Individuals participating in biobanks and other large research projects are increasingly asked to provide broad consent for open-ended research use and widespread sharing of their biosamples and data. We assessed willingness to participate in a biobank using different consent and data sharing models, hypothesizing that willingness would be higher under more restrictive scenarios. Perceived benefits, concerns, and information needs were also assessed. In this experimental survey, individuals from 11 US healthcare systems in the Electronic Medical Records and Genomics (eMERGE) Network were randomly allocated to one of three hypothetical scenarios: tiered consent and controlled data sharing; broad consent and controlled data sharing; or broad consent and open data sharing. Of 82,328 eligible individuals, exactly 13,000 (15.8%) completed the survey. Overall, 66% (95% CI: 63%-69%) of population-weighted respondents stated they would be willing to participate in a biobank; willingness and attitudes did not differ between respondents in the three scenarios. Willingness to participate was associated with self-identified white race, higher educational attainment, lower religiosity, perceiving more research benefits, fewer concerns, and fewer information needs. Most (86%, CI: 84%-87%) participants would want to know what would happen if a researcher misused their health information; fewer (51%, CI: 47%-55%) would worry about their privacy. The concern that the use of broad consent and open data sharing could adversely affect participant recruitment is not supported by these findings. Addressing potential participants' concerns and information needs and building trust and relationships with communities may increase acceptance of broad consent and wide data sharing in biobank research.

SummaryBackground and objectives Inaccurate determination of baseline kidney function can misclassify acute kidney injury (AKI) and affect the study of AKI-related outcomes. No consensus exists on how to optimally determine baseline kidney function when multiple preadmission creatinine measurements are available.Design, setting, participants, & measurements The accuracy of commonly used methods for estimating baseline serum creatinine was compared with that of a reference standard adjudicated by a panel of board-certified nephrologists in 379 patients with AKI or CKD admitted to a tertiary referral center.Results Agreement between estimating methods and the reference standard was highest when using creatinine values measured 7-365 days before admission. During this interval, the intraclass correlation coefficient (ICC) for the mean outpatient serum creatinine level (0.91 [95% confidence interval (CI), 0.88-0.92]) was higher than the most recent outpatient (ICC, 0.84 [95% CI, 0.80-0.88]; P,0.001) and the nadir outpatient (ICC, 0.83 [95% CI, 0.76-0.87; P,0.001) serum creatinine. Using the final creatinine value from a prior inpatient admission increased the ICC of the most recent outpatient creatinine method (0.88 [95% CI,). Performance of all methods declined or was unchanged when the time interval was broadened to 2 years or included serum creatinine measured within a week of admission. ConclusionsThe mean outpatient serum creatinine measured within a year of hospitalization most closely approximates nephrologist-adjudicated serum creatinine values.

Routine integration of genotype data into drug decision-making could improve patient safety, particularly if many relevant genetic variants can be assayed simultaneously before target drug prescribing. The frequency of pharmacogenetic prescribing opportunities and the potential adverse events (AE) mitigated are unknown. We examined the frequency with which 56 medications with known outcomes influenced by variant alleles were prescribed in a cohort of 52,942 medical home patients at Vanderbilt University Medical Center. Within a five-year window, we estimated that 64.8% (95% CI: 64.4%-65.2%) of individuals were exposed to at least one medication with an established pharmacogenetic association. Using previously published results for six medications with well-characterized, severe genetically-linked AEs, we estimated that 398 events (95% CI, 225 - 583) could have been prevented with an effective preemptive genotyping program. Our results suggest that multiplexed, preemptive genotyping may represent an efficient alternative approach to current single use (“reactive”) methods and may improve safety.

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Numerous pharmacogenetic clinical guidelines and recommendations have been published, but barriers have hindered the clinical implementation of pharmacogenetics. The Translational Pharmacogenetics Program (TPP) of the NIH Pharmacogenomics Research Network was established in 2011 to catalog and contribute to the development of pharmacogenetic implementations at eight US healthcare systems, with the goal to disseminate real-world solutions for the barriers to clinical pharmacogenetic implementation. The TPP collected and normalized pharmacogenetic implementation metrics through June 2015, including gene-drug pairs implemented, interpretations of alleles and diplotypes, numbers of tests performed and actionable results, and workflow diagrams. TPP participant institutions developed diverse solutions to overcome many barriers, but the use of Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provided some consistency among the institutions. The TPP also collected some pharmacogenetic implementation outcomes (scientific, educational, financial, and informatics), which may inform healthcare systems seeking to implement their own pharmacogenetic testing programs.

