Coriell Personalized Medicine Collaborative Research Articles

Genome-wide Association Study of Caffeine Consumption Using Coriell Personalized Medicine Collaborative Data

More than 90% of Americans consume caffeine daily, but the amount consumed varies widely. Previous studies have shown that genes related to caffeine metabolism and receptor binding may influence caffeine consumption. A better understanding of the relationship between genotype and caffeine consumption has the potential to inform mechanisms of this common dietary behavior. We performed a genome-wide association study (GWAS) of self-reported consumption data combining a wide range of caffeinated beverages including coffee, tea, soda, and energy drinks in the Coriell Personalized Medicine Collaborative (N=2,830) using a generalized linear model. Our analysis identified several candidate loci implicated in caffeine consumption. One previously identified SNP associated with caffeine consumption and replicated in the current study, rs2472297 (P-value=3.8x10-6), is located in an intergenic region between CYP1A1 and CYP1A2 (the gene that encodes the enzyme primarily responsible for caffeine metabolism), and has been associated with caffeine consumption in prior studies. Our results further support follow-up functional studies focused on the role of CYP1A1 and CYP1A2 on caffeine consumption habits, metabolism, and health status and outcomes.

Testing a best practices risk result format to communicate genetic risks

ObjectiveTo investigate the effect of a genetic report format using risk communication "best-practices" on risk perceptions, in part to reduce risk overestimates. MethodsAdults (N = 470) from the Coriell Personalized Medicine Collaborative (CPMC) were randomized to a 2 × 2 experimental design to receive a hypothetical "personalized" genetic risk result for leukemia (relative risk = 1.5 or 2.5) through either the standard CPMC report (N = 232) or an enriched report informed by best practices (N = 238). A one-time, online survey assessed numeracy and risk perceptions including “feelings of risk” and a numerical estimate. ResultsRegardless of numeracy, participants who received the enriched report had fewer overestimates of their lifetime risk estimate (LRE; odds ratio = 0.19, p < .001) and lower feelings of risk on two of three measures (p < .001). Participants with higher numeracy scores had fewer overestimates of LRE (OR = 0.66, p < .001) and lower feelings of risk on two out of three measures (p ≤ .01); the interaction between numeracy and report format was non-significant. ConclusionThe enriched report produced more accurate LRE and lower risk perceptions regardless of numeracy level, suggesting the enriched format was helpful to individuals irrespective of numeracy ability. Practice implicationsBest practice elements in risk reports may help individuals form more accurate risk perceptions.

Pharmacogenomic (PGx) Counseling: Exploring Participant Questions about PGx Test Results.

As pharmacogenomic (PGx) use in healthcare increases, a better understanding of patient needs will be necessary to guide PGx result delivery. The Coriell Personalized Medicine Collaborative (CPMC) is a prospective study investigating the utility of personalized medicine. Participants received online genetic risk reports for 27 potentially actionable complex diseases and 7 drug–gene pairs and could request free, telephone-based genetic counseling (GC). To explore the needs of individuals receiving PGx results, we conducted a retrospective qualitative review of inquiries from CPMC participants who requested counseling from March 2009 to February 2017. Eighty out of 690 (12%) total GC inquiries were focused on the discussion of PGx results, and six salient themes emerged: “general help”, “issues with drugs”, “relevant disease experience”, “what do I do now?”, “sharing results”, and “other drugs”. The number of reported medications with a corresponding PGx result and participant engagement were significantly associated with PGx GC requests (p < 0.01 and p < 0.02, respectively). Our work illustrates a range of questions raised by study participants receiving PGx test results, most of which were addressed by a genetic counselor with few requiring referrals to prescribing providers or pharmacists. These results further support a role for genetic counselors in the team-based approach to optimal PGx result delivery.

