Penetrance refers to the probability that a specific allele or alleles will exhibit any phenotypic expression (Forrest et al., 2022). Some pathogenic variants are fully penetrant, meaning that those who harbor them always develop a specific associated trait. For other variants, penetrance is incomplete, leading to a group of people who carry such variants remaining unaffected lifelong. Penetrance gives meaningful and measurable information in population screening and prenatal diagnosis (Spargo et al., 2022). Penetrance is also crucial to American College of Medical Genetics and Genomics Secondary Findings (ACMG SFs), which are actively sought out genetic variants but unrelated to the clinical indication for genetic testing and can therefore be considered as opportunistic genetic screening, research in penetrance can accelerate the application of ACMG SFs in clinical practice (McGurk et al., 2023).

ClinVar is a widely used resource for variant pathogenicity classification (Landrum et al., 2014, 2016), with most variants classified as uncertain significance, along with low-confidence classifications for pathogenic/likely pathogenic (P/LP) and benign/likely benign (B/LB). Furthermore, P/LP variants classified through ClinVar might have overestimated pathogenicity, and many P/LP variants have been downgraded to a low disease risk (Forrest et al., 2022). As a result, there is a need to accurately assess a variant's disease risk by incorporating variant penetrance.

Penetrance is scattered across thousands of studies, making it inconvenient for geneticists and clinicians to obtain and integrate. Therefore, it is urgently needed to develop an integrated platform for penetrance to cater to the needs of geneticists and clinicians.

Here, we developed PenCards, a user-friendly platform that consolidates all available penetrance data for searching, browsing, and analyzing, while providing a streamlined submission portal for users worldwide to share their genetic data for the continuous update of penetrance (Fig. 1). We manually curated penetrance from 5347 published studies and used a Bayesian method to calculate the penetrance of autism-related genes based on the large international cohorts Simons Foundation Powering Autism Research for Knowledge (SPARK) and UK Biobank (UKB). We then integrated this data into PenCards, which currently contains 244,531 variants, including 239,244 single nucleotide variants (SNVs), 4994 insertions and deletions (Indels), and 293 copy number variants (CNVs), making it a platform that comprehensively aggregates penetrance. Additionally, we integrated other genomic sources to provide comprehensive variant-level and gene-level annotations, including (i) functional effects; (ii) in silico prediction scores covering all potential variants, such as non-synonymous substitutions, non-canonical splicing variants, and non-coding variations; (iii) allele frequencies in different populations; (iv) disease- and phenotype-related information; (v) general meaningful gene-level information; and (vi) drug-gene interactions. PenCards offers a user-friendly interface for searching specific variants of interest and analyzing next-generation sequencing (NGS) data to screen for potential high-risk pathogenic variants using integrated information.