mtDNA Methodology
Complete documentation of how Helena classifies mitochondrial DNA variants under the ClinGen Mitochondrial Disease Working Group (MMDWG) 2020 specification (McCormick EM et al., Hum Mutat. 2020;41(12):2028-2057. PMID: 33058415. DOI: 10.1002/humu.24107). Every threshold, evidence source, and curation tier used in production is documented on this page. This documentation is intended for clinical geneticists, laboratory directors, and accreditation auditors.
mtDNA variants are classified under MMDWG 2020 (McCormick), nuclear variants under ACMG/AMP 2015 (Richards). The two frameworks operate as independent modules; every variant in the output carries an explicit framework provenance label so the reviewing geneticist always knows which framework produced the classification. Strength tiers follow ClinGen mtDNA VCEP v1.0.0 conventions. Combining rules retain the Richards 2015 eighteen-rule set unchanged per McCormick Section 5.2.
Pipeline Overview
Seven-stage mtDNA classification pipeline. mtDNA variants are routed to the MMDWG framework, annotated against the curated mitochondrial reference set, evaluated against the eleven automated criteria, integrated with reviewer-submitted curation evidence, and resolved through Richards 2015 combining rules with mtDNA-specific overrides.
mtDNA Variant Identification
Variants residing on the mitochondrial chromosome are identified during pipeline ingestion. Six standard mtDNA chromosome aliases are accepted (chrM, M, MT, chrMT, NC_012920.1, J01415.2) and harmonized to a single canonical reference. Nuclear pseudogene candidates (NUMT regions known from published catalogs) are flagged for visibility without blocking classification.
Two-Framework Architecture
Helena applies two independent classification frameworks in the same analysis: ACMG/AMP 2015 (Richards) for nuclear variants, and ClinGen MMDWG 2020 (McCormick) for mtDNA variants. Each variant carries explicit framework provenance in its output, so reviewing geneticists know which interpretive framework produced the classification.
mtDNA Reference Annotation
mtDNA variants are annotated against the curated mitochondrial reference set: ClinVar mtDNA assertions, gnomAD v3.1 mtDNA population frequencies with heteroplasmy distribution, APOGEE 2 missense scores, MitoTIP and PON-mt-tRNA tRNA scores, mt-Phylotree haplogroup-defining annotations, and Ensembl mtDNA gene coordinates with biotype.
MMDWG Criteria Evaluation
Eleven automated criteria are evaluated per variant per McCormick 2020: PVS1, PS1, PM2_Supporting, PM4, PM5_Moderate, PM5_Supporting, PP3, BA1, BS1, BP2_Supporting, BP4, BP7. Strength tiers follow ClinGen mtDNA VCEP v1.0.0 conventions. Tier suffixes appear on criteria emitted at non-default ACMG strength.
Curated Evidence Integration
Ten manual-curation criteria (PS2, PS3, PS4, PM6, PP1, PP4, BS2, BS3, BS4, BP5) accept geneticist input through an audit-trailed curation interface with explicit strength tiers (Very Strong, Strong, Moderate, Supporting). Submitted curation contributes to the same combining-rule evaluation as the automated criteria.
Combining Rules and Override
Richards 2015 combining rules (eighteen rules, retained unchanged per McCormick Section 5.2) determine the final five-tier classification (P, LP, VUS, LB, B). BA1 acts as stand-alone benign override. ClinVar P/LP/B/LB assertions at two or more review stars provide an override path (mtDNA-specific stricter threshold per McCormick Section 5.1). Conflicting pathogenic and benign evidence at moderate or above produces VUS.
Persistence and Audit Trail
Classification, criteria string with strength tiers, framework provenance (mmdwg_2020), MMDWG module version, and classification confidence are persisted alongside the variant. Categorized transparency notes record every non-default decision (PP1 disqualification, BA1 conservative fallback, manual curation contribution) for reviewer audit.
Helena Differentiators
The ClinGen MMDWG 2020 specification is the standard. The choices below describe how Helena addresses interpretive challenges that the specification raises but does not prescribe a single implementation for. Each differentiator is described at the conceptual level; the specific implementation is part of the Helena platform.
Personalized BA1 via Patient Haplogroup Ancestry
McCormick 2020 Section 5.2.10 requires BA1 to fire either when the variant exceeds 1% allele frequency or when the variant is haplogroup-defining for the patient haplogroup. A simple "haplogroup-defining anywhere" flag is insufficient because the clinical interpretation depends on whether the patient actually carries that haplogroup. Helena infers the patient haplogroup from the VCF and evaluates each candidate variant against the patient ancestral haplogroup branch (not against the global population). When haplogroup inference is uncertain, Helena falls back to a conservative evaluation that applies BA1 only to the high-frequency path, preserving sensitivity for rare variants. Illustrative example: m.3394T>C is haplogroup-defining for branch M9a but pathogenic in branch B4c (Ji 2012 PMID:22577229; Kang 2016 PMID:27220472). The same variant correctly receives BA1 in an M9a patient and remains pathogenic-eligible in a B4c patient.
