Identification of genetic loci simultaneously associated with multiple cardiometabolic traits

Background and aims: Cardiometabolic disorders (CMD) arise from a constellation of features such as increased adiposity, hyperlipidemia, hypertension and compromised glucose control. Many genetic loci have shown associations with individual CMD-related traits, but no investigations have focused on simultaneously identifying loci showing associations across all domains. We therefore sought to identify loci associated with risk across seven continuous CMD-related traits. Methods and results: We conducted separate genome-wide association studies (GWAS) for systolic and diastolic blood pressure (SBP/DBP), hemoglobin A1c (HbA1c), low- and high- density lipoprotein cholesterol (LDL-C/HDL-C), waist-to-hip-ratio (WHR), and triglycerides (TGs) in the UK Biobank (N = 356,574–456,823). Multiple loci reached genome-wide levels of significance (N = 145–333) for each trait, but only four loci (in/near VEGFA, GRB14-COBLL1, KLF14, and RGS19-OPRL1) were associated with risk across all seven traits (P < 5 × 10−8). We sought replication of these four loci in an independent set of seven trait-specific GWAS meta-analyses. GRB14-COBLL1 showed the most consistent replication, revealing nominally significant associations (P < 0.05) with all traits except DBP. Conclusions: Our analyses suggest that very few loci are associated in the same direction of risk with traits representing the full spectrum of CMD features. We identified four such loci, and an understanding of the pathways between these loci and CMD risk may eventually identify factors that can be used to identify pathologic disturbances that represent broadly beneficial therapeutic targets.National Institutes of Health12 month embargo; published: 07 January 2022This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Associations between ACE-Inhibitors, Angiotensin Receptor Blockers, and Lean Body Mass in Community Dwelling Older Women

Studies suggest that ACE-inhibitors (ACE-I) and angiotensin receptor blockers (ARBs) may preserve skeletal muscle with aging. We evaluated longitudinal differences in lean body mass (LBM) among women diagnosed with hypertension and classified as ACE-I/ARB users and nonusers among Women’s Health Initiative participants that received dual energy X-ray absorptiometry scans to estimate body composition (n=10,635) at baseline and at years 3 and 6 of follow-up. Of those, 2642 were treated for hypertension at baseline. Multivariate linear regression models, adjusted for relevant demographics, behaviors, and medications, assessed ACE-I/ARB use/nonuse and LBM associations at baseline, as well as change in LBM over 3 and 6 years. Although BMI did not differ by ACE-I/ARB use, LBM (%) was significantly higher in ACE-I/ARB users versus nonusers at baseline (52.2% versus 51.3%, resp., p=0.001). There was no association between ACE-I/ARB usage and change in LBM over time. Reasons for higher LBM with ACE-I/ARB use cross sectionally, but not longitundinally, are unclear and may reflect a threshold effect of these medications on LBM that is attenuated over time. Nevertheless, ACE-I/ARB use does not appear to negatively impact LBM in the long term

Genetically predicted physical activity levels are associated with lower colorectal cancer risk: a Mendelian randomisation study.

Funder: The Darwin Trust of EdinburghFunder: National Institute of Health [grant number R01 HL136528]BACKGROUND: We conducted a Mendelian randomisation (MR) study to investigate whether physical activity (PA) causes a reduction of colorectal cancer risk and to understand the contributions of effects mediated through changes in body fat. METHODS: Common genetic variants associated with self-reported moderate-to-vigorous PA (MVPA), acceleration vector magnitude PA (AMPA) and sedentary time were used as instrumental variables. To control for confounding effects of obesity, we included instrumental variables for body mass index (BMI), body fat percentage, waist circumference and arm, trunk and leg fat ratios. We analysed the effect of these instrumental variables in a colorectal cancer genome-wide association study comprising 31,197 cases and 61,770 controls of European ancestry by applying two-sample and multivariable MR study designs. RESULTS: We found decreased colorectal cancer risk for genetically represented measures of MVPA and AMPA that were additional to effects mediated through genetic measures of obesity. Odds ratio and 95% confidence interval (CI) per standard deviation increase in MVPA and AMPA was 0.56 (0.31, 1.01) and 0.60 (0.41, 0.88), respectively. No association has been found between sedentary time and colorectal cancer risk. The proportion of effect mediated through BMI was 2% (95% CI: 0, 14) and 32% (95% CI: 12, 46) for MVPA and AMPA, respectively. CONCLUSION: These findings provide strong evidence to reinforce public health measures on preventing colorectal cancer that promote PA at a population level regardless of body fatness

