Including Africa in the research on rare genetic diseases: A must!
Last Updated on December 9, 2022 by Joseph Gut – thasso
November 27, 2022 – About 3.5–5.9% of the world population are affected by a rare diseases. For Africa alone, this winds up to around 50 million possibly affected people, representing a large community of individuals and families in need of diagnostics and care. About 72% of rare diseases are thought to have a genetic etiology. Unfortunately, this rich and diverse information on the genetics of rare diseases stemming from African populations is still significantly underrepresented in reference and in disease-associated databases.
On February 28th 2022 the world celebrated the 14th Rare Diseases Day, and then the sixth Undiagnosed Diseases Day was celebrated on April 29th. These and previous such days have been opportunities for the members of the Rare Disease Working Group of the Human Heredity and Health in Africa Consortium (H3Africa) to reflect on major barriers that cause a high proportion of patients with rare diseases in Africa to remain undiagnosed.
This situation has to change by all means, and identified barriers have to come down. In fact, H3Africa has initiated projects that work within the rare genetic disorder niche and their research initiatives are aimed at identifying and filling the knowledge gaps in rare disease in Africa by characterizing the clinical and molecular epidemiology of specific groups of rare diseases, including developmental delay, deafness, neurodegenerative and neuromuscular diseases.
The impact of collecting African genomic data though such initiatives may allow to 1) consenting for sharing aggregate frequency data an essential component of research toolkits, 2) encouraging investigators with African data to share available data through public resources such as gnomAD, ClinVar, DECIPHER and to use MatchMaker Exchange, 3) to educate African research participants on the meaning and value of sharing aggregate frequency data, and 4) to increase funding to scale-up the production of African genomic data that will be more representative of the geographical and ethno-linguistic variation on the continent. The Rare Disease Working Group (RDWG) of H3Africa is hereby calling to action because this underrepresentation accentuates the health disparities.
In daily research life, applying the Next Generation Sequencing (NGS) may shorten the diagnostic odyssey by its ability to explore multiple types of genomic aberrations at once, even without a clear clinical hypothesis and guide therapeutic options for rare diseases; it will, however, fully work for Africans only when public repositories include sufficient data from African subjects. Rapid NGS testing is implemented for critically ill patients in Europe, America, Australia and the United Kingdom with a turn-around-time that allows NGS-guided therapeutic adjustments in therapies to be made.
In Africa, there is a sharp contrast between the implementation of NGS in pathogen genetics versus in human genetics. On one hand, multiple financial international supports are available for technology transfer to Africa for pathogen genetics. The Ebola epidemic in West Africa and the Covid-19 response have created a consensus on the utility of NGS on the continent and offered a momentum for broad expansion of short and long reads sequencing technologies as routine testing of pathogens in Africa. On the other hand, with regards to rare diseases, genetic service delivery in general, and NGS-based testing in particular, remains limited and extremely fragile in Africa. NGS-based diagnostics tests are not offered routinely to rare diseases patients in Africa yet. The main barriers include limited existing infrastructure and processes, insufficient funding and lack of political support, and poorly structured health systems. However, research projects such as the Deciphering Developmental Disorders in Africa (DDD-Africa, out of South Africa and the Democratic Republic of Congo), Hearing Impairment Genetics Studies in Africa (HI-GENES Africa, out of South Africa, Cameroun, Ghana, Mali), Clinical and Genetic Studies of Hereditary Neurological Disorders (CGSHND) in Mali or the genetic study of neuromuscular diseases (South Africa) are ensuring rare diseases patients in Africa can receive NGS tests in order to identify African patients and/or families with their underlying genetic defects for the disease addressed above. In addition, there is an important contribution of NGS tests free-of-charge to African rare diseases patients from international research collaborations and philanthropic initiatives such as the Centers for Mendelian Genomics (CMG) and the iHope Foundation. All these efforts have allowed adjusting care in many African patients when possible as well as identifying new disease genes.
Generating genomic data is only the first step on the path toward resolving and managing undiagnosed genetic diseases. Clinical interpretation of genomic data for rare diseases is complex and challenging. This process consists of filtering variants based on knowledge gathered from different sources (disease databases and literature, population databases labelled as reference databases, existing functional data), phenotypic overlap, segregation data (inheritance) and computational predictions (in silico tools). Variants are then prioritized based on different criteria which favor a pathogenic or benign interpretation, and finally classified into five categories according to the guidelines from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG-AMP). Thus, as an example, high technologies such as that applied in the Face2Gene approach may help to correlate phenotypes (faces in this case) to underlying (rare) diseases and genetic variants (thasso had three articles in the past on the phenomenon here, here, and here). Considering that functional data are not available for the vast majority of variants, and that the phenotypic spectrum of many rare undiagnosed diseases is not known or is poorly characterized in understudied communities, the population frequency remains among the strongest filters for NGS data interpretation. Therefore, the lack of representation in population frequency databases makes clinical interpretation of genomic data significantly more challenging in Africa and in African diaspora. In 2021, the H3Africa was contacted by a team in Canada, seeking information regarding 3 genomic variants identified in patients of African origin with rare diseases in Canada. The query in the H3Africa reference panel and in the internal database of the Center for Human Genetics of the University of Kinshasa indicated that two of these variant were absent and the last had very low frequency with no homozygous. Further evidence established the novelty or the rarity of these variants in an African dataset. This illustrate the complexity of data interpretation even in developed countries and supports the value of data sharing.
Increasing diversity in databases with diverse African data will be a powerful tool to improve the diagnostic yield and the diagnostic accuracy for African and non-African rare undiagnosed diseases patients. Fortunately, the production of genomic data from African individuals has significantly increased over the last decade. This production has been significantly facilitated by the H3Africa Consortium, funded by the National Institute of Health (NIH) and Wellcome Trust Foundation. Although most of the funded projects focused on complex and infectious diseases, research participants in those projects would qualify to populate an aggregate reference frequency database for rare diseases. An aggregate reference frequency populated with African data will be a game changer in resolving undiagnosed diseases not only in Africa but for 3.5–5.9% of the world population. A good illustration of the power of African data is the recent submission by the H3Africa of 41 variants to the ClinVar system. Some of these variant had conflicting interpretation in ClinVar but were all observed in more than 5% of the H3Africa participants. Adding this information from H3Africa data allowed these variants to be reclassified as benign.
Another initiative poised to have a significant impact is the Africa Pathogen Genomics Initiative (PGI) developed by the Africa CDC Institute for Pathogen Genomics, which aims to build and host an African-owned data library and real-time data sharing platform, as well as to expand and strengthen laboratory and bioinformatics capacity.
Overall, all these efforts are well suited to bring African patients, their rare diseases, and the (equivally rare) genetic variants behind them to the global landscape.
See a sequence of involved voices on this important theme:
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