NUMT-Aware Classification with Visibility Flags
Nuclear mitochondrial DNA segments (NUMTs) are stretches of mtDNA-like sequence integrated into the nuclear genome (Calabrese 2017 PMID:24723423). Variants overlapping known NUMT regions can produce false-positive mtDNA calls when sequencing depth or coverage characteristics suggest nuclear origin. Helena maintains a curated catalog of published NUMT regions and surfaces NUMT-overlap and depth-anomaly flags for the reviewing geneticist. The flags are advisory rather than blocking: classification still proceeds under MMDWG, and the geneticist makes the final pseudogene determination informed by the visibility signal.
Two-Framework Architecture with Explicit Provenance
Mitochondrial and nuclear genetics differ in inheritance, mutation rate, heteroplasmy, and allele frequency interpretation. McCormick 2020 explicitly modifies, downgrades, or excludes ACMG criteria for mtDNA. Helena keeps the two frameworks fully separated: nuclear variants are classified under ACMG/AMP 2015, mtDNA variants under ClinGen MMDWG 2020, and every variant in the output carries an explicit classification_framework label so the reviewing geneticist always knows which interpretive framework produced the result. There is no silent reuse of nuclear thresholds for mtDNA variants and no mixing of criteria sets.
Manual Curation Workflow with Strength Tiers
Ten of the twenty-five ACMG criteria require evidence not derivable from the VCF and reference data alone: parental segregation (PS2, PM6, PP1, BS4), functional studies (PS3, BS3), case-control statistics (PS4), phenotype specificity (PP4), independent healthy-individual observation (BS2), and alternative-diagnosis context (BP5). Helena exposes these criteria through an audit-trailed curation interface with explicit ClinGen mtDNA VCEP v1.0.0 strength tiers: four-tier (Very Strong / Strong / Moderate / Supporting) for PS2 and PM6 per McCormick Section 5.2.3 and 5.2.6; two-tier (Strong / Supporting) for BS2 per McCormick Section 5.2.10; specification-defined tiers for PS3, PS4, PM6, PP1, PP4, BS3, BS4, and BP5. PS4 and PP1 strength can also be derived inline from proband counts and haplogroup-diversity statistics where these are available.
Categorized Transparency Audit Trail
Every non-default classification decision generates an audit note attached to the variant record: PVS1 NMD branch removal per Abou Tayoun (mRNA path only), BA1 conservative fallback when haplogroup inference is uncertain, PM5_Supporting tRNA / rRNA fired per McCormick Section 5.2.2, manual curation contribution from a named reviewer, ClinVar override gating, and others. The audit notes are categorized so geneticists can quickly scan the rationale for any classification and so accreditation auditors can reconstruct the decision path for any variant.
Reference Databases
All mtDNA reference data is stored locally on EU-based infrastructure. No variant data is sent to external services during processing. Database versions are fixed per deployment and documented here.
mt_clinvar_variants
ClinVar clinical significance assertions filtered to chrM. Distribution: 78 Pathogenic, 109 Likely Pathogenic, 1,269 VUS, 612 Likely Benign, 1,017 Benign, 34 Not_provided, 3 Other. Review stars: 119 zero-star, 2,452 one-star, 238 two-star, 313 three-star. Helena retains both the canonical clinical significance code (P, LP, VUS, LB, B) and the original ClinVar string for audit transparency.
Used by: PS1 (same amino acid change as known pathogenic, mRNA path only), PM5_Moderate (different missense at same residue, mRNA), PM5_Supporting (same nucleotide position, tRNA / rRNA, McCormick Section 5.2.2), BP2_Supporting (another mtDNA variant in the same session is ClinVar P/LP), and the ClinVar override gate at two or more review stars (stricter than the nuclear one-star override per McCormick Section 5.1).
Source: NCBI ClinVar
mt_population_frequencies
Per-variant homoplasmic and heteroplasmic allele frequencies, per-individual maximum heteroplasmy, haplogroup-defining flag, common-low-heteroplasmy flag, MitoTIP raw score, MitoTIP tRNA prediction class, PON-mt-tRNA prediction class, and PON-mt-tRNA pathogenicity probability. Distribution: 124 variants > 5% allele frequency, 429 variants > 1%, 4,299 haplogroup-defining variants, 374 common-low-heteroplasmy variants.
Used by: BA1 (allele frequency > 1% stand-alone benign, or haplogroup-defining for the patient ancestral branch, McCormick Section 5.2.10), BS1 (allele frequency 0.5-0.99% Strong benign, McCormick Section 5.2.5), PM2_Supporting (allele frequency < 0.00002 absent-from-controls, downgraded from Moderate per McCormick Section 5.2.5), PP3 tRNA path (MitoTIP > 50th percentile combined with PON-mt-tRNA > 0.5), BP4 tRNA path (mirror inverse).
