Evidence map›Paper›PMID 35087072›Full record

ArticleNPJ genomic medicine2022

An evaluation of pipelines for DNA variant detection can guide a reanalysis protocol to increase the diagnostic ratio of genetic diseases.

Raquel Romero, Lorena de la Fuente, Marta Del Pozo-Valero, Rosa Riveiro-Álvarez, María José Trujillo-Tiebas, Inmaculada Martín-Mérida, Almudena Ávila-Fernández, Ionut-Florin Iancu, Irene Perea-Romero, Gonzalo Núñez-Moreno and 6 more

Abstract read
In one paragraph

Article in NPJ genomic medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  8. From DNA to Big Data: NGS Technologies and Their Applications.Methods in molecular biology (Clifton, N.J.) · 2025
    Review
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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

16 authors.

Raquel RomeroDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.
Lorena de la FuenteDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.
Marta Del Pozo-ValeroDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.
Rosa Riveiro-ÁlvarezDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.
María José Trujillo-TiebasDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.
Inmaculada Martín-MéridaDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.
Almudena Ávila-FernándezDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.
Ionut-Florin IancuDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.ORCID http://orcid.org/0000-0001-9742-2717
Irene Perea-RomeroDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.ORCID http://orcid.org/0000-0002-6402-4891
Gonzalo Núñez-MorenoDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.
Alejandra DamiánDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.
Cristina RodillaDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.
Berta AlmogueraDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.ORCID http://orcid.org/0000-0002-5599-2954
Marta CortónDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.
Carmen AyusoDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain. cayuso@fjd.es.ORCID http://orcid.org/0000-0002-9242-7065
Pablo MínguezDepartment of Genetics, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain. pablo.minguez@quironsalud.es.ORCID http://orcid.org/0000-0003-4099-9421

Funding

Comunidad de Madrid PEJ-2017-AI/BMD7256Consejería de Educación, Juventud y Deporte, Comunidad de Madrid (Consejería de Educación, Juventud y Deporte de la Comunidad de Madrid) 2019-T2/BMD-13714Consejería de Educación, Juventud y Deporte, Comunidad de Madrid (Consejería de Educación, Juventud y Deporte de la Comunidad de Madrid) PEJ-2020-AI/BMD-18610Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) CA18/00017Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) FI17/00192Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) FI18/00123Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) JR17/00020Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) PI19/00321Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III) PI20/00851
6 · The paper itself

Abstract

Clinical exome (CE) sequencing has become a first-tier diagnostic test for hereditary diseases; however, its diagnostic rate is around 30-50%. In this study, we aimed to increase the diagnostic yield of CE using a custom reanalysis algorithm. Sequencing data were available for three cohorts using two commercial protocols applied as part of the diagnostic process. Using these cohorts, we compared the performance of general and clinically relevant variant calling and the efficacy of an in-house bioinformatic protocol (FJD-pipeline) in detecting causal variants as compared to commercial protocols. On the whole, the FJD-pipeline detected 99.74% of the causal variants identified by the commercial protocol in previously solved cases. In the unsolved cases, FJD-pipeline detects more INDELs and non-exonic variants, and is able to increase the diagnostic yield in 2.5% and 3.2% in the re-analysis of 78 cancer and 62 cardiovascular cases. These results were considered to design a reanalysis, filtering and prioritization algorithm that was tested by reassessing 68 inconclusive cases of monoallelic autosomal recessive retinal dystrophies increasing the diagnosis by 4.4%. In conclusion, a guided NGS reanalysis of unsolved cases increases the diagnostic yield in genetic disorders, making it a useful diagnostic tool in medical genetics.

Identifiers

PMID35087072
PMCPMC8795168

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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 OpenQuestion graph.