{
  "abstract": "Introduction Penetrance estimates derived from clinical cohorts are often affected by ascertainment bias, as these populations typically comprise individuals or families presenting with disease prior to genetic testing. While informative for counselling affected families, such estimates may be misleading when applied to secondary findings or newborn screening (NBS) in asymptomatic individuals without relevant family history. Population-based cohorts, despite their own biases (e.g. survivor and healthy volunteer bias), offer an opportunity to assess penetrance in a broader context.Methods We examined penetrance across >10 gene-condition pairs in the UK Biobank (N~500,000 with whole genome sequencing), comparing results to existing literature.Results We highlighted key challenges, categorised into variant calling, variant classification, and phenotype definition. Inadequate variant curation — including the inclusion of common, misclassified, or mechanism-incompatible variants — can drastically alter penetrance estimates. For example, misclassified variants led to a 0% penetrance estimate for maturity-onset diabetes of the young in UK Biobank, revised to 64% following expert review. Additionally, difficulties in defining clinically relevant phenotypes and coding errors, particularly in rare diseases, further complicate interpretation.Discussion Rigorous curation and phenotype validation are essential to producing reliable penetrance estimates in population cohorts, with important implications for genomic NBS and genetic counselling.",
  "authors": [
    {
      "affiliations": [
        "University of Exeter Medical School"
      ],
      "name": "Leigh Jackson"
    },
    {
      "affiliations": [
        "University of Exeter Medical School"
      ],
      "name": "James Fasham"
    },
    {
      "affiliations": [
        "University of Exeter Medical School"
      ],
      "name": "Daisy Brooke"
    },
    {
      "affiliations": [
        "University of Exeter Medical School"
      ],
      "name": "Kashyap A Patel"
    },
    {
      "affiliations": [
        "University of Exeter Medical School"
      ],
      "name": "Michael N Weedon"
    },
    {
      "affiliations": [
        "University of Exeter Medical School"
      ],
      "name": "Caroline F Wright"
    }
  ],
  "title": "O5 Lessons from population cohorts regarding penetrance",
  "uid": "a244501b-77ae-5dec-ad60-9afd0b2976d5"
}