High-depth African genomes inform human migration and health

The African continent is regarded as the cradle of modern humans and African genomes contain more genetic variation than those from any other continent, yet only a fraction of the genetic diversity among African individuals has been surveyed1. Here we performed whole-genome sequencing analyses of 426 individuals—comprising 50 ethnolinguistic groups, including previously unsampled populations—to explore the breadth of genomic diversity across Africa. We uncovered more than 3 million previously undescribed variants, most of which were found among individuals from newly sampled ethnolinguistic groups, as well as 62 previously unreported loci that are under strong selection, which were predominantly found in genes that are involved in viral immunity, DNA repair and metabolism. We observed complex patterns of ancestral admixture and putative-damaging and novel variation, both within and between populations, alongside evidence that Zambia was a likely intermediate site along the routes of expansion of Bantu-speaking populations. Pathogenic variants in genes that are currently characterized as medically relevant were uncommon—but in other genes, variants denoted as ‘likely pathogenic’ in the ClinVar database were commonly observed. Collectively, these findings refine our current understanding of continental migration, identify gene flow and the response to human disease as strong drivers of genome-level population variation, and underscore the scientific imperative for a broader characterization of the genomic diversity of African individuals to understand human ancestry and improve health

High-depth African genomes inform human migration and health

The African continent is regarded as the cradle of modern humans and African genomes contain more genetic variation than those from any other continent, yet only a fraction of the genetic diversity among African individuals has been surveyed1. Here we performed whole-genome sequencing analyses of 426 individuals—comprising 50 ethnolinguistic groups, including previously unsampled populations—to explore the breadth of genomic diversity across Africa. We uncovered more than 3 million previously undescribed variants, most of which were found among individuals from newly sampled ethnolinguistic groups, as well as 62 previously unreported loci that are under strong selection, which were predominantly found in genes that are involved in viral immunity, DNA repair and metabolism. We observed complex patterns of ancestral admixture and putative-damaging and novel variation, both within and between populations, alongside evidence that Zambia was a likely intermediate site along the routes of expansion of Bantu-speaking populations. Pathogenic variants in genes that are currently characterized as medically relevant were uncommon—but in other genes, variants denoted as ‘likely pathogenic’ in the ClinVar database were commonly observed. Collectively, these findings refine our current understanding of continental migration, identify gene flow and the response to human disease as strong drivers of genome-level population variation, and underscore the scientific imperative for a broader characterization of the genomic diversity of African individuals to understand human ancestry and improve health

Candidate polymorphisms and severe malaria in a Malian population.

Malaria is a major health burden in sub-Saharan African countries, including Mali. The disease is complex, with multiple genetic determinants influencing the observed variation in response to infection, progression, and severity. We assess the influence of sixty-four candidate loci, including the sickle cell polymorphism (HbS), on severe malaria in a case-control study consisting of over 900 individuals from Bamako, Mali. We confirm the known protective effects of the blood group O and the HbS AS genotype on life-threatening malaria. In addition, our analysis revealed a marginal susceptibility effect for the CD40 ligand (CD40L)+220C allele. The lack of statistical evidence for other candidates may demonstrate the need for large-scale genome-wide association studies in malaria to discover new polymorphisms. It also demonstrates the need for establishing the region-specific repertoire of functional variation in important genes, including the glucose-6-phosphatase deficiency gene, before embarking on focused genotyping

Safety of epoietin beta-quinine drug combination in children with cerebral malaria in Mali

cerebral malaria in Mal

Improving the efficiency of scale-up and deployment of community health workers in Mali: A geospatial analysis.

