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Last Posted: Apr 08, 2024
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A phenome-wide association and Mendelian randomisation study of alcohol use variants in a diverse cohort comprising over 3 million individuals.
Mariela V Jennings et al. EBioMedicine 2024 4 105086

From the abstract: " We performed exploratory phenome-wide association studies (PheWAS) of three of the best studied protective single nucleotide polymorphisms (SNPs) in genes encoding ethanol metabolising enzymes (ADH1B: rs1229984-T, rs2066702-A; ADH1C: rs698-T) using up to 1109 health outcomes across 28 phenotypic categories (e.g., substance-use, mental health, sleep, immune, cardiovascular, metabolic) from a diverse 23andMe cohort, including European (N = 2,619,939), Latin American (N = 446,646) and African American (N = 146,776) populations to uncover new and perhaps unexpected associations. We found that that polymorphisms in genes encoding alcohol metabolising enzymes affect multiple domains of health beyond alcohol-related behaviours. Understanding the underlying mechanisms of these effects could have implications for treatments and preventative medicine."

Deep representation learning identifies associations between physical activity and sleep patterns during pregnancy and prematurity.
Neal G Ravindra et al. NPJ Digit Med 2023 9 (1) 171

From the abstract: "In this study, we use physical activity data collected using a wearable device comprising over 181,944?h of data across N?=?1083 patients. Using a new state-of-the art deep learning time-series classification architecture, we develop a ‘clock’ of healthy dynamics during pregnancy by using gestational age (GA) as a surrogate for progression of pregnancy. We also develop novel interpretability algorithms that integrate unsupervised clustering, model error analysis, feature attribution, and automated actigraphy analysis, allowing for model interpretation with respect to sleep, activity, and clinical variables. "

Brining it all together: wearable data fusion
Y Celik et al, NPJ Digital Medicine, August 17, 2023

Contemporary wearables like smartwatches are often equipped with advanced sensors and have associated algorithms to aid researchers monitor physiological outcomes like physical activity levels, sleep patterns or heart rate in free-living environments. But here’s the catch: all that valuable data is often collected separately because the sensors don’t always play nice with each other, and it’s a real challenge to put all the data together. To get the full picture, we may often need to combine different data streams.

Systematic review and meta-analysis of the effectiveness of chatbots on lifestyle behaviours
B Singh et al, NPJ Digital Medicine

Nineteen trials were included. Sample sizes ranged between 25–958, and mean participant age ranged between 9–71 years. Most interventions (n?=?15, 79%) targeted physical activity, and most trials had a low-quality rating (n?=?14, 74%). Meta-analysis results showed significant effects (all p?<?0.05) of chatbots for increasing total physical activity (SMD?=?0.28 [95% CI?=?0.16, 0.40]), daily steps (SMD?=?0.28 [95% CI?=?0.17, 0.39]), MVPA (SMD?=?0.53 [95% CI?=?0.24, 0.83]), fruit and vegetable consumption (SMD?=?0.59 [95% CI?=?0.25, 0.93]), sleep duration (SMD?=?0.44 [95% CI?=?0.32, 0.55]) and sleep quality (SMD?=?0.50 [95% CI?=?0.09, 0.90]).


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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