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1. Human candidate gene polymorphisms and risk of severe malaria in children in Kilifi, Kenya: a case-control association study

Author

Abathina, Amadou, Abubakar, Ismaela, Achidi, Eric, Agbenyega, Tsiri, Aiyegbo, Mohammed, Akoto, Alex, Allen, Angela, Allen, Stephen, Amenga-Etego, Lucas, Amodu, Folakemi, Amodu, Olukemi, Anchang-Kimbi, Judith, Ansah, Nana, Ansah, Patrick, Ansong, Daniel, Antwi, Sampson, Anyorigiya, Thomas, Apinjoh, Tobias, Asafo-Agyei, Emmanuel, Asoala, Victor, Atuguba, Frank, Auburn, Sarah, Bah, Abdou, Bamba, Kariatou, Bancone, Germana, Band, Gavin, Barnwell, David, Barry, Abdoulaye, Bauni, Evasius, Besingi, Richard, Bojang, Kalifa, Bougouma, Edith, Bull, Susan, Busby, George, Camara, Abdoulie, Camara, Landing, Campino, Susana, Carter, Richard, Carucci, Dan, Casals-Pascual, Climent, Ceesay, Ndey, Ceesay, Pa, Chau, Tran, Chuong, Ly, Clark, Taane, Clarke, Geraldine, Cole-Ceesay, Ramou, Conway, David, Cook, Katharine, Cook, Olivia, Cornelius, Victoria, Corran, Patrick, Correa, Simon, Cox, Sharon, Craik, Rachel, Danso, Bakary, Davis, Timothy, Day, Nicholas, Deloukas, Panos, Dembele, Awa, deVries, Jantina, Dewasurendra, Rajika, Diakite, Mahamadou, Diarra, Elizabeth, Dibba, Yaya, Diss, Andrea, Djimdé, Abdoulaye, Dolo, Amagana, Doumbo, Ogobara, Doyle, Alan, Drakeley, Chris, Drury, Eleanor, Duffy, Patrick, Dunstan, Sarah, Ebonyi, Augustine, Elhassan, Ahmed, Elhassan, Ibrahim, Elzein, Abier, Enimil, Anthony, Esangbedo, Pamela, Evans, Jennifer, Evans, Julie, Farrar, Jeremy, Fernando, Deepika, Fitzpatrick, Kathryn, Fullah, Janet, Garcia, Jacob, Ghansah, Anita, Gottleib, Michael, Green, Angie, Hart, Lee, Hennsman, Meike, Hien, Tran, Hieu, Nguyen, Hilton, Eliza, Hodgson, Abraham, Horstmann, Rolf, Hubbart, Christina, Hughes, Catherine, Hussein, Ayman, Hutton, Robert, Ibrahim, Muntaser, Ishengoma, Deus, Jaiteh, Jula, Jallow, Mariatou, Jallow, Muminatou, Jammeh, Kebba, Jasseh, Momodou, Jeffreys, Anna, Jobarteh, Amie, Johnson, Kimberly, Joseph, Sarah, Jyothi, Dushyanth, Kachala, David, Kamuya, Dorcas, Kanyi, Haddy, Karunajeewa, Harin, Karunaweera, Nadira, Keita, Momodou, Kerasidou, Angeliki, Khan, Aja, Kivinen, Katja, Kokwaro, Gilbert, Konate, Amadou, Konate, Salimata, Koram, Kwadwo, Kwiatkowski, Dominic, Laman, Moses, Le, Si, Leffler, Ellen, Lemnge, Martha, Lin, Enmoore, Ly, Alioune, Macharia, Alexander, MacInnis, Bronwyn, Mai, Nguyen, Makani, Julie, Malangone, Cinzia, Mangano, Valentina, Manjurano, Alphaxard, Manneh, Lamin, Manning, Laurens, Manske, Magnus, Marsh, Kevin, Marsh, Vicki, Maslen, Gareth, Maxwell, Caroline, Mbunwe, Eric, McCreight, Marilyn, Mead, Daniel, Mendy, Alieu, Mendy, Anthony, Mensah, Nathan, Michon, Pascal, Miles, Alistair, Miotto, Olivo, Modiano, David, Mohamed, Hiba, Molloy, Sile, Molyneux, Malcolm, Molyneux, Sassy, Moore, Mike, Moyes, Catherine, Mtei, Frank, Mtove, George, Mueller, Ivo, Mugri, Regina, Munthali, Annie, Mutabingwa, Theonest, Nadjm, Behzad, Ndi, Andre, Ndila, Carolyne, Newton, Charles, Niangaly, Amadou, Njie, Haddy, Njie, Jalimory, Njie, Madi, Njie, Malick, Njie, Sophie, Njiragoma, Labes, Nkrumah, Francis, Ntunthama, Neema, Nyika, Aceme, Nyirongo, Vysaul, O'Brien, John, Obu, Herbert, Oduro, Abraham, Ofori, Alex, Olaniyan, Subulade, Olaosebikan, Rasaq, Oluoch, Tom, Omotade, Olayemi, Oni, Olajumoke, Onykwelu, Emmanuel, Opi, Daniel, Orimadegun, Adebola, O'Riordan, Sean, Ouedraogo, Issa, Oyola, Samuel, Parker, Michael, Pearson, Richard, Pensulo, Paul, Peshu, Norbert, Phiri, Ajib, Phu, Nguyen, Pinder, Margaret, Pirinen, Matti, Plowe, Chris, Potter, Claire, Poudiougou, Belco, Puijalon, Odile, Quyen, Nguyen, Ragoussis, Ioannis, Ragoussis, Jiannis, Rasheed, Oba, Reeder, John, Reyburn, Hugh, Riley, Eleanor, Risley, Paul, Rockett, Kirk, Rodford, Joanne, Rogers, Jane, Rogers, William, Rowlands, Kate, Ruano-Rubio, Valentín, Sabally-Ceesay, Kumba, Sadiq, Abubacar, Saidy-Khan, Momodou, Saine, Horeja, Sakuntabhai, Anavaj, Sall, Abdourahmane, Sambian, David, Sambou, Idrissa, SanJoaquin, Miguel, Sepúlveda, Nuno, Shah, Shivang, Shelton, Jennifer, Siba, Peter, Silva, Nilupa, Simmons, Cameron, Simpore, Jaques, Singhasivanon, Pratap, Sinh, Dinh, Sirima, Sodiomon, Sirugo, Giorgio, Sisay-Joof, Fatoumatta, Sissoko, Sibiry, Small, Kerrin, Somaskantharajah, Elilan, Spencer, Chris, Stalker, Jim, Stevens, Marryat, Suriyaphol, Prapat, Sylverken, Justice, Taal, Bintou, Tall, Adama, Taylor, Terrie, Teo, Yik, Thai, Cao, Thera, Mahamadou, Titanji, Vincent, Toure, Ousmane, Troye-Blomberg, Marita, Usen, Stanley, Uyoga, Sophie, Vanderwal, Aaron, Wangai, Hannah, Watson, Renee, Williams, Thomas, Wilson, Michael, Wrigley, Rebecca, Yafi, Clarisse, Yamoah, Lawrence, Ndila, Carolyne M, Macharia, Alexander W, Nyutu, Gideon, Ojal, John, Shebe, Mohammed, Awuondo, Kennedy O, Mturi, Neema, Tsofa, Benjamin, Clark, Taane G, Kariuki, Silvia, Mackinnon, Margaret, Maitland, Kathryn, Kwiatkowski, Dominic P, Rockett, Kirk A, and Williams, Thomas N

