The deep evolutionary history of African populations, since the emergence of modern humans more than 300,000 years ago, has resulted in high genetic diversity and considerable population structure. Selected genetic variants have increased in frequency due to environmental adaptation, but recent exposures to novel pathogens and changes in lifestyle render some of them with properties leading to present health liabilities. The unique discoverability potential from African genomic studies promises invaluable contributions to understanding the genomic and molecular basis of health and disease. Globally, African populations are understudied, and precision medicine approaches are largely based on data from European and Asian-ancestry populations, which limits the transferability of findings to the continent of Africa. Africa needs innovative precision medicine solutions based on African data that use knowledge and implementation strategies aligned to its climatic, cultural, economic and genomic diversity.
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Rotimi, C. et al. Research capacity. Enabling the genomic revolution in Africa. Science 344, 1346–1348 (2014).
Cohoon, T. J. & Bhavnani, S. P. Toward precision health: applying artificial intelligence analytics to digital health biometric datasets. Per. Med. 17, 307–316 (2020).
Mapesi, H. & Paris, D. H. Non-communicable diseases on the rise in sub-Saharan Africa, the underappreciated threat of a dual disease burden. Praxis 108, 997–1005 (2019).
Mudie, K. et al. Non-communicable diseases in sub-Saharan Africa: a scoping review of large cohort studies. J. Glob. Health 9, 020409 (2019).
Tekola-Ayele, F. & Rotimi, C. N. Translational genomics in low- and middle-income countries: opportunities and challenges. Public Health Genomics 18, 242–247 (2015).
Mulder, N. et al. H3Africa: current perspectives. Pharmgenomics Pers. Med. 11, 59–66 (2018).
Owolabi, M. O. et al. Data resource profile: Cardiovascular H3Africa Innovation Resource (CHAIR). Int. J. Epidemiol. 48, 366–367g (2019).
Adedokun, B. O., Olopade, C. O. & Olopade, O. I. 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 (2016).
Stringer, C. The origin and evolution of Homo sapiens. Philos. Trans. R. Soc. Lond. B Biol. Sci. 371, 20150237 (2016).
Schlebusch, C. M. et al. Southern African ancient genomes estimate modern human divergence to 350,000 to 260,000 years ago. Science 358, 652–655 (2017).
Hublin, J. J. et al. New fossils from Jebel Irhoud, Morocco and the pan-African origin of Homo sapiens. Nature 546, 289–292 (2017).
Scerri, E. M. L. et al. Did our species evolve in subdivided populations across Africa, and why does it matter? Trends Ecol. Evol. 33, 582–594 (2018).
Cruciani, F. et al. A revised root for the human Y chromosomal phylogenetic tree: the origin of patrilineal diversity in Africa. Am. J. Hum. Genet. 88, 814–818 (2011).
Rito, T. et al. The first modern human dispersals across Africa. PLoS ONE 8, e80031 (2013).
Santander, C., Montinaro, F. & Capelli, C. Searching for archaic contribution in Africa. Ann. Hum. Biol. 46, 129–139 (2019).
Skoglund, P. & Mathieson, I. Ancient genomics of modern humans: the first decade. Annu. Rev. Genomics Hum. Genet. 19, 381–404 (2018).
Durvasula, A. & Sankararaman, S. Recovering signals of ghost archaic introgression in African populations. Sci. Adv. 6, eaax5097 (2020).
Chen, L., Wolf, A. B., Fu, Q., Li, L. & Akey, J. M. Identifying and interpreting apparent neanderthal ancestry in African individuals. Cell 180, 1–11 (2020).
Veeramah, K. R. et al. An early divergence of KhoeSan ancestors from those of other modern humans is supported by an ABC-based analysis of autosomal resequencing data. Mol. Biol. Evol. 29, 617–630 (2012).
Verdu, P. et al. Origins and genetic diversity of pygmy hunter-gatherers from Western Central Africa. Curr. Biol. 19, 312–318 (2009).
Fan, S. et al. African evolutionary history inferred from whole genome sequence data of 44 indigenous African populations. Genome Biol. 20, 82 (2019).
Tishkoff, S. A. et al. The genetic structure and history of Africans and African Americans. Science 324, 1035–1044 (2009).
Hernández, C. L. et al. Human genomic diversity where the Mediterranean joins the Atlantic. Mol. Biol. Evol. 37, 1041–1055 (2020).
van de Loosdrecht, M. et al. Pleistocene North African genomes link Near Eastern and sub-Saharan African human populations. Science 360, 548–552 (2018).
Pickrell, J. K. et al. The genetic prehistory of southern Africa. Nat. Commun. 3, 1143 (2012).
Triska, P. et al. Extensive admixture and selective pressure across the Sahel Belt. Genome Biol. Evol. 7, 3484–3495 (2015).
Patin, E. et al. Dispersals and genetic adaptation of Bantu-speaking populations in Africa and North America. Science 356, 543–546 (2017). This paper examines the genetic diversity of Bantu-speakers, modelling the timing of migration and admixture during the Bantu expansion. Interestingly, the paper identifies adaptive introgression of genes from local populations along the Bantu waves, including specific immune-related genes.
Lopez, M. et al. The demographic history and mutational load of African hunter-gatherers and farmers. Nat. Ecol. Evol. 2, 721–730 (2018).
