Dense sampling of ethnic groups within African countries reveals fine-scale genetic structure and extensive historical admixture

Previous studies have highlighted how African genomes have been shaped by a complex series of historical events. Despite this, genome-wide data have only been obtained from a small proportion of present-day ethnolinguistic groups. By analyzing new autosomal genetic variation data of 1333 individuals from over 150 ethnic groups from Cameroon, Republic of the Congo, Ghana, Nigeria, and Sudan, we demonstrate a previously underappreciated fine-scale level of genetic structure within these countries, for example, correlating with historical polities in western Cameroon. By comparing genetic variation patterns among populations, we infer that many northern Cameroonian and Sudanese groups share genetic links with multiple geographically disparate populations, likely resulting from long-distance migrations. In Ghana and Nigeria, we infer signatures of intermixing dated to over 2000 years ago, corresponding to reports of environmental transformations possibly related to climate change. We also infer recent intermixing signals in multiple African populations, including Congolese, that likely relate to the expansions of Bantu language-speaking peoples

Developing reproducible bioinformatics analysis workflows for heterogeneous computing environments to support African genomics

Background: The Pan-African bioinformatics network, H3ABioNet, comprises 27 research institutions in 17 African countries. H3ABioNet is part of the Human Health and Heredity in Africa program (H3Africa), an African-led research consortium funded by the US National Institutes of Health and the UK Wellcome Trust, aimed at using genomics to study and improve the health of Africans. A key role of H3ABioNet is to support H3Africa projects by building bioinformatics infrastructure such as portable and reproducible bioinformatics workflows for use on heterogeneous African computing environments. Processing and analysis of genomic data is an example of a big data application requiring complex interdependent data analysis workflows. Such bioinformatics workflows take the primary and secondary input data through several computationally-intensive processing steps using different software packages, where some of the outputs form inputs for other steps. Implementing scalable, reproducible, portable and easy-to-use workflows is particularly challenging. Results: H3ABioNet has built four workflows to support (1) the calling of variants from high-throughput sequencing data; (2) the analysis of microbial populations from 16S rDNA sequence data; (3) genotyping and genome-wide association studies; and (4) single nucleotide polymorphism imputation. A week-long hackathon was organized in August 2016 with participants from six African bioinformatics groups, and US and European collaborators. Two of the workflows are built using the Common Workflow Language framework (CWL) and two using Nextflow. All the workflows are containerized for improved portability and reproducibility using Docker, and are publicly available for use by members of the H3Africa consortium and the international research community. Conclusion: The H3ABioNet workflows have been implemented in view of offering ease of use for the end user and high levels of reproducibility and portability, all while following modern state of the art bioinformatics data processing protocols. The H3ABioNet workflows will service the H3Africa consortium projects and are currently in use. All four workflows are also publicly available for research scientists worldwide to use and adapt for their respective needs. The H3ABioNet workflows will help develop bioinformatics capacity and assist genomics research within Africa and serve to increase the scientific output of H3Africa and its Pan-African Bioinformatics Network

Consensus evidence-based clinical practice guidelines for the diagnosis and treat-to-target management of osteoporosis in Africa: an initiative by the African Society of Bone Health and Metabolic Bone Diseases.

The objective of this consensus statement is to inform the clinical practice communities, research centres and policymakers across Africa of the results of the recommendations for osteoporosis prevention, diagnosis and management. The developed guideline provides state-of-the-art information and presents the conclusions and recommendations of the consensus panel regarding these issues. To reach an African expert consensus on a treat-to-target strategy, based on current evidence for best practice, for the management of osteoporosis and prevention of fractures. A 3-round Delphi process was conducted with 17 osteoporosis experts from different African countries. All rounds were conducted online. In round 1, experts reviewed a list of 21 key clinical questions. In rounds 2 and 3, they rated the statements stratified under each domain for its fit (on a scale of 1-9). After each round, statements were retired, modified or added in view of the experts' suggestions and the percent agreement was calculated. Statements receiving rates of 7-9 by more than 75% of experts' votes were considered as achieving consensus. The developed guidelines adopted a fracture risk-centric approach. Results of round 1 revealed that of the 21 proposed domains, 10 were accepted whereas 11 were amended. In round 2, 32 statements were presented: 2 statements were retired for similarity, 9 statements reached consensus, whereas modifications were suggested for 21 statements. After the 3rd round of rating, the experts came to consensus on the 32 statements. Frequency of high-rate recommendation ranged from 83.33 to 100%. The response rate of the experts was 100%. An algorithm for the osteoporosis management osteoporosis was suggested. This study is an important step in setting up a standardised osteoporosis service across the continent. Building a single model that can be applied in standard practice across Africa will enable the clinicians to face the key challenges of managing osteoporosis; furthermore, it highlights the unmet needs for the policymakers responsible for providing bone health care together with and positive outcomes of patients' care. [Abstract copyright: © 2021. International Osteoporosis Foundation and National Osteoporosis Foundation.

Dense sampling of ethnic groups within African countries reveals fine-scale genetic structure and extensive historical admixture

Previous studies have highlighted how African genomes have been shaped by a complex series of historical events. Despite this, genome-wide data have only been obtained from a small proportion of present-day ethnolinguistic groups. By analyzing new autosomal genetic variation data of 1333 individuals from over 150 ethnic groups from Cameroon, Republic of the Congo, Ghana, Nigeria, and Sudan, we demonstrate a previously underappreciated fine-scale level of genetic structure within these countries, for example, correlating with historical polities in western Cameroon. By comparing genetic variation patterns among populations, we infer that many northern Cameroonian and Sudanese groups share genetic links with multiple geographically disparate populations, likely resulting from long-distance migrations. In Ghana and Nigeria, we infer signatures of intermixing dated to over 2000 years ago, corresponding to reports of environmental transformations possibly related to climate change. We also infer recent intermixing signals in multiple African populations, including Congolese, that likely relate to the expansions of Bantu language-speaking peoples

Enabling the genomic revolution in Africa

H3Africa is developing capacity for health-related genomics research in Afric

Research capacity. Enabling the genomic revolution in Africa.

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