Replication and characterisation of genetic variants in the fibrinogen gene cluster with plasma fibrinogen levels and haematological traits in the Third National Health and Nutrition Examination Survey

Association between genetic polymorphisms in fibrinogen genes and bleeding risk in patients treated with direct oral anticoagulants

Introduction

This study aimed to investigate the association between polymorphisms in fibrinogen genes and bleeding risk in patients receiving direct oral anticoagulants (DOACs).

Method

Patients treated with DOACs from June 2018 to December 2021 were enrolled in the study. Genotyping was done for rs2070011, rs6050, and rs2070022 in fibrinogen alpha chain (FGA); rs1800788, rs4220, and rs4463047 in fibrinogen beta chain (FGB); and rs2066865 and rs1800792 in fibrinogen gamma chain (FGG), along with F2 rs5896 and F10 rs5960. Multivariable logistic regression analysis was performed to investigate the risk factors for bleeding and to develop a risk scoring system.

Results

A total of 468 patients were included in the analysis, 14 of whom experienced major bleeding and 36 experienced clinically relevant non-major bleeding. In the multivariable analysis, overdose, anaemia, F2 rs5896, and FGG rs1800792 were found to be significantly associated with bleeding risk. Specifically, patients with the TT genotype of F2 rs5896 and the CC genotype of FGG rs1800792 had 2.1 times (95% confidence interval [CI] 1.1-3.9) and 2.7 times (95% CI 1.2-5.9) higher bleeding risk than the C allele and T allele carriers, respectively. Based on the risk scoring system, patients with 0, 1, 2, 3, 4, and 5 points were predicted to have 5.2%, 10.8%, 22.4%, 32.3%, 42.3%, and 61.8% of bleeding risk, respectively.

Conclusion

To our knowledge, this is the first study to investigate the effects of polymorphisms in fibrinogen genes on DOAC response. After validation, these results will be useful for personalised DOAC therapy.

Genetic Polymorphisms Associated with Spontaneous Intracerebral Hemorrhage

Differences in the incidence of spontaneous intracerebral hemorrhage (ICH) between ethnicities exist, with an estimated 42% of the variance explained by ethnicity itself. Caucasians have a higher proportion of lobar ICH (LICH, 15.4% of all ICH) than do Asians (3.4%). Alterations in the causal factor exposure between countries justify part of the ethnic variance in ICH incidence. One third of ICH risk can be explained by genetic variation; therefore, genetic differences between populations can partly explain the difference in ICH incidence. In this paper, we review the current knowledge of genetic variants associated with ICH in multiple ethnicities. Candidate gene variants reportedly associated with ICH were involved in the potential pathways of hypertension, vessel wall integrity, lipid metabolism, endothelial dysfunction, inflammation, platelet function, and coagulopathy. Furthermore, variations in APOE (in multiple ethnicities), PMF1/SLC25A44 (in European), ACE (in Asian), MTHFR (in multiple ethnicities), TRHDE (in European), and COL4A2 (in European) were the most convincingly associated with ICH. The majority of the associated genes provide small contributions to ICH risk, with few of them being replicated in multiple ethnicities.

Cardiovascular Health in African Americans: A Scientific Statement From the American Heart Association

BACKGROUND AND PURPOSE

Population-wide reductions in cardiovascular disease incidence and mortality have not been shared equally by African Americans. The burden of cardiovascular disease in the African American community remains high and is a primary cause of disparities in life expectancy between African Americans and whites. The objectives of the present scientific statement are to describe cardiovascular health in African Americans and to highlight unique considerations for disease prevention and management.

METHOD

The primary sources of information were identified with PubMed/Medline and online sources from the Centers for Disease Control and Prevention.

RESULTS

The higher prevalence of traditional cardiovascular risk factors (eg, hypertension, diabetes mellitus, obesity, and atherosclerotic cardiovascular risk) underlies the relatively earlier age of onset of cardiovascular diseases among African Americans. Hypertension in particular is highly prevalent among African Americans and contributes directly to the notable disparities in stroke, heart failure, and peripheral artery disease among African Americans. Despite the availability of effective pharmacotherapies and indications for some tailored pharmacotherapies for African Americans (eg, heart failure medications), disease management is less effective among African Americans, yielding higher mortality. Explanations for these persistent disparities in cardiovascular disease are multifactorial and span from the individual level to the social environment.

CONCLUSIONS

The strategies needed to promote equity in the cardiovascular health of African Americans require input from a broad set of stakeholders, including clinicians and researchers from across multiple disciplines.

Population Stratification in the Context of Diverse Epidemiologic Surveys Sans Genome-Wide Data

Population stratification or confounding by genetic ancestry is a potential cause of false associations in genetic association studies. Estimation of and adjustment for genetic ancestry has become common practice thanks in part to the availability of ancestry informative markers on genome-wide association study (GWAS) arrays. While array data is now widespread, these data are not ubiquitous as several large epidemiologic and clinic-based studies lack genome-wide data. One such large epidemiologic-based study lacking genome-wide data accessible to investigators is the National Health and Nutrition Examination Surveys (NHANES), population-based cross-sectional surveys of Americans linked to demographic, health, and lifestyle data conducted by the Centers for Disease Control and Prevention. DNA samples (n = 14,998) were extracted from biospecimens from consented NHANES participants between 1991-1994 (NHANES III, phase 2) and 1999-2002 and represent three major self-identified racial/ethnic groups: non-Hispanic whites (n = 6,634), non-Hispanic blacks (n = 3,458), and Mexican Americans (n = 3,950). We as the Epidemiologic Architecture for Genes Linked to Environment study genotyped candidate gene and GWAS-identified index variants in NHANES as part of the larger Population Architecture using Genomics and Epidemiology I study for collaborative genetic association studies. To enable basic quality control such as estimation of genetic ancestry to control for population stratification in NHANES san genome-wide data, we outline here strategies that use limited genetic data to identify the markers optimal for characterizing genetic ancestry. From among 411 and 295 autosomal SNPs available in NHANES III and NHANES 1999-2002, we demonstrate that markers with ancestry information can be identified to estimate global ancestry. Despite limited resolution, global genetic ancestry is highly correlated with self-identified race for the majority of participants, although less so for ethnicity. Overall, the strategies outlined here for a large epidemiologic study can be applied to other datasets accessible for genotype-phenotype studies but are sans genome-wide data.