Gallego Llorente, M. et al. Ancient Ethiopian genome reveals extensive Eurasian admixture throughout the African continent. Science 350, 820–822 (2015).
Skoglund, P. et al. Reconstructing prehistoric African population structure. Cell 171, 59–71.e21 (2017).
Lipson, M. et al. Ancient West African foragers in the context of African population history. Nature 577, 665–670 (2020).
Hellenthal, G. et al. A genetic atlas of human admixture history. Science 343, 747–751 (2014).
Semo, A. et al. Along the Indian Ocean coast: genomic variation in Mozambique provides new insights into the Bantu expansion. Mol. Biol. Evol. 37, 406–416 (2019).
Choudhury, A. et al. High-depth African genomes inform human migration and health. Nature 586, 741–748 (2020). This paper presents the largest whole-genome sequence study of African populations describing >3 million novel variants and highlighting disease-associated alleles.
Gurdasani, D. et al. The African genome variation project shapes medical genetics in Africa. Nature 517, 327–332 (2015). This paper introduces The African Genome Variation Project, with dense genotypes from 1481 individuals and whole-genome sequences from 320 individuals across SSA. Besides presenting novel evidence of complex population history and loci under selection, the paper demonstrates further improvements in imputation accuracy, strengthening the case for large-scale sequencing efforts of diverse African haplotypes.
Pickrell, J. K. et al. Ancient west Eurasian ancestry in southern and eastern Africa. Proc. Natl Acad. Sci. USA 111, 2632–2637 (2014).
Brucato, N. et al. The Comoros show the earliest Austronesian gene flow into the Swahili Corridor. Am. J. Hum. Genet. 102, 58–68 (2018).
Pierron, D. et al. Genomic landscape of human diversity across madagascar. Proc. Natl Acad. Sci. USA 114, E6498–E6506 (2017).
Brucato, N. et al. Evidence of austronesian genetic lineages in East Africa and South Arabia: complex dispersal from madagascar and Southeast Asia. Genome Biol. Evol. 11, 748–758 (2019).
Choudhury, A. et al. Whole-genome sequencing for an enhanced understanding of genetic variation among South Africans. Nat. Commun. 8, 2062 (2017).
May, A. et al. Genetic diversity in black South Africans from Soweto. BMC Genomics 14, 644 (2013).
Lovejoy, P. E. The impact of the Atlantic slave trade on Africa: a review of the literature. J. Afr. Hist. 30, 365–394 (1989).
Macaulay, V. et al. Single, rapid coastal settlement of Asia revealed by analysis of complete mitochondrial genomes. Science 308, 1034–1036 (2005).
Gravel, S. et al. Demographic history and rare allele sharing among human populations. Proc. Natl Acad. Sci. USA 108, 11983–11988 (2011).
The 1000 Genomes Project Consortium, et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).
Chen, J. et al. Genome-wide association study of type 2 diabetes in Africa. Diabetologia 62, 1204–1211 (2019).
Martin, A. R., Teferra, S., Möller, M., Hoal, E. G. & Daly, M. J. The critical needs and challenges for genetic architecture studies in Africa. Curr. Opin. Genet. Dev. 53, 113–120 (2018).
Gurdasani, D., Barroso, I., Zeggini, E. & Sandhu, M. S. Genomics of disease risk in globally diverse populations. Nat. Rev. Genet. 20, 520–535 (2019).
Fu, W. et al. Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants. Nature 493, 216–220 (2013).
Simons, Y. B., Turchin, M. C., Pritchard, J. K. & Sella, G. The deleterious mutation load is insensitive to recent population history. Nat. Genet. 46, 220–224 (2014).
Quintana-Murci, L. Human immunology through the lens of evolutionary genetics. Cell 177, 184–199 (2019).
Grossman, S. R. et al. Identifying recent adaptations in large-scale genomic data. Cell 152, 703–713 (2013).
Guernier, V., Hochberg, M. E. & Guegan, J. F. Ecology drives the worldwide distribution of human diseases. PLoS Biol. 2, e141 (2004).
Cairns, M. E. et al. Seasonality in malaria transmission: implications for case-management with long-acting artemisinin combination therapy in sub-Saharan Africa. Malar. J. 14, 321 (2015).
Zhao, S., Lin, Q., He, D. & Stone, L. Meningitis epidemics shift in sub-Saharan belt. Int. J. Infect. Dis. 68, 79–82 (2018).
Alexander, K. A. et al. What factors might have led to the emergence of Ebola in West Africa? PLoS Negl. Trop. Dis. 9, e0003652 (2015).
Fan, S., Hansen, M. E., Lo, Y. & Tishkoff, S. A. Going global by adapting local: a review of recent human adaptation. Science 354, 54–59 (2016).
Sierra, B. et al. OSBPL10, RXRA and lipid metabolism confer African-ancestry protection against dengue haemorrhagic fever in admixed Cubans. PLoS Pathog. 13, e1006220 (2017).
Bentley, A. R. & Rotimi, C. N. Interethnic variation in lipid profiles: implications for underidentification of African-Americans at risk for metabolic disorders. Expert Rev. Endocrinol. Metab. 7, 659–667 (2012).
Coram, M. A. et al. Genome-wide characterization of shared and distinct genetic components that influence blood lipid levels in ethnically diverse human populations. Am. J. Hum. Genet. 92, 904–916 (2013).
