1932

Abstract

To embrace the prospects of accurately diagnosing thousands of monogenic conditions, predicting disease risks for complex traits or diseases, tailoring treatment to individuals’ pharmacogenetic profiles, and potentially curing some diseases, research into African genomic variation is a scientific imperative. African genomes harbor millions of uncaptured variants accumulated over 300,000 years of modern humans’ evolutionary history, with successive waves of admixture, migration, and natural selection combining with extensive ecological diversity to create a broad and exceptional genomic complexity. Harnessing African genomic complexity, therefore, will require sustained commitment and equitable collaboration from the scientific community and funding agencies. African governments must support academic public research and industrial partnerships that build the necessary genetic medicine workforce, utilize the emerging genomic big data to develop expertise in computer science and bioinformatics, and evolve national and globalgovernance frameworks that recognize the ethical implications of data-driven genomic research and empower its application in African social, cultural, economic, and religious contexts.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-genom-111521-102452
2022-08-31
2024-06-22
Loading full text...

Full text loading...

/deliver/fulltext/genom/23/1/annurev-genom-111521-102452.html?itemId=/content/journals/10.1146/annurev-genom-111521-102452&mimeType=html&fmt=ahah

Literature Cited

  1. 1.
    Abayomi A, Christoffels A, Grewal R, Karam LA, Rossouw C et al. 2013. Challenges of biobanking in South Africa to facilitate indigenous research in an environment burdened with human immunodeficiency virus, tuberculosis, and emerging noncommunicable diseases. Biopreserv. Biobank. 11:347–54
    [Google Scholar]
  2. 2.
    Abimiku A, Mayne ES, Joloba M, Beiswanger CM, Troyer J, Wideroff L. 2017. H3Africa biorepository program: supporting genomics research on African populations by sharing high-quality biospecimens. Biopreserv. Biobank. 15:99–103
    [Google Scholar]
  3. 3.
    Adadey SM, Schrauwen I, Aboagye ET, Bharadwaj T, Esoh KK et al. 2021. Further confirmation of the association of SLC12A2 with non-syndromic autosomal-dominant hearing impairment. J. Hum. Genet. 66:1169–75
    [Google Scholar]
  4. 4.
    Adadey SM, Wonkam-Tingang E, Aboagye ET, Quaye O, Awandare GA, Wonkam A. 2022. Hearing loss in Africa: current genetic profile. Hum. Genet. 141:505–17
    [Google Scholar]
  5. 5.
    Adedokun BO, Olopade CO, Olopade OI. 2016. Building local capacity for genomics research in Africa: recommendations from analysis of publications in Sub-Saharan Africa from 2004 to 2013. Glob. Health Action 9:31026
    [Google Scholar]
  6. 6.
    Adeyemo AA, Zaghloul NA, Chen G, Doumatey AP, Leitch CC et al. 2019. ZRANB3 is an African-specific type 2 diabetes locus associated with beta-cell mass and insulin response. Nat. Commun. 10:3195
    [Google Scholar]
  7. 7.
    Altshuler DL, Durbin RM, Abecasis GR, Bentley DR, Chakravarti A et al. 2010. A map of human genome variation from population-scale sequencing. Nature 467:1061–73
    [Google Scholar]
  8. 8.
    Am. Soc. Hum. Genet. 2021. Mission & strategic plan. American Society of Human Genetics https://www.ashg.org/about/mission-strategic-plan
    [Google Scholar]
  9. 9.
    Appiah-Poku J, Newton S, Kass N 2011. Participants’ perceptions of research benefits in an African genetic epidemiology study. Dev. World Bioeth. 11:128–35
    [Google Scholar]
  10. 10.
    Auton A, Abecasis GR, Altshuler DM, Durbin RM, Bentley DR et al. 2015. A global reference for human genetic variation. Nature 526:68–74
    [Google Scholar]
  11. 11.
    Beck HE, Zimmermann NE, McVicar T, Vergoplan N, Berg A, Wood EF. 2018. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Sci. Data 5:180214 Correction 2020. Sci. Data 7:274
    [Google Scholar]
  12. 12.
    Bielinski SJ, St Sauver JL, Olson JE, Larson NB, Black JL III et al. 2020. Cohort profile: the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment Protocol (RIGHT Protocol). Int. J. Epidemiol. 49:23–24k
    [Google Scholar]
  13. 13.
    Bostoen K. 2018. The Bantu Expansion. The Oxford Research Encyclopedia of African History Oxford, UK: Oxford Univ. Press https://doi.org/10.1093/acrefore/9780190277734.013.191
    [Crossref] [Google Scholar]
  14. 14.
    Bukhman G, Mocumbi AO, Gupta N, Amuyunzu-Nyamongo M, Echodu M et al. 2021. From a Lancet Commission to the NCDI Poverty Network: reaching the poorest billion through integration science. Lancet 398:2217–20
    [Google Scholar]
  15. 15.
