Evaluating the involvement of mtDNA variants in patients diagnosed with myalgic encephalomyelitis

MSc (Biochemistry), North-West University, Potchefstroom Campus, 2016In mitochondrial research, many investigators have examined the association between mitochondrial DNA (mtDNA) variants in rare as well as common complex diseases. Previous studies at the CHM (NWU) detected three known pathogenic mtDNA variants (m.7497G>A, m.9185T>C and m.10197G>A) at low allele frequencies in a number of patients diagnosed with myalgic encephalomyelitis (ME). Since no diagnostic examinations or conclusive treatments currently exist for ME, an association between ME and known pathogenic variants, or a cumulative effect of rare non-synonymous variants (pathogenicity score) on ME, could provide valuable insights into understanding the causes of ME. Literature shows contradicting data regarding the role of mitochondrial dysfunction in ME, and while uncommon mtDNA deletions have been reported, the three known pathogenic mtDNA variants introduced here have not previously been observed in ME patients (but were later identified as sequencing artefacts in the duration of this study), nor has the combined effect of numerous rare non-synonymous variants on the mitochondrial bioenergetics of ME patients been assessed. To do this, cytoplasmic hybrid (cybrid) cells were developed by fusing ρ0 (mtDNA-depleted) cells with healthy control and ME patient‟s blood platelets (containing solely mtDNA). These cybrid cells were used for mitochondrial bioenergetic analyses, using a Seahorse XFe96 analyser, and for determination of the relative mtDNA copy number (RMCN), using real-time PCR. In addition, conditions for analysing selected cell lines (including the cybrids) using the Seahorse XFe96 analyser were optimized. While no apparent bioenergetic irregularities were observed in ME patient cybrids compared to healthy controls, an increased pathogenicity score appeared to be associated with a decrease in ATP production and a decreased electron transport system (ETS) capacity in ME patients. This new approach for investigating mtDNA variants and a common complex disease may provide new insights into the diagnostic and causative factors of ME.Master

The value of open-source clinical science in pandemic response: lessons from ISARIC

International audienc

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use