess the joint exposure to the 4 air pollutants. During a median of 11 years follow-up, we documented 18,239 incident T2D cases. The air pollution score was significantly associated with a higher risk of T2D. Compared to the lowest quintile of air pollution score, the hazard ratio (HR) (95% confidence interval [CI]) for T2D was 1.05 (0.99 to 1.10, p = 0.11), 1.06 (1.00 to 1.11, p = 0.051), 1.09 (1.03 to 1.15, p = 0.002), and 1.12 (1.06 to 1.19, p < 0.001) for the second to fifth quintile, respectively, after adjustment for sociodemographic characteristics, lifestyle factors, genetic factors, and other covariates. In addition, we found a significant interaction between the air pollution score and obesity status on the risk of T2D (p-interaction < 0.001). The observed association was more pronounced among overweight and obese participants than in the normal-weight people. Genetic risk score (GRS) for T2D or obesity did not modify the relationship between air pollution and risk of T2D. Key study limitations include unavailable data on other potential T2D-related air pollutants and single-time measurement on air pollutants.ConclusionsWe found that various air pollutants PM_2.5, PM_2.5–10, NO_2, and NO, individually or jointly, were associated with an increased risk of T2D in the population. The stratified analyses indicate that such associations were more strongly associated with T2D risk among those with higher adiposity.

Xiang Li and co-workers study the potential influence of obesity on associations between air pollutants and incidence of type 2 diabetes.     

MicroRNA-34a modulates genes involved in cellular motility and oxidative phosphorylation in neural precursors derived from human umbilical cord mesenchymal stem cells

Background

Uric acid is the primary byproduct of purine metabolism. Hyperuricemia is associated with body mass index (BMI), sex, and multiple complex diseases including gout, hypertension (HTN), renal disease, and type 2 diabetes (T2D). Multiple genome-wide association studies (GWAS) in individuals of European ancestry (EA) have reported associations between serum uric acid levels (SUAL) and specific genomic loci. The purposes of this study were: 1) to replicate major signals reported in EA populations; and 2) to use the weak LD pattern in African ancestry population to better localize (fine-map) reported loci and 3) to explore the identification of novel findings cognizant of the moderate sample size.

Methods

African American (AA) participants (n = 1,017) from the Howard University Family Study were included in this study. Genotyping was performed using the Affymetrix^® Genome-wide Human SNP Array 6.0. Imputation was performed using MACH and the HapMap reference panels for CEU and YRI. A total of 2,400,542 single nucleotide polymorphisms (SNPs) were assessed for association with serum uric acid under the additive genetic model with adjustment for age, sex, BMI, glomerular filtration rate, HTN, T2D, and the top two principal components identified in the assessment of admixture and population stratification.

Results

Four variants in the gene SLC2A9 achieved genome-wide significance for association with SUAL (p-values ranging from 8.88 × 10^-9 to 1.38 × 10^-9). Fine-mapping of the SLC2A9 signals identified a 263 kb interval of linkage disequilibrium in the HapMap CEU sample. This interval was reduced to 37 kb in our AA and the HapMap YRI samples.

Conclusions

The most strongly associated locus for SUAL in EA populations was also the most strongly associated locus in this AA sample. This finding provides evidence for the role of SLC2A9 in uric acid metabolism across human populations. Additionally, our findings demonstrate the utility of following-up EA populations GWAS signals in African-ancestry populations with weaker linkage disequilibrium.     

Development and Evaluation of a Genetic Risk Score for Obesity

Multi-locus profiles of genetic risk, so-called “genetic risk scores,” can be used to translate discoveries from genome-wide association studies into tools for population health research. We developed a genetic risk score for obesity from results of 16 published genome-wide association studies of obesity phenotypes in European-descent samples. We then evaluated this genetic risk score using data from the Atherosclerosis Risk in Communities (ARIC) cohort GWAS sample (N = 10,745, 55% female, 77% white, 23% African American). Our 32-locus GRS was a statistically significant predictor of body mass index (BMI) and obesity among ARIC whites [for BMI, r = 0.13, p<1?×?10^?30; for obesity, area under the receiver operating characteristic curve (AUC) = 0.57 (95% CI 0.55–0.58)]. The GRS predicted differences in obesity risk net of demographic, geographic, and socioeconomic information. The GRS performed less well among African Americans. The genetic risk score we derived from GWAS provides a molecular measurement of genetic predisposition to elevated BMI and obesity.[Supplemental materials are available for this article. Go to the publisher's online edition of Biodemography and Social Biology for the following resource: Supplement to Development & Evaluation of a Genetic Risk Score for Obesity.]     