Published
2018
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2. Genomic patterns of selection and differentiation in African populations and implications for mapping disease association

Author

Elzein, Abier

Subjects
616.9362
Abstract

The main objective of this thesis is to gain a better understanding of genomic patterns of natural selection and population differentiation in Africa, where there is great genetic diversity, and of the implications for genetic mapping of complex diseases. I began by studying two neighbouring villages in eastern Sudan that are of different ethnicity, Hausa and Masalit, and that appear to have different susceptibility to malaria and visceral leishmaniasis (VL). Specifically, I investigated patterns of linkage disequilibrium (LD) and haplotypic signals of positive selection in the 5q31 genomic region which contains immune genes that have been implicated in susceptibility to malaria and VL. In my first analysis, by genotyping 34 single nucleotide polymorphisms (SNPs) in the 5q31 region, I did not find signals of selection or population differentiation between the Hausa and Masalit using available statistical methods. I conceived the idea that patterns of LD might provide a more sensitive test of population differentiation, and I developed an approach for this using permutation analysis. This method revealed differentiation between the Hausa, the Masalit and other African ethnic groups. To better understand signals of selection, I next studied a region of the genome associated with a known malaria resistance factor, the haemoglobin S (HbS) variant of the HBB gene. By genotyping 26 SNPs in the region of the HBB gene, I observed a haplotype that extended in excess of 1 Mb, despite being at high frequency and spanning several recombinational hotspots. This long haplotype carried the HbS allele but, importantly, it could be readily detected without typing the HbS variant. Building on this observation, I designed a new method to screen the whole genome for long haplotypes that might be signals of selection, and developed a software programme to implement this method. I validated this method using haplotypic data for the Yoruba generated by the HapMap project and complemented by additional SNP data that I generated on HapMap cell lines, and found that the HbS allele resides on a haplotype that extends to 1.2 Mb, and is at strikingly high frequency compared to other haplotypes of similar length on the same chromosome. Next I applied this method to a large family-based association study of severe malaria in The Gambia, and identified several novel genomic regions with unusually long haplotypes of high frequency. These included a number of regions that may be associated with resistance to severe malaria, and which merit further investigation.

Published
2009
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4. A global network for investigating the genomic epidemiology of malaria

Author

Achidi, Eric Akum, Agbenyega, Tsiri, Allen, Stephen, Amodu, Olukemi, Bojang, Kalifa, Conway, David, Corran, Patrick, Deloukas, Panos, Djimde, Abdoulaye, Dolo, Amagana, Doumbo, Ogobara, Drakeley, Chris, Duffy, Patrick, Dunstan, Sarah, Evans, Jennifer, Farrar, Jeremy, Fernando, Deepika, Hien, Tran Tinh, Horstmann, Rolf, Ibrahim, Muntaser, Karunaweera, Nadira, Kokwaro, Gilbert, Koram, Kojo, Kwiatkowski, Dominic, Lemnge, Martha, Makani, Julie, Marsh, Kevin, Michon, Pascal, Modiano, David, Molyneux, Malcolm E., Mueller, Ivo, Mutabingwa, Theonest, Peshu, Norbert, Plowe, Chris, Puijalon, Odile, Ragoussis, Jiannis, Reeder, John, Reyburn, Hugh, Riley, Eleanor, Rogers, Jane, Sakuntabhai, Anavaj, Singhasivanon, Pratap, Sirima, Sodiomon, Sirugo, Giorgio, Tall, Adama, Taylor, Terrie, Thera, Mahamadou, Troye-Blomberg, Marita, Williams, Tom, Wilson, Michael, Amenga-Etego, Lucas, Apinjoh, Tobias O., Bougouma, Edith, Dewasurendra, Rajika, Diakite, Mahamadou, Enimil, Anthony, Hussein, Ayman, Ishengoma, Deus, Jallow, Muminatou, Lin, Enmoore, Ly, Alioune, Mangano, Valentina D., Manjurano, Alphaxard, Manning, Laurens, Ndila, Carolyne M., Nyirongo, Vysaul, Oluoch, Tom, Quyen, Nguyen T. N., Suriyaphol, Prapat, Toure, Ousman, Kwiatkowski, Dominic, Alcock, Daniel, Auburn, Sarah, Barnwell, David, Bull, Susan, Campino, Susana, deVries, Jantina, Elzein, Abier, Evans, Julie, Fitzpatrick, Kathryn, Ghansah, Anita, Green, Angie, Hart, Lee, Hilton, Eliza, Hubbart, Christina, Hughes, Catherine, Jeffreys, Anna E., Kivinen, Katja, MacInnis, Bronwyn, Manske, Magnus, Maslen, Gareth, McCreight, Marilyn, Mendy, Alieu, Moyes, Catherine, Nyika, Aceme, Potter, Claire, Risley, Paul, Rowlands, Kate, SanJoaquin, Miguel, Small, Kerrin, Somaskantharajah, Elilan, Stevens, Marryat, Teo, YikYing, Watson, Renee, Carucci, Dan, Cook, Katharine, Doyle, Alan, Duombo, Ogobara, Gottlieb, Michael, Kwiatkowski, Dominic, Rockett, Kirk A., Vanderwal, Aaron, Clark, Taane, Parker, Michael, and Wrigley, Rebecca