Cohen, J. et al. Low LDL cholesterol in individuals of African descent resulting from frequent nonsense mutations in PCSK9. Nat. Genet. 37, 161–165 (2005). This paper reports that loss-of-function mutations in the PCSK9 gene, preventing hypercholesterolaemia, were common in AAs (combined frequency, 2%) but rare in EAs (<0.1%) and were associated with a 40% reduction in plasma levels of LDL cholesterol.
Ng, M. C. Y. et al. Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium. PLoS Genet. 13, e1006719 (2017).
Doumatey, A. P., Ekoru, K., Adeyemo, A. & Rotimi, C. N. Genetic basis of obesity and type 2 diabetes in Africans: impact on precision medicine. Curr. Diab Rep. 19, 105 (2019).
Gomez-Olive, F. X. et al. Regional and sex differences in the prevalence and awareness of hypertension: an H3Africa AWI-Gen study across 6 sites in sub-Saharan Africa. Glob. Heart 12, 81–90 (2017).
Young, J. H. et al. Differential susceptibility to hypertension is due to selection during the out-of-Africa expansion. PLoS Genet. 1, e82 (2005).
Franceschini, N. et al. Genome-wide association analysis of blood-pressure traits in African-ancestry individuals reveals common associated genes in African and non-African populations. Am. J. Hum. Genet. 93, 545–554 (2013).
Band, G., Rockett, K. A., Spencer, C. C. & Kwiatkowski, D. P. A novel locus of resistance to severe malaria in a region of ancient balancing selection. Nature 526, 253–257 (2015).
Hamblin, M. T., Thompson, E. E. & Di Rienzo, A. Complex signatures of natural selection at the Duffy blood group locus. Am. J. Hum. Genet. 70, 369–383 (2002).
McManus, K. F. et al. Population genetic analysis of the DARC locus (Duffy) reveals adaptation from standing variation associated with malaria resistance in humans. PLoS Genet. 13, e1006560 (2017).
Pierron, D. et al. Strong selection during the last millennium for African ancestry in the admixed population of Madagascar. Nat. Commun. 9, 932 (2018).
Genovese, G. et al. Association of trypanolytic ApoL1 variants with kidney disease in African Americans. Science 329, 841–845 (2010).
Cooper, A. et al. APOL1 renal risk variants have contrasting resistance and susceptibility associations with African trypanosomiasis. eLife 6, e25461 (2017).
Ko, W. Y. et al. Identifying Darwinian selection acting on different human APOL1 variants among diverse African populations. Am. J. Hum. Genet. 93, 54–66 (2013).
Williams, T. N. et al. Negative epistasis between the malaria-protective effects of α+-thalassemia and the sickle cell trait. Nat. Genet. 37, 1253–1257 (2005).
Saraf, S. L. et al. APOL1, α-thalassemia, and BCL11A variants as a genetic risk profile for progression of chronic kidney disease in sickle cell anemia. Haematologica 102, e1–e6 (2017).
Zahr, R. S. et al. Children with sickle cell anemia and APOL1 genetic variants develop albuminuria early in life. Haematologica 104, e385–e387 (2019).
Engelken, J. et al. Extreme population differences in the human zinc transporter ZIP4 (SLC39A4) are explained by positive selection in sub-Saharan Africa. PLoS Genet. 10, e1004128 (2014).
Hood, M. I. & Skaar, E. P. Nutritional immunity: transition metals at the pathogen–host interface. Nat. Rev. Microbiol. 10, 525–537 (2012).
Schaafsma, T. et al. Africa’s oesophageal cancer corridor: geographic variations in incidence correlate with certain micronutrient deficiencies. PLoS ONE 10, e0140107 (2015).
Vicente, M., Jakobsson, M., Ebbesen, P. & Schlebusch, C. M. Genetic affinities among southern Africa hunter-gatherers and the impact of admixing farmer and herder populations. Mol. Biol. Evol. 36, 1849–1861 (2019).
Lachance, J. et al. Evolutionary history and adaptation from high-coverage whole-genome sequences of diverse African hunter-gatherers. Cell 150, 457–469 (2012).
Xu, D. et al. Archaic hominin introgression in Africa contributes to functional salivary MUC7 genetic variation. Mol. Biol. Evol. 34, 2704–2715 (2017).
Bustamante, C. D., Burchard, E. G. & De la Vega, F. M. Genomics for the world. Nature 475, 163–165 (2011).
Petrovski, S. & Goldstein, D. B. Unequal representation of genetic variation across ancestry groups creates healthcare inequality in the application of precision medicine. Genome Biol. 17, 157 (2016).
Popejoy, A. B. & Fullerton, S. M. Genomics is failing on diversity. Nature 538, 161–164 (2016).
Gurdasani, D. et al. Uganda genome resource enables insights into population history and genomic discovery in Africa. Cell 179, 984–1002.e36 (2019). By performing a multi-trait pan-African GWAS of up to 14,126 individuals, this paper identifies novel loci associated with anthropometric, haematological, lipid and glycaemic traits. Several functionally important signals are driven by Africa-specific variants, highlighting the value of studying diverse populations across the region.
Rotimi, C. N. et al. The genomic landscape of African populations in health and disease. Hum. Mol. Genet. 26, R225–R236 (2017).
