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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., (© 2015 Amendola et al.; Published by Cold Spring Harbor Laboratory Press.)

In 2007, the National Human Genome Research Institute (NHGRI) established the Electronic MEdical Records and GEnomics (eMERGE) Consortium (www.gwas.net) to develop, disseminate, and apply approaches to research that combine DNA biorepositories with electronic medical record (EMR) systems for large-scale, high-throughput genetic research. One of the major ethical and administrative challenges for the eMERGE Consortium has been complying with existing data-sharing policies. This paper discusses the challenges of sharing genomic data linked to health information in the electronic medical record (EMR) and explores the issues as they relate to sharing both within a large consortium and in compliance with the National Institutes of Health (NIH) data-sharing policy. We use the eMERGE Consortium experience to explore data-sharing challenges from the perspective of multiple stakeholders (i.e., research participants, investigators, and research institutions), provide recommendations for researchers and institutions, and call for clearer guidance from the NIH regarding ethical implementation of its data-sharing policy.

A common strategy for genotyping large samples begins with the characterization of human single nucleotide polymorphisms (SNPs) by sequencing candidate regions in a small sample for SNP discovery. This is usually followed by typing in a large sample those sites observed to vary in a smaller sample. We present results from a systematic investigation of variation at the human apolipoprotein E locus (APOE), as well as the evaluation of the two-tiered sampling strategy based on these data. We sequenced 5.5 kb spanning the entire APOE genomic region in a core sample of 72 individuals, including 24 each of African-Americans from Jackson, Mississippi; European-Americans from Rochester, Minnesota; and Europeans from North Karelia, Finland. This sequence survey detected 21 SNPs and 1 multiallelic indel, 14 of which had not been previously reported. Alleles varied in relative frequency among the populations, and 10 sites were polymorphic in only a single population sample. Oligonucleotide ligation assays (OLA) were developed for 20 of these sites (omitting the indel and a closely-linked SNP). These were then scored in 2179 individuals sampled from the same three populations (n = 843, 884, and 452, respectively). Relative allele frequencies were generally consistent with estimates from the core sample, although variation was found in some populations in the larger sample at SNPs that were monomorphic in the corresponding smaller core sample. Site variation in the larger samples showed no systematic deviation from Hardy-Weinberg expectation. The large OLA sample clearly showed that variation in many, but not all, of OLA-typed SNPs is significantly correlated with the classical protein-coding variants, implying that there may be important substructure within the classical epsilon 2, epsilon 3, and epsilon 4 alleles. Comparison of the levels and patterns of polymorphism in the core samples with those estimated for the OLA-typed samples shows how nucleotide diversity is underestimated when only a subset of sites are typed and underscores the importance of adequate population sampling at the polymorphism discovery stage. [The sequence data described in this paper have been submitted to the GenBank data library under accession no. AF261279.]