Kidney disease is a major complication of HIV infection. Persons with HIV have substantially elevated risk of end-stage renal disease compared with HIV-uninfected individuals.1,2 Elevated creatinine, a standard measure of kidney function, is associated with adverse health outcomes in HIV infection, including mortality, cardiovascular disease, and heart failure.3–6 However, creatinine is an imperfect marker of kidney function, due to bias by age, sex, race, muscle mass, and hydration status.7,8 In HIV-infected persons, early reductions in kidney function expressed as estimated glomerular filtration rate (eGFR) may not be detected by serum creatinine levels but seem to be captured by cystatin C.9,10 In the Study of Fat Redistribution and Metabolic Change in HIV Infection, reduced kidney function (eGFR <60 mL/min per 1.73 m2) was twice as prevalent when defined by cystatin C as by creatinine and had a much stronger association with mortality risk.11
Although cystatin C may detect early reductions in GFR, substantial kidney injury may occur in HIV-infected persons before any discernible effect on kidney filtration. In some patients, kidney injury can be detected before GFR is decreased by measuring the urine albumin-to-creatinine ratio (ACR). One study found 5-fold odds of albuminuria in HIV-infected individuals compared with HIV-uninfected persons, most of whom had eGFR in the normal range.12 Both albuminuria and total urinary protein levels have been associated with mortality risk in HIV-infected persons,5,6 and albuminuria and cystatin C have complementary associations with mortality.11 However, urine albumin is a marker of glomerular injury and thus may not capture renal injury at other sites of the nephron. This is important because both HIV and its treatments may have nonglomerular effects on the kidney. Kidney biopsy studies suggest that the proximal and distal tubules are early targets of HIV.13–16 Several tubular injury markers have been developed for early detection of acute kidney injury (AKI); among these, kidney injury marker-1 (KIM-1), interleukin-18 (IL-18), and neutrophil gelatinase-associated lipocalin (NGAL) have been extensively studied in humans.17 To our knowledge, these markers have not been evaluated in longitudinal studies of HIV-infected persons.
We designed this study within the Women's Interagency HIV Study (WIHS) to test the hypothesis that markers of tubular injury could forecast the rate of subsequent eGFR decline among women at risk for kidney disease. Our primary hypotheses were that ambulatory women with and without HIV infection would have detectable damage to their kidney tubules, measurable by IL-18, KIM-1, and NGAL levels, and that the level of the injury markers would be associated independently with the rate of subsequent kidney function decline.
The WIHS is the largest, long-term, observational study of the progression of HIV in US women. The WIHS study design and methods have been described previously.18,19 In brief, 3766 women (2791 HIV-infected and 975 HIV-uninfected) were enrolled in either 1994–1995 (n = 2623) or 2001–2002 (n = 1143) from 6 US sites (Bronx, Brooklyn, Chicago, Los Angeles, San Francisco, and Washington, DC). HIV-infected women were recruited to be representative of HIV-infected women in each community. HIV-uninfected women were recruited from similar venues. Participants are interviewed and examined every 6 months. Serum specimens were stored in a −80°C freezer until biomarker measurement.
The WIHS HIV Kidney Aging study was designed as a nested cohort study to investigate the onset of kidney disease in the setting of HIV, using stored urine and serum specimens. Baseline measures were collected between October 1999 and March 2000, as this was the most recent visit that had collected and stored urine in WIHS. This study included all participants with available serum specimens during this time interval. A total of 1403 women (1032 HIV-infected and 371 HIV-uninfected) had cystatin C measured at baseline; 1197 (908 HIV-infected and 289 HIV-uninfected) had stored urine available and at least one follow-up cystatin C measure; these participants were included in the longitudinal analyses of this manuscript. WIHS was approved by the relevant institutional review boards at all study sites. This study of kidney injury was also approved by the University of California, San Francisco; San Francisco Veterans Affairs Medical Center; and Yale committees on human research.
Primary predictors in this study were urine ACR, IL-18, KIM-1, and NGAL. All urinary kidney injury biomarkers were measured at the Cincinnati Children's Hospital Medical Center Biomarker Laboratory. Urine albumin and creatinine were measured by immunoturbidimetry and colorimetric enzyme assay, respectively, using a Siemens Dimension Xpand plus HM clinical analyzer (Siemens, Munich, Germany). Urine IL-18 was measured using a commercially available ELISA kit (Medical & Biological Laboratories Co, Nagoya, Japan). The urine KIM-1 ELISA was constructed using commercially available reagents (R&D Systems, Inc, Minneapolis, MN).20 Urine NGAL was assayed using a human-specific commercially available ELISA (AntibodyShop, Grusbakken, Denmark).21 All urine specimens were in continuous storage without prior freeze-thaw. Laboratory personnel were blinded to clinical information about the participants, including HIV status, and specimens were evaluated in random order. Coefficients of variation for the urine measures were: albumin, 5.9%; creatinine, 4.1%; IL-18, 7.2%; KIM-1, 5.2%; and NGAL, 5.4%.
