Common genetic variants associated with obesity in an African-American and Hispanic/Latino population

Clinical Genetic Testing for Atrial Fibrillation: Are We There Yet?

Important progress has been made toward unravelling the complex genetics underlying atrial fibrillation (AF). Initial studies were aimed to identify monogenic causes; however, it has become increasingly clear that the most common predisposing genetic substrate for AF is polygenic. Despite intensive investigations, there is robust evidence for rare variants for only a limited number of genes and cases. Although the current yield for genetic testing in early onset AF might be modest, there is an increasing appreciation that genetic culprits for potentially life-threatening ventricular cardiomyopathies and channelopathies might initially present with AF. The potential clinical significance of this recognition is highlighted by evidence that suggests that identification of a pathogenic or likely pathogenic rare variant in a patient with early onset AF is associated with an increased risk of death. These findings suggest that it might be warranted to screen patients with early onset AF for these potentially more sinister cardiac conditions. Beyond facilitating the early identification of genetic culprits associated with potentially malignant phenotypes, insight into underlying AF genetic substrates might improve the selection of patients for existing therapies and guide the development of novel ones. Herein, we review the evidence that links genetic factors to AF, then discuss an approach to using genetic testing for early onset AF patients in the present context, and finally consider the potential value of genetic testing in the foreseeable future. Although further work might be necessary before recommending uniform integration of genetic testing in cases of early onset AF, ongoing research increasingly highlights its potential contributions to clinical care.

Body mass index and waist circumference trajectories across the life course and birth cohorts, 1996-2015 Malaysia: sex and ethnicity matter

OBJECTIVE

The global obesity epidemic remains a significant threat to public health and the economy. Age-period-cohort (APC) analysis is one method to model the trajectory of obesity. However, there is scarce published evidence of such analyses among the South East Asian population. This study aims to explore the sex and ethnic variations of BMI and waist circumference trajectories over time among non-institutionalized Malaysian adults aged 18 to 80 years.

METHODS

Data from four population-based National Health and Morbidity Surveys conducted in 1996, 2006, 2010, and 2015 were pooled. Hierarchical Age-Period-Cohort (HAPC) analysis explored the trajectories of BMI and waist circumference across the life course and birth cohorts by sex and ethnicity. These models assumed no period effect.

RESULTS

Generally, BMI and waist circumference trajectories increased across age and birth cohorts. These trajectories varied by sex and ethnicity. Females have more profound increasing BMI and waist circumference trajectories than their male counterparts as they age and as cohort recency increases. Chinese have less profound BMI and waist circumference increases across the life course and birth cohorts than other ethnic groups.

CONCLUSIONS

The profound increasing cohort trajectories of obesity, regardless of sex and ethnicity, are alarming. Future studies should focus on identifying factors associated with the less profound cohort effect among the Chinese to reduce the magnitude of trajectories in obesity, particularly among future generations.

How does obesity affect mortality through blood pressure and blood glucose in Chinese and US citizens? Insights from a causal mediation analysis of two large cohorts

Background

Obesity, which has reached the scale of a global pandemic, is a leading cause of premature death. It is unclear to what extent its effect on mortality was driven by blood pressure or glucose levels in people of different ethnicities.

Methods

We conducted a causal mediation analysis to estimate the mediation effect of blood pressure and glucose between body mass index (BMI) or waist-hip ratio (WHR) on mortality based on data from the China Kadoorie Biobank (CKB) (n = 458 385) and US National Health and Nutrition Examination Survey (NHANES) (1999-2008, n = 20 726).

Results

The WHR's effect on mortality was mediated by blood pressure and glucose in the CKB data set by 38.7% (95% confidence interval (CI) = 34.1, 43.2) and 36.4% (95% CI = 31.6, 42.8), whereas in NHANES by 6.0% (95% CI = 2.3, 8.3) and 11.2% (95% CI = 4.7, 22.7), respectively. For associations between BMI and mortality in subjects with overweight or obesity, the mediator proportion of blood glucose and pressure was 49.4% (95% CI = 40.1, 62.5) and 16.9% (95% CI = 13.6, 22.9) in CKB and 9.10% (95% CI = 2.2, 25.9) and 16.7% (95% CI = 7.3, 49.0) in NHANES, respectively. We stratified the patients by their blood glucose, blood pressure level, or both into four groups. The effect of WHR on mortality was comparable across subgroups in either cohort. The associations between BMI and mortality were stronger in patients with higher blood pressure in CKB (P = 0.011) and blood glucose in NHANES (P = 0.035) in patients with overweight and obesity.

