glomerular filtration rate
A Race-Free Approach to Diagnosing Chronic Kidney Disease
Posted on by Dr. Francis Collins
Race has a long and tortured history in America. Though great strides have been made through the work of leaders like Dr. Martin Luther King, Jr. to build an equal and just society for all, we still have more work to do, as race continues to factor into American life where it shouldn’t. A medical case in point is a common diagnostic tool for chronic kidney disease (CKD), a condition that affects one in seven American adults and causes a gradual weakening of the kidneys that, for some, will lead to renal failure.
The diagnostic tool is a medical algorithm called estimated glomerular filtration rate (eGFR). It involves getting a blood test that measures how well the kidneys filter out a common waste product from the blood and adding in other personal factors to score how well a person’s kidneys are working. Among those factors is whether a person is Black. However, race is a complicated construct that incorporates components that go well beyond biological and genetic factors to social and cultural issues. The concern is that by lumping together Black people, the algorithm lacks diagnostic precision for individuals and could contribute to racial disparities in healthcare delivery—or even runs the risk of reifying race in a way that suggests more biological significance than it deserves.
That’s why I was pleased recently to see the results of two NIH-supported studies published in The New England Journal of Medicine that suggest a way to take race out of the kidney disease equation [1, 2]. The approach involves a new equation that swaps out one blood test for another and doesn’t ask about race.
For a variety of reasons, including socioeconomic issues and access to healthcare, CKD disproportionately affects the Black community. In fact, Blacks with the condition are also almost four times more likely than whites to develop kidney failure. That’s why Blacks with CKD must visit their doctors regularly to monitor their kidney function, and often that visit involves eGFR.
The blood test used in eGFR measures creatinine, a waste product produced from muscle. For about the past 20 years, a few points have been automatically added to the score of African Americans, based on data showing that adults who identify as Black, on average, have a higher baseline level of circulating creatinine. But adjusting the score upward toward normal function runs the risk of making the kidneys seem a bit healthier than they really are and delaying life-preserving dialysis or getting on a transplant list.
A team led by Chi-yuan Hsu, University of California, San Francisco, took a closer look at the current eGFR calculations. The researchers used long-term data from the Chronic Renal Insufficiency Cohort (CRIC) Study, an NIH-supported prospective, observational study of nearly 4,000 racially and ethnically diverse patients with CKD in the U.S. The study design specified that about 40 percent of its participants should identify as Black.
To look for race-free ways to measure kidney function, the researchers randomly selected more than 1,400 of the study’s participants to undergo a procedure that allows kidney function to be measured directly instead of being estimated based on blood tests. The goal was to develop an accurate approach to estimating GFR, the rate of fluid flow through the kidneys, from blood test results that didn’t rely on race.
Their studies showed that simply omitting race from the equation would underestimate GFR in Black study participants. The best solution, they found, was to calculate eGFR based on cystatin C, a small protein that the kidneys filter from the blood, in place of the standard creatinine. Estimation of GFR using cystatin C generated similarly accurate results but without the need to factor in race.
The second NIH-supported study led by Lesley Inker, Tufts Medical Center, Boston, MA, came to similar conclusions. They set out to develop new equations without race using data from several prior studies. They then compared the accuracy of their new eGFR equations to measured GFR in a validation set of 12 other studies, including about 4,000 participants.
Their findings show that currently used equations that include race, sex, and age overestimated measured GFR in Black Americans. However, taking race out of the equation without other adjustments underestimated measured GFR in Black people. Equations including both creatinine and cystatin C, but omitting race, were more accurate. The new equations also led to smaller estimated differences between Black and non-Black study participants.
The hope is that these findings will build momentum toward widespread adoption of cystatin C for estimating GFR. Already, a national task force has recommended immediate implementation of a new diagnostic equation that eliminates race and called for national efforts to increase the routine and timely measurement of cystatin C [3]. This will require a sea change in the standard measurements of blood chemistries in clinical and hospital labs—where creatinine is routinely measured, but cystatin C is not. As these findings are implemented into routine clinical care, let’s hope they’ll reduce health disparities by leading to more accurate and timely diagnosis, supporting the goals of precision health and encouraging treatment of CKD for all people, regardless of their race.
References:
[1] Race, genetic ancestry, and estimating kidney function in CKD. Hsu CY, Yang W, Parikh RV, Anderson AH, Chen TK, Cohen DL, He J, Mohanty MJ, Lash JP, Mills KT, Muiru AN, Parsa A, Saunders MR, Shafi T, Townsend RR, Waikar SS, Wang J, Wolf M, Tan TC, Feldman HI, Go AS; CRIC Study Investigators. N Engl J Med. 2021 Sep 23.
[2] New creatinine- and cystatin C-based equations to estimate GFR without race. Inker LA, Eneanya ND, Coresh J, Tighiouart H, Wang D, Sang Y, Crews DC, Doria A, Estrella MM, Froissart M, Grams ME, Greene T, Grubb A, Gudnason V, Gutiérrez OM, Kalil R, Karger AB, Mauer M, Navis G, Nelson RG, Poggio ED, Rodby R, Rossing P, Rule AD, Selvin E, Seegmiller JC, Shlipak MG, Torres VE, Yang W, Ballew SH,Couture SJ, Powe NR, Levey AS; Chronic Kidney Disease Epidemiology Collaboration. N Engl J Med. 2021 Sep 23.
[3] A unifying approach for GFR estimation: recommendations of the NKF-ASN Task Force on Reassessing the Inclusion of Race in Diagnosing Kidney Disease. Delgado C, Baweja M, Crews DC, Eneanya ND, Gadegbeku CA, Inker LA, Mendu ML, Miller WG, Moxey-Mims MM, Roberts GV, St Peter WL, Warfield C, Powe NR. Am J Kidney Dis. 2021 Sep 22:S0272-6386(21)00828-3.
