Points to consider for sharing variant-level information from clinical genetic testing with ClinVar

被引:22
作者
Azzariti, Danielle R. [1 ]
Riggs, Erin Rooney [2 ]
Niehaus, Annie [3 ]
Rodriguez, Laura Lyman [3 ]
Ramos, Erin M. [3 ]
Kattman, Brandi [4 ]
Landrum, Melissa J. [4 ]
Martin, Christa L. [2 ]
Rehm, Heidi L. [1 ,5 ,6 ]
机构
[1] Partners HealthCare Personalized Med, Lab Mol Med, Cambridge, MA 02139 USA
[2] Autism & Dev Med Inst, Danville, PA 17837 USA
[3] NHGRI, NIH, Bethesda, MD 20894 USA
[4] Natl Lib Med, Natl Ctr Biotechnol Informat, NIH, Bethesda, MD 20894 USA
[5] Brigham & Womens Hosp, 75 Francis St, Boston, MA 02115 USA
[6] Harvard Med Sch, Boston, MA 02115 USA
基金
美国国家卫生研究院;
关键词
D O I
10.1101/mcs.a002345
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Data sharing between laboratories, clinicians, researchers, and patients is essential for improvements and standardization in genomic medicine; encouraging genomic data sharing (GDS) is a key activity of the National Institutes of Health (NIH)-funded Clinical Genome Resource (ClinGen). The ClinGen initiative is dedicated to evaluating the clinical relevance of genes and variants for use in precision medicine and research. Currently, data originating from each of the aforementioned stakeholder groups is represented in ClinVar, a publicly available repository of genomic variation, and its relationship to human health hosted by the National Center for Biotechnology Information at the NIH. Although policies such as the 2014 NIH GDS policy are clear regarding the mandate for informed consent for broad data sharing from research participants, no clear guidance exists on the level of consent appropriate for the sharing of information obtained through clinical testing to advance knowledge. ClinGen has collaborated with ClinVar and the National Human Genome Research Institute to develop points to consider for clinical laboratories on sharing de-identified variant-level data in light of both the NIH GDS policy and the recent updates to the Common Rule. We propose specific data elements from interpreted genomic variants that are appropriate for submission to ClinVar when direct patient consent was not sought and describe situations in which obtaining informed consent is recommended.
引用
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页数:9
相关论文
共 18 条
[1]  
American Medical Association, 2013, GENOME ANAL VARIANT
[2]   Reducing patient re-identification risk for laboratory results within research datasets [J].
Atreya, Ravi V. ;
Smith, Joshua C. ;
McCoy, Allison B. ;
Malin, Bradley ;
Miller, Randolph A. .
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2013, 20 (01) :95-101
[3]   Evaluating re-identification risks with respect to the HIPAA privacy rule [J].
Benitez, Kathleen ;
Malin, Bradley .
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2010, 17 (02) :169-177
[4]   Deterministic identification of specific individuals from GWAS results [J].
Cai, Ruichu ;
Hao, Zhifeng ;
Winslett, Marianne ;
Xiao, Xiaokui ;
Yang, Yin ;
Zhang, Zhenjie ;
Zhou, Shuigeng .
BIOINFORMATICS, 2015, 31 (11) :1701-1707
[5]   The Personal Genome Project [J].
Church, G. M. .
MOLECULAR SYSTEMS BIOLOGY, 2005, 1 (1)
[6]   "Matching" consent to purpose: The example of the Matchmaker Exchange [J].
Dyke, Stephanie O. M. ;
Knoppers, Bartha M. ;
Hamosh, Ada ;
Firth, Helen V. ;
Hurles, Matthew ;
Brudno, Michael ;
Boycott, Kym M. ;
Philippakis, Anthony A. ;
Rehm, Heidi L. .
HUMAN MUTATION, 2017, 38 (10) :1281-1285
[7]   Reassessment of Genomic Sequence Variation to Harmonize Interpretation for Personalized Medicine [J].
Garber, Kathryn B. ;
Vincent, Lisa M. ;
Alexander, John J. ;
Bean, Lora J. H. ;
Bale, Sherri ;
Hegde, Madhuri .
AMERICAN JOURNAL OF HUMAN GENETICS, 2016, 99 (05) :1140-1149
[8]   Identifying Personal Genomes by Surname Inference [J].
Gymrek, Melissa ;
McGuire, Amy L. ;
Golan, David ;
Halperin, Eran ;
Erlich, Yaniv .
SCIENCE, 2013, 339 (6117) :321-324
[9]   Clinical laboratories collaborate to resolve differences in variant interpretations submitted to ClinVar [J].
Harrison, Steven M. ;
Dolinsky, Jill S. ;
Johnson, Amy E. Knight ;
Pesaran, Tina ;
Azzariti, Danielle R. ;
Bale, Sherri ;
Chao, Elizabeth C. ;
Das, Soma ;
Vincent, Lisa ;
Rehm, Heidi L. .
GENETICS IN MEDICINE, 2017, 19 (10) :1096-1104
[10]   GenomeConnect: Matchmaking Between Patients, Clinical Laboratories, and Researchers to Improve Genomic Knowledge [J].
Kirkpatrick, Brianne E. ;
Riggs, Erin Rooney ;
Azzariti, Danielle R. ;
Miller, Vanessa Rangel ;
Ledbetter, David H. ;
Miller, David T. ;
Rehm, Heidi ;
Martin, Christa Lese ;
Faucett, W. Andrew .
HUMAN MUTATION, 2015, 36 (10) :974-978