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Malaria is a cause of iron deficiency in African children

Abstract

Malaria and iron deficiency (ID) are common and interrelated public health problems in African children. Observational data suggest that interrupting malaria transmission reduces the prevalence of ID1. To test the hypothesis that malaria might cause ID, we used sickle cell trait (HbAS, rs334), a genetic variant that confers specific protection against malaria2, as an instrumental variable in Mendelian randomization analyses. HbAS was associated with a 30% reduction in ID among children living in malaria-endemic countries in Africa (n = 7,453), but not among individuals living in malaria-free areas (n = 3,818). Genetically predicted malaria risk was associated with an odds ratio of 2.65 for ID per unit increase in the log incidence rate of malaria. This suggests that an intervention that halves the risk of malaria episodes would reduce the prevalence of ID in African children by 49%.

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Fig. 1: Sickle cell trait (HbAS) is associated with protection from ID.
Fig. 2: How malaria might cause a hepcidin-mediated blockade of iron absorption and recycling leading to ID.

Data availability

All data are available in the main text or in the Supplementary Information. Primary individual-level de-identified data for the Kilifi, Kenya; Entebbe, Uganda; Banfora, Burkina Faso; and West Kiang, The Gambia cohorts are available in Harvard Dataverse at https://doi.org/10.7910/DVN/UKGRVJ; applications for access to these data and to the Nairobi dataset can be made through the Data Governance Committee (dgc@kemri-wellcome.org). Data from the 2015–2016 MMS are available from the DHS Program at https://dhsprogram.com/what-we-do/survey/survey-display-483.cfm. The data underlying the results from the Ghana site are owned by the UNICEF Ghana and the Ministry of Health Ghana and contain confidential, identifying information. Data are available from the UNICEF Ghana (accra@unicef.org) for researchers who meet the criteria for access to confidential data. De-identified data from the western Kenya study are available on Open Science Framework at the following link: https://osf.io/dsrv2/. Data from the Sud Kivu and Kongo Central, DRC studies are available at https://doi.org/10.7910/DVN/RNWYR8. All data used in the analysis of the MOMS Project cohort (Muheza, Tanzania) are available under human data transfer agreement for purposes of reproducing or extending the analysis. Data for the Cameroon study are available upon reasonable request to the survey representative A. Ndjebayi (andjebayi@hki.org), Helen Keller International, Cameroon Office, Rue 1771, Bastos, BP 14227, Yaoundé. All JHS data are available at https://www.jacksonheartstudy.org/Research/Study-Data/Data-Access. Additionally, much of the JHS phenotype data are available at BioLINCC (https://biolincc.nhlbi.nih.gov/studies/jhs/), and data for genetic analyses are available through dbGaP at phs000286. Source data are provided with this paper.

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Acknowledgements

We thank all study participants who contributed to this study and staff involved with consent, sample and data collection and preparation. This work was funded by Wellcome (grant nos. (110255 to S.H.A.), (202800 to T.N.W.), (103951 to A.O.E.), (106289 to A.J.M.) and (064693, 079110, 095778 to A.M.E.)) and by core awards to the KEMRI-Wellcome Trust Research Programme (203077), the Wellcome Centre for Human Genetics (090532, 203141) and the Wellcome Sanger Institute (098051, 206194). A.J.M. was also supported by an Oxford University Clinical Academic School Transitional Fellowship. R.W.S. is funded by a Wellcome Trust Principal Fellowship (nos. 103602 and 212176). J.M.M. was supported through the DELTAS Africa Initiative (DEL-15-003). The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences’ Alliance for Accelerating Excellence in Science in Africa and is supported by the New Partnership for Africa’s Development Planning and Coordinating (NEPAD) Agency with funding from Wellcome (107769) and the UK government. The views expressed in this publication are those of the author(s) and not necessarily those of the African Academy of Sciences, the NEPAD Agency, Wellcome or the UK government. G.D.S. and R.M. are supported by the MRC IEU (grant code, MC_UU_00011/1). Funding for the conduct of the micronutrient survey in Ghana was provided by the UNICEF and Canada’s Ministry of Foreign Affairs, Trade and Development through an agreement between the UNICEF Ghana and the University of Ghana (43210308). The overall Malawi Demographic Health Survey was funded by Irish Aid, the World Bank and the UNICEF with technical assistance from the Centers for Disease Control and Prevention and Emory University. The Western Kenya study was supported by the Thrasher Research Fund (award no. 11860), the Bill & Melinda Gates Foundation (OPPGD759) and the US Agency for International Development (AID-OAA-F-13-00040), and K.A.B. was supported by a National Institutes of Health Research Training grant R25 TW009343, funded by the Fogarty International Center and the University of California Global Health Institute. The MOMS Project in Muheza, Tanzania was supported by the National Institute of Allergy and Infectious Diseases (NIAID), the National Institutes of Health (grant AI52059), and M.F. and P.E.D. are supported by the Intramural Research Program of the NIAID. The Cameroon study received support from Sight and Life and from the Thrasher Research Fund (award 12144). L.M.R. was supported by T32 HL129982. The Gambian work was supported by the UK MRC (U1232661351, U105960371 and MC-A760-5QX00) and DFID under the MRC/DFID Concordat. The JHS is supported and conducted in collaboration with Jackson State University (HHSN268201800013I), Tougaloo College (HHSN268201800014I), the Mississippi State Department of Health (HHSN268201800015I) and the University of Mississippi Medical Center (HHSN268201800010I, HHSN268201800011I and HHSN268201800012I) contracts from the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute on Minority Health and Health Disparities. We also wish to thank the staff and participants of the JHS. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Whole-genome sequencing for the Trans-Omics in Precision Medicine (TOPMed) program was supported by NHLBI. Whole-genome sequencing for ‘NHLBI TOPMed: The Jackson Heart Study’ (phs000964) was performed at the University of Washington Northwest Genomics Center (HHSN268201100037C). Centralized read mapping and genotype calling along with variant quality metrics and filtering were performed by the TOPMed Informatics Research Center (3R01HL-117626-02S1; contract HHSN268201800002I). Phenotype harmonization, data management, sample identity quality control and general study coordination were provided by the TOPMed Data Coordinating Center (3R01HL-120393-02S1; contract HHSN268201800001I). We gratefully acknowledge the studies and participants who provided biological samples and data for TOPMed.

