Alcohol consumption and its interaction with adiposity-associated genetic variants in relation to subsequent changes in waist circumference and body weight

Drinking Habits and Physical Activity Interact and Attenuate Obesity Predisposition of TMEM18 Polymorphisms Carriers

The transmembrane protein 18 (TMEM18) gene plays a central and peripheral role in weight regulation. TMEM18 genetic polymorphisms have been identified as an important risk factor for obesity, depending on ethnic population and age. This research aimed to study the association of common TMEM18 polymorphisms with obesity and their interactions with modifiable factors, namely drinking habits (sugar-sweetened beverages (SSBs), flavored water and wine) and physical activity (PA) in the Israeli population. Adults (n = 3089) were analyzed for common TMEM18 polymorphisms and lifestyle and nutrition habits were obtained from questionnaires using adjusted (age, sex) binary logistic regression models. TMEM18 rs939583 and rs1879523 were significantly associated with increased obesity risk (OR = 1.35, 95% CI (1.17−1.57) and OR = 1.66, 95% CI (1.29−2.15), respectively). TMEM18 rs939583 interacted with consumption of 1−3 weekly glasses of wine and PA to attenuate obesity risk (OR = 0.82 95% CI (0.74−0.9; p < 0.001) and OR = 0.74 95% CI (0.68−0.8), respectively), while physical inactivity, SSBs and flavored water consumption significantly enhanced obesity risk (OR = 1.54 95% CI (1.41−1.67), OR = 1.31 95% CI (1.14−1.51) and OR = 1.35 95% CI (1.13−1.62), respectively). PA duration was significantly associated with a lower BMI for rs939583 risk carriers, with a PA cutoff of >30 min/week (p = 0.005) and >90 min/week (p = 0.01). Common TMEM18 SNPs were significantly linked with adult obesity risk and interacted with modifiable lifestyle factors.

In the context of the triple burden of malnutrition: A systematic review of gene-diet interactions and nutritional status

Genetic background interacts with dietary components to modulate nutritional health status. This study aimed to review the evidence for gene-diet interactions in all forms of malnutrition. A comprehensive systematic literature search was conducted through April 2021 to identify observational and intervention studies reporting the effects of gene-diet interactions in over-nutrition, under-nutrition and micronutrient status. Risk of publication bias was assessed using the Quality Criteria Checklist and a tool specifically designed for gene-diet interaction research. 167 studies from 27 populations were included. The majority of studies investigated single nucleotide polymorphisms (SNPs) in overnutrition (n = 158). Diets rich in whole grains, vegetables, fruits and low in total and saturated fats, such as Mediterranean and DASH diets, showed promising effects for reducing obesity risk among individuals who had higher genetic risk scores for obesity, particularly the risk alleles carriers of FTO rs9939609, rs1121980 and rs1421085. Other SNPs in MC4R, PPARG and APOA5 genes were also commonly studied for interaction with diet on overnutrition though findings were inconclusive. Only limited data were found related to undernutrition (n = 1) and micronutrient status (n = 9). The findings on gene-diet interactions in this review highlight the importance of personalized nutrition, and more research on undernutrition and micronutrient status is warranted.

Synergizing Mouse and Human Studies to Understand the Heterogeneity of Obesity

Obesity is routinely considered as a single disease state, which drives a "one-size-fits-all" approach to treatment. We recently convened the first annual University of North Carolina Interdisciplinary Nutrition Sciences Symposium to discuss the heterogeneity of obesity and the need for translational science to advance understanding of this heterogeneity. The symposium aimed to advance scientific rigor in translational studies from animal to human models with the goal of identifying underlying mechanisms and treatments. In this review, we discuss fundamental gaps in knowledge of the heterogeneity of obesity ranging from cellular to population perspectives. We also advocate approaches to overcoming limitations in the field. Examples include the use of contemporary mouse genetic reference population models such as the Collaborative Cross and Diversity Outbred mice that effectively model human genetic diversity and the use of translational models that integrate -omics and computational approaches from pre-clinical to clinical models of obesity. Finally, we suggest best scientific practices to ensure strong rigor that will allow investigators to delineate the sources of heterogeneity in the population with obesity. Collectively, we propose that it is critical to think of obesity as a heterogeneous disease with complex mechanisms and etiologies, requiring unique prevention and treatment strategies tailored to the individual.

