New Research to be Presented at AAAAI 2022 on Hereditary Angioedema

ThinkGenetic is proud to announce a recent collaborative research project will be presented at the 2022 American Academy of Allergy, Asthma & Immunology (AAAAI) annual meeting this February 25-29th in Phoenix, Arizona.

To learn more about the event and register visit https://annualmeeting.aaaai.org/.

Presented Research

Implementation of an automated prediction scoring system to identify patients at possible increased risk for Hereditary Angioedema

Authors
Marissa Shams, MD ¹
Dawn A. Laney, MS* ¹
Dave A. Jacob, BS ²
Jingjing Yang, PhD ¹
Jessica Dronen, MS ³
Amanda Logue, MD ⁴
Ami Rosen, MS ¹
Marc Riedl, MD ⁵

Presented By
Dawn Laney, MS, CGC, CCRC is a leader in the fields of genetics and education as well as a certified genetic counselor with over 20 years of experience. In 2016, she was formally recognized as a leader in the field of rare genetic diseases by the National Organization for Rare Disorders. Dawn’s academic roles include Assistant Professor of Human Genetics, Director of the Genetic Clinical Trials Center, and Program Leader of the Lysosomal Storage Disease Center (LSDC) Program at Emory University School of Medicine. As a founder and Chief Genetic Officer of ThinkGenetic, Dawn is instrumental in designing and developing the rich, informative content that ThinkGenetic uses as our knowledge base.

Rationale
Hereditary angioedema (HAE) is a genetic condition characterized by dysregulation of the complement pathway leading to intermittent and recurrent episodes of angioedema. The goal of this project was to determine if an automated prediction scoring system can identify patients at increased risk for Hereditary Angioedema (HAE).

Methods
A prediction scoring system for HAE was created and validated using known cases of HAE from the medical literature as well as positive and negative controls from HAE-focused centers. Using key features of medical and family history, a series of logistic regression models for the five known genetic causes of HAE were created. Top variables populated the digital suspicion scoring system and were run against de-identified electronic health record (EHR) data. Patients were categorized as increased, possible, or no increased risk of HAE at two diverse sites.

The abstracts findings and results will be presented at the conference. 

References

1. Emory University
2. ThinkGenetic Foundation
3. ThinkGenetic, Inc.
4. Lafayette General Health / Ochsner
5. UC San Diego Health