Publications by authors named "Paul S de Vries"

68 Publications

No prospective association of a polygenic risk score for coronary artery disease with venous thromboembolism incidence.

J Thromb Haemost 2021 Aug 19. Epub 2021 Aug 19.

Department of Medicine and Department of Pathology and Laboratory Medicine, University of Vermont, Burlington, VT, USA.

Background: Previous studies are inconsistent about whether chronic coronary artery disease or generalized atherosclerosis is a causal risk factor for venous thromboembolism. No study seems to have taken a genomic approach to this question.

Objective: To test in a prospective study whether a polygenic risk score for coronary artery disease is associated with risk of venous thromboembolism.

Participants/methods: Within the Atherosclerosis Risk in Communities Study cohort, we computed a previously validated polygenic risk score for coronary artery disease among 9144 White participants at baseline in 1987-1989. We followed the participants through 2015 for incident hospitalized venous thromboembolism events, validated by physician review. We used Cox proportional hazards regression to associate quintiles of the polygenic risk score to venous thromboembolism incidence rates.

Results: Over the median of 26 years of follow-up, 476 participants had a venous thromboembolism event. There was no apparent association between the coronary artery disease polygenic risk score and incident venous thromboembolism, with age, sex, body mass index adjusted hazard ratios across quintiles being 1 (reference), 0.87 (0.65, 1.15), 1.08 (0.82, 1.42), 0.96 (0.72, 1.27), and 1.03 (0.78, 1.37).

Conclusions: A genetic disposition to coronary artery disease did not confer an increased risk of venous thromboembolism in this prospective study.
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http://dx.doi.org/10.1111/jth.15501DOI Listing
August 2021

Progress and Research Priorities in Imaging Genomics for Heart and Lung Disease: Summary of an NHLBI Workshop.

Circ Cardiovasc Imaging 2021 Aug 13;14(8):e012943. Epub 2021 Aug 13.

Sections of Preventive Medicine and Epidemiology, and Cardiology, Department of Medicine, Department of Epidemiology, Boston University Schools of Medicine and Public Health, and Center for Computing and Data Sciences, Boston University, MA (R.S.V.).

Imaging genomics is a rapidly evolving field that combines state-of-the-art bioimaging with genomic information to resolve phenotypic heterogeneity associated with genomic variation, improve risk prediction, discover prevention approaches, and enable precision diagnosis and treatment. Contemporary bioimaging methods provide exceptional resolution generating discrete and quantitative high-dimensional phenotypes for genomics investigation. Despite substantial progress in combining high-dimensional bioimaging and genomic data, methods for imaging genomics are evolving. Recognizing the potential impact of imaging genomics on the study of heart and lung disease, the National Heart, Lung, and Blood Institute convened a workshop to review cutting-edge approaches and methodologies in imaging genomics studies, and to establish research priorities for future investigation. This report summarizes the presentations and discussions at the workshop. In particular, we highlight the need for increased availability of imaging genomics data in diverse populations, dedicated focus on less common conditions, and centralization of efforts around specific disease areas.
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http://dx.doi.org/10.1161/CIRCIMAGING.121.012943DOI Listing
August 2021

Genetic testing in ambulatory cardiology clinics reveals high rate of findings with clinical management implications.

Genet Med 2021 Aug 6. Epub 2021 Aug 6.

Department of Medicine, Division of Diabetes, Endocrinology and Metabolism, Baylor College of Medicine, Houston, TX, USA.

Purpose: Cardiovascular disease (CVD) is the leading cause of death in adults in the United States, yet the benefits of genetic testing are not universally accepted.

Methods: We developed the "HeartCare" panel of genes associated with CVD, evaluating high-penetrance Mendelian conditions, coronary artery disease (CAD) polygenic risk, LPA gene polymorphisms, and specific pharmacogenetic (PGx) variants. We enrolled 709 individuals from cardiology clinics at Baylor College of Medicine, and samples were analyzed in a CAP/CLIA-certified laboratory. Results were returned to the ordering physician and uploaded to the electronic medical record.

