article · Orphanet Journal of Rare Diseases
African genomic data is significantly underrepresented in global databases, which complicates the interpretation of Next Generation Sequencing (NGS) results for diagnosing rare diseases in Africa and its diaspora. This underrepresentation can lead to misclassifying genetic variants as pathogenic due to their novelty or rarity, thereby increasing false positives. To address this, the H3Africa rare diseases working group proposes several actions: making consent for sharing aggregate frequency data a standard research practice, encouraging researchers to share existing African genomic data through public resources, educating participants on the value of data sharing, and increasing funding to generate more geographically and ethno-linguistically representative African genomic data. This initiative aims to reduce health disparities and ensure NGS technologies can effectively benefit African populations.
The lack of African genomic data in global databases creates significant health disparities, making it harder to diagnose and treat rare diseases in African populations. Increasing this data is essential for accurate genetic testing, preventing misdiagnoses, and ensuring that advanced genomic technologies can effectively improve health outcomes across the continent.
The abstract highlights a critical need for increased African genomic data generation and sharing to improve diagnostic accuracy for rare diseases. While it does not indicate a direct commercial application or product, this foundational work is essential for developing future diagnostic tools and guiding therapeutic options that are effective for African populations. It focuses on infrastructure and data availability rather than specific market-ready solutions.
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The rich and diverse genomics of African populations is significantly underrepresented in reference and in disease-associated databases. This renders interpreting the Next Generation Sequencing (NGS) data and reaching a diagnostic more difficult in Africa and for the African diaspora. It increases chances for false positives with variants being misclassified as pathogenic due to their novelty or rarity. We can increase African genomic data by (1) making consent for sharing aggregate frequency data an essential component of research toolkit; (2) encouraging investigators with African data to share available data through public resources such as gnomAD, AVGD, ClinVar, DECIPHER and to use MatchMaker Exchange; (3) educating African research participants on the meaning and value of sharing aggregate frequency data; and (4) increasing funding to scale-up the production of African genomic data that will be more representative of the geographical and ethno-linguistic variation on the continent. The RDWG of H3Africa is hereby calling to action because this underrepresentation accentuates the health disparities. Applying the NGS to shorten the diagnostic odyssey or to guide therapeutic options for rare diseases will fully work for Africans only when public repositories include sufficient data from African subjects.
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DOI: 10.1186/s13023-022-02391-w
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