Information concerning the impact of environmental factors on cystic fibrosis (CF) is limited. We conducted a cohort study to assess the impact of air pollutants in CF. The study included patients over the age of 6 years enrolled in the Cystic Fibrosis Foundation National Patient Registry in 1999 and 2000. Exposure was assessed by linking air pollution values from the Aerometric Information Retrieval System with the patients' home zip code. After adjusting for confounders, a 10 microg/m(3) rise in particulate matter (both with a median aerodynamic diameter of 10 microm (PM(10)) or less and with an aerodynamic diameter of 2.5 microm or less (PM(2.5)) was associated with an 8% (95% confidence interval [CI], 2-15%) and 21% (95% CI, 7-33%) increase in the odds of two or more exacerbations, respectively; a 10-ppb rise in ozone was associated with a 10% (95% CI, 3-17%) increase in odds of two or more exacerbations. For every increase in PM(2.5) of 10 microg/m(3), there was an associated fall in FEV(1) of 24 ml (7-40) (95% CI) after adjusting for confounders. PM(2.5)'s association with mortality did not achieve statistical significance (adjusted RR = 1.32 per 10 microg/m(3) 0.91-1.93; 95% CI). Annual average exposures to particulate air pollution was associated with an increased risk of pulmonary exacerbations and a decline in lung function, suggesting a role of environmental exposures on prognosis in CF.

Background Electrocardiographic QRS duration, a measure of cardiac intraventricular conduction, varies ~2-fold in individuals without cardiac disease. Slow conduction may promote reentrant arrhythmias. Methods and Results We performed a genome-wide association study (GWAS) to identify genomic markers of QRS duration in 5,272 individuals without cardiac disease selected from electronic medical record (EMR) algorithms at five sites in the Electronic Medical Records and Genomics (eMERGE) network. The most significant loci were evaluated within the CHARGE consortium QRS GWAS meta-analysis. Twenty-three single nucleotide polymorphisms in 5 loci, previously described by CHARGE, were replicated in the eMERGE samples; 18 SNPs were in the chromosome 3 SCN5A and SCN10A loci, where the most significant SNPs were rs1805126 in SCN5A with p=1.2×10−8 (eMERGE) and p=2.5×10−20 (CHARGE) and rs6795970 in SCN10A with p=6×10−6 (eMERGE) and p=5×10−27 (CHARGE). The other loci were in NFIA, near CDKN1A, and near C6orf204. We then performed phenome-wide association studies (PheWAS) on variants in these five loci in 13,859 European Americans to search for diagnoses associated with these markers. PheWAS identified atrial fibrillation and cardiac arrhythmias as the most common associated diagnoses with SCN10A and SCN5A variants. SCN10A variants were also associated with subsequent development of atrial fibrillation and arrhythmia in the original 5,272 “heart-healthy” study population. Conclusions We conclude that DNA biobanks coupled to EMRs provide a platform not only for GWAS but may also allow broad interrogation of the longitudinal incidence of disease associated with genetic variants. The PheWAS approach implicated sodium channel variants modulating QRS duration in subjects without cardiac disease as predictors of subsequent arrhythmias.

Aim Warfarin pharmacogenomic algorithms reduce dosing error, but perform poorly in non-European–Americans. Electronic health record (EHR) systems linked to biobanks may allow for pharmacogenomic analysis, but they have not yet been used for this purpose. Patients & methods We used BioVU, the Vanderbilt EHR-linked DNA repository, to identify European–Americans (n = 1022) and African–Americans (n = 145) on stable warfarin therapy and evaluated the effect of 15 pharmacogenetic variants on stable warfarin dose. Results Associations between variants in VKORC1, CYP2C9 and CYP4F2 with weekly dose were observed in European–Americans as well as additional variants in CYP2C9 and CALU in African–Americans. Compared with traditional 5 mg/day dosing, implementing the US FDA recommendations or the International Warfarin Pharmacogenomics Consortium (IWPC) algorithm reduced error in weekly dose in European–Americans (13.5–12.4 and 9.5 mg/week, respectively) but less so in African–Americans (15.2–15.0 and 13.8 mg/week, respectively). By further incorporating associated variants specific for European–Americans and African–Americans in an expanded algorithm, dose-prediction error reduced to 9.1 mg/week (95% CI: 8.4–9.6) in European–Americans and 12.4 mg/week (95% CI: 10.0–13.2) in African–Americans. The expanded algorithm explained 41 and 53% of dose variation in African–Americans and European–Americans, respectively, compared with 29 and 50%, respectively, for the IWPC algorithm. Implementing these predictions via dispensable pill regimens similarly reduced dosing error. Conclusion These results validate EHR-linked DNA biorepositories as real-world resources for pharmacogenomic validation and discovery.