Results: Notably, 32% of patients had a genetic finding with clinical management implications, even after excluding PGx results, including 9% who were molecularly diagnosed with a Mendelian condition. Among surveyed physicians, 84% reported medical management changes based on these results, including specialist referrals, cardiac tests, and medication changes. LPA polymorphisms and high polygenic risk of CAD were found in 20% and 9% of patients, respectively, leading to diet, lifestyle, and other changes. Warfarin and simvastatin pharmacogenetic variants were present in roughly half of the cohort.

Conclusion: Our results support the use of genetic information in routine cardiovascular health management and provide a roadmap for accompanying research.
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http://dx.doi.org/10.1038/s41436-021-01294-8DOI Listing
August 2021

Genetic susceptibility, obesity and lifetime risk of type 2 diabetes: The ARIC study and Rotterdam Study.

Diabet Med 2021 Oct 2;38(10):e14639. Epub 2021 Aug 2.

Department of Biostatistics and Epidemiology, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.

Aims: Both lifestyle factors and genetic background contribute to the development of type 2 diabetes. Estimation of the lifetime risk of diabetes based on genetic information has not been presented, and the extent to which a normal body weight can offset a high lifetime genetic risk is unknown.

Methods: We used data from 15,671 diabetes-free participants of European ancestry aged 45 years and older from the prospective population-based ARIC study and Rotterdam Study (RS). We quantified the remaining lifetime risk of diabetes stratified by genetic risk and quantified the effect of normal weight in terms of relative and lifetime risks in low, intermediate and high genetic risk.

Results: At age 45 years, the lifetime risk of type 2 diabetes in ARIC in the low, intermediate and high genetic risk category was 33.2%, 41.3% and 47.2%, and in RS 22.8%, 30.6% and 35.5% respectively. The absolute lifetime risk for individuals with normal weight compared to individuals with obesity was 24% lower in ARIC and 8.6% lower in RS in the low genetic risk group, 36.3% lower in ARIC and 31.3% lower in RS in the intermediate genetic risk group, and 25.0% lower in ARIC and 29.4% lower in RS in the high genetic risk group.

Conclusions: Genetic variants for type 2 diabetes have value in estimating the lifetime risk of type 2 diabetes. Normal weight mitigates partly the deleterious effect of high genetic risk.
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http://dx.doi.org/10.1111/dme.14639DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8429251PMC
October 2021

Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality.

PLoS One 2021 3;16(6):e0247235. Epub 2021 Jun 3.

School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States of America.

Understanding sociodemographic, behavioral, clinical, and laboratory risk factors in patients diagnosed with COVID-19 is critically important, and requires building large and diverse COVID-19 cohorts with both retrospective information and prospective follow-up. A large Health Information Exchange (HIE) in Southeast Texas, which assembles and shares electronic health information among providers to facilitate patient care, was leveraged to identify COVID-19 patients, create a cohort, and identify risk factors for both favorable and unfavorable outcomes. The initial sample consists of 8,874 COVID-19 patients ascertained from the pandemic's onset to June 12th, 2020 and was created for the analyses shown here. We gathered demographic, lifestyle, laboratory, and clinical data from patient's encounters across the healthcare system. Tobacco use history was examined as a potential risk factor for COVID-19 fatality along with age, gender, race/ethnicity, body mass index (BMI), and number of comorbidities. Of the 8,874 patients included in the cohort, 475 died from COVID-19. Of the 5,356 patients who had information on history of tobacco use, over 26% were current or former tobacco users. Multivariable logistic regression showed that the odds of COVID-19 fatality increased among those who were older (odds ratio = 1.07, 95% CI 1.06, 1.08), male (1.91, 95% CI 1.58, 2.31), and had a history of tobacco use (2.45, 95% CI 1.93, 3.11). History of tobacco use remained significantly associated (1.65, 95% CI 1.27, 2.13) with COVID-19 fatality after adjusting for age, gender, and race/ethnicity. This effort demonstrates the impact of having an HIE to rapidly identify a cohort, aggregate sociodemographic, behavioral, clinical and laboratory data across disparate healthcare providers electronic health record (HER) systems, and follow the cohort over time. These HIE capabilities enable clinical specialists and epidemiologists to conduct outcomes analyses during the current COVID-19 pandemic and beyond. Tobacco use appears to be an important risk factor for COVID-19 related death.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0247235PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8174716PMC
June 2021

Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program.