Source: gnomAD
mt_apogee2_scores
APOGEE 2 numeric pathogenicity scores for every possible mtDNA missense substitution across the 13 protein-coding genes. Score range 0.0 to 0.981 with associated probability and class label. Auxiliary predictor scores (AlphaMissense, MitoClass1, PolyPhen2, SIFT, FATHMM, CADD) and MitoMap disease status are retained alongside for clinical reference. APOGEE 1 score is retained as a legacy column for backward compatibility but is not used by the production PP3 / BP4 mRNA path.
Used by: PP3 mRNA path (APOGEE 2 score > 0.5 triggers Supporting pathogenic per McCormick Figure 3), BP4 mRNA path (APOGEE 2 score <= 0.5 triggers Supporting benign, mirror inverse).
Source: MitImpact
mt_gene_coordinates
Coordinate boundaries and biotype classification for every mtDNA gene. Biotype distribution: 22 Mt_tRNA, 13 protein_coding, 2 Mt_rRNA (MT-RNR1, MT-RNR2). Strand information is retained to handle the reverse-strand light-chain genes (MT-TQ, MT-TA, MT-TN, MT-TC, MT-TY, MT-TS1, MT-ND6, MT-TE, MT-TP).
Used by: Gene-class dispatch for criteria with biotype-specific behavior: PVS1, PS1, PM4, PM5_Moderate, PM5_Supporting, PP3, BP4, and BP7 each have biotype-aware logic per McCormick 2020.
Source: Ensembl
mt_haplogroups
Maternal-haplogroup phylogenetic tree with per-edge variant assignments, parent-haplogroup links, back-mutation flags, insertion flags, and variant modifier annotations. Provides the data structure required to evaluate whether a candidate variant is haplogroup-defining for any ancestor of the patient haplogroup.
Used by: BA1 personalized path (variant is haplogroup-defining for the patient maternal lineage). When haplogroup inference is unavailable for a sample, Helena falls back to a conservative BA1 evaluation that does not over-apply the stand-alone benign override.
Source: PhyloTree
mt_helix_curated
Reserved table for Helena clinical-curation overrides of ClinVar assertions. Each entry records the canonical Helena classification, the rationale, and a flag indicating whether the entry supersedes a conflicting ClinVar record. The table is empty in the public reference set and is populated only by named reviewers through the audit-trailed curation interface.
Used by: Curation override layer applied before the ClinVar override gate.
Source: Helena Bioinformatics
nuclear_numt_known_regions
Catalog of nuclear mitochondrial DNA (NUMT) regions with chromosome, start, end, length, and source attribution. Used to flag candidate pseudogene calls during chromosome routing.
Used by: NUMT visibility flags surfaced for reviewer audit. NUMT-overlap and depth-anomaly flags are advisory; classification proceeds under MMDWG and the reviewing geneticist makes the final pseudogene determination.
Source: Published NUMT catalogs
MMDWG Classification
Variant classification follows the ClinGen Mitochondrial Disease Working Group 2020 specification with twenty-five evidence criteria evaluated systematically. Eleven criteria are fully automated; ten require manual curation by the reviewing geneticist; seven are excluded per McCormick Section 5.3.
Classification Priority Order
Classification logic is applied in strict priority order. Higher-priority rules are evaluated first, and the first matching rule determines the final classification:
BA1 Stand-alone
Allele frequency above 1% homoplasmic, or variant is haplogroup-defining for the patient ancestral branch (Helena personalized BA1 path). BA1 is the only stand-alone criterion in the MMDWG framework and cannot be overridden by any other evidence, including ClinVar assertions.
Conflicting Evidence
If a variant has pathogenic evidence at moderate strength or above (PVS, PS, or PM criteria triggered) AND strong benign evidence (BS criteria triggered), the variant is classified as VUS regardless of the individual evidence strength. This is a conservative approach that prioritizes clinical safety.
ClinVar Override
ClinVar P/LP/B/LB classification is applied only when no conflicting computational evidence exists. Requires two or more review stars (stricter than the nuclear one-star default per McCormick Section 5.1). ClinVar VUS does not override computational classification.
Combining Rules
The Richards 2015 eighteen combining rules (Table 5) are evaluated against the criteria triggered for the variant. Rules are retained unchanged for mtDNA per McCormick Section 5.2.
Default
Variants that do not meet any of the above criteria are classified as Uncertain Significance (VUS).
Classification Output
Each variant receives one of five standard classifications, a list of all criteria triggered with explicit strength tiers (e.g. "PVS1, PM2_Supporting, PP3"), an explicit framework provenance label (mmdwg_2020), the MMDWG module version, and a continuous classification confidence score:
Pathogenic
Likely Pathogenic
VUS
Likely Benign
Benign
Automated Criteria (11 of 25)
These criteria are evaluated automatically for every mtDNA variant. Conditions and thresholds follow the McCormick 2020 specification. Each criterion lists the reference data sources it depends on and any biotype-specific behavior.
