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Purpose: Research is underway worldwide to investigate the feasibility, acceptability, and utility of sequencing-based newborn screening. Different methods have been used to select gene-condition pairs for screening, leading to highly inconsistent gene lists across studies.
Methods: Early Check developed and utilized actionability-based frameworks for evaluating gene-condition pairs for inclusion in newborn panels (panel 1-high actionability, panel 2-possible actionability). A previously developed framework, the Age-based Semi Quantitative Metric (ASQM), was adapted. Increasing ASQM scores, with a maximum of 15, suggest greater actionability. Wilcoxon tests were performed to compare panel 1 gene-condition pairs on the Recommended Uniform Screening Panel (RUSP) with non-RUSP pairs.
Results: In our first round of assessment, Early Check identified 178 gene-condition pairs for inclusion in panel 1 and 29 for panel 2. Median ASQM scores of RUSP conditions on panel 1 was 12 (range 4 to 15) and non-RUSP was 13 (range 9 to 15). Median scores for panel 2 was 10 (range 6 to 14).
Conclusion: The Early Check frameworks provide a transparent, semiquantitative, and reproducible methodology for selecting gene-condition pairs for newborn screening sequencing pilot studies that may inform future integration of genomic sequencing into population-level newborn screening. Collaborative efforts among newborn sequencing studies to establish shared criteria is needed to enhance cross-study comparisons.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11625596 | PMC |
http://dx.doi.org/10.1016/j.gim.2024.101290 | DOI Listing |
Genet Med
January 2025
The Clinical Genome Resource (ClinGen) is a National Institutes of Health-funded program founded 10 years ago that defines the clinical relevance of genes and variants for medical and research use. ClinGen working groups develop standards for data sharing and curating genomic knowledge. Expert panels, with >2500 active members from 67 countries, curate the validity of monogenic disease relationships, pathogenicity of genetic variation, dosage sensitivity of genes, and actionability of gene-disease interventions using ClinGen standards, infrastructure, and curation interfaces.
View Article and Find Full Text PDFGenet Med
December 2024
GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC.
Purpose: Research is underway worldwide to investigate the feasibility, acceptability, and utility of sequencing-based newborn screening. Different methods have been used to select gene-condition pairs for screening, leading to highly inconsistent gene lists across studies.
Methods: Early Check developed and utilized actionability-based frameworks for evaluating gene-condition pairs for inclusion in newborn panels (panel 1-high actionability, panel 2-possible actionability).
Genet Med
August 2024
Genomics, Ethics, and Translational Research Program, RTI International, Research Triangle Park, NC.
Genet Med
June 2022
Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC.
Purpose: Synthesis and curation of evidence regarding the clinical actionability of secondary findings (SFs) from genome-scale sequencing are needed to support decision-making on reporting of these findings. To assess actionability of SFs in children and adolescents, the Clinical Genome Resource established the Pediatric Actionability Working Group (AWG).
Methods: The Pediatric AWG modified the framework of the existing Adult AWG, which included production of summary reports of actionability for genes and associated conditions and consensus actionability scores for specific outcome-intervention pairs.
Mol Syst Biol
December 2019
European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
Loss-of-function (LoF) mutations associated with disease do not manifest equally in different individuals. The impact of the genetic background on the consequences of LoF mutations remains poorly characterized. Here, we systematically assessed the changes in gene deletion phenotypes for 3,786 gene knockouts in four Saccharomyces cerevisiae strains and 38 conditions.
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