The PS4-likelihood ratio calculator: flexible allocation of evidence weighting for case-control data in variant classification
Year: 2024
Type: article
Abstract: BACKGROUND: The 2015 American College of Medical Genetics/Association of Molecular Pathology (ACMG/AMP) variant classification framework specifies that case-control observations can be scored as 'strong' evidence (PS4) towards pathogenicity. METHODS: We developed the PS4-likelihood ratio calculator (PS4-LRCalc) for quantitative evidence assignment based on the observed variant frequencies in cases and controls. Binomial likelihoods are computed for two models, each defined by prespecified OR thresholds. Model 1 represents the hypothesis of association between variant and phenotype (eg, OR≥5) and model 2 represents the hypothesis of non-association (eg, OR≤1). RESULTS: PS4-LRCalc enables continuous quantitation of evidence for variant classification expressed as a likelihood ratio (LR), which can be log-converted into log LR (evidence points). Using PS4-LRCalc, observed data can be used to quantify evidence towards either pathogenicity or benignity. Variants can also be evaluated against models of different penetrance. The approach is applicable to balanced data sets generated for more common phenotypes and smaller data sets more typical in very rare disease variant evaluation. CONCLUSION: PS4-LRCalc enables flexible evidence quantitation on a continuous scale for observed case-control data. The converted LR is amenable to incorporation into the now widely used 2018 updated Bayesian ACMG/AMP framework.
Source: Journal of Medical Genetics
Authors: Charlie F. Rowlands, Alice Garrett, Sophie Allen, Miranda Durkie, George J. Burghel, Rachel Robinson, Alison Callaway, Joanne Field, Bethan Frugtniet, Sheila Palmer-Smith, Jonathan Grant, Judith Pagan, Trudi McDevitt, Terri McVeigh, Helen Hanson, Nicola Whiffin, Michael Jones, Clare Turnbull, CanVIG-UK
Institutions: Institute of Cancer Research, St George’s University Hospitals NHS Foundation Trust, Sheffield Children's NHS Foundation Trust, Sheffield Children's Hospital, Manchester University NHS Foundation Trust, Leeds Teaching Hospitals NHS Trust, University Hospital Southampton NHS Foundation Trust, Nottingham University Hospitals NHS Trust, Cardiff and Vale University Health Board, University Hospital of Wales, NHS Greater Glasgow and Clyde, Queen Elizabeth University Hospital, Western General Hospital, Children's Health Ireland at Crumlin, Royal Marsden NHS Foundation Trust, University of Exeter, Royal Devon University Healthcare NHS Foundation Trust, Broad Institute, University of Oxford, Massachusetts Institute of Technology
Language: English
Topic: Genomics and Rare Diseases
Subfield: Genetics
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4402191257