Am J Hum Genet 2021 05 21;108(5):874-893. Epub 2021 Apr 21.

Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA.

Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.
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http://dx.doi.org/10.1016/j.ajhg.2021.04.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8206199PMC
May 2021

FGL1 as a modulator of plasma D-dimer levels: Exome-wide marker analysis of plasma tPA, PAI-1, and D-dimer.

J Thromb Haemost 2021 08 30;19(8):2019-2028. Epub 2021 May 30.

Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.

Background: Use of targeted exome-arrays with common, rare variants and functionally enriched variation has led to discovery of new genes contributing to population variation in risk factors. Plasminogen activator-inhibitor 1 (PAI-1), tissue plasminogen activator (tPA), and the plasma product D-dimer are important components of the fibrinolytic system. There have been few large-scale genome-wide or exome-wide studies of PAI-1, tPA, and D-dimer.

Objectives: We sought to discover new genetic loci contributing to variation in these traits using an exome-array approach.

Methods: Cohort-level analyses and fixed effects meta-analyses of PAI-1 (n = 15 603), tPA (n = 6876,) and D-dimer (n = 19 306) from 12 cohorts of European ancestry with diverse study design were conducted, including single-variant analyses and gene-based burden testing.

Results: Five variants located in NME7, FGL1, and the fibrinogen locus, all associated with D-dimer levels, achieved genome-wide significance (P < 5 × 10 ). Replication was sought for these 5 variants, as well as 45 well-imputed variants with P < 1 × 10 in the discovery using an independent cohort. Replication was observed for three out of the five significant associations, including a novel and uncommon (0.013 allele frequency) coding variant p.Trp256Leu in FGL1 (fibrinogen-like-1) with increased plasma D-dimer levels. Additionally, a candidate-gene approach revealed a suggestive association for a coding variant (rs143202684-C) in SERPINB2, and suggestive associations with consistent effect in the replication analysis include an intronic variant (rs11057830-A) in SCARB1 associated with increased D-dimer levels.

Conclusion: This work provides new evidence for a role of FGL1 in hemostasis.
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http://dx.doi.org/10.1111/jth.15345DOI Listing
August 2021

A System for Phenotype Harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program.

Am J Epidemiol 2021 Apr 16. Epub 2021 Apr 16.

Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington.

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data sharing mechanisms. This system was developed for the National Heart, Lung and Blood Institute's Trans-Omics for Precision Medicine program, which is generating genomic and other omics data for >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 studies per phenotype (participants recruited 1948-2012). We discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled-access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include (1) the code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms.
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http://dx.doi.org/10.1093/aje/kwab115DOI Listing
April 2021

Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure.

Mol Psychiatry 2021 Apr 15. Epub 2021 Apr 15.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 P < 5 × 10), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (P < 5 × 10). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (P = 2 × 10). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (P < 10). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.
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http://dx.doi.org/10.1038/s41380-021-01087-0DOI Listing
April 2021

Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices.

Nat Commun 2021 04 12;12(1):2182. Epub 2021 Apr 12.

Division of Cardiology, George Washington University School of Medicine and Healthcare Sciences, Washington, DC, USA.

Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.
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http://dx.doi.org/10.1038/s41467-021-22339-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8042019PMC
April 2021

Association between ABO haplotypes and the risk of venous thrombosis: impact on disease risk estimation.

Blood 2021 Apr;137(17):2394-2402

Aix Marseille University, INSERM, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (INRAE), Centre de Recherche en CardioVasculaire et Nutrition, Marseille, France.

