MétaCan
Menu
Back to cohort
Record W2252902406 · doi:10.1136/jmedgenet-2015-103292

Bone marrow failure and developmental delay caused by mutations in poly(A)-specific ribonuclease (<i>PARN</i>)

2015· article· en· W2252902406 on OpenAlexafffund
Santhosh Dhanraj, Sethu Madhava Rao Gunja, Adam P Deveau, Mikael Nissbeck, Boonchai Boonyawat, Andrew J Coombs, Alessandra Renieri, Mafalda Mucciolo, Annabella Marozza, Sabrina Buoni, Lesley Turner, Hongbing Li, Ameer Jarrar, Mathura Sabanayagam, Melanie Kirby, Mary Shago, Dalila Pinto, Jason N. Berman, Stephen W. Scherer, Anders Virtanen, Yigal Dror

Bibliographic record

VenueJournal of Medical Genetics · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsMemorial University of NewfoundlandIzaak Walton Killam Health CentreDalhousie UniversityHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsZebrafishBiologyDyskeratosis congenitaMutationGeneticsCancer researchGeneTelomere

Abstract

fetched live from OpenAlex

BACKGROUND: Deadenylation regulates RNA function and fate. Poly(A)-specific ribonuclease (PARN) is a deadenylase that processes mRNAs and non-coding RNA. Little is known about the biological significance of germline mutations in PARN. METHODS: We identified mutations in PARN in patients with haematological and neurological manifestations. Genomic, biochemical and knockdown experiments in human marrow cells and in zebrafish have been performed to clarify the role of PARN in the human disease. RESULTS: We identified large monoallelic deletions in PARN in four patients with developmental delay or mental illness. One patient in particular had a severe neurological phenotype, central hypomyelination and bone marrow failure. This patient had an additional missense mutation on the non-deleted allele and severely reduced PARN protein and deadenylation activity. Cells from this patient had impaired oligoadenylation of specific H/ACA box small nucleolar RNAs. Importantly, PARN-deficient patient cells manifested short telomeres and an aberrant ribosome profile similar to those described in some variants of dyskeratosis congenita. Knocking down PARN in human marrow cells and zebrafish impaired haematopoiesis, providing further evidence for a causal link with the human disease. CONCLUSIONS: Large monoallelic mutations of PARN can cause developmental/mental illness. Biallelic PARN mutations cause severe bone marrow failure and central hypomyelination.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.277
Teacher spread0.259 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations95
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Medical GeneticsSame topicRNA Research and SplicingFrench-language works237,207