Null variant in a gene where loss-of-function is a known disease mechanism
Conditions
Applies to mtDNA protein-coding (mRNA) genes only.
Truncating consequence: stop_gained or frameshift.
Strength modulation per Abou Tayoun 2018 (PMID:30192042) decision tree adapted for mtDNA: McCormick 2020 retains the Abou Tayoun framework with the explicit removal of the NMD branch (mtDNA mRNAs are not subject to canonical nuclear NMD).
Exclusions
tRNA and rRNA genes (PVS1 not defined under McCormick for these biotypes).
Stop-retained and stop-lost variants.
Non-canonical splice variants (mtDNA does not undergo nuclear-style splicing).
Reference data: Ensembl mtDNA gene coordinates (biotype dispatch), VEP (consequence)
Per McCormick Section 5.2.1, the nuclear NMD branch of the Abou Tayoun decision tree is removed for mtDNA. mtDNA truncating variants are evaluated for their effect on the mature protein only.
Same amino acid change as an established pathogenic variant
Conditions
Applies to mtDNA protein-coding (mRNA) genes only.
ClinVar Pathogenic or Likely Pathogenic at two or more review stars at the same protein residue with the same amino acid substitution.
Exclusions
tRNA and rRNA genes (PS1 not applicable for non-coding biotypes).
Reference data: mt_clinvar_variants
McCormick Section 5.2.1 retains PS1 with the standard amino-acid match definition for mRNA genes. The two-star ClinVar threshold is stricter than the nuclear default and aligns with the elevated-evidence requirement specified in McCormick Section 5.1.
Absent from population databases
Conditions
gnomAD v3.1 mtDNA homoplasmic allele frequency below the absent-from-controls threshold (default 0.00002), or variant absent from gnomAD entirely.
Reference data: mt_population_frequencies
McCormick Section 5.2.5 explicitly downgrades PM2 from Moderate (the nuclear default) to Supporting for mtDNA, reflecting the reduced statistical power of population-frequency arguments at extremely low frequencies in mtDNA.
Protein length change in a non-repetitive region
Conditions
Applies to mtDNA protein-coding (mRNA) genes only.
In-frame insertion or in-frame deletion that alters protein length in a region not annotated as repetitive or low-complexity.
Exclusions
tRNA and rRNA genes (PM4 not applicable, length changes are evaluated through PM5_Supporting and PP3 tRNA path).
Reference data: Ensembl mtDNA gene coordinates (biotype dispatch), VEP (consequence)
Different missense change at a residue with established pathogenic missense
Conditions
Applies to mtDNA protein-coding (mRNA) genes only.
ClinVar Pathogenic or Likely Pathogenic at two or more review stars at the same protein residue but with a different amino acid substitution.
Exclusions
tRNA and rRNA genes (handled by PM5_Supporting under McCormick Section 5.2.2).
Reference data: mt_clinvar_variants
Different nucleotide change at a position with established pathogenic variant in tRNA / rRNA
Conditions
Applies to mtDNA tRNA and rRNA genes only.
ClinVar Pathogenic or Likely Pathogenic at two or more review stars at the same nucleotide position but with a different alternate allele.
Exclusions
Protein-coding (mRNA) genes (covered by PM5_Moderate at residue level).
Reference data: mt_clinvar_variants, Ensembl mtDNA gene coordinates (biotype dispatch)
McCormick Section 5.2.2 introduces PM5_Supporting specifically for tRNA and rRNA biotypes where amino-acid-level matching is not applicable. Same-nucleotide-different-allele matching at Supporting strength.
Computational evidence supports a deleterious effect
Conditions
mRNA path: APOGEE 2 score above the pathogenic threshold (default 0.5). Per McCormick Figure 3, APOGEE is the recommended in silico tool for mtDNA missense variants.
tRNA path: MitoTIP score above the 50th percentile combined with PON-mt-tRNA pathogenicity probability above 0.5.
rRNA path: not evaluated. McCormick 2020 does not endorse a calibrated in silico predictor for rRNA, so PP3 is not applied for the two rRNA genes.
Exclusions
rRNA biotype (PP3 not applied per McCormick).
PVS1 active for the same variant (no double-counting per ClinGen SVI 2023).
Reference data: mt_apogee2_scores, mt_population_frequencies (MitoTIP, PON-mt-tRNA), Ensembl mtDNA gene coordinates (biotype dispatch)
Allele frequency consistent with stand-alone benign
Conditions
gnomAD v3.1 mtDNA homoplasmic allele frequency above 1% (McCormick Section 5.2.10), OR the variant is haplogroup-defining for the patient ancestral haplogroup branch (Helena personalized BA1 path).