Primary outcomes of this study were derived from cystatin C measures from the 3 WIHS visits, which were conducted concurrently at the UCLA Clinical Immunology Research Laboratory. Cystatin C was chosen as the outcome because it is less correlated with muscle mass or health status than creatinine and may thus be less biased in the setting of HIV infection.9 Cystatin C was measured by a particle-enhanced immunoturbidimetric assay (Gentian, Moss, Norway), which has been calibrated against the new World Standard Reference material ERM-DA471/IFCC.22 Intra-assay coefficients of variation, based on 10 replicates, were <2% at serum concentrations of 0.7 and 1.1 mg/L. Inter-assay coefficients of variation were 4.4% and 3.9% at serum concentrations of 0.8 and 2.2 mg/L, respectively. We estimated GFR using the CKD-EPI equation for cystatin C (eGFRcys).22,23 Alternative analyses were conducted using serum creatinine estimates of GFR by the CKD-EPI equation. Creatinine measures were conducted at the clinical laboratories of each WIHS site at the time of collection.
As in our prior work, we truncated eGFR at 120 mL/min per 1.73 m2 because the equations have not been validated in persons with very high GFR, and higher GFR estimates are unlikely to be accurate or precise.10 We analyzed eGFR decline over the 8 years of follow-up as both continuous and dichotomous outcomes. The linear outcome was expressed as annual change in eGFR in milliliters per minute per 1.73 square meters over the entire 8-year follow-up. We dichotomized eGFR to distinguish persons with clinically meaningful rates of declining kidney function: mild (≥3% annual eGFR decline), moderate (≥5% decline), or severe (≥10% decline). We defined each dichotomized outcome by calculating the relative change in eGFR from baseline to each follow-up visit for each participant. We defined the cystatin C analyses as primary a priori because the measures were conducted concurrently and were less likely to be biased by health status. Secondary analyses were implemented with the clinical creatinine measures and are presented in the Supplemental Digital Content (see Tables and Figures, http://links.lww.com/QAI/A357).
Other covariates of interest included demographic characteristics, kidney disease risk factors, and HIV-specific risk factors obtained as part of the WIHS semiannual assessment. Specifically, the following characteristics were tested as candidate covariates in all multivariate models: age and race/ethnicity; menopause status, antihypertensive use, diabetes (fasting glucose ≥126 mg/dL, self-reported diabetes, self-reported medication, or HbA1c ≥6.5), cigarette smoking (current, former, never); systolic and diastolic blood pressure, LDL and HDL cholesterol, triglycerides, body mass index, and waist circumference. We also tested the following HIV-related characteristics: hepatitis C virus (HCV) infection (defined by detectable HCV RNA), current heroin use, current CD4 cell count, nadir CD4 cell count, history of AIDS diagnosis (including low CD4), current HIV viral load, current highly active antiretroviral therapy use, current nucleoside reverse transcriptase inhibitor use, current nonnucleoside reverse transcriptase inhibitor use, and current protease inhibitor use. There was minimal use of tenofovir at the baseline of this study. In a sensitivity analysis, we included tenofovir use during follow-up. Factors forced in the full model included age, race/ethnicity, hypertension and diabetes, current HIV viral load, current CD4 cell count, and HCV infection. All time-varying covariates in the model were time updated, except for the urine biomarkers that were collected only at baseline. After forcing the above variables, we used a stepwise backward selection with a significance level of α = 0.05 to remove candidate covariates that were not associated with the outcome. Multiple imputation with the Markov chain Monte Carlo method was used to impute missing covariates, with 5 imputations to yield ∼95% relative efficiency.24 The percentage of observations with missing covariates ranged from less than 1% to 15%.
We began our analyses by comparing the baseline characteristics of HIV-infected and HIV-uninfected participants. We first analyzed the urine injury biomarkers as continuous (log-transformed) predictors of kidney decline, but the assumption of linearity did not hold for all measures. We therefore present results with the biomarkers categorized into tertiles, with the HIV-infected and uninfected participants tertiled separately. We analyzed tertiles of ACR to facilitate comparisons of the effect sizes of ACR with the novel urine markers; however, we also dichotomized ACR at 30 mg/g, the standard clinical cut point.
