Ratnaike et al et al., The American Journal of Human Genetics - This episode reviews a Solve-RD reanalysis that integrated an mtDNA-focused bioinformatic pipeline (MToolBox) with MitoPhen HPO-based phenotype similarity scoring to prioritize mitochondrial variants from exome and genome data, leading to new diagnoses in a large rare-disease cohort. Key terms: mitochondrial DNA, MToolBox, MitoPhen, phenotype similarity, Solve-RD.

Study Highlights:
The authors reanalyzed 10,157 exome and genome datasets from 9,923 affected individuals using MToolBox for mtDNA variant calling and MitoPhen phenotype similarity scoring. After automated and manual filtering, 136 rare mtDNA variants in 135 individuals were prioritized and 37 confirmed or likely diagnoses were made, representing a 0.4% diagnostic uplift. A phenotype similarity score threshold >0.3 captured 92% of diagnosed or likely causative cases, but the approach was limited by variable mtDNA coverage and the quality/quantity of HPO data. The pipeline reduced candidate variants to a small, manageable set for expert review and highlighted the value of integrating mtDNA analyses into routine ES/GS reanalysis.

Conclusion:
A semi-automated mtDNA analysis pipeline combined with HPO-based phenotype similarity scoring can identify previously undiagnosed mitochondrial disorders from ES/GS data, producing a modest diagnostic uplift (0.4%) in a heterogeneous rare-disease cohort; careful validation, comprehensive phenotyping, and attention to coverage and ancestry biases remain essential.

Music:
Enjoy the music based on this article at the end of the episode.

Article title:
Mitochondrial DNA disease discovery through evaluation of genotype and phenotype data: The Solve-RD experience

First author:
Ratnaike et al

Journal:
The American Journal of Human Genetics

DOI:
10.1016/j.ajhg.2025.04.003

Reference:
Ratnaike et al., 2025, The American Journal of Human Genetics 112, 1376–1387

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

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Episode link: https://basebybase.com/episodes/mtdna-discovery-solve-rd

QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-06-21.

QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Audited the transcript's coverage of the mtDNA Solve-RD reanalysis workflow, including MToolBox with NUMT filtering, heteroplasmy filtering, haplogroup filtering, MitoPhen phenotype scoring, cohort scale, diagnostic yield, and stated limitations.
- transcript topics: Diagnostic odyssey and mtDNA focus; MToolBox pipeline and NUMT filtering; Heteroplasmy levels and tissue distribution; Haplogroup filtering and ancestry; MitoPhen phenotype similarity scoring and threshold; Solve-RD cohort analysis and diagnostic yield

QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 6
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0

Metadata Audited:
- article_doi
- article_title
- article_journal
- license

Factual Items Audited:
- MToolBox used for mtDNA variant calling with NUMT filtering
- Heteroplasmy threshold for prioritization is ≥1%
- Haplogroup filtering removes common haplogroup markers to reduce noise
- MitoPhen phenotype similarity scoring with threshold >0.3; 92% of diagnosed/likely cases >0.3
- From 11,305 datasets, 136 mtDNA variants in 135 individuals prioritized; 37 new/likely diagnoses
- Diagnostic uplift of 0.4% across Solve-RD cohort

QC result: Pass.