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The protective effect of sickle cell haemoglobin against severe malaria depends on parasite genotype
9 Dec 2021

Gavin Band, Ellen M. Leffler, Muminatou Jallow, Fatoumatta Sisay-Joof, Carolyne M. Ndila, Alexander W. Macharia, Christina Hubbart, Anna E. Jeffreys, Kate Rowlands, Thuy Nguyen, Sónia Gonçalves, Cristina V. Ariani, Jim Stalker, Richard D. Pearson, Roberto Amato, Eleanor Drury, Giorgio Sirugo, Umberto d’Alessandro, Kalifa A. Bojang, Kevin Marsh, Norbert Peshu, Joseph W. Saelens, Mahamadou Diakité, Steve M. Taylor, David J. Conway, Thomas N. Williams, Kirk A. Rockett & Dominic P. Kwiatkowski

Malaria protection due to sickle haemoglobin depends on parasite genotype, 2021; DOI: 10.1038/s41586-021-04288-3

Human

This resource page accompanies the article “Malaria protection due to sickle haemoglobin depends on parasite genotype” which is published in Nature and available online: https://doi.org/10.1038/s41586-021-04288-3. This page provides information about data that is being released to accompany this manuscript, including:

  • A set of human and Plasmodium falciparum genotype calls that were used in the above analysis.
  • Plasmodium falciparum genomesequence data underlying the above calls.
  • Summary statistics from the association tests carried out in our paper.
  • And links to software that we developed for the analysis.

Background

We used DNA from over 4,000 children ascertained with severe malaria in the period 1995-2009 to test for association between human and P.falciparum genetic variants. All individuals were from Banjul, The Gambia, and from Kilifi County, Kenya, and were previously analysed for human genotypes (see doi:10.1038/s41467-019-13480-z and https://www.malariagen.net/resource/25/). For this study, we generated P.falciparum genome sequence reads using the Illumina X Ten platform and used this to identify and call parasite genetic variation. We then tested for association between human and parasite variants using a logistic regression approach implemented in the software HPTEST (https://www.well.ox.ac.uk/~gav/hptest). Full details of our data generation and processing are available in the above manuscript.

Content of the data release
The following datasets related to the above manuscript are available:

  • Plasmodium falciparum genome sequencing. DNA sequence reads aligning to the P.falciparum genome from all samples in our data have been deposited at the European Nucleotide Archive and are available under open-access terms. A full list of the relevant sample accessions is available on Zenodo (https://doi.org/10.5281/zenodo.5723515).
  • Human genotypes. Genome-wide human genotypes, and genotyping of specific loci for these samples has previously been released. This data is available from the European Genome-Phenome Archive under managed access terms. See https://www.malariagen.net/resource/25/ for full details.
  • A joint dataset of human and Plasmodium falciparum genotypes. The core dataset of genome-wide P.falciparum genotypes, and human genotypes in the specific regions analysed in our manuscript has been deposited at Zenodo (10.5281/zenodo.4973476) and is available under open-access terms.
  • Association summary statistics. A full set of association summary statistics, reflecting association tests between human and parasite variants in the 3,346 samples included in our discovery analysis, is also available on Zenodo (https://doi.org/10.5281/zenodo.5722497).

Note. our manuscript also makes use of P.falciparum transcriptional data that has previously been reported, including from Saelens et al, “Impact of Sickle Cell Trait Hemoglobin on the Intraerythrocytic Transcriptional Program of Plasmodium falciparum” mSphere 2021 https://doi.org/10.1128/mSphere.00755-21. Please see that manuscript for relevant data accessions.

Available software

We also developed two software packages to conduct the analysis in our paper:

  • Software for human-parasite association testing. The HPTEST software can be used to test for association between host and pathogen genotypes using a logistic regression approach. Full documentation can be found at https://www.well.ox.ac.uk/~gav/hptest.
  • Software for computing linkage disequilibrium (LD) metrics. The LDBIRD software can be used to compute between-locus LD metrics in human or parasite data. Full documentation can be found at https://www.well.ox.ac.uk/~gav/ldbird.

Source code for both packages is available as part of the QCTOOL package (https://code.enkre.net/qctool) under an open-source license. A snapshot of this code has also been deposited on Zenodo (https://doi.org/10.5281/zenodo.5685580). For the analysis in our paper, version 2.1.9 (revision 7b2ccee228) of the package was used.

Citation

Please use the following citation if you make use of the above data or software in published work:

Band, G., Leffler, E.M., Jallow, M. et al. Malaria protection due to sickle haemoglobin depends on parasite genotype. Nature (2021). https://doi.org/10.1038/s41586-021-04288-3

Acknowledgements and partner study information

We thank the patients and staff of Kilifi County Hospital and the KEMRI-Wellcome Trust Research Programme, Kilifi for their help with this study, and members of the Human Genetics Group in Kilifi for help with sample collection and processing. We thank the patients and staff at the Paediatric Department of the Royal Victoria Hospital in Banjul, Gambia for their help with the study. The human genetic data used in this study has previously been reported by the Malaria Genomic Epidemiology Network, and we thank all our colleagues who contributed to this previous work as part of MalariaGEN Consortial Project 1.

Details of the partner studies involved in the above work can be found here.