Algorithmic approach to the diagnosis of mitochondrial disorders: integrating clinical, biochemical, and genomic data

Abstract

orders, making early diagnostic stratification essential. This study aimed to evaluate the performance of a stepwise molecular diagnostic algorithm integrating High-Resolution Melting qPCR screening and targeted sequencing in individuals suspected of mitochondrial pathology based on a Nijmegen Mitochondrial Disease Score (NMDS) ≥3. Materials and methods. The analysis included 240 patients with clinical suspicion of mitochondrial disease and an NMDS ≥3, all evaluated through a standardized clinical, biochemical, and instrumental assessment. Molecular testing followed a tiered workflow: initial qPCR-HRM screening for seven common mtDNA mutations, followed by targeted Sanger sequencing of mitochondrial genes, including POLG hotspot regions, in patients meeting predefined clinical and NMDS thresholds. For individuals subsequently identified with non-mitochondrial etiologies, next-generation sequencing approaches were performed in accredited external laboratories. Statistical evaluation relied on descriptive statistical methods and non-parametric comparative analyses. Results. Molecular analysis confirmed mitochondrial involvement in 37 patients (15.4%) and identified non-mitochondrial genetic disorders in 44 patients (18.3%), while 159 individuals (66.3%) remained without a definitive molecular diagnosis. Patients with mitochondrial involvement showed higher frequencies of severe neuromuscular dysfunction, developmental regression, ophthalmic manifestations including ophthalmoplegia, and cardiovascular involvement. By contrast, neurodevelopmental and behavioral impairments and dysmorphic features were more prevalent in non-mitochondrial and undiagnosed patients. Biochemically, elevated plasma lactate and hyperalaninemia were significantly more common among individuals with mitochondrial involvement. Neuroimaging findings in this group were characterized by cerebral and cerebellar atrophy and basal ganglia abnormalities. Consistently, NMDS values were markedly higher in patients with mitochondrial involvement, and their integration as threshold-based decision points within the stepwise diagnostic algorithm substantially enhanced diagnostic stratification, enabling more precise differentiation between mitochondrial involvement and alternative genetic etiologies. Conclusions. The structured algorithm integrating NMDS-based selection, qPCR-HRM screening, and targeted sequencing demonstrated effective stratification of patients with suspected mitochondrial disease, achieving a combined diagnostic rate of 33.7%. These findings support the utility of this tiered approach in distinguishing mitochondrial from non-mitochondrial genetic conditions and in optimizing molecular diagnostic workflows.