The incorporation of genomics into medicine is stimulating interest on the return of incidental findings (IFs) from exome and genome sequencing. However, no large-scale study has yet estimated the number of expected actionable findings per individual; therefore, we classified actionable pathogenic single-nucleotide variants in 500 European- and 500 African-descent participants randomly selected from the National Heart, Lung, and Blood Institute Exome Sequencing Project. The 1,000 individuals were screened for variants in 114 genes selected by an expert panel for their association with medically actionable genetic conditions possibly undiagnosed in adults. Among the 1,000 participants, 585 instances of 239 unique variants were identified as disease causing in the Human Gene Mutation Database (HGMD). The primary literature supporting the variants' pathogenicity was reviewed. Of the identified IFs, only 16 unique autosomal-dominant variants in 17 individuals were assessed to be pathogenic or likely pathogenic, and one participant had two pathogenic variants for an autosomal-recessive disease. Furthermore, one pathogenic and four likely pathogenic variants not listed as disease causing in HGMD were identified. These data can provide an estimate of the frequency (∼3.4% for European descent and ∼1.2% for African descent) of the high-penetrance actionable pathogenic or likely pathogenic variants in adults. The 23 participants with pathogenic or likely pathogenic variants were disproportionately of European (17) versus African (6) descent. The process of classifying these variants underscores the need for a more comprehensive and diverse centralized resource to provide curated information on pathogenicity for clinical use to minimize health disparities in genomic medicine.

Recommendations for laboratories to report incidental findings from genomic tests have stimulated interest in such results. In order to investigate the criteria and processes for assigning the pathogenicity of specific variants and to estimate the frequency of such incidental findings in patients of European and African ancestry, we classified potentially actionable pathogenic single-nucleotide variants (SNVs) in all 4300 European- and 2203 African-ancestry participants sequenced by the NHLBI Exome Sequencing Project (ESP). We considered 112 gene-disease pairs selected by an expert panel as associated with medically actionable genetic disorders that may be undiagnosed in adults. The resulting classifications were compared to classifications from other clinical and research genetic testing laboratories, as well as with in silico pathogenicity scores. Among European-ancestry participants, 30 of 4300 (0.7%) had a pathogenic SNV and six (0.1%) had a disruptive variant that was expected to be pathogenic, whereas 52 (1.2%) had likely pathogenic SNVs. For African-ancestry participants, six of 2203 (0.3%) had a pathogenic SNV and six (0.3%) had an expected pathogenic disruptive variant, whereas 13 (0.6%) had likely pathogenic SNVs. Genomic Evolutionary Rate Profiling mammalian conservation score and the Combined Annotation Dependent Depletion summary score of conservation, substitution, regulation, and other evidence were compared across pathogenicity assignments and appear to have utility in variant classification. This work provides a refined estimate of the burden of adult onset, medically actionable incidental findings expected from exome sequencing, highlights challenges in variant classification, and demonstrates the need for a better curated variant interpretation knowledge base.

We describe here the design and initial implementation of the eMERGE-PGx project. eMERGE-PGx, a partnership of the eMERGE and PGRN consortia, has three objectives : 1) Deploy PGRNseq, a next-generation sequencing platform assessing sequence variation in 84 proposed pharmacogenes, in nearly 9,000 patients likely to be prescribed drugs of interest in a 1–3 year timeframe across several clinical sites; 2) Integrate well-established clinically-validated pharmacogenetic genotypes into the electronic health record with associated clinical decision support and assess process and clinical outcomes of implementation; and 3) Develop a repository of pharmacogenetic variants of unknown significance linked to a repository of EHR-based clinical phenotype data for ongoing pharmacogenomics discovery. We describe site-specific project implementation and anticipated products, including genetic variant and phenotype data repositories, novel variant association studies, clinical decision support modules, clinical and process outcomes, approaches to manage incidental findings, and patient and clinician education methods.

High-density lipoprotein (HDL), a lipid nanoparticle containing many different low abundance proteins, is an attractive target for clinical proteomics because its compositional heterogeneity is linked to its cardioprotective effects. Selected reaction monitoring (SRM) is currently the method of choice for targeted quantification of proteins in such a complex biological matrix. However, model system studies suggest that parallel reaction monitoring (PRM) is more specific than SRM because many product ions can be used to confirm the identity of a peptide. We therefore compared PRM and SRM for their abilities to quantify proteins in HDL, using 15N-labeled apolipoprotein A-I (HDL’s most abundant protein) as the internal standard. PRM and SRM exhibited comparable linearity, dynamic range, precision, and repeatability for protein quantification of HDL. Moreover, the single internal standard protein performed as well as protein-specific peptide internal standards when quantifying 3 different proteins. Importantly, PRM and SRM yielded virtually identical quantitative results for 26 proteins in HDL isolated from 44 subjects. Because PRM requires less method development than SRM and is potentially more specific, our observations indicate that PRM in concert with a single isotope-labeled protein is a promising new strategy for quantifying HDL proteins in translational studies.