Evidence map›Paper›PMID 36481303›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2023

A concurrent dual analysis of genomic data augments diagnoses: Experiences of 2 clinical sites in the Undiagnosed Diseases Network.

Rebecca C Spillmann, Queenie K-G Tan, Chloe Reuter, Kelly Schoch, Undiagnosed Diseases Network, Jennefer Kohler, Devon Bonner, Diane Zastrow, Anna Alkelai, Evan Baugh and 6 more

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02450851 (Clinical and Genetic Evaluation of Patients With Undiagnosed Disorders Through the Undiagnosed Diseases Network), which is not on this map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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.

NCT02450851 recruitingnot on this map

Clinical and Genetic Evaluation of Patients With Undiagnosed Disorders Through the Undiagnosed Diseases Network

TypeobservationalSponsorNational Human Genome Research Institute (NHGRI)Ran2015 to 2028Enrolled20,000ConditionsGenetic Disease
3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Arriving at a diagnosis: Effective strategies used by the Undiagnosed Diseases Network.Genetics in medicine : official journal of the American College of Medical Genetics · 2026
    Article
  2. 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

16 authors.

Rebecca C SpillmannDivision of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, NC.
Queenie K-G TanDivision of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, NC.
Chloe ReuterStanford Center for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA; Stanford Center for Undiagnosed Diseases, Stanford University, and Department of Pediatrics, Stanford University School of Medicine, Stanford, CA.
Kelly SchochDivision of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, NC.
Undiagnosed Diseases Network
Jennefer KohlerStanford Center for Undiagnosed Diseases, Stanford University, and Department of Pediatrics, Stanford University School of Medicine, Stanford, CA.
Devon BonnerStanford Center for Undiagnosed Diseases, Stanford University, and Department of Pediatrics, Stanford University School of Medicine, Stanford, CA.
Diane ZastrowStanford Center for Undiagnosed Diseases, Stanford University, and Department of Pediatrics, Stanford University School of Medicine, Stanford, CA.
Anna AlkelaiInstitute for Genome Medicine, Columbia University Medical Center, New York, NY.
Evan BaughInstitute for Genome Medicine, Columbia University Medical Center, New York, NY.
Heidi CopeDivision of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, NC.
Shruti MarwahaStanford Center for Undiagnosed Diseases, Stanford University, and Department of Pediatrics, Stanford University School of Medicine, Stanford, CA.
Matthew T WheelerStanford Center for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA; Stanford Center for Undiagnosed Diseases, Stanford University, and Department of Pediatrics, Stanford University School of Medicine, Stanford, CA.
Jonathan A BernsteinStanford Center for Undiagnosed Diseases, Stanford University, and Department of Pediatrics, Stanford University School of Medicine, Stanford, CA.
Vandana ShashiDivision of Medical Genetics, Department of Pediatrics, Duke University School of Medicine, Durham, NC. Electronic address: vandana.shashi@duke.edu.
Undiagnosed Diseases Network

Funding

An integrated and diverse genomic medicine program for undiagnosed diseasesU01HG007672 · NHGRI · DUKE UNIVERSITY · PI SHASHI, VANDANA · 2014 to 2022
$13.4M
Clinical Sequencing Core Facility for the Undiagnosed Diseases Network (UDN)U01HG007942 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI ENG, CHRISTINE · 2014 to 2021
$10.2M
Stanford Center for Undiagnosed DiseasesU01HG007708 · NHGRI · STANFORD UNIVERSITY · PI ASHLEY, EUAN A, BERNSTEIN, JONATHAN ADAM · 2014 to 2018
$8.0M
Clinical Genome Wide Sequencing Core for the Undiagnosed Disease NetworkU01HG007943 · NHGRI · MEDICAL COLLEGE OF WISCONSIN · PI WORTHEY, ELIZABETH A · 2014 to 2017
$4.1M
C BRIGGSAE AND C ELEGANS GENOMIC SEQUENCE COMPARISONF32HG000130 · NHGRI · WASHINGTON UNIVERSITY · PI COUCH, JENNIFER A · 1994 to 1995
–
NHGRI NIH HHS F32 HG000130NHGRI NIH HHS U01 HG007672NHGRI NIH HHS U01 HG007708NHGRI NIH HHS U01 HG007942NHGRI NIH HHS U01 HG007943
6 · The paper itself

Abstract

purposeNext-generation sequencing (NGS) has revolutionized the diagnostic process for rare/ultrarare conditions. However, diagnosis rates differ between analytical pipelines. In the National Institutes of Health-Undiagnosed Diseases Network (UDN) study, each individual's NGS data are concurrently analyzed by the UDN sequencing core laboratory and the clinical sites. We examined the outcomes of this practice.

methodsA retrospective review was performed at 2 UDN clinical sites to compare the variants and diagnoses/candidate genes identified with the dual analyses of the NGS data.

resultsIn total, 95 individuals had 100 diagnoses/candidate genes. There was 59% concordance between the UDN sequencing core laboratories and the clinical sites in identifying diagnoses/candidate genes. The core laboratory provided more diagnoses, whereas the clinical sites prioritized more research variants/candidate genes (P < .001). The clinical sites solely identified 15% of the diagnoses/candidate genes. The differences between the 2 pipelines were more often because of variant prioritization disparities than variant detection.

conclusionThe unique dual analysis of NGS data in the UDN synergistically enhances outcomes. The core laboratory provided a clinical analysis with more diagnoses and the clinical sites prioritized more research variants/candidate genes. Implementing such concurrent dual analyses in other genomic research studies and clinical settings can improve both variant detection and prioritization.

Indexed as

Undiagnosed DiseasesGenomicsHigh-Throughput Nucleotide SequencingHumansLaboratoriesRare DiseasesUnited StatesDual analysisGenomic sequencingRare diseases

Identifiers

PMID36481303
PMCPMC10506157

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Registered trials

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.