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Genomic Ascertainment - Molecular and Genetic Aspects

$801,371ZIAFY2023HGNIH

National Human Genome Research Institute

Investigators

Linked publications & trials

Abstract

Infrastructure for the TGAC Project TGAC is The Genomic Ascertainment Cohort, a project to build capacity for genomic ascertainment research. A phase I cohort of 9,000 individuals has been entered into the study including ClinSeq participants, NIAID sequencing initiative participants, and Inova Hospital participants is now available to all NIH investigators at https://tgac.nhgri.nih.gov. Soon the nearly 5,000 NIEHS environmental polymorphism registry participants will be added. All of these individuals genomic data are available on the browser for viewing by intramural researchers. Then, they can apply to have us or their clinical team pursue phenotyping to test the hypothesis as to whether there is a phenotype associated with a given variant. We have already completed or have in process 20 such studies for intramural investigators. Two have been published or are in press. Based on its success, we have transferred this activity to become its own core facility within CPHR called the Reverse Phenotyping Core. Genomic Services Research Protocol (GSRP) A second activity of this project is the Genomic Services Research Protocol (GSRP). In this study, we are ascertaining individuals with secondary findings in one of the American College of Medical Genetics 59 gene secondary findings list. We have developed agreements or agreements in principle with 20 diagnostic laboratories that return secondary findings who refer patients to our study for evaluation. We intake individual and family histories and phenotypic evaluations. We supplement that by inviting selected participants to the NIHCC for deep phenotyping. We also perform molecular cascade testing to identify affected family members. Predictive genomic medicine or precision genomic medicine is of the highest medical importance and is an active area of research. We began piloting the return of genome-wide rare variants with the inception of the ClinSeq program in 2006, well before exome and genome sequencing became widespread (Biesecker et al., Genome Res 2009). We have continually expanded our work in this area by searching the genome for high penetrance variants that could be useful for clinical care, reproductive risks, pharmacogenetics, and other uses. My vision is that the genome is a health care resource, not a test, and that the cost of this health care resource can be amortized over the lifetime of an individual, long after its primary indicated usage is accomplished. Genomic medicine has at its foundation prediction - predicting phenotype based on genotype. To address this foundational challenge, we need to develop research modes that can model and test the predictive power of genomic variants. Resources such as gnomAD provide critical data on population prevalence but are seriously limited with respect to phenotype data. The UK BioBank is supporting genotype ascertainment, but its data are limited to pre-hoc phenotypes and blood samples and participants cannot be re-contacted. There is thus a compelling need for the capacity to perform bespoke phenotyping based on genotypes. A spinoff opportunity from my CSER activities is the realm of variant interpretation, which is one of the main bottlenecks limiting the utility of exome and genome sequencing. We have developed a philosophy or approach that variant interpretation must be improved by orders of magnitude with respect to speed and cost, in order for the benefits of rare variant predictive medicine to be realized. To accomplish this, I have stepped up to co-chair the Sequence Variant Interpretation (SVI) working group of the ClinGen consortium. The primary function of the SVI working group was to clarify and refine the original ACMG/AMP pathogenicity criteria (Richards et al., Genet Med 2015). But we have, in addition, developed much larger goals which is to transition them from a subjective clinical practice into an objective, data-driven process that is amenable to at least partial automation. This ambitious goal is critical not only to the success of ClinGen, but to the success of predictive genomic medicine overall. In recognition of this leadership, I have been appointed to co-chair the ACMG/AMP/ClinGen working group to update the 2015 ACMG/AMP guidelines. In the realm of variant interpretation, our approach has been productive and fruitful with a number of advances that have supported the vision of objective, quantitative, data-driven variant interpretation. We developed a Bayesian framework and searched for actual values for prior and conditional probabilities that could be used to yield highly (but not completely) similar pathogenicity assertions as did Richards et al. This quantitative Bayesian framework now serves as the basis for many SVI discussions and activities We have followed this up by publishing a points-based system for variant pathogenicity to simplify the process and have published Variant Curation Expert Panel Recommendations for RYR1. We are now working to completely revise the 2015 recommendations and plan to have new guidelines in place in the coming year.

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