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For years, clinicians have used genomics to better inform treatment and personalize therapies. Now, Verici Dx, an immunodiagnostics company based in Tennessee (US), wants to turn that personalized medicine lens to a different field: kidney transplants.

Tens of thousands of patients receive kidney transplants every year worldwide—with many more waiting in the wings. But even after the organ is transplanted, the risk of rejection is unpredictable. Currently, accurate measurements of whether or not the recipient will be at high-risk of rejecting the transplant are lacking, leaving uncertainty as to whether the recipient will require higher doses of drugs to cope with their immune system, which mediates the rejection.

Clinicians predict rejection of kidney grafts by measuring protein concentration in the urine, or levels of a molecule called creatinine in the blood. High creatinine or protein levels could signal a need for clinicians to take a more invasive approach and biopsy the kidney to assess damage. But the need for a biopsy doesn’t always correlate with high protein or creatinine levels, explains Patti Connolly, COO at Verici Dx. “If you biopsied everyone, you would find about 20 percent are having rejection, but they have normal signal coming from urine protein or serum creatinine. Those patients may go untreated, and that rejection may simmer, risking long-term damage.”

Verici Dx is now validating their technology—which uses artificial intelligence to create RNA signatures that correlate with injury, rejection, or graft-failure—in an ongoing clinical trial across the US and Europe. With hundreds of patients enrolled, this trial will validate test performance, and will compare the RNA signature to pathology findings to support more accurate and tailored care plans for transplant recipients. 

The technology that Verici Dx developed is based off research spearheaded by the late Dr. Barbara Murphy, a renowned transplant nephrologist at Mt. Sinai School of Medicine in New York. From 2008 to 2015, Murphy and her collaborators in the US and Australia enrolled nearly 600 patients in a clinical trial to study their transcriptome for clues as to why they were rejecting kidney transplants. This study, more commonly referred to as “The GoCAR study” (Genomics of Chronic Renal Allograft Rejection), established a set of genes involved in the immune response that, using a proprietary algorithm, could predict how a patient would fare after kidney transplantation. It’s this data, Connolly says, that has formed the basis of Verici Dx’s training set for their analysis.