Evidence map›Paper›PMID 37372455›Full record

ArticleGenes2023

Identification and Molecular Characterization of a Novel Large-Scale Variant (Exons 4_18 Loss) in the LDLR Gene as a Cause of Familial Hypercholesterolaemia in an Italian Family.

Paola Concolino, Elisa De Paolis, Simona Moffa, Maria Elisabetta Onori, Laura Soldovieri, Claudio Ricciardi Tenore, Maria De Bonis, Claudio Rabacchi, Concetta Santonocito, Martina Rinelli and 4 more

Open access · goldAbstract readCase Reports
In one paragraph

Article in Genes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

14 authors at 3 institutions in 1 country.

Paola ConcolinoDepartmental Unit of Molecular and Genomic Diagnostics, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.ORCID 0000-0002-0523-5744
Elisa De PaolisDepartmental Unit of Molecular and Genomic Diagnostics, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.
Simona MoffaCenter for Endocrine and Metabolic Diseases, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.
Maria Elisabetta OnoriDepartmental Unit of Molecular and Genomic Diagnostics, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.ORCID 0000-0003-1507-3547
Laura SoldovieriCenter for Endocrine and Metabolic Diseases, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.
Claudio Ricciardi TenoreDepartmental Unit of Molecular and Genomic Diagnostics, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.
Maria De BonisDepartmental Unit of Molecular and Genomic Diagnostics, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.
Claudio RabacchiDepartment of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, 41121 Modena, Italy.
Concetta SantonocitoDepartmental Unit of Molecular and Genomic Diagnostics, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.
Martina RinelliDepartmental Unit of Molecular and Genomic Diagnostics, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.ORCID 0000-0001-7691-3314
Sebastiano CalandraDepartment of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41121 Modena, Italy.
Andrea GiaccariCenter for Endocrine and Metabolic Diseases, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.ORCID 0000-0002-7462-7792
Andrea UrbaniDepartmental Unit of Molecular and Genomic Diagnostics, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.
Angelo MinucciDepartmental Unit of Molecular and Genomic Diagnostics, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy.ORCID 0000-0002-0833-4334
Agostino Gemelli University Polyclinic · ITUniversità Cattolica del Sacro Cuore · ITUniversity of Modena and Reggio Emilia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Next-generation sequencing (NGS) is nowadays commonly used for clinical purposes, and represents an efficient approach for the molecular diagnosis of familial hypercholesterolemia (FH). Although the dominant form of the disease is mostly due to the low-density lipoprotein receptor (LDLR) small-scale pathogenic variants, the copy number variations (CNVs) represent the underlying molecular defects in approximately 10% of FH cases. Here, we reported a novel large deletion in the LDLR gene involving exons 4-18, identified by the bioinformatic analysis of NGS data in an Italian family. A long PCR strategy was employed for the breakpoint region analysis where an insertion of six nucleotides (TTCACT) was found. Two Alu sequences, identified within intron 3 and exon 18, could underlie the identified rearrangement by a nonallelic homologous recombination (NAHR) mechanism. NGS proved to be an effective tool suitable for the identification of CNVs, together with small-scale alterations in the FH-related genes. For this purpose, the use and implementation of this cost-effective, efficient molecular approach meets the clinical need for personalized diagnosis in FH cases.

Indexed as

DNA Copy Number VariationsHyperlipoproteinemia Type IIComputational BiologyExonsHumansIntronsReceptors, LDLLDLR protein, humanReceptors, LDLAlu sequencescopy number variations (CNVs)familial hypercholesterolemiaLDL cholesterolLDLR genenext-generation sequencing

Identifiers

PMID37372455
PMCPMC10298720
OpenAlexW4380878053

What OpenQuestion holds

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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.