The genetic influences on bone mass likely change throughout the life span, but most genetic studies of bone mass regulation have focused on adults. There is, however, a growing awareness of the importance of genes influencing the acquisition of bone mass during childhood on lifelong bone health. The present investigation examines genetic influences on childhood bone mass by estimating the residual heritabilities of different measures of second metacarpal bone mass in a sample of 600 10-year-old participants from 144 families in the Fels Longitudinal Study. Bivariate quantitative genetic analyses were conducted to estimate genetic correlations between cortical bone mass measures, and measures of bone growth and development. Using a maximum likelihood-based variance components method for pedigree data, we found a residual heritability estimate of 0.71 for second metacarpal cortical index. Residual heritability estimates for individual measures of cortical bone (e.g., lateral cortical thickness, medial cortical thickness) ranged from 0.47 to 0.58, at this pre-pubertal childhood age. Low genetic correlations were found between cortical bone measures and both bone length and skeletal age. However, after Bonferonni adjustment for multiple testing, rho(G) was not significantly different from 0 for any of these pairs of traits. Results of this investigation provide evidence of significant genetic control over bone mass largely independent of maturation while bones are actively growing and before rapid accrual of bone that typically occurs during puberty.

Background: Previous studies have shown that various social determinants of health (SDOH) may have contributed to the disparities in COVID-19 incidence and mortality among minorities and underserved populations at the county or zip code level. Objective: This analysis was carried out at a granular spatial resolution of census tracts to explore the spatial patterns and contextual SDOH associated with COVID-19 incidence from a Hispanic population mostly consisting of a Mexican American population living in Cameron County, Texas on the border of the United States and Mexico. We performed age-stratified analysis to identify different contributing SDOH and quantify their effects by age groups. Methods: We included all reported COVID-19–positive cases confirmed by reverse transcription–polymerase chain reaction testing between March 18 (first case reported) and December 16, 2020, in Cameron County, Texas. Confirmed COVID-19 cases were aggregated to weekly counts by census tracts. We adopted a Bayesian spatiotemporal negative binomial model to investigate the COVID-19 incidence rate in relation to census tract demographics and SDOH obtained from the American Community Survey. Moreover, we investigated the impact of local mitigation policy on COVID-19 by creating the binary variable “shelter-in-place.” The analysis was performed on all COVID-19–confirmed cases and age-stratified subgroups. Results: Our analysis revealed that the relative incidence risk (RR) of COVID-19 was higher among census tracts with a higher percentage of single-parent households (RR=1.016, 95% posterior credible intervals [CIs] 1.005, 1.027) and a higher percentage of the population with limited English proficiency (RR=1.015, 95% CI 1.003, 1.028). Lower RR was associated with lower income (RR=0.972, 95% CI 0.953, 0.993) and the percentage of the population younger than 18 years (RR=0.976, 95% CI 0.959, 0.993). The most significant association was related to the “shelter-in-place” variable, where the incidence risk of COVID-19 was reduced by over 50%, comparing the time periods when the policy was present versus absent (RR=0.506, 95% CI 0.454, 0.563). Moreover, age-stratified analyses identified different significant contributing factors and a varying magnitude of the “shelter-in-place” effect. Conclusions: In our study, SDOH including social environment and local emergency measures were identified in relation to COVID-19 incidence risk at the census tract level in a highly disadvantaged population with limited health care access and a high prevalence of chronic conditions. Results from our analysis provide key knowledge to design efficient testing strategies and assist local public health departments in COVID-19 control, mitigation, and implementation of vaccine strategies.

Severe obesity (SevO) is a primary driver of cardiovascular diseases (CVD), cardiometabolic diseases (CMD) and several cancers, with a disproportionate impact on marginalized populations. SevO is an understudied global health disease, limiting knowledge about its mechanisms and impacts. In genome-wide association study (GWAS) meta-analyses of the tail end of the BMI distribution (≥95^th percentile BMI) and two SevO phenotypes [Obesity Class III BMI ≥ 40 kg/m² and Obesity Class IV BMI ≥ 50 kg/m²] in 159,359 individuals across eleven ancestrally diverse population-based studies followed by replication in 480,897 individuals across six ancestrally diverse studies, we identified and replicated three novel signals in known loci of BMI [TENM2, PLCL2, ZNF184], associated with SevO traits. We confirmed a large overlap in the genetic architecture of continuous BMI and severe obesity phenotypes, suggesting little genetic heterogeneity in common variants, between obesity subgroups. Systematic analyses combining functional mapping, polygenic risk scores (PRS), phenome wide association studies (PheWAS) and environmental risk factors further reinforce shared downstream comorbidities associated with continuous measures of BMI and the importance of known lifestyle factors in interaction with genetic predisposition to SevO. Our study expands the number of SevO signals, demonstrates a strong overlap in the genetic architecture of SevO and BMI and reveals a remarkable impact of SevO on the clinical phenome, affording new opportunities for clinical prevention and mechanistic insights.

Background: Excess visceral adipose tissue (VAT) is a primary driver for the cardiometabolic complications of obesity; VAT‐associated cardiovascular disease risk varies by race, but most studies have been done on Non‐Hispanics. This study aimed to evaluate the clinical and metabolic correlates of VAT, its association with subclinical atherosclerosis, and the factors affecting this association in Mexican Americans. Methods and Results: Participants (n=527) were drawn from the Cameron County Hispanic Cohort (CCHC), on whom a carotid ultrasound to assess carotid intima media thickness and a dual‐energy X‐ray absorptiometry scan to assess for VAT were obtained. Those in the highest quartiles of VAT were more likely to have hypertension, hypertriglyceridemia, low high‐density lipoprotein, diabetes mellitus, and metabolic syndrome. Increased carotid intima media thickness was more prevalent in those in the highest quartile for VAT (57.4% versus 15.4% for the lowest quartile; P <0.001). There was a graded increase in mean carotid intima media thickness with increasing VAT, after adjusting for covariates; for every 10 cm ² increase in VAT, there was an increase of 0.004 mm (SE=0.002; P =0.0299) in mean carotid intima media thickness. However, this association was only seen among second or higher generation US‐born Mexican Americans but not among first generation immigrants ( P =0.024). Conclusions: Excess VAT is associated with indicators of metabolic disorders and subclinical atherosclerosis in Mexican Americans regardless of body mass index. However, acculturation appears to be an important modulator of this association. Longitudinal follow‐up with targeted interventions among second or higher generation Hispanics to lower VAT and improve cardiometabolic risk may help prevent premature cardiovascular disease in this cohort.