SALIVA TO PREDICT DISEASE RISK (version 1)
Research type
Research Study
Full title
Saliva to Predict rIsk of disease using Transcriptomics and epigenetics (SPIT)
IRAS ID
217388
Contact name
Laurence Lovat
Contact email
Sponsor organisation
University College London (UCL)
Clinicaltrials.gov Identifier
Z6364106/2017/01/40, University College London Data Protection registration
Duration of Study in the UK
3 years, 1 months, 2 days
Research summary
Summary of Research
There are numerous lifestyle-altering diseases in the UK for which patients undergo invasive tests before a diagnosis can be made. These tests are often uncomfortable and inconvenient for patients, and very costly for the NHS. They typically involve a degree of risk to patients (e.g. bleeding and bowel rupture during endoscopy; or harmful radiation exposure from CT scanning). Many of these tests yield normal results, since only a small percentage of patients being investigated actually have the disease in question. This study will focus on using analysis of symptoms, risk factors and saliva samples to predict patients’ risk of developing various diseases.
The research process will involve identifying patients who are already known to have certain diseases, plus those who are awaiting investigations to confirm those diseases. We will explain the study to patients, after which we will use a questionnaire to obtain information regarding their symptoms and risk factors for the disease. We will then collect saliva and blood samples from the patient, and when appropriate, obtain tissue samples during investigations that they are already scheduled to undergo as part of their treatment. No additional procedures will be performed on these patients, and their clinical treatment will not be affected in any way. We will perform complex genetic analysis on these samples to see if the characteristics of the patients’ saliva can accurately predict the disease in their tissues. Once we have confirmed this accuracy, we aim to create a cheap, portable and quick bedside test that uses patients’ saliva to predict their risk of disease, so that only high-risk patients can be scheduled to undergo further investigations. This will save the NHS and other healthcare systems worldwide significant amounts of money and resources, while saving patients time and inconvenience, and reducing their risk of complications from unnecessary investigations.Summary of Results
Oesophageal Arm
On this arm of the study, we aimed to use saliva in detecting oesophageal cancer. We collected a total of more than 380 samples throughout the trial. These samples were analysed in three batches with 146 oesophageal adenocarcinomas and 234 controls including those with non-dysplastic Barrett’s and without. We found that it was possible to identify patients with oesophageal cancer with an accuracy of about 70%. This finding was reproducible in the 2nd batch but less good in the 3rd batch.
Colorectal Arm
For the colorectal arm, we were unable to collect adequate samples due to COVID-19. No analysis were performed on this arm.
Crohn’s Arm
Initial batch of 192 samples have previously been collected in a group of Ashkenazi Jews of European descent. A strong predictor of the presence of Crohn’s appeared to be present. Repeated analysis were performed in two further cohorts including a further 360 patients and controls. In neither of these cohorts, we did find a reproducible signal of disease.
REC name
West Midlands - Coventry & Warwickshire Research Ethics Committee
REC reference
17/WM/0079
Date of REC Opinion
28 Feb 2017
REC opinion
Further Information Favourable Opinion