Rs11670527 Upstream of ZNF264 Associated with Body Mass Index in the Coriell Personalized Medicine Collaborative.

the effects of obesity on health are a concern for the military as they affect the fitness to serve of active service members, increase costs to the Military Health System, and reduce quality of life for veterans and beneficiaries. Although obesity can be influenced by behavioral and environmental factors, it has also been shown to be associated with genetic risk factors that are not fully understood. we performed a genome-wide association study of 5,251 participants in the Coriell Personalized Medicine Collaborative, which includes 2,111 Air Force participants. We applied a generalized linear model, using principal component analysis to account for population structure, and analyzed single-variant associations with body mass index (BMI) as a continuous variable, using a Bonferroni-corrected P-value threshold to account for multiplicity. we identified one genome-wide significant locus, rs11670527, upstream of the ZNF264 gene on chromosome 19, associated with BMI. the finding of an association between rs11670527 and BMI adds to the growing body of literature characterizing the complex genetics of obesity. These efforts may eventually inform personalized interventions aimed at achieving and maintaining healthy weight.

Individuals with CYP2C8 and CYP2C9 reduced metabolism haplotypes self-adjusted ibuprofen dose in the Coriell Personalized Medicine Collaborative.

The objectives of this study were to determine whether differences in CYP2C8 and CYP2C9 haplotype influence the dose of ibuprofen self-administered by individuals, and to examine the potential relationship between CYP2C8 and CYP2C9 reduced metabolism haplotypes and adverse events. We investigated relationships between genetic variations in CYP2C8 and CYP2C9 and ibuprofen use, dose, and side effects (reported by questionnaire) in 445 participants from the Coriell Personalized Medicine Collaborative. Carriers of reduced metabolism haplotypes for CYP2C8 (*2, *3, *4) and CYP2C9 (*2, *3) were significantly (P=0.0171) more likely than those lacking these variants to take less than the recommended dose of ibuprofen, after controlling for sex, age, race, and cohort. In contrast to ibuprofen dose, there were no differences in ibuprofen use frequency or reported side effects based on haplotype. However, there are often no early signs of acute kidney injury, the most serious side effect of elevated ibuprofen exposure. These results suggest a subset of individuals with genetic variation in CYP2C8 and CYP2C9 recognize that they obtain adequate drug efficacy with lower ibuprofen doses, or take lower doses due to prior side effects. However, most (82.6%) individuals with reduced metabolism haplotypes nonetheless took recommended or higher doses, potentially putting them at increased risk for side effects.

Precision Military Medicine: Conducting a multi-site clinical utility study of genomic and lifestyle risk factors in the United States Air Force

Following several years enrolling disease-specific and otherwise healthy cohorts into the Coriell Personalized Medicine Collaborative, a prospective study aimed at evaluating the clinical utility of personal genomic information for common complex disease and pharmacogenomics, the Coriell Personalized Medicine Collaborative expanded to create a military cohort, specifically, the United States Air Force. Initial recruitment focused on Air Force Medical Service personnel and later expanded to include all Active Duty Air Force members and beneficiaries. Now in its 6th year, the study has produced a wide variety of insights, including optimal study design for military-sponsored genomic research, and discussion on genetic information sharing between and amongst Air Force study participants, civilian and military researchers, and the United States Department of Defense. Over the longer term, analyses will further contribute to the development of policies and processes relevant to clinical decision support and data sharing within the US military, and on-going work with the Air Force Medical Service sub-cohort will generate critical insights into how best to deploy useful genomic information in clinical care. Here we discuss challenges faced and critical success factors for military-civilian collaborations around genomic research.

Counselees' Perspectives of Genomic Counseling Following Online Receipt of Multiple Actionable Complex Disease and Pharmacogenomic Results: a Qualitative Research Study.

Genomic applications raise multiple challenges including the optimization of genomic counseling (GC) services as part of the results delivery process. More information on patients' motivations, preferences, and informational needs are essential to guide the development of new, more efficient practice delivery models that capitalize on the existing strengths of a limited genetic counseling workforce. Semi-structured telephone interviews were conducted with a subset of counselees from the Coriell Personalized Medicine Collaborative following online receipt of multiple personalized genomic test reports. Participants previously had either in-person GC (chronic disease cohort, n=20; mean age 60years) or telephone GC (community cohort, n=31; mean age 46.8years). Transcripts were analyzed using a Grounded Theory framework. Major themes that emerged from the interviews include 1) primary reasons for seeking GC were to clarify results, put results into perspective relative to other health-related concerns, and to receive personalized recommendations; 2) there is need for a more participant driven approach in terms of mode of GC communication (in-person, phone, video), and refining the counseling agenda pre-session; and 3) there was strong interest in the option of follow up GC. By clarifying counselees' expectations, views and desired outcomes, we have uncovered a need for a more participant-driven GC model when potentially actionable genomic results are received online.