    Campbell MC, Tishkoff SA. 2008. African genetic diversity: implications for human demographic history, modern human origins, and complex disease mapping. Annu. Rev. Genom. Hum. Genet. 9:403–33
    [Google Scholar]
  16. 16.
    Cárdenas-Rodríguez N, Carmona-Aparicio L, Pérez-Lozano DL, Ortega-Cuellar D, Gómez-Manzo S, Ignacio-Mejía I. 2020. Genetic variations associated with pharmacoresistant epilepsy (review). Mol. Med. Rep. 21:1685–701
    [Google Scholar]
  17. 17.
    Carr DF, Bourgeois S, Chaponda M, Takeshita LY, Morris AP et al. 2017. Genome-wide association study of nevirapine hypersensitivity in a sub-Saharan African HIV-infected population. J. Antimicrob. Chemother. 72:1152–62
    [Google Scholar]
  18. 18.
    Ceballos FC, Hazelhurst S, Clark DW, Agongo G, Asiki G et al. 2020. Autozygosity influences cardiometabolic disease-associated traits in the AWI-Gen sub-Saharan African study. Nat. Commun. 11:5754
    [Google Scholar]
  19. 19.
    Choudhury A, Aron S, Botigué LR, Sengupta D, Botha G et al. 2020. High-depth African genomes inform human migration and health. Nature 586:741–48
    [Google Scholar]
  20. 20.
    Claussen M, Dallmeyer A, Bader J. 2017. Theory and modeling of the African Humid Period and the Green Sahara. The Oxford Research Encyclopedia of Climate Science Oxford, UK: Oxford Univ. Press https://doi.org/10.1093/acrefore/9780190228620.013.532
    [Crossref] [Google Scholar]
  21. 21.
    Cohen J, Pertsemlidis A, Kotowski IK, Graham R, Garcia CK, Hobbs HH. 2005. Low LDL cholesterol in individuals of African descent resulting from frequent nonsense mutations in PCSK9. Nat. Genet. 37:161–65 Corrigendum 2005. Nat. Genet. 37:328
    [Google Scholar]
  22. 22.
    Colombatti R, Martella M, Cattaneo L, Viola G, Cappellari A et al. 2019. Results of a multicenter universal newborn screening program for sickle cell disease in Italy: a call to action. Pediatr. Blood Cancer 66:e27657
    [Google Scholar]
  23. 23.
    Cooper A, Ilboudo H, Alibu VP, Ravel S, Enyaru J et al. 2017. APOL1 renal risk variants have contrasting resistance and susceptibility associations with African trypanosomiasis. eLife 6:e25461
    [Google Scholar]
  24. 24.
    Creary LE, Ulug P, Menzel S, McKenzie CA, Hanchard NA et al. 2009. Genetic variation on chromosome 6 influences F cell levels in healthy individuals of African descent and HbF levels in sickle cell patients. PLOS ONE 4:e4218
    [Google Scholar]
  25. 25.
    da Rocha JEB, Lombard Z, Ramsay M. 2021. Potential impact of DPYD variation on fluoropyrimidine drug response in sub-Saharan African populations. Front. Genet. 12:626954
    [Google Scholar]
  26. 26.
    Daak AA, Elsamani E, Ali EH, Mohamed FA, Abdel-Rahman ME et al. 2016. Sickle cell disease in western Sudan: genetic epidemiology and predictors of knowledge attitude and practices. Trop. Med. Int. Health 21:642–53
    [Google Scholar]
  27. 27.
    Dai Y, Shaikho EM, Perez J, Wilson CA, Liu LY et al. 2019. BCL2L1 is associated with γ-globin gene expression. Blood Adv 3:2995–3001
    [Google Scholar]
  28. 28.
    Dandara C, Masimirembwa C, Haffani YZ, Ogutu B, Mabuka J et al. 2019. African Pharmacogenomics Consortium: consolidating pharmacogenomics knowledge, capacity development and translation in Africa. AAS Open Res 2:19
    [Google Scholar]
  29. 29.
    Dandara C, Swart M, Mpeta B, Wonkam A, Masimirembwa C. 2014. Cytochrome p450 pharmacogenetics in African populations: implications for public health. Expert Opin. Drug Metab. Toxicol. 10:769–85
    [Google Scholar]
  30. 30.
    Dauda B, Joffe S. 2018. The benefit sharing vision of H3Africa. Dev. World Bioeth. 18:165–70
    [Google Scholar]
  31. 31.
    de Vries J, Landouré G, Wonkam A. 2020. Stigma in African genomics research: gendered blame, polygamy, ancestry and disease causal beliefs impact on the risk of harm. Soc. Sci. Med. 258:113091
    [Google Scholar]
  32. 32.
    Durvasula A, Sankararaman S. 2020. Recovering signals of ghost archaic introgression in African populations. Sci. Adv. 6:5097
    [Google Scholar]
  33. 33.
