Ancestry gaps in cardiovascular GWAS: a multi-database review of African representation in genomic studies

TL;DR

This paper reviews how genetic studies on heart disease mostly focus on European populations, leaving African populations underrepresented and affecting treatment effectiveness.

Contribution

The paper provides a multi-database analysis highlighting the lack of African representation in cardiovascular genomic research.

Findings

Genetic studies on cardiovascular diseases are predominantly based on European ancestry populations.

African ancestry populations have higher genetic diversity not well captured by current datasets.

There is a need for improved representation to enhance diagnosis and treatment effectiveness in underrepresented groups.

Abstract

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, claiming millions of lives each year. Genome-wide association studies (GWASs) have identified thousands of CVD-associated variants and have created the foundation for risk assessment and prevention through genetic testing. However, despite all the progress in understanding cardiovascular genomics, our genetic research and findings are overwhelmingly skewed towards individuals of European ancestry. This fact has limited our understanding and effectiveness for the diagnosis and treatment of CVDs in underrepresented populations, such as individuals of African ancestry. This gap is especially consequential because African ancestry populations harbor the greatest global genetic diversity, with variant frequencies and haplotypes that are often poorly captured by current reference datasets. In this review, we highlight recent efforts to understand the effectiveness of current tools in accurately diagnosing and treating CVDs in individuals of African ancestry compared to other populations. Additionally, we also performed a multi-database analysis to explore the persistent diversity gap in cardiovascular genetics. In doing so, we aim to raise awareness about the ancestry gaps faced in disease genomic research, supported by recent findings and the current landscape of our genetic databases.

Figures