The association of each injury marker with annual mean change in eGFR was assessed using linear mixed models with random intercepts and slopes.25 Interaction terms between each injury marker and time were used to determine the rate of change in eGFR. We used generalized estimating equations using a Poisson working model to account for clustering from repeated events to determine relative risks for the association of each covariate with the dichotomized kidney outcomes.
To determine whether injury markers were independently associated with kidney outcomes, multivariable models were sequentially adjusted for (1) demographics and (2) traditional kidney disease risk factors, HIV-specific risk factors, and ACR. We included ACR because it is an established marker in widespread clinical use. Therefore, any novel marker should be demonstrated to have associations independent of ACR. In our final model, we adjusted for all 4 injury markers concurrently, allowing them to compete as predictors of each kidney outcome. We also conducted a sensitivity analysis in which we forced in tenofovir use, as a time-dependent covariate, into the final model.
To account for informative lost to follow-up, we also adjusted estimates using an inverse probability weighting approach by modeling the participant's probability of having a nonmissing outcome at each visit.26 The inverse of this probability was then used as a weight applied to persons with known outcome in the multivariable regression analyses of kidney decline. All analyses were conducted using SAS version 9.2 (SAS Institute Inc, Cary, NC).
In our study, 1032 HIV-infected women and 371 HIV-uninfected women with cystatin C measured at baseline were included. More than half of women were African American or reported current smoking; one-fourth had hypertension (Table 1). HCV infection was more common in HIV-infected than HIV-uninfected women. Baseline eGFRcys was significantly lower in HIV-infected compared with uninfected women (median 89 vs. 105 mL/min per 1.73 m2, P < 0.0001). During the approximately 8-year follow-up period, rates of annual eGFRcys decline were −1.18 (95% CI: −1.29 to −1.06) in HIV-infected women and −0.97 (−1.16 to −0.79) mL/min per 1.73 m2 in HIV-uninfected women (P = 0.06 for difference). Among the HIV-infected women, eGFRcys decline was faster among those coinfected with HCV (−1.46; −1.79 to −1.14) compared with monoinfected women (−0.92; −1.07 to −0.93; P < 0.0001).
We initially examined the association of tertiles of each biomarker with the linear outcome of rate of change in eGFRcys in HIV-infected women (Fig. 1). All 4 markers were independently associated with faster eGFRcys decline in both demographic and multivariate-adjusted models. When we controlled for all 4 biomarkers simultaneously, the highest tertiles of ACR, IL-18, and KIM-1 remained independently associated with kidney function decline, whereas the association of NGAL weakened substantially (Fig. 1). The magnitude of association for the highest ACR tertile was larger than that of IL-18 or KIM-1. When we repeated analyses with eGFRcr as the outcome, the biomarker associations with eGFRcr decline were approximately half the magnitude of the eGFRcys associations (see Figure S1, Supplemental Digital Content 1,http://links.lww.com/QAI/A357). The high tertiles of ACR, KIM-1, and NGAL were independently associated with faster eGFRcr decline in single marker models, but only ACR and KIM-1 remained associated in the combined model. Adjustment for tenofovir use during follow-up had no material impact on the associations between the urine biomarkers and kidney function decline.
We next compared biomarker associations with the dichotomized eGFRcys outcomes in HIV-infected women, using similar staged adjusted models (Table 2). In fully adjusted analysis, the highest tertile of ACR was not significantly associated with any of the dichotomized outcomes relative to the lowest tertile. Dichotomized at ACR >30 mg/g, fully adjusted associations were 1.17 (0.93 to 1.47), 1.49 (1.14 to 1.95), and 1.43 (0.83 to 2.44) for 3%, 5%, and 10% decline, respectively. The highest tertile of IL-18 was progressively associated with increased risk for each endpoint. The middle tertile of IL-18 was also significantly associated with the 3% and 5% thresholds of kidney function decline. The highest tertile of KIM-1 was significantly associated with a doubling in risk for the 10% annual eGFR decline outcome, but this finding was attenuated by adjustment for IL-18. NGAL showed little association with any of these outcomes; relative risks were 1.02 (0.79 to 1.31), 0.90 (0.65 to 1.24), and 0.85 (0.44 to 1.63) for 3%, 5%, and 10% decline, respectively. In analyses based on eGFRcr (see Table S1, Supplemental Digital Content 1,http://links.lww.com/QAI/A357), significant associations were observed for the high tertile of KIM-1 with the 5% and 10% decline outcomes, and the high tertile of IL-18 was associated with the 10% decline outcome.
