This document summarizes three papers on population genetics and genomics research in African populations. The first paper discusses the African Genome Variation Project, which characterized genetic diversity in Africa and improved genomic studies on the continent. The second paper reviews pharmacogenetics studies in African populations, finding relatively few but highlighting their importance. The third paper summarizes prostate cancer genome-wide association studies, including initial studies identifying risk loci and more recent work identifying additional variants in African populations.

1. AFRICAN
POPULATION
GENETICS
By: David Osarieme Enoma
(RA-CApIC-ACE)
Supervisor: Prof. V.C. Osamor
Co-Supervisor: Prof. O.O. Ogunlana

2. OUTLINE OF PAPERS
• The African Genome Variation Project shapes medical
genetics in Africa
• A review of clinical pharmacogenetics studies in African
populations
• A Review of Prostate Cancer Genome-Wide Association
Studies (GWAS)
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3. THE AFRICAN GENOME VARIATION
PROJECT SHAPES MEDICAL
GENETICS IN AFRICA
(Gurdasani et al., 2015)

4. THE AFRICAN GENOME VARIATION
PROJECT(AGVP) SHAPES MEDICAL GENETICS
IN AFRICA
• Lack of genomic variation studies in African Population
which is useful in problems of Human Origins and
Disease Susceptibility especially in the problem of
cancer.
• AGVP provides a resource with which to design,
implement and interpret genomic studies in sub-
Saharan Africa and worldwide.
• AGVP systematically assessed genetic diversity among
1,481individualsfrom 18 ethno-linguistic groups from
sub-Saharan Africa (SSA)
4

5. THE AFRICAN GENOME VARIATION PROJECT
SHAPES MEDICAL GENETICS IN AFRICA
5
Figure 318 African
populations
studied in the AGVP
including 2
populations from the
1000 Genomes Project.
• The AGVP has evolved to help develop
local resources for public health and genomic
research that are currently lacking in the
continent.

6. EXPLORING RELATIONSHIPS AMONG
POPULATIONS AND ADMIXTURE
6
• The lack of knowledge of population relationships is a
problem and they used PCA to explore this problem.
• ADMIXTURE program supported evidence for
substantial Eurasian and HG ancestry in SSA.

7. ADMIXTURE CLUSTERING ANALYSIS FOR AGVP
SAMPLES COMBINED WITH THE 1000 GENOMES
PROJECT
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8. DESIGNING MEDICAL GENETICS
STUDIES IN AFRICA
8
• The 1000 genomes array had lower imputation
accuracy among Sotho, Zulu and Afro-Asiatic
populations, this shows poor representation of
African Haplotypes within the panel.
• However, Current genotype arrays and imputation
panels allowed for identification of relevant
association signals at most loci.
• Finally, Gurdasani et al., 2015 generated a panel
integrating the 1000Genomes Project phase I and
AGVP WGS panels

9. IMPROVEMENT IN STUDY DESIGN AND
RESULTS
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• There was an improvement in imputation accuracy
across the whole range of the allele frequency
spectrum relative to the 1000 genomes panel.
• They suggest that designing a pan-African
genotype array to effectively capture common
genetic variation across Africa is feasible, and
could greatly facilitate large-scale genomic
studies in Africa

10. CONCLUSION
• Africa is the most genetically diverse region in the
world, there are relatively modest differentiation
among populations representing the major sub-
populations in SSA and this study explored the
problem.
• The marked haplotype diversity within Africa has
important implications for the design of large-scale
studies and techniques which were addressed.
• Further research will help us identify and understand
signals of ancient admixture, patterns of historical
population movements and provide comprehensive
resource for genomic research which is unavailable.
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11. CLINICAL
PHARMACOGENETICS STUDIES
IN AFRICAN POPULATIONS
(Radouani et al., 2020)

12. INTRODUCTION
• Pharmacogenomics studies the influence of
genomic variations on drug processing and
response.
• Pharmacogenetics looks specifically at the impact
of variations in a single or few genes on drug
response.
• African pharmacogenetics studies have been
comparatively lower due to lack of capacity,
clinical applicability and knowledge.
• Great ethnolinguistic and genetic diversity is a
problem too.
12

13. SCOPE OF PHARMACOGENETIC
STUDIES
• Radouani et al. (2020) investigated the scope of
pharmacogenetics studies that have been
conducted in African populations.
13
Figure 1:
Pharmacogenetic
Studies conducted within
African Populations
segmented by Region.

14. SCOPE OF PHARMACOGENETIC
STUDIES CONTD.
• This review highlighted the major
pharmacogenetic studies done in African
populations. However scanty!
14
Figure 2: Pharmacogenetic
Studies done in African
Populations and the major
Diseases.

