Increasing African genomic data generation and sharing to resolve rare and undiagnosed diseases in Africa: a call-to-action by the H3Africa rare diseases working group

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dc.contributor.authorLumaka, Aimé
dc.contributor.authorCarstens, Nadia
dc.contributor.authorDevriendt, Koenraad
dc.contributor.authorKrause, Amanda
dc.contributor.authorKulohoma, Benard
dc.contributor.authorKumuthini, Judit
dc.contributor.authorMubungu, Gerrye
dc.contributor.authorMukisa, John
dc.contributor.authorNel, Melissa
dc.contributor.authorOlanrewaju, Timothy O
dc.contributor.authorLombard, Zané
dc.contributor.authorLandouré, Guida
dc.date.accessioned2022-09-15T11:11:24Z
dc.date.available2022-09-15T11:11:24Z
dc.date.issued2022-06-16
dc.date.updated2022-06-19T03:11:43Z
dc.description.abstractThe 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.en_US
dc.identifier.apacitationLumaka, A., Carstens, N., Devriendt, K., Krause, A., Kulohoma, B., Kumuthini, J., ... Landouré, G. (2022). Increasing African genomic data generation and sharing to resolve rare and undiagnosed diseases in Africa: a call-to-action by the H3Africa rare diseases working group. <i>Orphanet Journal of Rare Diseases</i>, 17(1), 230. http://hdl.handle.net/11427/36812en_ZA
dc.identifier.chicagocitationLumaka, Aimé, Nadia Carstens, Koenraad Devriendt, Amanda Krause, Benard Kulohoma, Judit Kumuthini, Gerrye Mubungu, et al "Increasing African genomic data generation and sharing to resolve rare and undiagnosed diseases in Africa: a call-to-action by the H3Africa rare diseases working group." <i>Orphanet Journal of Rare Diseases</i> 17, 1. (2022): 230. http://hdl.handle.net/11427/36812en_ZA
dc.identifier.citationLumaka, A., Carstens, N., Devriendt, K., Krause, A., Kulohoma, B., Kumuthini, J., Mubungu, G. & Mukisa, J. et al. 2022. Increasing African genomic data generation and sharing to resolve rare and undiagnosed diseases in Africa: a call-to-action by the H3Africa rare diseases working group. <i>Orphanet Journal of Rare Diseases.</i> 17(1):230. http://hdl.handle.net/11427/36812en_ZA
dc.identifier.ris TY - Journal Article AU - Lumaka, Aimé AU - Carstens, Nadia AU - Devriendt, Koenraad AU - Krause, Amanda AU - Kulohoma, Benard AU - Kumuthini, Judit AU - Mubungu, Gerrye AU - Mukisa, John AU - Nel, Melissa AU - Olanrewaju, Timothy O AU - Lombard, Zané AU - Landouré, Guida AB - 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. DA - 2022-06-16 DB - OpenUCT DP - University of Cape Town IS - 1 J1 - Orphanet Journal of Rare Diseases KW - Data sharing KW - NGS interpretation KW - Diversity KW - Reference database LK - https://open.uct.ac.za PY - 2022 T1 - Increasing African genomic data generation and sharing to resolve rare and undiagnosed diseases in Africa: a call-to-action by the H3Africa rare diseases working group TI - Increasing African genomic data generation and sharing to resolve rare and undiagnosed diseases in Africa: a call-to-action by the H3Africa rare diseases working group UR - http://hdl.handle.net/11427/36812 ER - en_ZA
dc.identifier.urihttps://doi.org/10.1186/s13023-022-02391-w
dc.identifier.urihttp://hdl.handle.net/11427/36812
dc.identifier.vancouvercitationLumaka A, Carstens N, Devriendt K, Krause A, Kulohoma B, Kumuthini J, et al. Increasing African genomic data generation and sharing to resolve rare and undiagnosed diseases in Africa: a call-to-action by the H3Africa rare diseases working group. Orphanet Journal of Rare Diseases. 2022;17(1):230. http://hdl.handle.net/11427/36812.en_ZA
dc.language.isoenen_US
dc.language.rfc3066en
dc.publisher.departmentDivision of Neurologyen_US
dc.publisher.facultyFaculty of Health Sciencesen_US
dc.rights.holderThe Author(s)
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourceOrphanet Journal of Rare Diseasesen_US
dc.source.journalissue1en_US
dc.source.journalvolume17en_US
dc.source.pagination230en_US
dc.source.urihttps://ojrd.biomedcentral.com/
dc.subjectData sharingen_US
dc.subjectNGS interpretationen_US
dc.subjectDiversityen_US
dc.subjectReference databaseen_US
dc.titleIncreasing African genomic data generation and sharing to resolve rare and undiagnosed diseases in Africa: a call-to-action by the H3Africa rare diseases working groupen_US
dc.typeJournal Articleen_US
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