Applying genomic and transcriptomic advances to mitochondrial medicine

Next-generation sequencing (NGS) has increased our understanding of the molecular basis of many primary mitochondrial diseases (PMDs). Despite this progress, many patients with suspected PMD remain without a genetic diagnosis, which restricts their access to in-depth genetic counselling, reproductive options and clinical trials, in addition to hampering efforts to understand the underlying disease mechanisms. Although they represent a considerable improvement over their predecessors, current methods for sequencing the mitochondrial and nuclear genomes have important limitations, and molecular diagnostic techniques are often manual and time consuming. However, recent advances in genomics and transcriptomics offer realistic solutions to these challenges. In this Review, we discuss the current genetic testing approach for PMDs and the opportunities that exist for increased use of whole-genome NGS of nuclear and mitochondrial DNA (mtDNA) in the clinical environment. We consider the possible role for long-read approaches in sequencing of mtDNA and in the identification of novel nuclear genomic causes of PMDs. We examine the expanding applications of RNA sequencing, including the detection of cryptic variants that affect splicing and gene expression and the interpretation of rare and novel mitochondrial transfer RNA variants

Mitochondrial DNA variants in genomic data: diagnostic uplifts and predictive implications

A broad spectrum of rare disease presentations can now be investigated by analysing mitochondrial DNA (mtDNA) variants from whole-genome sequencing (WGS) data. However, mtDNA mutations may cause unanticipated, extended phenotypes and have reproductive implications. We recommend that these be considered by patients and clinicians before embarking on WGS

Mitochondrial Strokes: Diagnostic Challenges and Chameleons

Mitochondrial stroke-like episodes (SLEs) are a hallmark of mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS). They should be suspected in anyone with an acute/subacute onset of focal neurological symptoms at any age and are usually driven by seizures. Suggestive features of an underlying mitochondrial pathology include evolving MRI lesions, often originating within the posterior brain regions, the presence of multisystemic involvement, including diabetes, deafness, or cardiomyopathy, and a positive family history. The diagnosis of MELAS has important implications for those affected and their relatives, given it enables early initiation of appropriate treatment and genetic counselling. However, the diagnosis is frequently challenging, particularly during the acute phase of an event. We describe four cases of mitochondrial strokes to highlight the considerable overlap that exists with other neurological disorders, including viral and autoimmune encephalitis, ischemic stroke, and central nervous system (CNS) vasculitis, and discuss the clinical, laboratory, and imaging features that can help distinguish MELAS from these differential diagnoses

Enhanced mitochondrial genome analysis: bioinformatic and long-read sequencing advances and their diagnostic implications

Introduction: Primary mitochondrial diseases (PMDs) comprise a large and heterogeneous group of genetic diseases that result from pathogenic variants in either nuclear DNA (nDNA) or mitochondrial DNA (mtDNA). Widespread adoption of next-generation sequencing (NGS) has improved the efficiency and accuracy of mtDNA diagnoses; however, several challenges remain. Areas covered: In this review, we briefly summarize the current state of the art in molecular diagnostics for mtDNA and consider the implications of improved whole genome sequencing (WGS), bioinformatic techniques, and the adoption of long-read sequencing, for PMD diagnostics. Expert opinion: We anticipate that the application of PCR-free WGS from blood DNA will increase in diagnostic laboratories, while for adults with myopathic presentations, WGS from muscle DNA may become more widespread. Improved bioinformatic strategies will enhance WGS data interrogation, with more accurate delineation of mtDNA and NUMTs (nuclear mitochondrial DNA segments) in WGS data, superior coverage uniformity, indirect measurement of mtDNA copy number, and more accurate interpretation of heteroplasmic large-scale rearrangements (LSRs). Separately, the adoption of diagnostic long-read sequencing could offer greater resolution of complex LSRs and the opportunity to phase heteroplasmic variants

Mitochondrial DNA analysis from exome sequencing data improves the diagnostic yield in neurological diseases

A rapidly expanding catalogue of neurogenetic disorders has encouraged a diagnostic shift towards early clinical whole exome sequencing (WES). Adult primary mitochondrial diseases (PMDs) frequently exhibit neurological manifestations that overlap with other nervous system disorders. However, mitochondrial DNA (mtDNA) is not routinely analyzed in standard clinical WES bioinformatic pipelines. We reanalyzed 11,424 exomes, enriched with neurological diseases, for pathogenic mtDNA variants. Twenty‐four different mtDNA mutations were detected in 64 exomes, 11 of which were considered disease causing based on the associated clinical phenotypes. These findings highlight the diagnostic uplifts gained by analyzing mtDNA from WES data in neurological diseases

Mitochondrial DNA Analysis from Exome Sequencing Data Improves Diagnostic Yield in Neurological Diseases

A rapidly expanding catalog of neurogenetic disorders has encouraged a diagnostic shift towards early clinical whole exome sequencing (WES). Adult primary mitochondrial diseases (PMDs) frequently exhibit neurological manifestations that overlap with other nervous system disorders. However, mitochondrial DNA (mtDNA) is not routinely analyzed in standard clinical WES bioinformatic pipelines. We reanalyzed 11,424 exomes, enriched with neurological diseases, for pathogenic mtDNA variants. Twenty‐four different mtDNA mutations were detected in 64 exomes, 11 of which were considered disease causing based on the associated clinical phenotypes. These findings highlight the diagnostic uplifts gained by analyzing mtDNA from WES data in neurological diseases

Exome reanalysis and proteomic profiling identified TRIP4 as a novel cause of cerebellar hypoplasia and spinal muscular atrophy (PCH1)

TRIP4 is one of the subunits of the transcriptional coregulator ASC-1, a ribonucleoprotein complex that participates in transcriptional coactivation and RNA processing events. Recessive variants in the TRIP4 gene have been associated with spinal muscular atrophy with bone fractures as well as a severe form of congenital muscular dystrophy. Here we present the diagnostic journey of a patient with cerebellar hypoplasia and spinal muscular atrophy (PCH1) and congenital bone fractures. Initial exome sequencing analysis revealed no candidate variants. Reanalysis of the exome data by inclusion in the Solve-RD project resulted in the identification of a homozygous stop-gain variant in the TRIP4 gene, previously reported as disease-causing. This highlights the importance of analysis reiteration and improved and updated bioinformatic pipelines. Proteomic profile of the patient’s fibroblasts showed altered RNA-processing and impaired exosome activity supporting the pathogenicity of the detected variant. In addition, we identified a novel genetic form of PCH1, further strengthening the link of this characteristic phenotype with altered RNA metabolism

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

\ua9 The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain. 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 \u27solved\u27 or \u27possibly solved\u27 ∼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% \u27solved\u27 and ∼13% \u27possibly solved\u27 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

Systematic review of the relationship between family history and lung cancer risk

We performed a systematic review of 28 case–control, 17 cohort and seven twin studies of the relationship between family history and risk of lung cancer and a meta-analysis of risk estimates. Data from both case–control and cohort studies show a significantly increased lung cancer risk associated with having an affected relative. Risk appears to be greater in relatives of cases diagnosed at a young age and in those with multiple affected family members. Increased lung cancer risk was observed in association with an affected spouse and twin studies, while limited, favour shared environmental exposures. The limitations of the currently published epidemiological studies to infer genetic susceptibility are discussed

Knowledge growth, complexity and the returns to R&D

Growth theory, Technological change, N–K model, Complexity, Modularity, O3, D83,