Genetic Determinants for Gestational Diabetes Mellitus and Related Metabolic Traits in Mexican Women

Epidemiological and physiological similarities among Gestational Diabetes Mellitus (GDM) and Type 2 Diabetes (T2D) suggest that both diseases, share a common genetic background. T2D risk variants have been associated to GDM susceptibility. However, the genetic architecture of GDM is not yet completely understood. We analyzed 176 SNPs for 115 loci previously associated to T2D, GDM and body mass index (BMI), as well as a set of 118 Ancestry Informative Markers (AIMs), in 750 pregnant Mexican women. Association with GDM was found for two of the most frequently replicated T2D loci: a TCF7L2 haplotype (CTTC: rs7901695, rs4506565, rs7903146, rs12243326; P=2.16x10^-06; OR=2.95) and a KCNQ1 haplotype (TTT: rs2237892, rs163184, rs2237897; P=1.98x10^-05; OR=0.55). In addition, we found two loci associated to glycemic traits: CENTD2 (60’ OGTT glycemia: rs1552224, P=0.03727) and MTNR1B (HOMA B: rs1387153, P=0.05358). Remarkably, a major susceptibility SLC16A11 locus for T2D in Mexicans was not shown to play a role in GDM risk. The fact that two of the main T2D associated loci also contribute to the risk of developing GDM in Mexicans, confirm that both diseases share a common genetic background. However, lack of association with a Native American contribution T2D risk haplotype, SLC16A11, suggests that other genetic mechanisms may be in play for GDM.     

Gene-Based Sequencing Identifies Lipid-Influencing Variants with Ethnicity-Specific Effects in African Americans

Although a considerable proportion of serum lipids loci identified in European ancestry individuals (EA) replicate in African Americans (AA), interethnic differences in the distribution of serum lipids suggest that some genetic determinants differ by ethnicity. We conducted a comprehensive evaluation of five lipid candidate genes to identify variants with ethnicity-specific effects. We sequenced ABCA1, LCAT, LPL, PON1, and SERPINE1 in 48 AA individuals with extreme serum lipid concentrations (high HDLC/low TG or low HDLC/high TG). Identified variants were genotyped in the full population-based sample of AA (n = 1694) and tested for an association with serum lipids. rs328 (LPL) and correlated variants were associated with higher HDLC and lower TG. Interestingly, a stronger effect was observed on a “European” vs. “African” genetic background at this locus. To investigate this effect, we evaluated the region among West Africans (WA). For TG, the effect size among WA was the same in AA with only African local ancestry (2–3% lower TG), while the larger association among AA with local European ancestry matched previous reports in EA (10%). For HDLC, there was no association with rs328 in AA with only African local ancestry or in WA, while the association among AA with European local ancestry was much greater than what has been observed for EA (15 vs. ∼5 mg/dl), suggesting an interaction with an environmental or genetic factor that differs by ethnicity. Beyond this ancestry effect, the importance of African ancestry-focused, sequence-based work was also highlighted by serum lipid associations of variants that were in higher frequency (or present only) among those of African ancestry. By beginning our study with the sequence variation present in AA individuals, investigating local ancestry effects, and seeking replication in WA, we were able to comprehensively evaluate the role of a set of candidate genes in serum lipids in AA.     

