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Biomedical subjects

Xiuqing Guo

Publications and source records attributed to Xiuqing Guo.

At least 19 recordsLinked to original sources

Longitudinal Repeated Protein Measurements in a Multiethnic Cohort Identify Novel Diabetes Biomarkers That Reveal Unique Disease Pathways.

There is up to a fourfold increase in diabetes biomarkers identified with longitudinal repeated versus single time point proteomic measurements. The increase in biomarkers identified with longitudinal repeated measurements is supported by a similar proportion being nominated as causal for type 2 diabetes with Mendelian randomization. Proteins unique to the longitudinal repeated analyses highlighted biological pathways (e.g., posttranslational protein modification and cellular structure and cycle regulation) that were distinct from pathways enriched among the shared proteins (e.g., small-molecule metabolic and catabolic processes). Longitudinal protein measurements identify additional novel disease biomarkers and disparate biological pathways compared with single measurement analyses.

Journal Article

Addition of CAD polygenic risk score to coronary artery calcium score enhances prediction of MACE.

BACKGROUND: Coronary heart disease (CHD) is prevalent in the United States, highlighting the need for accurate risk prediction to inform primary prevention strategies. While multivariate risk models like the Framingham Risk Score and ACC/AHA Pooled Cohort Equations are commonly utilized, novel risk markers, such as the coronary artery calcium score (CACS) and polygenic risk score (PRS), are increasingly gaining recognition. OBJECTIVES: This study aimed to compare the diagnostic utility of CACS and CAD PRS, both individually and in combination, for predicting major adverse cardiovascular events (MACE). METHODS: We conducted a retrospective analysis of a cohort comprising 1,380 predominantly Caucasian participants from the Sanford Health System. CAD PRS was constructed using genetic variants, while CACS was assessed via cardiac computed tomography (CT). Statistical analyses evaluated the relationship between each modality and MACE. RESULTS: Both CAD PRS and CACS were significantly associated with future MACE. Following the adjustment for covariates, the area under the curve (AUC) for both the CACS and PRS models was comparable, indicating similar predictive capabilities for MACE. However, the combination of CAD PRS with CACS significantly enhanced predictive accuracy, outperforming either modality alone. CONCLUSIONS: This study underscores the value of integrating CACS and CAD PRS in predicting MACE. The synergistic effect of CAD PRS combined with CACS markedly improves predictive power. Further research and prospective studies are necessary to validate these findings and assess their clinical implications. Investigating the interactions between PRS and CACS will be crucial for refining cardiovascular risk prediction and optimizing prevention strategies.

cardiac genetics

Estimating population structure using epigenome-wide methylation data.

Population stratification is one of the source of inflation in epigenome-wide association studies (EWAS) when not properly accounted for. To address this, we developed methylation population scores (MPSs) to predict genetic principal components (GPCs) using a feature selection approach. We used multi-ethnic DNA methylation data from Illumina EPIC arrays across five cohorts, including MESA (n&#xa0;=&#xa0;929), CARDIA (n&#xa0;=&#xa0;1123), JHS (n&#xa0;=&#xa0;1365), ARIC (n&#xa0;=&#xa0;2338), and HCHS/SOL (n&#xa0;=&#xa0;1475), randomly splitting participants into training (85%) and test (15%) sets. Within each cohort, associations between GPCs and CpG sites were estimated using linear regression adjusting for age, sex, smoking and alcohol use, race/ethnicity, body mass index, and cell type proportions, followed by meta-analysis and selection of CpGs with FDR <0.05. We then applied a two-stage weighted least squares Lasso regression to construct MPSs, adjusting for the aforementioned covariates. In the test dataset, MPSs showed strong correlation with GPCs, with R&#xb2; ranging from 0.27 (MPS7 vs. GPC7) to 0.98 (MPS1 vs. GPC1). Visualization demonstrated that MPSs recapitulated the pattern shown by GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups and outperformed methylation-based principal components constructed using alternative published methods. Additionally, MPSs showed comparable performance to GPCs in reducing inflation in EWAS. Overall, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations, and provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent.