Published
2008
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5. Human candidate gene polymorphisms and risk of severe malaria in children in Kilifi, Kenya: a case-control association study

Author

Ndila, Carolyne M, Uyoga, Sophie, Macharia, Alexander W, Nyutu, Gideon, Peshu, Norbert, Ojal, John, Shebe, Mohammed, Awuondo, Kennedy O, Mturi, Neema, Tsofa, Benjamin, Sepúlveda, Nuno, Clark, Taane G, Band, Gavin, Clarke, Geraldine, Rowlands, Kate, Hubbart, Christina, Jeffreys, Anna, Kariuki, Silvia, Marsh, Kevin, Mackinnon, Margaret, Maitland, Kathryn, Kwiatkowski, Dominic P, Rockett, Kirk A, Williams, Thomas N, Abathina, Amadou, Abubakar, Ismaela, Achidi, Eric, Agbenyega, Tsiri, Aiyegbo, Mohammed, Akoto, Alex, Allen, Angela, Allen, Stephen, Amenga-Etego, Lucas, Amodu, Folakemi, Amodu, Olukemi, Anchang-Kimbi, Judith, Ansah, Nana, Ansah, Patrick, Ansong, Daniel, Antwi, Sampson, Anyorigiya, Thomas, Apinjoh, Tobias, Asafo-Agyei, Emmanuel, Asoala, Victor, Atuguba, Frank, Auburn, Sarah, Bah, Abdou, Bamba, Kariatou, Bancone, Germana, Barnwell, David, Barry, Abdoulaye, Bauni, Evasius, Besingi, Richard, Bojang, Kalifa, Bougouma, Edith, Bull, Susan, Busby, George, Camara, Abdoulie, Camara, Landing, Campino, Susana, Carter, Richard, Carucci, Dan, Casals-Pascual, Climent, Ceesay, Ndey, Ceesay, Pa, Chau, Tran, Chuong, Ly, Clark, Taane, Cole-Ceesay, Ramou, Conway, David, Cook, Katharine, Cook, Olivia, Cornelius, Victoria, Corran, Patrick, Correa, Simon, Cox, Sharon, Craik, Rachel, Danso, Bakary, Davis, Timothy, Day, Nicholas, Deloukas, Panos, Dembele, Awa, Devries, Jantina, Dewasurendra, Rajika, Diakite, Mahamadou, Diarra, Elizabeth, Dibba, Yaya, Diss, Andrea, Djimdé, Abdoulaye, Dolo, Amagana, Doumbo, Ogobara, Doyle, Alan, Drakeley, Chris, Drury, Eleanor, Duffy, Patrick, Dunstan, Sarah, Ebonyi, Augustine, Elhassan, Ahmed, Elhassan, Ibrahim, Elzein, Abier, Enimil, Anthony, Esangbedo, Pamela, Evans, Jennifer, Evans, Julie, Farrar, Jeremy, Fernando, Deepika, Fitzpatrick, Kathryn, Fullah, Janet, Garcia, Jacob, Ghansah, Anita, Gottleib, Michael, Green, Angie, Hart, Lee, Hennsman, Meike, Hien, Tran, Hieu, Nguyen, Hilton, Eliza, Hodgson, Abraham, Horstmann, Rolf, Hughes, Catherine, Hussein, Ayman, Hutton, Robert, Ibrahim, Muntaser, Ishengoma, Deus, Jaiteh, Jula, Jallow, Mariatou, Jallow, Muminatou, Jammeh, Kebba, Jasseh, Momodou, Jobarteh, Amie, Johnson, Kimberly, Joseph, Sarah, Jyothi, Dushyanth, Kachala, David, Kamuya, Dorcas, Kanyi, Haddy, Karunajeewa, Harin, Karunaweera, Nadira, Keita, Momodou, Kerasidou, Angeliki, Khan, Aja, Kivinen, Katja, Kokwaro, Gilbert, Konate, Amadou, Konate, Salimata, Koram, Kwadwo, Kwiatkowski, Dominic, Laman, Moses, Si, Le, Leffler, Ellen, Lemnge, Martha, Lin, Enmoore, Alioune, Ly, Macharia, Alexander, Macinnis, Bronwyn, Mai, Nguyen, Makani, Julie, Malangone, Cinzia, Mangano, Valentina, Manjurano, Alphaxard, Manneh, Lamin, Manning, Laurens, Manske, Magnus, Marsh, Vicki, Maslen, Gareth, Maxwell, Caroline, Mbunwe, Eric, Mccreight, Marilyn, Mead, Daniel, Mendy, Alieu, Mendy, Anthony, Mensah, Nathan, Michon, Pascal, Miles, Alistair, Miotto, Olivo, Modiano, David, Mohamed, Hiba, Molloy, Sile, Molyneux, Malcolm, Molyneux, Sassy, Moore, Mike, Moyes, Catherine, Mtei, Frank, Mtove, George, Mueller, Ivo, Mugri, Regina, Munthali, Annie, Mutabingwa, Theonest, Nadjm, Behzad, Ndi, Andre, Ndila, Carolyne, Newton, Charles, Niangaly, Amadou, Njie, Haddy, Njie, Jalimory, Njie, Madi, Njie, Malick, Njie, Sophie, Njiragoma, Labes, Nkrumah, Francis, Ntunthama, Neema, Nyika, Aceme, Nyirongo, Vysaul, O'Brien, John, Obu, Herbert, Oduro, Abraham, Ofori, Alex, Olaniyan, Subulade, Olaosebikan, Rasaq, Oluoch, Tom, Omotade, Olayemi, Oni, Olajumoke, Onykwelu, Emmanuel, Opi, Daniel, Orimadegun, Adebola, O'Riordan, Sean, Ouedraogo, Issa, Oyola, Samuel, Parker, Michael, Pearson, Richard, Pensulo, Paul, Phiri, Ajib, Phu, Nguyen, Pinder, Margaret, Pirinen, Matti, Plowe, Chris, Potter, Claire, Poudiougou, Belco, Puijalon, Odile, Quyen, Nguyen, Ragoussis, Ioannis, Ragoussis, Jiannis, Rasheed, Oba, Reeder, John, Reyburn, Hugh, Riley, Eleanor, Risley, Paul, Rockett, Kirk, Rodford, Joanne, Rogers, Jane, Rogers, William, Ruano-Rubio, Valentín, Sabally-Ceesay, Kumba, Sadiq, Abubacar, Saidy-Khan, Momodou, Saine, Horeja, Sakuntabhai, Anavaj, Sall, Abdourahmane, Sambian, David, Sambou, Idrissa, Sanjoaquin, Miguel, Shah, Shivang, Shelton, Jennifer, Siba, Peter, Silva, Nilupa, Simmons, Cameron, Simpore, Jaques, Singhasivanon, Pratap, Sinh, Dinh, Sirima, Sodiomon, Sirugo, Giorgio, Sisay-Joof, Fatoumatta, Sissoko, Sibiry, Small, Kerrin, Somaskantharajah, Elilan, Spencer, Chris, Stalker, Jim, Stevens, Marryat, Suriyaphol, Prapat, Sylverken, Justice, Taal, Bintou, Tall, Adama, Taylor, Terrie, Teo, Yik, Thai, Cao, Thera, Mahamadou, Titanji, Vincent, Toure, Ousmane, Troye-Blomberg, Marita, Usen, Stanley, Vanderwal, Aaron, Wangai, Hannah, Watson, Renee, Williams, Thomas, Wilson, Michael, Wrigley, Rebecca, Yafi, Clarisse, Yamoah, Lawrence, The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford, London School of Hygiene and Tropical Medicine (LSHTM), The Wellcome Trust Sanger Institute [Cambridge], St Mary's Hospital, Imperial College, TNW and MM are funded through awards from the Wellcome Trust (grants 091758 and 202800 [to TNW] and grant 088634 [to MM]) and DPK and TGC receive support from the Medical Research Council (grant G19/9 [to DPK] and grants MR/K000551/1, MR/M01360X/1, MR/N010469/1, and MC_PC_15103 [to TGC]). The research leading to these results received funding from the European Community's Seventh Framework Programme (FP7/2007-2013, under grant agreement 242095) and from the Medical Research Council (grant G0600718). MalariaGEN is supported by the Wellcome Trust (WT077383/Z/05/Z) and by the Foundation for the National Institutes of Health (grant 566) as part of the Bill & Melinda Gates' Grand Challenges in Global Health Initiative. The Resource Centre for Genomic Epidemiology of Malaria is supported by the Wellcome Trust (grant 090770/Z/09/Z). Support was also provided by the Medical Research Council (grant G0600718). The Wellcome Trust also provides core awards to the Wellcome Trust Centre for Human Genetics (grant 090532/Z/09/Z) and to the Wellcome Trust Sanger Institute (grant 098051). This work forms part of a larger collaboration with the MalariaGEN Consortium, whose members are listed at http://www.malariagen.net/projects/host/consortium-members. This paper is published with permission from the Director of the Kenya Medical Research Institute (KEMRI)., MalariaGEN Consortium (Anavaj Sakuntabhai), and European Project: 242095,EC:FP7:HEALTH,FP7-HEALTH-2009-single-stage,EVIMALAR(2009)