A randomized trial Examining The Impact Of Communicating Genetic And Lifestyle Risks For Obesity.

Genetic testing for obesity is available directly to consumers, yet little is understood about its behavioral impact and its added value to nongenetic risk communication efforts based on lifestyle factors. A randomized trial examined the short-term impact of providing personalized obesity risk information, using a 2 × 2 factorial design. Participants were recruited from the Coriell Personalized Medicine Collaborative (CPMC) and randomized to receive (1) no risk information (control), (2) genetic risk, (3) lifestyle risk, or (4) combined genetic/lifestyle risks. Baseline and 3-month follow-up survey data were collected. Analyses examined the impact of risk feedback on intentions to lose weight and self-reported weight. A total of 696 participants completed the study. A significant interaction effect was observed for genetic and lifestyle information on intent to lose weight (P = 0.0150). Those who received genetic risk alone had greater intentions at follow-up, compared with controls (P = 0.0034). The impact of receiving elevated risk information on intentions varied by source and combination of risks presented. Non-elevated genetic risk did not lower intentions. No group differences were observed for self-reported weight. Genetic risk information for obesity may add value to lifestyle risk information depending on the context in which it is presented.

Coronary artery disease genetic risk awareness motivates heart health behaviors in the Coriell Personalized Medicine Collaborative

ABSTRACTObjective: The Coriell Personalized Medicine Collaborative (CPMC) research study is designed to evaluate the potential contributions of common genetic risk factors to complex disease prevention, screening, and management. Here we have focused on the impact of personalized risk reports including genetic and non-genetic risk factors for coronary artery disease (CAD) on heart health behaviors.Methods: We analyzed self-reported behavioral outcome data from 683 CPMC participants who received personalized CAD risk reports including: genetic risk, family history risk, and self-reported non-genetic risks based on smoking and diabetes status.Results: Participants with awareness of increased genetic risk for CAD were significantly more likely to report increases in heart health behaviors after viewing their personalized risk report (F-value=14.11, p-value=9.92 x 10−7). This result remained significant after controlling for BMI and gender (eta=0.58, p-value = 6.91 x 10−7).Conclusion: Our study indicates that individuals who are aware of their genetic risk for CAD may have higher motivation to increase heart health behaviors.

Encouraging physician adoption of genetic testing for precision medicine.

Exciting discoveries in genetics and genomics continue to translate into novel predictions of disease susceptibility and increasing use of targeted therapeutics. BRCA1 and BRCA2 gene testing provide timely opportunities for breast and ovarian cancer prevention strategies [1]. CYP1A1 gene testing to assess favorable therapeutic response to imatinib, a targeted therapy for chronic myelogenous leukemia, is improving survival rates [2]. The cost–effectiveness of KRAS gene testing for colorectal cancer has been demonstrated [3]. Our own research with the Coriell Personalized Medicine Collaborative (CPMC) has shown genetic information to be a motivating factor for positive health behavior change in melanoma prevention [4] and coronary artery disease prevention [ Scheinfeldt LB, Schmidlen TJ, Gharani N et al. Unpublished Data ], identified genes associated with sleep duration [5], and generated new models for genomic counseling and education [6,7]. Pharmacogenomics (PGx) to predict and optimize therapeutic response and reduce risk of adverse events is rarely utilized in the clinic despite that as of May 2015, 137 US FDA-approved drugs have PGx information in their labeling [8]. The opportunity to practice meaningful patientcentric care is here; seizing that opportunity could mean easing the chronic disease burden consuming 86% of our nation’s healthcare resources [9]. Genetic testing is a central element of precision medicine. The myriad challenges in moving diagnostics from development to clinical application are many and complex. Physician adoption is one such challenge, frequently highlighted by the startling finding that intervention discovery to utilization takes on average 17 years [10]. It is hardly surprising that genetic testing is experiencing a similar adoption timeline. Acronyms such as genome-wide association studies (GWAS), variant call format (VCF) file and SNP, terms such as haplotype and amplification or the prospect of deciphering analytic algorithms are unlikely to motivate physicians. Moreover, the range of testing available, the steady entrance of new tests and controversies such as FDA warning letters and the use of secondary findings complicate this nascent field of medicine. Do physicians perceive the adoption learning curve for genetic testing to be overwhelming? Learning curves demonstrate performance as a function of volume of training. The upward trajectory of ‘learning’ along the vertical axis before it curves right and plateaus across the horizontal axis of ‘experience’ represents the speed at which the knowledge is acquired and not ‘difficulty’ of knowledge as often supposed. In short, a steep learning curve exhibits one’s rapid movement from low to high performance. Our genetic testing learning curve is composed of six practical learning points to acquire a working knowledge of genetic testing. It begins simply: what is genetic testing? No need for a deep dive in molecular biology; physicians should understand that genetic testing is the analysis of human DNA, RNA Encouraging physician adoption of genetic testing for precision medicine

