Estimating causality between smoking and abdominal obesity by Mendelian randomization.

BACKGROUND AND AIMS: Smokers tend to have a lower body weight than non-smokers, but also more abdominal fat. It remains unclear whether or not the relationship between smoking and abdominal obesity is causal. Previous Mendelian randomization (MR) studies have investigated this relationship by relying upon a single genetic variant for smoking heaviness. This approach is sensitive to pleiotropic effects and may produce imprecise causal estimates. We aimed to estimate causality between smoking and abdominal obesity using multiple genetic instruments. DESIGN: MR study using causal analysis using summary effect estimates (CAUSE) and latent heritable confounder MR (LHC-MR) methods that instrument smoking using genome-wide data, and also two-sample MR (2SMR) methods. SETTING: Genome-wide association studies (GWAS) summary statistics from participants of European ancestry, obtained from the GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN), Genetic Investigation of Anthropometric Traits (GIANT) Consortium and the UK Biobank. PARTICIPANTS: We used GWAS results for smoking initiation (n = 1 232 091), life-time smoking (n = 462 690) and smoking heaviness (n = 337 334) as exposure traits, and waist-hip ratio (WHR) and waist and hip circumferences (WC and HC) (n up to 697 734), with and without adjustment for body mass index (adjBMI), as outcome traits. MEASUREMENTS: Smoking initiation, life-time smoking, smoking heaviness, WHR, WC, HC, WHRadjBMI, WCadjBMI and HCadjBMI. FINDINGS: Both CAUSE and LHC-MR indicated a positive causal effect of smoking initiation on WHR (0.13 [95% confidence interval (CI) = 0.10, 0.16 and 0.49 (0.41, 0.57), respectively] and WHRadjBMI (0.07 (0.03, 0.10) and 0.31 (0.26, 0.37). Similarly, they indicated a positive causal effect of life-time smoking on WHR [0.35 (0.29, 0.41) and 0.44 (0.38, 0.51)] and WHRadjBMI [0.18 (0.13, 0.24) and 0.26 (0.20, 0.31)]. In follow-up analyses, smoking particularly increased visceral fat. There was no evidence of a mediating role by cortisol or sex hormones. CONCLUSIONS: Smoking initiation and higher life-time smoking may lead to increased abdominal fat distribution. The increase in abdominal fat due to smoking is characterized by an increase in visceral fat. Thus, efforts to prevent and cease smoking can have the added benefit of reducing abdominal fat.

Targeting postsynaptic glutamate receptor scaffolding proteins PSD-95 and PICK1 for obesity treatment.

Human genome-wide association studies (GWAS) suggest a functional role for central glutamate receptor signaling and plasticity in body weight regulation. Here, we use UK Biobank GWAS summary statistics of body mass index (BMI) and body fat percentage (BF%) to identify genes encoding proteins known to interact with postsynaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and N-methyl-d-aspartate (NMDA) receptors. Loci in/near discs large homolog 4 (DLG4) and protein interacting with C kinase 1 (PICK1) reached genome-wide significance (P < 5 × 10-8) for BF% and/or BMI. To further evaluate the functional role of postsynaptic density protein-95 (PSD-95; gene name: DLG4) and PICK1 in energy homeostasis, we used dimeric PSD-95/disc large/ZO-1 (PDZ) domain-targeting peptides of PSD-95 and PICK1 to demonstrate that pharmacological inhibition of PSD-95 and PICK1 induces prolonged weight-lowering effects in obese mice. Collectively, these data demonstrate that the glutamate receptor scaffolding proteins, PICK1 and PSD-95, are genetically linked to obesity and that pharmacological targeting of their PDZ domains represents a promising therapeutic avenue for sustained weight loss.

Refinement of a published gene-physical activity interaction impacting HDL-cholesterol: role of sex and lipoprotein subfractions.