Association of Type 2 Diabetes Genetic Variants with Breast Cancer Survival among Chinese Women

ObjectiveTo evaluate whether the genetic susceptibility of T2D was associated with overall survival (OS) and disease-free survival (DFS) outcomes for breast cancer (BC).MethodsIncluded in the study were 6346 BC patients who participated in three population-based epidemiological studies of BC and were genotyped with either GWAS or Exome-chip. We constructed a genetic risk score (GRS) for diabetes using risk variants identified from the GWAS catalog (http://genome.gov/gwastudies) that were associated with T2D risk at a minimum significance level of P ≤ 5.0E-8 among Asian population and evaluated its associations with BC outcomes with Cox proportional hazards models.ResultsDuring a median follow-up of 8.08 years (range, 0.01–16.95 years), 1208 deaths were documented in 6346 BC patients. Overall, the diabetes GRS was not associated with OS and DFS. Analyses stratified by estrogen receptor status (ER) showed that the diabetes GRS was inversely associated with OS among women with ER- but not in women with ER+ breast cancer; the multivariable adjusted HR was 1.38 (95% CI: 1.05–1.82) when comparing the highest to the lowest GRS quartiles. The association of diabetes GRS with OS varied by diabetes status (P for interaction <0.01). In women with history of diabetes, higher diabetes GRS was significantly associated with worse OS, with HR of 2.22 (95% CI: 1.28–3.88) for the highest vs. lowest quartile, particularly among women with an ER- breast cancer, with corresponding HR being 4.59 (95% CI: 1.04–20.28). No significant association between the diabetes GRS and OS was observed across different BMI and PR groups.ConclusionsOur study suggested that genetic susceptibility of T2D was positively associated with total mortality among women with ER- breast cancer, particularly among subjects with a history of diabetes. Additional studies are warranted to verify the associations and elucidate the underlying biological mechanism.     

Genetic Markers Enhance Coronary Risk Prediction in Men: The MORGAM Prospective Cohorts

Background

More accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design.

Methods

Using data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5–18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived.

Results

Both scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50–59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events.

Conclusions

Genetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men.     

Waist Circumference Independently Associates with the Risk of Insulin Resistance and Type 2 Diabetes in Mexican American Families

Objective

In spite of the growing recognition of the specific association of waist circumference (WC) with type 2 diabetes (T2D) and insulin resistance (IR), current guidelines still use body mass index (BMI) as a tool of choice. Our objective was to determine whether WC is a better T2D predictor than BMI in family-based settings.

Research Design and Methods

Using prospectively collected data on 808 individuals from 42 extended Mexican American families representing 7617.92 person-years follow-up, we examined the performance of WC and BMI as predictors of cumulative and incident risk of T2D. We used robust statistical methods that accounted for the kinships and included polygenic models, discrete trait modeling, Akaike information criterion, odds ratio (OR), relative risk (RR) and Kullback-Leibler R². SOLAR software was used to conduct all the data analyses.

Results

We found that in multivariate polygenic models, WC was an independent predictor of cumulative (OR = 2.76, p = 0.0002) and future risk of T2D (RR = 2.15, p = 3.56×10⁻⁹) and outperformed BMI when compared in a head-to-head fashion. High WC (≥94.65 cm after adjusting for age and sex) was also associated with high fasting glucose, insulin and triglyceride levels and low high-density lipoprotein levels indicating a potential association with IR. Moreover, WC was specifically and significantly associated with insulin resistant T2D (OR = 4.83, p = 1.01×10⁻¹³).

Conclusions

Our results demonstrate the value of using WC as a screening tool of choice for future risk of T2D in Mexican American families. Also, WC is specifically associated with insulin resistant T2D.     

Genetic risk scores to predict the prognosis of chronic heart failure patients in Chinese Han

Chronic heart failure (CHF) has poor prognosis and polygenic heritability, and the genetic risk score (GRS) to predict CHF outcome has not yet been researched comprehensively. In this study, we sought to establish GRS to predict the outcomes of CHF. We re‐analysed the proteomics data of failing human heart and combined them to filter the data of high‐throughput sequencing in 1000 Chinese CHF cohort. Cox hazards models were used based on single nucleotide polymorphisms (SNPs) to estimate the association of GRS with the prognosis of CHF, and to analyse the difference between individual SNPs and tertiles of genetic risk. In the cohort study, GRS encompassing eight SNPs harboured in seven genes were significantly associated with the prognosis of CHF (P = 2.19 × 10^?10 after adjustment). GRS was used in stratifying individuals into significantly different CHF risk, with those in the top tertiles of GRS distribution having HR of 3.68 (95% CI: 2.40‐5.65 P = 2.47 × 10^?10) compared with those in the bottom. We developed GRS and demonstrated its association with first event of heart failure endpoint. GRS might be used to stratify individuals for CHF prognostic risk and to predict the outcomes of genomic screening as a complement to conventional risk and NT‐proBNP.     

