🎙️ Episode 25: Uncovering Mitochondrial DNA Diseases — The Solve-RD Experience with Genotype and Phenotype Integration

🧬 In this episode of Base por Base, we delve into a groundbreaking study by Ratnaike et al. (2025) published in The American Journal of Human Genetics, which presents a semi-automated workflow combining mtDNA variant filtering and MitoPhen-based HPO phenotype similarity scoring applied to exome and genome data from the Solve-RD cohort of undiagnosed rare disease cases .

🔍 Study highlights:
Our workflow applied MToolBox for mtDNA reconstruction and MITOMAP annotations with stringent quality filters (≥50% mtDNA assembly and ≥5× coverage) to prioritize 136 rare variants across 9,923 individuals from 9,483 families without prior suspicion of mitochondrial disease .
Phenotype similarity scoring using the curated MitoPhen database achieved 100% sensitivity at a 0.3 threshold and distinguished confirmed mtDNA disease cases from nuclear genetic diagnoses with an AUC of 0.82 .
A total of 21 confirmed and 16 likely causative mtDNA diagnoses were made, boosting the overall diagnostic yield by 0.4% and uncovering 37 new diagnoses .
The pipeline efficiently handled off-target exome sequencing data, retaining 90% of datasets for analysis and enabling detection of pathogenic variants at heteroplasmy levels as low as 1% .
Structured, phenotype-driven curation underscored the importance of comprehensive HPO annotation and highlighted the value of iterative genotype-phenotype evaluation in improving rare disease diagnostics .

🧠 Conclusion:
This study demonstrates a scalable approach to integrate mtDNA analysis into routine exome and genome reanalysis by leveraging automated bioinformatic filtering and phenotype similarity scoring, offering a powerful tool to improve diagnostic rates for mitochondrial disorders in heterogeneous cohorts .

📖 Reference:
Ratnaike, T., Paramonov, I., Olimpio, C., et al. (2025). Mitochondrial DNA disease discovery through evaluation of genotype and phenotype data: The Solve-RD experience. The American Journal of Human Genetics, 112(1), 1–12. https://doi.org/10.1016/j.ajhg.2025.04.003

📜 License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International (CC BY 4.0) license – http://creativecommons.org/licenses/by/4.0/