Skip directly to search Skip directly to A to Z list Skip directly to navigation Skip directly to page options Skip directly to site content
Diabetes PHGKB

Specific PHGKB|Diabetes PHGKB|Public Health Genomics and Precision Health Knowledge Base (PHGKB)
Effective August 1, 2024, this database was discontinued. All content will remain searchable and be preserved online for historical purposes only until 2029.

spot light Spotlight

Prediction of progression to type 1 diabetes with dynamic biomarkers and risk scores

From the abstract: "Identifying biomarkers of functional ß-cell loss is an important step in the risk stratification of type 1 diabetes. Genetic risk scores (GRS), generated by profiling an array of single nucleotide polymorphisms, are a widely used type 1 diabetes risk-prediction tool. Type 1 diabetes screening studies have relied on a combination of biochemical (autoantibody) and GRS screening methodologies for identifying individuals at high-risk of type 1 diabetes. "

Equitable implementation of a precision digital health program for glucose management in individuals with newly diagnosed type 1 diabetes

From the abstract: " Few young people with type 1 diabetes (T1D) meet glucose targets. Continuous glucose monitoring improves glycemia, but access is not equitable. We prospectively assessed the impact of a systematic and equitable digital-health-team-based care program implementing tighter glucose targets (HbA1c?<?7%), early technology use (continuous glucose monitoring starts <1?month after diagnosis) and remote patient monitoring on glycemia in young people with newly diagnosed T1D enrolled in the Teamwork, Targets, Technology, and Tight Control (4T Study)."

Polygenic scores for longitudinal prediction of incident type 2 diabetes in an ancestrally and medically diverse primary care physician network: a patient cohort study

From the article: "Genetic information, if available, could improve T2D prediction among patients lacking measured clinical risk factors. Genome-wide association studies (GWAS) have identified hundreds of unique loci associated with T2D, the results of which can be used to calculate polygenic scores (PGS) that model genetic risk independently of established clinical risk factors including family history. Previous work has evaluated how PGS can be used within healthcare systems, but analyses have been largely cross-sectional in biobanks of mostly European ancestry, limiting the generalizability of results to a more ancestrally and medically diverse US healthcare system. "

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. "


news Latest News and Publications
Study of obesity research using machine learning methods: A bibliometric and visualization analysis from 2004 to 2023. External Web Site Icon
Gong Xiao-Wei, et al. Medicine 2024 0 0. (36) e39610
Impact of Diabetes Mellitus On In-Hospital Mortality of COVID-19 Patients in Japan Since COVID-19 Became a Common Infectious Disease. External Web Site Icon
Fujita Yohei, et al. Cureus 2024 0 0. (8) e66373
IL6 receptor inhibitors: exploring the therapeutic potential across multiple diseases through drug target Mendelian randomization. External Web Site Icon
Fu Chong, et al. Frontiers in immunology 2024 0 0. 1452849
Machine learning approaches to predict the need for intensive care unit admission among Iranian COVID-19 patients based on ICD-10: A cross-sectional study. External Web Site Icon
Karimi Zahra, et al. Health science reports 2024 0 0. (9) e70041
Investigating the Research Trajectory and Future Trends of Immune Disorders in Diabetes Cardiovascular Complications: A Bibliometric Analysis Over the Past Decade Based on Big Data. External Web Site Icon
Li Xinglei, et al. Ageing research reviews 2024 0 0. 102473
Advances in Oral Exfoliative Cytology: From Cancer Diagnosis to Systemic Disease Detection. External Web Site Icon
Wang Shan, et al. Diagnostic cytopathology 2024 0 0.
Onset of Type I Diabetes Followed by Scleroderma Syndrome in a Child After the COVID-19: A Case Report. External Web Site Icon
Burlaka Ievgeniia, et al. Global pediatric health 2024 0 0. 2333794X241276356
Effect of SARS-CoV-2 Infection on Incident Diabetes by Viral Variant: Findings From the National COVID Cohort Collaborative (N3C). External Web Site Icon
Wong Rachel, et al. Diabetes care 2024 0 0.
Generalized Eruptive Keratoacanthoma (GEKA) after Pfizer mRNABNT162b2 (Comirnaty) COVID-19 Vaccination Successfully Treated with Cemiplimab. External Web Site Icon
Ilaria Proietti, et al. Viruses 2024 0 0. (8)
Health Status and COVID-19 Epidemiology in an Inland Region of Portugal: A Retrospective Study. External Web Site Icon
Lindo Jorge, et al. International journal of environmental research and public health 2024 0 0. (8)

More


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.

TOP