Evidence map›Paper›PMID 40225944›Full record

ArticleHuman mutation2024

Beyond Single Diagnosis: Exploring Multidiagnostic Realities in Pediatric Patients through Genome Sequencing.

Fen Guo, Ruby Liu, Yinghong Pan, Mary Colasanto, Christin Collins, Madhuri Hegde

Abstract read
In one paragraph

Article in Human mutation, 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

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

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

6 authors.

Fen GuoRevvity Omics, Pittsburgh, Pennsylvania, USA.ORCID 0000-0003-1847-6317
Ruby LiuRevvity Omics, Pittsburgh, Pennsylvania, USA.
Yinghong PanRevvity Omics, Pittsburgh, Pennsylvania, USA.ORCID 0000-0001-7334-1787
Mary ColasantoRevvity Omics, Pittsburgh, Pennsylvania, USA.
Christin CollinsRevvity Omics, Pittsburgh, Pennsylvania, USA.
Madhuri HegdeRevvity Omics, Pittsburgh, Pennsylvania, USA.ORCID 0000-0002-4500-0368

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advancements in the next-generation sequencing have illuminated the occurrence of multiple genetic diagnoses (MGD). While exome sequencing has provided insights, genome sequencing (GS), the most comprehensive diagnostic tool, remains underexplored for studying MGD prevalence. We retrospectively analyzed 1487 pediatric cases from our laboratory, employing GS to investigate the incidence of single definitive genetic diagnosis (SDD) and MGD in children suspected of having a genetic disease. Of these patients, 273 received at least one definitive diagnosis, including 245 with SDD (16.5%) and 28 with MGD (1.9%). Diagnostic yield was consistent across genders and unaffected by previous testing in SDD cases. Notably, prior testing significantly increased the diagnostic yield in MGD cases to 2.7% overall and 14.4% among diagnosed cases, compared to 1.1% for those with GS as a first-tier test. Age was a significant factor in diagnostic outcome for both SDD and MGD cases with neonates showing the highest diagnostic yield of 24.5% in SDD and a notably higher yield in MGD at 4.9%, representing 16.7% of the diagnosed cases. Of the 28 MGD cases, 17 exhibited distinct phenotypes, 9 had overlapping features, and 2 presented a mix, underscoring the genetic and phenotypic heterogeneity within this group. This study is the first to exclusively use GS to assess MGD prevalence. Our findings highlight the complexity of rare diseases and emphasize the importance of comprehensive, genome-level diagnostics. Clinicians must ensure that diagnoses fully account for the observed phenotypes to inform optimal therapeutic strategies and management.

Indexed as

Genetic Diseases, InbornGenetic TestingWhole Genome SequencingAdolescentChildChild, PreschoolFemaleGenome, HumanHigh-Throughput Nucleotide SequencingHumansInfantInfant, NewbornMalePhenotypeRetrospective Studies

Identifiers

PMID40225944
PMCPMC11919036

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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.