Estimating Genetic Ancestry Proportions from Faces

Ethnicity can be a means by which people identify themselves and others. This type of identification mediates many kinds of social interactions and may reflect adaptations to a long history of group living in humans. Recent admixture in the US between groups from different continents, and the historically strong emphasis on phenotypic differences between members of these groups, presents an opportunity to examine the degree of concordance between estimates of group membership based on genetic markers and on visually-based estimates of facial features. We first measured the degree of Native American, European, African and East Asian genetic admixture in a sample of 14 self-identified Hispanic individuals, chosen to cover a broad range of Native American and European genetic admixture proportions. We showed frontal and side-view photographs of the 14 individuals to 241 subjects living in New Mexico, and asked them to estimate the degree of NA admixture for each individual. We assess the overall concordance for each observer based on an aggregated measure of the difference between the observer and the genetic estimates. We find that observers reach a significantly higher degree of concordance than expected by chance, and that the degree of concordance as well as the direction of the discrepancy in estimates differs based on the ethnicity of the observer, but not on the observers' age or sex. This study highlights the potentially high degree of discordance between physical appearance and genetic measures of ethnicity, as well as how perceptions of ethnic affiliation are context-specific. We compare our findings to those of previous studies and discuss their implications

A Conserved Role for Syndecan Family Members in the Regulation of Whole-Body Energy Metabolism

Syndecans are a family of type-I transmembrane proteins that are involved in cell-matrix adhesion, migration, neuronal development, and inflammation. Previous quantitative genetic studies pinpointed Drosophila Syndecan (dSdc) as a positional candidate gene affecting variation in fat storage between two Drosophila melanogaster strains. Here, we first used quantitative complementation tests with dSdc mutants to confirm that natural variation in this gene affects variability in Drosophila fat storage. Next, we examined the effects of a viable dSdc mutant on Drosophila whole-body energy metabolism and associated traits. We observed that young flies homozygous for the dSdc mutation had reduced fat storage and slept longer than homozygous wild-type flies. They also displayed significantly reduced metabolic rate, lower expression of spargel (the Drosophila homologue of PGC-1), and reduced mitochondrial respiration. Compared to control flies, dSdc mutants had lower expression of brain insulin-like peptides, were less fecund, more sensitive to starvation, and had reduced life span. Finally, we tested for association between single nucleotide polymorphisms (SNPs) in the human SDC4 gene and variation in body composition, metabolism, glucose homeostasis, and sleep traits in a cohort of healthy early pubertal children. We found that SNP rs4599 was significantly associated with resting energy expenditure (P = 0.001 after Bonferroni correction) and nominally associated with fasting glucose levels (P = 0.01) and sleep duration (P = 0.044). On average, children homozygous for the minor allele had lower levels of glucose, higher resting energy expenditure, and slept shorter than children homozygous for the common allele. We also observed that SNP rs1981429 was nominally associated with lean tissue mass (P = 0.035) and intra-abdominal fat (P = 0.049), and SNP rs2267871 with insulin sensitivity (P = 0.037). Collectively, our results in Drosophila and humans argue that syndecan family members play a key role in the regulation of body metabolism

Associations of air pollution with obesity and body fat percentage, and modification by polygenic risk score for BMI in the UK Biobank

Air pollution has consistently been associated with cardiometabolic outcomes, although associations with obesity have only been recently reported. Studies of air pollution and adiposity have mostly relied on body mass index (BMI) rather than body fat percentage (BF%), and most have not accounted for noise as a possible confounder. Additionally, it is unknown whether genetic predisposition for obesity increases susceptibility to the obesogenic effects of air pollution. To help fill these gaps, we used the UK Biobank, a large, prospective cohort study in the United Kingdom, to explore the relationship between air pollution and adiposity, and modification by a polygenic risk score for BMI. We used 2010 annual averages of air pollution estimates from land use regression (NO2, NOX, PM2.5, PM2.5absorbance, PM2.5-10, PM10), traffic intensity (TI), inverse distance to road (IDTR), along with examiner-measured BMI, waist-hip-ratio (WHR), and impedance measures of BF%, which were collected at enrollment (2006-2010, n = 473,026) and at follow-up (2012-2013, n = 19,518). We estimated associations of air pollution with BMI, WHR, and BF% at enrollment and follow-up, and with obesity, abdominal obesity, and BF%-obesity at enrollment and follow-up. We used linear and logistic regression and controlled for noise and other covariates. We also assessed interactions of air pollution with a polygenic risk score for BMI. On average, participants at enrollment were 56 years of age, 54% were female, and 32% had completed college or a higher degree. Almost all participants (~95%) were white. All air pollution measures except IDTR were positively associated with at least one continuous measure of adiposity at enrollment. However, NO2 was negatively associated with BMI but positively associated with WHR at enrollment, and IDTR was also negatively associated with BMI. At follow-up (controlling for enrollment adiposity), we observed positive associations for PM2.5-10 with BMI, PM10 with BF%, and TI with BF% and BMI. Associations were similar for binary measures of adiposity, with minor differences for some pollutants. Associations of NOX, NO2, PM2.5absorbance, PM2.5 and PM10, with BMI at enrollment, but not at follow-up, were stronger among individuals with higher BMI polygenic risk scores (interaction p <0.05). In this large, prospective cohort, air pollution was associated with several measures of adiposity at enrollment and follow-up, and associations with adiposity at enrollment were modified by a polygenic risk score for obesity.24 month embargo; published online: 12 March 2020This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Sample Characteristics.

<p>Sample Characteristics.</p

Averaged difference between observer and genetic estimates by self-identified race of observer.

<p>Positive values indicate an overall overestimation of NA ancestry by the observers, compared to the genetic estimates. Error bars show 95% CI of Mean.</p