Integrating enriched case data from national laboratory testing with population-based case-control analyses: a novel statistical likelihood-ratio methodology for PS4 applied to 325,345 breast cancer cases and 671,006 controls
Abstract Background For many evidence criteria within v3.0 of the ACMG/AMP guidelines, methodologies have been developed to empower their use outside the stipulated evidence strengths. However, no such methodology has been established for case-control data (PS4). With the release of large-scale unselected case-control datasets and expansion of nationally-collected laboratory datasets enriched for pathogenic variant carriers, there is potential to combine datasets across ascertainment contexts in a more quantitative manner using novel likelihood ratio tools. Methods Using our published PS4-LR-Calculator, we calculated a combined log likelihood ratio (PS4-LLR) across five datasets (three unselected, and two enriched), and estimated enrichment of pathogenic variants in clinically-ascertained laboratory data using truncating variant prevalence. Results Data were combined for 10,817 missense variants from 325,345 female breast cancer patients and 671,006 controls of Western European ancestry for five breast cancer susceptibility genes ( BRCA1, BRCA2, PALB2, ATM, CHEK2 ). A combined LLR was produced for 4,690 missense variants; 927 variants received evidence towards pathogenicity (LLR≥ 1), and 3,242 received evidence towards benignity (LLR≤ -1). Conclusion This flexible, variant-level methodology combines nationally-collected ‘enriched’ datasets with unselected case-control cohorts, expanding the available information for case-control analysis, boosting power, enabling exploration of atypical penetrance and empowering variant classification.
Combining genotype with height-adjusted kidney length predicts rapid progression of ADPKD
ABSTRACT Introduction Our main objective was to identify baseline prognostic factors predictive of rapid disease progression in a large unselected clinical autosomal dominant polycystic kidney disease (ADPKD) cohort. Methods A cross-sectional analysis was performed in 618 consecutive ADPKD patients assessed and followed-up for over a decade. A total of 123 patients (19.9%) had reached kidney failure by the study date. Data were available for the following: baseline eGFR (n = 501), genotype (n = 549), baseline ultrasound mean kidney length (MKL, n = 424) and height-adjusted baseline MKL (HtMKL, n = 377). Rapid disease progression was defined as an annualized eGFR decline (∆eGFR) of >2.5 mL/min/year by linear regression over 5 years (n = 158). Patients were further divided into slow, rapid and very rapid ∆eGFR classes for analysis. Genotyped patients were classified into several categories: PKD1 (T, truncating; or NT, non-truncating), PKD2, other genes (non-PKD1 or -PKD2), no mutation detected or variants of uncertain significance. Results A PKD1-T genotype had the strongest influence on the probability of reduced baseline kidney function by age. A multivariate logistic regression model identified PKD1-T genotype and HtMKL (>9.5 cm/m) as independent predictors for rapid disease progression. The combination of both factors increased the positive predictive value for rapid disease progression over age 40 years and of reaching kidney failure by age 60 years to 100%. Exploratory analysis in a subgroup with available total kidney volumes showed higher positive predictive value (100% vs 80%) and negative predictive value (42% vs 33%) in predicting rapid disease progression compared with the Mayo Imaging Classification (1C–E). Conclusion Real-world longitudinal data confirm the importance of genotype and kidney length as independent variables determining ∆eGFR. Individuals with the highest risk of rapid disease progression can be positively selected for treatment based on this combination.