Show Notes
Sapp JC et al., The American Journal of Human Genetics - A longitudinal study of recipients of medically actionable secondary genomic findings develops a Bayesian approach that integrates variant, family genotypic, and phenotypic data to estimate the probability that a secondary finding represents a true clinicomolecular diagnosis, with a detailed analysis of BRCA1/BRCA2 families and implications for screening policy and clinical management. Key terms: secondary findings, BRCA1, BRCA2, Bayesian risk assessment, population genomic screening.
Study Highlights:
The team enrolled 227 secondary findings recipients and completed genotyping and deep phenotyping for 163 probands, using cascade testing and variant reclassification. They piloted a Bayesian method combining prior population prevalence, variant pathogenicity, and family genotype–phenotype data to estimate clinicomolecular diagnosis (CMD) probabilities for BRCA1/2 families. CMD probabilities varied widely (26.2% to >99.9%) and over half of BRCA1/2 families met NCCN diagnostic testing criteria, indicating underuse of diagnostic testing.
Conclusion:
In opportunistic secondary findings contexts the posterior probability that a patient has the implicated monogenic disease can differ substantially from variant pathogenicity; integrating familial genotypic and phenotypic data via Bayesian methods refines risk estimates and should guide shared decision-making, management strategies, and policy for population genomic screening.
Music:
Enjoy the music based on this article at the end of the episode.
Article title:
Measuring disease likelihood in genomic ascertainment
First author:
Sapp JC
Journal:
The American Journal of Human Genetics
DOI:
10.1016/j.ajhg.2026.03.009
Reference:
Sapp JC, Lewis KL, Modlin EW, et al. Measuring disease likelihood in genomic ascertainment. The American Journal of Human Genetics. 2026;113:1–12. doi:10.1016/j.ajhg.2026.03.009
License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/
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Episode link: https://basebybase.com/episodes/measuring-disease-likelihood-genomic-ascertainment
QC:
This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-04-07.
QC Scope:
- article metadata and core scientific claims from the narration
- excludes analogies, intro/outro, and music
- transcript coverage: Audited transcript sections describing the Bayesian CMD approach, the BRCA1/BRCA2 findings, the Family 8334 case, NCCN criteria implications, and study design/limitations.
- transcript topics: ACMG secondary findings context and selection bias; Bayesian probability model for CMD; Cascade testing and family data integration; BRCA1 vs BRCA2 variant distribution and penetrance; NCCN criteria and clinical testing underutilization; Study design and recruitment (163 probands from 41 sources)
QC Summary:
- factual score: 10/10
- metadata score: 10/10
- supported core claims: 5
- claims flagged for review: 0
- metadata checks passed: 4
- metadata issues found: 0
Metadata Audited:
- article_doi
- article_title
- article_journal
- license
Factual Items Audited:
- CMD probability range across BRCA1/BRCA2 families: 26.2% to 100%
- Baseline posterior probability for BRCA2-related CMD: 58.2%
- Posterior CMD probability for family 8334: 99.2%
- Average CMD probability across BRCA1/BRCA2 families: 86.9%
- BRCA2 variants comprised 83% and BRCA1 17% of BRCA1/BRCA2 findings
- 51% of BRCA1/BRCA2 families met NCCN diagnostic testing criteria
QC result: Pass.
