Asthma
What's New
Last Posted: Mar 07, 2024
- Genetics of chronic respiratory disease.
Ian Sayers et al. Nat Rev Genet 2024 3 - Multivariate analysis and data mining help predict asthma exacerbations.
Stefan Mihaicuta et al. J Asthma 2023 1-16 - The infant gut virome is associated with preschool asthma risk independently of bacteria
CL Rodriguez et al, Nature Medicine, December 15, 2023 - Cord blood DNA methylation signatures associated with preeclampsia are enriched for cardiovascular pathways: insights from the VDAART trial.
Hanna M Knihtilä et al. EBioMedicine 2023 11 104890 - Return of Participants' Incidental Genetic Research Findings: Experience from a Case-Control Study of Asthma in an American Indian Community.
Lyle G Best et al. J Pers Med 2023 13(9) - Genetic relationships between high blood eosinophil count, asthma susceptibility and asthma severity.
Huashi Li et al. J Asthma 2023 1-15 - A smartphone-based application for cough counting in patients with acute asthma exacerbation.
Ji-Su Shim et al. J Thorac Dis 2023 15(7) 4053-4065 - Correlation of vitamin D receptor genotypes, Specific IgE levels and other variables with asthma control in children.
Walid Al-Qerem et al. J Asthma 2023 1-21 - Machine learning for prediction of asthma exacerbations among asthmatic patients: a systematic review and meta-analysis.
Shiqiu Xiong et al. BMC Pulm Med 2023 23(1) 278 - Australian parental perceptions of genomic newborn screening for non-communicable diseases.
Sarah Casauria et al. Front Genet 2023 141209762 - Using Machine-Learning to Predict Sleep-Disordered Breathing Diagnosis From Medical Comorbidities and Craniofacial Features.
Stephen Cokim et al. Cureus 2023 15(5) e39798 - Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations.
Niall J Lennon et al. medRxiv 2023 - Prediction of mortality risk and duration of hospitalization of COVID-19 patients with chronic comorbidities based on machine learning algorithms.
Parastoo Amiri et al. Digit Health 2023 920552076231170493 - Importance of GWAS risk loci and clinical data in predicting asthma using machine-learning approaches.
Zan-Mei Qin et al. Comb Chem High Throughput Screen 2023 - Impact of Regional Mobility on Air Quality during COVID-19 Lockdown in Mississippi, USA Using Machine Learning.
Francis Tuluri et al. Int J Environ Res Public Health 2023 20(11) - Alpha-1 antitrypsin deficiency and Pi*S and Pi*Z SERPINA1 variants are associated with asthma exacerbations.
Elena Martín-González et al. Pulmonology 2023 - Home monitoring in asthma: towards digital twins.
David Drummond et al. Curr Opin Pulm Med 2023 - Prediction of persistent chronic cough in patients with chronic cough using machine learning.
Wansu Chen et al. ERJ open research 2023 9(2) - Genetic analyses of chr11p15.5 region identify MUC5AC-MUC5B associated with asthma-related phenotypes.
Xingnan Li et al. The Journal of asthma : official journal of the Association for the Care of Asthma 2023 1-16 - Challenges in the Management of Hereditary Angioedema in Urban and Rural Settings: Results of a US Survey.
J Allen Meadows et al. Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology 2023
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About HLBS-PopOmics
HLBS-PopOmics is an online, continuously updated, searchable database of published scientific literature, CDC and NIH resources, and other materials that address the translation of genomic and other precision health discoveries into improved health care and prevention related to Heart and Vascular Diseases(H), Lung Diseases(L), Blood Diseases(B), and Sleep Disorders(S)...more
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Site Citation:
Mensah GA, Yu W, Barfield WL, Clyne M, Engelgau MM, Khoury MJ. HLBS-PopOmics: an online knowledge base to accelerate dissemination and implementation of research advances in population genomics to reduce the burden of heart, lung, blood, and sleep disorders. Genet Med. 2018 Sep 10. doi: 10.1038/s41436-018-0118-1
Disclaimer: Articles listed in the Public Health Knowledge Base are selected by Public Health Genomics Branch 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.
- Page last reviewed:Feb 1, 2024
- Page last updated:Mar 27, 2024
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