Evidence map›Paper›PMID 39707869›Full record

ArticleClinical genetics2025

Effectiveness and Impact of Transcript Analysis in Clinical Genetics Daily Practice.

Giovanni Innella, Emanuele Coccia, Carlotta Pia Cristalli, Eliana Zacchi, Sara Calabrese, Isabelle Bacchi, Flavia Palombo, Sara Taormina, Cecilia Evangelisti, Giulia Lanzoni and 8 more

Abstract read
In one paragraph

Article in Clinical genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

18 authors.

Giovanni InnellaDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Emanuele CocciaDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Carlotta Pia CristalliMedical Genetics Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Eliana ZacchiDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Sara CalabreseDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Isabelle BacchiDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.ORCID 0009-0007-3981-5994
Flavia PalomboIRCCS Istituto Delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy.
Sara TaorminaDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Cecilia EvangelistiMedical Genetics Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Giulia LanzoniMedical Genetics Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Valerio CarelliIRCCS Istituto Delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy.
Chiara DiquigiovanniDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Simona FerrariMedical Genetics Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Emanuele PanzaDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Cesare RossiMedical Genetics Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Alessandro VaisfeldDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Elena BonoraDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Daniela TurchettiDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.

Funding

grant PNRR CN - mRNA - n J33C22001140001 to E.B.
6 · The paper itself

Abstract

Broad-spectrum genetic tests often lead to the identification of variants of uncertain significance (VUS), a major issue in modern clinical genetics. A fair proportion of VUS may alter the splicing processes, but their interpretation is challenging. This study aimed at providing a classification approach for VUS potentially-affecting splicing by integrating transcript analysis from peripheral blood mRNA into routine diagnostics. VUS in DICER1, MSH2, MLH1, DYNC1H1, RPS6KA3, and SCN9A, found in patients with phenotypes compatible with the related syndromes, altered splicing, leading to their re-classification as Pathogenic/Likely Pathogenic. This had a significant clinical impact for different diseases, from hereditary tumor predisposition to neurological and congenital syndromic disorders. Transcript analysis is valuable in VUS clinical evaluation, and its incorporation into routine diagnostic workflows facilitates timely and accurate clinical decision-making.

Indexed as

Genetics, MedicalGenetic TestingRNA, MessengerDEAD-box RNA HelicasesFemaleGenetic Predisposition to DiseaseHumansMaleMutationPhenotypeRibonuclease IIIRNA SplicingDEAD-box RNA HelicasesDICER1 protein, humanRibonuclease IIIRNA, Messengersplicingtranscript analysisVUS

Identifiers

PMID39707869
PMCPMC11973019

What OpenQuestion holds

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LicenceCC BY-NC
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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.