When:
Tuesday, May 9, 2017
12:00 PM - 1:00 PM CT
Where: Arthur Rubloff Building, Lakeview Conference Room (11th Floor), 750 N Lake Shore Dr, Chicago, IL 60611 map it
Contact:
Lindsay Jane Varasteh
(312) 503-1997
Group: Center for Biomedical Informatics and Data Science (CBIDS)
Category: Academic
In this presentation, we will discuss findings from a study comparing individual-level data from HealthLNK—an electronic health record database created from 6 Chicago hospitals—and The Multi-Ethic Study of Atherosclerosis (MESA), a community-based cohort. We will also discuss lessons learned from participation in ADAPTABLE, the first pragmatic clinical trial funded by the Patient-Centered Outcomes Research Institute and utilizing a national, electronic data research network called PCORnet.
When:
Tuesday, May 16, 2017
12:00 PM - 1:00 PM CT
Where: Arthur Rubloff Building, Lakeview Conference Room (11th Floor), 750 N Lake Shore Dr, Chicago, IL 60611 map it
Contact:
Lindsay Jane Varasteh
(312) 503-1997
Group: Center for Biomedical Informatics and Data Science (CBIDS)
Category: Academic
In-hospital adverse events such as cardiac arrests are associated with high morbidity and mortality. They also disrupt normal workflow, as nurses, doctors, and other emergency response personnel are summoned to the patient’s room. While beneficial to the sick patient, this diversion of resources may lead to inadequate supervision of other ward patients, leading to an increase in their risk of an adverse outcome. Patient safety research within the hospital have mostly concentrated on identifying patient-level risk factors associated with development of critical illness. Non-patient factors are lesser addressed. This talk will focus on exploring whether or not the development of critical illness in a patient in a ward affects the outcome of neighboring patients.
When:
Tuesday, May 23, 2017
12:00 PM - 1:00 PM CT
Where: Arthur Rubloff Building, Lakeview Conference Room (11th Floor), 750 N Lake Shore Dr, Chicago, IL 60611 map it
Contact:
Lindsay Jane Varasteh
(312) 503-1997
Group: Center for Biomedical Informatics and Data Science (CBIDS)
Category: Academic
“Approximately 1.5 billion people worldwide are overweight or affected by obesity, and are at risk of developing type 2 diabetes, cardiovascular disease and related metabolic and inflammatory disturbances1,2. Although the mechanisms linking adiposity to associated clinical conditions are poorly understood, recent studies suggest that adiposity may influence DNA methylation3–6, a key regulator of gene expression and molecular phenotype7. Here we use epigenome-wide association to show that body mass index (BMI; a key measure of adiposity) is associated with widespread changes in DNA methylation (187 genetic loci with P < 1 × 10−7, range P = 9.2 × 10−8 to 6.0 × 10−46; n = 10,261 samples). Genetic association analyses demonstrate that the alterations in DNA methylation are predominantly the consequence of adiposity, rather than the cause. We find that methylation loci are enriched for functional genomic features in multiple tissues (P < 0.05), and show that sentinel methylation markers identify gene expression signatures at 38 loci (P < 9.0 × 10−6, range P = 5.5 × 10−6 to 6.1 × 10−35, n = 1,785 samples). The methylation loci identify genes involved in lipid and lipoprotein metabolism, substrate transport and inflammatory pathways. Finally, we show that the disturbances in DNA methylation predict future development of type 2 diabetes (relative risk per 1 standard deviation increase in methylation risk score: 2.3 (2.07–2.56); P = 1.1 × 10−54). Our results provide new insights into the biologic pathways influenced by adiposity, and may enable development of new strategies for prediction and prevention of type 2 diabetes and other adverse clinical consequences of obesity.”