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Hot Topics of the Day|PHGKB
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07/22/2022

Hot Topics of the Day are picked by experts to capture the latest information and publications on public health genomics and precision health for various diseases and health topics. Sources include published scientific literature, reviews, blogs and popular press articles.

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Success Stories
CDC, 2022 Brand

Whole genome sequencing is used to generate DNA fingerprints from bacteria like Listeria. Data from WGS analyses support epidemiologic investigations and help public health investigators identify and solve more outbreaks. Check out these success stories.

As Omicron rages on, scientists have no idea what comes next
K Kupferschmidt, Science, July 19, 2022

A rapid succession of subvariants is the new normal—but a completely new variant could still emerge. Omicron’s lasting dominance has evolutionary biologists wondering what comes next. Some think it’s a sign that SARS-CoV-2’s initial frenzy of evolution is over and it, like other coronaviruses that have been with humanity much longer, is settling into a pattern of gradual evolution.

Prior Omicron infection protects against BA.4 and BA.5 variants
M Prillaman, Nature News, July 21, 2022

The Omicron BA.4 and BA.5 subvariants of SARS-CoV-2 have proven to be stealthier at evading people’s immune defences than all of their predecessors. But recent research shows that previous infection with an older variant (such as Alpha, Beta or Delta) offers some protection against reinfection with BA.4 or BA.5, and that a prior Omicron infection is substantially more effective.

Mathematical assessment of the role of waning and boosting immunity against the BA.1 Omicron variant in the United States
S Safdar et al, MEDRXIV, July 21, 2022

A blockchain-based framework to support pharmacogenetic data sharing
F Albalwy et all, The PGX journal, July 22, 2022

The successful implementation of pharmacogenetics (PGx) into clinical practice requires patient genomic data to be shared between stakeholders in multiple settings. This creates a number of barriers to widespread adoption of PGx, including privacy concerns related to the storage and movement of identifiable genomic data. Informatic solutions that support secure and equitable data access for genomic data are therefore important to PGx. Here we propose a methodology that uses smart contracts implemented on a blockchain-based framework, PGxChain, to address this issue.

Exome sequencing—one test to rule them all?
A McNeill, EJHG, July 22, 2022

Advances in genomic testing have vastly improved clinicians’ ability to identify a molecular genetic cause for both common and rare diseases. But could such testing replace more conventional diagnostic modalities entirely? Exome sequencing is a valuable diagnostic tool—but it does have limitations in the types of variant it can detect. A classic limitation of exome sequencing is limited coverage of deep intronic variants.

Age estimation from sleep studies using deep learning predicts life expectancy
AB Kjaer et al, NPJ Digital Medicine, July 21, 2022

After controlling for demographics, sleep, and health covariates, each 10-year increment in age estimate error (AEE) was associated with increased all-cause mortality rate of 29% (95% confidence interval: 20–39%). An increase from -10 to +10?years in AEE translates to an estimated decreased life expectancy of 8.7?years (95% confidence interval: 6.1–11.4?years). Greater AEE was mostly reflected in increased sleep fragmentation, suggesting this is an important biomarker of future health independent of sleep apnea.

Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis
R Adams et al, Nature Medicine, July 21, 2022

Early recognition and treatment of sepsis are linked to improved patient outcomes. Machine learning-based early warning systems may reduce the time to recognition, but few systems have undergone clinical evaluation. In this prospective, multi-site cohort study, we examined the association between patient outcomes and provider interaction with a deployed sepsis alert system called the Targeted Real-time Early Warning System (TREWS). Our findings indicate that early warning systems have the potential to identify sepsis patients early and improve patient outcomes and that sepsis patients who would benefit the most from early treatment can be identified and prioritized at the time of the alert.

Factors driving provider adoption of the TREWS machine learning-based early warning system and its effects on sepsis treatment timing
KE Henry et al, Nature Medicine, July 21, 2022

We analyzed provider interactions with a sepsis early detection tool (Targeted Real-time Early Warning System), which was deployed at five hospitals over a 2-year period. Among 9,805 retrospectively identified sepsis cases, the early detection tool achieved high sensitivity (82% of sepsis cases were identified) and a high rate of adoption: 89% of all alerts by the system were evaluated by a physician or advanced practice provider and 38% of evaluated alerts were confirmed by a provider. Patients with sepsis whose alert was confirmed by a provider within 3?h had a 1.85-h (95% CI 1.66–2.00) reduction in median time to first antibiotic order compared to patients with sepsis whose alert was either dismissed, confirmed more than 3?h after the alert or never addressed in the system.


Disclaimer: Articles listed in Hot Topics of the Day are selected by the CDC Office of Genomics and Precision Public Health to provide current awareness of the scientific 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 Clips, 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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