    El-Kamah GY, Mohamed AM, Gad YZ, Abdelhak S, Hennig BJ et al. 2020. Developing a road map to spread genomic knowledge in Africa: 10th Conference of the African Society of Human Genetics, Cairo, Egypt. Am. J. Trop. Med. Hyg. 102:719–23
    [Google Scholar]
  34. 34.
    Erwin ER, Addison AP, John SF, Olaleye OA, Rosell RC. 2019. Pharmacokinetics of isoniazid: the good, the bad, and the alternatives. Tuberculosis 116:S66–70
    [Google Scholar]
  35. 35.
    Esoh KK, Apinjoh TO, Nyanjom SG, Wonkam A, Chimusa ER et al. 2021. Fine scale human genetic structure in three regions of Cameroon reveals episodic diversifying selection. Sci. Rep. 11:1039
    [Google Scholar]
  36. 36.
    Esoh KK, Wonkam A. 2021. Evolutionary history of sickle cell mutation: implications for global genetic medicine. Hum. Mol. Genet. 30:R119–28
    [Google Scholar]
  37. 37.
    Feero WG, Guttmacher AE, Collins FS. 2010. Genomic medicine—an updated primer. N. Engl. J. Med. 362:2001–11
    [Google Scholar]
  38. 38.
    Galarneau G, Palmer CD, Sankaran VG, Orkin SH, Hirschhorn JN, Lettre G. 2010. Fine-mapping at three loci known to affect fetal hemoglobin levels explains additional genetic variation. Nat. Genet. 42:1049–51
    [Google Scholar]
  39. 39.
    Geard A, Pule GD, Chetcha Chemegni B, Ngo Bitoungui VJ, Kengne AP et al. 2017. Clinical and genetic predictors of renal dysfunctions in sickle cell anaemia in Cameroon. Br. J. Haematol. 178:629–39
    [Google Scholar]
  40. 40.
    Genovese G, Friedman DJ, Ross MD, Lecordier L, Uzureau P et al. 2010. Association of trypanolytic ApoL1 variants with kidney disease in African Americans. Science 329:841–45
    [Google Scholar]
  41. 41.
    Genovese G, Fromer M, Stahl EA, Ruderfer DM, Chambert K et al. 2016. Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia. Nat. Neurosci. 19:1433–41
    [Google Scholar]
  42. 42.
    Giri A, Edwards TL, Hartmann KE, Torstenson ES, Wellons M et al. 2017. African genetic ancestry interacts with body mass index to modify risk for uterine fibroids. PLOS Genet 13:e1006871
    [Google Scholar]
  43. 43.
    Gomez F, Hirbo J, Tishkoff SA. 2014. Genetic variation and adaptation in Africa: implications for human evolution and disease. Cold Spring Harb. Perspect. Biol. 6:a008524
    [Google Scholar]
  44. 44.
    Grollemund R, Branford S, Bostoen K, Meade A, Venditti C, Pagel M. 2015. Bantu expansion shows that habitat alters the route and pace of human dispersals. PNAS 112:13296–301
    [Google Scholar]
  45. 45.
    Guinto CO, Diarra S, Diallo S, Cissé L, Coulibaly T et al. 2017. A novel mutation in KIF5A in a Malian family with spastic paraplegia and sensory loss. Ann. Clin. Transl. Neurol. 4:272–75
    [Google Scholar]
  46. 46.
    Gulsuner S, Stein DJ, Susser ES, Sibeko G, Pretorius A et al. 2020. Genetics of schizophrenia in the South African Xhosa. Science 367:569–73
    [Google Scholar]
  47. 47.
    Gurdasani D, Barroso I, Zeggini E, Sandhu MS. 2019. Genomics of disease risk in globally diverse populations. Nat. Rev. Genet. 20:520–35
    [Google Scholar]
  48. 48.
    Gurdasani D, Carstensen T, Fatumo S, Chen G, Franklin CS et al. 2019. Uganda Genome Resource enables insights into population history and genomic discovery in Africa. Cell 179:984–1002.e36
    [Google Scholar]
  49. 49.
    Hedt-Gauthier BL, Jeufack HM, Neufeld NH, Alem A, Sauer S et al. 2019. Stuck in the middle: a systematic review of authorship in collaborative health research in Africa, 2014–2016. BMJ Glob. Health 4:e001853
    [Google Scholar]
  50. 50.
    Hellwege JN, Jeff JM, Wise LA, Gallagher CS, Wellons M et al. 2017. A multi-stage genome-wide association study of uterine fibroids in African Americans. Hum. Genet. 136:1363–73
    [Google Scholar]
  51. 51.
    Hum. Hered. Health Afr. (H3Africa). 2021. Publications. H3Africa. https://h3africa.org/index.php/resource/publication-2
    [Google Scholar]
  52. 52.
    Johns Hopkins Univ. 2021. OMIM gene map statistics. Online Mendelian Inheritance in Man. https://www.omim.org/statistics/geneMap
    [Google Scholar]
  53. 53.
    Kamulegeya R, Kateete DP, Bagaya BS, Nasinghe E, Muttamba W et al. 2022. Biobanking: strengthening Uganda's rapid response to COVID-19 and other epidemics. Biopreserv. Biobank 20:23843
    [Google Scholar]
  54. 54.