Cryptic relatedness in epidemiologic collections accessed for genetic association studies: experiences from the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study and the National Health and Nutrition Examination Surveys (NHANES)

Epidemiologic collections have been a major resource for genotype-phenotype studies of complex disease given their large sample size, racial/ethnic diversity, and breadth and depth of phenotypes, traits, and exposures. A major disadvantage of these collections is they often survey households and communities without collecting extensive pedigree data. Failure to account for substantial relatedness can lead to inflated estimates and spurious associations. To examine the extent of cryptic relatedness in an epidemiologic collection, we as the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study accessed the National Health and Nutrition Examination Surveys (NHANES) linked to DNA samples ("Genetic NHANES") from NHANES III and NHANES 1999-2002. NHANES are population-based cross-sectional surveys conducted by the National Center for Health Statistics at the Centers for Disease Control and Prevention. Genome-wide genetic data is not yet available in NHANES, and current data use agreements prohibit the generation of GWAS-level data in NHANES samples due issues in maintaining confidentiality among other ethical concerns. To date, only hundreds of single nucleotide polymorphisms (SNPs) genotyped in a variety of candidate genes are available for analysis in NHANES. We performed identity-by-descent (IBD) estimates in three self-identified subpopulations of Genetic NHANES (non-Hispanic white, non- Hispanic black, and Mexican American) using PLINK software to identify potential familial relationships from presumed unrelated subjects. We then compared the PLINKidentified relationships to those identified by an alternative method implemented in Kinship-based INference for Genome-wide association studies (KING). Overall, both methods identified familial relationships in NHANES III and NHANES 1999-2002 for all three subpopulations, but little concordance was observed between the two methods due in major part to the limited SNP data available in Genetic NHANES. Despite the lack of genome-wide data, our results suggest the presence of cryptic relatedness in this epidemiologic collection and highlight the limitations of restricted datasets such as NHANES in the context of modern day genetic epidemiology studies.

Leveraging Epidemiologic and Clinical Collections for Genomic Studies of Complex Traits

BACKGROUND/AIMS

Present-day limited resources demand DNA and phenotyping alternatives to the traditional prospective population-based epidemiologic collections.

METHODS

To accelerate genomic discovery with an emphasis on diverse populations, we--as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study--accessed all non-European American samples (n = 15,863) available in BioVU, the Vanderbilt University biorepository linked to de-identified electronic medical records, for genomic studies as part of the larger Population Architecture using Genomics and Epidemiology (PAGE) I study. Given previous studies have cautioned against the secondary use of clinically collected data compared with epidemiologically collected data, we present here a characterization of EAGLE BioVU, including the billing and diagnostic (ICD-9) code distributions for adult and pediatric patients as well as comparisons made for select health metrics (body mass index, glucose, HbA1c, HDL-C, LDL-C, and triglycerides) with the population-based National Health and Nutrition Examination Surveys (NHANES) linked to DNA samples (NHANES III, n = 7,159; NHANES 1999-2002, n = 7,839).

RESULTS

Overall, the distributions of billing and diagnostic codes suggest this clinical sample is a mixture of healthy and sick patients like that expected for a contemporary American population.

CONCLUSION

Little bias is observed among health metrics, suggesting this clinical collection is suitable for genomic studies along with traditional epidemiologic cohorts.

Identification of gene-gene and gene-environment interactions within the fibrinogen gene cluster for fibrinogen levels in three ethnically diverse populations

Elevated levels of plasma fibrinogen are associated with clot formation in the absence of inflammation or injury and is a biomarker for arterial clotting, the leading cause of cardiovascular disease. Fibrinogen levels are heritable with >50% attributed to genetic factors, however little is known about possible genetic modifiers that might explain the missing heritability. The fibrinogen gene cluster is comprised of three genes (FGA, FGB, and FGG) that make up the fibrinogen polypeptide essential for fibrinogen production in the blood. Given the known interaction with these genes, we tested 25 variants in the fibrinogen gene cluster for gene x gene and gene x environment interactions in 620 non-Hispanic blacks, 1,385 non-Hispanic whites, and 664 Mexican Americans from a cross-sectional dataset enriched with environmental data, the Third National Health and Nutrition Examination Survey (NHANES III). Using a multiplicative approach, we added cross product terms (gene x gene or gene x environment) to a linear regression model and declared significance at p < 0.05. We identified 19 unique gene x gene and 13 unique gene x environment interactions that impact fibrinogen levels in at least one population at p < 0.05. Over 90% of the gene x gene interactions identified include a variant in the rate-limiting gene, FGB that is essential for the formation of the fibrinogen polypeptide. We also detected gene x environment interactions with fibrinogen variants and sex, smoking, and body mass index. These findings highlight the potential for the discovery of genetic modifiers for complex phenotypes in multiple populations and give a better understanding of the interaction between genes and/or the environment for fibrinogen levels. The need for more powerful and robust methods to identify genetic modifiers is still warranted.