Koboldt, D. C., Steinberg, K. M., Larson, D. E., Wilson, R. K. & Mardis, E. R. The next-generation sequencing revolution and its impact on genomics. Cell 155, 27–38 (2013).
Richards, S. et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 17, 405–424 (2015).
Amr, S. S. et al. Using large sequencing data sets to refine intragenic disease regions and prioritize clinical variant interpretation. Genet. Med. 19, 496–504 (2017).
Mitropoulos, K. et al. Success stories in genomic medicine from resource-limited countries. Hum. Genomics 9, 11 (2015).
Romdhane, L. et al. Consanguinity and inbreeding in health and disease in North African populations. Annu. Rev. Genomics Hum. Genet. 20, 155–179 (2019).
Krause, A., Seymour, H. & Ramsay, M. Common and founder mutations for monogenic traits in sub-Saharan African populations. Annu. Rev. Genomics Hum. Genet. 19, 149–175 (2018).
Kabahuma, R. I. et al. Absence of GJB2 gene mutations, the GJB6 deletion (GJB6-D13S1830) and four common mitochondrial mutations in nonsyndromic genetic hearing loss in a South African population. Int. J. Pediatr. Otorhinolaryngol. 75, 611–617 (2011).
Wonkam, A. et al. No evidence for clinical utility in investigating the connexin genes GJB2, GJB6 and GJA1 in non-syndromic hearing loss in Black Africans. S Afr. Med. J. 105, 23–26 (2015).
Lebeko, K. et al. Targeted genomic enrichment and massively parallel sequencing identifies novel nonsyndromic hearing impairment pathogenic variants in Cameroonian families. Clin. Genet. 90, 288–290 (2016).
Brobby, G. W., Müller-Myhsok, B. & Horstmann, R. D. Connexin 26 R143W mutation associated with recessive nonsyndromic sensorineural deafness in Africa. N. Engl. J. Med. 338, 548–550 (1998).
Adadey, S. M. et al. GJB2 and GJB6 mutations in non-syndromic childhood hearing impairment in Ghana. Front. Genet. 10, 841 (2019).
Hamelmann, C. et al. Pattern of connexin 26 (GJB2) mutations causing sensorineural hearing impairment in Ghana. Hum. Mutat. 18, 84–85 (2001).
Manga, P., Kerr, R., Ramsay, M. & Kromberg, J. G. Biology and genetics of oculocutaneous albinism and vitiligo — common pigmentation disorders in southern Africa. S Afr. Med. J. 103, 984–988 (2013).
Manolio, T. A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009).
Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 42, 565–569 (2010).
Adeyemo, A. A. et al. Evaluation of genome wide association study associated type 2 diabetes susceptibility loci in sub Saharan Africans. Front. Genet. 6, 335 (2015).
Hauser, M. A. et al. Association of genetic variants with primary open-angle glaucoma among individuals with African ancestry. JAMA 322, 1682–1691 (2019).
Govind, N. et al. HLA-DRB1 amino acid positions and residues associated with antibody-positive rheumatoid arthritis in Black South Africans. J. Rheumatol. 46, 138–144 (2019).
Gulsuner, S. et al. Genetics of schizophrenia in the South African Xhosa. Science 367, 569–573 (2020).
Manolio, T. A. In retrospect: a decade of shared genomic associations. Nature 546, 360–361 (2017).
Drake, T. M., Knight, S. R., Harrison, E. M. & Søreide, K. Global inequities in precision medicine and molecular cancer research. Front. Oncol. 8, 346 (2018).
Burkitt, D. A sarcoma involving the jaws in African children. Br. J. Surg. 46, 218–223 (1958).
Spano, J. P., Atlan, D., Breau, J. L. & Farge, D. AIDS and non-AIDS-related malignancies: a new vexing challenge in HIV-positive patients. Part I: Kaposi’s sarcoma, non-Hodgkin’s lymphoma, and Hodgkin’s lymphoma. Eur. J. Intern. Med. 13, 170–179 (2002).
Pitt, J. J. et al. Characterization of Nigerian breast cancer reveals prevalent homologous recombination deficiency and aggressive molecular features. Nat. Commun. 9, 4181 (2018).
Zheng, Y. et al. Inherited breast cancer in Nigerian women. J. Clin. Oncol. 36, 2820–2825 (2018).
Rebbeck, T. R. et al. Mutational spectrum in a worldwide study of 29,700 families with BRCA1 or BRCA2 mutations. Hum. Mutat. 39, 593–620 (2018).
Manrai, A. K. et al. Genetic misdiagnoses and the potential for health disparities. N. Engl. J. Med. 375, 655–665 (2016).
Fitzmaurice, C. et al. Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 29 cancer groups, 1990 to 2017: a systematic analysis for the Global Burden of Disease Study. JAMA Oncol. 5, 1749–1768 (2019).
Reay, W. R. et al. Polygenic disruption of retinoid signalling in schizophrenia and a severe cognitive deficit subtype. Mol. Psychiatry 25, 719–731 (2018).
Martin, A. R. et al. Clinical use of current polygenic risk scores may exacerbate health disparities. Nat. Genet. 51, 584–591 (2019).
