Whole-Genome Analysis of Plasma Fibrinogen Reveals Population-Differentiated Genetic Regulators with Potential Liver Roles

Academic Background

Fibrinogen is a crucial coagulation factor and acute-phase reactive protein. Under normal physiological conditions, fibrinogen is abundant in circulation, but during the acute inflammatory response, transcriptional cascades mediated by interleukin-6 (IL-6) and IL-1 can increase its levels up to threefold above baseline. Fibrinogen levels are also clinical predictors of thrombotic diseases such as coronary heart disease, myocardial infarction, venous thromboembolism, and ischemic stroke. While animal models have established a causal relationship between fibrinogen and thrombosis, confirming this in human genetic studies has proven challenging.

Heritability of fibrinogen levels is estimated to range between 21% and 67%, with most estimates between 30% and 50%, and contributions differing between populations. African Americans reportedly have higher baseline fibrinogen levels, and their fibrinogen heritability may also exceed that of non-Hispanic Whites. While genome-wide and exome-wide sequencing studies have already identified several loci associated with fibrinogen levels, these variants explain a maximum of 3.7% of the variance in European populations. Little is known about the genetic regulation of fibrinogen across diverse populations.

Unlike genotyping arrays that are optimized for common European variants, whole-genome sequencing (WGS) allows untargeted genomic analysis across all populations. By improving power to detect associations with rare and low-frequency variants and distinguishing multiple signals within the same region, WGS reveals insights that may otherwise go undetected. This study integrates WGS data from the National Heart, Lung, and Blood Institute’s (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program with genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. The objective is to identify new genetic variants associated with circulating fibrinogen levels.

Source of the Paper

This paper was authored by Jennifer E. Huffman, Jayna Nicholas, Julie Hahn, and others from multiple research institutions. It was published in the November 21, 2024, issue of the journal Blood (Vol. 144, Issue 21). The research team includes members from prestigious organizations such as the Palo Alto VA Institute for Research, University of North Carolina at Chapel Hill, and University of Texas Health Science Center at Houston, among others.

Methodology

1. Study Design and Sample Population

The study employed population-wide genome-wide association studies (GWAS), transcriptome-wide association studies (TWAS), and phenome-wide association studies (PheWAS) to investigate the genetic architecture underlying circulating fibrinogen levels. A total of 163,912 participants were included, comprising 11,283 African ancestry, 741 Asian ancestry, 149,619 European ancestry, and 2,061 Hispanic ancestry individuals. Fibrinogen levels were measured using methods such as the Clauss assay or immunoturbidimetry.

2. Whole-Genome Sequencing and Genotyping

WGS was conducted by TOPMed at six sequencing centers, with an average sequencing depth greater than 30×. Genotype data for non-TOPMed studies was imputed using either the TOPMed or the Haplotype Reference Consortium (HRC) reference panel.

3. Data Analysis

• Single-Variant Analysis: Mixed models were used for single-variant testing, adjusting for age, sex, ancestry group, sequencing phases, and study-specific factors.
• Conditional Analysis: Conditional analysis was performed using COJO-SLCT to compute 95% credible sets for variant prioritization.
• Functional Annotation: Functional annotation of variants used the Ensembl Variant Effect Predictor (VEP), which predicted missense mutations and regulatory variants.
• Colocalization Analysis: Colocalization analyses leveraging FASTENLOC identified shared genetic signals between fibrinogen and transcript expression levels in various tissues.
• Transcriptome Association: TWAS was conducted using S-PrediXcan to pinpoint genetic regulators of fibrinogen in related tissues such as the liver, blood, and arteries.
• Phenome-Wide Association: PheWAS was conducted in the Veterans Affairs Million Veteran Program (MVP) using polygenic risk scores (PRS) to examine associations between fibrinogen and thrombotic- or inflammation-related phenotypes.

Key Results

1. Single-Variant Analysis

Across multiple populations, the single-variant analysis identified 54 loci associated with circulating fibrinogen, 18 of which were newly discovered. These loci contained 69 distinct variants, 20 being novel. Seven distinct signals emerged within the fibrinogen gene cluster (FGG, FGB, FGA), including one driven by a variant (rs28577061) common in African ancestry populations but rare in Europeans.

2. Functional Annotation

Many signals overlapped with variants previously associated with liver enzymes, lipids, and blood cell traits. Notably, 23 signals overlapped with known variants for C-reactive protein. Eighteen signals contained at least one missense variant, and thirteen contained predicted deleterious mutations. Most signals overlapped regulatory elements active in hepatocytes, suggesting potential liver-specific regulation.

3. Colocalization Analysis

Colocalization analysis identified 153 variant-tissue pairs with evidence of shared genetic architecture, indicating that the expression of 93 specific genes might influence fibrinogen levels. Strong statistical colocalization was detected in five regions, particularly in liver tissues.

4. Transcriptome-Wide Association Study

TWAS implicated 64 gene-tissue pairs in fibrinogen regulation. Fine-mapping prioritized 15 gene-tissue pairs, including TNKS in liver and several other genes in blood (e.g., AFT1, MS4A4E). Many of these genes also showed evidence of colocalization, adding confidence to their regulatory roles.

5. Phenome-Wide Association Results

The PheWAS identified consistent associations between fibrinogen PRS and thrombotic disorders, such as venous thromboembolism, as well as inflammatory phenotypes such as gout. Notably, removing variants from the FGG region in PRS analysis shifted the significance of associations between fibrinogen and thrombotic traits, suggesting distinct roles for fibrinogen isoforms.

Conclusion

This study utilized WGS and genotype imputation to identify 69 independent variants across 54 loci associated with fibrinogen. Among these, 18 are novel loci, including the first common variant driven by African ancestry participants. Several variants overlapped with liver regulatory elements, suggesting involvement in metabolic and inflammatory pathways. These results provide new insights into the genetic architecture of fibrinogen regulation and demonstrate the utility of diverse population studies for understanding its biology.

Study Highlights

• Novel Genetic Variants: Identified 18 new loci and 20 novel variants, providing deeper insights into fibrinogen’s regulatory mechanisms.
• Non-European Contributions: Several variants were discovered predominantly in African ancestry populations, addressing gaps in representation from previous studies.
• Liver-Specific Mechanisms: Many signals localized to regulatory elements active in the liver, indicating fibrinogen regulation may primarily involve hepatocyte pathways.
• Clinical Implications: Associations with thrombotic and inflammatory phenotypes, such as venous embolism and gout, highlight fibrinogen’s potential clinical significance.

Significance of Findings

The integration of large-scale WGS and imputed genotyping data has uncovered novel fibrinogen genetic regulators, particularly in underrepresented populations. These findings offer a foundation for future studies into the biology of fibrinogen, providing potential targets for functional validation and therapeutic exploration.