Evidence map›Paper›PMID 35583122›Full record

ArticleHuman mutation2022

MiRLog and dbmiR: Prioritization and functional annotation tools to study human microRNA sequence variants.

Agnese Giovannetti, Salvatore Daniele Bianco, Alice Traversa, Noemi Panzironi, Alessandro Bruselles, Sara Lazzari, Niccolò Liorni, Marco Tartaglia, Massimo Carella, Antonio Pizzuti and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Human mutation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 56% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

12 authors at 4 institutions in 1 country.

Agnese GiovannettiLaboratory of Clinical Genomics,  Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo (FG), Italy.ORCID 0000-0001-5207-7243
Salvatore Daniele BiancoDepartment of Experimental Medicine, Sapienza University of Rome, Rome, Italy.ORCID 0000-0001-7466-9741
Alice TraversaLaboratory of Clinical Genomics,  Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo (FG), Italy.ORCID 0000-0001-6138-6179
Noemi PanzironiLaboratory of Clinical Genomics,  Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo (FG), Italy.
Alessandro BrusellesDepartment of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy.
Sara LazzariDepartment of Experimental Medicine, Sapienza University of Rome, Rome, Italy.
Niccolò LiorniDepartment of Experimental Medicine, Sapienza University of Rome, Rome, Italy.ORCID 0000-0003-0472-5693
Marco TartagliaGenetics and Rare Diseases Research Division, Ospedale Pediatrico Bambino Gesù, IRCCS, Rome, Italy.ORCID 0000-0001-7736-9672
Massimo CarellaMedical Genetics Unit, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo (FG), Italy.
Antonio PizzutiDepartment of Experimental Medicine, Sapienza University of Rome, Rome, Italy.
Tommaso MazzaUnit of Bioinformatics, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo (FG), Italy.ORCID 0000-0003-0434-8533
Viviana CaputoDepartment of Experimental Medicine, Sapienza University of Rome, Rome, Italy.ORCID 0000-0001-6753-1234
Casa Sollievo della Sofferenza · ITSapienza University of Rome · ITBambino Gesù Children's Hospital · ITIstituto Superiore di Sanità · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recent identification of noncoding variants with pathogenic effects suggests that these variations could underlie a significant number of undiagnosed cases. Several computational methods have been developed to predict the functional impact of noncoding variants, but they exhibit only partial concordance and are not integrated with functional annotation resources, making the interpretation of these variants still challenging. MicroRNAs (miRNAs) are small noncoding RNA molecules that act as fine regulators of gene expression and play crucial functions in several biological processes, such as cell proliferation and differentiation. An increasing number of studies demonstrate a significant impact of miRNA single nucleotide variants (SNVs) both in Mendelian diseases and complex traits. To predict the functional effect of miRNA SNVs, we implemented a new meta-predictor, MiRLog, and we integrated it into a comprehensive database, dbmiR, which includes a precompiled list of all possible miRNA allelic SNVs, providing their biological annotations at nucleotide and miRNA levels. MiRLog and dbmiR were used to explore the genetic variability of miRNAs in 15,708 human genomes included in the gnomAD project, finding several ultra-rare SNVs with a potentially deleterious effect on miRNA biogenesis and function representing putative contributors to human phenotypes.

Indexed as

MicroRNAsBase SequenceComputational BiologyGenome, HumanHumansMolecular Sequence AnnotationNucleotidesPolymorphism, Single NucleotideMicroRNAsNucleotidesfunctional annotationmachine learningmicroRNAnoncoding elementsingle nucleotide variants

Identifiers

PMID35583122
PMCPMC9546175
OpenAlexW4280576496

What Socratic holds

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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 Socratic graph.