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

OBJECTIVES: 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. PARTICIPANTS AND METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Clinical pharmacogenomics: patient perspectives of pharmacogenomic testing and the incidence of actionable test results in a chronic disease cohort.

AIM: This study aimed to examine pharmacogenomic test results and patient perspectives at an academic cardiovascular medicine clinic. PATIENTS & METHODS: Test results for three common cardiovascular drug-gene tests (warfarin-CYP2C9-VKORC1, clopidogrel-CYP2C19 and simvastatin-SLCO1B1) of 208 patients in the Ohio State University-Coriell Personalized Medicine Collaborative were examined to determine the incidence of potentially actionable test results. A post-hoc, anonymous, patient survey was also conducted. RESULTS: Potentially actionable test results for at least one of the three drug-gene tests were determined in 170 (82%) patients. Survey responses (n = 134) suggested that patients generally considered their test results to be important (median of 7.5 on a 10-point scale of importance) and were interested (median of 7.3 on a 10-point scale of interest) in a Clinical Pharmacogenomic Service. CONCLUSION: Attitudes toward pharmacogenomic testing were generally favorable, and potentially actionable test results were not uncommon in this cardiovascular medicine cohort.

CYP2D6 Genetic Variation and Beta-Blocker Maintenance Dose in Patients with Heart Failure.

PURPOSE: This study examined whether a CYP2D6 polymorphism (CYP2D6*4) was related to beta-blocker maintenance dose in patients with heart failure. METHODS: Logistic regression modeling was utilized in a retrospective chart-review analysis of heart-failure patients (60% Male, 90% of European descent) to assess whether CYP2D6*4 (non-functional CYP2D6 allele present in 1 of 5 individuals of European descent) is associated with maintenance dose of carvedilol (n = 65) or metoprolol (n = 33). RESULTS: CYP2D6*4 was associated with lower maintenance dose of metoprolol (OR 0.13 [95% CI 0.02-0.75] p = 0.023), and a trend was observed between CYP2D6*4 and higher maintenance dose of carvedilol (OR 2.94 [95% CI 0.84-10.30] p = 0.093). None of the patients that carried CYP2D6*4 achieved the recommended target dose of metoprolol (200 mg/day). CONCLUSION: Consistent with the role of CYP2D6 in the metabolism of metoprolol, the tolerated maintenance dose of metoprolol was lower in CYP2D6*4 carriers compared to non-carriers. Consistent with the role of CYP2D6 in activation of carvedilol, tolerated maintenance dose of carvedilol was higher in CYP2D6*4 carriers compared to non-carriers. Further investigation is warranted to ascertain the potential of CYP2D6 as a potential predictive biomarker of beta-blocker maintenance dose in heart failure patients.

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

OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: Genetic risk information for obesity may add value to lifestyle risk information depending on the context in which it is presented.

Challenges in Translating GWAS Results to Clinical Care.

Clinical genetic testing for Mendelian disorders is standard of care in many cases; however, it is less clear to what extent and in which situations clinical genetic testing may improve preventive efforts, diagnosis and/or prognosis of complex disease. One challenge is that much of the reported research relies on tag single nucleotide polymorphisms (SNPs) to act as proxies for assumed underlying functional variants that are not yet known. Here we use coronary artery disease and melanoma as case studies to evaluate how well reported genetic risk variants tag surrounding variants across population samples in the 1000 Genomes Project Phase 3 data. We performed a simulation study where we randomly assigned a "functional" variant and evaluated how often this simulated functional variant was correctly tagged in diverse population samples. Our results indicate a relatively large error rate when generalizing increased genetic risk of complex disease across diverse population samples, even when generalizing within geographic regions. Our results further highlight the importance of including diverse populations in genome-wide association studies. Future work focused on identifying functional variants will eliminate the need for tag SNPs; however, until functional variants are known, caution should be used in the interpretation of genetic risk for complex disease using tag SNPs.

An expanded pharmacogenomics warfarin dosing table with utility in generalised dosing guidance.