Optimising the scale and deployment of community health workers (CHWs) is important for maximizing geographical accessibility of integrated primary health care (PHC) services. Yet little is known about approaches for doing so. We used geospatial analysis to model optimised scale-up and deployment of CHWs in Mali, to inform strategic and operational planning by the Ministry of Health and Social Development. Accessibility catchments were modelled based on travel time, accounting for barriers to movement. We compared geographic coverage of the estimated population, under-five deaths, and plasmodium falciparum (Pf) malaria cases across different hypothetical optimised CHW networks and identified surpluses and deficits of CHWs compared to the existing CHW network. A network of 15 843 CHW, if optimally deployed, would ensure that 77.3% of the population beyond 5 km of the CSCom (community health centre) and CSRef (referral health facility) network would be within a 30-minute walk of a CHW. The same network would cover an estimated 59.5% of U5 deaths and 58.5% of Pf malaria cases. As an intermediary step, an optimised network of 4 500 CHW, primarily filling deficits of CHW in the regions of Kayes, Koulikoro, Sikasso, and Ségou would ensure geographic coverage for 31.3% of the estimated population. There were no important differences in geographic coverage percentage when prioritizing CHW scale-up and deployment based on the estimated population, U5 deaths, or Pf malaria cases. Our geospatial analysis provides useful information to policymakers and planners in Mali for optimising the scale-up and deployment of CHW and, in turn, for maximizing the value-for-money of resources of investment in CHWs in the context of the country's health sector reform. Countries with similar interests in optimising the scale and deployment of their CHW workforce may look to Mali as an exemplar model from which to learn

Improving the efficiency of scale-up and deployment of community health workers in Mali: A geospatial analysis

Optimising the scale and deployment of community health workers (CHWs) is important for maximizing geographical accessibility of integrated primary health care (PHC) services. Yet little is known about approaches for doing so. We used geospatial analysis to model optimised scale-up and deployment of CHWs in Mali, to inform strategic and operational planning by the Ministry of Health and Social Development. Accessibility catchments were modelled based on travel time, accounting for barriers to movement. We compared geographic coverage of the estimated population, under-five deaths, and plasmodium falciparum ( Pf ) malaria cases across different hypothetical optimised CHW networks and identified surpluses and deficits of CHWs compared to the existing CHW network. A network of 15 843 CHW, if optimally deployed, would ensure that 77.3% of the population beyond 5 km of the CSCom (community health centre) and CSRef (referral health facility) network would be within a 30-minute walk of a CHW. The same network would cover an estimated 59.5% of U5 deaths and 58.5% of Pf malaria cases. As an intermediary step, an optimised network of 4 500 CHW, primarily filling deficits of CHW in the regions of Kayes, Koulikoro, Sikasso, and Ségou would ensure geographic coverage for 31.3% of the estimated population. There were no important differences in geographic coverage percentage when prioritizing CHW scale-up and deployment based on the estimated population, U5 deaths, or Pf malaria cases. Our geospatial analysis provides useful information to policymakers and planners in Mali for optimising the scale-up and deployment of CHW and, in turn, for maximizing the value-for-money of resources of investment in CHWs in the context of the country’s health sector reform. Countries with similar interests in optimising the scale and deployment of their CHW workforce may look to Mali as an exemplar model from which to learn. </p

A novel de novo variant in the RUNX2 gene causes cleidocranial dysplasia in a Malian girl

Key Clinical Message Cleidocranial dysplasia (CCD) is a rare genetic skeletal disorder with only few cases reported in Africa, mostly based on clinical and radiological findings. We report the first case in Mali, caused by a novel de novo variant in the RUNX2 gene. Abstract Cleidocranial dysplasia (CCD) is a rare autosomal dominant skeletal dysplasia characterized by an aplastic/hypoplastic clavicles, patent sutures and fontanels, dental abnormalities and a variety of other skeletal changes. We report a novel de novo variant in the RUNX2 gene causing a severe phenotype of CCD in a Malian girl

Single nucleotide polymorphisms.

<p>MinA = minor allele, MajA = major allele, MAF = overall minor allele frequency, HWE P is the Hardy-Weinberg p-value, OR = odds ratio, 95% Confidence interval (LCL, UCL), P = P-value; rs8176746 and rs8176719 are used to infer ABO blood groups; for X chromosome SNPs (rs3092945 (CD40), rs1126535 (CD40), rs1050829 (G6PD-376), rs1050828 (G6PD-202/A-), analyses are presented for separately for females (F) and males (M) and pooled to obtain overall results (Ov), NA not applicable; rs33950507, rs5743611, rs2814778, rs2227478, rs2535611 and rs1801274 did not pass quality control filters and are not presented.</p

Minimum p-values from tests of association for the autosomal SNPs ^*.

<p>^*Genotypic tests of dominant, recessive, general, heterozygous advantage, and additive models, adjusted for HbS and ethnicity; in this analysis controls include uncomplicated malaria cases; the dashed line represents a p-value of 0.002.</p