Neuromuscular disease genetics in under-represented populations: increasing data diversity
Lindsay A. Wilson, William L. Macken, Luke Perry, Christopher J. Record, Katherine Schon, Rodrigo Siqueira Soares Frezatti, Sharika Raga, K. Satyam Naidu, Özlem Yayıcı Köken, İpek Polat, Musambo M Kapapa, Natalia Dominik, Stéphanie Efthymiou, Heba Morsy, Melissa Nel, Mahmoud R. Fassad, Fei Gao, Krutik Patel, Maryke Schoonen, Michelle Bisschoff, Armand Vorster, Hallgeir Jonvik, Ronel Human, Elsa Lubbe, Malebo Nonyane, Seena Vengalil, Saraswati Nashi, Kosha Srivastava, Richard J.L.F. Lemmers, Alisha Reyaz, Rinkle Mishra, Ana Töpf, Christina Trainor, Elizabeth Steyn, Amokelani C. Mahungu, Patrick J. van der Vliet, Ahmet Cevdet Ceylan, Semra Hız Kurul, Büşranur Çavdarlı, Cavidan Nur Semerci Gündüz, Gülay Güleç Ceylan, Madhu Nagappa, Karthik Bharadwaj Tallapaka, Periyasamy Govindaraj, Silvère M. van der Maarel, Gayathri Narayanappa, Bevinahalli N. Nandeesh, Somwe Wa Somwe, David Bearden, Michelle Kvalsund, Gita Ramdharry, Yavuz Oktay, Uluç Yiş, Haluk Topaloğlu, Anna Sárközy, Enrico Bugiardini, Franclo Henning, Jo M. Wilmshurst, Jeannine M. Heckmann, Robert McFarland, Robert W. Taylor, Izelle Smuts, Francois H. van der Westhuizen, Cláudia Ferreira da Rosa Sobreira, Pedro José Tomaselli, Wilson Marques, Rohit Bhatia, Ashwin Dalal, M.V. Padma Srivastava, Sireesha Yareeda, Atchayaram Nalini, Venugopalan Y. Vishnu, Kumarasamy Thangaraj, Volker Straub, Rita Horváth, Patrick F. Chinnery, Robert D. S. Pitceathly, Francesco Muntoni, Henry Houlden, Jana Vandrovcová, Mary M. Reilly, Michael G. Hanna
Abstract
Neuromuscular diseases (NMDs) affect ∼15 million people globally. In high income settings DNA-based diagnosis has transformed care pathways and led to gene-specific therapies. However, most affected families are in low-to-middle income countries (LMICs) with limited access to DNA-based diagnosis. Most (86%) published genetic data is derived from European ancestry. This marked genetic data inequality hampers understanding of genetic diversity and hinders accurate genetic diagnosis in all income settings. We developed a cloud-based transcontinental partnership to build diverse, deeply-phenotyped and genetically characterized cohorts to improve genetic architecture knowledge, and potentially advance diagnosis and clinical management. We connected 18 centres in Brazil, India, South Africa, Turkey, Zambia, Netherlands and the UK. We co-developed a cloud-based data solution and trained 17 international neurology fellows in clinical genomic data interpretation. Single gene and whole exome data were analysed via a bespoke bioinformatics pipeline and reviewed alongside clinical and phenotypic data in global webinars to inform genetic outcome decisions. We recruited 6001 participants in the first 43 months. Initial genetic analyses 'solved' or 'possibly solved' ∼56% probands overall. In-depth genetic data review of the four commonest clinical categories (limb girdle muscular dystrophy, inherited peripheral neuropathies, congenital myopathy/muscular dystrophies and Duchenne/Becker muscular dystrophy) delivered a ∼59% 'solved' and ∼13% 'possibly solved' outcome. Almost 29% of disease causing variants were novel, increasing diverse pathogenic variant knowledge. Unsolved participants represent a new discovery cohort. The dataset provides a large resource from under-represented populations for genetic and translational research. In conclusion, we established a remote transcontinental partnership to assess genetic architecture of NMDs across diverse populations. It supported DNA-based diagnosis, potentially enabling genetic counselling, care pathways and eligibility for gene-specific trials. Similar virtual partnerships could be adopted by other areas of global genomic neurological practice to reduce genetic data inequality and benefit patients globally.