Erynn S. Gordon

Motivations and perceptions of early adopters of personalized genomics: perspectives from research participants.

Background/Aims: To predict the potential public health impact of personal genomics, empirical research on public perceptions of these services is needed. In this study, ‘early adopters’ of personal genomics were surveyed to assess their motivations, perceptions and intentions. Methods: Participants were recruited from everyone who registered to attend an enrollment event for the Coriell Personalized Medicine Collaborative, a United States-based (Camden, N.J.) research study of the utility of personalized medicine, between March 31, 2009 and April 1, 2010 (n = 369). Participants completed an Internet-based survey about their motivations, awareness of personalized medicine, perceptions of study risks and benefits, and intentions to share results with health care providers. Results: Respondents were motivated to participate for their own curiosity and to find out their disease risk to improve their health. Fewer than 10% expressed deterministic perspectives about genetic risk, but 32% had misperceptions about the research study or personal genomic testing. Most respondents perceived the study to have health-related benefits. Nearly all (92%) intended to share their results with physicians, primarily to request specific medical recommendations. Conclusion: Early adopters of personal genomics are prospectively enthusiastic about using genomic profiling information to improve their health, in close consultation with their physicians. This suggests that early users (i.e. through direct-to-consumer companies or research) may follow up with the health care system. Further research should address whether intentions to seek care match actual behaviors.

Coriell Personalized Medicine Collaborative®: a prospective study of the utility of personalized medicine

There is a dearth of large prospective studies to determine if genetic risk factors are useful predictors of health outcomes and if reporting them to individuals or physicians changes health behavior. The Coriell Personalized Medicine Collaborative® (CPMC, NJ, USA) is a prospective observational study with three cohorts - community, cancer and chronic disease cohorts. Participants provide detailed medical history through a dynamic internet-based portal. DNA is tested and personalized risk reports are provided for potentially actionable health conditions. To date, the community cohort has enrolled 4372 participants. The internet-based portal supplies educational content, captures phenotypic data and delivers customized risk reports. The Informed Cohort Oversight Board has approved 16 health conditions to date, and risk reports with genetic and nongenetic risks for six conditions have been released. The majority (87%) of participants who completed requisite questionnaires viewed at least one report. The CPMC is a cohort study delivering customized risk reports for actionable conditions using a web interface and measuring outcomes longitudinally.

Novel LMNA Mutations in Patients With Emery-Dreifuss Muscular Dystrophy and Functional Characterization of Four LMNA Mutations

Mutations in LMNA cause a variety of diseases affecting striated muscle including autosomal Emery‐Dreifuss muscular dystrophy (EDMD), LMNA‐associated congenital muscular dystrophy (L‐CMD), and limb‐girdle muscular dystrophy type 1B (LGMD1B). Here, we describe novel and recurrent LMNA mutations identified in 50 patients from the United States and Canada, which is the first report of the distribution of LMNA mutations from a large cohort outside Europe. This augments the number of LMNA mutations known to cause EDMD by 16.5%, equating to an increase of 5.9% in the total known LMNA mutations. Eight patients presented with either p.R249W/Q or p.E358K mutations and an early onset EDMD phenotype: two mutations recently associated with L‐CMD. Importantly, 15 mutations are novel and include eight missense mutations (p.R189P, p.F206L, p.S268P, p.S295P, p.E361K, p.G449D, p.L454P, and p.W467R), three splice site mutations (c.IVS4 + 1G>A, c.IVS6 − 2A>G, and c.IVS8 + 1G>A), one duplication/in frame insertion (p.R190dup), one deletion (p.Q355del), and two silent mutations (p.R119R and p.K270K). Analysis of 4 of our lamin A mutations showed that some caused nuclear deformations and lamin B redistribution in a mutation specific manner. Together, this study significantly augments the number of EDMD patients on the database and describes 15 novel mutations that underlie EDMD, which will contribute to establishing genotype–phenotype correlations. Hum Mutat 31:–16, 2011.

