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Kamiza AB, Toure SM, Vujkovic M, Machipisa T, Soremekun OS, Kintu C, Corpas M, Pirie F, Young E, Gill D, Sandhu MS, Kaleebu P, Nyirenda M, Motala AA, Chikowore T, Fatumo S. Transferability of genetic risk scores in African populations. Nat Med 2022; 28:1163-1166. [PMID: 35654908 PMCID: PMC9205766 DOI: 10.1038/s41591-022-01835-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 04/20/2022] [Indexed: 01/02/2023]
Abstract
The poor transferability of genetic risk scores (GRSs) derived from European ancestry data in diverse populations is a cause of concern. We set out to evaluate whether GRSs derived from data of African American individuals and multiancestry data perform better in sub-Saharan Africa (SSA) compared to European ancestry-derived scores. Using summary statistics from the Million Veteran Program (MVP), we showed that GRSs derived from data of African American individuals enhance polygenic prediction of lipid traits in SSA compared to European and multiancestry scores. However, our GRS prediction varied greatly within SSA between the South African Zulu (low-density lipoprotein cholesterol (LDL-C), R2 = 8.14%) and Ugandan cohorts (LDL-C, R2 = 0.026%). We postulate that differences in the genetic and environmental factors between these population groups might lead to the poor transferability of GRSs within SSA. More effort is required to optimize polygenic prediction in Africa.
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Affiliation(s)
- Abram B Kamiza
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda
- Malawi Epidemiology and Intervention Research Unit, Lilongwe, Karonga, Malawi
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Sounkou M Toure
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda
- African Centre of Excellence in Bioinformatics, University of Science and Technologies of Bamako, Bamako, Mali
| | - Marijana Vujkovic
- Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, Hamilton, Ontario, Canada
| | - Tafadzwa Machipisa
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Hatter Institute for Cardiovascular Diseases Research in Africa (HICRA), Department of Medicine, University of Cape Town, Cape Town, South Africa
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
| | - Opeyemi S Soremekun
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda
| | - Christopher Kintu
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda
| | - Manuel Corpas
- Cambridge Precision Medicine Limited, ideaSpace, University of Cambridge Biomedical Innovation Hub, Cambridge, United Kingdom
- Institute of Continuing Education, Madingley Hall, University of Cambridge, Cambridge, UK
- Facultad de Ciencias de la Salud, Universidade Internacional de La Rioja, Madrid, Spain
| | - Fraser Pirie
- Department of Diabetes and Endocrinology, University of KwaZulu-Natal, Durban, South Africa
| | | | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London, London, UK
| | - Manjinder S Sandhu
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | | | | | - Ayesha A Motala
- Department of Diabetes and Endocrinology, University of KwaZulu-Natal, Durban, South Africa
| | - Tinashe Chikowore
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - Segun Fatumo
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda.
- MRC/UVRI and LSHTM, Entebbe, Uganda.
- London School of Hygiene and Tropical Medicine, London, UK.
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria.
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Maiga FO, Wele M, Toure SM, Keita M, Tangara CO, Refeld RR, Thiero O, Kayentao K, Diakite M, Dara A, Li J, Toure M, Sagara I, Djimdé A, Mather FJ, Doumbia SO, Shaffer JG. Artemisinin-based combination therapy for uncomplicated Plasmodium falciparum malaria in Mali: a systematic review and meta-analysis. Malar J 2021; 20:356. [PMID: 34461901 PMCID: PMC8404312 DOI: 10.1186/s12936-021-03890-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 08/20/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Artemisinin-based combination therapy (ACT) was deployed in 2005 as an alternative to chloroquine and is considered the most efficacious treatment currently available for uncomplicated falciparum malaria. While widespread artemisinin resistance has not been reported to date in Africa, recent studies have reported partial resistance in Rwanda. The purpose of this study is to provide a current systematic review and meta-analysis on ACT at Mali study sites, where falciparum malaria is highly endemic. METHODS A systematic review of the literature maintained in the bibliographic databases accessible through the PubMed, ScienceDirect and Web of Science search engines was performed to identify research studies on ACT occurring at Mali study sites. Selected studies included trials occurring at Mali study sites with reported polymerase chain reaction (PCR)-corrected adequate clinical and parasite response rates (ACPRcs) at 28 days. Data were stratified by treatment arm (artemether-lumefantrine (AL), the first-line treatment for falciparum malaria in Mali and non-AL arms) and analysed using random-effects, meta-analysis approaches. RESULTS A total of 11 studies met the inclusion criteria, and a risk of bias assessment carried out by two independent reviewers determined low risk of bias among all assessed criteria. The ACPRc for the first-line AL at Mali sites was 99.0% (95% CI (98.3%, 99.8%)), while the ACPRc among non-AL treatment arms was 98.9% (95% CI (98.3%, 99.5%)). The difference in ACPRcs between non-AL treatment arms and AL treatment arms was not statistically significant (p = .752), suggesting that there are potential treatment alternatives beyond the first-line of AL in Mali. CONCLUSIONS ACT remains highly efficacious in treating uncomplicated falciparum malaria in Mali. Country-specific meta-analyses on ACT are needed on an ongoing basis for monitoring and evaluating drug efficacy patterns to guide local malaria treatment policies, particularly in the wake of observed artemisinin resistance in Southeast Asia and partial resistance in Rwanda.
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Affiliation(s)
- Fatoumata O Maiga
- University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali.
| | - Mamadou Wele
- University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Sounkou M Toure
- University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Makan Keita
- University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | | | - Randi R Refeld
- Department of Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street #8310, Suite 1610, New Orleans, LA, 70112-2703, USA
| | - Oumar Thiero
- University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Kassoum Kayentao
- University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Mahamadou Diakite
- University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Antoine Dara
- University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Jian Li
- Department of Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street #8310, Suite 1610, New Orleans, LA, 70112-2703, USA
| | - Mahamoudou Toure
- University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Issaka Sagara
- University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Abdoulaye Djimdé
- University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
| | - Frances J Mather
- Department of Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street #8310, Suite 1610, New Orleans, LA, 70112-2703, USA
| | - Seydou O Doumbia
- University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali.
| | - Jeffrey G Shaffer
- Department of Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, 1440 Canal Street #8310, Suite 1610, New Orleans, LA, 70112-2703, USA.
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