Pharmacogenomics (PGx) guided warfarin dosing, using a comprehensive dosing algorithm, is expected to improve dose optimisation and lower the risk of adverse drug reactions. As a complementary tool, a simple genotype-dosing table, such as in the US Food and Drug Administration (FDA) Coumadin drug label, may be utilised for general risk assessment of likely over- or under-anticoagulation on a standard dose of warfarin. This tool may be used as part of the clinical decision support for the interpretation of genetic data, serving as a first step in the anticoagulation therapy decision making process. Here we used a publicly available warfarin dosing calculator (www.warfarindosing.org) to create an expanded gene-based warfarin dosing table, the CPMC-WD table that includes nine genetic variants in CYP2C9, VKORC1, and CYP4F2. Using two datasets, a European American cohort (EUA, n=73) and the Quebec Warfarin Cohort (QWC, n=769), we show that the CPMC-WD table more accurately predicts therapeutic dose than the FDA table (51 % vs 33 %, respectively, in the EUA, McNemar's two-sided p=0.02; 52 % vs 37 % in the QWC, p<1×10(-6)). It also outperforms both the standard of care 5 mg/day dosing (51 % vs 34 % in the EUA, p=0.04; 52 % vs 31 % in the QWC, p<1×10(-6)) as well as a clinical-only algorithm (51 % vs 38 % in the EUA, trend p=0.11; 52 % vs 45 % in the QWC, p=0.003). This table offers a valuable update to the PGx dosing guideline in the drug label.

Toward clinical genomics in everyday medicine: perspectives and recommendations.

Precision or personalized medicine through clinical genome and exome sequencing has been described by some as a revolution that could transform healthcare delivery, yet it is currently used in only a small fraction of patients, principally for the diagnosis of suspected Mendelian conditions and for targeting cancer treatments. Given the burden of illness in our society, it is of interest to ask how clinical genome and exome sequencing can be constructively integrated more broadly into the routine practice of medicine for the betterment of public health. In November 2014, 46 experts from academia, industry, policy and patient advocacy gathered in a conference sponsored by Illumina, Inc. to discuss this question, share viewpoints and propose recommendations. This perspective summarizes that work and identifies some of the obstacles and opportunities that must be considered in translating advances in genomics more widely into the practice of medicine.

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.

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.

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.

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.

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

BACKGROUND: 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. PURPOSE: 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. METHODS: 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. RESULTS: 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. LIMITATIONS: 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. CONCLUSIONS: 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.

Multiple loci associated with renal function in African Americans.

The incidence of chronic kidney disease varies by ethnic group in the USA, with African Americans displaying a two-fold higher rate than European Americans. One of the two defining variables underlying staging of chronic kidney disease is the glomerular filtration rate. Meta-analysis in individuals of European ancestry has identified 23 genetic loci associated with the estimated glomerular filtration rate (eGFR). We conducted a follow-up study of these 23 genetic loci using a population-based sample of 1,018 unrelated admixed African Americans. We included in our follow-up study two variants in APOL1 associated with end-stage kidney disease discovered by admixture mapping in admixed African Americans. To address confounding due to admixture, we estimated local ancestry at each marker and global ancestry. We performed regression analysis stratified by local ancestry and combined the resulting regression estimates across ancestry strata using an inverse variance-weighted fixed effects model. We found that 11 of the 24 loci were significantly associated with eGFR in our sample. The effect size estimates were not significantly different between the subgroups of individuals with two copies of African ancestry vs. two copies of European ancestry for any of the 11 loci. In contrast, allele frequencies were significantly different at 10 of the 11 loci. Collectively, the 11 loci, including four secondary signals revealed by conditional analyses, explained 14.2% of the phenotypic variance in eGFR, in contrast to the 1.4% explained by the 24 loci in individuals of European ancestry. Our findings provide insight into the genetic basis of variation in renal function among admixed African Americans.

Transferability and fine mapping of genome-wide associated loci for lipids in African Americans.

BACKGROUND: A recent, large genome-wide association study (GWAS) of European ancestry individuals has identified multiple genetic variants influencing serum lipids. Studies of the transferability of these associations to African Americans remain few, an important limitation given interethnic differences in serum lipids and the disproportionate burden of lipid-associated metabolic diseases among African Americans. METHODS: We attempted to evaluate the transferability of 95 lipid-associated loci recently identified in European ancestry individuals to 887 non-diabetic, unrelated African Americans from a population-based sample in the Washington, DC area. Additionally, we took advantage of the generally reduced linkage disequilibrium among African ancestry populations in comparison to European ancestry populations to fine-map replicated GWAS signals. RESULTS: We successfully replicated reported associations for 10 loci (CILP2/SF4, STARD3, LPL, CYP7A1, DOCK7/ANGPTL3, APOE, SORT1, IRS1, CETP, and UBASH3B). Through trans-ethnic fine-mapping, we were able to reduce associated regions around 75% of the loci that replicated. CONCLUSIONS: Between this study and previous work in African Americans, 40 of the 95 loci reported in a large GWAS of European ancestry individuals also influence lipid levels in African Americans. While there is now evidence that the lipid-influencing role of a number of genetic variants is observed in both European and African ancestry populations, the still considerable lack of concordance highlights the importance of continued ancestry-specific studies to elucidate the genetic underpinnings of these traits.