Large-scale gene-environment interaction (GxE) discovery efforts often involve compromises in the definition of outcomes and choice of covariates for the sake of data harmonization and statistical power. Consequently, refinement of exposures, covariates, outcomes, and population subsets may be helpful to establish often-elusive replication and evaluate potential clinical utility. Here, we used additional datasets, an expanded set of statistical models, and interrogation of lipoprotein metabolism via nuclear magnetic resonance (NMR)-based lipoprotein subfractions to refine a previously discovered GxE modifying the relationship between physical activity (PA) and HDL-cholesterol (HDL-C). This GxE was originally identified by Kilpeläinen et al., with the strongest cohort-specific signal coming from the Women's Genome Health Study (WGHS). We thus explored this GxE further in the WGHS (N = 23,294), with follow-up in the UK Biobank (UKB; N = 281,380), and the Multi-Ethnic Study of Atherosclerosis (MESA; N = 4,587). Self-reported PA (MET-hrs/wk), genotypes at rs295849 (nearest gene: LHX1), and NMR metabolomics data were available in all three cohorts. As originally reported, minor allele carriers of rs295849 in WGHS had a stronger positive association between PA and HDL-C (pint = 0.002). When testing a range of NMR metabolites (primarily lipoprotein and lipid subfractions) to refine the HDL-C outcome, we found a stronger interaction effect on medium-sized HDL particle concentrations (M-HDL-P; pint = 1.0×10-4) than HDL-C. Meta-regression revealed a systematically larger interaction effect in cohorts from the original meta-analysis with a greater fraction of women (p = 0.018). In the UKB, GxE effects were stronger both in women and using M-HDL-P as the outcome. In MESA, the primary interaction for HDL-C showed nominal significance (pint = 0.013), but without clear differences by sex and with a greater magnitude using large, rather than medium, HDL-P as an outcome. Towards reconciling these observations, further exploration leveraging NMR platform-specific HDL subfraction diameter annotations revealed modest agreement across all cohorts in the interaction affecting medium-to-large particles. Taken together, our work provides additional insights into a specific known gene-PA interaction while illustrating the importance of phenotype and model refinement towards understanding and replicating GxEs.

Child-to-adult body size change and risk of type 2 diabetes and cardiovascular disease.

AIMS/HYPOTHESIS: Childhood overweight increases the risk of type 2 diabetes and cardiovascular disease in adulthood. However, the impact of childhood leanness on adult obesity and disease risk has been overlooked. We examined the independent and combined influences of child and adult body size on the risk of type 2 diabetes and cardiovascular disease. METHODS: Data from the UK Biobank on 364,695 individuals of European ancestry and free of type 2 diabetes and cardiovascular disease were divided into nine categories based on their self-reported body size at age 10 and measured BMI in adulthood. After a median follow-up of 12.8 years, 33,460 individuals had developed type 2 diabetes and/or cardiovascular disease. We used Cox regression models to assess the associations of body size categories with disease incidence. RESULTS: Individuals with low body size in childhood and high body size in adulthood had the highest risk of type 2 diabetes (HR 4.73; 95% CI 4.50, 4.99), compared to those with average body size in both childhood and adulthood. This was significantly higher than the risk in those with high body size in both childhood and adulthood (HR 4.05; 95% CI 3.84, 4.26). By contrast, cardiovascular disease risk was determined by adult body size, irrespective of childhood body size. CONCLUSIONS/INTERPRETATION: Low body size in childhood exacerbates the risk of type 2 diabetes associated with adult obesity but not the risk of cardiovascular disease. Thus, promoting healthy weight management from childhood to adulthood, among lean children, is crucial.

Abdominal Obesity Genetic Variants Predict Waist Circumference Regain After Weight Loss.

Although many individuals are able to achieve weight loss, maintaining this loss over time is challenging. We aimed to study whether genetic predisposition to general or abdominal obesity predicts weight regain after weight loss. We examined the associations between genetic risk scores for higher BMI and higher waist-to-hip ratio adjusted for BMI (WHRadjBMI) with changes in weight and waist circumference up to 3 years after a 1-year weight loss program in participants (n = 822 women, n = 593 men) from the Look AHEAD (Action for Health in Diabetes) study who had lost ≥3% of their initial weight. Genetic predisposition to higher BMI or WHRadjBMI was not associated with weight regain after weight loss. However, the WHRadjBMI genetic score did predict an increase in waist circumference independent of weight change. To conclude, a genetic predisposition to higher WHRadjBMI predicts an increase in abdominal obesity after weight loss, whereas genetic predisposition to higher BMI is not predictive of weight regain. These results suggest that genetic effects on abdominal obesity may be more pronounced than those on general obesity during weight regain. ARTICLE HIGHLIGHTS: Nearly all individuals who intentionally lose weight experience weight regain. Individuals with a higher genetic risk for abdominal adiposity experience increased regain in waist circumference after weight loss. Genetic predisposition to higher BMI does not predict weight regain after weight loss.

