Comparative analysis of functional assay evidence use by ClinGen Variant Curation Expert Panels.

BACKGROUND: The 2015 American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) guidelines for clinical sequence variant interpretation state that "well-established" functional studies can be used as evidence in variant classification. These guidelines articulated key attributes of functional data, including that assays should reflect the biological environment and be analytically sound; however, details of how to evaluate these attributes were left to expert judgment. The Clinical Genome Resource (ClinGen) designates Variant Curation Expert Panels (VCEPs) in specific disease areas to make gene-centric specifications to the ACMG/AMP guidelines, including more specific definitions of appropriate functional assays. We set out to evaluate the existing VCEP guidelines for functional assays. METHODS: We evaluated the functional criteria (PS3/BS3) of six VCEPs (CDH1, Hearing Loss, Inherited Cardiomyopathy-MYH7, PAH, PTEN, RASopathy). We then established criteria for evaluating functional studies based on disease mechanism, general class of assay, and the characteristics of specific assay instances described in the primary literature. Using these criteria, we extensively curated assay instances cited by each VCEP in their pilot variant classification to analyze VCEP recommendations and their use in the interpretation of functional studies. RESULTS: Unsurprisingly, our analysis highlighted the breadth of VCEP-approved assays, reflecting the diversity of disease mechanisms among VCEPs. We also noted substantial variability between VCEPs in the method used to select these assays and in the approach used to specify strength modifications, as well as differences in suggested validation parameters. Importantly, we observed discrepancies between the parameters VCEPs specified as required for approved assay instances and the fulfillment of these requirements in the individual assays cited in pilot variant interpretation. CONCLUSIONS: Interpretation of the intricacies of functional assays often requires expert-level knowledge of the gene and disease, and current VCEP recommendations for functional assay evidence are a useful tool to improve the accessibility of functional data by providing a starting point for curators to identify approved functional assays and key metrics. However, our analysis suggests that further guidance is needed to standardize this process and ensure consistency in the application of functional evidence.

Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework.

BACKGROUND: The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) clinical variant interpretation guidelines established criteria for different types of evidence. This includes the strong evidence codes PS3 and BS3 for "well-established" functional assays demonstrating a variant has abnormal or normal gene/protein function, respectively. However, they did not provide detailed guidance on how functional evidence should be evaluated, and differences in the application of the PS3/BS3 codes are a contributor to variant interpretation discordance between laboratories. This recommendation seeks to provide a more structured approach to the assessment of functional assays for variant interpretation and guidance on the use of various levels of strength based on assay validation. METHODS: The Clinical Genome Resource (ClinGen) Sequence Variant Interpretation (SVI) Working Group used curated functional evidence from ClinGen Variant Curation Expert Panel-developed rule specifications and expert opinions to refine the PS3/BS3 criteria over multiple in-person and virtual meetings. We estimated the odds of pathogenicity for assays using various numbers of variant controls to determine the minimum controls required to reach moderate level evidence. Feedback from the ClinGen Steering Committee and outside experts were incorporated into the recommendations at multiple stages of development. RESULTS: The SVI Working Group developed recommendations for evaluators regarding the assessment of the clinical validity of functional data and a four-step provisional framework to determine the appropriate strength of evidence that can be applied in clinical variant interpretation. These steps are as follows: (1) define the disease mechanism, (2) evaluate the applicability of general classes of assays used in the field, (3) evaluate the validity of specific instances of assays, and (4) apply evidence to individual variant interpretation. We found that a minimum of 11 total pathogenic and benign variant controls are required to reach moderate-level evidence in the absence of rigorous statistical analysis. CONCLUSIONS: The recommendations and approach to functional evidence evaluation described here should help clarify the clinical variant interpretation process for functional assays. Further, we hope that these recommendations will help develop productive partnerships with basic scientists who have developed functional assays that are useful for interrogating the function of a variety of genes.

Comparative genome analysis of ciprofloxacin-resistant Pseudomonas aeruginosa reveals genes within newly identified high variability regions associated with drug resistance development.

The alarming rise of ciprofloxacin-resistant Pseudomonas aeruginosa has been reported in several clinical studies. Though the mutation of resistance genes and their role in drug resistance has been researched, the process by which the bacterium acquires high-level resistance is still not well understood. How does the genomic evolution of P. aeruginosa affect resistance development? Could the exposure of antibiotics to the bacteria enrich genomic variants that lead to the development of resistance, and if so, how are these variants distributed through the genome? To answer these questions, we performed 454 pyrosequencing and a whole genome analysis both before and after exposure to ciprofloxacin. The comparative sequence data revealed 93 unique resistance strain variation sites, which included a mutation in the DNA gyrase subunit A gene. We generated variation-distribution maps comparing the wild and resistant types, and isolated 19 candidates from three discrete resistance-associated high variability regions that had available transposon mutants, to perform a ciprofloxacin exposure assay. Of these region candidates with transposon disruptions, 79% (15/19) showed a reduction in the ability to gain high-level resistance, suggesting that genes within these high variability regions might enrich for certain functions associated with resistance development.