    Keaton JM, Jasper EA, Hellwege JN, Jones SH, Torstenson ES et al. 2021. Evidence that geographic variation in genetic ancestry associates with uterine fibroids. Hum. Genet. 140:1433–40
    [Google Scholar]
  55. 55.
    Kengne Kamga K, De Vries J, Nguefack S, Munung NS, Wonkam A 2021. Explanatory models for the cause of Fragile X Syndrome in rural Cameroon. J. Genet. Couns. 30:1727–36
    [Google Scholar]
  56. 56.
    Khera AV, Chaffin M, Aragam KG, Haas ME, Roselli C et al. 2018. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat. Genet. 50:1219–24
    [Google Scholar]
  57. 57.
    Kirkland EB, Heincelman M, Bishu KG, Schumann SO, Schreiner A et al. 2018. Trends in healthcare expenditures among US adults with hypertension: national estimates, 2003–2014. J. Am. Heart Assoc. 7:e008731
    [Google Scholar]
  58. 58.
    Krishnakumariamma K, Ellappan K, Muthuraj M, Tamilarasu K, Kumar SV, Joseph NM. 2020. Molecular diagnosis, genetic diversity and drug sensitivity patterns of mycobacterium tuberculosis strains isolated from tuberculous meningitis patients at a tertiary care hospital in South India. PLOS ONE 15:e0240257
    [Google Scholar]
  59. 59.
    Landouré G, Dembélé K, Cissé L, Samassékou O, Diarra S et al. 2019. Hereditary spastic paraplegia type 35 in a family from Mali. Am. J. Med. Genet. A 179:1122–25
    [Google Scholar]
  60. 60.
    Landouré G, Dembélé K, Diarra S, Cissé L, Samassékou O et al. 2020. A novel variant in the spatacsin gene causing SPG11 in a Malian family. Neurol. Sci. 411:116675
    [Google Scholar]
  61. 61.
    Landouré G, Samassékou O, Traoré M, Meilleur KG, Guinto CO et al. 2016. Genetics and genomic medicine in Mali: challenges and future perspectives. Mol. Genet. Genom. Med. 4:126–34
    [Google Scholar]
  62. 62.
    Landouré G, Zhu PP, Lourenço CM, Johnson JO, Toro C et al. 2013. Hereditary spastic paraplegia type 43 (SPG43) is caused by mutation in C19orf12. Hum. Mutat. 34:1357–60
    [Google Scholar]
  63. 63.
    Laval G, Peyrégne S, Zidane N, Harmant C, Renaud F et al. 2019. Recent adaptive acquisition by African rainforest hunter-gatherers of the Late Pleistocene sickle-cell mutation suggests past differences in malaria exposure. Am. J. Hum. Genet. 104:553–61
    [Google Scholar]
  64. 64.
    Ma S, Dubin AE, Zhang Y, Mousavi SAR, Wang Y et al. 2021. A role of PIEZO1 in iron metabolism in mice and humans. Cell 184:969–982.e13
    [Google Scholar]
  65. 65.
    Ma Z, Cheng G, Wang P, Khalighi B, Khalighi K. 2019. Clinical model for predicting warfarin sensitivity. Sci. Rep. 9:12856
    [Google Scholar]
  66. 66.
    Mackinnon MJ, Mwangi TW, Snow RW, Marsh K, Williams TN. 2005. Heritability of malaria in Africa. PLOS Med 2:1253–59
    [Google Scholar]
  67. 67.
    Makani J, Menzel S, Nkya S, Cox SE, Drasar E et al. 2011. Genetics of fetal hemoglobin in Tanzanian and British patients with sickle cell anemia. Blood 117:1390–92
    [Google Scholar]
  68. 68.
    Makani J, Sangeda RZ, Nnodu O, Nembaware V, Osei-Akoto A et al. 2020. SickleInAfrica. Lancet Haematol 7:e98–99
    [Google Scholar]
  69. 69.
    Malar. Genom. Epidemiol. Netw. 2014. Reappraisal of known malaria resistance loci in a large multicenter study. Nat. Genet. 46:1197–204
    [Google Scholar]
  70. 70.
    Manrai AK, Funke BH, Rehm HL, Olesen MS, Maron BA et al. 2016. Genetic misdiagnoses and the potential for health disparities. N. Engl. J. Med. 375:655–65
    [Google Scholar]
  71. 71.
    Martin AR, Kanai M, Kamatani Y, Okada Y, Neale BM, Daly MJ 2019. Clinical use of current polygenic risk scores may exacerbate health disparities. Nat. Genet. 51:584–91
    [Google Scholar]
  72. 72.
    Masiye F, Mayosi B, De Vries J. 2017.. “ I passed the test!” Evidence of diagnostic misconception in the recruitment of population controls for an H3Africa genomic study in Cape Town, South Africa. BMC Med. Ethics 18:12
    [Google Scholar]
  73. 73.