Genetic risk score (GRS) analysis is a popular approach to derive individual risk prediction models for complex diseases. In venous thrombosis (VT), such type of analysis shall integrate information at the ABO blood group locus, which is one of the major susceptibility loci. However, there is no consensus about which single nucleotide polymorphisms (SNPs) must be investigated when properly assessing association between ABO locus and VT risk. Using comprehensive haplotype analyses of ABO blood group tagging SNPs in 5425 cases and 8445 controls from 6 studies, we demonstrate that using only rs8176719 (tagging O1) to correctly assess the impact of ABO locus on VT risk is suboptimal, because 5% of rs8176719-delG carriers do not have an increased risk of developing VT. Instead, we recommend the use of 4 SNPs, rs2519093 (tagging A1), rs1053878 (A2), rs8176743 (B), and rs41302905 (O2), when assessing the impact of ABO locus on VT risk to avoid any risk misestimation. Compared with the O1 haplotype, the A2 haplotype is associated with a modest increase in VT risk (odds ratio, ∼1.2), the A1 and B haplotypes are associated with an ∼1.8-fold increased risk, whereas the O2 haplotype tends to be slightly protective (odds ratio, ∼0.80). In addition, although the A1 and B blood groups are associated with increased von Willebrand factor and factor VIII plasma levels, only the A1 blood group is associated with ICAM levels, but in an opposite direction, leaving additional avenues to be explored to fully understand the spectrum of biological effects mediated by ABO locus on cardiovascular traits.
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http://dx.doi.org/10.1182/blood.2020008997DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085481PMC
April 2021

Lifestyle Risk Score: handling missingness of individual lifestyle components in meta-analysis of gene-by-lifestyle interactions.

Eur J Hum Genet 2021 May 26;29(5):839-850. Epub 2021 Jan 26.

Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.

Recent studies consider lifestyle risk score (LRS), an aggregation of multiple lifestyle exposures, in identifying association of gene-lifestyle interaction with disease traits. However, not all cohorts have data on all lifestyle factors, leading to increased heterogeneity in the environmental exposure in collaborative meta-analyses. We compared and evaluated four approaches (Naïve, Safe, Complete and Moderator Approaches) to handle the missingness in LRS-stratified meta-analyses under various scenarios. Compared to "benchmark" results with all lifestyle factors available for all cohorts, the Complete Approach, which included only cohorts with all lifestyle components, was underpowered due to lower sample size, and the Naïve Approach, which utilized all available data and ignored the missingness, was slightly inflated. The Safe Approach, which used all data in LRS-exposed group and only included cohorts with all lifestyle factors available in the LRS-unexposed group, and the Moderator Approach, which handled missingness via moderator meta-regression, were both slightly conservative and yielded almost identical p values. We also evaluated the performance of the Safe Approach under different scenarios. We observed that the larger the proportion of cohorts without missingness included, the more accurate the results compared to "benchmark" results. In conclusion, we generally recommend the Safe Approach, a straightforward and non-inflated approach, to handle heterogeneity among cohorts in the LRS based genome-wide interaction meta-analyses.
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http://dx.doi.org/10.1038/s41431-021-00808-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8110957PMC
May 2021

A Mendelian randomization of γ' and total fibrinogen levels in relation to venous thromboembolism and ischemic stroke.

Blood 2020 12;136(26):3062-3069

Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX.

Fibrinogen is a key component of the coagulation cascade, and variation in its circulating levels may contribute to thrombotic diseases, such as venous thromboembolism (VTE) and ischemic stroke. Gamma prime (γ') fibrinogen is an isoform of fibrinogen that has anticoagulant properties. We applied 2-sample Mendelian randomization (MR) to estimate the causal effect of total circulating fibrinogen and its isoform, γ' fibrinogen, on risk of VTE and ischemic stroke subtypes using summary statistics from genome-wide association studies. Genetic instruments for γ' fibrinogen and total fibrinogen were selected, and the inverse-variance weighted MR approach was used to estimate causal effects in the main analysis, complemented by sensitivity analyses that are more robust to the inclusion of pleiotropic variants, including MR-Egger, weighted median MR, and weighted mode MR. The main inverse-variance weighted MR estimates based on a combination of 16 genetic instruments for γ' fibrinogen and 75 genetic instruments for total fibrinogen indicated a protective effect of higher γ' fibrinogen and higher total fibrinogen on VTE risk. There was also a protective effect of higher γ' fibrinogen levels on cardioembolic and large artery stroke risk. Effect estimates were consistent across sensitivity analyses. Our results provide evidence to support effects of genetically determined γ' fibrinogen on VTE and ischemic stroke risk. Further research is needed to explore mechanisms underlying these effects and their clinical applications.
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http://dx.doi.org/10.1182/blood.2019004781DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7770565PMC
December 2020

Genetic loci associated with prevalent and incident myocardial infarction and coronary heart disease in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

PLoS One 2020 13;15(11):e0230035. Epub 2020 Nov 13.

