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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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