Integrated Molecular and Clinical Profiling of Primary Mitochondrial Oxidative Phosphorylation Disorders in an Indian Cohort: Insights from Genetics, Neuroimaging, and Machine Learning

Mitochondrial disorders are a diverse group of inherited diseases caused by defects in oxidative phosphorylation, the primary way cells produce energy. These disorders often affect multiple organ systems, particularly those with high energy demands, such as the brain, muscles, and heart. Although increasingly recognized worldwide, mitochondrial diseases are still underdiagnosed in resource-limited areas. This prospective observational study aimed to describe the clinical, biochemical, imaging, electrophysiological, and genetic features of 48 patients suspected of having mitochondrial disease at a tertiary care center in Eastern India. Participants were classified into four main clinical syndromes: mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes; Leber hereditary optic neuropathy; Leigh syndrome; and chronic progressive external ophthalmoplegia. The average age was 20.4 years (standard deviation 12.3; range 5–60), with a slight male predominance. Molecular testing confirmed known pathogenic mutations in mitochondrial transfer RNA genes, mitochondrial respiratory complex genes, and ATP synthase subunits, depending on the syndrome. Patients exhibited characteristic abnormalities on brain imaging, including stroke-like lesions in the temporal and parietal lobes or symmetrical involvement of the basal ganglia. Biochemical tests revealed elevated lactate levels in blood and cerebrospinal fluid. Electroencephalography often showed slowing or epileptiform discharges in those with brain involvement. Machine learning techniques helped identify clinical patterns, demonstrating their potential to aid in diagnosis. We offer one of the most comprehensive overviews of mitochondrial diseases in South Asia to date, highlighting the need for accessible molecular diagnostics and the usefulness of computational tools in understanding complex disease phenotypes.