We also evaluated associations of biomarker tertiles with kidney function decline in HIV-uninfected women (Fig. 2). In the linear analyses, the highest tertiles of IL-18, KIM-1, and NGAL were each individually associated with more rapidly declining kidney function in demographic and individual multivariate-adjusted analyses, whereas ACR was not associated with decline. When we controlled for all 4 biomarkers simultaneously, only IL-18 remained independently associated with declining eGFRcys. In analyses using eGFRcr, the high tertiles of ACR and KIM-1 were independently associated with faster kidney function decline (see Figure S2, Supplemental Digital Content 1, http://links.lww.com/QAI/A357). For the dichotomized outcomes based on eGFRcys (Table 3), IL-18 was significantly associated with 3% annual decline in fully adjusted models, and showed a weaker, nonsignificant association with 5% decline. For the 10% annual decline endpoint, the high tertiles of IL-18 and KIM-1 were each associated with substantially elevated risk in individual marker models; but, when combined in the same model, both weakened. An ACR >30 mg/g was also significantly associated with higher risk of the 10% endpoint (2.95, 1.34 to 6.45), but not with the 3% (1.14, 0.79 to 1.66) or 5% (1.28, 0.77 to 2.13) outcomes. In eGFRcr-based dichotomized outcomes, the high tertile of KIM-1 had the strongest association with the 5% decline outcome, whereas the high tertile of IL-18 was most strongly associated with 10% decline (see Table S2, Supplemental Digital Content 1, http://links.lww.com/QAI/A357). Both associations became statistically nonsignificant when the biomarkers were adjusted for one another.
Although HIV-infected individuals have an elevated risk of CKD and end-stage renal disease,9,27 ongoing kidney tubular injury has been difficult to quantify, because albuminuria is primarily a manifestation of glomerular injury and urine proteinuria concentrations are nonspecific. We hypothesized that novel markers of kidney injury, which have been developed for the early detection of hospitalized AKI, would be detectable in HIV-infected ambulatory women and would forecast subsequent rates of declining kidney function. We found that both IL-18 and KIM-1 had strong and independent associations with both linear and dichotomized outcomes of kidney decline in HIV-infected women. Of particular interest, the relative effects of ACR and these tubular injury markers had minimal attenuating effect on one another, suggesting that these 2 categories of injury markers capture distinct patterns of kidney damage.
The findings of this study should be compared with other recent studies in this emerging literature on urine markers of kidney tubular injury. In a study from Tokyo of 424 HIV-infected persons without CKD, Ando et al28 measured a different set of tubular injury markers—N-acetyl-β-D-glucosaminidase, γ-glutamyl transpeptidase, β2-microglobulin, and α1-microglobulin. At 1 year of follow-up, eGFRcr decline was faster among participants with a higher index of tubular damage. In a general population study, the Multi-Ethnic Study of Atherosclerosis (MESA), Peralta et al.29 found that higher urine concentrations of KIM-1, but not NGAL, were associated with rapidly declining kidney function and incident CKD. In contrast, a nested case-control study from the Atherosclerosis Risk in Communities Study identified NGAL, but not KIM-1, as a significant predictor of incident CKD.30 Relative to these prior manuscripts, our study is the first to combine both HIV-infected and HIV-uninfected and to use a cohort design with prolonged follow-up.
Because urine IL-18 and KIM-1 are specific to the proximal tubule of the nephron, they may be particularly useful for detecting HIV-related kidney injury and are biological intermediates in the causal mechanisms of ischemia-reperfusion injury in the kidney. Both biomarkers are present at very low concentrations in healthy patients, and their levels increase by several folds in patients who develop AKI.31,32 IL-18 is produced by proximal tubules and is activated by caspase-1; mice deficient in caspase-1 are protected from AKI because of impaired IL-18 processing. KIM-1 is also expressed by proximal tubule cells in response to injury, and its ectodomain, shed into the tubule lumen, is detectable in urine.33 IL-18 and KIM-1 have been studied as early biomarkers in critically ill patients, perioperative patients, in diabetic nephropathy and polycystic kidney disease, and in acute and chronic kidney disease after kidney transplant.34–36 Conversely, NGAL is produced predominantly in the distal tubules.37 The stronger associations of IL-18 and KIM-1 with kidney function decline, relative to NGAL, may suggest that HIV damages the proximal tubules preferentially.
