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Genomics data are currently being produced at unprecedented rates, resulting in increased knowledge discovery and submission to public data repositories. Despite these advances, genomic information on African-ancestry populations remains significantly low compared with European- and Asian-ancestry populations. This information is typically segmented across several different biomedical data repositories, which often lack sufficient fine-grained structure and annotation to account for the diversity of African populations, leading to many challenges related to the retrieval, representation and findability of such information. To overcome these challenges, we developed the African Genomic Medicine Portal (AGMP), a database that contains metadata on genomic medicine studies conducted on African-ancestry populations. The metadata is curated from two public databases related to genomic medicine, PharmGKB and DisGeNET. The metadata retrieved from these source databases were limited to genomic variants that were associated with disease aetiology or treatment in the context of African-ancestry populations. Over 2000 variants relevant to populations of African ancestry were retrieved. Subsequently, domain experts curated and annotated additional information associated with the studies that reported the variants, including geographical origin, ethnolinguistic group, level of association significance and other relevant study information, such as study design and sample size, where available. The AGMP functions as a dedicated resource through which to access African-specific information on genomics as applied to health research, through querying variants, genes, diseases and drugs. The portal and its corresponding technical documentation, implementation code and content are publicly available. [ABSTRACT FROM AUTHOR]

Genetic diseases in Tunisia are a real public health problem given their chronicity and the lack of knowledge concerning their prevalence and etiology, and the high rates of consanguinity. Hence, we performed systematic reviews of the literature in order to provide a more recent spectrum of these disorders and to expose the challenges that still exist to tackle these kinds of diseases. A manual textual data mining was conducted using MeSH and PubMed databases. Collected data were classified according to the CIM-10 classification and the transmission mode. The spectrum of these diseases is estimated to be 589 entities. This suggests remarkable progress through the development of biomedical health research activities and building capacities. Sixty percent of the reported disorders are autosomal recessive, which could be explained by the high prevalence of endogamous mating. Congenital malformations (29.54%) are the major disease group, followed by metabolic diseases (22%). Sixty percent of the genetic diseases have a known molecular etiology. We also reported additional cases of comorbidity that seem to be a common phenomenon in our population. We also noticed that epidemiological data are scarce. Newborn and carrier screening was only limited to pilot projects for a few genetic diseases. Collected data are being integrated into a database under construction that will be a valuable decision-making tool. This study provides the current situation of genetic diseases in Tunisia and highlights their particularities. Early detection of the disease is important to initiate critical intervention and to reduce morbidity and mortality. [ABSTRACT FROM AUTHOR]