Evidence map›Paper›PMID 39265286›Full record

ArticleMolecular genetics and metabolism

Developing a scoring system for gene curation prioritization in lysosomal diseases.

Matheus Vernet Machado Bressan Wilke, Jennifer Goldstein, Emily Groopman, Shruthi Mohan, Amber Waddell, Raquel Fernandez, Hongjie Chen, Deeksha Bali, Heather Baudet, Lorne Clarke and 5 more

Abstract read
In one paragraph

Article in Molecular genetics and metabolism. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Matheus Vernet Machado Bressan WilkeDepartment of Pathology and Immunology, Washington University in St. Louis, MO, United States of America.
Jennifer GoldsteinUniversity of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America.
Emily GroopmanChildren's National Hospital, Washington, DC, United States of America.
Shruthi MohanUniversity of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America.
Amber WaddellUniversity of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America.
Raquel FernandezAmerican College of Genetics and Genomics, Bethesda, MD, United States of America.
Hongjie ChenPrevention Genetics, part of Exact Sciences, Marshfield, WI, United States of America.
Deeksha BaliDuke University Health System, Durham, NC, United States of America.
Heather BaudetUniversity of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America.
Lorne ClarkeUniversity of British Columbia, Vancouver, Canada.
Christina HungInvitae, San Francisco, CA, United States of America.
Rong MaoARUP Laboratories, Salt Lake City, UT, United States of America; University of Utah, Salt Lake City, UT, United States of America.
Tatiana YuzyukARUP Laboratories, Salt Lake City, UT, United States of America; University of Utah, Salt Lake City, UT, United States of America.
William J CraigenBaylor College of Medicine, Houston, TX, United States of America.
Filippo Pinto E VairoCenter for Individualized Medicine, Mayo Clinic, Rochester, MN, United States of America; Department of Clinical Genomics, Mayo Clinic, Rochester, MN, United States of America. Electronic address: vairo.filippo@mayo.edu.

Funding

Baylor College of Medicine/Stanford University Clinical Genome Resource (CLINGEN)U24HG009649 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI TERI Ellen KLEIN, Aleksandar Milosavljevic · 2021 to 2026
$31.5M
The Clinical Genome Resource – Advancing genomic medicine through biocuration and expert assessment of genes and variants at scaleU24HG009650 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI JONATHAN S BERG, Jessica Ezzell Hunter · 2021 to 2026
$30.0M
NHGRI NIH HHS U24 HG009649NHGRI NIH HHS U24 HG009650
6 · The paper itself

Abstract

introductionDiseases caused by lysosomal dysfunction often exhibit multisystemic involvement, resulting in substantial morbidity and mortality. Ensuring accurate diagnoses for individuals with lysosomal diseases (LD) is of great importance, especially with the increasing prominence of genetic testing as a primary diagnostic method. As the list of genes associated with LD continues to expand due to the use of more comprehensive tests such as exome and genome sequencing, it is imperative to understand the clinical validity of the genes, as well as identify appropriate genes for inclusion in multi-gene testing and sequencing panels. The Clinical Genome Resource (ClinGen) works to determine the clinical importance of genes and variants to support precision medicine. As part of this work, ClinGen has developed a semi-quantitative framework to assess the strength of evidence for the role of a gene in a disease. Given the diversity in gene composition across LD panels offered by various laboratories and the evolving comprehension of genetic variants affecting secondary lysosomal functions, we developed a scoring system to define LD (Lysosomal Disease Scoring System - LDSS). This system sought to aid in the prioritization of genes for clinical validity curation and assess their suitability for LD-targeted sequencing panels.

methodsThrough literature review encompassing terms associated with both classically designated LD and LFRD, we identified 14 criteria grouped into "Overall Definition," "Phenotype," and "Pathophysiology." These criteria included concepts such as the "accumulation of undigested or partially digested macromolecules within the lysosome" and being "associated with a wide spectrum of clinical manifestations impacting multiple organs and systems." The criteria, along with their respective weighted values, underwent refinement through expert panel evaluation differentiating them between "major" and "minor" criteria. Subsequently, the LDSS underwent validation on 12 widely acknowledged LD and was later tested by applying these criteria to the Lysosomal Disease Network's (LDN) official Gene List.

resultsThe final LDSS comprised 4 major criteria and 10 minor criteria, with a cutoff of 2 major or 1 major and 3 minor criteria established to define LD. Interestingly, when applied to both the LDN list and a comprehensive gene list encompassing genes included in clinical panels and published as LFRD genes, we identified four genes (GRN, SLC29A3, CLN7 and VPS33A) absent from the LDN list, that were deemed associated with LD. Conversely, a subset of non-classic genes included in the LDN list, such as MTOR, OCRL, and SLC9A6, received lower LDSS scores for their associated disease entities. While these genes may not be suitable for inclusion in clinical LD multi-gene panels, they could be considered for inclusion on other, non-LD gene panels. DISCUSSION: The LDSS offers a systematic approach to prioritize genes for clinical validity assessment. By identifying genes with high scores on the LDSS, this method enhanced the efficiency of gene curation by the ClinGen LD GCEP.

conclusionThe LDSS not only serves as a tool for gene prioritization prior to clinical validity curation, but also contributes to the ongoing discussion on the definition of LD. Moreover, the LDSS provides a flexible framework adaptable to future discoveries, ensuring its relevance in the ever-expanding landscape of LD research.

Indexed as

Genetic TestingLysosomal Storage DiseasesDatabases, GeneticGenetic Predisposition to DiseaseHumansLysosomesClinGenGeneticsLysosomal diseasesLysosomal storage diseases

Identifiers

PMID39265286
PMCPMC11473227

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