Evidence map›Paper›PMID 42305255›Full record

ArticleKidney international reports2026

Enrichment of Rare Mitochondrial DNA Variants Among Individuals With Kidney Disease Reveals Undiagnosed Mitochondrial Disease.

Daniel R Schecter, Rory J Tinker, Patrick O'Connell, Jiuhong Pang, Simon SzeKing Lee, Meltem Ece Kars, Aysegul Guvenek, Michael Preuss, Yuval Itan, Eva Morava and 4 more

Abstract read
In one paragraph

Article in Kidney international reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Daniel R SchecterDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Rory J TinkerDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Patrick O'ConnellDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Jiuhong PangDepartment of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York, USA.
Simon SzeKing LeeDepartment of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Meltem Ece KarsDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Aysegul GuvenekDepartment of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Michael PreussDepartment of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Yuval ItanDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Eva MoravaDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Tamas KoziczDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Michio HiranoDepartment of Neurology, Columbia University Irving Medical Center, New York, New York, USA.
Ali NainiDepartment of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York, USA.
Jaya GaneshDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Pathogenic mitochondrial DNA (mtDNA) variants cause multisystem disease, yet their contribution to kidney disease remains incompletely characterized, partly because of exclusion of the mitochondrial genome from genetic studies. Methods: We evaluated mtDNA variation in 27,747 participants from the Mount Sinai Million Health Discoveries Program (MSM), an ancestrally diverse biobank with whole-exome sequencing and linked electronic health records (EHR). mtDNA variants were identified using MitoVerse and classified with MITOMAP. Kidney disease was defined using renal PheCodes for glomerular disease (GU_580) and renal failure (GU_582). Previous mitochondrial diagnoses were ascertained from EHR to identify undiagnosed individuals. Associations were adjusted for age, self-reported gender, and ancestry, with genotype-phenotype review. Results: Among 3935 individuals with kidney disease, 45 carried clinically associated mtDNA variants, 42 of whom had no previous clinical mitochondrial diagnosis. mtDNA variants were enriched among individuals with kidney disease and associated with increased odds of renal involvement (odds ratio [OR] = 1.72). Associations were strongest for chronic kidney disease (CKD; GU_582.2; OR = 1.55) and renal failure (GU_582; OR = 1.53). Among undiagnosed carriers, genotype-phenotype review identified concordant manifestations in 14%, including mitochondrial CKD with hyperuricemia. Variant-level analysis identified enrichment of m.1630A>G in Conclusion: Pathogenic mtDNA variants are overrepresented among individuals with kidney disease, often without a known mitochondrial diagnosis. These findings support a contributory role for mtDNA in renal disease and highlight the value of mtDNA analysis into kidney disease research and clinical evaluation, particularly for identifying unrecognized mitochondrial disease with renal involvement.

Indexed as

mitochondrial diseasemitochondrial DNApopulation biobankprecision medicinevariant-level association

Identifiers

PMID42305255
PMCPMC13265648

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