Kidney disease: How urine, blood tests may help predict progression

Between December 2009 and February 2015, researchers involved in the ASSESS-AKI study recruited 1,538 hospitalized adults with and without acute kidney disease (in a 1:1 ratio) from four clinical centers in North America.

Participants in the two groups were matched based on their pre-admission chronic kidney disease status, age, medical history and baseline estimated glomerular filtration rate (a measure of renal function).

The study participants had their first follow-up visit three months after being discharged from the hospital. They then returned to the study center for follow-up visits every 12 months. The researchers also maintained contact with the participants through telephone calls every 6 months.

During hospitalization and at the 3-month and 12-month follow-up visits, the researchers collected blood and urine samples, which they analyzed for biomarkers of kidney injury (urine albumin, KIM-1, and NGAL), inflammation (urine IL-18, MCP-1, YKL-40), plasma (TNFR1 and TNFR2), and tubular health (urine UMOD).

The researchers conducted statistical analyses to determine the association between biomarker changes and the development or progression of chronic kidney disease.

The study also included experiments on mice to assess how the expression of specific genes related to kidney injury, inflammation and tubular health changes at different time points after acute kidney injury.

In one group of mice, the researchers blocked blood flow to one kidney for 27 minutes, leaving the other kidney untouched (the “atrophy model”).

In another group of mice, they blocked blood flow to one kidney and surgically removed the other kidney (the “repair model”).

They then used a technique called single-cell sequencing to examine the genes in individual kidney cells and another technique called quantitative polymerase chain reaction (qPCR) to measure the gene expression in the whole kidney.

After 4.3 years, 106 study participants developed chronic kidney disease while 52 participants experienced worsening symptoms.

The researchers said they found that for every standard deviation increase in the changes of certain biomarkers (urine KIM-1, MCP-1, and plasma TNFR1) from baseline to 12 months, there was a 2-fold to 3-fold higher risk of developing chronic kidney disease.

On the other hand, an increase in urine uromodulin was associated with a 40% reduced risk of developing chronic kidney disease.

From the experiments conducted in mice, the researchers reported that certain genes related to injury and inflammation were more active in the mice with kidney atrophy compared to the mice with kidney repair, while a gene related to healthy tubular function was less active.

Dr. Katalin Susztak, a professor of medicine and director of Penn/CHOP Kidney Innovation Center in Philadelphia who was not involved in the study, told Medical News Today that the approach of testing of multiple biomarkers “gave a detailed view of kidney health, injury, and inflammation”.

Dr. Tomokazu Souma, an assistant professor in medicine specializing in nephrology at Duke University in North Carolina who was also not involved in the study, told Medical News Today that the measurement of biomarkers at multiple time points was one of the strengths of this study.

Both Susztak and Souma commended the comparison of human kidney disease progression with similar disease models in mice, which could provide more insight into the underlying biological mechanisms.

However, Souma noted that it cannot be assumed that people with acute kidney injury have any of the kidney tissue features seen in the mouse models. This would have to be confirmed by studies that examine kidney tissues from humans with acute kidney injury.

The fact that all study participants were hospitalized with acute kidney injury and may not be representative of all people with the condition limits the generalizability of the results, according to Susztak.

“In addition, while the study tracked some biomarkers, these may not be fully genome wide and capture all relevant aspects of the disease process,” she added.

Souma also felt that a direct comparison of serum creatinine (which clinicians typically use to predict the recovery from acute kidney injury) versus the blood and urine biomarkers would have been valuable.

Souma said that “this study highlights the importance of long-term follow-up of patients with [acute kidney injury] beyond the initial hospitalization course in clinical practice.”

Since most of the biomarkers investigated in this study are not routinely used in clinical practice, Souma added that “these findings do not immediately translate into the change in new routine tests.”

However, he added that “while the authors did not emphasize the finding, the changes in urinary albumin excretion (routinely tested in clinical practice for chronic kidney disease evaluation) correlate well with the renal outcome, so this measurement could be helpful in assessing patients who experienced severe [acute kidney injury] or AKI with high-risk factors for [chronic kidney disease] progression.”

Susztak observed that routine tests based on these biomarkers would potentially allow earlier detection and intervention, but “before these biomarkers can make their way into everyday clinical practice… the study’s findings need to be replicated in different settings and among diverse patient populations.”

“Even if these biomarkers successfully detect AKI to CKD transition, the course of action to be taken remains somewhat unclear,” Susztak added.

She explained that “current treatment options for AKI are limited and mainly supportive. Unless new, more effective treatment options are developed, earlier detection may not necessarily lead to better outcomes for patients.”

Both Souma and Susztak pointed out that people at risk of chronic kidney disease should avoid medications that can potentially worsen kidney function, such as non-steroidal anti-inflammatory drugs (NSAIDs).

Susztak added that people at risk of chronic kidney disease could benefit from lifestyle modifications. These include a healthy diet and regular exercise to help control blood pressure (since high blood pressure contributes to kidney failure) and limiting protein and sodium intake to decrease the workload on the kidneys.