Evidence map›Paper›PMID 34177904›Full record

ArticleFrontiers in immunology2021

Next Generation Sequencing Based Multiplex Long-Range PCR for Routine Genotyping of Autoinflammatory Disorders.

Ferhat Guzel, Micol Romano, Erdi Keles, David Piskin, Seza Ozen, Hakan Poyrazoglu, Ozgur Kasapcopur, Erkan Demirkaya

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 48% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. 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

8 authors at 4 institutions in 2 countries.

Ferhat GuzelDepartment of Research and Development, Gentera Biotechnology, Istanbul, Turkey.
Micol RomanoDepartment of Paediatrics, Division of Paediatric Rheumatology, Schulich School of Medicine & Dentistry, University of Western Ontario, London, ON, Canada.
Erdi KelesDepartment of Research and Development, Gentera Biotechnology, Istanbul, Turkey.
David PiskinDepartment of Paediatrics, Division of Paediatric Rheumatology, Schulich School of Medicine & Dentistry, University of Western Ontario, London, ON, Canada.
Seza OzenDepartment of Paediatrics, Division of Paediatric Rheumatology, Hacettepe University, Ankara, Turkey.
Hakan PoyrazogluDepartment of Paediatrics, Division of Paediatric Rheumatology, Erciyes University, Kayseri, Turkey.
Ozgur KasapcopurDepartment of Paediatrics, Division of Paediatric Rheumatology, Cerrhapasa Medical School, Istanbul University, Istanbul, Turkey.
Erkan DemirkayaDepartment of Paediatrics, Division of Paediatric Rheumatology, Schulich School of Medicine & Dentistry, University of Western Ontario, London, ON, Canada.
Western University · CAErciyes University · TRHacettepe University · TRIstanbul University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: During the last decade, remarkable progress with massive sequencing has been made in the identification of disease-associated genes for AIDs using next-generation sequencing technologies (NGS). An international group of experts described the ideal genetic screening method which should give information about SNVs, InDels, Copy Number Variations (CNVs), GC rich regions. We aimed to develop and validate a molecular diagnostic method in conjunction with the NGS platform as an inexpensive, extended and uniform coverage and fast screening tool which consists of nine genes known to be associated with various AIDs. Methods: For the validation of basic and expanded panels, long-range multiplex models were setup on healthy samples without any known variations for MEFV, MVK, TNFRSF1A, NLRP3, PSTPIP1, IL1RN, NOD2, NLRP12 and LPIN2 genes. Patients with AIDs who had already known causative variants in these genes were sequenced for analytical validation. As a last step, multiplex models were validated on patients with pre-diagnosis of AIDs. All sequencing steps were performed on the Illumina NGS platform. Validity steps included the selection of related candidate genes, primer design, development of screening methods, validation and verification of the product. The GDPE (Gentera) bioinformatics pipeline was followed. Results: Although there was no nonsynonymous variation in 21 healthy samples, 107 synonymous variant alleles and some intronic and UTR variants were detected. In 10 patients who underwent analytical validation, besides the 11 known nonsynonymous variant alleles, 11 additional nonsynonymous variant alleles and a total of 81 synonymous variants were found. In the clinical validation phase, 46 patients sequenced with multiplex panels, genetic and clinical findings were combined for diagnosis. Conclusion: In this study, we describe the development and validation of an NGS-based multiplex array enabling the "long-amplicon" approach for targeted sequencing of nine genes associated with common AIDs. This screening tool is less expensive and more comprehensive compared to other methods and more informative than traditional sequencing. The proposed panel offers advantages to WES or hybridization probe equivalents in terms of CNV analysis, high sensitivity and uniformity, GC-rich region sequencing, InDel detection and intron covering.

Indexed as

AllelesGenetic TestingGenotypeHereditary Autoinflammatory DiseasesHigh-Throughput Nucleotide SequencingHumansMultiplex Polymerase Chain ReactionMutationReproducibility of ResultsSequence Analysis, DNAautoinflammationgenetic diagnosislong range PCRmultiplexnext generation sequencing - NGS

Identifiers

PMID34177904
PMCPMC8219981
OpenAlexW3168211716

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.