Reference data: mt_population_frequencies, mt_haplogroups
McCormick Section 5.2.10 lowers the BA1 threshold from the nuclear 5% to 1% for mtDNA. Helena evaluates the haplogroup-defining clause against the patient ancestral branch (not against any branch globally) so that variants haplogroup-defining for an unrelated branch do not silently receive BA1 in the patient. When haplogroup inference is uncertain, Helena falls back to a conservative path that applies BA1 only to the > 1% high-frequency arm.
Allele frequency above expected for the disorder
Conditions
gnomAD v3.1 mtDNA homoplasmic allele frequency between 0.5% and 0.99%.
Exclusions
Variant satisfies BA1 (BA1 takes precedence as stand-alone benign).
Reference data: mt_population_frequencies
McCormick Section 5.2.5 specifies the 0.5% Strong-benign threshold for mtDNA, separate from the 1% BA1 threshold. The two together replace the nuclear 5% / 1% pair.
Observed alongside an established pathogenic mtDNA variant in the same individual
Conditions
Another variant in the same patient session is ClinVar Pathogenic or Likely Pathogenic in mtDNA at two or more review stars.
Reference data: mt_clinvar_variants
mtDNA-specific reframing of BP2: in the absence of nuclear-style trans / cis configuration, the presence of an established pathogenic mtDNA variant in the same individual provides Supporting benign evidence for an additional candidate variant in the same mitochondrial genome.
Computational evidence suggests no impact
Conditions
mRNA path: APOGEE 2 score below the benign threshold (default 0.5). Mirror inverse of PP3 mRNA path.
tRNA path: MitoTIP score at or below the 50th percentile, combined with PON-mt-tRNA pathogenicity probability at or below 0.5.
Exclusions
rRNA biotype (BP4 not applied per McCormick, no calibrated rRNA predictor).
PVS1 active for the same variant.
Reference data: mt_apogee2_scores, mt_population_frequencies, Ensembl mtDNA gene coordinates (biotype dispatch)
Synonymous variant without predicted impact
Conditions
Applies to mtDNA protein-coding (mRNA) genes only.
Synonymous consequence (no amino acid change).
No predicted splice impact (mtDNA does not undergo nuclear-style splicing; the splice clause from the nuclear ACMG version is not evaluated).
Exclusions
tRNA and rRNA genes (synonymous concept not applicable).
Reference data: Ensembl mtDNA gene coordinates (biotype dispatch), VEP (consequence)
Curated Criteria (10 of 25)
These criteria require evidence not derivable from VCF and reference data alone: maternal segregation, functional assays, case-control statistics, phenotype specificity, healthy-individual observation, and alternative-diagnosis context. Reviewing geneticists submit curation evidence through the Helena audit-trailed interface with explicit ClinGen mtDNA VCEP v1.0.0 strength tiers.
De novo variant with confirmed maternity
mtDNA is maternally inherited. PS2 strength is determined by the number of independent maternally-confirmed de novo observations and the segregation evidence supporting de novo origin. The four-tier strength scale is selected by the reviewing geneticist through the curation interface.
Functional studies show a deleterious effect
McCormick caps PS3 at Supporting strength for mtDNA pending future calibration of mitochondrial functional assays. Reviewing geneticists submit published functional evidence through the curation interface and cite the supporting PMID.
Increased prevalence in affected versus controls
PS4 strength is selected by the reviewing geneticist or, where proband-count and haplogroup-diversity statistics are available in the session metadata, derived inline by the curation interface. Curated values always supersede inline derivations and are recorded with the derivation source for audit transparency.
Assumed de novo without maternity confirmation
Counterpart to PS2 when maternal confirmation is not available. The four-tier scale matches PS2.
Cosegregation with disease in maternal relatives
McCormick Section 5.2.7 specifies a homoplasmic-in-all-maternal-members disqualifier: if the variant is homoplasmic in every maternal relative regardless of phenotype, PP1 cannot fire because cosegregation is not informative. Helena enforces this disqualifier automatically when the curated maternal-member counts indicate uniform homoplasmy. The audit trail records the disqualification when it applies.
Patient phenotype highly specific for a mitochondrial disorder
Reviewing geneticist confirms phenotype specificity through the curation interface. mtDNA-specific phenotype patterns (Leber hereditary optic neuropathy, MELAS, MERRF, NARP, Leigh syndrome) provide the typical evidence base.
Observed in a healthy maternal relative
McCormick omits the Very Strong and Moderate tiers from BS2 for mtDNA. The two-tier scale is selected by the reviewing geneticist.
Functional studies show no deleterious effect
Strength capped at Supporting per McCormick. Reviewing geneticists submit published benign functional evidence with the supporting PMID.
Lack of segregation in affected maternal relatives
Strong benign evidence when affected maternal relatives do not carry the variant. Selected by the reviewing geneticist through the curation interface.
Variant found in a case with an alternate molecular basis
Reviewing geneticist confirms the alternate diagnosis through the curation interface, with the alternate diagnosis recorded in the audit trail.