Subjects
Case-Control Studies, Child, Child, Preschool, Female, Gene Frequency, Genetic Predisposition to Disease, Humans, Kenya, Malaria, Male, Polymorphism, Genetic, Hematology, macromolecular substances, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Article, Genetic, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, parasitic diseases, [SDV.MP.PAR]Life Sciences [q-bio]/Microbiology and Parasitology/Parasitology, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Polymorphism, Preschool
Abstract

Summary Background Human genetic factors are important determinants of malaria risk. We investigated associations between multiple candidate polymorphisms—many related to the structure or function of red blood cells—and risk for severe Plasmodium falciparum malaria and its specific phenotypes, including cerebral malaria, severe malaria anaemia, and respiratory distress. Methods We did a case-control study in Kilifi County, Kenya. We recruited as cases children presenting with severe malaria to the high-dependency ward of Kilifi County Hospital. We included as controls infants born in the local community between Aug 1, 2006, and Sept 30, 2010, who were part of a genetics study. We tested for associations between a range of candidate malaria-protective genes and risk for severe malaria and its specific phenotypes. We used a permutation approach to account for multiple comparisons between polymorphisms and severe malaria. We judged p values less than 0·005 significant for the primary analysis of the association between candidate genes and severe malaria. Findings Between June 11, 1995, and June 12, 2008, 2244 children with severe malaria were recruited to the study, and 3949 infants were included as controls. Overall, 263 (12%) of 2244 children with severe malaria died in hospital, including 196 (16%) of 1233 with cerebral malaria. We investigated 121 polymorphisms in 70 candidate severe malaria-associated genes. We found significant associations between risk for severe malaria overall and polymorphisms in 15 genes or locations, of which most were related to red blood cells: ABO, ATP2B4, ARL14, CD40LG, FREM3, INPP4B, G6PD, HBA (both HBA1 and HBA2), HBB, IL10, LPHN2 (also known as ADGRL2), LOC727982, RPS6KL1, CAND1, and GNAS. Combined, these genetic associations accounted for 5·2% of the variance in risk for developing severe malaria among individuals in the general population. We confirmed established associations between severe malaria and sickle-cell trait (odds ratio [OR] 0·15, 95% CI 0·11–0·20; p=2·61 × 10−58), blood group O (0·74, 0·66–0·82; p=6·26 × 10−8), and –α3·7-thalassaemia (0·83, 0·76–0·90; p=2·06 × 10−6). We also found strong associations between overall risk of severe malaria and polymorphisms in both ATP2B4 (OR 0·76, 95% CI 0·63–0·92; p=0·001) and FREM3 (0·64, 0·53–0·79; p=3·18 × 10−14). The association with FREM3 could be accounted for by linkage disequilibrium with a complex structural mutation within the glycophorin gene region (comprising GYPA, GYPB, and GYPE) that encodes for the rare Dantu blood group antigen. Heterozygosity for Dantu was associated with risk for severe malaria (OR 0·57, 95% CI 0·49–0·68; p=3·22 × 10−11), as was homozygosity (0·26, 0·11–0·62; p=0·002). Interpretation Both ATP2B4 and the Dantu blood group antigen are associated with the structure and function of red blood cells. ATP2B4 codes for plasma membrane calcium-transporting ATPase 4 (the major calcium pump on red blood cells) and the glycophorins are ligands for parasites to invade red blood cells. Future work should aim at uncovering the mechanisms by which these polymorphisms can result in severe malaria protection and investigate the implications of these associations for wider health. Funding Wellcome Trust, UK Medical Research Council, European Union, and Foundation for the National Institutes of Health as part of the Bill & Melinda Gates Grand Challenges in Global Health Initiative.

Published
2018
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6. Candidate malaria susceptibility/protective SNPs in hospital and population-based studies: the effect of sub-structuring

Author

Rockett Kirk A, Mohamed Hiba S, Elzein Abier M, Hussein Aymen A, Eid Nahid A, Kwiatkowski Dominic P, and Ibrahim Muntaser E

Subjects
Arctic medicine. Tropical medicine, RC955-962, Infectious and parasitic diseases, RC109-216
Abstract

Abstract Background Populations of East Africa including Sudan, exhibit some of the highest indices of genetic diversity in the continent and worldwide. The current study aims to address the possible impact of population structure and population stratification on the outcome of case-control association-analysis of malaria candidate-genes in different Sudanese populations, where the pronounced genetic heterogeneity becomes a source of concern for the potential effect on the studies outcome. Methods A total of 72 SNPs were genotyped using the Sequenom® iPLEX Gold assay in 449 DNA samples that included; cases and controls from two village populations, malaria patients and out-patients from the area of Sinnar and additional controls consisting of healthy Nilo-Saharan speaking individuals. The population substructure was estimated using the Structure 2.2 programme. Results & Discussion The Hardy-Weinberg Equilibrium values were generally within expectation in Hausa and Massalit. However, in the Sinnar area there was a notable excess of homozygosity, which was attributed to the Whalund effect arising from population amalgamation within the sample. The programme STRUCTURE revealed a division of both Hausa and Massalit into two substructures with the partition in Hausa more pronounced than in Massalit; In Sinnar there was no defined substructure. More than 25 of the 72 SNPs assayed were informative in all areas. Some important SNPs were not differentially distributed between malaria cases and controls, including SNPs in CD36 and NOS2. A number of SNPs showed significant p-values for differences in distribution of genotypes between cases and controls including: rs1805015 (in IL4R1) (P = 0.001), rs17047661 (in CR1) (P = 0.02) and rs1800750 (TNF-376)(P = 0.01) in the hospital samples; rs1050828 (G6PD+202) (P = 0.02) and rs1800896 (IL10-1082) (P = 0.04) in Massalit and rs2243250 (IL4-589) (P = 0.04) in Hausa. Conclusions The difference in population structure partly accounts for some of these significant associations, and the strength of association proved to be sensitive to all levels of sub-structuring whether in the hospital or population-based study.

Published
2010
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7. Classical sickle beta-globin haplotypes exhibit a high degree of long-range haplotype similarity in African and Afro-Caribbean populations

Author

Jallow Muminatou, Pinder Margaret, Rockett Kirk, Trafford Clare, Elzein Abier, Hanchard Neil, Harding Rosalind, Kwiatkowski Dominic, and McKenzie Colin

Subjects
Genetics, QH426-470
Abstract

Abstract Background The sickle (βs) mutation in the beta-globin gene (HBB) occurs on five "classical" βs haplotype backgrounds in ethnic groups of African ancestry. Strong selection in favour of the βs allele – a consequence of protection from severe malarial infection afforded by heterozygotes – has been associated with a high degree of extended haplotype similarity. The relationship between classical βs haplotypes and long-range haplotype similarity may have both anthropological and clinical implications, but to date has not been explored. Here we evaluate the haplotype similarity of classical βs haplotypes over 400 kb in population samples from Jamaica, The Gambia, and among the Yoruba of Nigeria (Hapmap YRI). Results The most common βs sub-haplotype among Jamaicans and the Yoruba was the Benin haplotype, while in The Gambia the Senegal haplotype was observed most commonly. Both subtypes exhibited a high degree of long-range haplotype similarity extending across approximately 400 kb in all three populations. This long-range similarity was significantly greater than that seen for other haplotypes sampled in these populations (P < 0.001), and was independent of marker choice and marker density. Among the Yoruba, Benin haplotypes were highly conserved, with very strong linkage disequilibrium (LD) extending a megabase across the βs mutation. Conclusion Two different classical βs haplotypes, sampled from different populations, exhibit comparable and extensive long-range haplotype similarity and strong LD. This LD extends across the adjacent recombination hotspot, and is discernable at distances in excess of 400 kb. Although the multi-centric geographic distribution of βs haplotypes indicates strong subdivision among early Holocene sub-Saharan populations, we find no evidence that selective pressures imposed by falciparum malaria varied in intensity or timing between these subpopulations. Our observations also suggest that cis-acting loci, which may influence outcomes in sickle cell disease, could lie considerable distances away from β-globin.

Published
2007
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8. Genetic determinants of anti-malarial acquired immunity in a large multi-centre study

Author

Shelton, Jennifer MG, Corran, Patrick, Risley, Paul, Silva, Nilupa, Hubbart, Christina, Jeffreys, Anna, Rowlands, Kate, Craik, Rachel, Cornelius, Victoria, Hensmann, Meike, Molloy, Sile, Sepulveda, Nuno, Clark, Taane G, Band, Gavin, Clarke, Geraldine M, Spencer, Christopher CA, Kerasidou, Angeliki, Campino, Susana, Auburn, Sarah, Tall, Adama, Ly, Alioune Badara, Mercereau-Puijalon, Odile, Sakuntabhai, Anavaj, Djimdé, Abdoulaye, Maiga, Boubacar, Touré, Ousmane, Doumbo, Ogobara K, Dolo, Amagana, Troye-Blomberg, Marita, Mangano, Valentina D, Verra, Frederica, Modiano, David, Bougouma, Edith, Sirima, Sodiomon B, Ibrahim, Muntaser, Hussain, Ayman, Eid, Nahid, Elzein, Abier, Mohammed, Hiba, Elhassan, Ahmed, Elhassan, Ibrahim, Williams, Thomas N, Ndila, Carolyne, Macharia, Alexander, Marsh, Kevin, Manjurano, Alphaxard, Reyburn, Hugh, Lemnge, Martha, Ishengoma, Deus, Carter, Richard, Karunaweera, Nadira, Fernando, Deepika, Dewasurendra, Rajika, Drakeley, Christopher J, Riley, Eleanor M, Kwiatkowski, Dominic P, Rockett, Kirk A, MalariaGEN Consortium, The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford [Oxford], London School of Hygiene and Tropical Medicine (LSHTM), National Institute for Biological Standards and Control (NIBSC), Medicines and Healthcare Products Regulatory Agency (MHRA), Nuffield Department of Population Health [Oxford], The Wellcome Trust Sanger Institute [Cambridge], Unité d'Epidémiologie des Maladies Infectieuses, Institut Pasteur de Dakar, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Immunologie Moléculaire des Parasites, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Génétique fonctionnelle des Maladies infectieuses - Functional Genetics of Infectious Diseases, Centre National de la Recherche Scientifique (CNRS)-Institut Pasteur [Paris], Malaria Research and Training Center [Bamako, Mali], Université de Bamako, Stockholm University, Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome], Centre National de Recherche et de Formation sur le Paludisme [Ouagadougou, Burkina Faso] (CNRFP), University of Khartoum, KEMRI-Wellcome Trust Research Programme (KWTRP), Tumaini University Makumira, National Institute for Medical Research [Tanzania] (NIMR), University of Edinburgh, University of Colombo [Sri Lanka], MalariaGEN is supported by the Wellcome Trust (077383/Z/05/Z) and by the Foundation for the National Institutes of Health (566) as part of the Bill & Melinda Gates Grand Challenges in Global Health Initiative. The Resource Centre for Genomic Epidemiology of Malaria is supported by the Wellcome Trust (090770/Z/09/Z). Support was also provided by the Medical Research Council (G0600718). DPK receives support from the Medical Research Council (G19/9). CCAS was supported by a Wellcome Trust Career Development Fellowship (097364/Z/11/Z). The Wellcome Trust also provides core awards to The Wellcome Trust Centre for Human Genetics (075491/Z/04, 090532/Z/09/Z) and the Wellcome Trust Sanger Institute (077012/Z/05/Z). MTB and BM received funding through the EU Network of Excellence EviMalar. VDM was funded by a Biomalpar (European Community’s Sixth Framework Programme) PhD fellowship. FV was funded by the Italian Malaria Network, sponsored by Compagnia di San Paolo, Turin, Italy. TNW is supported by a Senior Research Fellowship from the Wellcome Trust (091758/Z/10/Z). This study was conducted as part of the Joint Malaria Programme, a collaboration between the National Institute for Medical Research (NIMR), Kilimanjaro Christian Medical College (KCMC), the London School of Hygiene and Tropical Medicine (LSHTM) and the Centre for Medical Parasitology, University of Copenhagen (CMP) with funding from the UK Medical Research Council (GG9901439) and the Danish International Development Agency. CJD is supported by the Wellcome Trust (091924). RD is supported by the University of Colombo Research Grants 2011 (AP/3/2011/PG/15)., European Project: 26843,BIOMALPAR, University of Oxford, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), and Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome] (UNIROMA)

Subjects
Male, Hemoglobin, Sickle, Antibodies, Protozoan, Sickle, MESH: Linear Models, MESH: Child, Child, HbAS, MESH: Infant, Newborn, Antibody, CD36, Genotype, Malaria, Sickle cell trait, Adolescent, Adult, Africa South of the Sahara, Child, Preschool, Female, Humans, Infant, Infant, Newborn, Linear Models, Sri Lanka, Young Adult, Infectious Diseases, Parasitology, MESH: Infant, MESH: Young Adult, Protozoan, [SDV.IMM]Life Sciences [q-bio]/Immunology, MESH: Malaria, Antibodies, parasitic diseases, MESH: Antibodies, Protozoan, Hemoglobin, MESH: Africa South of the Sahara, Preschool, MESH: Sri Lanka, MESH: Adolescent, MESH: Humans, Research, MESH: Child, Preschool, MESH: Adult, Newborn, MESH: Hemoglobin, Sickle, MESH: Male, antibody, cd36, genotype, hbas, malaria, sickle cell trait, infectious diseases, parasitology, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, MESH: Female
Abstract

Background Many studies report associations between human genetic factors and immunity to malaria but few have been reliably replicated. These studies are usually country-specific, use small sample sizes and are not directly comparable due to differences in methodologies. This study brings together samples and data collected from multiple sites across Africa and Asia to use standardized methods to look for consistent genetic effects on anti-malarial antibody levels. Methods Sera, DNA samples and clinical data were collected from 13,299 individuals from ten sites in Senegal, Mali, Burkina Faso, Sudan, Kenya, Tanzania, and Sri Lanka using standardized methods. DNA was extracted and typed for 202 Single Nucleotide Polymorphisms with known associations to malaria or antibody production, and antibody levels to four clinical grade malarial antigens [AMA1, MSP1, MSP2, and (NANP)4] plus total IgE were measured by ELISA techniques. Regression models were used to investigate the associations of clinical and genetic factors with antibody levels. Results Malaria infection increased levels of antibodies to malaria antigens and, as expected, stable predictors of anti-malarial antibody levels included age, seasonality, location, and ethnicity. Correlations between antibodies to blood-stage antigens AMA1, MSP1 and MSP2 were higher between themselves than with antibodies to the (NANP)4 epitope of the pre-erythrocytic circumsporozoite protein, while there was little or no correlation with total IgE levels. Individuals with sickle cell trait had significantly lower antibody levels to all blood-stage antigens, and recessive homozygotes for CD36 (rs321198) had significantly lower anti-malarial antibody levels to MSP2. Conclusion Although the most significant finding with a consistent effect across sites was for sickle cell trait, its effect is likely to be via reducing a microscopically positive parasitaemia rather than directly on antibody levels. However, this study does demonstrate a framework for the feasibility of combining data from sites with heterogeneous malaria transmission levels across Africa and Asia with which to explore genetic effects on anti-malarial immunity. Electronic supplementary material The online version of this article (doi:10.1186/s12936-015-0833-x) contains supplementary material, which is available to authorized users.

Published
2015
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9. Genetic determinants of anti-malarial acquired immunity in a large multi-centre study

Author

Shelton, Jennifer M. G., Corran, Patrick, Risley, Paul, Silva, Nilupa, Hubbart, Christina, Jeffreys, Anna, Rowlands, Kate, Craik, Rachel, Cornelius, Victoria, Hensmann, Meike, Molloy, Sile, Sepulveda, Nuno, Clark, Taane G., Band, Gavin, Clarke, Geraldine M., Spencer, Christopher C. A., Kerasidou, Angeliki, Campino, Susana, Auburn, Sarah, Tall, Adama, Ly, Alioune Badara, Mercereau-Puijalon, Odile, Sakuntabhai, Anavaj, Djimde, Abdoulaye, Maiga, Boubacar, Toure, Ousmane, Doumbo, Ogobara K., Dolo, Amagana, Troye-Blomberg, Marita, Mangano, Valentina D., Verra, Frederica, Modiano, David, Bougouma, Edith, Sirima, Sodiomon B., Ibrahim, Muntaser, Hussain, Ayman, Eid, Nahid, Elzein, Abier, Mohammed, Hiba, Elhassan, Ahmed, Elhassan, Ibrahim, Williams, Thomas N., Ndila, Carolyne, Macharia, Alexander, Marsh, Kevin, Manjurano, Alphaxard, Reyburn, Hugh, Lemnge, Martha, Ishengoma, Deus, Carter, Richard, Karunaweera, Nadira, Fernando, Deepika, Dewasurendra, Rajika, Drakeley, Christopher J., Riley, Eleanor M., Kwiatkowski, Dominic P., Rockett, Kirk A., Shelton, Jennifer M. G., Corran, Patrick, Risley, Paul, Silva, Nilupa, Hubbart, Christina, Jeffreys, Anna, Rowlands, Kate, Craik, Rachel, Cornelius, Victoria, Hensmann, Meike, Molloy, Sile, Sepulveda, Nuno, Clark, Taane G., Band, Gavin, Clarke, Geraldine M., Spencer, Christopher C. A., Kerasidou, Angeliki, Campino, Susana, Auburn, Sarah, Tall, Adama, Ly, Alioune Badara, Mercereau-Puijalon, Odile, Sakuntabhai, Anavaj, Djimde, Abdoulaye, Maiga, Boubacar, Toure, Ousmane, Doumbo, Ogobara K., Dolo, Amagana, Troye-Blomberg, Marita, Mangano, Valentina D., Verra, Frederica, Modiano, David, Bougouma, Edith, Sirima, Sodiomon B., Ibrahim, Muntaser, Hussain, Ayman, Eid, Nahid, Elzein, Abier, Mohammed, Hiba, Elhassan, Ahmed, Elhassan, Ibrahim, Williams, Thomas N., Ndila, Carolyne, Macharia, Alexander, Marsh, Kevin, Manjurano, Alphaxard, Reyburn, Hugh, Lemnge, Martha, Ishengoma, Deus, Carter, Richard, Karunaweera, Nadira, Fernando, Deepika, Dewasurendra, Rajika, Drakeley, Christopher J., Riley, Eleanor M., Kwiatkowski, Dominic P., and Rockett, Kirk A.

Abstract

Background: Many studies report associations between human genetic factors and immunity to malaria but few have been reliably replicated. These studies are usually country-specific, use small sample sizes and are not directly comparable due to differences in methodologies. This study brings together samples and data collected from multiple sites across Africa and Asia to use standardized methods to look for consistent genetic effects on anti-malarial antibody levels. Methods: Sera, DNA samples and clinical data were collected from 13,299 individuals from ten sites in Senegal, Mali, Burkina Faso, Sudan, Kenya, Tanzania, and Sri Lanka using standardized methods. DNA was extracted and typed for 202 Single Nucleotide Polymorphisms with known associations to malaria or antibody production, and antibody levels to four clinical grade malarial antigens [AMA1, MSP1, MSP2, and (NANP) 4] plus total IgE were measured by ELISA techniques. Regression models were used to investigate the associations of clinical and genetic factors with antibody levels. Results: Malaria infection increased levels of antibodies to malaria antigens and, as expected, stable predictors of anti-malarial antibody levels included age, seasonality, location, and ethnicity. Correlations between antibodies to blood-stage antigens AMA1, MSP1 and MSP2 were higher between themselves than with antibodies to the (NANP)(4) epitope of the pre-erythrocytic circumsporozoite protein, while there was little or no correlation with total IgE levels. Individuals with sickle cell trait had significantly lower antibody levels to all blood-stage antigens, and recessive homozygotes for CD36 (rs321198) had significantly lower anti-malarial antibody levels to MSP2. Conclusion: Although the most significant finding with a consistent effect across sites was for sickle cell trait, its effect is likely to be via reducing a microscopically positive parasitaemia rather than directly on antibody levels. However, this study does demons

Published
2015
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12. Y Chromosome Lineage- and Village-Specific Genes on Chromosomes 1p22 and 6q27 Control Visceral Leishmaniasis in Sudan

Author

Miller, E. Nancy, primary, Fadl, Manal, additional, Mohamed, Hiba S, additional, Elzein, Abier, additional, Jamieson, Sarra E, additional, Cordell, Heather J, additional, Peacock, Christopher S, additional, Fakiola, Michaela, additional, Raju, Madhuri, additional, Khalil, Eltahir A, additional, Elhassan, Ahmed, additional, Musa, Ahmed M, additional, Ibrahim, Muntaser E, additional, and Blackwell, Jenefer M, additional

Published
2007
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13. Y Chromosome Lineage- and Village-Specific Genes on Chromosomes 1p22 and 6q27 Control Visceral Leishmaniasis in The Sudan

Author

Miller, E. Nancy, primary, Fadl, Manal, additional, Mohamed, Hiba S, additional, Elzein, Abier, additional, Jamieson, Sarra E, additional, Cordell, Heather J, additional, Peacock, Christopher S, additional, Fakiola, Michaela, additional, Raju, Madhuri, additional, Khalil, Eltahir Awad Gasim, additional, Elhassan, Ahmed, additional, Musa, Ahmed M, additional, Ibrahim, Muntaser E, additional, and Blackwell, Jenefer M, additional

Published
2005
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14. Genomic, patterns of selection and differentiation in African populations and implications for mapping disease association

Author

Elzein, Abier and Elzein, Abier

Abstract

The main objective of this thesis is to gain a better understanding of genomic patterns of natural selection and population differentiation in Africa, where there is great genetic diversity, and of the implications for genetic mapping of complex diseases. I began by studying two neighbouring villages in eastern Sudan that are of different ethnicity, Hausa and Masalit, and that appear to have different susceptibility to malaria and visceral leishmaniasis (VL). Specifically, I investigated patterns of linkage disequilibrium (LD) and haplotypic signals of positive selection in the 5q31 genomic region which contains immune genes that have been implicated in susceptibility to malaria and VL. In my first analysis, by genotyping 34 single nucleotide polymorphisms (SNPs) in the 5q31 region, I did not find signals of selection or population differentiation between the Hausa and Masalit using available statistical methods. I conceived the idea that patterns of LD might provide a more sensitive test of population differentiation, and I developed an approach for this using permutation analysis. This method revealed differentiation between the Hausa, the Masalit and other African ethnic groups. To better understand signals of selection, I next studied a region of the genome associated with a known malaria resistance factor, the haemoglobin S (HbS) variant of the HBB gene. By genotyping 26 SNPs in the region of the HBB gene, I observed a haplotype that extended in excess of 1 Mb, despite being at high frequency and spanning several recombinational hotspots. This long haplotype carried the HbS allele but, importantly, it could be readily detected without typing the HbS variant. Building on this observation, I designed a new method to screen the whole genome for long haplotypes that might be signals of selection, and developed a software programme to implement this method. I validated this method

15. Genomic, patterns of selection and differentiation in African populations and implications for mapping disease association

Author

Elzein, Abier and Elzein, Abier

Abstract

The main objective of this thesis is to gain a better understanding of genomic patterns of natural selection and population differentiation in Africa, where there is great genetic diversity, and of the implications for genetic mapping of complex diseases. I began by studying two neighbouring villages in eastern Sudan that are of different ethnicity, Hausa and Masalit, and that appear to have different susceptibility to malaria and visceral leishmaniasis (VL). Specifically, I investigated patterns of linkage disequilibrium (LD) and haplotypic signals of positive selection in the 5q31 genomic region which contains immune genes that have been implicated in susceptibility to malaria and VL. In my first analysis, by genotyping 34 single nucleotide polymorphisms (SNPs) in the 5q31 region, I did not find signals of selection or population differentiation between the Hausa and Masalit using available statistical methods. I conceived the idea that patterns of LD might provide a more sensitive test of population differentiation, and I developed an approach for this using permutation analysis. This method revealed differentiation between the Hausa, the Masalit and other African ethnic groups. To better understand signals of selection, I next studied a region of the genome associated with a known malaria resistance factor, the haemoglobin S (HbS) variant of the HBB gene. By genotyping 26 SNPs in the region of the HBB gene, I observed a haplotype that extended in excess of 1 Mb, despite being at high frequency and spanning several recombinational hotspots. This long haplotype carried the HbS allele but, importantly, it could be readily detected without typing the HbS variant. Building on this observation, I designed a new method to screen the whole genome for long haplotypes that might be signals of selection, and developed a software programme to implement this method. I validated this method

16. Genetic determinants of anti-malarial acquired immunity in a large multi-centre study.

Author

Shelton JM, Corran P, Risley P, Silva N, Hubbart C, Jeffreys A, Rowlands K, Craik R, Cornelius V, Hensmann M, Molloy S, Sepulveda N, Clark TG, Band G, Clarke GM, Spencer CC, Kerasidou A, Campino S, Auburn S, Tall A, Ly AB, Mercereau-Puijalon O, Sakuntabhai A, Djimdé A, Maiga B, Touré O, Doumbo OK, Dolo A, Troye-Blomberg M, Mangano VD, Verra F, Modiano D, Bougouma E, Sirima SB, Ibrahim M, Hussain A, Eid N, Elzein A, Mohammed H, Elhassan A, Elhassan I, Williams TN, Ndila C, Macharia A, Marsh K, Manjurano A, Reyburn H, Lemnge M, Ishengoma D, Carter R, Karunaweera N, Fernando D, Dewasurendra R, Drakeley CJ, Riley EM, Kwiatkowski DP, and Rockett KA

Subjects
Adolescent, Adult, Africa South of the Sahara epidemiology, Antibodies, Protozoan blood, Child, Child, Preschool, Female, Hemoglobin, Sickle genetics, Humans, Infant, Infant, Newborn, Linear Models, Male, Sri Lanka epidemiology, Young Adult, Antibodies, Protozoan immunology, Malaria epidemiology, Malaria genetics, Malaria immunology
Abstract

Background: Many studies report associations between human genetic factors and immunity to malaria but few have been reliably replicated. These studies are usually country-specific, use small sample sizes and are not directly comparable due to differences in methodologies. This study brings together samples and data collected from multiple sites across Africa and Asia to use standardized methods to look for consistent genetic effects on anti-malarial antibody levels., Methods: Sera, DNA samples and clinical data were collected from 13,299 individuals from ten sites in Senegal, Mali, Burkina Faso, Sudan, Kenya, Tanzania, and Sri Lanka using standardized methods. DNA was extracted and typed for 202 Single Nucleotide Polymorphisms with known associations to malaria or antibody production, and antibody levels to four clinical grade malarial antigens [AMA1, MSP1, MSP2, and (NANP)4] plus total IgE were measured by ELISA techniques. Regression models were used to investigate the associations of clinical and genetic factors with antibody levels., Results: Malaria infection increased levels of antibodies to malaria antigens and, as expected, stable predictors of anti-malarial antibody levels included age, seasonality, location, and ethnicity. Correlations between antibodies to blood-stage antigens AMA1, MSP1 and MSP2 were higher between themselves than with antibodies to the (NANP)4 epitope of the pre-erythrocytic circumsporozoite protein, while there was little or no correlation with total IgE levels. Individuals with sickle cell trait had significantly lower antibody levels to all blood-stage antigens, and recessive homozygotes for CD36 (rs321198) had significantly lower anti-malarial antibody levels to MSP2., Conclusion: Although the most significant finding with a consistent effect across sites was for sickle cell trait, its effect is likely to be via reducing a microscopically positive parasitaemia rather than directly on antibody levels. However, this study does demonstrate a framework for the feasibility of combining data from sites with heterogeneous malaria transmission levels across Africa and Asia with which to explore genetic effects on anti-malarial immunity.

Published
2015
Full Text
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