Evidence map›Paper›PMID 39704901›Full record

ArticleMolecular genetics and genomics : MGG2024

Six genetic variants are associated with cardiovascular disease independently from canonical risk factors: a new method to refine GWAS results based on the UKBiobank phenotype database.

Davide Noto, Carola Maria Gagliardo, Rossella Spina, Antonina Giammanco, Marcello Ciaccio, Angelo B Cefalù, Maurizio Averna

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Article in Molecular genetics and genomics : MGG, 2024. 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
–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

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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.

  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

7 authors.

Davide Noto *Department of Health Promotion, Maternal and Child Care, Internal Medicine and Medical Specialities "G. D'Alessandro" (PROMISE), University of Palermo, Via del Vespro 129, Palermo, 90127, Italy. davide.noto04@unipa.it.ORCID http://orcid.org/0000-0002-5346-2829
Carola Maria Gagliardo *Department of Health Promotion, Maternal and Child Care, Internal Medicine and Medical Specialities "G. D'Alessandro" (PROMISE), University of Palermo, Via del Vespro 129, Palermo, 90127, Italy.
Rossella SpinaDepartment of Health Promotion, Maternal and Child Care, Internal Medicine and Medical Specialities "G. D'Alessandro" (PROMISE), University of Palermo, Via del Vespro 129, Palermo, 90127, Italy.
Antonina GiammancoDepartment of Health Promotion, Maternal and Child Care, Internal Medicine and Medical Specialities "G. D'Alessandro" (PROMISE), University of Palermo, Via del Vespro 129, Palermo, 90127, Italy.
Marcello CiaccioDepartment of Biomedicine, Neuroscience and Advanced Diagnostics (BIND), Section of Clinical Biochemistry, Clinical Molecular Medicine and Laboratory Medicine, University of Palermo, Palermo, Italy.
Angelo B CefalùDepartment of Health Promotion, Maternal and Child Care, Internal Medicine and Medical Specialities "G. D'Alessandro" (PROMISE), University of Palermo, Via del Vespro 129, Palermo, 90127, Italy.
Maurizio AvernaDepartment of Health Promotion, Maternal and Child Care, Internal Medicine and Medical Specialities "G. D'Alessandro" (PROMISE), University of Palermo, Via del Vespro 129, Palermo, 90127, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper describes a novel methodology based on GWAS filtering, aimed to find novel phenotypes associated to genetic loci independently of canonical risk factors using the large database of UK Biobank. Genome wide association studies (GWAS) is an untargeted methodology able to identify novel gene variants associated with diseases. Novel gene-phenotype associations might be discovered by this method. UKBiobank was interrogated by an automated routine to search associations between hundreds of phenotypes and single nucleotide polymorphisms (SNPs) resulting from GWAS, using Cardiovascular Disease as investigated trait. Six gene variants associated with CVD, independently of canonical risk factors, were identified using a variants database of more than 400k genotyped subjects (rs9349379 PHACTR1;intragenic_variant, rs74617384 LPA; intron_variant, rs4977574 CDKN2B-AS1;intron_variant, rs11191846 STN1;intron_variant, rs3184504, SH2B3;missense_variant, rs2929155 ADAMTS7;synonymous_variant). Novel clinical and biochemical phenotypes have been associated to the variants. The phenotypical characterization of the loci helped to propose mechanistic links that could explain their connection to CVD.

Indexed as

Cardiovascular DiseasesGenetic Predisposition to DiseaseGenome-Wide Association StudyPhenotypePolymorphism, Single NucleotideAdaptor Proteins, Signal TransducingBiological Specimen BanksDatabases, GeneticHumansMicrofilament ProteinsRisk FactorsUnited KingdomAdaptor Proteins, Signal TransducingMicrofilament ProteinsPHACTR1 protein, humanCardiovascular diseaseCardiovascular risk factorsGWASSingle nucleotide polymorphismsUKBiobank

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Registered trials

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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.