Dr. Michael Marvin is Chair of the Department of Transplantation and Liver Surgery at Geisinger Health System and Professor of Surgery at Geisinger Commonwealth School of Medicine. He is also an active transplant surgeon who believes the community of transplant clinicians as a whole may regularly over-immunosuppress patients in an effort to reduce rejection outcomes.

His interest in molecular biomarkers came about in part due to this belief, as biomarkers can help teams walk more proactive lines in comprehensively treating transplant patients. At the American Transplant Congress in 2024, Dr. Marvin presented information about the development of TruGraf and TRAC as biomarker tests and applications in transplant medicine today.

Understanding the Scope of Our Study

As part of his presentation, Dr. Marvin summarized a study conducted from March 2011 to May 2014 to develop and validate a novel blood-based molecular biomarker for subclinical acute rejection post-kidney transplant. The study involved 307 participants who met the following inclusion requirements:

  • They were adult kidney transplant recipients aged 18 or older. 
  • Patients did not have HIV and were Hep C negative.
  • Patients had, at the time of selection, seemingly stable kidney function.

The concept of the study was to take seemingly stable transplants to determine if biomarkers alone could accurately predict subclinical rejection. For this reason, the research team purposefully excluded cases likely to create outlier data.

Patients in the study underwent surveillance biopsies at 2, 6, 12, and 24 months to gather data about any potential subclinical rejection via the most accurate method at the time. This was in addition to any for-cause biopsies that were indicated by symptoms, patient history, or other factors.

At the same time, the team used gene expression profiling and donor-derived cell-free DNA quantitation to assess immune states and graft inquiry. This data was used to develop and verify the use of molecular biomarkers for subclinical rejection.

To enhance the reliability of this study, a uniform immunosuppression protocol was used across all three centers where patients participated. 

Results of the Study and Their Implications

This study and the resulting paper was the first to evaluate dd-cfDNA as a surveillance option in stable renal function patients while also examining whether there were benefits of combining dd-cfDNA and gene expression to assess the same population for subclinical rejection. 

Some critical findings from the study include:

  • Multiple abnormal gene expression profile assay results (TruGraf) within the first year after transplant were highly correlated with negative outcomes related to histology, eGFR, and graft survival. 
  • TruGraf was more sensitive to TCMR and borderline rejection than TRAC was.
  • TRAC was more sensitive to AMR than TruGraf was.
  • Subclinical acute cellular rejection tended to occur earlier within the follow-up period of the study than antibody-mediated rejection.

Dr. Marvin notes that despite the fact that TruGraf and TRAC pair well and are sensitive to different types of rejection, insurance companies often only pay for one of these tests at a time. This is an example of the challenges that clinicians can face in implementing new protocols and innovations while they wait for regulatory and payment environments to catch up.

Despite such obstacles, molecular biomarkers inspire practical changes for healthcare providers working in post-transplant environments. Specifically, integrating these diagnostic tools in routine post-transplant care allows clinicians to personalize treatment and improve patient outcomes without relying solely on more expensive and invasive biopsies. 

For example, elevated dd-cfDNA levels can indicate the presence of organ injury or transplant failure before symptoms reach a point to support a for-cause biopsy. This level of monitoring allows teams to intervene appropriately and in a more timely manner to support better allograft health. Adopting combined molecular testing approaches alongside for-cause biopsy procedures can minimize rejection risks and optimize therapy outcomes. 

TRAC and TruGraf also offer helpful tools in balancing immunosuppression—a topic of interest to Dr. Marvin. “How you balance your patient’s immunosuppression—trying to avoid infection and rejection—is a balancing act,” he says. “Diagnostics that provide great insight in the net state of immunosuppression for your patients may be helpful as we continue the challenge of post-transplant patient management.”

To understand the common danger of viruses in these patient populations, consider these figures from the CTOT-08 samples in the study.

Virus detectedPositive samples% positive samples 
ADV522.6%
BKV22811.5%
CMV1648.3%
EBV512.6%
HSV170.3%
HSV220.1%
HHV6A20.1%
HHV6B442.3%
HHV7271.4%
HPyV890.5%
JCV392.0%
VZV20.1%

While not all detected viruses require medical intervention, this is a relatively large population of positive samples and is indicative of the risks post-transplant patients may face. By leveraging biomarker tools, clinicians can assess immunosuppression and appropriately tweak dosages to ensure patients have the immune strength required to mitigate some of these issues. 

Future Directions in Transplant Research

Research published based on this study notes that biomarkers have a high negative predictive value—when compared to biopsy findings, the biomarkers were 78%-88% accurate in predicting the absence of subclinical acute rejection.[1] The tests had a positive predictive value of 47%-61%, with false positives due to factors such as inflammation. 

While these results are exciting and have definite practical applications in post-transplant treatment, as outlined by Dr. Marvin, there is room for future research and development. Focusing on how these molecular diagnostic tools increase the accuracy of treatment and further reduce the incidence of subclinical rejection can help address a decades-long challenge in kidney transplant and renal medicine. 

Another important area for research relates to enhancing the accuracy of detecting subclinical rejection with these tools. Dr. Marvin points out that clinicians must understand the nature of the tools and their limitations to apply them correctly and that combining gene expression profile assay and dd-cfDNA can help create a comprehensive picture for precise, early detection of transplant complications. In addition, the integration of other technologies, including AI, for data gathering and analysis can create a better understanding of these diagnostic strategies and how they relate to real-world patient outcomes. 

Enhancing Transplant Outcomes Through Innovation

Current 1-year graft and patient survival rates for kidney transplants is more than 95%, a vast improvement over historic performance in this discipline.[2] But that’s still not perfect, and that statistic doesn’t take into account subclinical rejection that’s found and treated, potentially creating additional physical, mental, emotional, and financial strain for patients already enduring those things. 

Ongoing research and innovation in improving transplant outcomes can help raise the bar even higher. Transplant Genomics aims to improve transplant outcomes for recipients through non-invasive treatment options. Learn more today.

Bibliography

  1. Friedewald JJ, Kurian SM, Heilman RL, et al. Development and clinical validity of a novel blood-based molecular biomarker for subclinical acute rejection following kidney transplant. American Journal of Transplantation. 2019;19(1):98-109. doi:10.1111/ajt.15011. https://pubmed.ncbi.nlm.nih.gov/29985559/
  2. Poggio ED, Augustine JJ, Arrigain S, Brennan DC, Schold JD. Long-term kidney transplant graft survival—Making progress when most needed. American Journal of Transplantation. 2021;21(8):2824-2832. doi:10.1111/ajt.16463. https://www.amjtransplant.org/article/S1600-6135(22)08680-4/fulltext