Neuromuscular disease genetics in under-represented populations: increasing data diversity.

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.

Clinical, biochemical, and genetic spectrum of MADD in a South African cohort: an ICGNMD study.

BACKGROUND: Multiple acyl-CoA dehydrogenase deficiency (MADD) is an autosomal recessive disorder resulting from pathogenic variants in three distinct genes, with most of the variants occurring in the electron transfer flavoprotein-ubiquinone oxidoreductase gene (ETFDH). Recent evidence of potential founder variants for MADD in the South African (SA) population, initiated this extensive investigation. As part of the International Centre for Genomic Medicine in Neuromuscular Diseases study, we recruited a cohort of patients diagnosed with MADD from academic medical centres across SA over a three-year period. The aim was to extensively profile the clinical, biochemical, and genomic characteristics of MADD in this understudied population. METHODS: Clinical evaluations and whole exome sequencing were conducted on each patient. Metabolic profiling was performed before and after treatment, where possible. The recessive inheritance and phase of the variants were established via segregation analyses using Sanger sequencing. Lastly, the haplotype and allele frequencies were determined for the two main variants in the four largest SA populations. RESULTS: Twelve unrelated families (ten of White SA and two of mixed ethnicity) with clinically heterogeneous presentations in 14 affected individuals were observed, and five pathogenic ETFDH variants were identified. Based on disease severity and treatment response, three distinct groups emerged. The most severe and fatal presentations were associated with the homozygous c.[1067G > A];c.[1067G > A] and compound heterozygous c.[976G > C];c.[1067G > A] genotypes, causing MADD types I and I/II, respectively. These, along with three less severe compound heterozygous genotypes (c.[1067G > A];c.[1448C > T], c.[740G > T];c.[1448C > T], and c.[287dupA*];c.[1448C > T]), resulting in MADD types II/III, presented before the age of five years, depending on the time and maintenance of intervention. By contrast, the homozygous c.[1448C > T];c.[1448C > T] genotype, which causes MADD type III, presented later in life. Except for the type I, I/II and II cases, urinary metabolic markers for MADD improved/normalised following treatment with riboflavin and L-carnitine. Furthermore, genetic analyses of the most frequent variants (c.[1067G > A] and c.[1448C > T]) revealed a shared haplotype in the region of ETFDH, with SA population-specific allele frequencies of < 0.00067-0.00084%. CONCLUSIONS: This study reveals the first extensive genotype-phenotype profile of a MADD patient cohort from the diverse and understudied SA population. The pathogenic variants and associated variable phenotypes were characterised, which will enable early screening, genetic counselling, and patient-specific treatment of MADD in this population.

The mutational profile in a South African cohort with inherited neuropathies and spastic paraplegia.

Introduction: Limited diagnostics are available for inherited neuromuscular diseases (NMD) in South Africa and (excluding muscle disease) are mainly aimed at the most frequent genes underlying genetic neuropathy (GN) and spastic ataxias in Europeans. In this study, we used next-generation sequencing to screen 61 probands with GN, hereditary spastic paraplegia (HSP), and spastic ataxias for a genetic diagnosis. Methods: After identifying four GN probands with PMP22 duplication and one spastic ataxia proband with SCA1, the remaining probands underwent whole exome (n = 26) or genome sequencing (n = 30). The curation of coding/splice region variants using gene panels was guided by allele frequencies from internal African-ancestry control genomes (n = 537) and the Clinical Genome Resource's Sequence Variant Interpretation guidelines. Results: Of 32 GN probands, 50% had African-genetic ancestry, and 44% were solved: PMP22 (n = 4); MFN2 (n = 3); one each of MORC2, ATP1A1, ADPRHL2, GJB1, GAN, MPZ, and ATM. Of 29 HSP probands (six with predominant ataxia), 66% had African-genetic ancestry, and 48% were solved: SPG11 (n = 3); KIF1A (n = 2); and one each of SPAST, ATL1, SPG7, PCYT2, PSEN1, ATXN1, ALDH18A1, CYP7B1, and RFT1. Structural variants in SPAST, SPG11, SPG7, MFN2, MPZ, KIF5A, and GJB1 were excluded by computational prediction and manual visualisation. Discussion: In this preliminary cohort screening panel of disease genes using WES/WGS data, we solved ~50% of cases, which is similar to diagnostic yields reported for global cohorts. However, the mutational profile among South Africans with GN and HSP differs substantially from that in the Global North.