Humans

Impact of AGT rs5050(T>G) variants on associations between estradiol and angiotensinogen levels: Multi-Ethnic Study of Atherosclerosis (MESA).

AIMS: Angiotensinogen plays an essential role in maintaining circulatory homeostasis. AGT rs5050(T&#x2009;>&#x2009;G) has been identified as a regulator of the transcription of AGT mRNA, with differential expression between sexes. We sought to determine if rs5050(T&#x2009;>&#x2009;G), an estrogen response element, modifies the relationship between estrogen and angiotensinogen levels. METHODS: rs5050(T&#x2009;>&#x2009;G) was genotyped, and plasma angiotensinogen levels were measured in 4,831 MESA participants, including postmenopausal women, on hormone therapy (n&#x2009;=&#x2009;709) or not (n&#x2009;=&#x2009;1,551), and 2,581 men. Linear regression models were employed to determine the associations of angiotensinogen with rs5050(T&#x2009;>&#x2009;G) allele dosage; and to evaluate whether rs5050(T&#x2009;>&#x2009;G) modifies the association between estradiol and angiotensinogen, with a main effect term and interaction term between rs5050(T&#x2009;>&#x2009;G)*estradiol. Estimated marginal means (EMMs) were used to further evaluate the effect of estradiol on angiotensinogen across different rs5050 alleles (T&#x2009;>&#x2009;G). RESULTS: rs5050TT had the highest median levels of angiotensinogen, followed by TG and GG. Adjusted main effect model showed positive associations between estradiol and angiotensinogen, with each rs5050T allele associated with 0.329 SD higher log-angiotensinogen levels (CI 95% 0.293, 0.365). The interaction rs5050(T&#x2009;>&#x2009;G)*estradiol was not significant, with EMMs exhibiting overlapping slope confidence intervals across genotypes. The proportion of the variance in angiotensinogen explained by modeling increases from 47.9% to 51.6% when including rs5050(T&#x2009;>&#x2009;G) or interation rs5050(T&#x2009;>&#x2009;G)*estradiol in the model. CONCLUSIONS: rs5050(T&#x2009;>&#x2009;G) is associated with circulating angiotensinogen levels, but rs5050(T&#x2009;>&#x2009;G) alleles do not influence the relationship between estradiol and angiotensinogen. This suggests that estrogen's effect on angiotensinogen regulation occurs independently of rs5050(T&#x2009;>&#x2009;G), despite its location within an estrogen-responsive element.

Angiotensinogen

Proteome-wide association study of prostate cancer risk across populations.

There is insufficient understanding of the molecular basis of prostate cancer (PCa) across different populations. We perform a large-scale proteome-wide association study&#xa0;(PWAS) to identify proteins with genetically regulated expression in plasma to be associated with PCa risk across populations. We develop genetic prediction models for expression of 1578, 1993, 1218, and 1390 proteins for African (n&#x2009;=&#x2009;450), European (n&#x2009;=&#x2009;758), Asian (n&#x2009;=&#x2009;289), and Hispanic/Latino (n&#x2009;=&#x2009;474) males, respectively, and evaluate associations of genetically regulated protein expression with PCa risk in 19,391 PCa cases and 61,608 controls of African population, 122,188 cases and 604,640 controls of European population, 10,809 cases and 95,790 controls of Asian population, and 3931 cases and 26,405 controls of Hispanic/Latino population. We identify three, four, 15, and 73 PCa-associated proteins in African, Hispanic/Latino, Asian, and European populations, respectively, and 83 in trans-population meta-analysis. There are both pan-population and population-specific associations. Our findings provide valuable insights into etiology of PCa.

Humans

Genome-wide gene-sleep interaction study identifies novel lipid loci in 732,564 participants.

BACKGROUND AND AIMS: Deviations from the population mean in sleep duration have been associated with increased risk for developing dyslipidemia and atherosclerotic cardiovascular disease, but the mechanism of effect is poorly characterized. We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets. METHODS: We collected data from 55 cohorts with a combined sample size of 732,564 participants (87&#xa0;% European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) total sleep time were defined by the extreme 20&#xa0;% of the age- and sex-standardized values within each cohort. Based on cohort-level summary statistics data, we performed meta-analyses for one-degree of freedom tests of interaction and two-degree of freedom joint tests of the SNP-main and -interaction effect on lipid levels. RESULTS: The one-degree of freedom variant-sleep interaction test identified 10 novel loci (Pint<5.0e-9), and we additionally identify 7 loci within the two-degree of freedom analyses (Pjoint<5.0e-9 in combination with Pint<6.6e-6). Multiple loci, including those mapped to APSH (target for aspartic and succinic acid) and SLC8A1 showed biological plausibility and druggability potential based on literature. CONCLUSIONS: Collectively, the 17 (9 with short and 8 with long sleep) loci provided evidence into the biomolecular mechanisms underlying sleep-associated lipid changes, including potential involvement of the vitamin D receptor pathway. Collectively, these findings may contribute developing novel interventions for treating dyslipidemia in people with sleep disturbances.

Humans

Whole genome sequence analysis of low-density lipoprotein cholesterol across 246&#xa0;K individuals.

BACKGROUND: Rare genetic variation provided by whole genome sequence datasets has been relatively less explored for its contributions to human traits. Meta-analysis of sequencing data offers advantages by integrating larger sample sizes from diverse cohorts, thereby increasing the likelihood of discovering novel insights into complex traits. Furthermore, emerging methods in genome-wide rare variant association testing further improve power and interpretability. RESULTS: Here, we conduct the largest meta-analysis of whole genome sequencing for low-density lipoprotein cholesterol (LDL-C), a therapeutic target for coronary artery disease, analyzing data from 246&#xa0;K participants and integrating 1.23B variants from the UK Biobank and the Trans-Omics for Precision Medicine (TOPMed) program. We identify numerous rare coding and non-coding gene associations related to LDL-C, with replication across 86&#xa0;K participants in All of Us. Our findings are based on single-variant analyses, rare coding and non-coding variant aggregation tests, and sliding window approaches. Through this comprehensive analysis, we identify 704 novel single-variant associations, 25 novel rare coding variant aggregates, 28 novel rare non-coding variant aggregates, and one novel sliding window aggregate. CONCLUSIONS: This study provides a meta-analysis framework for large-scale whole genome sequence association analyses from diverse population groups, yielding novel rare non-coding variant associations.

Humans

Estimating population structure using epigenome-wide methylation data.

INTRODUCTION: In epigenome-wide association analysis (EWAS), unaddressed population stratification often leads to inflation. We aimed to compute methylation population scores (MPSs) that predict genetic principal components (GPCs) using a feature selection and regression approach. METHODS: We used multi-ethnic methylation data (Illumina 450K/EPIC array) from unrelated MESA (n=929), CARDIA (n=1123), JHS (n=1365), ARIC (n=2338), and HCHS/SOL (n=1475) individuals, randomly assigning 85% of participants from each cohort to a training dataset and the remaining 15% to a test dataset. First, we estimated the associations of GPCs with each available CpG methylation site using linear regression within each cohort, adjusting for age, sex, smoking status, race/ethnic background (as a proxy for background information associated with lifestyle and other environmental exposures that may impact methylation), alcohol use status, body mass index, and cell type proportions. We meta-analyzed the associations across cohorts and selected CpG sites with association FDR-adjusted q-value <0.05. We next aggregated individuallevel data across the cohort-specific training datasets, and applied two-stage weighted least squares Lasso regression, with the GPCs as the outcomes and the selected CpG sites as penalized predictors, adjusting for the aforementioned covariates. The developed MPSs are the weighted sum of selected CpG sites from the Lasso. To evaluate the developed MPSs, we constructed them in the test dataset, and compared them with GPCs, and with MPSs constructed based on a previously-published paper. Comparison was based on correlation analysis and data visualization. We demonstrate the use of the MPSs in EWAS. RESULTS: In the test dataset, the MPSs were highly correlated with GPCs, with correlation decreasing, though not monotonically, for later components. Specifically, MPS1 and GPC1 had R2= 0.99, while MPS7 and GPC7 had R2=0.27 (the lowest observed correlation). In data visualization, MPSs had similar patterns as GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups, while outperforming MPC constructed using alternative published methods. MPSs showed comparable performance to GPCs in reducing some of the inflation in EWAS. CONCLUSIONS: Methylation-based population scores provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent. Unlike previous methods based on unsupervised methylation PCA, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations. The weights for each GPCs derived in our study can be applied to generate MPSs in other studies.