Relative to the mean annual eGFR decline of approximately 1 mL/min per 1.73 m2, the high tertiles of either IL-18 or KIM-1 were associated with approximately a 7%–8% faster rate of annual kidney function decline among the HIV-infected women. For dichotomized outcomes of rapidly declining kidney function, the high IL-18 tertile identified a group of women with approximately 40%, 90%, and 110% higher adjusted risks for the thresholds of 3%, 5%, and 10% annual decline, respectively. In the general population, rates of kidney decline of 3 mL/min per 1.73 m2 per year or 5% annual decline have been shown to have independent associations with death and cardiovascular disease.38–40
Our findings differed somewhat between our primary analyses using cystatin C as the outcome and our secondary analyses using eGFRcr. In the continuous variable model, biomarker associations with eGFRcys were stronger in magnitude than with eGFRcr. IL-18 was the tubular injury marker with the strongest associations with dichotomous eGFRcys outcomes in both HIV-infected and HIV-uninfected participants. In analyses of eGFRcr decline, KIM-1 had stronger overall associations than IL-18. Although the cystatin C and creatinine results differed, we believe that they mutually reinforce the overall finding that urine markers of tubular injury can signal risk for declining kidney function among women with or without HIV-infection.
These findings have potential implications for the clinical care of patients with HIV infection. Current strategies for monitoring the impact of HIV on the kidney rely primarily on surveillance with serum creatinine concentrations, which are an indicator of glomerular filtration rate rather than injury. The effectiveness of antiretroviral therapy for preventing kidney complications could potentially be monitored by specific kidney injury biomarkers, such as ACR, IL-18, and KIM-1. Another application of these biomarkers could be for surveillance of toxicity from antiretroviral medications such as tenofovir.41 The specimens in this study were collected in 1999–2000, before the widespread use of tenofovir. These biomarkers are already used in animal studies to detect drug toxicity.42 Future studies should evaluate whether an injury marker panel can detect reversible medication-related injury in humans. Finally, kidney injury biomarkers could be used to guide the intensity of risk-factor control, such as systolic blood pressure and glycemia targets to mitigate ongoing damage to the kidney. Thus, urine biomarkers and plasma filtration markers may be useful to capture the processes of kidney injury and functional decline in the setting of HIV infection.
There are several notable limitations in this study. First, our urine injury markers were measured only at baseline and were obtained from specimens collected over a decade before analysis. However, we believe that any protein degradation would have biased our study toward null results. Second, we used a kidney filtration marker instead of direct GFR measures; however, measured GFR is rarely used in clinical research or practice.43 Our cystatin C measures were conducted concurrently from all 3 visits and had excellent precision; however, creatinine measures were conducted in multiple laboratories and at different time periods. Furthermore, we cannot be certain whether or not our findings apply to HIV-infected or HIV-uninfected men, although we have no reason to expect different biology in men. Because tenofovir was not used extensively at the time of our urine collections, we cannot evaluate any effect of tenofovir on kidney injury. Finally, we prioritized measures in the HIV-infected participants and thus had limited statistical power among the HIV-uninfected.
In conclusion, our study has made novel observations that specific urine biomarkers for tubular injury can forecast subsequent declines in kidney function. Future research should determine whether changes in the biomarkers are accompanied by parallel changes in kidney function, and the specific risk factors for increases in each injury marker. An additional objective should be to determine the role of urine injury biomarkers for predicting kidney function decline in broader samples of the general population. Although our results are promising, the above steps in research are critical to complete before the biomarkers being used in clinical medicine.
Authors contributions: M. G. Shlipak: study concept and design, analysis and interpretation of data, drafting of the manuscript; R. Scherzer: analysis and interpretation of data, drafting of the manuscript; A. Abraham: manuscript revision, cohort development; P. C. Tien: manuscript revision and cohort development; C. Grunfeld: analysis and interpretation of data and manuscript revision; C. A. Peralta: manuscript revision; P. Devarajan: measurement of data and manuscript revision; M. Bennett: measurement of data and manuscript revision; A. W. Butch: measurement of data and manuscript revision; K. Anastos: manuscript revision and cohort development; M. H. Cohen: manuscript revision and cohort development; M. Nowicki: cohort development; A. Sharma: cohort development; M. Young: cohort development; M. J. Sarnak: manuscript revision; C. R. Parikh: analysis and interpretation of data and manuscript revision. Dr M. G. Shlipak had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
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HIV; KIM-1; NGAL; IL-18; albumin-to-creatinine ratio; cystatin C; kidney injury
Supplemental Digital Content
© 2012 Lippincott Williams & Wilkins, Inc.