    McGuire AL, Gabriel S, Tishkoff SA, Wonkam A, Chakravarti A et al. 2020. The road ahead in genetics and genomics. Nat. Rev. Genet. 21:581–96
    [Google Scholar]
  74. 74.
    McQuillan MA, Zhang C, Tishkoff SA, Platt A. 2020. The importance of including ethnically diverse populations in studies of quantitative trait evolution. Curr. Opin. Genet. Dev. 62:30–35
    [Google Scholar]
  75. 75.
    Menzel S, Garner C, Gut I, Matsuda F, Yamaguchi M et al. 2007. A QTL influencing F cell production maps to a gene encoding a zinc-finger protein on chromosome 2p15. Nat. Genet. 39:1197–99
    [Google Scholar]
  76. 76.
    Miga KH, Koren S, Rhie A, Vollger MR, Gershman A et al. 2020. Telomere-to-telomere assembly of a complete human X chromosome. Nature 585:79–84
    [Google Scholar]
  77. 77.
    Mnika K, Mazandu GK, Jonas M, Pule GD, Chimusa ER et al. 2019. Hydroxyurea-induced miRNA expression in sickle cell disease patients in Africa. Front. Genet. 10:509
    [Google Scholar]
  78. 78.
    Moodley K, Kleinsmidt A. 2021. Allegations of misuse of African DNA in the UK: Will data protection legislation in South Africa be sufficient to prevent a recurrence?. Dev. World Bioeth. 21:125–30
    [Google Scholar]
  79. 79.
    Munung NS, de Vries J. 2020. Benefit sharing for human genomics research: awareness and expectations of genomics researchers in sub-Saharan Africa. Ethics Hum. Res. 42:14–20
    [Google Scholar]
  80. 80.
    Munung NS, de Vries J, Pratt B. 2021. Genomics governance: advancing justice, fairness and equity through the lens of the African communitarian ethic of Ubuntu. Med. Health Care Philos. 24:377–88
    [Google Scholar]
  81. 81.
    Munung NS, Nembaware V, de Vries J, Bukini D, Tluway F et al. 2019. Establishing a multi-country sickle cell disease registry in Africa: ethical considerations. Front. Genet. 10:943
    [Google Scholar]
  82. 82.
    Musanabaganwa C, Mihigo B, Tumusime R, Uwanyirigira M, Da Rocha J et al. 2020. Building skills and resources for genomics, epigenetics, and bioinformatics research for Africa: report of the joint 11th Conference of the African Society of Human Genetics and 12th H3Africa Consortium, 2018. Am. J. Trop. Med. Hyg. 102:1417–24
    [Google Scholar]
  83. 83.
    Mutapi F. 2019. Africa should set its own health-research agenda. Nature 575:567
    [Google Scholar]
  84. 84.
    Mweemba O, Musuku J, Mayosi BM, Parker M, Rutakumwa R et al. 2020. Use of broad consent and related procedures in genomics research: perspectives from research participants in the Genetics of Rheumatic Heart Disease (RHDGen) study in a University Teaching Hospital in Zambia. Glob. Bioeth. 31:184–99
    [Google Scholar]
  85. 85.
    Mwesigwa S, Williams L, Retshabile G, Katagirya E, Mboowa G et al. 2021. Unmapped exome reads implicate a role for Anelloviridae in childhood HIV-1 long-term non-progression. NPJ Genom. Med. 6:24
    [Google Scholar]
  86. 86.
    Natl. Inst. Health. 2021. NIH-wide strategic plan. National Institutes of Health. https://www.nih.gov/about-nih/nih-wide-strategic-plan
    [Google Scholar]
  87. 87.
    Ndadza A, Thomford NE, Mukanganyama S, Wonkam A, Ntsekhe M, Dandara C. 2019. The genetics of warfarin dose-response variability in Africans: an expert perspective on past, present, and future. OMICS 23:152–66
    [Google Scholar]
  88. 88.
    Ndiaye Diallo R, Gadji M, Hennig BJ, Guèye MV, Gaye A et al. 2017. Strengthening human genetics research in Africa: report of the 9th meeting of the African Society of Human Genetics in Dakar in May 2016. Glob. Health Epidemiol. Genom. 2:e10
    [Google Scholar]
  89. 89.
    Nembaware V, Johnston K, Diallo AA, Kotze MJ, Matimba A et al. 2019. A framework for tiered informed consent for health genomic research in Africa. Nat. Genet. 51:1566–71
    [Google Scholar]
  90. 90.
    Nembaware V, Mulder N. 2019. The African Genomic Medicine Training Initiative (AGMT): showcasing a community and framework driven genomic medicine training for nurses in Africa. Front. Genet. 10:1209
    [Google Scholar]
  91. 91.
    Niama FR, Vidal N, Diop-Ndiaye H, Nguimbi E, Ahombo G et al. 2017. HIV-1 genetic diversity and primary drug resistance mutations before large-scale access to antiretroviral therapy, Republic of Congo. BMC Res. Notes 10:243
    [Google Scholar]
  92. 92.