Conclusions

The relationship between WHR and mortality in the CKB data set was potentially caused by blood pressure and glucose to a much greater extent than in the NHANES one. The effect of BMI influenced by blood pressure was significantly higher among Chinese individuals with overweight and obesity. These results implicate a different intervention strategy is required for blood pressure and blood glucose in China and US to prevent obesity and obesity-related premature death.

Racial and Ethnic Disparities in Diabetes Clinical Care and Management: A Narrative Review

Diabetes affects nearly 37 million Americans, with disproportionately higher disease burden amongst those from minoritized communities. The result of this is greater rates of diabetic complications and mortality. To close this gap in care, it is important to assess the differences in both diagnosis and care between White and ethnic/racial minoritized persons with diabetes. The purpose of this narrative review is to explore this further by assessing the differences in diagnosis, management, diabetes education, and complications.

Risk variants of obesity associated genes demonstrate BMI raising effect in a large cohort

Obesity is highly polygenic disease where several genetic variants have been reportedly associated with obesity in different ethnicities of the world. In the current study, we identified the obesity risk or protective association and BMI raising effect of the minor allele of adiponectin, C1Q and collagen domain containing (ADIPOQ), cholesteryl ester transfer protein (CEPT), FTO alpha-ketoglutarate dependent dioxygenase (FTO), leptin (LEP), and leptin receptor (LEPR) genes in a large cohort stratified into four BMI-based body weight categories i.e., normal weight, lean, over-weight, and obese. Based on selected candidate genetic markers, the genotyping of all study subjects was performed by PCR assays, and genotypes and allele frequencies were calculated. The minor allele frequencies (MAFs) of all genetic markers were computed for total and BMI-based body weight categories and compared with MAFs of global and South Asian (SAS) populations. Genetic associations of variants with obesity risk were calculated and BMI raising effect per copy of the minor allele were estimated. The genetic variants with higher MAFs in obese BMI group were; rs2241766 (G = 0.43), rs17817449 (G = 0.54), rs9939609 (A = 0.51), rs1421085 (C = 0.53), rs1558902 (A = 0.63), and rs1137101 (G = 0.64) respectively. All these variants were significantly associated with obesity (OR = 1.03–4.42) and showed a high BMI raising effect (β = 0.239–0.31 Kg/m²) per copy of the risk allele. In contrast, the MAFs of three variants were higher in lean-normal BMI groups; rs3764261 A = 0.38, rs9941349 T = 0.43, and rs7799039 G = 0.40–0.43). These variants showed obesity protective associations (OR = 0.68–0.76), and a BMI lowering effect per copy of the protective allele (β = -0.103–0.155 Kg/m²). The rs3764261 variant also showed significant and positive association with lean body mass (OR = 2.38, CI = 1.30–4.34). Overall, we report six genetic variants of ADIPOQ, FTO and LEPR genes as obesity-risk markers and a CETP gene variant as lean mass/obesity protective marker in studied Pakistani cohort.

Genetic and epigenetic nutritional interactions influencing obesity risk and adiposity outcomes

PURPOSE OF REVIEW

This article aims to critically overview the current interplay of genetic/epigenetic factors and several nutritional aspects influencing obesity susceptibility and adiposity outcomes for obesity management and weight status monitoring.

RECENT FINDINGS

Single nucleotide polymorphisms located in or near genes participating in energy homeostasis, fatty acid metabolism, appetite control, brain regulation, and thermogenesis have been associated with body composition measures (body weight, body mass index, waist circumference, body fat percentage, and visceral adipose tissue) depending on nutrient intakes, dietary patterns, and eating behaviors. Moreover, studies analyzing interactions between the epigenome and dietary intakes in relation to adiposity outcomes are reported. The main epigenetic mechanisms include methylation levels of promoter sequences, telomere length, and micro-ribonucleic acid expression profiles, whereas covalent histone modifications remain less studied.

SUMMARY

Exploring potential interactions between the genetic/epigenetic background and nutritional features is improving the current understanding of the obesity physiopathogenesis and the usefulness of translating this precision information in the clinical setting for weight gain prediction, the design of personalized nutrition therapies as well as individual responsiveness estimation to dietary advice. The analysis of further relationships between the genotype, the epigenotype and other precision markers including the gut microbiota and the metabolome is warranted.

