The DiscovEHR collaboration between the Regeneron Genetics Center and Geisinger Health System couples high-throughput sequencing to an integrated health care system using longitudinal electronic health records (EHRs). We sequenced the exomes of 50,726 adult participants in the DiscovEHR study to identify ~4.2 million rare single-nucleotide variants and insertion/deletion events, of which ~176,000 are predicted to result in a loss of gene function. Linking these data to EHR-derived clinical phenotypes, we find clinical associations supporting therapeutic targets, including genes encoding drug targets for lipid lowering, and identify previously unidentified rare alleles associated with lipid levels and other blood level traits. About 3.5% of individuals harbor deleterious variants in 76 clinically actionable genes. The DiscovEHR data set provides a blueprint for large-scale precision medicine initiatives and genomics-guided therapeutic discovery.

Familial hypercholesterolemia (FH) remains underdiagnosed despite widespread cholesterol screening. Exome sequencing and electronic health record (EHR) data of 50,726 individuals were used to assess the prevalence and clinical impact of FH-associated genomic variants in the Geisinger Health System. The estimated FH prevalence was 1:256 in unselected participants and 1:118 in participants ascertained via the cardiac catheterization laboratory. FH variant carriers had significantly increased risk of coronary artery disease. Only 24% of carriers met EHR-based presequencing criteria for probable or definite FH diagnosis. Active statin use was identified in 58% of carriers; 46% of statin-treated carriers had a low-density lipoprotein cholesterol level below 100 mg/dl. Thus, we find that genomic screening can prompt the diagnosis of FH patients, most of whom are receiving inadequate lipid-lowering therapy.

The discovery and reliable detection of markers for neurodegenerative diseases have been complicated by the inaccessibility of the diseased tissue- such as the inability to biopsy or test tissue from the central nervous system directly. RNAs originating from hard to access tissues, such as neurons within the brain and spinal cord, have the potential to get to the periphery where they can be detected non-invasively. The formation and extracellular release of microvesicles and RNA binding proteins have been found to carry RNA from cells of the central nervous system to the periphery and protect the RNA from degradation. Extracellular miRNAs detectable in peripheral circulation can provide information about cellular changes associated with human health and disease. In order to associate miRNA signals present in cell-free peripheral biofluids with neurodegenerative disease status of patients with Alzheimer's and Parkinson's diseases, we assessed the miRNA content in cerebrospinal fluid and serum from postmortem subjects with full neuropathology evaluations. We profiled the miRNA content from 69 patients with Alzheimer's disease, 67 with Parkinson's disease and 78 neurologically normal controls using next generation small RNA sequencing (NGS). We report the average abundance of each detected miRNA in cerebrospinal fluid and in serum and describe 13 novel miRNAs that were identified. We correlated changes in miRNA expression with aspects of disease severity such as Braak stage, dementia status, plaque and tangle densities, and the presence and severity of Lewy body pathology. Many of the differentially expressed miRNAs detected in peripheral cell-free cerebrospinal fluid and serum were previously reported in the literature to be deregulated in brain tissue from patients with neurodegenerative disease. These data indicate that extracellular miRNAs detectable in the cerebrospinal fluid and serum are reflective of cell-based changes in pathology and can be used to assess disease progression and therapeutic efficacy.

Key Points Question Can population-level genomic screening identify those at risk for disease? Findings In this cross-sectional study of an unselected population cohort of 50 726 adults who underwent exome sequencing, pathogenic and likely pathogenic BRCA1 and BRCA2 variants were found in a higher proportion of patients than was previously reported. Meaning Current methods to identify BRCA1/2 variant carriers may not be sufficient as a screening tool; population genomic screening for hereditary breast and ovarian cancer may better identify patients at high risk and provide an intervention opportunity to reduce mortality and morbidity.

There has been a growing interest in using next-generation sequencing (NGS) to profile extracellular small RNAs from the blood and cerebrospinal fluid (CSF) of patients with neurological diseases, CNS tumors, or traumatic brain injury for biomarker discovery. Small sample volumes and samples with low RNA abundance create challenges for downstream small RNA sequencing assays. Plasma, serum, and CSF contain low amounts of total RNA, of which small RNAs make up a fraction. The purpose of this study was to maximize RNA isolation from RNA-limited samples and apply these methods to profile the miRNA in human CSF by small RNA deep sequencing. We systematically tested RNA isolation efficiency using ten commercially available kits and compared their performance on human plasma samples. We used RiboGreen to quantify total RNA yield and custom TaqMan assays to determine the efficiency of small RNA isolation for each of the kits. We significantly increased the recovery of small RNA by repeating the aqueous extraction during the phenol-chloroform purification in the top performing kits. We subsequently used the methods with the highest small RNA yield to purify RNA from CSF and serum samples from the same individual. We then prepared small RNA sequencing libraries using Illumina's TruSeq sample preparation kit and sequenced the samples on the HiSeq 2000. Not surprisingly, we found that the miRNA expression profile of CSF is substantially different from that of serum. To our knowledge, this is the first time that the small RNA fraction from CSF has been profiled using next-generation sequencing.