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Record W4200194650 · doi:10.1212/wnl.0000000000013165

Mitochondrial DNA Copy Number as a Marker and Mediator of Stroke Prognosis

2021· article· en· W4200194650 on OpenAlexafffund
Michael Chong, Sukrit Narula, Robert W. Morton, Conor Judge, Loubna Akhabir, Nathan Cawte, Nazia Pathan, Ricky Lali, Pedrum Mohammadi‐Shemirani, Ashkan Shoamanesh, Martin O’Donnell, Salim Yusuf, Peter Langhorne, Guillaume Paré

Bibliographic record

VenueNeurology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsMcMaster UniversityImpactThrombosis and Atherosclerosis Research Institute
FundersCanadian Institutes of Health Research
KeywordsBuffy coatMendelian randomizationStroke (engine)Odds ratioMedicineConfidence intervalInternal medicineMitochondrial DNAGeneticsGenotypeBiologySurgeryGenetic variantsGene

Abstract

fetched live from OpenAlex

Background and Objectives Low buffy coat mitochondrial DNA copy number (mtDNA-CN) is associated with incident risk of stroke and poststroke mortality; however, its prognostic utility has not been extensively explored. Our goal was to investigate whether low buffy coat mtDNA-CN is a marker and causal determinant of poststroke outcomes using epidemiologic and genetic studies. Methods First, we performed association testing between baseline buffy coat mtDNA-CN measurements and 1-month poststroke outcomes in 3,498 cases of acute, first stroke from 25 countries from the international, multicenter case-control study Importance of Conventional and Emerging Risk Factors of Stroke in Different Regions and Ethnic Groups of the World (INTERSTROKE). Then, we performed 2-sample mendelian randomization analyses to evaluate potential causative effects of low mtDNA-CN on 3-month modified Rankin Scale (mRS) score. Genetic variants associated with mtDNA-CN levels were derived from the UK Biobank study (N = 383,476), and corresponding effects on 3-month mRS score were ascertained from the Genetics of Ischemic Stroke Functional Outcome (GISCOME; N = 6,021) study. Results A 1-SD lower mtDNA-CN at baseline was associated with stroke severity (baseline mRS score: odds ratio [OR] 1.27, 95% confidence interval [CI] 1.19–1.36; p = 4.7 × 10−12). Independently of baseline stroke severity, lower mtDNA-CN was associated with increased odds of greater 1-month disability (ordinal mRS score: OR 1.16, 95% CI 1.08–1.24; p = 4.4 × 10−5), poor functional outcome status (mRS score 3–6 vs 0–2: OR 1.21, 95% CI 1.08–1.34; p = 6.9 × 10−4), and mortality (OR 1.35, 95% CI 1.14–1.59; p = 3.9 × 10−4). Subgroup analyses demonstrated consistent effects across stroke type, sex, age, country income level, and education level. In addition, mtDNA-CN significantly improved reclassification of poor functional outcome status (net reclassification index [NRI] score 0.16, 95% CI 0.08–0.23; p = 3.6 × 10−5) and mortality (NRI score 0.31, 95% CI 0.19–0.43; p = 1.7 × 10−7) beyond known prognosticators. With the use of independent datasets, mendelian randomization revealed that a 1-SD decrease in genetically determined mtDNA-CN was associated with increased odds of greater 3-month disability quantified by ordinal mRS score (OR 2.35, 95% CI 1.13–4.90; p = 0.02) and poor functional outcome status (OR 2.68, 95% CI 1.05–6.86; p = 0.04). Discussion Buffy coat mtDNA-CN is a novel and robust marker of poststroke prognosis that may also be a causal determinant of poststroke outcomes. Classification of Evidence This study provides Class II evidence that low buffy coat mtDNA-CN (>1 SD) was associated with worse baseline severity and 1-month outcomes in patients with ischemic or hemorrhagic stroke.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.238
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations27
Published2021
Admission routes2
Has abstractyes

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