Candidate gene and genome-wide association studies (GWAS) have identified genetic variants that modulate risk for human disease; many of these associations require further study to replicate the results. Here we report the first large-scale application of the phenome-wide association study (PheWAS) paradigm within electronic medical records (EMRs), an unbiased approach to replication and discovery that interrogates relationships between targeted genotypes and multiple phenotypes. We scanned for associations between 3,144 single-nucleotide polymorphisms (previously implicated by GWAS as mediators of human traits) and 1,358 EMR-derived phenotypes in 13,835 individuals of European ancestry. This PheWAS replicated 66% (51/77) of sufficiently powered prior GWAS associations and revealed 63 potentially pleiotropic associations with P < 4.6 × 10−6 (false discovery rate < 0.1); the strongest of these novel associations were replicated in an independent cohort (n = 7,406). These findings validate PheWAS as a tool to allow unbiased interrogation across multiple phenotypes in EMR-based cohorts and to enhance analysis of the genomic basis of human disease.

In previous studies examining the structural determinants of antidepressant and substrate recognition by serotonin transporters (SERTs), we identified Tyr-95 in transmembrane segment 1 (TM1) of human SERT as a major determinant of binding for several antagonists, including racemic citalopram ((RS)-CIT). Here we described a separate site in hSERT TM3 (Ile-172) that impacts (RS)-CIT recognition when switched to the corresponding Drosophila SERT residue (I172M). The hSERT I172M mutant displays a marked loss of inhibitor potency for multiple inhibitors such as (RS)-CIT, clomipramine, RTI-55, fluoxetine, cocaine, nisoxetine, mazindol, and nomifensine, whereas recognition of substrates, including serotonin and 3,4-methylenedioxymethamphetamine, is unaffected. Selectivity for antagonist interactions is evident with this substitution because the potencies of the antidepressants tianeptine and paroxetine are unchanged. Reduced cocaine analog recognition was verified in photoaffinity labeling studies using [ 125 I]MFZ 2-24. In contrast to the I172M substitution, other substitutions at this position significantly affected substrate recognition and/or transport activity. Additionally, the mouse mutation (mSERT I172M) exhibits similar selective changes in inhibitor potency. Unlike hSERT or mSERT, analogous substitutions in mouse dopamine transporter (V152M) or human norepinephrine transporter (V148M) result in transporters that bind substrate but are deficient in the subsequent translocation of the substrate. A double mutant hSERT Y95F/ I172M had a synergistic impact on (RS)-CIT recognition (ϳ10,000-fold decrease in (RS)-CIT potency) in the context of normal serotonin recognition. The less active enantiomer (R)-CIT responded to the I172M substitution like (S)-CIT but was relatively insensitive to the Y95F substitution and did not display a synergistic loss at Y95F/ I172M. An hSERT mutant with single cysteine substitutions in TM1 and TM3 resulted in formation of a high affinity cadmium metal coordination site, suggesting proximity of these domains in the tertiary structure of SERT. These studies provided evidence for distinct binding sites coordinating SERT antagonists and revealed a close interaction between TM1 and TM3 differentially targeted by stereoisomers of CIT. SERT,2 like several other members of the SLC6A gene family, acts to remove neurotransmitter from the synapse following neurotransmission (1) and is a major target for treatment of mood disorders, including major depression, anxiety, post-traumatic stress, and obsessive-compulsive disorders (2). Agents that target SERT include tricyclic antidepressants and serotonin-specific reuptake inhibitors (SSRIs) that block 5HT binding and uptake. Despite its clinical significance, very little is understood concerning the structural aspects of SERT and how they relate to its function and antagonist recognition. The current data predict that SERT proteins are composed of 12 transmembrane-spanning segments, intracellular NH 2 and COOH termini and a large second extracellular...

BackgroundPatients, clinicians, researchers and payers are seeking to understand the value of using genomic information (as reflected by genotyping, sequencing, family history or other data) to inform clinical decision-making. However, challenges exist to widespread clinical implementation of genomic medicine, a prerequisite for developing evidence of its real-world utility.MethodsTo address these challenges, the National Institutes of Health-funded IGNITE (Implementing GeNomics In pracTicE; www.ignite-genomics.org) Network, comprised of six projects and a coordinating center, was established in 2013 to support the development, investigation and dissemination of genomic medicine practice models that seamlessly integrate genomic data into the electronic health record and that deploy tools for point of care decision making. IGNITE site projects are aligned in their purpose of testing these models, but individual projects vary in scope and design, including exploring genetic markers for disease risk prediction and prevention, developing tools for using family history data, incorporating pharmacogenomic data into clinical care, refining disease diagnosis using sequence-based mutation discovery, and creating novel educational approaches.ResultsThis paper describes the IGNITE Network and member projects, including network structure, collaborative initiatives, clinical decision support strategies, methods for return of genomic test results, and educational initiatives for patients and providers. Clinical and outcomes data from individual sites and network-wide projects are anticipated to begin being published over the next few years.ConclusionsThe IGNITE Network is an innovative series of projects and pilot demonstrations aiming to enhance translation of validated actionable genomic information into clinical settings and develop and use measures of outcome in response to genome-based clinical interventions using a pragmatic framework to provide early data and proofs of concept on the utility of these interventions. Through these efforts and collaboration with other stakeholders, IGNITE is poised to have a significant impact on the acceleration of genomic information into medical practice.

Numerous pharmacogenetic clinical guidelines and recommendations have been published, but barriers have hindered the clinical implementation of pharmacogenetics. The Translational Pharmacogenetics Program (TPP) of the NIH Pharmacogenomics Research Network was established in 2011 to catalog and contribute to the development of pharmacogenetic implementations at eight US healthcare systems, with the goal to disseminate real-world solutions for the barriers to clinical pharmacogenetic implementation. The TPP collected and normalized pharmacogenetic implementation metrics through June 2015, including gene-drug pairs implemented, interpretations of alleles and diplotypes, numbers of tests performed and actionable results, and workflow diagrams. TPP participant institutions developed diverse solutions to overcome many barriers, but the use of Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provided some consistency among the institutions. The TPP also collected some pharmacogenetic implementation outcomes (scientific, educational, financial, and informatics), which may inform healthcare systems seeking to implement their own pharmacogenetic testing programs.

The use of electronic medical record data linked to biological specimens in health care settings is expected to enable cost-effective and rapid genomic analyses. Here, we present a model that highlights potential advantages for genomic discovery and describe the operational infrastructure that facilitated multiple simultaneous discovery efforts.