Predicting anthropometric and metabolic traits with a genetic risk score for obesity in a sample of Pakistanis

Forensic height estimation using polygenic score in Korean population

Height is known to be a classically heritable trait controlled by complex polygenic factors. Numerous height-associated genetic variants across the genome have been identified so far. It is also a representative of externally visible characteristics (EVC) for predicting appearance in forensic science. When biological evidence at a crime scene is deficient in identifying an individual, the examination of forensic DNA phenotyping using some genetic variants could be considered. In this study, we aimed to predict 'height', a representative forensic phenotype, by using a small number of genetic variants when short tandem repeat (STR) analysis is hard with insufficient biological samples. Our results not only replicated previous genetic signals but also indicated an upward trend in polygenic score (PGS) with increasing height in the validation and replication stages for both genders. These results demonstrate that the established SNP sets in this study could be used for height estimation in the Korean population. Specifically, since the PGS model constructed in this study targets only a small number of SNPs, it contributes to enabling forensic DNA phenotyping even at crime scenes with a minimal amount of biological evidence. To the best of our knowledge, this was the first study to evaluate a PGS model for height estimation in the Korean population using GWAS signals. Our study offers insight into the polygenic effect of height in East Asians, incorporating genetic variants from non-Asian populations.

Deciphering the Interplay between Genetic Risk Scores and Lifestyle Factors on Individual Obesity Predisposition

Obesity's variability is significantly influenced by the interplay between genetic and environmental factors. We aimed to integrate the combined impact of genetic risk score (GRSBMI) with physical activity (PA), sugar-sweetened beverages (SSB), wine intake, and eating habits score (EHS) on obesity predisposition risk. Adults' (n = 5824) data were analyzed for common obesity-related single nucleotide polymorphisms and lifestyle habits. The weighted GRSBMI was constructed and categorized into quartiles (Qs), and the adjusted multivariate logistic regression models examined the association of GRSBMI with obesity (BMI ≥ 30) and lifestyle factors. GRSBMI was significantly associated with obesity risk. Each GRSBMI unit was associated with an increase of 3.06 BMI units (p ≤ 0.0001). PA markedly reduced obesity risk across GRSBMI Qs. Inactive participants' (≥90 min/week) mean BMI was higher in GRSBMI Q3-Q4 compared to Q1 (p = 0.003 and p < 0.001, respectively). Scoring EHS ≥ median, SSBs (≥1 cup/day), and non-wine drinking were associated with higher BMI within all GRSBMI Qs compared to EHS < median, non-SSBs, and non-wine drinkers. Mean BMI was higher in GRSBMI Q4 compared to other quartiles (p < 0.0001) in non-wine drinkers and compared to Q1 for SSB's consumers (p = 0.07). A higher GRSBMI augmented the impact of lifestyle factors on obesity. The interplay between GRSBMI and modifiable lifestyle factors provides a tailored personalized prevention and treatment for obesity management.

Associations of Chinese visceral adiposity index and new-onset stroke in middle-aged and older Chinese adults: an observational study

BACKGROUND

Stroke represents the second most prevalent contributor to global mortality. The Chinese Visceral Adiposity Index (CVAI) serves as an established metric for assessing visceral adiposity in the Chinese population, exhibiting prognostic capabilities. This investigation aimed to explore the association of CVAI and new-onset stroke among middle-aged and older Chinese populations.

METHODS

The study employed data from the 2011 and 2018 China Health and Retirement Longitudinal Study (CHARLS) to assess the association of CVAI and the incidence of new-onset stroke. Utilizing a directed acyclic graph (DAG), 10 potential confounders were identified. Moreover, to explore the association between CVAI and new-onset stroke, three multifactor logistic regression models were constructed, accounting for the identified confounders and mitigating their influence on the findings.

RESULTS

The study comprised 7070 participants, among whom 417 (5.9%) experienced new-onset strokes. After controlling for confounding variables, regression analysis suggested that the new-onset stroke's highest risk was linked to the fourth quartile (Q4) of the CVAI, with an odds ratio (OR) of 2.33 and a 95% confidence interval (CI) of 1.67-3.28. The decision tree analysis demonstrated a heightened probability of new-onset stroke among hypertensive individuals with a CVAI equal to or greater than 83, coupled with a C-reactive protein level no less than 1.1 mg/l. Age seemed to have a moderating influence on the CVAI and new-onset stroke association, exhibiting a more prominent interaction effect in participants under 60 years.

CONCLUSIONS

In middle-aged and older Chinese populations, a linear relationship was discerned between CVAI and the probability of new-onset stroke. CVAI provides a predictive framework for stroke incidence in this demographic, laying the groundwork for more sophisticated risk prediction models that improve the precision and specificity of stroke risk evaluations.

The relationship of genetic risk score with cardiometabolic risk factors: a cross-sectional study

Background & aims

For more than eight decades, cardiovascular disease (CVD) has remained the leading cause of death in the world. CVD risk factors are multifaceted, with genetics and lifestyle both playing a role. The aim of this study was to investigate the association between a genetic profile risk score for obesity GRS and cardio-metabolic risk factors in overweight and obese women.

Methods

The current cross-sectional study was conducted on 391 overweight and obese women. The genetic risk score was created by combining three single nucleotide polymorphisms [MC4R (rs17782313), CAV-1 (rs3807992), and Cry-1 (rs2287161)]. Anthropometric measurements, blood pressure, and some blood parameters were measured by standard protocols.

Results

A significant association between the GRS and some of cardiometabolic risk factors variables such as body mass index (β = 0. 49, 95%CI = 0.22 to 0.76, p < 0.001), waist circumference (β = 0. 86, 95%CI = 0.18 to 1.54, p = 0.01), body fat mass (β = 0. 82, 95%CI = 0.25 to 1.39, p = 0.005), %body fat (β = 0. 44, 95%CI = 0.06 to 0.82, p = 0.02), and hs-CRP (β = 0.46, 95% CI = 0.14 to 0.78, p = 0.005) was observed in crude model. After adjustment for confounding factors (age, BMI, and physical activity), a significant positive association was observed between BMI (p = 0.004), WC (p = 0.02), body fat mass (p = 0.01), %BF (p = 0.01), hs-CRP (p = 0.009), and GRS. In addition, we discovered a significant negative association between the GRS and BMC (= -0.02, 95%CI = -0.05 to -0.001, p = 0.04). But other variables did not show any significant association with GRS among obese and overweight women.

Conclusion

We found a significant positive association between GRS, including MC4R (rs17782313), CAV-1 (rs3807992), and Cry-1 (rs2287161) and cardiometabolic risk factors among overweight and obese Iranian women.