Excluded Criteria (7 of 25)
McCormick 2020 Section 5.3 excludes seven nuclear ACMG criteria from mtDNA interpretation because their underlying assumptions do not hold for the mitochondrial genome. Helena does not apply any of these criteria to mtDNA variants.
Functional-domain hot-spot evidence for mtDNA tRNA variants is captured through MitoTIP (PP3 tRNA path), which is itself a domain-aware computational tool. Adding PM1 on top would double-count the same biological argument. McCormick Section 5.3 excludes PM1 to prevent this double-counting.
PM3 (in trans with a pathogenic variant for recessive disorders) presupposes biparental inheritance and a recessive autosomal-recessive mechanism. mtDNA is maternally inherited and does not have an autosomal-recessive analog, so PM3 is biologically inapplicable.
PP2 requires that missense variants be a common mechanism of disease in a constraint-quantified gene. mtDNA exhibits high sequence variability across haplotypes, making gene-level missense constraint statistics uninformative. McCormick Section 5.3 excludes PP2.
ClinGen Sequence Variant Interpretation Working Group (Biesecker 2018, PMID:29543229) recommended retiring PP5 as a redundant criterion subsumed by PS1, PM5, and the ClinVar override gate. McCormick adopts this recommendation for mtDNA.
BP1 applies to genes for which primarily truncating variants cause disease, used to argue against missense pathogenicity. The mtDNA disease catalog includes substantial pathogenic missense burden across the protein-coding genes, so the BP1 premise does not hold.
BP3 covers in-frame indels in repetitive or low-complexity nuclear regions (HVR-style). mtDNA HVR (D-loop) regions are clinically excluded from interpretation entirely, so BP3 is not needed as a separate Supporting benign criterion.
Same ClinGen SVI removal rationale as PP5: subsumed by the ClinVar override gate at two or more review stars and not needed as a separate Supporting benign criterion.
Computational Predictors (PP3 / BP4)
PP3 and BP4 dispatch by gene biotype. mtDNA protein-coding genes use APOGEE 2 (Bianco 2023). mtDNA tRNA genes use a combined MitoTIP plus PON-mt-tRNA evaluation per McCormick Figure 3. mtDNA rRNA genes have no calibrated predictor and PP3 / BP4 are not applied for the two rRNA genes.
APOGEE 2 (mRNA Path)
APOGEE 2 (Bianco 2023, PMID:PMC10439926) is a multi-layer machine-learning model calibrated for the prediction of mtDNA missense variant pathogenicity. Helena uses precomputed APOGEE 2 scores from the MitImpact 3.1.3 distribution covering all 24,190 possible missense substitutions across the 13 protein-coding genes. Score above the pathogenic threshold (default 0.5) triggers PP3 Supporting; score at or below the threshold triggers BP4 Supporting. APOGEE 1 is retained as a legacy column for backward compatibility but is not used by the production PP3 / BP4 logic.
MitoTIP + PON-mt-tRNA (tRNA Path)
McCormick Figure 3 specifies a combined MitoTIP (Sonney 2017, PMID:28809476) plus PON-mt-tRNA (Niroula and Vihinen 2019, PMID:31504522) evaluation for tRNA variants. PP3 fires when MitoTIP exceeds the 50th percentile and PON-mt-tRNA pathogenicity probability exceeds 0.5. BP4 is the mirror inverse. Both tools are calibrated specifically for mtDNA tRNA variants and provide complementary domain-aware and probability-based evaluations.
rRNA Path: Not Evaluated
McCormick 2020 does not endorse a calibrated in silico predictor for the two mtDNA rRNA genes (MT-RNR1, MT-RNR2). PP3 and BP4 are not applied for rRNA biotype variants. Pathogenicity assessment for rRNA variants relies on PVS1 (where applicable), PS1, PM2_Supporting, BA1, BS1, the audit-trailed curation criteria, and the ClinVar override gate.
Combining Rules
The Richards 2015 eighteen combining rules (Table 5) are retained unchanged for mtDNA per McCormick Section 5.2. Strength tiers from McCormick (PM2_Supporting, PM5_Supporting, BS2 two-tier, PS3 / BS3 capped at Supporting) feed directly into the same combining-rule evaluation.
