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Health Equity PHGKB

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Last Posted: Jun 18, 2021
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Fine-scale genetic ancestry as a potential new tool for precision medicine
NP Tatonetti et al, Nature Medicine, June 18, 2021

Race and ethnicity (R/E) and genetic ancestry have long been conflated in biomedical research. The use of self-reported R/E as a proxy for genetic ancestry holds back precision medicine by confounding biological risks with those stemming from the environment, economic status, other socioeconomic factors and racism. The advent of large institutional biobanks connected to both genomic databases and electronic health records therefore represents an opportunity for disentangling the social and cultural from the ancestral.

Deaths involving COVID-19 by disability status: a retrospective analysis of 29 million adults during the first two waves of the Coronavirus pandemic in England
ML Bosworth et al, MEDRXIV, June 13, 2021

This is a cohort study of >29 million adults using data from the Office for National Statistics Public Health Data Asset. Age-adjusted analyses showed that, compared to non-disabled people, mortality involving COVID-19 was higher among both more-disabled people (HR=3.05, 95% CI: 2.98 to 3.11 in males; 3.48, 3.41 to 3.56 in females) and less-disabled people (HR=1.88, 95% CI: 1.84 to 1.92 in males; 2.03, 1.98 to 2.08 in females).

Expanding Discovery in Cardiovascular Genome-Wide Association Studies
P Natarajan et al, JAMA Cardiology, June 9, 2021

Genome-wide association studies of individuals of African ancestry typically living in the US are uncommon, yet they have yielded high-impact observations, including the discovery that PCSK9 loss-of-function mutations protect against coronary artery disease. Genome-wide association studies of individuals living in Africa are even rarer, representing approximately 0.4% of GWAS participants.

To benefit diverse groups, AI must address bias, researchers say
J Lee, Stanford Scope Blog, June 8, 2021

Artificial intelligence has the potential to transform health and medicine, from improving access to mental health care to tagging molecular details in tumor images. AI algorithms can spot patterns in massive troves of data -- even better than humans, in some cases. These technologies, however, are susceptible to bias. Biases in sex, gender and race within datasets can produce models that are poor predictors for certain groups, and the use of such biased models could exacerbate existing structural health disparities.


news Latest News and Publications
Community research collaboration to develop a promotores-based hereditary breast cancer education program for Spanish-speaking Latinas. External Web Site Icon
Almeida Rebeca et al. Health education research 2021
Choice of measurement approach for area-level social determinants of health and risk prediction model performance. External Web Site Icon
Vest J R et al. Informatics for health & social care 2021 1-12
To benefit diverse groups, AI must address bias, researchers say External Web Site Icon
J Lee, Stanford Scope Blog, June 8, 2021
Ecological Analysis of the Temporal Trends in the Association of Social Vulnerability and Race/Ethnicity with County-Level COVID-19 Incidence and Outcomes in the United States External Web Site Icon
S Islam et al, MEDRXIV, June 7, 2021
Social determinants of atrial fibrillation External Web Site Icon
UR Essien et al, Nat Rev Cardio, June 2, 2021
Conference report: inaugural Pharmacogenomics Access and Reimbursement Symposium. External Web Site Icon
Rogers Sara L et al. Pharmacogenomics 2021
Development and Validation of a Machine Learning Model Using Administrative Health Data to Predict Onset of Type 2 Diabetes. External Web Site Icon
Ravaut Mathieu et al. JAMA network open 2021 4(5) e2111315
Application of a risk stratification tool for familial hypercholesterolaemia in primary care: an observational cross-sectional study in an unselected urban population. External Web Site Icon
Carvalho Chris et al. Heart (British Cardiac Society) 2021
Heterozygous familial hypercholesterolemia: prevalence and control rates. External Web Site Icon
Polychronopoulos Georgios et al. Expert review of endocrinology & metabolism 2021 1-5
The Role of TCF7L2 in Type 2 Diabetes. External Web Site Icon
Del Bosque-Plata Laura et al. Diabetes 2021

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Disclaimer: Articles listed in the Public 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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