University of Cambridge > Talks.cam > Computational and Systems Biology > Bioinformatic analysis of T-cell antigen receptors as a novel diagnostic test for coeliac disease/ gluten sensitivity

Bioinformatic analysis of T-cell antigen receptors as a novel diagnostic test for coeliac disease/ gluten sensitivity

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Aurora Gutierrez Antonio.

Coeliac disease presents with very variable symptoms, which occur when gluten is eaten. It affects at least 1% of the UK population and more than 2/3 affected individuals remain undiagnosed, often because current tests give uncertain or false negative results or are unacceptable to patients, due to the requirement prior to testing to eat gluten, which makes them ill. Coeliac disease is caused by T-cell mediated injury to the epithelial lining of the intestine, with many of the T-cells responding to gluten. Holistic analysis of the T-cell receptor nucleic acid/ amino acid sequences in patient samples allows us to compare the T-cell populations, to determine whether they are responding to similar or different immunological targets. Provided there is a sufficiently sized training set for this artificial intelligence based, bioinformatic approach, patient samples can be separated by diagnosis, regardless of whether the patient has eaten gluten prior to the test. This approach can also be used in the diagnosis of inflammatory bowel disease and a range of other immune-mediated conditions, as well as to determine immune status to antigens post-vaccination. We are currently testing its applicability to the determination of an individual’s COVID -19 immune status. Analysis of T-cell receptors is a powerful and widely used tool. The bioinformatic approaches used will be discussed.

This talk is part of the Computational and Systems Biology series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2020 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity