Imputation-based meta-analysis of severe malaria in three African populations.
Combining data from genome-wide association studies (GWAS) conducted at different locations, using genotype imputation and fixed-effects meta-analysis, has been a powerful approach for dissecting complex disease genetics in populations of European ancestry. Here we investigate the feasibility of app...
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Language: | English |
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Public Library of Science (PLoS)
2013-05-01
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| Series: | PLoS Genetics |
| Online Access: | https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1003509&type=printable |
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| author | Gavin Band Quang Si Le Luke Jostins Matti Pirinen Katja Kivinen Muminatou Jallow Fatoumatta Sisay-Joof Kalifa Bojang Margaret Pinder Giorgio Sirugo David J Conway Vysaul Nyirongo David Kachala Malcolm Molyneux Terrie Taylor Carolyne Ndila Norbert Peshu Kevin Marsh Thomas N Williams Daniel Alcock Robert Andrews Sarah Edkins Emma Gray Christina Hubbart Anna Jeffreys Kate Rowlands Kathrin Schuldt Taane G Clark Kerrin S Small Yik Ying Teo Dominic P Kwiatkowski Kirk A Rockett Jeffrey C Barrett Chris C A Spencer Malaria Genomic Epidemiology Network Malaria Genomic Epidemiological Network |
| author_facet | Gavin Band Quang Si Le Luke Jostins Matti Pirinen Katja Kivinen Muminatou Jallow Fatoumatta Sisay-Joof Kalifa Bojang Margaret Pinder Giorgio Sirugo David J Conway Vysaul Nyirongo David Kachala Malcolm Molyneux Terrie Taylor Carolyne Ndila Norbert Peshu Kevin Marsh Thomas N Williams Daniel Alcock Robert Andrews Sarah Edkins Emma Gray Christina Hubbart Anna Jeffreys Kate Rowlands Kathrin Schuldt Taane G Clark Kerrin S Small Yik Ying Teo Dominic P Kwiatkowski Kirk A Rockett Jeffrey C Barrett Chris C A Spencer Malaria Genomic Epidemiology Network Malaria Genomic Epidemiological Network |
| author_sort | Gavin Band |
| collection | DOAJ |
| description | Combining data from genome-wide association studies (GWAS) conducted at different locations, using genotype imputation and fixed-effects meta-analysis, has been a powerful approach for dissecting complex disease genetics in populations of European ancestry. Here we investigate the feasibility of applying the same approach in Africa, where genetic diversity, both within and between populations, is far more extensive. We analyse genome-wide data from approximately 5,000 individuals with severe malaria and 7,000 population controls from three different locations in Africa. Our results show that the standard approach is well powered to detect known malaria susceptibility loci when sample sizes are large, and that modern methods for association analysis can control the potential confounding effects of population structure. We show that pattern of association around the haemoglobin S allele differs substantially across populations due to differences in haplotype structure. Motivated by these observations we consider new approaches to association analysis that might prove valuable for multicentre GWAS in Africa: we relax the assumptions of SNP-based fixed effect analysis; we apply Bayesian approaches to allow for heterogeneity in the effect of an allele on risk across studies; and we introduce a region-based test to allow for heterogeneity in the location of causal alleles. |
| format | Article |
| id | doaj-art-dd877dc78f1d428cbcceaa37cc85a325 |
| institution | OA Journals |
| issn | 1553-7390 1553-7404 |
| language | English |
| publishDate | 2013-05-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Genetics |
| spelling | doaj-art-dd877dc78f1d428cbcceaa37cc85a3252025-08-20T02:05:37ZengPublic Library of Science (PLoS)PLoS Genetics1553-73901553-74042013-05-0195e100350910.1371/journal.pgen.1003509Imputation-based meta-analysis of severe malaria in three African populations.Gavin BandQuang Si LeLuke JostinsMatti PirinenKatja KivinenMuminatou JallowFatoumatta Sisay-JoofKalifa BojangMargaret PinderGiorgio SirugoDavid J ConwayVysaul NyirongoDavid KachalaMalcolm MolyneuxTerrie TaylorCarolyne NdilaNorbert PeshuKevin MarshThomas N WilliamsDaniel AlcockRobert AndrewsSarah EdkinsEmma GrayChristina HubbartAnna JeffreysKate RowlandsKathrin SchuldtTaane G ClarkKerrin S SmallYik Ying TeoDominic P KwiatkowskiKirk A RockettJeffrey C BarrettChris C A SpencerMalaria Genomic Epidemiology NetworkMalaria Genomic Epidemiological NetworkCombining data from genome-wide association studies (GWAS) conducted at different locations, using genotype imputation and fixed-effects meta-analysis, has been a powerful approach for dissecting complex disease genetics in populations of European ancestry. Here we investigate the feasibility of applying the same approach in Africa, where genetic diversity, both within and between populations, is far more extensive. We analyse genome-wide data from approximately 5,000 individuals with severe malaria and 7,000 population controls from three different locations in Africa. Our results show that the standard approach is well powered to detect known malaria susceptibility loci when sample sizes are large, and that modern methods for association analysis can control the potential confounding effects of population structure. We show that pattern of association around the haemoglobin S allele differs substantially across populations due to differences in haplotype structure. Motivated by these observations we consider new approaches to association analysis that might prove valuable for multicentre GWAS in Africa: we relax the assumptions of SNP-based fixed effect analysis; we apply Bayesian approaches to allow for heterogeneity in the effect of an allele on risk across studies; and we introduce a region-based test to allow for heterogeneity in the location of causal alleles.https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1003509&type=printable |
| spellingShingle | Gavin Band Quang Si Le Luke Jostins Matti Pirinen Katja Kivinen Muminatou Jallow Fatoumatta Sisay-Joof Kalifa Bojang Margaret Pinder Giorgio Sirugo David J Conway Vysaul Nyirongo David Kachala Malcolm Molyneux Terrie Taylor Carolyne Ndila Norbert Peshu Kevin Marsh Thomas N Williams Daniel Alcock Robert Andrews Sarah Edkins Emma Gray Christina Hubbart Anna Jeffreys Kate Rowlands Kathrin Schuldt Taane G Clark Kerrin S Small Yik Ying Teo Dominic P Kwiatkowski Kirk A Rockett Jeffrey C Barrett Chris C A Spencer Malaria Genomic Epidemiology Network Malaria Genomic Epidemiological Network Imputation-based meta-analysis of severe malaria in three African populations. PLoS Genetics |
| title | Imputation-based meta-analysis of severe malaria in three African populations. |
| title_full | Imputation-based meta-analysis of severe malaria in three African populations. |
| title_fullStr | Imputation-based meta-analysis of severe malaria in three African populations. |
| title_full_unstemmed | Imputation-based meta-analysis of severe malaria in three African populations. |
| title_short | Imputation-based meta-analysis of severe malaria in three African populations. |
| title_sort | imputation based meta analysis of severe malaria in three african populations |
| url | https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1003509&type=printable |
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