Pathogenic (8 rules)
Likely Pathogenic (6 rules)
Benign (2 rules)
Likely Benign (2 rules)
The Mitochondrial Genome
The 16,569-base human mitochondrial genome encodes 37 genes: 13 protein-coding genes (subunits of OXPHOS complexes I, III, IV, V), 22 transfer-RNA genes (one per amino acid plus two for leucine and serine), and 2 ribosomal-RNA genes (12S and 16S). Gene biotype determines the criterion path under MMDWG.
| Gene | Biotype | Start | End | Strand |
|---|---|---|---|---|
| MT-TF | Mt_tRNA | 577 | 647 | + |
| MT-RNR1 | Mt_rRNA | 648 | 1,601 | + |
| MT-TV | Mt_tRNA | 1,602 | 1,670 | + |
| MT-RNR2 | Mt_rRNA | 1,671 | 3,229 | + |
| MT-TL1 | Mt_tRNA | 3,230 | 3,304 | + |
| MT-ND1 | protein_coding | 3,307 | 4,262 | + |
| MT-TI | Mt_tRNA | 4,263 | 4,331 | + |
| MT-TQ | Mt_tRNA | 4,329 | 4,400 | - |
| MT-TM | Mt_tRNA | 4,402 | 4,469 | + |
| MT-ND2 | protein_coding | 4,470 | 5,511 | + |
| MT-TW | Mt_tRNA | 5,512 | 5,579 | + |
| MT-TA | Mt_tRNA | 5,587 | 5,655 | - |
| MT-TN | Mt_tRNA | 5,657 | 5,729 | - |
| MT-TC | Mt_tRNA | 5,761 | 5,826 | - |
| MT-TY | Mt_tRNA | 5,826 | 5,891 | - |
| MT-CO1 | protein_coding | 5,904 | 7,445 | + |
| MT-TS1 | Mt_tRNA | 7,446 | 7,514 | - |
| MT-TD | Mt_tRNA | 7,518 | 7,585 | + |
| MT-CO2 | protein_coding | 7,586 | 8,269 | + |
| MT-TK | Mt_tRNA | 8,295 | 8,364 | + |
| MT-ATP8 | protein_coding | 8,366 | 8,572 | + |
| MT-ATP6 | protein_coding | 8,527 | 9,207 | + |
| MT-CO3 | protein_coding | 9,207 | 9,990 | + |
| MT-TG | Mt_tRNA | 9,991 | 10,058 | + |
| MT-ND3 | protein_coding | 10,059 | 10,404 | + |
| MT-TR | Mt_tRNA | 10,405 | 10,469 | + |
| MT-ND4L | protein_coding | 10,470 | 10,766 | + |
| MT-ND4 | protein_coding | 10,760 | 12,137 | + |
| MT-TH | Mt_tRNA | 12,138 | 12,206 | + |
| MT-TS2 | Mt_tRNA | 12,207 | 12,265 | + |
| MT-TL2 | Mt_tRNA | 12,266 | 12,336 | + |
| MT-ND5 | protein_coding | 12,337 | 14,148 | + |
| MT-ND6 | protein_coding | 14,149 | 14,673 | - |
| MT-TE | Mt_tRNA | 14,674 | 14,742 | - |
| MT-CYB | protein_coding | 14,747 | 15,887 | + |
| MT-TT | Mt_tRNA | 15,888 | 15,953 | + |
| MT-TP | Mt_tRNA | 15,956 | 16,023 | - |
Coordinates are GRCh38 chrM (NC_012920.1, the revised Cambridge Reference Sequence). Source: Ensembl mtDNA annotation.
Limitations and Disclaimers
Helena is a clinical decision support tool, not a diagnostic device. Every classification requires review and confirmation by a qualified clinical geneticist.
Ten of the twenty-five MMDWG criteria require evidence not derivable from VCF and reference data alone (PS2, PS3, PS4, PM6, PP1, PP4, BS2, BS3, BS4, BP5). These criteria are entered through the audit-trailed curation interface by the reviewing geneticist with explicit ClinGen mtDNA VCEP v1.0.0 strength tiers.
Heteroplasmy interpretation is patient-specific. Homoplasmic, heteroplasmic, and tissue-restricted heteroplasmy patterns each carry different clinical implications. Helena exposes max-heteroplasmy and per-individual heteroplasmy distribution for every variant, but the clinical interpretation of heteroplasmy levels remains a judgment call by the reviewing geneticist.
Patient haplogroup inference depends on the input VCF. When haplogroup-informative variants are absent or insufficient, Helena falls back to a conservative BA1 evaluation rather than guessing the haplogroup. The audit trail records the fallback when it applies.
Nuclear mitochondrial DNA segments (NUMTs) can produce false-positive mtDNA calls. Helena flags NUMT-overlap and depth-anomaly signals for reviewer audit but does not block classification. The reviewing geneticist makes the final pseudogene determination.
Population frequency data from gnomAD v3.1 mtDNA may underrepresent certain ancestral populations. Allele frequency thresholds should be interpreted in the context of the patient ancestry.
ClinVar mtDNA assertions vary in quality and currency. The two-or-more review-star threshold for the override gate (stricter than the nuclear default per McCormick Section 5.1) reduces the impact of unreviewed single-submitter assertions but cannot eliminate it entirely.
PS3 and BS3 are capped at Supporting strength per McCormick 2020 pending future calibration of mitochondrial functional assays. Functional evidence that would qualify for Strong or Moderate strength under the nuclear ACMG framework is currently down-tiered.