Duncan, L. et al. Analysis of polygenic risk score usage and performance in diverse human populations. Nat. Commun. 10, 3328 (2019). This paper presents a reanalysis of 10 years of polygenic scoring studies, showing that 67% involve European ancestry participants, 19% East Asian populations and 3.8% African, Hispanic or Indigenous people, revealing that the predictive performance of current polygenic scores is lower in non-European ancestry samples. There is a clear need for large-scale GWAS in diverse human populations.
Torkamani, A., Wineinger, N. E. & Topol, E. J. The personal and clinical utility of polygenic risk scores. Nat. Rev. Genet. 19, 581–590 (2018).
Mosley, J. D. et al. Predictive accuracy of a polygenic risk score compared with a clinical risk score for incident coronary heart disease. JAMA 323, 627–635 (2020).
Tada, H. et al. Risk prediction by genetic risk scores for coronary heart disease is independent of self-reported family history. Eur. Heart J. 37, 561–567 (2016).
Rao, A. S. & Knowles, J. W. Polygenic risk scores in coronary artery disease. Curr. Opin. Cardiol. 34, 435–440 (2019).
Elliott, J. et al. Predictive accuracy of a polygenic risk score-enhanced prediction model vs a clinical risk score for coronary artery disease. JAMA 323, 636–645 (2020).
Khera, A. V. et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat. Genet. 50, 1219–1224 (2018).
Kuchenbaecker, K. et al. The transferability of lipid loci across African, Asian and European cohorts. Nat. Commun. 10, 4330 (2019). This paper assesses whether the genetic determinants of blood lipids are shared across populations, finding evidence of reproducibility for ~75% of the major lipid loci from European discovery studies, except TG loci in the Ugandan samples (10% of loci). The authors hypothesize that the non-transferable loci might affect lipids by modifying food intake in environments rich in certain nutrients.
Wojcik, G. L. et al. Genetic analyses of diverse populations improves discovery for complex traits. Nature 570, 514–518 (2019). The Population Architecture using Genomics and Epidemiology (PAGE) study conducts a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals, and the results show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications.
Wei, C. Y., Lee, M. T. & Chen, Y. T. Pharmacogenomics of adverse drug reactions: implementing personalized medicine. Hum. Mol. Genet. 21, R58–R65 (2012).
Loscalzo, J. Precision medicine. Circ. Res. 124, 987–989 (2019).
Spear, B. B., Heath-Chiozzi, M. & Huff, J. Clinical application of pharmacogenetics. Trends Mol. Med. 7, 201–204 (2001).
Urban, M. F. Genomics in medicine: from promise to practice. S Afr. Med. J. 105, 545–547 (2015).
Hovelson, D. H. et al. Characterization of ADME gene variation in 21 populations by exome sequencing. Pharmacogenet. Genomics 27, 89–100 (2017).
Nordling, L. How the genomics revolution could finally help Africa. Nature 544, 20–22 (2017).
Masimirembwa, C., Dandara, C. & Leutscher, P. D. Rolling out efavirenz for HIV precision medicine in Africa: are we ready for pharmacovigilance and tackling neuropsychiatric adverse effects? OMICS 20, 575–580 (2016).
Gross, R. et al. Slow efavirenz metabolism genotype is common in Botswana. J. Acquir. Immune Defic. Syndr. 49, 336–337 (2008).
Zembutsu, H. Pharmacogenomics toward personalized tamoxifen therapy for breast cancer. Pharmacogenomics 16, 287–296 (2015).
Walko, C. M. & McLeod, H. Use of CYP2D6 genotyping in practice: tamoxifen dose adjustment. Pharmacogenomics 13, 691–697 (2012).
Popejoy, A. B. Diversity in precision medicine and pharmacogenetics: methodological and conceptual considerations for broadening participation. Pharmgenomics Pers. Med. 12, 257–271 (2019).
De, T. et al. Association of genetic variants with warfarin-associated bleeding among patients of African descent. JAMA 320, 1670–1677 (2018).
Hobbs, A. & Ramsay, M. Epigenetics and the burden of noncommunicable disease: a paucity of research in Africa. Epigenomics 7, 627–639 (2015).
Sokolowski, H. M. et al. The Drosophila foraging gene human orthologue PRKG1 predicts individual differences in the effects of early adversity on maternal sensitivity. Cogn. Dev. 42, 62–73 (2017).
Fraser, H. B., Lam, L. L., Neumann, S. M. & Kobor, M. S. Population-specificity of human DNA methylation. Genome Biol. 13, R8 (2012).
Huan, T. et al. Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease. Nat. Commun. 10, 4267 (2019).
Pierce, B. L. et al. Co-occurring expression and methylation QTLs allow detection of common causal variants and shared biological mechanisms. Nat. Commun. 9, 804 (2018).
Fagny, M. et al. The epigenomic landscape of African rainforest hunter-gatherers and farmers. Nat. Commun. 6, 10047 (2015).
Vukojevic, V. et al. Epigenetic modification of the glucocorticoid receptor gene is linked to traumatic memory and post-traumatic stress disorder risk in genocide survivors. J. Neurosci. 34, 10274–10284 (2014).
Perroud, N. et al. The Tutsi genocide and transgenerational transmission of maternal stress: epigenetics and biology of the HPA axis. World J. Biol. Psychiatry 15, 334–345 (2014).
