Maureen E. Smith

Interaction between ERAP1 and HLA-B27 in ankylosing spondylitis implicates peptide handling in the mechanism for HLA-B27 in disease susceptibility

Ankylosing spondylitis is a common form of inflammatory arthritis predominantly affecting the spine and pelvis that occurs in approximately 5 out of 1,000 adults of European descent. Here we report the identification of three variants in the RUNX3, LTBR-TNFRSF1A and IL12B regions convincingly associated with ankylosing spondylitis (P < 5 × 10−8 in the combined discovery and replication datasets) and a further four loci at PTGER4, TBKBP1, ANTXR2 and CARD9 that show strong association across all our datasets (P < 5 × 10−6 overall, with support in each of the three datasets studied). We also show that polymorphisms of ERAP1, which encodes an endoplasmic reticulum aminopeptidase involved in peptide trimming before HLA class I presentation, only affect ankylosing spondylitis risk in HLA-B27–positive individuals. These findings provide strong evidence that HLA-B27 operates in ankylosing spondylitis through a mechanism involving aberrant processing of antigenic peptides.

The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future

The Electronic Medical Records and Genomics Network is a National Human Genome Research Institute–funded consortium engaged in the development of methods and best practices for using the electronic medical record as a tool for genomic research. Now in its sixth year and second funding cycle, and comprising nine research groups and a coordinating center, the network has played a major role in validating the concept that clinical data derived from electronic medical records can be used successfully for genomic research. Current work is advancing knowledge in multiple disciplines at the intersection of genomics and health-care informatics, particularly for electronic phenotyping, genome-wide association studies, genomic medicine implementation, and the ethical and regulatory issues associated with genomics research and returning results to study participants. Here, we describe the evolution, accomplishments, opportunities, and challenges of the network from its inception as a five-group consortium focused on genotype–phenotype associations for genomic discovery to its current form as a nine-group consortium pivoting toward the implementation of genomic medicine.Genet Med 15 10, 761–771.Genetics in Medicine (2013); 15 10, 761–771. doi:10.1038/gim.2013.72

Public and biobank participant attitudes toward genetic research participation and data sharing.

Research assessing attitudes toward consent processes for high-throughput genomic-wide technologies and widespread sharing of data is limited. In order to develop a better understanding of stakeholder views toward these issues, this cross-sectional study assessed public and biorepository participant attitudes toward research participation and sharing of genetic research data. Forty-nine individuals participated in 6 focus groups; 28 in 3 public focus groups and 21 in 3 NUgene biorepository participant focus groups. In the public focus groups, 75% of participants were women, 75% had some college education or more, 46% were African-American and 29% were Hispanic. In the NUgene focus groups, 67% of participants were women, 95% had some college education or more, and the majority (76%) of participants was Caucasian. Five major themes were identified in the focus group data: (a) a wide spectrum of understanding of genetic research; (b) pros and cons of participation in genetic research; (c) influence of credibility and trust of the research institution; (d) concerns about sharing genetic research data and need for transparency in the Policy for Sharing of Data in National Institutes of Health-Supported or Conducted Genome-Wide Association Studies; (e) a need for more information and education about genetic research. In order to increase public understanding and address potential concerns about genetic research, future efforts should be aimed at involving the public in genetic research policy development and in identifying or developing appropriate educational strategies to meet the public’s needs.

Design and anticipated outcomes of the eMERGE-PGx project: a multicenter pilot for preemptive pharmacogenomics in electronic health record systems.

We describe here the design and initial implementation of the eMERGE‐PGx project. eMERGE‐PGx, a partnership of the Electronic Medical Records and Genomics Network and the Pharmacogenomics Research Network, has three objectives: (i) to 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‐ to 3‐year time frame across several clinical sites; (ii) to integrate well‐established clinically validated pharmacogenetic genotypes into the electronic health record with associated clinical decision support and to assess process and clinical outcomes of implementation; and (iii) to develop a repository of pharmacogenetic variants of unknown significance linked to a repository of electronic health record–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 managing incidental findings, and patient and clinician education methods.

Association of Arrhythmia-Related Genetic Variants With Phenotypes Documented in Electronic Medical Records.

IMPORTANCE Large-scale DNA sequencing identifies incidental rare variants in established Mendelian disease genes, but the frequency of related clinical phenotypes in unselected patient populations is not well established. Phenotype data from electronic medical records (EMRs) may provide a resource to assess the clinical relevance of rare variants. OBJECTIVE To determine the clinical phenotypes from EMRs for individuals with variants designated as pathogenic by expert review in arrhythmia susceptibility genes. DESIGN, SETTING, AND PARTICIPANTS This prospective cohort study included 2022 individuals recruited for nonantiarrhythmic drug exposure phenotypes from October 5, 2012, to September 30, 2013, for the Electronic Medical Records and Genomics Network Pharmacogenomics project from 7 US academic medical centers. Variants in SCN5A and KCNH2, disease genes for long QT and Brugada syndromes, were assessed for potential pathogenicity by 3 laboratories with ion channel expertise and by comparison with the ClinVar database. Relevant phenotypes were determined from EMRs, with data available from 2002 (or earlier for some sites) through September 10, 2014. EXPOSURES One or more variants designated as pathogenic in SCN5A or KCNH2. MAIN OUTCOMES AND MEASURES Arrhythmia or electrocardiographic (ECG) phenotypes defined by International Classification of Diseases, Ninth Revision (ICD-9) codes, ECG data, and manual EMR review. RESULTS Among 2022 study participants (median age, 61 years [interquartile range, 56-65 years]; 1118 [55%] female; 1491 [74%] white), a total of 122 rare (minor allele frequency <0.5%) nonsynonymous and splice-site variants in 2 arrhythmia susceptibility genes were identified in 223 individuals (11% of the study cohort). Forty-two variants in 63 participants were designated potentially pathogenic by at least 1 laboratory or ClinVar, with low concordance across laboratories (Cohen κ = 0.26). An ICD-9 code for arrhythmia was found in 11 of 63 (17%) variant carriers vs 264 of 1959 (13%) of those without variants (difference, +4%; 95% CI, -5% to +13%; P = .35). In the 1270 (63%) with ECGs, corrected QT intervals were not different in variant carriers vs those without (median, 429 vs 439 milliseconds; difference, -10 milliseconds; 95% CI, -16 to +3 milliseconds; P = .17). After manual review, 22 of 63 participants (35%) with designated variants had any ECG or arrhythmia phenotype, and only 2 had corrected QT interval longer than 500 milliseconds. CONCLUSIONS AND RELEVANCE Among laboratories experienced in genetic testing for cardiac arrhythmia disorders, there was low concordance in designating SCN5A and KCNH2 variants as pathogenic. In an unselected population, the putatively pathogenic genetic variants were not associated with an abnormal phenotype. These findings raise questions about the implications of notifying patients of incidental genetic findings.

Return of individual research results from genome-wide association studies: experience of the Electronic Medical Records and Genomics (eMERGE) Network.

Purpose:Return of individual genetic results to research participants, including participants in archives and biorepositories, is receiving increased attention. However, few groups have deliberated on specific results or weighed deliberations against relevant local contextual factors.Methods:The Electronic Medical Records and Genomics (eMERGE) Network, which includes five biorepositories conducting genome-wide association studies, convened a return of results oversight committee to identify potentially returnable results. Network-wide deliberations were then brought to local constituencies for final decision making.Results:Defining results that should be considered for return required input from clinicians with relevant expertise and much deliberation. The return of results oversight committee identified two sex chromosomal anomalies, Klinefelter syndrome and Turner syndrome, as well as homozygosity for factor V Leiden, as findings that could warrant reporting. Views about returning findings of HFE gene mutations associated with hemochromatosis were mixed due to low penetrance. Review of electronic medical records suggested that most participants with detected abnormalities were unaware of these findings. Local considerations relevant to return varied and, to date, four sites have elected not to return findings (return was not possible at one site).Conclusion:The eMERGE experience reveals the complexity of return of results decision making and provides a potential deliberative model for adoption in other collaborative contexts.Genet Med 2012:14(4):424–431

Ethical and practical challenges of sharing data from genome-wide association studies: The eMERGE Consortium experience

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.

Confronting real time ethical, legal, and social issues in the Electronic Medical Records and Genomics (eMERGE) Consortium.

