Development of a clinical polygenic risk score assay and reporting workflow.

Implementation of polygenic risk scores (PRS) may improve disease prevention and management but poses several challenges: the construction of clinically valid assays, interpretation for individual patients, and the development of clinical workflows and resources to support their use in patient care. For the ongoing Veterans Affairs Genomic Medicine at Veterans Affairs (GenoVA) Study we developed a clinical genotype array-based assay for six published PRS. We used data from 36,423 Mass General Brigham Biobank participants and adjustment for population structure to replicate known PRS-disease associations and published PRS thresholds for a disease odds ratio (OR) of 2 (ranging from 1.75 (95% CI: 1.57-1.95) for type 2 diabetes to 2.38 (95% CI: 2.07-2.73) for breast cancer). After confirming the high performance and robustness of the pipeline for use as a clinical assay for individual patients, we analyzed the first 227 prospective samples from the GenoVA Study and found that the frequency of PRS corresponding to published OR > 2 ranged from 13/227 (5.7%) for colorectal cancer to 23/150 (15.3%) for prostate cancer. In addition to the PRS laboratory report, we developed physician- and patient-oriented informational materials to support decision-making about PRS results. Our work illustrates the generalizable development of a clinical PRS assay for multiple conditions and the technical, reporting and clinical workflow challenges for implementing PRS information in the clinic.

Metadata Standard and Data Exchange Specifications to Describe, Model, and Integrate Complex and Diverse High-Throughput Screening Data from the Library of Integrated Network-based Cellular Signatures (LINCS).

The National Institutes of Health Library of Integrated Network-based Cellular Signatures (LINCS) program is generating extensive multidimensional data sets, including biochemical, genome-wide transcriptional, and phenotypic cellular response signatures to a variety of small-molecule and genetic perturbations with the goal of creating a sustainable, widely applicable, and readily accessible systems biology knowledge resource. Integration and analysis of diverse LINCS data sets depend on the availability of sufficient metadata to describe the assays and screening results and on their syntactic, structural, and semantic consistency. Here we report metadata specifications for the most important molecular and cellular components and recommend them for adoption beyond the LINCS project. We focus on the minimum required information to model LINCS assays and results based on a number of use cases, and we recommend controlled terminologies and ontologies to annotate assays with syntactic consistency and semantic integrity. We also report specifications for a simple annotation format (SAF) to describe assays and screening results based on our metadata specifications with explicit controlled vocabularies. SAF specifically serves to programmatically access and exchange LINCS data as a prerequisite for a distributed information management infrastructure. We applied the metadata specifications to annotate large numbers of LINCS cell lines, proteins, and small molecules. The resources generated and presented here are freely available.

Metabolomic identification of novel biomarkers of myocardial ischemia.

BACKGROUND: Recognition of myocardial ischemia is critical both for the diagnosis of coronary artery disease and the selection and evaluation of therapy. Recent advances in proteomic and metabolic profiling technologies may offer the possibility of identifying novel biomarkers and pathways activated in myocardial ischemia. METHODS AND RESULTS: Blood samples were obtained before and after exercise stress testing from 36 patients, 18 of whom demonstrated inducible ischemia (cases) and 18 of whom did not (controls). Plasma was fractionated by liquid chromatography, and profiling of analytes was performed with a high-sensitivity electrospray triple-quadrupole mass spectrometer under selected reaction monitoring conditions. Lactic acid and metabolites involved in skeletal muscle AMP catabolism increased after exercise in both cases and controls. In contrast, there was significant discordant regulation of multiple metabolites that either increased or decreased in cases but remained unchanged in controls. Functional pathway trend analysis with the use of novel software revealed that 6 members of the citric acid pathway were among the 23 most changed metabolites in cases (adjusted P=0.04). Furthermore, changes in 6 metabolites, including citric acid, differentiated cases from controls with a high degree of accuracy (P<0.0001; cross-validated c-statistic=0.83). CONCLUSIONS: We report the novel application of metabolomics to acute myocardial ischemia, in which we identified novel biomarkers of ischemia, and from pathway trend analysis, coordinate changes in groups of functionally related metabolites.

Global mapping of the yeast genetic interaction network.

A genetic interaction network containing approximately 1000 genes and approximately 4000 interactions was mapped by crossing mutations in 132 different query genes into a set of approximately 4700 viable gene yeast deletion mutants and scoring the double mutant progeny for fitness defects. Network connectivity was predictive of function because interactions often occurred among functionally related genes, and similar patterns of interactions tended to identify components of the same pathway. The genetic network exhibited dense local neighborhoods; therefore, the position of a gene on a partially mapped network is predictive of other genetic interactions. Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.