Rudahindwa, S. et al. Transgenerational effects of the genocide against the Tutsi in Rwanda: a post-traumatic stress disorder symptom domain analysis. AAS Open Res. https://doi.org/10.12688/aasopenres.12848.1 (2020).
Dominguez-Salas, P. et al. Maternal nutrition at conception modulates DNA methylation of human metastable epialleles. Nat. Commun. 5, 3746 (2014).
Schulze, K. V. et al. Edematous severe acute malnutrition is characterized by hypomethylation of DNA. Nat. Commun. 10, 5791 (2019).
Waterland, R. A. et al. Season of conception in rural gambia affects DNA methylation at putative human metastable epialleles. PLoS Genet. 6, e1001252 (2010).
Black, R. E. et al. Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet 382, 427–451 (2013).
Bhutta, Z. A. et al. Severe childhood malnutrition. Nat. Rev. Dis. Prim. 3, 17067 (2017).
Steyn, A. et al. Epigenetic modification of the pentose phosphate pathway and the IGF-axis in women with gestational diabetes mellitus. Epigenomics 11, 1371–1385 (2019).
Costantino, S. et al. Epigenetics and precision medicine in cardiovascular patients: from basic concepts to the clinical arena. Eur. Heart J. 39, 4150–4158 (2018).
Musanabaganwa, C. et al. 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, 1417–1424 (2020). Local African genetics societies are paramount in encouraging research in Africa. This paper is the meeting report for the 11th Congress of the African Society of Human Genetics (AfSHG) in conjunction with the 12th H3Africa Consortium meeting in 2018.
El-Kamah, G. Y. et al. 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, 719–723 (2020).
Ndiaye Diallo, R. et al. 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 (2017).
de Vries, J. et al. Ethical issues in human genomics research in developing countries. BMC Med. Ethics 12, 5 (2011).
Nyika, A. Ethical and practical challenges surrounding genetic and genomic research in developing countries. Acta Trop. 112 (Suppl. 1), S21–S31 (2009).
Marshall, P. A. et al. Voluntary participation and informed consent to international genetic research. Am. J. Public Health 96, 1989–1995 (2006).
Tindana, P. et al. Seeking consent to genetic and genomic research in a rural Ghanaian setting: a qualitative study of the MalariaGEN experience. BMC Med. Ethics 13, 15 (2012).
Ghansah, A. et al. Monitoring parasite diversity for malaria elimination in sub-Saharan Africa. Science 345, 1297–1298 (2014).
Yakubu, A. et al. Model framework for governance of genomic research and biobanking in Africa — a content description. AAS Open Res. 1, 13 (2018).
Rotimi, C. et al. Community engagement and informed consent in the International HapMap project. Community Genet. 10, 186–198 (2007).
Tindana, P. et al. Community engagement strategies for genomic studies in Africa: a review of the literature. BMC Med. Ethics 16, 24 (2015).
Sankoh, O. & Ijsselmuiden, C. Sharing research data to improve public health: a perspective from the Global South. Lancet 378, 401–402 (2011).
Bull, S. et al. Best practices for ethical sharing of individual-level health research data from low- and middle-income settings. J. Empir. Res. Hum. Res Ethics 10, 302–313 (2015).
Kraft, S. A. et al. Beyond consent: building trusting relationships with diverse populations in precision medicine research. Am. J. Bioeth. 18, 3–20 (2018).
Sabatello, M., Callier, S., Garrison, N. A. & Cohn, E. G. Trust, precision medicine research, and equitable participation of underserved populations. Am. J. Bioeth. 18, 34–36 (2018).
Magnus, D. & Batten, J. N. Building a trustworthy precision health research enterprise. Am. J. Bioeth. 18, 1–2 (2018).
Tindana, P. & de Vries, J. Broad consent for genomic research and biobanking: perspectives from low- and middle-income countries. Annu. Rev. Genomics Hum. Genet. 17, 375–393 (2016).
Stein, D. T. & Terry, S. F. Reforming biobank consent policy: a necessary move away from broad consent toward dynamic consent. Genet. Test. Mol. Biomarkers 17, 855–856 (2013).
Kaye, J. et al. Dynamic consent: a patient interface for twenty-first century research networks. Eur. J. Hum. Genet. 23, 141–146 (2015).
Munung, N. S. et al. Obtaining informed consent for genomics research in Africa: analysis of H3Africa consent documents. J. Med. Ethics 42, 132–137 (2016).
Jao, I. et al. Involving research stakeholders in developing policy on sharing public health research data in Kenya: views on fair process for informed consent, access oversight, and community engagement. J. Empir. Res. Hum. Res Ethics 10, 264–277 (2015).
van Delden, J. J. & van der Graaf, R. Revised CIOMS International Ethical Guidelines for Health-Related Research Involving Humans. JAMA 317, 135–136 (2017).
Nembaware, V. et al. A framework for tiered informed consent for health genomic research in Africa. Nat. Genet. 51, 1566–1571 (2019). This paper proposes a framework for the conduct of ethically sound, tiered informed-consent processes in Africa. This framework guarantees the autonomy and individual choices of African research participants but at the same time enables global health benefits gathered from sharing and meta-analysis of African genomic data.
Knoppers, B. M., Deschenes, M., Zawati, M. H. & Tasse, A. M. Population studies: return of research results and incidental findings policy statement. Eur. J. Hum. Genet. 21, 245–247 (2013).