    Nordling L. 2021. Give African research participants more say in genomic data, say scientists. Nature 590:542
    [Google Scholar]
  93. 93.
    Oluwole OG, Esoh KK, Wonkam-Tingang E, Manyisa N, Noubiap JJ et al. 2020. Whole exome sequencing identifies rare coding variants in novel human-mouse ortholog genes in African individuals diagnosed with non-syndromic hearing impairment. Exp. Biol. Med. 246:197–206
    [Google Scholar]
  94. 94.
    Ormond KE, Laurino MY, Barlow-Stewart K, Wessels TM, Macaulay S et al. 2018. Genetic counseling globally: Where are we now?. Am. J. Med. Genet. C 178:98–107
    [Google Scholar]
  95. 95.
    Pepper MS. 2011. Launch of the Southern African Human Genome Programme. S. Afr. Med. J. 101:287–88
    [Google Scholar]
  96. 96.
    Piel FB, Patil AP, Howes RE, Nyangiri OA, Gething PW et al. 2010. Global distribution of the sickle cell gene and geographical confirmation of the malaria hypothesis. Nat. Commun. 1:104
    [Google Scholar]
  97. 97.
    Piel FB, Patil AP, Howes RE, Nyangiri OA, Gething PW et al. 2013. Global epidemiology of sickle haemoglobin in neonates: a contemporary geostatistical model-based map and population estimates. Lancet 381:142–51
    [Google Scholar]
  98. 98.
    Pule GD, Mowla S, Novitzky N, Wonkam A. 2016. Hydroxyurea down-regulates BCL11A, KLF-1 and MYB through miRNA-mediated actions to induce γ-globin expression: implications for new therapeutic approaches of sickle cell disease. Clin. Transl. Med. 5:15
    [Google Scholar]
  99. 99.
    Pule GD, Ngo Bitoungui VJ, Chetcha Chemegni B, Kengne AP, Antonarakis S, Wonkam A 2015. Association between variants at BCL11A erythroid-specific enhancer and fetal hemoglobin levels among sickle cell disease patients in Cameroon: implications for future therapeutic interventions. OMICS 19:627–31
    [Google Scholar]
  100. 100.
    Ralefala D, Kasule M, Wonkam A, Matshaba M, de Vries J. 2020. Do solidarity and reciprocity obligations compel African researchers to feedback individual genetic results in genomics research?. BMC Med. Ethics 21:112
    [Google Scholar]
  101. 101.
    Rotimi CN. 2004. Inauguration of the African Society of Human Genetics. Nat. Genet. 36:544
    [Google Scholar]
  102. 102.
    Rotimi CN, Abayomi A, Abimiku A, Adabayeri VM, Adebamowo C et al. 2014. Enabling the genomic revolution in Africa. Science 334:1346–48
    [Google Scholar]
  103. 103.
    Rotimi CN, Bentley AR, Doumatey AP, Chen G, Shriner D, Adeyemo A. 2017. The genomic landscape of African populations in health and disease. Hum. Mol. Genet. 26:R225–36
    [Google Scholar]
  104. 104.
    Røttingen JA, Chamas C, Goyal LC, Harb H, Lagradae L, Mayosi BM. 2012. Securing the public good of health research and development for developing countries. Bull. World Health Organ. 90:398–400
    [Google Scholar]
  105. 105.
    Royal CDM, Babyak M, Shah N, Srivatsa S, Stewart KA et al. 2021. Sickle cell disease is a global prototype for integrative research and healthcare. Adv. Genet. 2:e10037
    [Google Scholar]
  106. 106.
    Rumaney MB, Ngo Bitoungui VJ, Vorster AA, Ramesar R, Kengne AP et al. 2014. The co-inheritance of alpha-thalassemia and sickle cell anemia is associated with better hematological indices and lower consultations rate in Cameroonian patients and could improve their survival. PLOS ONE 9:e100516
    [Google Scholar]
  107. 107.
    Sandoval R, Monteghirfo M, Salazar O, Galarza M. 2020. Resistencia cruzada entre isoniacida y etionamida y su alta correlación con la mutación C-15T en aislamientos de Mycobacterium tuberculosis de Perú [Cross-resistance between isoniazid and ethionamide and its strong association with mutation C-15T in Mycobacterium tuberculosis isolates from Peru]. Rev. Argent. Microbiol. 52:36–42
    [Google Scholar]
  108. 108.
    Sangaré M, Hendrickson B, Sango HA, Chen K, Nofziger J et al. 2014. Genetics of low spinal muscular atrophy carrier frequency in sub-Saharan Africa. Ann. Neurol. 75:525–32
    [Google Scholar]
  109. 109.
    Schroeder D, Chatfield K, Singh M, Chennells R, Herissone-Kelly P. 2019. The San code of research ethics. Equitable Research Partnerships: A Global Code of Conduct to Counter Ethics Dumping73–87 Cham, Switz: Springer
    [Google Scholar]
  110. 110.
