NEW YORK – After obtaining promising initial results in a smaller trial launched earlier this year, startup RenalytixAI has begun a new multi-center trial with academic collaborators that aims to predict long-term kidney disease risk in recovering COVID-19 patients.
The London-based firm believes that monitoring post-COVID 19 patients will also help demonstrate the clinical utility of its KidneyIntelX blood-based assay for predicting the risk of progressive decline in patients' kidney function.
RenalytixaAI's KidneyIntelX platform currently analyzes a patient's blood or urine sample to identify well-known biomarkers to predictive of kidney disease; sTNFR1, sTNRF2, and KIM1. The firm's researchers run a sample on a multiplex electrochemiluminescence assay to identify the three biomarkers, then combines data derived from a patient's electronic medical record to generate a risk score of the patient's progressive kidney decline.
As part of the new trial, the team will use KidneyIntelX to monitor recovered patients that developed acute kidney injury (AKI) while in the hospital or may potentially suffer from chronic kidney disease (CKD) in the future.
In the smaller study, called "Prediction of Major Adverse Kidney Events and Recovery," (Pred-MAKER), the researchers collected both blood and urine samples from patients hospitalized with COVID-19. The team analyzed the incidence and severity of AKI, certain risk factors associated with AKI, the proportion of patients needing dialysis, patient mortality, and how often surviving patients recovered kidney function.
Coca's team initially published a preprint regarding Pred-MAKER's results on Medrxiv, and expects to publish a finalized version of the study examining a total of 3,993 COVID-19 patients in the Journals of American Society of Nephrology later this year.
"While 46 percent (1,835) of the population acquired AKI, 17 percent of those [patients] required dialysis, and the mortality [of the AKI population] was about 50 percent," Steven Coca, RenalytixAI cofounder and associate nephrology professor at the Icahn School of Medicine at Mount Sinai, explained. "We found that about a third of patients with AKI that survived did not recover kidney function by the time of discharge."
Despite patients in the trial having a median hospital stay length of about 10 days, Coca and his colleagues realized they needed to track patients' recovery time and observe long-term kidney function post-discharge to better gauge their risk of CKD.
Coca explained that in the new trial, called "Multi-center Assessment of Survivors for Kidney Disease After COVID-19" (MASKeD-COVID), his team will collect blood and urine samples of COVID-19 survivors with AKI before they are released from the hospital. The team will analyze the samples for selected biomarkers on the KidneyIntelX instrument and attempt to re-stratify patient populations to determine who will have CKD over time versus individuals who will remain healthy.
"Severity and duration of AKI in the setting of COVID appears to more severe than 'standard AKI,'" Coca noted in an email. "Thus, we believe the risk for CKD after surviving COVID-AKI will be higher than routine AKI, and risk stratification will be needed to determine who will need to be seen by nephrologists and who needs more aggressive post-AKI care."
While RenalytixAI will continue working with Mount Sinai's recently launched COVID-19 Center of Excellence, the firm has also partnered with academic collaborators, including the Yale School of Medicine, the University of Michigan Medical School, the Johns Hopkins University Medical School, and Rutgers New Jersey Medical School in the new project.
RenalytixAI's academic collaborators will collect blood and urine samples from their health systems and send them to Mount Sinai, where Coca's team will analyze the samples using KidneyIntelX. The group aims to process samples from as many as 4,000 patients over the course of the multi-year longitudinal study.
"Now that patients have recovered from COVID-19, you can see them in person and measure markers including their IGG antibodies as part of the longitudinal assessment." Coca said. "Obviously, you'd overwhelm nephrologists since you can't follow up with every COVID-19 patient, so we want to do a re-stratification of these samples."
Coca and his colleagues will examine blood and urine biomarkers found by KidneyIntelX after three months to determine if they help predict which patients progress with CKD. Plasma biomarkers will include sTNFR1, sTNFR2, KIM1, suPAR, Angpt-1, and Angpt-2, while urine biomarkers will include KIM1, IL-18, MCP-1, YKL-40, EGF, NGAL, osteopontin, and uromodulin. The biomarkers Coca's team will examine are broadly associated with either inflammation, AKI, or CKD progression
The group will then create a risk score with KidneyIntelX based on the samples to establish a prediction for long-term outcome. Coca said that the team will watch for changes in biomarkers found by the assay in patients who return for longitudinal visits.
The researchers aim to overlap data between the Pred-MAKER and MASKeD-COVID, but Coca acknowledged that several limitations exist when attempting to merge data from both trials. Because the mortality rate of AKI-afflicted COVID-19 patients may be as high as 50 percent, the team will encounter some attrition as part of the longer-term study. In addition, patients may also choose not to undergo blood and urine draws as part of follow up visits with their nephrologists.
However, Coca pointed out that the group will be able to passively examine a patient's kidney behavior over time by accessing their electronic medical records following the initial sample collection.
Coca argued that a patient's one- to three-month follow up sample — even when adjusted for EGFR, kidney function, urine albumin, and other clinical variables — contains blood markers that add additional prognostic value "above and beyond" what the clinical variables can provide. He therefore anticipates spotting critical clinical findings from the MASKeD-COVID trial.
"Because we were in a surge phase in the past few months, we did not assay a large proportion of samples from patients … and thus the first collection will be in the post-discharge phase," Coca explained. "Ironically, the post-discharge sample is the most valuable sample for predicting [CKD] progression."
RenalytixAI also hopes that the trial will further demonstrate the real-world use of its KidneyIntelX for use in patients following their hospital discharge. The assay is currently used to report risk assessment for progressive decline in kidney function in patients with type 2 diabetes and CKD.
While the current commercial version of KidneyIntelX only looks at three protein biomarkers, Coca noted that RenalytixAI can add new inputs and features using its machine learning models and data science pipeline. Therefore, the KidneyIntelX for COVID could potentially expand to include the inputs, depending on the findings of the MASKeD-COVID trial.
Matthias Kretzler, a nephrology, computational medicine, and bioinformatics professor at the University of Michigan and MASKeD-COVID collaborator, noted that KidneyIntelX can be deployed to help predict which recovered patients may lose kidney function rapidly and need renal replacements.
RenalytixAI previously received a clinical laboratory permit from the New York State Department of Health in June that allowed the firm to offer the assay to state residents. The firm aims to start reporting patient results later this year.
Noting that there have been "some rumblings" from pharmaceutical companies about COVID-19 drug development, Coca said that the last aim of the study will be to research how distinct phenotypes occur for COVID-related kidney disease. By collecting kidney biopsies from a patient subset with persistent evidence of kidney disease, the team will perform transcriptomic and proteomic analysis using single-cell sequencing to further understand the condition.
Kretzler's team at the University of Michigan will also use the MASKeD-COVID trial to help to understand how COVID-19 can cause lasting damage to a surviving patient's organs in addition to the kidneys, including the heart, lungs, and the endocrine system.
"We are also looking at kidney and immune cell single-cell sequencing [data] of patients with COVID-19 to learn what molecular mechanisms it is using while damaging cells, and conversely, if we identify such mechanisms, how we can modify them with existing treatment," Kretzler added.
RenalytixAI previously signed an agreement with Kretlzer's team in June to further develop the KidneyIntelX assay. The firm will have access to the University of Michigan Medical School's Clinical Phenotyping Resource and Biobank Core (C-Probe), where they will examine medical data on CKD patients with a range of disease subtypes.