Journal Article

Polygenic prediction of body mass index and obesity through the life course and across ancestries.

Polygenic scores (PGSs) for body mass index (BMI) may guide early prevention and targeted treatment of obesity. Using genetic data from up to 5.1 million people (4.6% African ancestry, 14.4% American ancestry, 8.4% East Asian ancestry, 71.1% European ancestry and 1.5% South Asian ancestry) from the GIANT consortium and 23andMe, Inc., we developed ancestry-specific and multi-ancestry PGSs. The multi-ancestry score explained 17.6% of BMI variation among UK Biobank participants of European ancestry. For other populations, this ranged from 16% in East Asian-Americans to 2.2% in rural Ugandans. In the ALSPAC study, children with higher PGSs showed accelerated BMI gain from age 2.5&#x2009;years to adolescence, with earlier adiposity rebound. Adding the PGS to predictors available at birth nearly doubled explained variance for BMI from age 5 onward (for example, from 11% to 21% at age 8). Up to age 5, adding the PGS to early-life BMI improved prediction of BMI at age 18 (for example, from 22% to 35% at age 5). Higher PGSs were associated with greater adult weight gain. In intensive lifestyle intervention trials, individuals with higher PGSs lost modestly more weight in the first year (0.55&#x2009;kg per s.d.) but were more likely to regain it. Overall, these data show that PGSs have the potential to improve obesity prediction, particularly when implemented early in life.

Adolescent

Genome-wide association study of angiotensinogen levels and key single nucleotide polymorphism associations with blood pressure.

OBJECTIVE: The renin angiotensin aldosterone system plays a key role in circulatory homeostasis. We sought to identify genetic determinants of measured plasma angiotensinogen levels and subsequently evaluate the association of these single nucleotide polymorphisms (SNPs) with blood pressure (BP) and hypertension in a multiethnic population. METHODS: Genome-wide association study (GWAS) of plasma angiotensinogen levels, measured using an enzyme-linked immunoassay, was conducted in 4899 Multi-Ethnic Study of Atherosclerosis (MESA) participants (self-identified as White, n = 1865; Hispanic, n &#x200a;=&#x200a;1113; Black, n &#x200a;=&#x200a;1224; and Chinese, n &#x200a;=&#x200a;629). Linear and logistic models examined the association between SNPs with angiotensinogen and hypertension, respectively. Mediation analysis evaluated the effect of angiotensinogen on BP/hypertension through the top SNPs identified by GWAS. RESULTS: In the analysis utilizing all participants, 115 SNPs were associated with angiotensinogen ( P &#x200a;<&#x200a;5&#x200a;&#xd7;&#x200a;10 -8 ), including lead SNP rs4762(G>A) in exon 2 ( P &#x200a;=&#x200a;1.51E -100 ) and rs5050(T>G) in the promoter region ( P &#x200a;=&#x200a;2.26E -69 ) of the AGT gene. Race/ethnic-specific analyses identified rs4762(G>A) as the lead SNP for White and Hispanic participants, whereas Black and Chinese participants had rs5050(T>G) and rs16852311(G>C), respectively. Both rs4762(G>A) and rs5050(T>G) indirectly increased systolic BP, diastolic BP, and the odds of hypertension through its effect of increasing angiotensinogen. CONCLUSIONS: Our findings demonstrate racial/ethnic differences in genetic effects on angiotensinogen levels across multiple SNPs. AGT rs4762(G>A) and rs5050(T>G) impact BP and hypertension through a mediated effect via angiotensinogen, though opposing direct effects may mask the overall association.