Fernandez, C. V., Kodish, E. & Weijer, C. Informing study participants of research results: an ethical imperative. IRB 25, 12–19 (2003).
Wonkam, A. & de Vries, J. Returning incidental findings in African genomics research. Nat. Genet. 52, 17–20 (2020).
de Vries, J. et al. Regulation of genomic and biobanking research in Africa: a content analysis of ethics guidelines, policies and procedures from 22 African countries. BMC Med. Ethics 18, 8 (2017). This comprehensive analysis of 30 ethics regulatory documents from 22 African countries concludes that there is a need for ethics guidelines in African countries to be adapted to the changing science policy landscape. Most pertinent are the principles of openness, storage, sharing and secondary use.
Barchi, F. & Little, M. T. National ethics guidance in sub-Saharan Africa on the collection and use of human biological specimens: a systematic review. BMC Med. Ethics 17, 64 (2016).
Ramsay, M., de Vries, J., Soodyall, H., Norris, S. A. & Sankoh, O. Ethical issues in genomic research on the African continent: experiences and challenges to ethics review committees. Hum. Genomics 8, 15 (2014).
van Panhuis, W. G. et al. A systematic review of barriers to data sharing in public health. BMC Public Health 14, 1144 (2014).
Qureshi, N., Modell, B. & Modell, M. Timeline: raising the profile of genetics in primary care. Nat. Rev. Genet. 5, 783–790 (2004).
Alwan, A. & Modell, B. Recommendations for introducing genetics services in developing countries. Nat. Rev. Genet. 4, 61–68 (2003).
Bentley, A. R., Callier, S. L. & Rotimi, C. N. Evaluating the promise of inclusion of African ancestry populations in genomics. NPJ Genom. Med. 5, 5 (2020).
Ramsay, M. Africa: continent of genome contrasts with implications for biomedical research and health. FEBS Lett. 586, 2813–2819 (2012).
Mulder, N. J. et al. Development of bioinformatics infrastructure for genomics research. Glob. Heart 12, 91–98 (2017).
Gootenberg, J. S. et al. Nucleic acid detection with CRISPR–Cas13a/C2c2. Science 356, 438–442 (2017).
Wilkinson, M. D. et al. The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016).
Samuels, D. C. et al. Heterozygosity ratio, a robust global genomic measure of autozygosity and its association with height and disease risk. Genetics 204, 893–904 (2016).
Schlebusch, C. M. et al. Genomic variation in seven Khoe-San groups reveals adaptation and complex African history. Science 338, 374–379 (2012).
Chatterjee, N., Shi, J. & Garcia-Closas, M. Developing and evaluating polygenic risk prediction models for stratified disease prevention. Nat. Rev. Genet. 17, 392–406 (2016).
Krapohl, E. et al. Multi-polygenic score approach to trait prediction. Mol. Psychiatry 23, 1368–1374 (2018).
Martin, A. R. et al. Human demographic history impacts genetic risk prediction across diverse populations. Am. J. Hum. Genet. 100, 635–649 (2017).
De La Vega, F. M. & Bustamante, C. D. Polygenic risk scores: a biased prediction? Genome Med. 10, 100 (2018).
Reisberg, S., Iljasenko, T., Lall, K., Fischer, K. & Vilo, J. Comparing distributions of polygenic risk scores of type 2 diabetes and coronary heart disease within different populations. PLoS ONE 12, e0179238 (2017).
Retshabile, G. et al. Whole-exome sequencing reveals uncaptured variation and distinct ancestry in the southern African population of Botswana. Am. J. Hum. Genet. 102, 731–743 (2018).
L.P. is a principal researcher at i3S, which is financed by Fundo Europeu de Desenvolvimento Regional (FEDER) funds through COMPETE 2020, Portugal 2020 and by Portuguese funds through Fundação para a Ciência e a Tecnologia/Ministério da Ciência, Tecnologia e Inovação (POCI-01-0145-FEDER-007274). L.M. is a Professor of Human Genetics at the University of Rwanda and principal investigator of a National Institutes of Health (NIH)-funded Human Heredity and Health in Africa (H3Africa) grant (U01MH115485) (transgenerational epigenomics of trauma and post-traumatic stress disorder in Rwanda). P.T. is a senior lecturer at the University of Ghana School of Public Health and the co-principal investigator of an NIH-funded H3Africa grant (U54HG010275). M.R. holds a South African Research Chair in Genomics and Bioinformatics of African populations hosted by the University of the Witwatersrand, funded by the Department of Science and Innovation, and administered by the National Research Foundation and is principal investigator of an NIH-funded H3Africa grant (U54HG006938). The views expressed in this Review do not necessarily reflect the views of the funding institutions.
The authors declare no competing interests.
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Africa CDC: http://www.africacdc.org/
African Society of Human Genetics (AfSHG): https://www.afshg.org/
H3Africa Genotyping Chip: https://www.h3abionet.org/h3africa-chip
H3Africa Guideline for the Return of Individual Genetic Research Findings: https://h3africa.org/wp-content/uploads/2018/05/H3Africa%20Feedback%20of%20Individual%20Genetic%20Results%20Policy.pdf
United Nations Sustainable Development: https://sustainabledevelopment.un.org/
United Nations World Population Prospects: https://population.un.org/wpp/
West African Genetic Medicine Centre (WAGMC): https://wagmc.org
World Economic Forum Precision Medicine Programme: https://www.weforum.org/communities/precision-medicine
- Precision medicine
An approach to clinical practice that includes information from state-of-the-art technologies to understand the underlying causes of a disease such that a patient can receive the most appropriate therapeutic intervention for the best possible health outcome.