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. © 2015 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Genetic Knowledge Among Participants in the Coriell Personalized Medicine Collaborative.

Genetic literacy is essential for the effective integration of genomic information into healthcare; yet few recent studies have been conducted to assess the current state of this knowledge base. Participants in the Coriell Personalized Medicine Collaborative (CPMC), a prospective study assessing the impact of personalized genetic risk reports for complex diseases and drug response on behavior and health outcomes, completed genetic knowledge questionnaires and other surveys through an online portal. To assess the association between genetic knowledge and genetic education background, multivariate linear regression was performed. 4 062 participants completed a genetic knowledge and genetic education background questionnaire. Most were older (mean age: 50), Caucasian (90 %), female (59 %), highly educated (69 % bachelor's or higher), with annual household income over $100 000 (49 %). Mean percent correct was 76 %. Controlling for demographics revealed that health care providers, participants previously exposed to genetics, and participants with 'better than most' self-rated knowledge were significantly more likely to have a higher knowledge score (p < 0.001). Overall, genetic knowledge was high with previous genetic education experience predictive of higher genetic knowledge score. Education is likely to improve genetic literacy, an important component to expanded use of genomics in personalized medicine.

Common Genetic Risk for Melanoma Encourages Preventive Behavior Change

There is currently great interest in using genetic risk estimates for common disease in personalized healthcare. Here we assess melanoma risk-related preventive behavioral change in the context of the Coriell Personalized Medicine Collaborative (CPMC). As part of on-going reporting activities within the project, participants received a personalized risk assessment including information related to their own self-reported family history of melanoma and a genetic risk variant showing a moderate effect size (1.7, 3.0 respectively for heterozygous and homozygous individuals). Participants who opted to view their report were sent an optional outcome survey assessing risk perception and behavioral change in the months that followed. Participants that report family history risk, genetic risk, or both risk factors for melanoma were significantly more likely to increase skin cancer preventive behaviors when compared to participants with neither risk factor (ORs = 2.04, 2.79, 4.06 and p-values = 0.02, 2.86 × 10−5, 4.67 × 10−5, respectively), and we found the relationship between risk information and behavior to be partially mediated by anxiety. Genomic risk assessments appear to encourage positive behavioral change in a manner that is complementary to family history risk information and therefore may represent a useful addition to standard of care for melanoma prevention.

Genetic Testing of Children for Predisposition to Mood Disorders: Anticipating the Clinical Issues

Large-scale sequencing information may provide a basis for genetic tests for predisposition to common disorders. In this study, participants in the Coriell Personalized Medicine Collaborative (N = 53) with a personal and/or family history of Major Depressive Disorder or Bipolar Disorder were interviewed based on the Health Belief Model around hypothetical intention to test one’s children for probability of developing a mood disorder. Most participants (87 %) were interested in a hypothetical test for children that had high (“90 %”) positive predictive value, while 51 % of participants remained interested in a modestly predictive test (“20 %”). Interest was driven by beliefs about effects of test results on parenting behaviors and on discrimination. Most participants favored testing before adolescence (64 %), and were reluctant to share results with asymptomatic children before adulthood. Participants anticipated both positive and negative effects of testing on parental treatment and on children’s self-esteem. Further investigation will determine whether these findings will generalize to other complex disorders for which early intervention is possible but not clearly demonstrated to improve outcomes. More information is also needed about the effects of childhood genetic testing and sharing of results on parent–child relationships, and about the role of the child in the decision-making process.Electronic supplementary materialThe online version of this article (doi:10.1007/s10897-014-9710-y) contains supplementary material, which is available to authorized users.