The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California, United States of America.

Background: Genome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome.

Methods And Results: Using samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 × 10-7). We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) ≥ 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event.

Conclusion: This study identified one known locus (ANGPTL4) and four new loci (PLCL1, RC3H2, TMPRSS5, and LDLRAD1) associated with cardiovascular disease risk that warrant further investigation.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0230035PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665790PMC
December 2020

Mendelian Randomization Analysis of Hemostatic Factors and Their Contribution to Peripheral Artery Disease-Brief Report.

Arterioscler Thromb Vasc Biol 2021 01 27;41(1):380-386. Epub 2020 Aug 27.

Corporal Michael J. Crescenz VA Medical Center, PA (A.M.S., K.-M.C., S.M.D.).

Background And Objective: Peripheral artery disease (PAD) is the third most common form of atherosclerotic vascular disease and is characterized by significant functional disability and increased cardiovascular mortality. Recent genetic data support a role for a procoagulation protein variant, the factor V Leiden mutation, in PAD. The role of other hemostatic factors in PAD remains unknown. We evaluated the role of hemostatic factors in PAD using Mendelian randomization. Approach and Results: Two-sample Mendelian randomization to evaluate the roles of FVII (factor VII), FVIII (factor VIII), FXI (factor XI), VWF (von Willebrand factor), and fibrinogen in PAD was performed using summary statistics from GWAS for hemostatic factors performed within the Cohorts for Heart and Aging Research in the Genome Epidemiology Consortium and from GWAS performed for PAD within the Million Veteran Program. Genetically determined FVIII and VWF, but not FVII, FXI, or fibrinogen, were associated with PAD in Mendelian randomization experiments (FVIII: odds ratio, 1.41 [95% CI, 1.23-1.62], =6.0×10, VWF: odds ratio, 1.28 [95% CI, 1.07-1.52], =0.0073). In single variant sensitivity analysis, the locus was the strongest genetic instrument for both FVIII and VWF.

Conclusions: Our results suggest a role for hemostasis, and by extension, thrombosis in PAD. Further study is warranted to determine whether VWF and FVIII independently affect the biology of PAD.
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http://dx.doi.org/10.1161/ATVBAHA.119.313847DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785109PMC
January 2021

The choline transporter Slc44a2 controls platelet activation and thrombosis by regulating mitochondrial function.

Nat Commun 2020 07 13;11(1):3479. Epub 2020 Jul 13.

Aab Cardiovascular Research Institute, Department of Medicine, University of Rochester Medical Center, Rochester, NY, 14642, USA.

Genetic factors contribute to the risk of thrombotic diseases. Recent genome wide association studies have identified genetic loci including SLC44A2 which may regulate thrombosis. Here we show that Slc44a2 controls platelet activation and thrombosis by regulating mitochondrial energetics. We find that Slc44a2 null mice (Slc44a2(KO)) have increased bleeding times and delayed thrombosis compared to wild-type (Slc44a2(WT)) controls. Platelets from Slc44a2(KO) mice have impaired activation in response to thrombin. We discover that Slc44a2 mediates choline transport into mitochondria, where choline metabolism leads to an increase in mitochondrial oxygen consumption and ATP production. Platelets lacking Slc44a2 contain less ATP at rest, release less ATP when activated, and have an activation defect that can be rescued by exogenous ADP. Taken together, our data suggest that mitochondria require choline for maximum function, demonstrate the importance of mitochondrial metabolism to platelet activation, and reveal a mechanism by which Slc44a2 influences thrombosis.
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http://dx.doi.org/10.1038/s41467-020-17254-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359028PMC
July 2020

Deriving stratified effects from joint models investigating gene-environment interactions.

BMC Bioinformatics 2020 Jun 18;21(1):251. Epub 2020 Jun 18.

Department of Computational Biology, USR 3756 CNRS, Institut Pasteur, Paris, France.