15. PHARMACOGENETIC STUDIES IN CVDS
• The CVD pharmacogenetics has been widely
investigated in African-American populations.
• Genetic variation in CYP2C9, VKORC1, CYP4F2 and
APOE has previously been investigated.
• In Morocco, rs1799853 and rs1057910 (CYP2C9), as
well as rs9923231 (VKORC1), have been associated
with weekly acenocoumarol dose.
• NO pharmacogenetic CVD studies in Nigerian
Population noted.
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16. CANCER PHARMACOGENETICS IN
AFRICAN POPULATIONS
• The molecular landscape of cancer differs by
geographical location and genetic ancestry and
African genomic diversity can help address this.
• African-American individuals have been found to
have 25% higher cancer mortality rates than
Caucasian Americans.
• ABCB1 (rs1045642) has been associated with
lower through plasma concentration of imatinib
in Nigerian CML patients
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17. CONCLUSION
• In another Egyptian study, rs2032582 (in ABCB1)
was associated with imatinib sensitivity and
resistance.
• This paper highlighted current progress in
African pharmacogenetic studies.
• However, there is relative paucity of work in this
area. More work must be done to identify
possible leads for precision medicine in African
Populations.
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18. A REVIEW OF PROSTATE CANCER
GENOME-WIDE
ASSOCIATION STUDIES (GWAS)
(Benafif et al., 2018)

19. INTRODUCTION
19
• Prostate cancer is the second most common cancer
in men worldwide.
• Cancer is complex and there are highly penetrant
genetic variants and moderate to commonly
occurring variants conferring lower risks.
Computational GWAS approaches are well suited
for this sort of problem.
• The first GWAS reported in 2006 was carried out in
prostate cancer and identified SNPs in 8q24.

20. VARIANTS IDENTIFIED BY GWAS
20
• 44 prostate cancer GWAS have been reported
(listed in NHGRI-EBI Catalogue of published
GWASs: http://www.ebi.ac.uk/gwas)
• In a study reported by Eeles and colleagues in
2008, a two-stage GWAS identified 7 novel
prostate cancer associated variants
• Rare predisposition variants involved in synthetic
association are likely to be limited to certain
ethnicities.

21. THE ONCO-ARRAY NETWORK
21
• The OncoArray project was established with the
long-term goal of providing a rigorous
knowledge base to enable clinical translation of
GWAS findings.
• Computational methods such as enrichment
analysis suggest that a large number of the
prostate cancer risk loci are enriched in multiple
functional regions.
• The OncoArray was used to genotype 46,939
prostate cancer cases and 27,910 controls of
European ancestry. They Identified 63 novel loci
related to prostate cancer susceptibility.

22. PROSTATE CANCER GWAS IN MEN OF
AFRICAN DESCENT
22
• A major problem is that Epidemiologic data have
long shown that the risk of prostate cancer
development as well as the mortality rate is
increased in men of African descent compared with
other ethnicities.
• A 2017 GWAS meta-analysis (22) of African men
combined data from 2prostate cancer consortia
and 2 large prostate cancer studies.
• Two novel signals were identified: rs75823044 on
13q34 [OR 1.55, 95% confidence interval (CI), 1.37–
1.76], and rs78554043 on 22q12.1 (OR 1.62; 95% CI,
1.39–1.89).

23. APPLICATIONS OF GWAS FINDINGS
• Prostate cancer susceptibility loci and polygenic
risk profiles are currently applied to the
genetically complex disease to find individuals at
risk.
• Germline variants influencing somatic alterations
could be used as biomarkers to guide the risk
stratification and/or management of men with
prostate cancer.
• They are also applied in Precision Medicine viz
predictors of aggressive prostate cancer and
treatment modality decisions.
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24. REFERENCES
• Benafif, S., Kote-Jarai, Z., & Eeles, R. A. (2018). A review of prostate
cancer Genome-Wide Association Studies (GWAS). Cancer
Epidemiology Biomarkers and Prevention 27(8), pp. 845–857.
https://doi.org/10.1158/1055-9965.EPI-16-1046
• Gurdasani, D., Carstensen, T., Tekola-Ayele, F., Pagani, L.,
Tachmazidou, I., Hatzikotoulas, K., Karthikeyan, S., Iles, L., Pollard, M.
O., Choudhury, A., Ritchie, G. R. S., Xue, Y., Asimit, J., Nsubuga, R. N.,
Young, E. H., Pomilla, C., Kivinen, K., Rockett, K., Kamali, A., … Sandhu,
M. S. (2015). The African Genome Variation Project shapes medical
genetics in Africa. Nature, 517(7534), 327–332.
https://doi.org/10.1038/nature13997
• Radouani, F., Zass, L., Hamdi, Y., Rocha, J. da, Sallam, R., Abdelhak, S.,
Ahmed, S., Azzouzi, M., Benamri, I., Benkahla, A., Bouhaouala-Zahar, B.,
Chaouch, M., Jmel, H., Kefi, R., Ksouri, A., Kumuthini, J., Masilela, P.,
Masimirembwa, C., Othman, H., … Mulder, N. (2020). A review of
clinical pharmacogenetics Studies in African populations. Personalized
Medicine, 17(2), 155–170. https://doi.org/10.2217/pme-2019-0110
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