Evidence map›Paper›PMID 33879512›Full record

ArticleJournal of medical genetics2022

Personalised virtual gene panels reduce interpretation workload and maintain diagnostic rates of proband-only clinical exome sequencing for rare disorders.

Leslie Patricia Molina-Ramírez, Claire Kyle, Jamie M Ellingford, Ronnie Wright, Algy Taylor, Sanjeev S Bhaskar, Christopher Campbell, Harriet Jackson, Adele Fairclough, Abigail Rousseau and 18 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of medical genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
7.6field-weighted citation impact, top 2% 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

24 citing papers in PubMed, 44 citations in OpenAlex.

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  12. PANGEN: an online platform for the comparison and creation of diagnostic gene panels.Database : the journal of biological databases and curation · 2024
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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

28 authors at 3 institutions in 1 country.

Leslie Patricia Molina-RamírezDivision of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.ORCID 0000-0001-7573-6846
Claire KyleNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.
Jamie M EllingfordDivision of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.ORCID 0000-0003-1137-9768
Ronnie WrightNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.
Algy TaylorNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.
Sanjeev S BhaskarNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.
Christopher CampbellNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.
Harriet JacksonNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.
Adele FaircloughNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.
Abigail RousseauNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.
George J BurghelNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.ORCID 0000-0001-9360-8194
Laura DuttonNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.
Siddharth BankaDivision of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.ORCID 0000-0002-8527-2210
Tracy A BriggsDivision of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
Jill Clayton-SmithDivision of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
Sofia DouzgouDivision of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.ORCID 0000-0001-8890-7544
Elizabeth A JonesDivision of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
Helen M KingstonNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.
Bronwyn KerrNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.
John EalingManchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, UK.
Suresh SomarathiNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.
Kate E ChandlerDivision of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
Helen M StuartDivision of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
Emma Mm Burkitt-WrightDivision of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
William G NewmanDivision of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
Iain A BruceDivision of Infection, Immunity and Respiratory Medicine, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
Graeme C BlackDivision of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK graeme.black@manchester.ac.uk.
David GokhaleNorth West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, Greater Manchester, UK.
Manchester University NHS Foundation Trust · GBUniversity of Manchester · GBSalford Royal NHS Foundation Trust · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

purposeThe increased adoption of genomic strategies in the clinic makes it imperative for diagnostic laboratories to improve the efficiency of variant interpretation. Clinical exome sequencing (CES) is becoming a valuable diagnostic tool, capable of meeting the diagnostic demand imposed by the vast array of different rare monogenic disorders. We have assessed a clinician-led and phenotype-based approach for virtual gene panel generation for analysis of targeted CES in patients with rare disease in a single institution.

methodsRetrospective survey of 400 consecutive cases presumed by clinicians to have rare monogenic disorders, referred on singleton basis for targeted CES. We evaluated diagnostic yield and variant workload to characterise the usefulness of a clinician-led approach for generation of virtual gene panels that can incorporate up to three different phenotype-driven gene selection methods.

resultsAbnormalities of the nervous system (54.5%), including intellectual disability, head and neck (19%), skeletal system (16%), ear (15%) and eye (15%) were the most common clinical features reported in referrals. Combined phenotype-driven strategies for virtual gene panel generation were used in 57% of cases. On average, 7.3 variants (median=5) per case were retained for clinical interpretation. The overall diagnostic rate of proband-only CES using personalised phenotype-driven virtual gene panels was 24%.

conclusionsOur results show that personalised virtual gene panels are a cost-effective approach for variant analysis of CES, maintaining diagnostic yield and optimising the use of resources for clinical genomic sequencing in the clinic.

Indexed as

ExomeRare DiseasesExome SequencingHumansRetrospective StudiesWorkloadearly diagnosisgeneticsgenomicsmedical

Identifiers

PMID33879512
PMCPMC8961756
OpenAlexW3152698247

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.