Background: Models including an interaction term and performing a joint test of SNP and/or interaction effect are often used to discover Gene-Environment (GxE) interactions. When the environmental exposure is a binary variable, analyses from exposure-stratified models which consist of estimating genetic effect in unexposed and exposed individuals separately can be of interest. In large-scale consortia focusing on GxE interactions in which only the joint test has been performed, it may be challenging to get summary statistics from both exposure-stratified and marginal (i.e not accounting for interaction) models.

Results: In this work, we developed a simple framework to estimate summary statistics in each stratum of a binary exposure and in the marginal model using summary statistics from the "joint" model. We performed simulation studies to assess our estimators' accuracy and examined potential sources of bias, such as correlation between genotype and exposure and differing phenotypic variances within exposure strata. Results from these simulations highlight the high theoretical accuracy of our estimators and yield insights into the impact of potential sources of bias. We then applied our methods to real data and demonstrate our estimators' retained accuracy after filtering SNPs by sample size to mitigate potential bias.

Conclusions: These analyses demonstrated the accuracy of our method in estimating both stratified and marginal summary statistics from a joint model of gene-environment interaction. In addition to facilitating the interpretation of GxE screenings, this work could be used to guide further functional analyses. We provide a user-friendly Python script to apply this strategy to real datasets. The Python script and documentation are available at https://gitlab.pasteur.fr/statistical-genetics/j2s.
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http://dx.doi.org/10.1186/s12859-020-03569-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302007PMC
June 2020

Role of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels.

Circ Genom Precis Med 2020 08 8;13(4):e002772. Epub 2020 Jun 8.

Department of Epidemiology, School of Public Health (L.F.B., J.A.S., W.Z., S.L.R.K.), University of Michigan, Ann Arbor, MI.

Background: Alcohol intake influences plasma lipid levels, and such effects may be moderated by genetic variants. We aimed to characterize the role of aggregated rare and low-frequency protein-coding variants in gene by alcohol consumption interactions associated with fasting plasma lipid levels.

Methods: In the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, fasting plasma triglycerides and high- and low-density lipoprotein cholesterol were measured in 34 153 individuals with European ancestry from 5 discovery studies and 32 277 individuals from 6 replication studies. Rare and low-frequency functional protein-coding variants (minor allele frequency, ≤5%) measured by an exome array were aggregated by genes and evaluated by a gene-environment interaction test and a joint test of genetic main and gene-environment interaction effects. Two dichotomous self-reported alcohol consumption variables, current drinker, defined as any recurrent drinking behavior, and regular drinker, defined as the subset of current drinkers who consume at least 2 drinks per week, were considered.

Results: We discovered and replicated 21 gene-lipid associations at 13 known lipid loci through the joint test. Eight loci (, , , , , , , and ) remained significant after conditioning on the common index single-nucleotide polymorphism identified by previous genome-wide association studies, suggesting an independent role for rare and low-frequency variants at these loci. One significant gene-alcohol interaction on triglycerides in a novel locus was significantly discovered (=6.65×10 for the interaction test) and replicated at nominal significance level (=0.013) in .

Conclusions: In conclusion, this study applied new gene-based statistical approaches and suggested that rare and low-frequency genetic variants interacted with alcohol consumption on lipid levels.
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http://dx.doi.org/10.1161/CIRCGEN.119.002772DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442680PMC
August 2020

Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci.

Mol Psychiatry 2021 Jun 5;26(6):2111-2125. Epub 2020 May 5.

Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21224, USA.

Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 × 10). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.
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http://dx.doi.org/10.1038/s41380-020-0719-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641978PMC
June 2021

Identifying blood pressure loci whose effects are modulated by multiple lifestyle exposures.

Genet Epidemiol 2020 09 29;44(6):629-641. Epub 2020 Mar 29.

Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri.