Humans

A comprehensive evaluation of candidate genetic polymorphisms in a large histologically characterized MASLD cohort using a novel framework.

BACKGROUND: There is a substantial heritable component to metabolic dysfunction-associated steatotic liver disease (MASLD), and several genetic variants that promote MASLD development or associate with its severity have been reported. These associations vary in terms of their effect size and degree of replication. METHODS: We developed a framework to classify previously identified MASLD genetic polymorphisms into 4 tiers based on effect size and extent of replication in the literature. We tested the association between "tier 1" single-nucleotide polymorphisms (OR &#x2265;1.5, replicated in >2 independent studies) and biopsy measures of MASLD severity in a large, well-characterized histologic cohort of MASLD patients (n=3094). RESULTS: Across 19 "tier 1" variants reflecting 11 genetic loci, only those in the PNPLA3-SAMM50-PARVB locus showed significant associations with biopsy-proven fibrosis severity and NAFLD activity score; the highest risk was for the rs738409 p.I148M variant in PNPLA3. A genetic risk score based on "tier 1" variants, as well as a previously developed genetic risk score based on variants in PNPLA3, TM6SF2, and HSD17B13, were both associated with fibrosis and NAFLD activity score, but these results were driven entirely by PNPLA3 rs738409. CONCLUSIONS: Our study provides a framework to prioritize evaluation of genetic polymorphisms for future replication efforts and demonstrates that in a large case-only cohort, histologic severity of MASLD is only robustly associated with the presence of variation in PNPLA3 among known candidate genes. These findings may have implications for patient risk stratification based on the presence of PNPLA3 rs738409.

Humans

Epigenetic mechanisms underlying variation of IL-6, a well-established inflammation biomarker and risk factor for cardiovascular disease.

BACKGROUND AND AIMS: Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality worldwide, yet the underlying molecular mechanisms remain less understood. Chronic low-grade inflammation is a complex immune response contributing to the pathophysiology of cardiovascular disease. This response is signaled in part by interleukin-6 (IL-6), a pleiotropic, pro-inflammatory cytokine. Phenotypic variance in circulating IL-6 level may be explained in part by DNA methylation which is increasingly being associated with cardiovascular effects. METHODS: In this study we evaluated methylated DNA (CpG sites) associated with blood IL-6 levels across &#x223c;4,400 ancestrally diverse individuals (81&#xa0;% self-reported White; 9&#xa0;% Black or African American, 8&#xa0;% Hispanic or Latino/a, and 2&#xa0;% Chinese American). RESULTS: We identified 178 CpG sites associated with IL-6 (p<0.05/&#x223c;395,000). Among the sites, cg04437762 is located within the transcription unit of IL6R, a current therapeutic target for inflammatory disease, and cg26692003 and cg00464927 were significant for IL6 and IL6ST trans-CpG-gene transcripts. Functional gene expression downstream of methylation identified cellular response to IL-6 and B-cell regulation and activation pathways. Four genes were linked with both a genetic component of cardiovascular disease and an IL-6 associated CpG site. Three CpG sites identified through Mendelian randomization analyses supported inference of a causal effect on IL-6 levels, including the LYN gene that regulates immune cell signaling and has been previously associated with atherosclerosis. CONCLUSIONS: Overall, we identified several novel IL-6-CpG sites and downstream pathways affected by methylation. Follow-up functional studies including the regulation of IL-6 would complement current knowledge of CVD pathophysiology and potential therapeutic targets.

Humans

Genetic study of von Willebrand factor antigen levels &#x2264; 50 IU/dL identifies variants associated with increased risk of von Willebrand disease and bleeding.