Nanopore sequencing reveals methylation changes associated with obesity in circulating cell-free DNA from Göttingen Minipigs.

Profiling of circulating cell-free DNA (cfDNA) by tissue-specific base modifications, such as 5-methylcytosines (5mC), may enable the monitoring of ongoing pathophysiological processes. Nanopore sequencing allows genome-wide 5mC detection in cfDNA without bisulphite conversion. The aims of this study were: i) to find differentially methylated regions (DMRs) of cfDNA associated with obesity in Göttingen minipigs using Nanopore sequencing, ii) to validate a subset of the DMRs using methylation-specific PCR (MSP-PCR), and iii) to compare the cfDNA DMRs with those from whole blood genomic DNA (gDNA). Serum cfDNA and gDNA were obtained from 10 lean and 7 obese Göttingen Minipigs both with experimentally induced myocardial infarction and sequenced using Oxford Nanopore MinION. A total of 1,236 cfDNA DMRs (FDR<0.01) were associated with obesity. In silico analysis showed enrichment of the adipocytokine signalling, glucagon signalling, and cellular glucose homoeostasis pathways. A strong cfDNA DMR was discovered in PPARGC1B, a gene linked to obesity and type 2 diabetes. The DMR was validated using MSP-PCR and correlated significantly with body weight (P < 0.05). No DMRs intersected between cfDNA and gDNA, suggesting that cfDNA originates from body-wide shedding of DNA. In conclusion, nanopore sequencing detected differential methylation in minute quantities (0.1-1 ng/µl) of cfDNA. Future work should focus on translation into human and comparing 5mC from somatic tissues to pinpoint the exact location of pathology.

Oxford nanopore sequencing can reveal changes in methylation patterns associated with obesity in minute quantities of cell-free DNA from serum.Bisulphite conversion and methylation-specific PCR can be used to validate differentially methylated regions in cell-free DNA.A differentially methylated region in an intronic region of the PPARGC1B gene was found associated with obesity.Differentially methylated regions in cell-free DNA could be useful as early risk markers of certain diseases and pathologies.

The Arg82Cys Polymorphism of the Protein Nepmucin Implies a Role in HDL Metabolism.

Context: Blood lipid levels are linked to the risk of cardiovascular disease and regulated by genetic factors. A low-frequency polymorphism Arg82Cys (rs72836561) in the membrane protein nepmucin, encoded by CD300LG, is associated with lower fasting concentration of high-density lipoprotein cholesterol (HDLc) and higher fasting triglycerides. However, whether the variant is linked to postprandial lipids and glycemic status remains elusive. Objective: Here, we augment the genetic effect of Arg82Cys on fasting plasma concentrations of HDL subclasses, postprandial lipemia after a standardized high-fat meal, and glycemic status to further untangle its role in HDL metabolism. Methods: We elucidated fasting associations with HDL subclasses in a population-based cohort study (Oxford BioBank, OBB), including 4522 healthy men and women. We investigated fasting and postprandial consequences on HDL metabolism in recall-by-genotype (RbG) studies (fasting: 20 carrier/20 noncarrier; postprandial: 7 carrier/17 noncarrier), and shed light on the synergistic interaction with glycemic status. Results: A lower fasting plasma concentration of cholesterol in large HDL particles was found in healthy male carriers of the Cys82 polymorphism compared to noncarriers, both in the OBB (P = .004) and RbG studies (P = .005). In addition, the Cys82 polymorphism was associated with low fasting plasma concentrations of ApoA1 (P = .008) in the OBB cohort. On the contrary, we did not find differences in postprandial lipemia or 2-hour plasma glucose levels. Conclusion: Taken together, our results indicate an association between the Arg82Cys variant and a lower concentration of HDL particles and HDLc, especially in larger HDL subclasses, suggesting a link between nepmucin and HDLc metabolism or maturation.

