Evidence map›Paper›PMID 40684348›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2025

Assessment of the variant prioritization strategy for genomic newborn screening in the Generation Study.

Joanna Kaplanis, Dasha Deen, Prasanth Sivakumar, Mafalda de Almeida Gomes, Arina Puzriakova, Ivone Leong, Kevin Savage, Gabriel Aldam, James Skelton, Paul Quinn and 10 more

Abstract read
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

20 authors.

Joanna KaplanisGenomics England, London, United Kingdom.
Dasha DeenGenomics England, London, United Kingdom.
Prasanth SivakumarGenomics England, London, United Kingdom.
Mafalda de Almeida GomesGenomics England, London, United Kingdom.
Arina PuzriakovaGenomics England, London, United Kingdom.
Ivone LeongGenomics England, London, United Kingdom.
Kevin SavageGenomics England, London, United Kingdom.
Gabriel AldamGenomics England, London, United Kingdom.
James SkeltonGenomics England, London, United Kingdom.
Paul QuinnGenomics England, London, United Kingdom.
Andrew ParrishGenomics Laboratory, Royal Devon and Exeter NHS Foundation Trust, Exeter, United Kingdom; South West Genomic Medicine Service, England, United Kingdom.
Emma BapleSouth West Genomic Medicine Service, England, United Kingdom; Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, United Kingdom; Peninsula Clinical Genetics Service, Exeter, United Kingdom.
Meekai ToGenomics England, London, United Kingdom; Harris Birthright Centre, King's College Hospital, London, United Kingdom.
Katrina StoneGenomics England, London, United Kingdom; Clinical Genetics Department, Great Ormond Street Hospital for Children, London, United Kingdom.
David BickGenomics England, London, United Kingdom.
Amanda PichiniGenomics England, London, United Kingdom.
Alice Tuff-LaceyGenomics England, London, United Kingdom.
Richard ScottGenomics England, London, United Kingdom; Clinical Genetics Department, Great Ormond Street Hospital for Children, London, United Kingdom; Genetics and Genomic Medicine Department, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.
Ellen ThomasGenomics England, London, United Kingdom.
Dalia KasperaviciuteGenomics England, London, United Kingdom. Electronic address: dalia.kasperaviciute@genomicsengland.co.uk.

Funding

Medical Research Council MR/X021351/1
6 · The paper itself

Abstract

purposeGenomic sequencing offers the opportunity to screen for hundreds of rare genetic conditions. To minimize potential negative impact on families and clinical services, it is crucial to reduce false-positive results while prioritizing clinical utility. We present an automated variant prioritization approach in the Generation Study, a research study investigating genomic sequencing in 100,000 newborns in England. Prioritized variants will subsequently undergo manual review by a registered clinical scientist and a specialist clinician before being reported back to parents.

methodsWe assessed specificity of our automated variant prioritization approach in 34,410 samples not enriched for rare diseases and sensitivity in 546 samples from patients with diagnostic variants in genes relevant to newborn screening. We used coverage and copy-number variants callability metrics to evaluate variant detection.

resultsWe estimated that 3% to 5% of samples will have prioritized variants that require manual review and that <1% of cases will have reportable variants requiring further confirmation of the condition. Sensitivity in genes included in the Generation Study was estimated to be approximately 80%. Gene-level specificity results led to changes in variant prioritization rules and conditions that are included.

conclusionGene-specific assessment of variant prioritization is crucial to establish analytical validity prior to inclusion in genomic newborn screening.

Indexed as

Genetic TestingGenomicsNeonatal ScreeningDNA Copy Number VariationsEnglandGenetic VariationHigh-Throughput Nucleotide SequencingHumansInfant, NewbornAnalytical validityGenome sequencingNewborn screeningRare diseaseVariant prioritization

Identifiers

PMID40684348
PMCPMC12714140

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.