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.

Design and Implementation of a Randomized Controlled Trial of Genomic Counseling for Patients with Chronic Disease

We describe the development and implementation of a randomized controlled trial to investigate the impact of genomic counseling on a cohort of patients with heart failure (HF) or hypertension (HTN), managed at a large academic medical center, the Ohio State University Wexner Medical Center (OSUWMC). Our study is built upon the existing Coriell Personalized Medicine Collaborative (CPMC®). OSUWMC patient participants with chronic disease (CD) receive eight actionable complex disease and one pharmacogenomic test report through the CPMC® web portal. Participants are randomized to either the in-person post-test genomic counseling—active arm, versus web-based only return of results—control arm. Study-specific surveys measure: (1) change in risk perception; (2) knowledge retention; (3) perceived personal control; (4) health behavior change; and, for the active arm (5), overall satisfaction with genomic counseling. This ongoing partnership has spurred creation of both infrastructure and procedures necessary for the implementation of genomics and genomic counseling in clinical care and clinical research. This included creation of a comprehensive informed consent document and processes for prospective return of actionable results for multiple complex diseases and pharmacogenomics (PGx) through a web portal, and integration of genomic data files and clinical decision support into an EPIC-based electronic medical record. We present this partnership, the infrastructure, genomic counseling approach, and the challenges that arose in the design and conduct of this ongoing trial to inform subsequent collaborative efforts and best genomic counseling practices.

A randomized trial of the clinical utility of genetic testing for obesity: Design and implementation considerations

Obesity rates in the United States have escalated in recent decades and present a major challenge in public health prevention efforts. Currently, testing to identify genetic risk for obesity is readily available through several direct-to-consumer companies. Despite the availability of this type of testing, there is a paucity of evidence as to whether providing people with personal genetic information on obesity risk will facilitate or impede desired behavioral responses. We describe the key issues in the design and implementation of a randomized controlled trial examining the clinical utility of providing genetic risk information for obesity. Participants are being recruited from the Coriell Personalized Medicine Collaborative, an ongoing, longitudinal research cohort study designed to determine the utility of personal genome information in health management and clinical decision making. The primary focus of the ancillary Obesity Risk Communication Study is to determine whether genetic risk information added value to traditional communication efforts for obesity, which are based on lifestyle risk factors. The trial employs a 2 × 2 factorial design in order to examine the effects of providing genetic risk information for obesity, alone or in combination with lifestyle risk information, on participants' psychological responses, behavioral intentions, health behaviors, and weight. The factorial design generated four experimental arms based on communication of estimated risk to participants: (1) no risk feedback (control), (2) genetic risk only, (3) lifestyle risk only, and (4) both genetic and lifestyle risk (combined). Key issues in study design pertained to the selection of algorithms to estimate lifestyle risk and determination of information to be provided to participants assigned to each experimental arm to achieve a balance between clinical standards and methodological rigor. Following the launch of the trial in September 2011, implementation challenges pertaining to low enrollment and differential attrition became apparent and required immediate attention and modifications to the study protocol. Although monitoring of these efforts is ongoing, initial observations show a doubling of enrollment and reduced attrition. The trial is evaluating the short-term impact of providing obesity risk information as participants are followed for only 3 months. This study is built upon the structure of an existing personalized medicine study wherein participants have been provided with genetic information for other diseases. This nesting in a larger study may attenuate the effects of obesity risk information and has implications for the generalizability of study findings. This randomized trial examines value of obesity genetic information, both when provided independently and when combined with lifestyle risk assessment, to motivate individuals to engage in healthy lifestyle behaviors. Study findings will guide future intervention efforts to effectively communicate genetic risk information.

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.

Translating pharmacogenomics discoveries into the clinic: an implementation framework

The implementation of pharmacogenomics-guided care has the potential to improve clinical outcomes; however, the adoption of pharmacogenomics into clinical practice remains slow. This is partly due to the lack of a standardized framework for translating key findings into diagnostic tests. A recent study describes a comprehensive system developed by the Coriell Personalized Medicine Collaborative for facilitating the translation of genomic findings into clinical practice, and its application for seven commonly prescribed drugs.See related Research paper, http://genomemedicine.com/content/5/10/93

“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.