Evidence map›Paper›PMID 34040194›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2021

Improved detection of mitochondrial DNA instability in mitochondrial genome maintenance disorders.

Celine Bris, David Goudenège, Valerie Desquiret-Dumas, Naig Gueguen, Sylvie Bannwarth, Pauline Gaignard, Benoit Rucheton, Aurelien Trimouille, Stephane Allouche, Cecile Rouzier and 18 more

Abstract read
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In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 33% of its field
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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Primary mitochondrial disorders and mimics: Insights from a large French cohort.Annals of clinical and translational neurology · 2024
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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

28 authors at 11 institutions in 1 country.

Celine BrisMitoLab, UMR CNRS 6015, INSERM U1083, Institut MitoVasc, Université d'Angers, Angers, France.
David GoudenègeMitoLab, UMR CNRS 6015, INSERM U1083, Institut MitoVasc, Université d'Angers, Angers, France.
Valerie Desquiret-DumasMitoLab, UMR CNRS 6015, INSERM U1083, Institut MitoVasc, Université d'Angers, Angers, France.
Naig GueguenMitoLab, UMR CNRS 6015, INSERM U1083, Institut MitoVasc, Université d'Angers, Angers, France.
Sylvie BannwarthUniversité Côte d'Azur, CHU de Nice, INSERM, CNRS, IRCAN, Nice, France.
Pauline GaignardService de Biochimie, CHU Bicêtre, APHP Université Paris Saclay, Le Kremlin-Bicêtre, France.
Benoit RuchetonDépartement de Biochimie et Génétique, APHP, GHU Pitié-Salpêtrière, Paris, France.
Aurelien TrimouilleService de Génétique médicale, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France.
Stephane AlloucheService de Biochimie, EA4650, Centre Hospitalier Universitaire, Caen, France.
Cecile RouzierUniversité Côte d'Azur, CHU de Nice, INSERM, CNRS, IRCAN, Nice, France.
Samira SaadiUniversité Côte d'Azur, CHU de Nice, INSERM, CNRS, IRCAN, Nice, France.
Claude JardelDépartement de Biochimie et Génétique, APHP, GHU Pitié-Salpêtrière, Paris, France.
Abdel SlamaService de Biochimie, CHU Bicêtre, APHP Université Paris Saclay, Le Kremlin-Bicêtre, France.
Magalie BarthDépartement de Biochimie et Génétique, CHU d'Angers, Angers, France.
Christophe VernyMitoLab, UMR CNRS 6015, INSERM U1083, Institut MitoVasc, Université d'Angers, Angers, France.
Marco SpinazziMitoLab, UMR CNRS 6015, INSERM U1083, Institut MitoVasc, Université d'Angers, Angers, France.
Julien CassereauMitoLab, UMR CNRS 6015, INSERM U1083, Institut MitoVasc, Université d'Angers, Angers, France.
Estelle ColinMitoLab, UMR CNRS 6015, INSERM U1083, Institut MitoVasc, Université d'Angers, Angers, France.
Magot ArmelleCentre de Référence Maladies Neuromusculaires, CHU Nantes, Nantes, France.
Yann PereonCentre de Référence Maladies Neuromusculaires, CHU Nantes, Nantes, France.
Marie Laure Martin-NegrierService de Pathologie, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France.
Veronique Paquis-FlucklingerUniversité Côte d'Azur, CHU de Nice, INSERM, CNRS, IRCAN, Nice, France.
Franck LetournelUF de Neurobiologie-Neuropathologie, UMR INSERM 1066 - CNRS 6021, MINT, Angers, France.
Guy LenaersMitoLab, UMR CNRS 6015, INSERM U1083, Institut MitoVasc, Université d'Angers, Angers, France.
Dominique BonneauMitoLab, UMR CNRS 6015, INSERM U1083, Institut MitoVasc, Université d'Angers, Angers, France.
Pascal ReynierMitoLab, UMR CNRS 6015, INSERM U1083, Institut MitoVasc, Université d'Angers, Angers, France.
Patrizia Amati-BonneauMitoLab, UMR CNRS 6015, INSERM U1083, Institut MitoVasc, Université d'Angers, Angers, France.
Vincent ProcaccioMitoLab, UMR CNRS 6015, INSERM U1083, Institut MitoVasc, Université d'Angers, Angers, France. ViProcaccio@chu-angers.fr.
Inserm · FRUniversité d'Angers · FRCentre Hospitalier Universitaire d'Angers · FRCentre National de la Recherche Scientifique · FRAssistance Publique – Hôpitaux de Paris · FRCentre Hospitalier Universitaire de Bordeaux · FRInstitut de Recherche sur le Cancer et le Vieillissement de Nice · FRBicêtre Hospital · FRCentre Hospitalier Universitaire de Caen · FRCentre Hospitalier Universitaire de Nice · FRSorbonne Université · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeDiseases caused by defects in mitochondrial DNA (mtDNA) maintenance machinery, leading to mtDNA deletions, form a specific group of disorders. However, mtDNA deletions also appear during aging, interfering with those resulting from mitochondrial disorders.

methodsHere, using next-generation sequencing (NGS) data processed by eKLIPse and data mining, we established criteria distinguishing age-related mtDNA rearrangements from those due to mtDNA maintenance defects. MtDNA deletion profiles from muscle and urine patient samples carrying pathogenic variants in nuclear genes involved in mtDNA maintenance (n = 40) were compared with age-matched controls (n = 90). Seventeen additional patient samples were used to validate the data mining model.

resultsOverall, deletion number, heteroplasmy level, deletion locations, and the presence of repeats at deletion breakpoints were significantly different between patients and controls, especially in muscle samples. The deletion number was significantly relevant in adults, while breakpoint repeat lengths surrounding deletions were discriminant in young subjects.

conclusionAltogether, eKLIPse analysis is a powerful tool for measuring the accumulation of mtDNA deletions between patients of different ages, as well as in prioritizing novel variants in genes involved in mtDNA stability.

Indexed as

Genome, MitochondrialMitochondrial DiseasesAdultDNA, MitochondrialHigh-Throughput Nucleotide SequencingHumansMitochondriaSequence DeletionDNA, Mitochondrial

Identifiers

PMID34040194
OpenAlexW3165426752

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.