Mendelian randomization suggests a bidirectional, causal relationship between physical inactivity and adiposity.

Physical inactivity and increased sedentary time are associated with excess weight gain in observational studies. However, some longitudinal studies indicate reverse causality where weight gain leads to physical inactivity and increased sedentary time. As observational studies suffer from reverse causality, it is challenging to assess the true causal directions. Here, we assess the bidirectional causality between physical inactivity, sedentary time, and adiposity by bidirectional Mendelian randomization analysis. We used results from genome-wide association studies for accelerometer-based physical activity and sedentary time in 91,105 individuals and for body mass index (BMI) in 806,834 individuals. We implemented Mendelian randomization using CAUSE method that accounts for pleiotropy and sample overlap using full genome-wide data. We also applied inverse variance-weighted, MR-Egger, weighted median, and weighted mode methods using genome-wide significant variants only. We found evidence of bidirectional causality between sedentary time and BMI: longer sedentary time was causal for higher BMI [beta (95% CI) from CAUSE method: 0.11 (0.02, 0.2), p = 0.02], and higher BMI was causal for longer sedentary time (0.13 (0.08, 0.17), p = 6.3 x 10-4). Our analyses suggest that higher moderate and vigorous physical activity are causal for lower BMI (moderate: -0.18 (-0.3,-0.05), p = 0.006; vigorous: -0.16 (-0.24,-0.08), p = 3.8 × 10-4), but indicate that the association between higher BMI and lower levels of physical activity is due to horizontal pleiotropy. The bidirectional, causal relationship between sedentary time and BMI suggests that decreasing sedentary time is beneficial for weight management, but also that targeting adiposity may lead to additional health benefits by reducing sedentary time.

Association of milk intake with hay fever, asthma, and lung function: a Mendelian randomization analysis.

BACKGROUND: Previous observational studies have indicated a protective effect of drinking milk on asthma and allergy. In Mendelian Randomization, one or more genetic variants are used as unbiased markers of exposure to examine causal effects. We examined the causal effect of milk intake on hay fever, asthma, forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) by using the lactase rs4988235 genotype associated with milk intake. METHODS: We performed a Mendelian Randomization study including 363,961 participants from the UK Biobank. RESULTS: Observational analyses showed that self-reported milk-drinkers vs. non-milk drinkers had an increased risk of hay fever: odds ratio (OR) = 1.36 (95% CI 1.32, 1.40, p < 0.001), asthma: OR = 1.33 (95% CI 1.38, 1.29, p < 0.001), yet a higher FEV1: ß = 0.022 (SE = 0.004, p < 0.001) and FVC: ß = 0.026 (SE = 0.005, p < 0.001). In contrast, genetically determined milk-drinking vs. not drinking milk was associated with a lower risk of hay fever: OR = 0.791 (95% CI 0.636, 0.982, p = 0.033), and asthma: OR = 0.587 (95% CI 0.442, 0.779, p = 0.001), and lower FEV1: ß = - 0.154 (standard error, SE = 0.034, p < 0.001) liter, and FVC: ß = - 0.223 (SE = 0.034, p < 0.001) liter in univariable MR analyses. These results were supported by multivariable Mendelian randomization analyses although not statistically significant. CONCLUSIONS: As opposed to observational results, genetic association findings indicate that drinking milk has a protective effect on hay fever and asthma but may also have a negative effect on lung function. The results should be confirmed in other studies before any recommendations can be made.

Do gene-environment interactions have implications for the precision prevention of type 2 diabetes?

