Project description:Precision medicine (PM) programs typically use broad consent. This approach requires maintenance of the social license and public trust. The ultimate success of PM programs will thus likely be contingent upon understanding public expectations about data sharing and establishing appropriate governance structures. There is a lack of data on public attitudes towards PM in Asia. The aim of the research was to measure the priorities and preferences of Singaporeans for sharing health-related data for PM. We used adaptive choice-based conjoint analysis (ACBC) with four attributes: uses, users, data sensitivity and consent. We recruited a representative sample of n = 1000 respondents for an in-person household survey. Of the 1000 respondents, 52% were female and majority were in the age range of 40-59 years (40%), followed by 21-39 years (33%) and 60 years and above (27%). A total of 64% were generally willing to share de-identified health data for IRB-approved research without re-consent for each study. Government agencies and public institutions were the most trusted users of data. The importance of the four attributes on respondents' willingness to share data were: users (39.5%), uses (28.5%), data sensitivity (19.5%), consent (12.6%). Most respondents found it acceptable for government agencies and hospitals to use de-identified data for health research with broad consent. Our sample was consistent with official government data on the target population with 52% being female and majority in the age range of 40-59 years (40%), followed by 21-39 years (33%) and 60 years and above (27%). While a significant body of prior research focuses on preferences for consent, our conjoint analysis found consent was the least important attribute for sharing data. Our findings suggest the social license for PM data sharing in Singapore currently supports linking health and genomic data, sharing with public institutions for health research and quality improvement; but does not support sharing with private health insurers or for private commercial use.
Project description:Precision medicine (PM) aims to revolutionise healthcare, but little is known about the role religion and spirituality might play in the ethical discourse about PM. This Perspective reports the outcomes of a knowledge exchange fora with religious authorities in Singapore about data sharing for PM. While the exchange did not identify any foundational religious objections to PM, ethical concerns were raised about the possibility for private industry to profiteer from social resources and the potential for genetic discrimination by private health insurers. According to religious authorities in Singapore, sharing PM data with private industry will require a clear public benefit and robust data governance that incorporates principles of transparency, accountability and oversight.Supplementary informationThe online version contains supplementary material available at 10.1007/s41649-021-00180-4.
Project description:miRNA expression of 6h EBSS treatment induced autophagy in Atg5 WT and KO mouse embryonic fibroblasts (MEF) were examined. For the 1st comparison, the control group is Atg5 WT MEF without EBSS treatment, the experiment group is Atg5 KO MEF without EBSS treatment; For the 2nd comparison, the control group is Atg5 WT MEF without EBSS treatment, the experiment group is Atg5 WT MEF with 6h EBSS treatment; For the 3rd comparison, the control group is Atg5 WT MEF with 6h EBSS treatment, the experiment group is Atg5 KO MEF with 6h EBSS treatment.The PIQORTM Analyzer were used for the analysis.
Project description:The Genetic Association Information Network (GAIN) Data Access Committee was established in June 2007 to provide prompt and fair access to data from six genome-wide association studies through the database of Genotypes and Phenotypes (dbGaP). Of 945 project requests received through 2011, 749 (79%) have been approved; median receipt-to-approval time decreased from 14 days in 2007 to 8 days in 2011. Over half (54%) of the proposed research uses were for GAIN-specific phenotypes; other uses were for method development (26%) and adding controls to other studies (17%). Eight data-management incidents, defined as compromises of any of the data-use conditions, occurred among nine approved users; most were procedural violations, and none violated participant confidentiality. Over 5 years of experience with GAIN data access has demonstrated substantial use of GAIN data by investigators from academic, nonprofit, and for-profit institutions with relatively few and contained policy violations. The availability of GAIN data has allowed for advances in both the understanding of the genetic underpinnings of mental-health disorders, diabetes, and psoriasis and the development and refinement of statistical methods for identifying genetic and environmental factors related to complex common diseases.