Assessment of a proposed BMI formula in predicting body fat percentage among Filipino young adults

Body mass index (BMI), while routinely used in evaluating adiposity, cannot distinguish between fat and lean mass, and thus can misclassify weight status particularly among athletic, physically active, and tall- and short-statured individuals, whose lean-to-fat ratios and body proportions vary considerably from average individuals. Believing that the traditional BMI formula divides weight by too much with short people and by too little with tall people, University of Oxford professor L. N. Trefethen proposed a modified formula in computing BMI. This study was conducted among a sample of Filipino young adults (n = 190) to assess the performance of the modified BMI formula against the traditional one in: (1) predicting body fat percentage (%BF) measured using bioelectric impedance analysis, and (2) diagnosing overweight/obesity. Using robust polynomial regression analysis (covariates: age, waist circumference, smoking history and alcohol intake), the BMI quadratic models had the highest adjusted R2 and the lowest AIC and BIC for both sexes compared to the linear models. The AuROCs of the traditional BMI were higher than those of the proposed BMI, albeit nonsignificant. In conclusion, both traditional and modified BMIs significantly predicted %BF, as well as adequately discriminated between %BF-defined normal and overweight-obese states using optimal BMI cutoff values.

Gene-obesogenic environment interactions on body mass indices for older black and white men and women from the Health and Retirement Study

BACKGROUND

Gene-obesogenic environment interactions influence body mass index (BMI) across the life course; however, limited research examines how these interactions may differ by race and sex.

METHODS

Utilizing mixed-effects models, we examined the interaction effects of a polygenic risk score (PGS) generated from BMI-associated single-nucleotide polymorphisms, and environmental factors, including age, physical activity, alcohol intake, and childhood socioeconomic status on measured longitudinal BMI from the Health and Retirement Study (HRS). HRS is a population representative survey of older adults in the United States. This study used a subsample of genotyped Black (N = 1796) and White (N = 4925) men and women (50-70 years) with measured BMI.

RESULTS

Higher PGS was associated with higher BMI. The association between PGS and BMI weakened as individuals aged among White men (Pinteraction = 0.0383) and White women (Pinteraction = 0.0514). The mean BMI difference between the 90th and 10th PGS percentile was 4.25 kg/m2 among 50-year-old White men, and 3.11 kg/m2 among the 70 years old's, i.e., a 1.14 kg/m2 (95% CI: -0.27, 2.82) difference. The difference among 50- and 70-year-old White women was 1.34 kg/m2 (95% CI: 0.09, 2.60). In addition, the protection effect of physical activity was stronger among White women with higher PGS (Pinteraction = 0.0546). Vigorous physical activity (compared with never) was associated with 1.66 kg/m2 (95% CI: 1.06, 2.29) lower mean BMI among those in the 90th PGS percentile, compared with 0.83 kg/m2 (95% CI: 0.37, 1.29) lower among those in the 10th PGS percentile. Interactions were also observed between both PGS and alcohol intake among White men (Pinteraction = 0.0034) and women (Pinteraction = 0.0664) and Black women (Pinteraction = 0.0108), and PGS and childhood socioeconomic status among White women (Pinteraction = 0.0007).

CONCLUSIONS

Our findings reinforce the importance of physical activity among those with an elevated genetic risk; additionally, other detected interactions may underscore the influence of broader social environments on obesity-promoting genes.

Association between DNA damage, dietary patterns, nutritional status, and non-communicable diseases in coal miners

Several negative health effects have been associated with environmental pollution. Coal mining activities are related to DNA damage. However, the impact of lifestyle as well as environmental exposure must be considered when evaluating the extent of DNA damage. The aim of this cross-sectional study was to analyze nutritional status, dietary patterns, and the prevalence of non-communicable diseases (CNCDs) among coal miners as well as to investigate the correlation of these variables with DNA damage. We used a questionnaire to assess demographics, health, and dietary habits. The nutritional status was measured in terms of BMI (body mass index) and DNA damage was assessed by the comet assay. The sample population was composed of 158 coal miners from the largest coal mining company in South of Brazil, and majority of them were classified as overweight (51.3%) or obese (28.5%). Hypertension was the most common CNCD (50.6%) and a majority of these workers consumed all groups of foods three or more times a week. There was a significant positive correlation between BMI and DNA damage (r = 0.1646, p = 0.04) and this association was stronger (r = 0.2556, p = 0.04) in coal miners with some CNCD. There was no significant correlation between dietary patterns and DNA damage in coal miners. These results suggest that the nutritional status and CNCD increase the extent of DNA damage in coal miners. Since this population is at high occupational risk, specific strategies should be designed to improve the health of these workers, aiming to achieve health equity.