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Last Posted: Apr 09, 2024
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Research biobank participants attitudes towards genetic exceptionalism and health record confidentiality.
Victoria Dortenzio et al. J Community Genet 2024 3

From the abstract: "The goals of this study were to determine biobank participants’ attitudes towards genetic exceptionalism and confidentiality and whether those attitudes are related to their preference for return of genetic results. An online questionnaire was distributed to patients with an EHR and email address who had previously enrolled in the BioMe Biobank program. Most participants responded with similar levels of concern in scenarios involving the use of genetic information and other types of health information, suggesting that participants want similar protections for genetic data as other types of sensitive health information, particularly mental health and family history records. "

Multi-ancestry polygenic mechanisms of type 2 diabetes
K Smith et al, Nature Medicine, March 6, 2024

From the abstract: "Type 2 diabetes (T2D) is a multifactorial disease with substantial genetic risk, for which the underlying biological mechanisms are not fully understood. In this study, we identified multi-ancestry T2D genetic clusters by analyzing genetic data from diverse populations in 37 published T2D genome-wide association studies representing more than 1.4 million individuals. We implemented soft clustering with 650 T2D-associated genetic variants and 110 T2D-related traits, capturing known and novel T2D clusters with distinct cardiometabolic trait associations across two independent biobanks. "

Prospective study design and data analysis in UK Biobank.
Naomi E Allen et al. Sci Transl Med 2024 1 (729) eadf4428

From the abstract: " Population-based prospective studies, such as UK Biobank, are valuable for generating and testing hypotheses about the potential causes of human disease. We describe how UK Biobank’s study design, data access policies, and approaches to statistical analysis can help to minimize error and improve the interpretability of research findings, with implications for other population-based prospective studies being established worldwide."

Revolutionizing Cancer Research: The Impact of Artificial Intelligence in Digital Biobanking
C Frascarelli et al, J Per Med, September 2023

From the abstract: "As digital pathology and artificial intelligence (AI) have entered the precision medicine arena, biobanks are progressively transitioning from mere biorepositories to integrated computational databanks. Consequently, the application of AI and machine learning on these biobank datasets holds huge potential to profoundly impact cancer research. Methods. In this paper, we explore how AI and machine learning can respond to the digital evolution of biobanks with flexibility, solutions, and effective services. "

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Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.

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