Diagnosis of Graft Pathology by TruGraf

Development of a Machine Learning Tool for Non-invasive Diagnosis of Liver Graft Pathology Using TruGraf

The goal of this observational study is to to identify different causes of liver diseases or damage in liver transplant patients and develop a machine learning algorithm as a non-invasive tool leveraging gene expression and patient clinical information to classify transplant liver diseases We will collect blood samples of the participants who had undergone or will undergo the liver biopsy as part of standard of care, and use this blood in TruGarf. TruGraf is a non-invasive test that measures differentially expressed genes in the blood of transplant recipients to rule out liver damage. Researcher will collect the biopsy result from the medical record and this will be compared with the TruGarf results.

Study Overview

• Status: Recruiting
• Conditions: Acute Graft Rejection
• Intervention / Treatment: Genetic: TruGraf liver gene expression

Detailed Description

Given the significant investment of healthcare resources into transplantation, it is critical to identify recipients with graft pathologies such as Acute Cellular Rejection (ACR), NASH, cholestasis, etc. at an earlier stage to implement the appropriate intervention, rather than initiating empiric treatment that could be unsafe. This project will develop a practical Machine learning-based tool based on the results of the TruGraf assay alongside clinical and laboratory data for non-invasive diagnosis of graft pathology. TruGraf is a non-invasive test that measures differentially expressed genes in the blood of transplant recipients to identify patients who are likely to be adequately immunosuppressed and, in doing so, rule out graft damage. TruGraf measures the difference in gene expression for a precise panel of specific genes that have been empirically determined to discriminate between allografts that are truly healthy (Non-ACR), and those in transplant patients that have acute rejection on biopsy (AR). Nevertheless, the exact etiology of graft damage may be difficult to discern for the transplant clinician. The clinical characteristics and history of the liver transplant recipient as well as liver enzyme patterns can provide a pre-test probability of one diagnosis being more likely than the other (Acute cellular rejection, NASH, biliary or viral disease). The proposed tool will leverage our expertise in Machine Learning tools applied to clinical and molecular data (TruGraf assay results) to enable effective clinical implementation of the TruGraf assay.

• Study Type: Observational
• Enrollment (Estimated): 471

Contacts and Locations

• Study Contact: Name: Sameera Rizvi; Phone Number: 4878 4163404800; Email: sameera.rizvi@uhn.ca

Study Locations

• Canada
  • Ontario
    • Toronto, Ontario, Canada, M5G 2N2
      • Recruiting
      • Toronto General Hospital -UHN
      • Contact: Sameera Rizvi; Phone Number: 4878 416-340-4800; Email: sameera.rizvi@uhn.ca
      • Principal Investigator: Mamatha Bhat, MD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Probability Sample

Study Population

Liver transplant patient with graft pathology

Description

Inclusion Criteria:

1. . Single-organ Liver transplant recipients
2. Male or female, age > 18 years at the time of signing informed consent.
3. Willing and able to provide informed consent.
4. Patients will be undergoing liver graft biopsy (for any reason), or have had a liver biopsy within 48 hours of consent.

Exclusion Criteria:

1. Repeat transplant
2. Recipient of multi organ transplantation
3. Any treatment for graft rejection such as IV steroids has been given before biopsy.
4. Targeted biopsies for diagnosis of malignancy.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

Liver Transplant patient will be undergoing liver graft biopsy.; Liver transplant patients will be undergoing liver graft biopsy (for any reason), or have had a liver biopsy within 48 hours of consent.

Genetic: TruGraf liver gene expression; Blood from the patients undergoing graft liver biopsy will be collected on the day of the liver biopsy, preferable prior to tissue collection or within 48 hours following the biopsy. Two specialized PaxGene tubes containing 2.5mL of blood each will be filled and will be sent to TGI laboratory in USA for processing, storage, and analysis using TGI's proprietary bioinformatics TruGraf will provide UHN with a Liver binary result: ACR or non-ACR. The results data will be batched and sent to UHN at agreed upon timepoints.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Develop and validate a ML-based algorithm	Develop and validate a ML-based algorithm that identifies major graft pathologies using liver biopsy as the reference method.	36 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Identify specific etiologies of ongoing graft damage	Identify specific etiologies of ongoing graft damage by examining TruGraf gene expression array.	36 months

Collaborators and Investigators

• Sponsor: University Health Network, Toronto
• Collaborators: Transplant Genomics, Inc.
• Investigators: Principal Investigator: Mamatha Bhat, MD, UHN

Study record dates

Study Major Dates

• Study Start (Actual): July 20, 2024
• Primary Completion (Estimated): July 20, 2027
• Study Completion (Estimated): December 30, 2027

Study Registration Dates

• First Submitted: August 13, 2024
• First Submitted That Met QC Criteria: August 13, 2024
• First Posted (Actual): August 16, 2024

Study Record Updates

• Last Update Posted (Actual): August 16, 2024
• Last Update Submitted That Met QC Criteria: August 13, 2024
• Last Verified: June 1, 2024

More Information

Terms related to this study

• Keywords: Liver transplant patients
• Other Study ID Numbers: 24-5056

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: Data will be collected from EPIC by UHN study team. Patient information will be de-identified, and each participant will be identified by a unique study number. The study investigators and UHN Ethics Board may access all PHI being collected for this study for audit/inspection purposes.
• IPD Sharing Time Frame: 36 months
• IPD Sharing Access Criteria: At the time of publication, data generated and analyzed as part of this study, including de-identified datasets and gene expression, will be made available in appropriate community-endorsed, public repositories and/or databases. In particular, gene expression data, and the corresponding sex, age, and disease type of each sample will be made available in open-access or controlled-access platforms. This access is subject to restrictions that may be imposed via existing collaboration agreements. No identifiers will leave UHN.
• IPD Sharing Supporting Information Type: SAP

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No