Links:
Chronic Kidney Disease (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)
Explaining Your Kidney Test Results: A Tool for Clinical Use (NIDDK)
Chronic Renal Insufficiency Cohort Study
Chi-yuan Hsu (University of California, San Francisco)
Lesley Inker (Tufts Medical Center, Boston)
NIH Support: National Institute of Diabetes and Digestive and Kidney Diseases
Pursuing Precision Medicine for Chronic Kidney Disease
Posted on by Dr. Francis Collins
Caption: Scanning electron micrograph showing a part of one of the kidney’s glomerular filters, which are damaged in people with chronic kidney disease (CKD). The cells with the lacy cytoplasmic extensions are called podocytes.
Credit: Kretzler Lab, University of Michigan Health System, Ann Arbor
Every day, our kidneys filter more than 30 gallons of blood to allow excretion of molecules that can harm us if they build up as waste. But, for more than 20 million Americans and a growing number of people around the world, this important function is compromised by chronic kidney disease (CKD) [1]. Some CKD patients are at high risk of progressing to actual kidney failure, treatable only by dialysis or kidney transplants, while others remain generally healthy with stable kidney function for many years with minimal treatment.
The dilemma is that, even when CKD is diagnosed early, there’s been no good way to predict which individuals are at high risk for rapid progression. Those individuals would potentially benefit from more intensive measures to slow or prevent kidney failure, such as drug regimens that tightly control blood pressure and/or blood glucose. So, I’m pleased to report that NIH-funded researchers have made some progress toward developing more precise strategies for identifying individuals at high risk for kidney failure. In recent findings published in Science Translational Medicine [2], an international research team has identified a protein, easily detectable in urine, which appears to serve as an early warning sign of CKD progression.
A wide range of conditions, from diabetes to hypertension to the autoimmune disease lupus, can contribute to the gradual loss of kidney function seen in people with CKD. But research suggests that once kidney damage reaches a critical threshold, it veers off to follow a common downhill course, driven by shared cell signaling pathways and almost independent of the conditions causing it. If there was an easy, reliable way to determine when a CKD patient’s kidneys are approaching this threshold, it could open the door to better strategies for protecting them from kidney failure.
With this need in mind, a team, led by Matthias Kretzler and Wenjun Ju of the University of Michigan, began analyzing gene activity in kidney biopsy samples donated by 164 CKD patients and stored in the European Renal cDNA Bank. Specifically, the researchers looked for patterns of gene activity that corresponded with the patients’ estimated glomerular filtration rates, an indicator of renal function frequently calculated as part of a routine blood workup. Their first pass produced a list of 72 genes that displayed varying levels of activity that corresponded to differences in the patients’ estimated glomerular filtration rates. Importantly, the activity of many of those genes is also increased in cell signaling pathways thought to drive CKD progression.
Further study in two more groups of CKD patients, one from the United States and another from Europe, whittled the list down to three genes that best predicted kidney function. The researchers then zeroed in on the gene that codes for epidermal growth factor (EGF), a protein that, within the kidney, seems to be produced specifically in tubules, which are key components of the waste filtration system. Because EGF appears to enhance tubular repair after injury, researchers had a hunch that it might serve as a positive biomarker of tubular function that could be combined with existing tests of glomerular filtration to detect progression of CKD at an earlier stage.
In groups of CKD patients from the United States and China, the researchers went on to find that the amount of EGF in the urine provides an accurate measure of the protein’s activity in the kidney, making it a promising candidate for a simple urine test. In fact, CKD patients with low levels of EGF in their urine were four times more likely than those with higher EGF levels to have their kidney function worsen within a few years.
These lines of evidence suggest that, if these findings are replicated in additional studies, it may be possible to develop a simple EGF urine test to help identify which individuals with CKD would benefit the most from aggressive disease management and clinical follow-up. Researchers also plan to explore the possibility that such a urine test might prove useful in the early diagnosis of CKD, before there are any other indications of kidney disease. These are very promising new findings, but much remains to be done before we can think of applying these results as standard of care in the clinic. For example, the EGF work needs to be replicated in larger groups of CKD patients, as well as CKD patients with diabetes.
Beyond their implications for CKD, these results demonstrate the power of identifying new biologically important indicators directly from patients and then testing them in large, diverse cohorts of people. I look forward to the day when these sorts of studies will become possible on an even larger scale through our U.S. Precision Medicine Initiative Cohort.
References:
[1] National Chronic Kidney Disease Fact Sheet, 2014. Centers for Disease Control and Prevention.
[2] Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker. Ju W, Nair V, Smith S, Zhu L, Shedden K, Song PX, Mariani LH, Eichinger FH, Berthier CC, Randolph A, Lai JY, Zhou Y, Hawkins JJ, Bitzer M, Sampson MG, Thier M, Solier C, Duran-Pacheco GC, Duchateau-Nguyen G, Essioux L, Schott B, Formentini I, Magnone MC, Bobadilla M, Cohen CD, Bagnasco SM, Barisoni L, Lv J, Zhang H, Wang HY, Brosius FC, Gadegbeku CA, Kretzler M; ERCB, C-PROBE, NEPTUNE, and PKU-IgAN Consortium. Sci Transl Med. 2015 Dec 2;7(316):316ra193.
Links:
Chronic Kidney Disease: What Does it Mean to Me? (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)
Personalized Molecular Nephrology Research Laboratory (University of Michigan)
C-Probe (University of Michigan)
Precision Medicine Initiative Cohort Program (NIH)
NIH Support: National Center for Advancing Translational Sciences; National Institute of Diabetes and Digestive and Kidney Diseases
