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Record W4403811505 · doi:10.1681/asn.202421s12k91

Mitochondrial DNA Copy Number Is Associated with Incident AKI, CKD, and Inflammatory Biomarkers

2024· article· en· W4403811505 on OpenAlexaffabout
Pukhraj S. Gaheer, Giuliano Caltagirone, Adeera Levin, Wei Q. Deng, Michael Chong, Matthew B. Lanktree

Bibliographic record

VenueJournal of the American Society of Nephrology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsUniversity of British ColumbiaMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsMitochondrial DNAMedicineBiologyGeneticsGene

Abstract

fetched live from OpenAlex

Background: Mitochondrial DNA copy number (mtDNA-CN) is an estimate of the number of mitochondria per leukocyte and a surrogate measure of net mitochondrial function. Reduced mtDNA-CN has been reported associated with diabetes, cardiovascular disease, and CKD. We sought to evaluate the association of blood mtDNA-CN with incident acute kidney injury (AKI), CKD, and inflammatory biomarkers. Methods: mtDNA-CN was estimated from whole-genome sequencing data in the UK Biobank cohort, consisting of 38,440 samples from the general population. We estimated mtDNA-CN using a quantitative polymerase chain reaction (qPCR) in the Canadian study of prediction of death, dialysis, and interim cardiovascular events (CanPREDDICT) cohort, consisting of 1,435 patients with advanced CKD. Linear and Cox proportional hazard regressions were adjusted for blood cell counts, age, sex, and comorbidities. We also used two-sample Mendelian randomization to test if genetically predicted mtDNA-CN was associated with eGFR. Reverse Mendelian randomization tested the opposite direction: if genetically predicted kidney function was associated with mtDNA-CN. Results: In the UK Biobank, we observed a 12% higher risk of incident AKI (hazard ratio (HR)=0.88, 95% CI = 0.86–0.91, P=2.4x10-6) and 8% increased odds of incident CKD (odds ratio=0.92, 95% CI = 0.89-0.94, P=0.0008) per 1 standard deviation (SD) decrease in mtDNA-CN while adjusting for baseline eGFR. Meta-analyzing across CanPREDDICT and UK Biobank revealed a 16% higher risk of incident kidney failure (HR=0.84, 95% CI = 0.76-0.93; P=0.0006) and a 3% increase in uACR (95% CI = 1%-5%, P=0.002) per 1 SD decrease in mtDNA-CN. In CanPREDDICT, mtDNA-CN was also associated with transforming growth factor-ß1 (TGFß1, ß=-9.5% per 1 SD decrease, P=0.0005) and C reactive protein (CRP, ß=8.9% per 1 SD decrease, P=0.005). Bidirectional Mendelian randomization analysis did not support either mtDNA-CN or eGFR as causally impacting the other (P>0.05). Conclusion: mtDNA-CN was associated with incident AKI, CKD, and kidney failure, as well as pro-inflammatory markers TGFß1 and CRP. However, Mendelian randomization analysis did not support a causal relationship between kidney function and mtDNA-CN, suggesting a separate causal pathway mediates the association. Funding: Government Support – Non-U.S.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.241
Teacher spread0.236 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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