Increasingly, genomic research is being conducted through large, multi-site consortia. For example, the eMERGE (Electronic Medical Records and Genomics) Consortium was funded by the National Human Genome Research Institute to evaluate the scientific feasibility and potential value of performing genome wide association studies (GWAS) using information from electronic medical records together with hundreds of thousands of single nucleotide polymorphisms (SNPs) from samples obtained in the course of existing cohort studies, biorepositories, or from residual tissue or blood samples. This experiment, if successful, will enable a vast amount of research, especially as more and more medical information is stored electronically and as the cost of genotyping and sequencing decreases. However, the ability to use existing clinical information and samples for GWAS, while exciting, raises a number of ethical, legal, social, and policy issues. Examples of some of the issues raised by this type of research include: What sort of consent, if any, is required for such research? When might it be necessary to obtain new consent for the use of previously collected samples? Recognizing the value and the cost of obtaining such rich clinical and genetic variation data, and the desirability of combining datasets to permit more robust analysis, the NIH has strongly encouraged GWAS funded by the NIH, including the eMERGE data, be placed in a central repository called the database of Genotypes and Phenotypes (dbGaP) for use by other qualified investigators.1 To what extent should patients and research participants be able to opt out of having their data shared with the broader research community through government-sponsored databases such as dbGaP? When diverse data sources are combined and then shared beyond the originating institutions, the abilities of investigators or biorepository managers to protect participants’ interests, including privacy, necessarily change. Given this shift, do the obligations of those who originally collected samples change, and if so, how? Should investigators’ obligations differ depending on whether data and samples come from patients seeking routine care or from participants in a preexisting research project? When, if ever, should research results, either aggregate or individual, be returned to participants? What about incidental findings? And what role should communities play in long-term oversight and governance of these projects? To address these, and related concerns, each eMERGE site was required to bring together genetic researchers and ELSI investigators to address the ethical and social challenges of such research. Building an ethics component into large scientific studies provides an opportunity for transdisciplinary ELSI (ethical, legal, and social implications) research that is immediately responsive to the emerging issues raised by scientific innovation, an approach that is becoming more common in genomics research.2-4 The eMERGE Consortium provides a particularly rich landscape in which to pursue such research. The five partner institutions are examining data from a variety of populations that differ in their demographic characteristics, the ways they were recruited, and in the depth and stability of their relationships with the particular research team and institution (Table 1). Each eMERGE site includes investigators who bring particular disciplinary perspectives and approaches to studying the implications of using information from electronic medical records for GWAS (Table 1). (Additional Information about each member site and its research can be found at www.gwas.net). Table 1 In order to maximize what can be learned from the diverse eMERGE research settings, ELSI investigators are not only conducting transdisciplinary research at their own institutions, but have also joined together in a Consent and Community Consultation (C&CC) Working Group to share strategies and results and to collaborate on ethical issues and policy related to the conduct of GWAS. To facilitate this work, a number of prominent investigators from non-eMERGE institutions were invited to join the C&CC Working Group. Their names and affiliations are listed at the end of this article. The larger group quickly organized a number of smaller groups to focus on key, cross-cutting topics. The current groups, their leadership, and their goals follow:

Stakeholder engagement: a key component of integrating genomic information into electronic health records

Integrating genomic information into clinical care and the electronic health record can facilitate personalized medicine through genetically guided clinical decision support. Stakeholder involvement is critical to the success of these implementation efforts. Prior work on implementation of clinical information systems provides broad guidance to inform effective engagement strategies. We add to this evidence-based recommendations that are specific to issues at the intersection of genomics and the electronic health record. We describe stakeholder engagement strategies employed by the Electronic Medical Records and Genomics Network, a national consortium of US research institutions funded by the National Human Genome Research Institute to develop, disseminate, and apply approaches that combine genomic and electronic health record data. Through select examples drawn from sites of the Electronic Medical Records and Genomics Network, we illustrate a continuum of engagement strategies to inform genomic integration into commercial and homegrown electronic health records across a range of health-care settings. We frame engagement as activities to consult, involve, and partner with key stakeholder groups throughout specific phases of health information technology implementation. Our aim is to provide insights into engagement strategies to guide genomic integration based on our unique network experiences and lessons learned within the broader context of implementation research in biomedical informatics. On the basis of our collective experience, we describe key stakeholder practices, challenges, and considerations for successful genomic integration to support personalized medicine.Genet Med 15 10, 792–801.Genetics in Medicine (2013); 15 10, 792–801. doi:10.1038/gim.2013.127

Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.