Abstract
Background
Indoxyl sulfate (IS), a protein-bound uremic toxin derived from tryptophan metabolism, accumulates in patients with chronic kidney disease (CKD) and contributes to renal, vascular, and systemic injury. Conventional detection using LC–MS/MS is accurate but resource-intensive. To simplify IS quantification, Leadgene Biomedical developed a competitive enzyme-linked immunosorbent assay (ELISA) that employs anti-IS monoclonal antibodies capable of recognizing both free and protein-bound IS forms.
Methods
Serum samples from 188 participants –classified as low-risk (healthy or CKD ≤ stage 2, n = 79) and high-risk (CKD stage G3a and above (eGFR <60 mL/min/1.73 m2, n = 109) – were analyzed using the Leadgene® IS ELISA Kit. Diagnostic performance was assessed through ROC analysis, precision by nested-ANOVA (total %CV < 10%), and accuracy by comparison with LC–MS/MS.
Results
Mean age was higher in the high-risk group (65.17 ± 11.66 vs 57.96 ± 13.88 years, p < 0.001). The ELISA demonstrated excellent diagnostic performance with an area under the curve of 0.96 and an optimal cutoff of 2.233 µg/mL, yielding sensitivity 0.872 (95% confidence interval (CI) 0.816–0.912) and specificity 0.940 (95% CI 0.856–0.977). The Pearson correlation coefficient between the ELISA and LC-MS/MS results was 0.964, confirming high analytical concordance.
Conclusion
The Leadgene® IS ELISA Kit provides a rapid and accessible platform for serum indoxyl sulfate quantification with validated analytical performance and significant association with higher-risk CKD classification.
Keywords: Indoxyl sulfate, chronic kidney disease, protein-bound uremic toxins, ELISA, diagnostic performance, LC–MS/MS
Introduction
Chronic kidney disease (CKD) is characterized by progressive deterioration of renal function and may ultimately progress to end-stage renal disease (ESRD), requiring renal replacement therapy such as dialysis or kidney transplantation. CKD often progresses silently, with symptoms typically emerging only in the advanced stages. Major risk factors include diabetes, hypertension, and cardiovascular disease. In 2017, the Global Burden of Disease Study estimated 697.5 million cases worldwide, with a prevalence of 9.1% [1]. By 2021, cases exceeded 850 million, exceeding the prevalence of diabetes, cancer, and HIV/AIDS. CKD is also closely linked to cardiovascular morbidity and mortality, contributing to 1.4 million CVD-related deaths due to impaired kidney function. From 1990 to 2019, it rose from the 19th to the 11th leading cause of death, driven by aging populations and increasing risk factors such as diabetes and hypertension [2], underscoring its substantial global burden. Current CKD risk stratification frameworks integrate both estimated glomerular filtration rate (eGFR) and albuminuria to better reflect disease severity and prognosis.
Indoxyl sulfate (IS) is a protein-bound uremic toxin (PBUT), which primarily forms through hepatic metabolism of indole. Indole originates from the breakdown of dietary protein-derived tryptophan by intestinal bacteria’s tryptophanase, which enters the bloodstream and is transformed into IS within the liver. Following hepatic sulfation, IS circulates in the bloodstream and is predominantly eliminated through renal tubular secretion via organic anion transporters. In patients with CKD, impaired renal excretory capacity and tubular secretory dysfunction contribute to the accumulation of IS in the circulation [3–5]. Elevated IS levels have been associated with CKD severity and increased uremic toxin burden. In addition to impaired renal clearance, IS accumulation has been implicated in multiple pathophysiological processes, including oxidative stress, endothelial dysfunction, inflammation, cardiovascular toxicity, and CKD-related systemic complications [6,7]. Higher circulating IS concentrations have also been associated with adverse clinical outcomes, including uremic sarcopenia, cardiovascular disease, and increased all-cause mortality [8–11]. Additionally, patients with high IS levels have a higher all-cause mortality rate [12–14]. These findings suggest that IS may reflect important biological dimensions of CKD beyond glomerular filtration alone. Therefore, practical and accessible methods for serum IS measurement may provide complementary information for multidimensional CKD risk assessment and uremic toxin monitoring.
Traditionally, serum IS in patients with CKD has been measured using methods such as high-Performance Liquid Chromatography (HPLC), ultra-performance liquid chromatography (UPLC), and liquid chromatography–tandem mass spectrometry (LC-MS/MS) [15–17]. Although these techniques provide high analytical sensitivity and accuracy, they require specialized instrumentation, experienced personnel, and complex sample preparation procedures, and sample preparation prior to analysis is complex (e.g. involving protein precipitation steps). These limitations reduce the accessibility and scalability of routine IS monitoring in both clinical and research settings.
To facilitate accessible measurement of serum total IS, an enzyme-linked immunosorbent assay (ELISA)-based method was developed using a competitive ELISA platform. This approach enables relatively rapid and practical quantification of serum IS levels while simplifying assay procedures. However, different ELISA detection kits demonstrate varying levels of performance. Previous studies primarily focused on preliminary assay feasibility and analytical development [18]. In contrast, the present study further extends prior work by providing CLSI-guided analytical validation, independent validation cohort analysis, subgroup analyses in patients with eGFR <60 mL/min/1.73 m2, and multivariable analyses evaluating the association between serum indoxyl sulfate concentration and KDIGO-aligned CKD risk stratification.