BACKGROUND: von Willebrand disease (VWD) is a common inherited bleeding disorder caused by low levels or activity of circulating von Willebrand factor (VWF). Genetic susceptibility to VWF antigen (VWF:Ag) below normal (&#x2264; 50 IU/dL) in the general population is underexplored. OBJECTIVES: To identify genetic variants influencing VWF:Ag levels &#x2264; 50 IU/dL. METHODS: We performed a genome-wide association study in 926 cases with VWF:Ag levels &#x2264; 50 IU/dL and 12 846 controls from 7 studies from the Trans-Omics for Precision Medicine program. We then examined whether significant genome-wide findings were also associated with clinical diagnosis of VWD in 5 biobanks with 708 VWD cases and 1 286 069 controls, and with 6 bleeding and thrombotic disorders in FinnGen. RESULTS: Variants at 2 loci were associated (P < 5 &#xd7; 10-9) with VWF:Ag levels &#x2264; 50 IU/dL: ABO and VWF. The VWF index variant, p.Tyr1584Cys, is a rare (0.22%) missense variant with odds ratio (OR) of 78.58, while the ABO index variant is a common intronic variant with a smaller effect (OR = 2.52). Notably, both VWF (OR = 7.16) and ABO (OR = 1.57) variants were also associated (P < .025) with diagnosed VWD. Among p.Tyr1584Cys heterozygotes, the penetrance of VWF:Ag levels &#x2264; 50 IU/dL was 24.2% and the penetrance of diagnosed VWD was 0.3%. p.Tyr1584Cys was associated (P < .0042) with increased odds of heavy menstrual bleeding (OR = 1.27), iron deficiency anemia (OR = 1.55), and intrapartum hemorrhage (OR = 2.20), but decreased odds of deep vein thrombosis (OR = 0.54). CONCLUSIONS: Although there are currently conflicting interpretations of pathogenicity p.Tyr1584Cys, our results suggest that it is a low penetrance pathogenic variant that contributes to VWF:Ag levels &#x2264; 50 IU/dL, bleeding, and VWD.

Humans

Large-scale multi-omics analyses in Hispanic/Latino populations identify genes for cardiometabolic traits.

Here, we present a multi-omics study of type 2 diabetes and quantitative blood lipid and lipoprotein traits conducted to date in Hispanic/Latino populations (nmax&#x2009;=&#x2009;63,184). We conduct a meta-analysis of 16 type 2 diabetes and 19 lipid trait GWAS, identifying 20 genome-wide significant loci for type 2 diabetes, including one novel locus and novel signals at two known loci, based on fine-mapping. We also identify sixty-one genome-wide significant loci across the lipid/lipoprotein traits, including nine novel loci, and novel signals at 19 known loci through fine-mapping. Next, we analyze genetically regulated expression, perform Mendelian randomization, and analyze association with transcriptomic and proteomic measure using multi-omics data from a Hispanic/Latino population. Using this approach, we identify genes linked to type 2 diabetes and lipid/lipoprotein traits, including TMEM205 and NEDD9 for HDL cholesterol, TREH for triglycerides, and ANXA4 for type 2 diabetes.

Female

Rare damaging CCR2 variants are associated with lower lifetime cardiovascular risk.