Genetic risk estimation in the Coriell Personalized Medicine Collaborative.

Purpose: Recent genome wide-association studies have identified hundreds of single nucleotide polymorphisms associated with common complex diseases. With the momentum of these discoveries comes a need to communicate this information to individuals.Methods: The Coriell Personalized Medicine Collaborative is an observational research study designed to evaluate the utility of personalized genomic information in health care. Participants provide saliva samples for genotyping and complete extensive on-line medical history, family history, and lifestyle questionnaires. Only results for diseases deemed potentially actionable by an independent advisory board are reported.Results: We present our methodology for developing personalized reports containing risks for both genetic and nongenetic factors. Risk estimates are given as relative risk, derived or reported from representative peer-reviewed publications. Estimates of disease prevalence are also provided. Presenting risk as relative risk allows for consistent reporting across multiple diseases and across genetic and nongenetic factors. Using this approach eliminates the need for assumptions regarding population lifetime risk estimates. Publications used for risk reporting are selected based on the strength of the design and study quality.Conclusion: Coriell Personalized Medicine Collaborative risk reports demonstrate an approach to communicating risk of complex disease via the web that encompasses risks due to genetic variants along with risks caused by family history and lifestyle factors.

“It’s Not Like Judgment Day”: Public Understanding of and Reactions to Personalized Genomic Risk Information

The value of genomic risk assessment depends upon patients making appropriate behavioral changes in response to increased risk leading to disease prevention and early detection. To date, few studies have investigated consumers’ response to personalized genomic disease risk information. To address this gap, we conducted semi-structured interviews with 60 adults participating in the Coriell Personalized Medicine Collaborative. The interviews took place after receiving results providing genomic and other risk information for up to eight common complex diseases. We found that participants were most likely to recall results which conferred an increased risk or those of particular personal interest. Participants understood the multi-factorial nature of common complex disease, and generally did not have negative emotional responses or overly deterministic perceptions of their results. Although most participants expressed a desire to use results to improve their health, a minority had actually taken action (behavior change or shared results with their doctor) at the time of the interview. These results suggest that participants have a reasonable understanding of genomic risk information and that provision of genomic risk information may motivate behavior change in some individuals; however additional work is needed to better understand the lack of change seen in the majority of participants.

Characterizing genetic variants for clinical action

Genome‐wide association studies, DNA sequencing studies, and other genomic studies are finding an increasing number of genetic variants associated with clinical phenotypes that may be useful in developing diagnostic, preventive, and treatment strategies for individual patients. However, few variants have been integrated into routine clinical practice. The reasons for this are several, but two of the most significant are limited evidence about the clinical implications of the variants and a lack of a comprehensive knowledge base that captures genetic variants, their phenotypic associations, and other pertinent phenotypic information that is openly accessible to clinical groups attempting to interpret sequencing data. As the field of medicine begins to incorporate genome‐scale analysis into clinical care, approaches need to be developed for collecting and characterizing data on the clinical implications of variants, developing consensus on their actionability, and making this information available for clinical use. The National Human Genome Research Institute (NHGRI) and the Wellcome Trust thus convened a workshop to consider the processes and resources needed to: (1) identify clinically valid genetic variants; (2) decide whether they are actionable and what the action should be; and (3) provide this information for clinical use. This commentary outlines the key discussion points and recommendations from the workshop.

The Coriell personalized medicine collaborative pharmacogenomics appraisal, evidence scoring and interpretation system

Implementation of pharmacogenomics (PGx) in clinical care can lead to improved drug efficacy and reduced adverse drug reactions. However, there has been a lag in adoption of PGx tests in clinical practice. This is due in part to a paucity of rigorous systems for translating published clinical and scientific data into standardized diagnostic tests with clear therapeutic recommendations. Here we describe the Pharmacogenomics Appraisal, Evidence Scoring and Interpretation System (PhAESIS), developed as part of the Coriell Personalized Medicine Collaborative research study, and its application to seven commonly prescribed drugs.

