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GenomeWebinars

Mon
Dec
06
1:00 PM
US Eastern

Sponsored by Tecan

Whole-Genome Sequence and Electronic Health Record Machine Learning for Hospital Outbreak Detection: A Novel Paradigm

Approaches for hospital outbreak detection have remained unchanged for years. When an outbreak is suspected, a method to establish genetic relatedness such as whole-genome sequencing (WGS) may be performed. This approach can miss outbreaks and falsely identify suspected outbreaks that are refuted by WGS.

In late 2016, University of Pittsburgh Professor of Medicine and Epidemiology, Dr. Lee Harrison and colleagues began developing the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT), which combines WGS surveillance with data mining and machine learning of the electronic health record (EHR) to detect outbreaks and correctly identify their routes of transmission, respectively. The team found EHR machine learning useful for transmission routes that cannot be identified by traditional means. The purpose of this talk is to describe the results of using this novel approach for detecting hospital outbreaks.

Participants can expect to learn:

  • The difference between reactive WGS and WGS surveillance
  • The advantages of reactive WGS and WGS surveillance
  • How data mining of the electronic health record with machine learning can be used to identify transmission routes that are not readily apparent
  • How EDS-HAT identifies outbreaks that are missed by traditional hospital infection prevention methods

Sponsored by

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Tue
Dec
07
3:00 PM
US Eastern

Sponsored by Allelica

Polygenic Risk Scores in Clinical Care: Filling the Gap in Risk Assessments for Common Diseases

Current clinical risk models rely heavily on traditional risk factors and only rarely incorporate genetic information. However, evidence that genome-wide variation contributes substantially to disease risk is mounting, with polygenic risk scores (PRS) emerging as a robust and accurate method to assess the genetic liability of disease. This webinar will explore how integrating PRS into clinical risk assessments leads to greater precision by enabling greater numbers of people at high genetic risk of disease to be identified and treated with disease-reduction interventions.

Dr. Noura Abul-Husn, clinical director of the Institute for Genomic Health at the Icahn School of Medicine at Mount Sinai, will provide insights on how PRS can be used to increase precision in risk assessment compared to current clinical genetic screening approaches, describe diverse patients’ perspectives on the use of clinical PRS, and discuss ongoing efforts to implement clinical PRS for common diseases in diverse populations. Professor Pradeep Natarajan, director of preventive cardiology at Massachusetts General Hospital, will discuss the limitations of contemporary guidelines in identifying patients at high risk of coronary artery disease and how PRS can help address this problem. Dr. George Busby, CSO & co-founder at Allelica, will discuss software available to enable PRS analysis implementation in-house at genetics laboratories and health systems and the best practices for clinical application.

Attendees will learn about:

  • The role of PRS in estimating risk for cardiovascular and other common diseases.
  • How PRS has been used to identify and rectify limitations in current risk assessments.
  • How PRS is currently being integrated into patient care at leading healthcare institutions.

Sponsored by

Allelica
Thu
Dec
09
12:00 PM
US Eastern

Sponsored by Qiagen

Latent Tuberculosis Infection Testing, Control, and Management in Diabetes Mellitus

Tuberculosis (TB) is a leading cause of morbidity and mortality due to an infectious agent, with nearly 10 million new cases and 1.4 million deaths worldwide in 2019. Type 2 diabetes is a risk factor for the development of active TB. The global increase in type 2 diabetes, with 642 million cases predicted worldwide by 2040, poses a challenge for TB control. The elderly are an understudied and vulnerable population with a high prevalence of diabetes and are highly susceptible to TB, with 20 to 30 percent dying from the disease.

In this webinar, Blanca I. Restrepo will describe the epidemiological landscape of TB and diabetes, with contrasting observations between adults and the elderly. Most notably, the elderly have a high prevalence of type 2 diabetes, yet this is not associated with higher odds of TB in this population. Also, Restrepo and colleagues find that elderly vaccinated with the BCG vaccine at birth appear to be more protected from developing TB. These provocative findings require further testing in other cohorts. Finally, Restrepo will discuss the challenges for latent TB infection testing in the elderly and the performance of the QuantiFERON-Gold Plus TB test.

Sponsored by

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