C-reactive protein (CRP) promoter polymorphisms influence circulating CRP levels in a genome-wide association study of African Americans.

C-reactive protein (CRP) is an acute phase reactant protein produced primarily by the liver. Circulating CRP levels are influenced by genetic and non-genetic factors, including infection and obesity. Genome-wide association studies (GWAS) provide an unbiased approach towards identifying loci influencing CRP levels. None of the six GWAS for CRP levels has been conducted in an African ancestry population. The present study aims to: (i) identify genetic variants that influence serum CRP in African Americans (AA) using a genome-wide association approach and replicate these findings in West Africans (WA), (ii) assess transferability of major signals for CRP reported in European ancestry populations (EA) to AA and (iii) use the weak linkage disequilibrium (LD) structure characteristic of African ancestry populations to fine-map the previously reported CRP locus. The discovery cohort comprised 837 unrelated AA, with the replication of significant single-nucleotide polymorphisms (SNPs) assessed in 486 WA. The association analysis was conducted with 2 366 856 genotyped and imputed SNPs under an additive genetic model with adjustment for appropriate covariates. Genome-wide and replication significances were set at P < 5 × 10(-8) and P < 0.05, respectively. Ten SNPs in (CRP pseudogene-1) CRPP1 and CRP genes were associated with serum CRP (P = 2.4 × 10(-09) to 4.3 × 10(-11)). All but one of the top-scoring SNPs associated with CRP in AA were successfully replicated in WA. CRP signals previously identified in EA samples were transferable to AAs, and we were able to fine-map this signal, reducing the region of interest from the 25 kb of LD around the locus in the HapMap CEU sample to only 8 kb in our AA sample.

Broadening research consent in the era of genome-informed medicine.

Genetic variant associations and advances in research technologies are generating an unprecedented volume of genomic data. Whole-genome sequencing will introduce even greater depth to current data sets and will propel medical research and development. Yet as one area of biomedical research evolves, another stagnates: informed consent. As presently employed, informed consent is not entirely attuned to the era of whole-genome sequencing. The greatest value of genomic data lays in its accessibility over time; the current model of informed consent restricts the use of data and does not readily accommodate prospective basic and clinical research, a priori research, or opportunities to act upon incidental findings. It also disengages the research participant from the discovery process, discouraging the provision of research results that may have clinical value to that individual. A revisited informed consent approach-the Informed Cohort Oversight Board (ICOB)-has been proven successful at consenting individuals to a model which facilitates the simultaneous construction of longitudinal data with the return of results to participants as scientific knowledge and technology allows. The opportunity to sequence once and consult often is cost-effective, encourages scientific innovation, and provides the opportunity to quickly translate genomics into better clinical care.

Managing incidental findings and research results in genomic research involving biobanks and archived data sets.

Biobanks and archived data sets collecting samples and data have become crucial engines of genetic and genomic research. Unresolved, however, is what responsibilities biobanks should shoulder to manage incidental findings and individual research results of potential health, reproductive, or personal importance to individual contributors (using "biobank" here to refer both to collections of samples and collections of data). This article reports recommendations from a 2-year project funded by the National Institutes of Health. We analyze the responsibilities involved in managing the return of incidental findings and individual research results in a biobank research system (primary research or collection sites, the biobank itself, and secondary research sites). We suggest that biobanks shoulder significant responsibility for seeing that the biobank research system addresses the return question explicitly. When reidentification of individual contributors is possible, the biobank should work to enable the biobank research system to discharge four core responsibilities to (1) clarify the criteria for evaluating findings and the roster of returnable findings, (2) analyze a particular finding in relation to this, (3) reidentify the individual contributor, and (4) recontact the contributor to offer the finding. We suggest that findings that are analytically valid, reveal an established and substantial risk of a serious health condition, and are clinically actionable should generally be offered to consenting contributors. This article specifies 10 concrete recommendations, addressing new biobanks as well as those already in existence.