Personalized genomic results: analysis of informational needs.

Use of genomic information in healthcare is increasing; however data on the needs of consumers of genomic information is limited. The Coriell Personalized Medicine Collaborative (CPMC) is a longitudinal study investigating the utility of personalized medicine. Participants receive results reflecting risk of common complex conditions and drug—gene pairs deemed actionable by an external review board. To explore the needs of individuals receiving genomic information we reviewed all genetic counseling sessions with CPMC participants. A retrospective qualitative review of notes from 157 genetic counseling inquiries was conducted. Notes were coded for salient themes. Five primary themes; “understanding risk”, “basic genetics”, “complex disease genetics”, “what do I do now?” and “other” were identified. Further review revealed that participants had difficulty with basic genetic concepts, confused relative and absolute risks, and attributed too high a risk burden to individual single nucleotide polymorphisms (SNPs). Despite these hurdles, counseled participants recognized that behavior changes could potentially mitigate risk and there were few comments alluding to an overly deterministic or fatalistic interpretation of results. Participants appeared to recognize the multifactorial nature of the diseases for which results were provided; however education to understand the complexities of genomic risk information was often needed.

Using the Coriell Personalized Medicine Collaborative Data to conduct a genome‐wide association study of sleep duration

Sleep is critical to health and functionality, and several studies have investigated the inherited component of insomnia and other sleep disorders using genome‐wide association studies (GWAS). However, genome‐wide studies focused on sleep duration are less common. Here, we used data from participants in the Coriell Personalized Medicine Collaborative (CPMC) (n = 4,401) to examine putative associations between self‐reported sleep duration, demographic and lifestyle variables, and genome‐wide single nucleotide polymorphism (SNP) data to better understand genetic contributions to variation in sleep duration. We employed stepwise ordered logistic regression to select our model and retained the following predictive variables: age, gender, weight, physical activity, physical activity at work, smoking status, alcohol consumption, ethnicity, and ancestry (as measured by principal components analysis) in our association testing. Several of our strongest candidate genes were previously identified in GWAS related to sleep duration (TSHZ2, ABCC9, FBXO15) and narcolepsy (NFATC2, SALL4). In addition, we have identified novel candidate genes for involvement in sleep duration including SORCS1 and ELOVL2. Our results demonstrate that the self‐reported data collected through the CPMC are robust, and our genome‐wide association analysis has identified novel candidate genes involved in sleep duration. More generally, this study contributes to a better understanding of the complexity of human sleep.

Huntington disease reduced penetrance alleles occur at high frequency in the general population

Objective: To directly estimate the frequency and penetrance of CAG repeat alleles associated with Huntington disease (HD) in the general population. Methods: CAG repeat length was evaluated in 7,315 individuals from 3 population-based cohorts from British Columbia, the United States, and Scotland. The frequency of ≥36 CAG alleles was assessed out of a total of 14,630 alleles. The general population frequency of reduced penetrance alleles (36–39 CAG) was compared to the prevalence of patients with HD with genetically confirmed 36–39 CAG from a multisource clinical ascertainment in British Columbia, Canada. The penetrance of 36–38 CAG repeat alleles for HD was estimated for individuals ≥65 years of age and compared against previously reported clinical penetrance estimates. Results: A total of 18 of 7,315 individuals had ≥36 CAG, revealing that approximately 1 in 400 individuals from the general population have an expanded CAG repeat associated with HD (0.246%). Individuals with CAG 36–37 genotypes are the most common (36, 0.096%; 37, 0.082%; 38, 0.027%; 39, 0.000%; ≥40, 0.041%). General population CAG 36–38 penetrance rates are lower than penetrance rates extrapolated from clinical cohorts. Conclusion: HD alleles with a CAG repeat length of 36–38 occur at high frequency in the general population. The infrequent diagnosis of HD at this CAG length is likely due to low penetrance. Another important contributing factor may be reduced ascertainment of HD in those of older age.