BACKGROUND: Previous work has shown a role of CCL2, a key chemokine governing monocyte trafficking, in atherosclerosis. However, it remains unknown whether targeting CCR2, the cognate receptor of CCL2, provides protection against human atherosclerotic cardiovascular disease. METHODS: Computationally predicted damaging or loss-of-function (REVEL&#x2009;>&#x2009;0.5) variants within CCR2 were detected in whole-exome-sequencing data from 454,775 UK Biobank participants and tested for association with cardiovascular endpoints in gene-burden tests. Given the key role of CCR2 in monocyte mobilization, variants associated with lower monocyte count were prioritized for experimental validation. The response to CCL2 of human cells transfected with these variants was tested in migration and cAMP assays. Validated damaging variants were tested for association with cardiovascular endpoints, atherosclerosis burden, and vascular risk factors. Significant associations were replicated in six independent datasets (n&#x2009;=&#x2009;1,062,595). RESULTS: Carriers of 45 predicted damaging or loss-of-function CCR2 variants (n&#x2009;=&#x2009;787 individuals) were at lower risk of myocardial infarction and coronary artery disease. One of these variants (M249K, n&#x2009;=&#x2009;585, 0.15% of European ancestry individuals) was associated with lower monocyte count and with both decreased downstream signaling and chemoattraction in response to CCL2. While M249K showed no association with conventional vascular risk factors, it was consistently associated with a lower risk of myocardial infarction (odds ratio [OR]: 0.66, 95% confidence interval [CI]: 0.54-0.81, p&#x2009;=&#x2009;6.1&#x2009;&#xd7;&#x2009;10-5) and coronary artery disease (OR: 0.74, 95%CI: 0.63-0.87, p&#x2009;=&#x2009;2.9&#x2009;&#xd7;&#x2009;10-4) in the UK Biobank and in six replication cohorts. In a phenome-wide association study, there was no evidence of a higher risk of infections among M249K carriers. CONCLUSIONS: Carriers of an experimentally confirmed damaging CCR2 variant are at a lower lifetime risk of myocardial infarction and coronary artery disease without carrying a higher risk of infections. Our findings provide genetic support for the translational potential of CCR2-targeting as an atheroprotective approach.

Humans

Unveiling the Genetic Landscape of Coronary Artery Disease Through Common and Rare Structural Variants.

BACKGROUND: Genome-wide association studies have identified several hundred susceptibility single nucleotide variants for coronary artery disease (CAD). Despite single nucleotide variant-based genome-wide association studies improving our understanding of the genetics of CAD, the contribution of structural variants (SVs) to the risk of CAD remains largely unclear. METHOD AND RESULTS: We leveraged SVs detected from high-coverage whole genome sequencing data in a diverse group of participants from the National Heart Lung and Blood Institute's Trans-Omics for Precision Medicine program. Single variant tests were performed on 58&#x2009;706 SVs in a study sample of 11&#x2009;556 CAD cases and 42&#x2009;907 controls. Additionally, aggregate tests using sliding windows were performed to examine rare SVs. One genome-wide significant association was identified for a common biallelic intergenic duplication on chromosome 6q21 (P=1.54E-09, odds ratio=1.34). The sliding window-based aggregate tests found 1 region on chromosome 17q25.3, overlapping USP36, to be significantly associated with coronary artery disease (P=1.03E-10). USP36 is highly expressed in arterial and adipose tissues while broadly affecting several cardiometabolic traits. CONCLUSIONS: Our results suggest that SVs, both common and rare, may influence the risk of coronary artery disease.

Humans

Soluble Immune Checkpoint Protein and Lipid Network Associations with All-Cause Mortality Risk: Trans-Omics for Precision Medicine (TOPMed) Program.

Adverse cardiovascular events are emerging with the use of immune checkpoint therapies in oncology. Using datasets in the Trans-Omics for Precision Medicine program (Multi-Ethnic Study of Atherosclerosis, Jackson Heart Study [JHS], and Framingham Heart Study), we examined the association of immune checkpoint plasma proteins with each other, their associated protein network with high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C), and the association of HDL-C- and LDL-C-associated protein networks with all-cause mortality risk. Plasma levels of LAG3 and HAVCR2 showed statistically significant associations with mortality risk. Colocalization analysis using genome wide-association studies of HDL-C or LDL-C and protein quantitative trait loci from JHS and the Atherosclerosis Risk in Communities identified TFF3 rs60467699 and CD36 rs3211938 variants as significantly colocalized with HDL-C; in contrast, none colocalized with LDL-C. The measurement of plasma LAG3, HAVCR2, and associated proteins plus targeted genotyping may identify patients at increased mortality risk.

Journal Article