Although multiple lifestyle exposures simultaneously impact blood pressure (BP) and cardiovascular health, most analysis so far has considered each single lifestyle exposure (e.g., smoking) at a time. Here, we exploit gene-multiple lifestyle exposure interactions to find novel BP loci. For each of 6,254 Framingham Heart Study participants, we computed lifestyle risk score (LRS) value by aggregating the risk of four lifestyle exposures (smoking, alcohol, education, and physical activity) on BP. Using the LRS, we performed genome-wide gene-environment interaction analysis in systolic and diastolic BP using the joint 2 degree of freedom (DF) and 1 DF interaction tests. We identified one genome-wide significant (p < 5 × 10 ) and 11 suggestive (p < 1 × 10 ) loci. Gene-environment analysis using single lifestyle exposures identified only one of the 12 loci. Nine of the 12 BP loci detected were novel. Loci detected by the LRS were located within or nearby genes with biologically plausible roles in the pathophysiology of hypertension, including KALRN, VIPR2, SNX1, and DAPK2. Our results suggest that simultaneous consideration of multiple lifestyle exposures in gene-environment interaction analysis can identify additional loci missed by single lifestyle approaches.
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http://dx.doi.org/10.1002/gepi.22292DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7717887PMC
September 2020

Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations.

PLoS Genet 2019 12 23;15(12):e1008500. Epub 2019 Dec 23.

Genomics Platform, Broad Institute, Cambridge, Massachusetts, United States of America.

Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11-34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count <10 (including singletons) in the imputation target samples, average information content rescued was >86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations.
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http://dx.doi.org/10.1371/journal.pgen.1008500DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6953885PMC
December 2019

Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.

Nat Commun 2019 11 12;10(1):5121. Epub 2019 Nov 12.

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands.

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.
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http://dx.doi.org/10.1038/s41467-019-12958-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851116PMC
November 2019

Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program.

Am J Hum Genet 2019 10 26;105(4):706-718. Epub 2019 Sep 26.

National Heart, Lung, and Blood Institute and Boston University's Framingham Heart Study, Framingham MA 01702, USA; Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20814, USA.

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.
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http://dx.doi.org/10.1016/j.ajhg.2019.08.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6817529PMC
October 2019

Genomic and transcriptomic association studies identify 16 novel susceptibility loci for venous thromboembolism.

Blood 2019 11;134(19):1645-1657

Boston VA Healthcare System, Boston, MA.

Venous thromboembolism (VTE) is a significant contributor to morbidity and mortality. To advance our understanding of the biology contributing to VTE, we conducted a genome-wide association study (GWAS) of VTE and a transcriptome-wide association study (TWAS) based on imputed gene expression from whole blood and liver. We meta-analyzed GWAS data from 18 studies for 30 234 VTE cases and 172 122 controls and assessed the association between 12 923 718 genetic variants and VTE. We generated variant prediction scores of gene expression from whole blood and liver tissue and assessed them for association with VTE. Mendelian randomization analyses were conducted for traits genetically associated with novel VTE loci. We identified 34 independent genetic signals for VTE risk from GWAS meta-analysis, of which 14 are newly reported associations. This included 11 newly associated genetic loci (C1orf198, PLEK, OSMR-AS1, NUGGC/SCARA5, GRK5, MPHOSPH9, ARID4A, PLCG2, SMG6, EIF5A, and STX10) of which 6 replicated, and 3 new independent signals in 3 known genes. Further, TWAS identified 5 additional genetic loci with imputed gene expression levels differing between cases and controls in whole blood (SH2B3, SPSB1, RP11-747H7.3, RP4-737E23.2) and in liver (ERAP1). At some GWAS loci, we found suggestive evidence that the VTE association signal for novel and previously known regions colocalized with expression quantitative trait locus signals. Mendelian randomization analyses suggested that blood traits may contribute to the underlying risk of VTE. To conclude, we identified 16 novel susceptibility loci for VTE; for some loci, the association signals are likely mediated through gene expression of nearby genes.
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http://dx.doi.org/10.1182/blood.2019000435DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6871304PMC
November 2019

Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls.

Nature 2019 06 22;570(7759):71-76. Epub 2019 May 22.

Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, South Korea.

Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10) and candidate genes from knockout mice (P = 5.2 × 10). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.
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http://dx.doi.org/10.1038/s41586-019-1231-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6699738PMC
June 2019

Serum metabolic signatures of coronary and carotid atherosclerosis and subsequent cardiovascular disease.

Eur Heart J 2019 09;40(34):2883-2896

Section on Cardiovascular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA.

Aims: To characterize serum metabolic signatures associated with atherosclerosis in the coronary or carotid arteries and subsequently their association with incident cardiovascular disease (CVD).