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Contributions

J.M.M., R.M., G.D.S., A.M.E., T.N.W. and S.H.A. conceptualized and designed the methods for the research project; J.M.M. performed the analyses; J.M.M., A.J.M., E.L.W., A.O.E., C.K., A.M., W.K., F.M.N., A.W.M., C.J.N., J.M., S.A.L., S.K.M., L.M.R., C.L.C., S.B.S., A.D., A.B.T., M.F., M.G., S.A.-A., J.P.W., R.W., S.A.M., R.W.S., A.V.S.H., K.A.R., M.S.S., D.P.K., A.M.P., K.A.B., A.N., C.P.S., R.E.-S., T.J.G., C.D.K., P.S.S., P.B., P.E.D., A.M.E., T.N.W. and S.H.A. were responsible for generation of resources and curation of data; A.J.M., P.B., A.M.E., T.N.W. and S.H.A. were responsible for funding acquisition and supervision; J.M.M. and S.H.A. were responsible for writing the manuscript; and all co-authors reviewed the manuscript.

Corresponding authors

Correspondence to John Muthii Muriuki or Sarah H. Atkinson.

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Peer review information Nature Medicine thanks Sant-Rayn Pasricha, Olugbenga Mokuolu, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Editor recognition statement: Joao Monteiro was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Extended data

Extended Data Fig. 1 A meta-analysis of previous African studies investigating the effect of α-thalassemia and G6PD A and A- polymorphisms on uncomplicated febrile malaria.

Overall represents a fixed-effect meta-analysis of study-specific incidence rate ratio (IRR) by genetic polymorphism. Error bars indicate 95% confidence intervals. n shows the number of individuals included in the analysis. Few studies included G6PD homozygous females and numbers were small (Table S2). Het, heterozygous; Hom, homozygous.

Source data

Extended Data Fig. 2 A meta-analysis of the effect of sickle cell trait on iron deficiency anemia (IDA).

Overall represents a fixed-effect meta-analysis of cohort-specific odds ratios. Error bars indicate 95% confidence intervals. n shows the number of individuals included in the analysis. Numbers for IDA are fewer compared to those for ID since not all children had hemoglobin concentrations measured.

Extended Data Fig. 3 A meta-analysis of the effect of sickle cell trait on iron deficiency (ID) regression-corrected for inflammation.

ID was defined using ferritin levels adjusted for the effects of inflammation using a regression-correction approach as developed by BRINDA. Overall represents a fixed-effect meta-analysis of cohort-specific odds ratios. Error bars indicate 95% confidence intervals. n shows the number of individuals included in the analysis.

Extended Data Fig. 4 A meta-analysis of the effect of sickle cell trait on uncomplicated febrile malaria.

Overall represents a fixed-effect meta-analysis of study-specific incidence rate ratio (IRR). Error bars indicate 95% confidence intervals. n shows the number of individuals included in the analysis.

Source data

Extended Data Fig. 5 How HbAS, a genetic proxy for malaria exposure, may protect children from iron deficiency.

a, Individuals carrying normal beta hemoglobin gene (HbAA) are not protected from malaria. Malaria up-regulates production of hepcidin through inflammatory and non-inflammatory pathways and by increasing the prevalence of other infections. Hepcidin in turn blocks iron absorption. b, Sickle cell trait (HbAS) partially protects individuals from malaria infection, therefore inflammation is reduced leading to reduced hepcidin stimulation and increased iron absorption.

Extended Data Fig. 6 Relationship between geometric mean hepcidin concentrations, malaria parasitemia and inflammation.

Error bars indicate 95% confidence intervals. n indicates biologically independent samples. Horizontal dotted line indicates the threshold of hepcidin above which iron absorption is inhibited (5.5 µg/L). Inflammation was defined as CRP >5 mg/L, ACT >0.6 g/L or AGP >1 g/L. Malaria was defined as a blood slide positive for asexual P. falciparum parasites. Hepcidin was measured in the Burkina Faso, Western Kenya, Uganda, The Gambia, and Kilifi, Kenya cohorts.

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Muriuki, J.M., Mentzer, A.J., Mitchell, R. et al. Malaria is a cause of iron deficiency in African children. Nat Med 27, 653–658 (2021). https://doi.org/10.1038/s41591-021-01238-4

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