Malaria continues to select for sickle cell trait in Central Africa
Authors: Patrick Durand
Virginie Rougeron
Lucrèce M Délicat-Loembet
Eric M Leroy
Pierre Becquart
Eric Elguero
Benjamin Roche
Dieudonné Nkoghe
Lucas Sica
François Renaud
Céline Arnathau
Francisco J Ayala
Franck Prugnolle
Jean-Paul Gonzalez
Benjamin Ollomo
Journal: Proceedings of the National Academy of Sciences of the United States of America (2015)
Discipline: Multidisciplinary
Keywords: Gabon; Plasmodium falciparum; human evolution; natural selection; sickle cell disease.
Affiliations: Maladies Infectieuses et Vecteurs, Ecologie, Génétique, Evolution et Contrôle (Unité Mixte de Recherche 5290, Centre National de la Recherche Scientifique, Institut de Recherche pour le Développement, Université de Montpellier), 34295 Montpellier, France; fjayala@uci.edu   ., Maladies Infectieuses et Vecteurs, Ecologie, Génétique, Evolution et Contrôle (Unité Mixte de Recherche 5290, Centre National de la Recherche Scientifique, Institut de Recherche pour le Développement, Université de Montpellier), 34295 Montpellier, France; Evolutionary Parasitology Departement, Centre International de Recherches Médicales de Franceville, BP 769 Franceville, Gabon;, Maladies Infectieuses et Vecteurs, Ecologie, Génétique, Evolution et Contrôle (Unité Mixte de Recherche 5290, Centre National de la Recherche Scientifique, Institut de Recherche pour le Développement, Université de Montpellier), 34295 Montpellier, France;, Unité de Modélisation Mathématique et Informatique des Systèmes Complexes, Unité Mixte Internationale 209, Institut de Recherche pour le Développement, Université Pierre et Marie Curie, 93142 Bondy Cedex, France;, METABIOTA Inc., Emerging Diseases & Biosecurity, Silver Spring, MD 20910;, Evolutionary Parasitology Departement, Centre International de Recherches Médicales de Franceville, BP 769 Franceville, Gabon;, Department of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697 fjayala@uci.edu   ., Maladies Infectieuses et Vecteurs, Ecologie, Génétique, Evolution et Contrôle (Unité Mixte de Recherche 5290, Centre National de la Recherche Scientifique, Institut de Recherche pour le Développement, Université de Montpellier), 34295 Montpellier, France; Evolutionary Parasitology Departement, Centre International de Recherches Médicales de Franceville, BP 769 Franceville, Gabon; fjayala@uci.edu   .

Abstract:  Sickle cell disease (SCD) is a genetic disorder that poses a serious health threat in tropical Africa, which the World Health Organization has declared a public health priority. Its persistence in human populations has been attributed to the resistance it provides to Plasmodium falciparum malaria in its heterozygous state, called sickle cell trait (SCT). Because of migration, SCT is becoming common outside tropical countries: It is now the most important genetic disorder in France, affecting one birth for every 2,400, and one of the most common in the United States. We assess the strength of the association between SCT and malaria, using current data for both SCT and malaria infections. A total of 3,959 blood samples from 195 villages distributed over the entire Republic of Gabon were analyzed. Hemoglobin variants were identified by using HPLCy (HPLC). Infections by three species of Plasmodium were detected by PCR followed by sequencing of a 201-bp fragment of cytochrome b. An increase of 10% in P. falciparum malaria prevalence is associated with an increase by 4.3% of SCT carriers. An increase of 10 y of age is associated with an increase by 5.5% of SCT carriers. Sex is not associated with SCT. These strong associations show that malaria remains a selective factor in current human populations, despite the progress of medicine and the actions undertaken to fight this disease. Our results provide evidence that evolution is still present in humans, although this is sometimes questioned by scientific, political, or religious personalities. 

Retracted: No

PubPeer comments:
 Hi, I am trying to understand your publication and had a few questions. Your answers would be greatly appreciated. * I can t reproduce some of the data in the study. Given the seriousness of the authors, the journal and the reviewers the issue is most likely in either my interpretation and manipulation of the data, or in the dataset referenced online, or some other cause. * Crucially, I think that all the conclusions of the paper most likely still hold. * I don t think the paper is fraudulent, and think the authors are in good faith. * I am aware that even trying to reproduce their result was only possible because the authors gave direct access to their dataset to begin with. For this I am grateful. * Here s how I created my columns : ![file] * and here s the name of the dataset I found on PNAS website :  pnas.1505665112.sd01-1.ods * I used python3, pandas and plotly, but reproduced my findings in R also. # First issue : ![file] * this point does not appear to exist in the falciparum dataset but only in the plasmodium dataset. * Backing : ![file] ![file] ![file] * *(the lines indicate regression lines for either plasmodium or falciparum data)* * I can t reproduce the boxplot anyway, either the whiskers, the median location, or the outliers are not corresponding. ![file] ![file] * Here s the corresponding R code : ![file] * and the R output : ![file] # Second issue : * in the figure 1.C. The orange line seem to be a linear model applied to only the 5 boxplots instead of the whole datapoints. Am I correct? Boxing the datapoints in 20% chunks should have a non negligeable impact on the data. I checked : ![file] ![file] * Does that change any of the values you computed in the glm model? # Third issue : * Here s your table 2 : ![file] * I very badly wanted to double check your data but you didn t give access to it. I only got the mean, min and maximum age and not the actual age of the participants. Would you be so kind as to provide them? I would be very happy to check. Respectful regards ,