    Schroeder D, Cook J, Hirsch F, Fenet S, Muthuswamy V 2018. Ethics dumping: introduction. Ethics Dumping: Case Studies from North-South Research Collaborations D Schroeder, J Cook, F Hirsch, S Fenet, V Muthuswamy 1–8 Cham, Switz: Springer
    [Google Scholar]
  111. 111.
    Sherman RM, Forman J, Antonescu V, Puiu D, Daya M et al. 2019. Assembly of a pan-genome from deep sequencing of 910 humans of African descent. Nat. Genet. 51:30–35
    [Google Scholar]
  112. 112.
    Shriner D, Rotimi CN. 2018. Whole-genome-sequence-based haplotypes reveal single origin of the sickle allele during the Holocene Wet Phase. Am. J. Hum. Genet. 102:547–56
    [Google Scholar]
  113. 113.
    Sierra B, Triska P, Soares P, Garcia G, Perez AB et al. 2017. OSBPL10, RXRA and lipid metabolism confer African-ancestry protection against dengue haemorrhagic fever in admixed Cubans. PLOS Pathog 13:e1006220
    [Google Scholar]
  114. 114.
    Singh GM, Micha R, Khatibzadeh S, Shi P, Lim S et al. 2015. Global, regional, and national consumption of sugar-sweetened beverages, fruit juices, and milk: a systematic assessment of beverage intake in 187 countries. PLOS ONE 10:e0124845 Correction 2019. PLOS ONE 14:e0214344
    [Google Scholar]
  115. 115.
    Sirugo G, Williams SM, Royal CDM, Newport MJ, Hennig BJ et al. 2010. Report on the 6th African Society of Human Genetics (AfSHG) meeting, March 12–15, 2009, Yaoundé, Cameroon. Am. J. Trop. Med. Hyg. 83:226–29
    [Google Scholar]
  116. 116.
    Sirugo G, Williams SM, Tishkoff SA. 2019. The missing diversity in human genetic studies. Cell 177:26–31 Erratum 2019. Cell 177:1080
    [Google Scholar]
  117. 117.
    Skov L, Coll Macià M, Sveinbjörnsson G, Mafessoni F, Lucotte EA et al. 2020. The nature of Neanderthal introgression revealed by 27,566 Icelandic genomes. Nature 582:78–83
    [Google Scholar]
  118. 118.
    Soko ND, Chimusa E, Masimirembwa C, Dandara C. 2019. An African-specific profile of pharmacogene variants for rosuvastatin plasma variability: limited role for SLCO1B1 c.521T>C and ABCG2 c.421A>C. Pharmacogenom. J. 19:240–48
    [Google Scholar]
  119. 119.
    Staunton C, Adams R, Anderson D, Croxton T, Kamuya D et al. 2020. Protection of Personal Information Act 2013 and data protection for health research in South Africa. Int. Data Priv. Law 10:160–79
    [Google Scholar]
  120. 120.
    Stephens C 2007. Natural selection. Philosophy of Biology M Matthen, C Stephens 111–27 Amsterdam: North Holland
    [Google Scholar]
  121. 121.
    Swart M, Skelton M, Ren Y, Smith P, Takuva S, Dandara C. 2013. High predictive value of CYP2B6 SNPs for steady-state plasma efavirenz levels in South African HIV/AIDS patients. Pharmacogenet. Genom. 23:415–27
    [Google Scholar]
  122. 122.
    Thomford NE, Awortwe C, Dzobo K, Adu F, Chopera D et al. 2016. Inhibition of CYP2B6 by medicinal plant extracts: implication for use of efavirenz and nevirapine based highly active anti-retroviral therapy (HAART) in resource-limited settings. Molecules 21:211
    [Google Scholar]
  123. 123.
    Tindana P, Campbell M, Marshall P, Littler K, Vincent R et al. 2017. Developing the science and methods of community engagement for genomic research and biobanking in Africa. Glob. Health Epidemiol. Genom. 2:e13
    [Google Scholar]
  124. 124.
    Toivanen H, Ponomariov B. 2011. African regional innovation systems: bibliometric analysis of research collaboration patterns 2005–2009. Scientometrics 88:471–93
    [Google Scholar]
  125. 125.
    Urio F, Nkya S, Rooks H, Mgaya JA, Masamu U et al. 2020. F cell numbers are associated with an X-linked genetic polymorphism and correlate with haematological parameters in patients with sickle cell disease. Br. J. Haematol. 191:888–96
    [Google Scholar]
  126. 126.
    Wilkinson E, Giovanetti M, Tegally H, San JE, Lessells R et al. 2021. A year of genomic surveillance reveals how the SARS-CoV-2 pandemic unfolded in Africa. Science 374:423–31
    [Google Scholar]
  127. 127.
    Williams LM, Qi Z, Batai K, Hooker S, Hall NJ et al. 2018. A locus on chromosome 5 shows African ancestry-limited association with alloimmunization in sickle cell disease. Blood Adv 2:3637–47
    [Google Scholar]
  128. 128.