CDK4 IVS4-nt40G→A and T2D-associated obesity in Italians

Cell cycle regulators play crucial roles in the preadipocyte proliferation and adipocyte differentiation. Cyclin-dependent kinase 4 (CDK4) mediates with D-type cyclins entry of cells into cell cycle in response to external stimuli. CDK4 plays a role in body weight, adipogenesis, and beta cell proliferation. CDK4 null mice develop type 2 diabetes (T2D). Furthermore, CDK4 variants are associated with obesity-associated tumors/cancer. We aimed at identifying a role of CDK4 IVS4-nt40G → A variant in T2D-associated obesity (body mass index, BMI ≥ 30) by association tests in an Italian T2D subjects dataset. We recruited from Italy 128 unrelated T2D subjects with BMI <30 kg/m² and 54 unrelated T2D subjects with BMI ≥ 30 kg/m². We performed statistical power calculations in our dataset. DNA samples were directly sequenced with specific primers for CDK4 IVS4-nt40G → A variant. We identified a significant association of the G allele with T2D-associated obesity and of the A allele with T2D-associated BMI < 30. In our study, we found that the CDK4 IVS4-nt40GG genotype is a risk variant for T2D-associated obesity and that the AA genotype is associated with BMI < 30 in T2D. Hence, CDK4 IVS4-nt40A allele is protective and G allele confers risk for obesity in T2D patients. This study should prompt further work aiming at establishing CDK4 role in contributing to human obesity and T2D-associated obesity. J. Cell. Physiol. 221: 273–275, 2009. © 2009 Wiley-Liss, Inc.     

Obesity polymorphisms identified in genome-wide association studies interact with n-3 polyunsaturated fatty acid intake and modify the genetic association with adiposity phenotypes in Yup’ik people

n-3 Polyunsaturated fatty acids (n-3 PUFAs) have anti-obesity effects that may modulate risk of obesity, in part, through interactions with genetic factors. Genome-wide association studies (GWAS) have identified genetic variants associated with body mass index (BMI); however, the extent to which these variants influence adiposity through interactions with n-3 PUFAs remains unknown. We evaluated 10 highly replicated obesity GWAS single nucleotide polymorphisms (SNPs) for individual and cumulative associations with adiposity phenotypes in a cross-sectional sample of Yup’ik people (n = 1,073) and evaluated whether genetic associations with obesity were modulated by n-3 PUFA intake. A genetic risk score (GRS) was calculated by adding the BMI-increasing alleles across all 10 SNPs. Dietary intake of n-3 PUFAs was estimated using nitrogen stable isotope ratio (δ¹⁵N) of red blood cells, and genotype–phenotype analyses were tested in linear models accounting for familial correlations. GRS was positively associated with BMI (p = 0.012), PBF (p = 0.022), ThC (p = 0.025), and waist circumference (p = 0.038). The variance in adiposity phenotypes explained by the GRS included BMI (0.7 %), PBF (0.3 %), ThC (0.7 %), and WC (0.5 %). GRS interactions with n-3 PUFAs modified the association with adiposity and accounted for more than twice the phenotypic variation (~1–2 %), relative to GRS associations alone. Obesity GWAS SNPs contribute to adiposity in this study population of Yup’ik people and interactions with n-3 PUFA intake potentiated the risk of fat accumulation among individuals with high obesity GRS. These data suggest the anti-obesity effects of n-3 PUFAs among Yup’ik people may, in part, be dependent upon an individual’s genetic predisposition to obesity.

Electronic supplementary material

The online version of this article (doi:10.1007/s12263-013-0340-z) contains supplementary material, which is available to authorized users.