Haplogrep3-based haplogroup inference and HmtVAR external annotation are reserved for a future deployment phase. Production currently relies on the maternal-haplogroup phylogenetic tree (PhyloTree FU1a) and the curated reference set described above.
Results should always be interpreted in the context of the patient clinical presentation, family history, mitochondrial functional studies if available, and other clinical information.
Version History
Every methodology change is versioned and documented. The MMDWG module version is independent of the main classifier engine version.
Production deployment of the ClinGen MMDWG 2020 mtDNA classifier (McCormick 2020 PMID:33058415). Eleven automated criteria, ten audit-trailed curation criteria with explicit ClinGen mtDNA VCEP v1.0.0 strength tiers, seven excluded per McCormick Section 5.3.
Two-framework architecture: nuclear ACMG/AMP 2015 (Richards) and mtDNA MMDWG 2020 (McCormick) operate as independent classification modules with explicit framework provenance on every variant in the output.
Personalized BA1 path: the haplogroup-defining clause from McCormick Section 5.2.10 is evaluated against the patient ancestral haplogroup branch using PhyloTree build 17 (FU1a release). Conservative fallback when haplogroup inference is uncertain.
NUMT-aware classification: a curated catalog of 784 NUMT regions across 23 chromosomes feeds visibility flags surfaced for reviewer audit. Classification proceeds under MMDWG; pseudogene determination remains a geneticist judgment call.
Audit-trailed manual curation interface for the ten curated criteria (PS2, PS3, PS4, PM6, PP1, PP4, BS2, BS3, BS4, BP5) with strength tier selection and PMID citation capture.
Categorized transparency notes: every non-default decision (PVS1 NMD branch removal, BA1 conservative fallback, PP1 disqualification, PM5_Supporting tRNA / rRNA, manual curation contribution) is recorded for reviewer audit.
References
McCormick EM, Lott MT, Dulik MC, Shen L, Attimonelli M, Vitale O, et al. Specifications of the ACMG/AMP standards and guidelines for mitochondrial DNA variant interpretation.
Human Mutation. 2020;41(12):2028-2057.
PMID: 33058415Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.
Genetics in Medicine. 2015;17(5):405-424.
PMID: 25741868Abou Tayoun AN, Pesaran T, DiStefano MT, Oza A, Rehm HL, Biesecker LG, Harrison SM. Recommendations for interpreting the loss of function PVS1 ACMG/AMP variant criterion.
Human Mutation. 2018;39(11):1517-1524.
PMID: 30192042Bianco SD, Parca L, Petrizzelli F, Biagini T, Giovannetti A, Liorni N, et al. APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants.
Nature Communications. 2023;14:5562.
PMID: PMC10439926Sonney S, Leipzig J, Lott MT, Zhang S, Procaccio V, Wallace DC, Sondheimer N. Predicting the pathogenicity of novel variants in mitochondrial tRNA with MitoTIP.
PLoS Computational Biology. 2017;13(12):e1005867.
PMID: 28809476Niroula A, Vihinen M. PON-mt-tRNA: a multifactorial probability-based method for classification of mitochondrial tRNA variations.
Nucleic Acids Research. 2016;44(5):2020-2027.
PMID: 31504522Schoenherr S, Weissensteiner H, Kronenberg F, Forer L. Haplogrep 3 - phylogenetic analysis and quality control for mitochondrial DNA variants.
Nucleic Acids Research. 2023;51(W1):W263-W268.
PMID: PMC10320189Calabrese FM, Simone D, Attimonelli M. Primates and mouse NumtS in the UCSC Genome Browser.
BMC Bioinformatics. 2012;13(Suppl 4):S15.
PMID: 24723423Ji Y, Liang M, Zhang J, Zhang M, Zhu J, Meng X, et al. Mitochondrial haplotypes may modulate the phenotypic manifestation of the LHON-associated m.11778G>A mutation.
Mitochondrion. 2012;12(5):597-602.
PMID: 22577229Kang X, Wei X, Jiang L, Niu C, Zhang J, Chen S, Meng D. Composition and variation analysis of the 16S rDNA in mitochondrial haplogroups.
Mitochondrion. 2016;30:60-65.
PMID: 27220472Walker LC, Hoya M, Wiggins GAR, Lindy A, Vincent LM, Parsons MT, et al. Using the ACMG/AMP framework to capture evidence related to predicted and observed impact on splicing: Recommendations from the ClinGen SVI Splicing Subgroup.
American Journal of Human Genetics. 2023;110(7):1046-1067.
PMID: 37352859Biesecker LG, Harrison SM; ClinGen Sequence Variant Interpretation Working Group. The ACMG/AMP reputable source criteria for the interpretation of sequence variants.
Genetics in Medicine. 2018;20(12):1687-1688.
PMID: 29543229Questions About Our mtDNA Methodology?
We welcome technical questions from clinical geneticists, mitochondrial-disease specialists, and laboratory directors. Transparency is foundational to clinical trust.