The Impact of ACEs on BMI: An Investigation of the Genotype-Environment Effects of BMI

Adverse Childhood Experiences are stressful and traumatic events occurring before the age of eighteen shown to cause mental and physical health problems, including increased risk of obesity. Obesity remains an ongoing national challenge with no predicted solution. We examine a subset of the Healthy Nevada Project, focusing on a multi-ethnic cohort of 15,886 sequenced participants with recalled adverse childhood events, to study how ACEs and their genotype-environment interactions affect BMI. Specifically, the Healthy Nevada Project participants sequenced by the Helix Exome+ platform were cross-referenced to their electronic medical records and social health determinants questionnaire to identify: 1) the effect of ACEs on BMI in the absence of genetics; 2) the effect of genotype-environment interactions on BMI; 3) how these gene-environment interactions differ from standard genetic associations of BMI. The study found very strong significant associations between the number of adverse childhood experiences and adult obesity. Additionally, we identified fifty-five common and rare variants that exhibited gene-interaction effects including three variants in the CAMK1D gene and four variants in LHPP; both genes are linked to schizophrenia. Surprisingly, none of the variants identified with interactive effects were in canonical obesity-related genes. Here we show the delicate balance between genes and environment, and how the two strongly influence each other.

Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics

Multimorbidity is characterized by multidimensional complexity emerging from interactions between multiple diseases across levels of biological (including genetic) and environmental determinants and the complex array of interactions between and within cells, tissues and organ systems. Advances in spatial genomic research have led to an unprecedented expansion in our ability to link alterations in genome folding with changes that are associated with human disease. Studying disease-associated genetic variants in the context of the spatial genome has enabled the discovery of transcriptional regulatory programmes that potentially link dysregulated genes to disease development. However, the approaches that have been used have typically been applied to uncover pathological molecular mechanisms occurring in a specific disease-relevant tissue. These forms of reductionist, targeted investigations are not appropriate for the molecular dissection of multimorbidity that typically involves contributions from multiple tissues. In this perspective, we emphasize the importance of a whole-body understanding of multimorbidity and discuss how spatial genomics, when integrated with additional omic datasets, could provide novel insights into the molecular underpinnings of multimorbidity.

Interactions between Polygenic Risk Scores, Dietary Pattern, and Menarche Age with the Obesity Risk in a Large Hospital-Based Cohort

Obese Asians are more susceptible to metabolic diseases than obese Caucasians of the same body mass index (BMI). We hypothesized that the genetic variants associated with obesity risk interact with the lifestyles of middle-aged and elderly adults, possibly allowing the development of personalized interventions based on genotype. We aimed to examine this hypothesis in a large city hospital-based cohort in Korea. The participants with cancers, thyroid diseases, chronic kidney disease, or brain-related diseases were excluded. The participants were divided into case and control according to their BMI: ≥25 kg/m² (case; n = 17,545) and <25 kg/m² (control; n = 36,283). The genetic variants that affected obesity risk were selected using a genome-wide association study, and the genetic variants that interacted with each other were identified by generalized multifactor dimensionality reduction analysis. The selected genetic variants were confirmed in the Ansan/Ansung cohort, and polygenetic risk scores (PRS)−nutrient interactions for obesity risk were determined. A high BMI was associated with a high-fat mass (odds ratio (OR) = 20.71) and a high skeletal muscle-mass index (OR = 3.38). A high BMI was positively related to metabolic syndrome and its components, including lipid profiles, whereas the initial menstruation age was inversely associated with a high BMI (OR = 0.78). The best model with 5-SNPs included SEC16B_rs543874, DNAJC27_rs713586, BDNF_rs6265, MC4R_rs6567160, and GIPR_rs1444988703. The high PRS with the 5-SNP model was positively associated with an obesity risk of 1.629 (1.475–1.798) after adjusting for the covariates. The 5-SNP model interacted with the initial menstruation age, fried foods, and plant-based diet for BMI risk. The participants with a high PRS also had a higher obesity risk when combined with early menarche, low plant-based diet, and a high fried-food intake than in participants with late menarche, high plant-based diet, and low fried-food intake. In conclusion, people with a high PRS and earlier menarche age are recommended to consume fewer fried foods and a more plant-based diet to decrease obesity risk. This result can be applied to personalized nutrition for preventing obesity.