Erin M. Ramos

Finding the missing heritability of complex diseases

Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, ‘missing’ heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.

Potential etiologic and functional implications of genome-wide association loci for human diseases and traits

We have developed an online catalog of SNP-trait associations from published genome-wide association studies for use in investigating genomic characteristics of trait/disease-associated SNPs (TASs). Reported TASs were common [median risk allele frequency 36%, interquartile range (IQR) 21%−53%] and were associated with modest effect sizes [median odds ratio (OR) 1.33, IQR 1.20–1.61]. Among 20 genomic annotation sets, reported TASs were significantly overrepresented only in nonsynonymous sites [OR = 3.9 (2.2−7.0), p = 3.5 × 10−7] and 5kb-promoter regions [OR = 2.3 (1.5−3.6), p = 3 × 10−4] compared to SNPs randomly selected from genotyping arrays. Although 88% of TASs were intronic (45%) or intergenic (43%), TASs were not overrepresented in introns and were significantly depleted in intergenic regions [OR = 0.44 (0.34−0.58), p = 2.0 × 10−9]. Only slightly more TASs than expected by chance were predicted to be in regions under positive selection [OR = 1.3 (0.8−2.1), p = 0.2]. This new online resource, together with bioinformatic predictions of the underlying functionality at trait/disease-associated loci, is well-suited to guide future investigations of the role of common variants in complex disease etiology.

ClinGen — The Clinical Genome Resource

On autopsy, a patient is found to have hypertrophic cardiomyopathy. The patient’s family pursues genetic testing that shows a “likely pathogenic” variant for the condition on the basis of a study in an original research publication. Given the dominant inheritance of the condition and the risk of sudden cardiac death, other family members are tested for the genetic variant to determine their risk. Several family members test negative and are told that they are not at risk for hypertrophic cardiomyopathy and sudden cardiac death, and those who test positive are told that they need to be regularly monitored for cardiomyopathy on echocardiography. Five years later, during a routine clinic visit of one of the genotype-positive family members, the cardiologist queries a database for current knowledge on the genetic variant and discovers that the variant is now interpreted as “likely benign” by another laboratory that uses more recently derived population-frequency data. A newly available testing panel for additional genes that are implicated in hypertrophic cardiomyopathy is initiated on an affected family member, and a different variant is found that is determined to be pathogenic. Family members are retested, and one member who previously tested negative is now found to be positive for this new variant. An immediate clinical workup detects evidence of cardiomyopathy, and an intracardiac defibrillator is implanted to reduce the risk of sudden cardiac death.

The PhenX Toolkit: Get the Most From Your Measures

The potential for genome-wide association studies to relate phenotypes to specific genetic variation is greatly increased when data can be combined or compared across multiple studies. To facilitate replication and validation across studies, RTI International (Research Triangle Park, North Carolina) and the National Human Genome Research Institute (Bethesda, Maryland) are collaborating on the consensus measures for Phenotypes and eXposures (PhenX) project. The goal of PhenX is to identify 15 high-priority, well-established, and broadly applicable measures for each of 21 research domains. PhenX measures are selected by working groups of domain experts using a consensus process that includes input from the scientific community. The selected measures are then made freely available to the scientific community via the PhenX Toolkit. Thus, the PhenX Toolkit provides the research community with a core set of high-quality, well-established, low-burden measures intended for use in large-scale genomic studies. PhenX measures will have the most impact when included at the experimental design stage. The PhenX Toolkit also includes links to standards and resources in an effort to facilitate data harmonization to legacy data. Broad acceptance and use of PhenX measures will promote cross-study comparisons to increase statistical power for identifying and replicating variants associated with complex diseases and with gene-gene and gene-environment interactions.

Phenotype–Genotype Integrator (PheGenI): synthesizing genome-wide association study (GWAS) data with existing genomic resources

Rapidly accumulating data from genome-wide association studies (GWASs) and other large-scale studies are most useful when synthesized with existing databases. To address this opportunity, we developed the Phenotype–Genotype Integrator (PheGenI), a user-friendly web interface that integrates various National Center for Biotechnology Information (NCBI) genomic databases with association data from the National Human Genome Research Institute GWAS Catalog and supports downloads of search results. Here, we describe the rationale for and development of this resource. Integrating over 66 000 association records with extensive single nucleotide polymorphism (SNP), gene, and expression quantitative trait loci data already available from the NCBI, PheGenI enables deeper investigation and interrogation of SNPs associated with a wide range of traits, facilitating the examination of the relationships between genetic variation and human diseases.

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.

CHRNB3 is more strongly associated with Fagerström Test for Cigarette Dependence-based nicotine dependence than cigarettes per day: Phenotype definition changes genome-wide association studies results

AIMS Nicotine dependence is a highly heritable disorder associated with severe medical morbidity and mortality. Recent meta-analyses have found novel genetic loci associated with cigarettes per day (CPD), a proxy for nicotine dependence. The aim of this paper is to evaluate the importance of phenotype definition (i.e., CPD versus Fagerström test for cigarette dependence (FTCD) score as a measure of nicotine dependence) on genome-wide association studies of nicotine dependence. DESIGN Genome-wide association study. SETTING Community sample. PARTICIPANTS A total of 3365 subjects who had smoked at least one cigarette were selected from the Study of Addiction: Genetics and Environment (SAGE). Of the participants, 2267 were European Americans, 999 were African Americans. MEASUREMENTS Nicotine dependence defined by FTCD score ≥4, CPD. FINDINGS The genetic locus most strongly associated with nicotine dependence was rs1451240 on chromosome 8 in the region of CHRNB3 [odds ratio (OR) = 0.65, P = 2.4 × 10(-8) ]. This association was further strengthened in a meta-analysis with a previously published data set (combined P = 6.7 × 10(-16) , total n = 4200). When CPD was used as an alternate phenotype, the association no longer reached genome-wide significance (β  =  -0.08, P = 0.0004). CONCLUSIONS Daily cigarette consumption and the Fagerstrom Test for Cigarette Dependence show different associations with polymorphisms in genetic loci.

Next generation analytic tools for large scale genetic epidemiology studies of complex diseases.

Over the past several years, genome‐wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled “Next Generation Analytic Tools for Large‐Scale Genetic Epidemiology Studies of Complex Diseases” on September 15–16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large‐scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene‐gene and gene‐environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized. Genet. Epidemiol. 36 : 22–35, 2012.

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: