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Smith ME, Sanderson SC, Brothers KB, Myers MF, McCormick J, Aufox S, Shrubsole MJ, Garrison NA, Mercaldo ND, Schildcrout JS, Clayton EW, Antommaria AHM, Basford M, Brilliant M, Connolly JJ, Fullerton SM, Horowitz CR, Jarvik GP, Kaufman D, Kitchner T, Li R, Ludman EJ, McCarty C, McManus V, Stallings S, Williams JL, Holm IA. Conducting a large, multi-site survey about patients' views on broad consent: challenges and solutions. BMC Med Res Methodol 2016; 16:162. [PMID: 27881091 PMCID: PMC5122167 DOI: 10.1186/s12874-016-0263-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2016] [Accepted: 11/11/2016] [Indexed: 11/28/2022] Open
Abstract
Background As biobanks play an increasing role in the genomic research that will lead to precision medicine, input from diverse and large populations of patients in a variety of health care settings will be important in order to successfully carry out such studies. One important topic is participants’ views towards consent and data sharing, especially since the 2011 Advanced Notice of Proposed Rulemaking (ANPRM), and subsequently the 2015 Notice of Proposed Rulemaking (NPRM) were issued by the Department of Health and Human Services (HHS) and Office of Science and Technology Policy (OSTP). These notices required that participants consent to research uses of their de-identified tissue samples and most clinical data, and allowing such consent be obtained in a one-time, open-ended or “broad” fashion. Conducting a survey across multiple sites provides clear advantages to either a single site survey or using a large online database, and is a potentially powerful way of understanding the views of diverse populations on this topic. Methods A workgroup of the Electronic Medical Records and Genomics (eMERGE) Network, a national consortium of 9 sites (13 separate institutions, 11 clinical centers) supported by the National Human Genome Research Institute (NHGRI) that combines DNA biorepositories with electronic medical record (EMR) systems for large-scale genetic research, conducted a survey to understand patients’ views on consent, sample and data sharing for future research, biobank governance, data protection, and return of research results. Results Working across 9 sites to design and conduct a national survey presented challenges in organization, meeting human subjects guidelines at each institution, and survey development and implementation. The challenges were met through a committee structure to address each aspect of the project with representatives from all sites. Each committee’s output was integrated into the overall survey plan. A number of site-specific issues were successfully managed allowing the survey to be developed and implemented uniformly across 11 clinical centers. Conclusions Conducting a survey across a number of institutions with different cultures and practices is a methodological and logistical challenge. With a clear infrastructure, collaborative attitudes, excellent lines of communication, and the right expertise, this can be accomplished successfully.
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Affiliation(s)
- Maureen E Smith
- Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, 645 N. Michigan Avenue, Chicago, IL, 60611, USA.
| | - Saskia C Sanderson
- Icahn School of Medicine at Mount Sinai, New York, NY, USA.,University College London, London, UK
| | - Kyle B Brothers
- University of Louisville School of Medicine, Louisville, KY, USA
| | - Melanie F Myers
- Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | | | - Sharon Aufox
- Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, 645 N. Michigan Avenue, Chicago, IL, 60611, USA
| | - Martha J Shrubsole
- Vanderbilt University Medical Center and Vanderbilt University, Nashville, TN, USA
| | | | - Nathaniel D Mercaldo
- Vanderbilt University Medical Center and Vanderbilt University, Nashville, TN, USA
| | | | - Ellen Wright Clayton
- Vanderbilt University Medical Center and Vanderbilt University, Nashville, TN, USA
| | | | - Melissa Basford
- Vanderbilt University Medical Center and Vanderbilt University, Nashville, TN, USA
| | | | - John J Connolly
- The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | | | | | - Dave Kaufman
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Terri Kitchner
- Marshfield Clinic Research Foundation, Marshfield, WI, USA
| | - Rongling Li
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | | | | | | | - Sarah Stallings
- Vanderbilt University Medical Center and Vanderbilt University, Nashville, TN, USA
| | | | - Ingrid A Holm
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
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Bush WS, Crosslin DR, Owusu‐Obeng A, Wallace J, Almoguera B, Basford MA, Bielinski SJ, Carrell DS, Connolly JJ, Crawford D, Doheny KF, Gallego CJ, Gordon AS, Keating B, Kirby J, Kitchner T, Manzi S, Mejia AR, Pan V, Perry CL, Peterson JF, Prows CA, Ralston J, Scott SA, Scrol A, Smith M, Stallings SC, Veldhuizen T, Wolf W, Volpi S, Wiley K, Li R, Manolio T, Bottinger E, Brilliant MH, Carey D, Chisholm RL, Chute CG, Haines JL, Hakonarson H, Harley JB, Holm IA, Kullo IJ, Jarvik GP, Larson EB, McCarty CA, Williams MS, Denny JC, Rasmussen‐Torvik LJ, Roden DM, Ritchie MD. Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network. Clin Pharmacol Ther 2016; 100:160-9. [PMID: 26857349 PMCID: PMC5010878 DOI: 10.1002/cpt.350] [Citation(s) in RCA: 135] [Impact Index Per Article: 16.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2015] [Revised: 01/12/2016] [Accepted: 02/04/2016] [Indexed: 12/20/2022]
Abstract
Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.
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Giampietro PF, McCarty C, Mukesh B, McKiernan F, Wilson D, Shuldiner A, Liu J, LeVasseur J, Ivacic L, Kitchner T, Ghebranious N. The role of cigarette smoking and statins in the development of postmenopausal osteoporosis: a pilot study utilizing the Marshfield Clinic Personalized Medicine Cohort. Osteoporos Int 2010; 21:467-77. [PMID: 19506792 DOI: 10.1007/s00198-009-0981-3] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2009] [Accepted: 04/23/2009] [Indexed: 01/31/2023]
Abstract
SUMMARY A cohort of postmenopausal osteoporotic females and controls with normal bone mineral density, the interleukin 6 (IL6) -634G > C (rs1800796) C allele of the promoter region showed association with osteoporosis. The lipoprotein receptor-related protein 5 (LRP5) gene showed association between C135242T C/T alleles and osteoporosis only in smokers, suggesting a role for environmental interaction. INTRODUCTION A nested case-control study within a population-based cohort was undertaken to assess the relative impact of cigarette smoking, statin use, genetic polymorphisms, and one-way interaction of these factors on development of osteoporosis in postmenopausal women. METHODS Genotyping of 14 single-nucleotide polymorphisms (SNPs) corresponding to vitamin D receptor gene, estrogen receptor 1, collagen type 1 alpha 1, IL6, transcription growth factor beta, apolipoprotein E, and LRP5 genes was performed in cases (n = 309) with osteoporosis and controls (n = 293) with normal bone mineral density drawn from a homogeneous Caucasian population. SNPs were chosen based on known functional consequences or prior evidence for association and genotyped using matrix-assisted laser desorption ionization time-of-flight technology. RESULTS Cases differed from controls relative to body mass index, age, and smoking but not statin use. After adjusting for age, the IL6 -634G > C (rs1800796) allele showed association with osteoporosis (odds ratio (OR) for CC + CG = 2.51, p = 0.0047)), independent of statin use or smoking status. On stratification for smoking, association with LRP5 C135242T (rs545382) and osteoporosis emerged (OR 2.8 in smokers for CT alleles, p = 0.03)), suggestive of potential environmental interaction. CONCLUSION Evidence suggested a role for genetic variation in IL6 and LRP5 in conferring risk for osteoporosis in Caucasian women, with the latter manifest only in smokers.
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Affiliation(s)
- P F Giampietro
- Marshfield Clinic, Department of Medical Genetic Services, 1000 North Oak Avenue, Marshfield, WI 54449, USA.
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