    Williams SM, Tishkoff SA. 2011. Exploring genomic studies in Africa. Genome Med 3:45
    [Google Scholar]
  129. 129.
    Williams TN, Mwangi TW, Wambua S, Alexander ND, Kortok M et al. 2005. Sickle cell trait and the risk of Plasmodium falciparum malaria and other childhood diseases. J. Infect. Dis. 192:178–86
    [Google Scholar]
  130. 130.
    Wonkam A. 2020. Investigating the missing heritability of fetal haemoglobin level in Africa. Br. J. Haematol. 191:668–70
    [Google Scholar]
  131. 131.
    Wonkam A. 2021. Sequence three million genomes across Africa. Nature 590:209–11
    [Google Scholar]
  132. 132.
    Wonkam A, Chimusa ER, Mnika K, Pule GD, Ngo Bitoungui VJ et al. 2020. Genetic modifiers of long-term survival in sickle cell anemia. Clin. Transl. Med. 10:e152
    [Google Scholar]
  133. 133.
    Wonkam A, de Vries J. 2020. Returning incidental findings in African genomics research. Nat. Genet. 52:17–20
    [Google Scholar]
  134. 134.
    Wonkam A, Kenfack MA, Muna WFT, Ouwe-Missi-Oukem-Boyer O 2011. Ethics of human genetic studies in sub-Saharan Africa: the case of Cameroon through a bibliometric analysis. Dev. World Bioeth. 11:120–27
    [Google Scholar]
  135. 135.
    Wonkam A, Makani J. 2019. Sickle cell disease in Africa: an urgent need for longitudinal cohort studies. Lancet Glob. Health 7:E1310–11
    [Google Scholar]
  136. 136.
    Wonkam A, Manyisa N, Bope CD, Dandara C, Chimusa ER. 2021. Whole exome sequencing reveals pathogenic variants in MYO3A, MYO15A and COL9A3 and differential frequencies in ancestral alleles in hearing impairment genes among individuals from Cameroon. Hum. Mol. Genet. 29:3729–43
    [Google Scholar]
  137. 137.
    Wonkam A, Ngo Bitoungui VJ, Vorster AA, Ramesar R, Cooper RS et al. 2014. Association of variants at BCL11A and HBS1L-MYB with hemoglobin F and hospitalization rates among sickle cell patients in Cameroon. PLOS ONE 9:e92506
    [Google Scholar]
  138. 138.
    Wonkam A, Njamnshi AK, Angwafo FF. 2006. Knowledge and attitudes concerning medical genetics amongst physicians and medical students in Cameroon (sub-Saharan Africa). Genet. Med. 8:331–38
    [Google Scholar]
  139. 139.
    Wonkam A, Tekendo CN, Sama DJ, Zambo H, Dahoun S et al. 2011. Initiation of a medical genetics service in sub-Saharan Africa: experience of prenatal diagnosis in Cameroon. Eur. J. Med. Genet. 54:e399–404
    [Google Scholar]
  140. 140.
    Wonkam-Tingang E, Schrauwen I, Esoh KK, Bharadwaj T, Nouel-Saied LM et al. 2020. Bi-allelic novel variants in CLIC5 identified in a Cameroonian multiplex family with non-syndromic hearing impairment. Genes 11:1249
    [Google Scholar]
  141. 141.
    Wonkam-Tingang E, Schrauwen I, Esoh KK, Bharadwaj T, Nouel-Saied LM et al. 2021. A novel variant in DMXL2 gene is associated with autosomal dominant non-syndromic hearing impairment (DFNA71) in a Cameroonian family. Exp. Biol. Med. 246:1524–32
    [Google Scholar]
  142. 142.
    World Health Organ. 2019. Malaria incidence (per 1 000 population at risk) (Malaria). World Health Organization https://apps.who.int/gho/data/node.imr.SDGMALARIA?lang=en
    [Google Scholar]
  143. 143.
    World Health Organ. Advis. Comm. Health Res. 2002. Genomics and world health: report of the Advisory Committee on Health Research Rep. World Health Organ. Geneva:
    [Google Scholar]
  144. 144.
    Yakubu A, Tindana P, Matimba A, Littler K, Munung NS et al. 2018. Model framework for governance of genomic research and biobanking in Africa – a content description. AAS Open Res 1:13
    [Google Scholar]
  145. 145.
    Yalcouyé A, Diallo SH, Coulibaly T, Cissé L, Diallo S et al. 2019. A novel mutation in the GARS gene in a Malian family with Charcot-Marie-Tooth disease. Mol. Genet. Genom. Med. 7:782
    [Google Scholar]
  146. 146.
    Zeberg H, Pääbo S. 2020. The major genetic risk factor for severe COVID-19 is inherited from Neanderthals. Nature 587:610–12
    [Google Scholar]
/content/journals/10.1146/annurev-genom-111521-102452
Loading
/content/journals/10.1146/annurev-genom-111521-102452
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error