The past decades have seen a rapid global rise in the incidence of type 2 diabetes. This surge has been driven by diabetogenic environmental changes that may act together with a genetic predisposition to type 2 diabetes. It is possible that there is a synergistic gene-environment interaction, where the effects of the diabetogenic environment depend on the genetic predisposition to type 2 diabetes. Randomised trials have shown that it is possible to delay, or even prevent the development of type 2 diabetes in individuals at elevated risk through behavioural modification, focusing on weight loss, physical activity and diet. There is wide heterogeneity between individuals regarding the effectiveness of these interventions, which could, in part, be due to genetic differences. However, the studies of gene-environment interactions performed thus far suggest that behavioural modifications appear equally effective in reducing the incidence of type 2 diabetes from the stage of impaired glucose tolerance, regardless of the known underlying genetic predisposition. Recent studies suggest that there may be several subtypes of type 2 diabetes, which give new opportunities for gaining insight into gene-environment interactions. At present, the role of gene-environment interactions in the development of type 2 diabetes remains unclear. With many puzzle pieces missing in the general picture of type 2 diabetes development, the available evidence of gene-environment interactions is not ready for translation to individualised type 2 diabetes prevention based on genetic profiling.

Genetic Predictors of Change in Waist Circumference and Waist-to-Hip Ratio With Lifestyle Intervention: The Trans-NIH Consortium for Genetics of Weight Loss Response to Lifestyle Intervention.

Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with waist circumference (WC) and waist-to-hip ratio (WHR) adjusted for BMI (WCadjBMI and WHRadjBMI), but it remains unclear whether these SNPs relate to change in WCadjBMI or WHRadjBMI with lifestyle intervention for weight loss. We hypothesized that polygenic scores (PS) comprised of 59 SNPs previously associated with central adiposity would predict less of a reduction in WCadjBMI or WHRadjBMI at 8-10 weeks in two lifestyle intervention trials, NUGENOB and DiOGenes, and at 1 year in five lifestyle intervention trials, Look AHEAD, Diabetes Prevention Program, Diabetes Prevention Study, DIETFITS, and PREDIMED-Plus. One-SD higher PS related to a smaller 1-year change in WCadjBMI in the lifestyle intervention arms at year 1 and thus predicted poorer response (ß = 0.007; SE = 0.003; P = 0.03) among White participants overall and in White men (ß = 0.01; SE = 0.004; P = 0.01). At average weight loss, this amounted to 0.20-0.28 cm per SD. No significant findings emerged in White women or African American men for the 8-10-week outcomes or for WHRadjBMI. Findings were heterogeneous in African American women. These results indicate that polygenic risk estimated from these 59 SNPs relates to change in WCadjBMI with lifestyle intervention, but the effects are small and not of sufficient magnitude to be clinically significant.

Longitudinal and cross-sectional associations of adherence to 24-hour movement guidelines with cardiometabolic risk.

This study aimed to examine (1) adherence to 24 h movement guidelines over a 2 years follow-up in children aged 6-8 years and (2) association of this adherence with cardiometabolic risk factors. Physical activity and sleep were assessed by a monitor combining heart rate and accelerometry measurements. Screen time was reported by the parents. Body fat percentage, waist circumference, blood glucose, serum insulin, plasma lipids, and blood pressure were assessed, and a cardiometabolic risk score was calculated using z-scores. Children were classified as meeting the guidelines if they had on average ≥60 min/day of moderate-to-vigorous physical activity during the valid days; ≤120 min/day of screen time; and 9-11 h/day of sleep. In total, 485 children had valid data at baseline or at 2 years follow-up. Analyses were conducted using adjusted logistic and linear regression models. Most children adhered to the 24 h movement guidelines at baseline, but the adherence decreased over the 2 years follow-up. Meeting physical activity guidelines individually, or in combination with screen time and/or sleep, was longitudinally associated with a lower cardiometabolic risk score, insulin and waist circumference, and cross-sectionally additionally with lower diastolic blood pressure and higher high-density lipoprotein cholesterol. However, these associations became statistically non-significant after adjustment for body fat. In conclusion, meeting 24 h movement guidelines at baseline increases the odds of meeting them at 2 years follow-up in school-aged children. Furthermore, meeting 24 h movement guidelines is associated with lower levels of cardiometabolic risk factors, but these associations are partly explained by lower body fat. Thus, promoting movement behaviors, especially physical activity, and healthy weight in early childhood is important in supporting cardiometabolic health in children.

Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits.

Psychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from 5 ancestry groups. In the combined meta-analyses of Stages 1 and 2, we identified 59 loci (p value <5e-8), including nine novel BP loci. The novel associations were observed mostly with pulse pressure, with fewer observed with mean arterial pressure. Five novel loci were identified in African ancestry, and all but one showed patterns of interaction with at least one psychosocial factor. Functional annotation of the novel loci supports a major role for genes implicated in the immune response (PLCL2), synaptic function and neurotransmission (LIN7A, PFIA2), as well as genes previously implicated in neuropsychiatric or stress-related disorders (FSTL5, CHODL). These findings underscore the importance of considering psychological and social factors in gene discovery for BP, especially in non-European populations.

Composite trait Mendelian randomization reveals distinct metabolic and lifestyle consequences of differences in body shape.

Obesity is a major risk factor for a wide range of cardiometabolic diseases, however the impact of specific aspects of body morphology remains poorly understood. We combined the GWAS summary statistics of fourteen anthropometric traits from UK Biobank through principal component analysis to reveal four major independent axes: body size, adiposity, predisposition to abdominal fat deposition, and lean mass. Mendelian randomization analysis showed that although body size and adiposity both contribute to the consequences of BMI, many of their effects are distinct, such as body size increasing the risk of cardiac arrhythmia (b = 0.06, p = 4.2 ∗ 10-17) while adiposity instead increased that of ischemic heart disease (b = 0.079, p = 8.2 ∗ 10-21). The body mass-neutral component predisposing to abdominal fat deposition, likely reflecting a shift from subcutaneous to visceral fat, exhibited health effects that were weaker but specifically linked to lipotoxicity, such as ischemic heart disease (b = 0.067, p = 9.4 ∗ 10-14) and diabetes (b = 0.082, p = 5.9 ∗ 10-19). Combining their independent predicted effects significantly improved the prediction of obesity-related diseases (p < 10-10). The presented decomposition approach sheds light on the biological mechanisms underlying the heterogeneity of body morphology and its consequences on health and lifestyle.

Epigenetic rewiring of skeletal muscle enhancers after exercise training supports a role in whole-body function and human health.

OBJECTIVES: Regular physical exercise improves health by reducing the risk of a plethora of chronic disorders. We hypothesized that endurance exercise training remodels the activity of gene enhancers in skeletal muscle and that this remodeling contributes to the beneficial effects of exercise on human health. METHODS AND RESULTS: By studying changes in histone modifications, we mapped the genome-wide positions and activities of enhancers in skeletal muscle biopsies collected from young sedentary men before and after 6 weeks of endurance exercise. We identified extensive remodeling of enhancer activities after exercise training, with a large subset of the remodeled enhancers located in the proximity of genes transcriptionally regulated after exercise. By overlapping the position of enhancers with genetic variants, we identified an enrichment of disease-associated genetic variants within the exercise-remodeled enhancers. CONCLUSION: Our data provide evidence of a functional link between epigenetic rewiring of enhancers to control their activity after exercise training and the modulation of disease risk in humans.

Abdominal and gluteofemoral fat depots show opposing associations with postprandial lipemia.

BACKGROUND: High postprandial lipemia is associated with increased risk of cardiovascular disease, independently of fasting lipid concentrations. Abdominal and gluteofemoral fat depots handle lipoproteins differently, which could affect postprandial lipemia and contribute to the relation between abdominal fat distribution and cardiovascular disease risk. OBJECTIVES: We aimed to study the influences of higher abdominal compared with gluteofemoral fat on postprandial lipemia after a high-fat meal in individuals with obesity. METHODS: A total of 755 adults with obesity from a randomized controlled trial in 7 European countries consumed a liquid high-fat meal. Concentrations of triglycerides (TG), glycerol, free fatty acids, and the cholesterol component of remnant-like particles (RLP), LDL, and HDL were measured postprandially for 3 h. Associations of waist circumference (WC), hip circumference (HC), and waist-hip ratio (WHR) with changes in postprandial lipid concentrations, adjusted for fasting concentrations and BMI, were examined using linear regression models. To assess whether the association of WHR with postprandial lipemia could be causal, we performed instrumental variable analyses using a genetic score of 442 variants known to be associated with WHR adjusted for BMI in 2-stage least-squares regression models. RESULTS: WHR was associated with higher TG and RLP cholesterol concentrations, independent of fasting lipid concentrations and BMI. Instrumental variable analyses suggested that the associations of WHR with postprandial TG (ß = 0.038 µmol/L*min, SE = 0.019 µmol/L*min, P = 0.044) and RLP cholesterol concentrations (ß = 0.059 mmol/L, SE = 0.025 mmol/L, P = 0.020) may be causal. WC and HC showed opposite effects: higher WC was associated with higher TG and RLP cholesterol concentrations whereas higher HC was associated with lower concentrations. CONCLUSIONS: Our results suggest that higher fat deposition abdominally versus gluteofemorally may be causally associated with elevated postprandial lipemia after a high-fat meal, independent of fasting lipid concentrations and BMI. Furthermore, higher abdominal and gluteofemoral fat depots show opposing effects on postprandial lipemia.This trial was registered at www.isrctn.com as ISRCTN25867281.