Methods And Results: We used untargeted one-dimensional (1D) serum metabolic profiling by proton nuclear magnetic resonance spectroscopy (1H NMR) among 3867 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), with replication among 3569 participants from the Rotterdam and LOLIPOP studies. Atherosclerosis was assessed by coronary artery calcium (CAC) and carotid intima-media thickness (IMT). We used multivariable linear regression to evaluate associations between NMR features and atherosclerosis accounting for multiplicity of comparisons. We then examined associations between metabolites associated with atherosclerosis and incident CVD available in MESA and Rotterdam and explored molecular networks through bioinformatics analyses. Overall, 30 1H NMR measured metabolites were associated with CAC and/or IMT, P = 1.3 × 10-14 to 1.0 × 10-6 (discovery) and P = 5.6 × 10-10 to 1.1 × 10-2 (replication). These associations were substantially attenuated after adjustment for conventional cardiovascular risk factors. Metabolites associated with atherosclerosis revealed disturbances in lipid and carbohydrate metabolism, branched chain, and aromatic amino acid metabolism, as well as oxidative stress and inflammatory pathways. Analyses of incident CVD events showed inverse associations with creatine, creatinine, and phenylalanine, and direct associations with mannose, acetaminophen-glucuronide, and lactate as well as apolipoprotein B (P < 0.05).

Conclusion: Metabolites associated with atherosclerosis were largely consistent between the two vascular beds (coronary and carotid arteries) and predominantly tag pathways that overlap with the known cardiovascular risk factors. We present an integrated systems network that highlights a series of inter-connected pathways underlying atherosclerosis.
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http://dx.doi.org/10.1093/eurheartj/ehz235DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7963131PMC
September 2019

Mendelian randomization evaluation of causal effects of fibrinogen on incident coronary heart disease.

PLoS One 2019 10;14(5):e0216222. Epub 2019 May 10.

Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.

Background: Fibrinogen is an essential hemostatic factor and cardiovascular disease risk factor. Early attempts at evaluating the causal effect of fibrinogen on coronary heart disease (CHD) and myocardial infraction (MI) using Mendelian randomization (MR) used single variant approaches, and did not take advantage of recent genome-wide association studies (GWAS) or multi-variant, pleiotropy robust MR methodologies.

Methods And Findings: We evaluated evidence for a causal effect of fibrinogen on both CHD and MI using MR. We used both an allele score approach and pleiotropy robust MR models. The allele score was composed of 38 fibrinogen-associated variants from recent GWAS. Initial analyses using the allele score used a meta-analysis of 11 European-ancestry prospective cohorts, free of CHD and MI at baseline, to examine incidence CHD and MI. We also applied 2 sample MR methods with data from a prevalent CHD and MI GWAS. Results are given in terms of the hazard ratio (HR) or odds ratio (OR), depending on the study design, and associated 95% confidence interval (CI). In single variant analyses no causal effect of fibrinogen on CHD or MI was observed. In multi-variant analyses using incidence CHD cases and the allele score approach, the estimated causal effect (HR) of a 1 g/L higher fibrinogen concentration was 1.62 (CI = 1.12, 2.36) when using incident cases and the allele score approach. In 2 sample MR analyses that accounted for pleiotropy, the causal estimate (OR) was reduced to 1.18 (CI = 0.98, 1.42) and 1.09 (CI = 0.89, 1.33) in the 2 most precise (smallest CI) models, out of 4 models evaluated. In the 2 sample MR analyses for MI, there was only very weak evidence of a causal effect in only 1 out of 4 models.

Conclusions: A small causal effect of fibrinogen on CHD is observed using multi-variant MR approaches which account for pleiotropy, but not single variant MR approaches. Taken together, results indicate that even with large sample sizes and multi-variant approaches MR analyses still cannot exclude the null when estimating the causal effect of fibrinogen on CHD, but that any potential causal effect is likely to be much smaller than observed in epidemiological studies.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0216222PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510421PMC
January 2020

Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids.

Nat Genet 2019 04 29;51(4):636-648. Epub 2019 Mar 29.

Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA.

The concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.
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http://dx.doi.org/10.1038/s41588-019-0378-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6467258PMC
April 2019
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