Evidence map›Paper›PMID 37598215›Full record

ArticleNature communications2023

APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants.

Salvatore Daniele Bianco, Luca Parca, Francesco Petrizzelli, Tommaso Biagini, Agnese Giovannetti, Niccolò Liorni, Alessandro Napoli, Massimo Carella, Vincent Procaccio, Marie T Lott and 5 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
5.2field-weighted citation impact, top 4% 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

20 citing papers in PubMed, 34 citations in OpenAlex.

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  15. A novel mitochondrial DNA variant inMolecular genetics and metabolism reports · 2024
    Article
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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

15 authors at 4 institutions in 3 countries.

Salvatore Daniele BiancoBioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, S. Giovanni Rotondo (FG), Italy.
Luca ParcaBioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, S. Giovanni Rotondo (FG), Italy.ORCID http://orcid.org/0000-0002-0924-8518
Francesco PetrizzelliBioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, S. Giovanni Rotondo (FG), Italy.
Tommaso BiaginiBioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, S. Giovanni Rotondo (FG), Italy.
Agnese GiovannettiClinical Genomics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, S. Giovanni Rotondo (FG), Italy.ORCID http://orcid.org/0000-0001-5207-7243
Niccolò LiorniBioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, S. Giovanni Rotondo (FG), Italy.
Alessandro NapoliBioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, S. Giovanni Rotondo (FG), Italy.
Massimo CarellaMedical Genetics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, S. Giovanni Rotondo, (FG), Italy.
Vincent ProcaccioUniversity of Angers, Genetics Department CHU Angers, Mitolab UMR CNRS 6015-INSERM U1083, F-49000, Angers, France.
Marie T LottCenter for Mitochondrial and Epigenomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0003-2035-479X
Shiping ZhangCenter for Mitochondrial and Epigenomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Angelo Luigi VescoviISBReMIT Institute for Stem Cell Biology, Regenerative Medicine and Innovative Therapies, Fondazione IRCSS Casa Sollievo della Sofferenza, S. Giovanni Rotondo (FG), Italy.
Douglas C WallaceCenter for Mitochondrial and Epigenomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Viviana CaputoDepartment of Experimental Medicine, Sapienza University of Rome, Rome, Italy.
Tommaso MazzaBioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, S. Giovanni Rotondo (FG), Italy. t.mazza@css-mendel.it.ORCID http://orcid.org/0000-0003-0434-8533
Casa Sollievo della Sofferenza · ITChildren's Hospital of Philadelphia · USCentre National de la Recherche Scientifique · FRSapienza University of Rome · IT

Funding

The Intellectual and Developmental Disabilities Research Center (IDDRC) at CHOP/PennP50HD105354 · NICHD · CHILDREN'S HOSP OF PHILADELPHIA · PI ERIC D MARSH, ROBERT Thomas SCHULTZ · 2021 to 2026
$9.2M
MITOCHONDRIAL INBORN ERRORS OF METABOLISMR01NS021328 · NINDS · UNIVERSITY OF CALIFORNIA-IRVINE · PI WALLACE, DOUGLAS C · 1985 to 2017
$6.5M
Anti-tumor immunity and intestinal microbiota are modulated by mitochondrial DNAR01CA259635 · NCI · CHILDREN'S HOSP OF PHILADELPHIA · PI Douglas C Wallace · 2022 to 2026
$3.2M
A MITOCHONDRIAL-INTERNEURONAL HYPOTHESIS OF AUTISMR01MH108592 · NIMH · CHILDREN'S HOSP OF PHILADELPHIA · PI WALLACE, DOUGLAS C · 2016 to 2020
$3.1M
Mouse models for mitochondrial disorders caused by mutations in mtDNAR01OD010944 · OD · UNIVERSITY OF SOUTH ALABAMA · PI ALEXEYEV, MIKHAIL F., WALLACE, DOUGLAS C · 2012 to 2020
$2.6M
NCI NIH HHS R01 CA259635NICHD NIH HHS P50 HD105354NIH HHS R01 OD010944NIMH NIH HHS R01 MH108592NINDS NIH HHS R01 NS021328
6 · The paper itself

Abstract

Mitochondrial dysfunction has pleiotropic effects and is frequently caused by mitochondrial DNA mutations. However, factors such as significant variability in clinical manifestations make interpreting the pathogenicity of variants in the mitochondrial genome challenging. Here, we present APOGEE 2, a mitochondrially-centered ensemble method designed to improve the accuracy of pathogenicity predictions for interpreting missense mitochondrial variants. Built on the joint consensus recommendations by the American College of Medical Genetics and Genomics/Association for Molecular Pathology, APOGEE 2 features an improved machine learning method and a curated training set for enhanced performance metrics. It offers region-wise assessments of genome fragility and mechanistic analyses of specific amino acids that cause perceptible long-range effects on protein structure. With clinical and research use in mind, APOGEE 2 scores and pathogenicity probabilities are precompiled and available in MitImpact. APOGEE 2's ability to address challenges in interpreting mitochondrial missense variants makes it an essential tool in the field of mitochondrial genetics.

Indexed as

Amino AcidsMutation, MissenseHumansMachine LearningMitochondriaMutationAmino Acids

Identifiers

PMID37598215
PMCPMC10439926
OpenAlexW4385999365

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.