The Genetic Basis of Hypertriglyceridemia.

PURPOSE OF REVIEW: Hypertriglyceridemia is a common dyslipidemia associated with an increased risk of cardiovascular disease and pancreatitis. Severe hypertriglyceridemia may sometimes be a monogenic condition. However, in the vast majority of patients, hypertriglyceridemia is due to the cumulative effect of multiple genetic risk variants along with lifestyle factors, medications, and disease conditions that elevate triglyceride levels. In this review, we will summarize recent progress in the understanding of the genetic basis of hypertriglyceridemia. RECENT FINDINGS: More than 300 genetic loci have been identified for association with triglyceride levels in large genome-wide association studies. Studies combining the loci into polygenic scores have demonstrated that some hypertriglyceridemia phenotypes previously attributed to monogenic inheritance have a polygenic basis. The new genetic discoveries have opened avenues for the development of more effective triglyceride-lowering treatments and raised interest towards genetic screening and tailored treatments against hypertriglyceridemia. The discovery of multiple genetic loci associated with elevated triglyceride levels has led to improved understanding of the genetic basis of hypertriglyceridemia and opened new translational opportunities.

Do genetic risk scores for childhood adiposity operate independent of BMI of their mothers?

OBJECTIVES: Genetic predisposition and maternal body mass index (BMI) are risk factors for childhood adiposity, defined by either BMI or overweight. We aimed to investigate whether childhood-specific genetic risk scores (GRSs) for adiposity-related traits are associated with childhood adiposity independent of maternal BMI, or whether the associations are modified by maternal BMI. METHODS: We constructed a weighted 26-SNP child BMI-GRS and a weighted 17-SNP child obesity-GRS in overall 1674 genotyped children within the Danish National Birth Cohort. We applied a case-cohort (N = 1261) and exposure-based cohort (N = 912) sampling design. Using logistic regression models we estimated associations of the GRSs and child overweight at age 7 years and examined if the GRSs influence child adiposity independent of maternal BMI (per standard deviation units). RESULTS: In the case-cohort design analysis, maternal BMI and the child GRSs were associated with increased odds for childhood overweight [OR for maternal BMI: 2.01 (95% CI: 1.86; 2.17), OR for child BMI-GRS: 1.56 (95% CI: 1.47; 1.66), and OR for child obesity-GRS 1.46 (95% CI: 1.37; 1.54)]. Adjustment for maternal BMI did not change the results, and there were no significant interactions between the GRSs and maternal BMI. However, in the exposure-based cohort design analysis, significant interactions between the child GRSs and maternal BMI on child overweight were observed, suggesting 0.85-0.87-fold attenuation on ORs of child overweight at higher values of maternal BMI and child GRS. CONCLUSION: GRSs for childhood adiposity are strongly associated with childhood adiposity even when adjusted for maternal BMI, suggesting that the child-specific GRSs and maternal BMI contribute to childhood overweight independent of each other. However, high maternal BMI may attenuate the effects of child GRSs in children.

Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure.

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 Pjoint < 5 × 10-8), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (Pint < 5 × 10-8). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (Pint = 2 × 10-6). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (Pint < 10-3). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.