An estimation of the degree of variation in a phenotype that is due to genetic variation between individuals. Heritability can be estimated from general pedigrees using linear mixed models and from genomic relatedness estimated from genetic markers, but traditionally was based on twin studies.
Two populations come into contact with one another, often due to migration, and interbreeding occurs, generating a hybrid or admixed descendant population.
- Coalescent models
Models that, assuming that variants sampled from a population may have originated from a common ancestor, reconstruct backwards in time how variants can be shown to originate from a single ancestor according to a random process in coalescence events. The model produces many theoretical genealogies that can be compared with the observed data to test assumptions about the demographic history of a population.
- Population structure
Significant differences in allele frequencies between populations or between subpopulations in a population.
- Linkage disequilibrium
(LD). A measure of the non-random association of alleles at different loci in a given population. LD is lower in African populations compared with European and Asian populations, given the more ancient ancestry of African populations.
- Bantu migration
A massive migration of Bantu-speaking peoples that began 5,000 years ago in the region of Cameroon/Nigeria towards the southern and eastern parts of the African continent, with genetic, linguistic and cultural impacts. Currently, Bantu-speakers make up ~30% of the African population of ~1.3 billion people.
- African diaspora
People of African origin or ancestry resident in non-African countries.
- Human Heredity and Health in Africa
(H3Africa). A pan-African consortium that aims to study the genomic and environmental determinants of common and rare diseases with the goal of improving the health of African populations.
- Genome-wide association study
(GWAS). A study that aims to identify candidate genetic markers associated with diseases or traits when applied to case–control cohorts or to quantitative traits within a cohort. This is done by genotyping several million common single-nucleotide polymorphisms from across the genome and applying statistical analyses to determine the probability of association between individual genetic markers and the phenotype.
A response to an environmental challenge such that an advantageous phenotype is enriched by positive or balancing selection.
- Balancing selection
Multiple alleles at a locus are maintained in the population gene pool at higher frequencies than expected from genetic drift. Two possible causes are heterozygote advantage (higher fitness of heterozygotes compared with homozygotes) and frequency-dependent selection (fitness of a phenotype depends on the relative frequency of other phenotypes in the population).
- Admixture mapping
A gene-mapping algorithm applied to case–control cohorts in a recently admixed population, where there are differences in the rates of the disease or trait between the two parental populations and those differences are partly due to differences in the frequencies of associated or causal variants. If the associated variant in one ancestry is protective, it will be enriched in the control group; if it is causative, it will be enriched in the case group.
- Positive selection
A phenotype (and its associated alleles) confers an advantage to the individual in response to a challenge (for example, environmental), such that the variant alleles that confer the favourable phenotype rapidly increase in frequency in the population, sometimes attaining fixation.
- Autochthonous African people
Indigenous or native African people.
- Epistatic interactions
Interactions pertaining to epistasis, when specific combinations of multiple genetic variants at different loci have non-additive effects on a specific phenotype (for example, disease or trait).
- Variants of uncertain significance
(VUS). Genetic variants in coding regions or regulatory regions of known disease-associated genes with insufficient evidence to assess their potential functional or phenotypic impact.
- Incidental findings
Genetic variants of potential disease relevance that are unrelated to the condition under investigation. For example, searching for a mutation responsible for developmental delay in a child and then detecting a BRCA1 breast cancer susceptibility variant.
- Polygenic risk scores
(PRSs). Predictive scores made up from multiple genetic loci associated with a trait and weighted by the relative contribution of each marker/allele to the trait that can be used to stratify a population on a spectrum of high to low risk. The higher the heritability of the trait, the more predictive the PRS will be; however, clinical use is still debatable.
One variant that exerts an effect or has an association with multiple different (but sometimes related) phenotypes.
- Precision public health
Using information about genomic variation in a population to guide practices and develop policies that will benefit the majority of individuals in a given population. For example, identifying a common pharmacogenomic variant in a population that predicts an adverse drug effect, such that it leads to a policy advising against using that drug as a first-line treatment in that population.
- Broad consent
Consent provided by a study participant for the use of their data and biospecimens for future research that could not be defined at the time the consent was obtained. The governance process of the resources are explained to participants and, usually, the future use will be approved by an ethics committee.
- Tiered consent
A consent process that has several independent requests for specific uses of data and biospecimens. For example, research participants can consent to one or more of the following: consent for use in specific research; consent for data sharing; and consent for data and biospecimen sharing, with information on how the process will be governed.
- Genomic medicine
The use of genetic information (genomic variants) to guide diagnosis and clinical interventions or to be used in weighing reproductive options.
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Pereira, L., Mutesa, L., Tindana, P. et al. African genetic diversity and adaptation inform a precision medicine agenda. Nat Rev Genet 22, 284–306 (2021). https://doi.org/10.1038/s41576-020-00306-8
Human Molecular Genetics (2021)