The phenotypic and molecular spectrum of pediatric patients with mitochondrial involvement

Abstract

Abstract Introduction: Mitochondrial disorders exhibit unparalleled clinical and genetic complexity due to dual-genomic control, typically manifesting in pediatric populations with an ultra-rapid, multi-systemic progression that challenges conventional diagnostic boundaries. This study evaluates the phenotypic and molecular spectrum of 39 predominantly pediatric patients with mitochondrial involvement, identified from a broader multi-systemic referral cohort of 240 children. Materials and Methods: Primary enrollment comprised patients achieving a modified Nijmegen Mitochondrial Disease Score (NMDS) ≥ 3. The dual-genomic workflow paired peripheral blood quantitative PCR-high resolution melting screening with targeted mitochondrial DNA sequencing, real-time qPCR for quantitative copy number evaluation, and high-throughput nuclear genomic analysis. Clinical, metabolic, instrumental and neuroimaging parameters were cross-linked using a Spearman correlation matrix. Results: The cohort exhibited a highly intricate neurodevelopmental and systemic phenotype, prominently dominated by pervasive multi-organ involvement (87.2%), seizures (69.2%), brainstem involvement (43.6%), and marked neuromuscular dysfunction (41.0%). Biochemical profiling confirmed systemic metabolic disruption, primarily presenting as hyperlactatemia (89.7%) and hyperalaninemia (38.5%). Instrumental and neuroimaging assessments revealed abnormal neuroradiological (74.4%), electroencephalographic (53.8%), and electrocardiographic (30.8%) profiles. Spearman correlation analysis demonstrated that target group status was strongly anchored by hyperlactatemia (ρ = 0.40) and hyperalaninemia (ρ = 0.38), clustering tightly (ρ ≈ 0.26) with basal ganglia anomalies, neuromuscular dysfunction, and developmental regression. Conclusions: This study demonstrates that an integrated, multi-tiered genomic workflow successfully identifies relevant genetic variants across both the mitochondrial and nuclear genomes in 16.3% of cases within a complex screening pool. Pairing a modified clinical scoring system and core metabolic biomarkers with key neuroimaging findings establishes a dependable framework for identifying high-probability cases.