The Strong Heart Study (SHS) is a multi-center, longitudinal resource designed to better understand cardiovascular disease in American Indians, identify significant risk factors, promote new research and deliver better health care. To achieve these goals, SHS data should be accessible to interested and qualified researchers, while no harm is done to the study participants who contribute their data. Thus private information in the data and the identity of the participants should be protected, and SHS tribal sovereignty and agreements that include tribal review and approval of all SHS data use requests should be respected. Our study aims to address these issues using advanced technologies and scientific computing toolkits to enable shared, but protected, data access, as well as to understand the data sharing preferences of SHS participants.
The first aim i s to develop an innovative, secure data-centric service to protect computation on SHS data according to governance practices that are acceptable to participating SHS tribes, SHS investigators, and the NIH. Specifically, we will build a system for secure analysis on protected data through a virtual private network, in which only approved operations and outputs are permitted. The proposed framework will allow researchers to easily and securely perform specific statistical analysis on SHS data and meta-analyses.
The second aim i s to develop novel federated computing models to support the SHS Coordinating Center and Genetics Center to analyze data in a distributed manner. The methods for achieving the second aim rely on new, practical federated data analysis technology. For example, in the case of vertically partitioned data, different data from the same SHS participants may be stored at different sites, such as genomic data and phenotype data that are currently stored at the SHS Genetics Center and the SHS Coordinating Center, respectively.
The third aim i s to understand the data sharing expectations and preferences of SHS participants to inform the implementation of the data sharing models.
This aim will be carried out through qualitative and quantitative methods, which include the use of individual interviews and surveys of SHS participants.

Public Health Relevance

The proposed project aims to protect privacy and facilitate shared access of clinical and genetic data of special populations. Specifically, UCSD investigators will work closely with Strong Heart Study (SHS) investigators to investigate the implementation of a shared access model so that the data may be accessed, analyzed, and results can be obtained at differently approved and summarized levels by different qualified investigators without actually sharing the original participant-level data.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Project (R01)
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Biomedical Computing and Health Informatics Study Section (BCHI)
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Pandey, Mona
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University of California, San Diego
Internal Medicine/Medicine
Schools of Medicine
La Jolla
United States
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Hindorff, Lucia A; Bonham, Vence L; Ohno-Machado, Lucila (2018) Enhancing diversity to reduce health information disparities and build an evidence base for genomic medicine. Per Med 15:403-412
Ohno-Machado, Lucila; Kim, Jihoon; Gabriel, Rodney A et al. (2018) Genomics and electronic health record systems. Hum Mol Genet 27:R48-R55