Nine-Protein Plasma Signature Predicts Kidney Events and Mortality in High-Risk APOL1 Patients
- Researchers from the University of Pennsylvania have developed a proteomic risk score that can predict the progression of kidney disease in individuals of African ancestry who carry high-risk...
- The study focused on individuals with a high-risk APOL1 genotype and a preserved estimated glomerular filtration rate (eGFR), meaning their kidneys were still filtering waste effectively at the...
- The new tool, referred to as the APOL1 Proteomic Risk Score (APRS), utilizes a specific set of nine proteins found in the plasma.
Researchers from the University of Pennsylvania have developed a proteomic risk score that can predict the progression of kidney disease in individuals of African ancestry who carry high-risk genetic variants of the APOL1 gene. The findings, published in Nature Medicine on May 1, 2026, describe a nine-protein plasma signature capable of identifying those most likely to experience kidney events or mortality, even when their kidney function appears stable.
The study focused on individuals with a high-risk APOL1 genotype and a preserved estimated glomerular filtration rate (eGFR), meaning their kidneys were still filtering waste effectively at the time of testing. This early detection capability is significant because traditional clinical tools often fail to identify high-risk patients until substantial kidney damage has already occurred.
The APOL1 Proteomic Risk Score
The new tool, referred to as the APOL1 Proteomic Risk Score (APRS), utilizes a specific set of nine proteins found in the plasma. According to the researchers, this protein signature outperforms existing genetic and clinical risk tools in predicting future kidney failure and mortality.
The development of the score involved profiling the plasma proteomes of 851 participants from the Penn Medicine BioBank. All participants were of African ancestry and carried APOL1 high-risk genotypes. The cohort included 285 males and 566 females.
By identifying these markers early, clinicians may be able to implement interventions sooner. The study suggests the APRS provides a biologically plausible marker set
that can be used for early intervention and the enrichment of clinical trials, ensuring that the patients most likely to benefit from new therapies are prioritized.
Genetic Context and Kidney Risk
The APOL1 gene, which encodes apolipoprotein L1, is strongly associated with an increased risk of chronic kidney disease in people of African ancestry. Variants of this gene originally evolved to protect against trypanosomiasis, a sleeping sickness caused by parasites, but they are linked to a higher incidence of kidney failure in modern populations.
Recent research has highlighted the mechanisms behind this risk. A study published in Circulation in 2026 demonstrated that the inducible expression of APOL1 risk variants can cause hypertension and renal injury by triggering cellular stress and vascular dysfunction.
While the genetic risk is well-documented, not every individual with the high-risk APOL1 genotype will develop kidney disease. The APRS aims to bridge this gap by identifying the specific protein expressions that signal the transition from a genetic predisposition to active disease progression.
Clinical Implications and Future Use
The ability to predict kidney failure years before clinical symptoms appear allows for a shift toward preventative nephrology. Current standard tools, such as the Kidney Failure Risk Equation, provide a baseline for prediction, but the proteomic approach offers a more personalized assessment based on the patient’s current biological state.

This discovery aligns with ongoing efforts to develop targeted therapies for APOL1-mediated kidney disease. For example, previous clinical trials have evaluated inaxaplin, a therapeutic strategy that specifically targets the APOL1 pathway to reduce proteinuric kidney disease.
The use of the APRS could refine how these therapies are administered by identifying the specific window of time when intervention is most critical. By screening for the nine-protein signature, physicians may better determine which patients require aggressive monitoring or early enrollment in clinical trials for new medications.