Methods
Analytical performance studies
Linearity and recovery rate
The experimental design for assessing the linearity and recovery rate followed the Clinical and Laboratory Standards Institute (CLSI EP06-Ed2) guidelines using HIGH and LOW samples. HIGH and LOW analyte samples were prepared by diluting stock solutions with concentrations verified using LC–MS/MS and then mixing in various proportions to create intermediate concentrations [19]. The expected results were assessed for linearity, ensuring that each data point conformed to an Acceptable Deviation from Linearity (ADL) criterion of 10% or 0.23 μg/mL. Recovery rates were calculated using an acceptance criterion of 90–110%. Each intermediate concentration sample (S00–S10) was measured in five replicates, and all measurements were completed within the same day and run.
High-dose hook effect
This study evaluated whether the ELISA kit exhibits a hook effect, which can occur at high analyte concentrations and is often found in sandwich-type ELISA tests. The highest available concentration sample and its serial dilution samples were tested, following the following the CLSI EP06-Ed2 guideline [19]. Sample preparation was based on high-concentration samples of known concentration. The presence of a hook effect was determined by observing if there was a significant deviation from expected values. If a hook effect was found, the highest concentration test point without a hook effect was identified, indicating no hook effect below this concentration. If no hook effect was observed at any test point, it was concluded that there was no hook effect within the highest concentration tested. The acceptance criterion is ADL = 10%.
Interference and specificity study
This interference study followed the CLSI and Laboratory Standards Institute EP07-Ed3E guidelines [20]. Potential interfering substances, including conjugated and unconjugated bilirubin, hemoglobin, triglycerides, uric acid, human anti-mouse antibodies (HAMA), and rheumatoid factors (RFs), were tested at high concentrations. Each substance was evaluated in 12 replicates to determine significant differences in the measured values. The allowable difference (δ) is set to be approximately 1.5 times the repeatability (σ) (%difference: 11.121%; difference for low concentration: 0.141). For substances causing significant differences, a dose-response test was conducted at lower concentrations to establish the maximum allowable concentration without interference.
For the specificity study, high-concentration analogs of IS were tested to assess cross-reactivity. Five IS analogs – Indole, 3-indoleacetic acid, L-tryptophan, serotonin hydrochloride, and L-5-hydroxytryptophan – were evaluated at a concentration of 128 μg/mL. The cross-reactivity was calculated using the formula: %Cross-reaction = (average test value of high concentration analyte/added value of high concentration analyte,%). A %Cross-reaction threshold of < 3% was set to demonstrate high specificity of the ELISA kit. Each analog was tested in triplicate, and all measurements were completed within the same day and run.
Method comparison and bias
To evaluate the relationship between the ELISA kit and the reference method (LC/MS–MS), determine the best regression method, and calculate accuracy (Bias) at the medical decision-making concentration, this study follows CLSI EP09c, 3rd ed. Using more than 100 patient specimens, 1 test was performed on both the ELISA kit and the reference method with 1 instrument. Results were analyzed using a difference plot to observe fixed or % differences that amplify with concentration. Five different regression methods were compared, and the most appropriate regression method was selected based on CLSI EP09c, 3rd ed. criteria [21]. The 95% confidence interval (CI) of the slope must contain 1 and the 95% CI of the intercept must contain 0, with the narrowest 95% CI determining the best method. The accuracy (bias) of the medical decision-making concentration was set within ±6% (proportional bias).
Clinical performance studies
Ethics and study protocol
This study was conducted at a regional hospital in New Taipei City, Taiwan, in accordance with the Declaration of Helsinki. This study was approved by the Institutional Review Board of Cardinal Tien Hospital, New Taipei City, Taiwan (IRB No. CTH-110-1-4-049). In a previous study [19], preliminary findings suggested that serum indoxyl sulfate (IS) levels were associated with CKD severity classification and renal dysfunction, and these data were considered the primary cohort of the present study. The current study further included an independent validation cohort to evaluate the clinical performance of serum total IS concentration for identifying patients with CKD stage G3a and above (eGFR <60 mL/min/1.73 m2), including CKD stages G3a, G3b, G4, G5, and ESRD. Estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [22].
Participants included healthy volunteers with normal renal function, patients with CKD across different stages, and long-term dialysis patients. In both the primary and validation cohorts, CKD staging was adjudicated by experienced nephrologists according to the Kidney Disease: Improving Global Outcomes (KDIGO) 2012 clinical practice guideline. Written informed consent was obtained from all participants [23].
Is concentration determined by the ELISA kit?
Serum specimens were collected at enrollment for IS concentration determination using the ELISA Kit. The collected serum specimens were stored at −20 °C or −80 °C until measurement. Serum IS was measured using the Leadgene® IS ELISA Kit.
Statistical analyses
All statistical analyses were performed according to a pre-specified statistical plan approved by the Institutional Review Board (CTH-110-1-4-049). Continuous variables are presented as mean ± standard deviation (SD) or median with interquartile range (IQR), as appropriate, while categorical variables are expressed as counts and percentages. Between-group comparisons were conducted using the independent samples t-test or Mann–Whitney U test for continuous variables, and the χ2 test or Fisher’s exact test for categorical variables.
The diagnostic performance of serum indoxyl sulfate (IS) concentration for identifying CKD stage G3a and above (eGFR <60 mL/min/1.73 m2) was evaluated using receiver operating characteristic (ROC) curve analysis. The optimal cutoff value was determined using the Youden index to maximize sensitivity and specificity. Corresponding 95% confidence intervals (CIs) were calculated using the Wilson–Brown method.
Correlation analyses between serum IS concentration and eGFR were performed using Spearman correlation coefficients. Based on the identified cutoff value, participants were categorized into low-risk and high-risk groups according to serum IS levels.
To further evaluate the independent association between the IS cutoff and clinical classification, logistic regression analyses were performed. The outcome variable was defined for low-risk status. A multivariable logistic regression model was constructed to assess the association between IS > 2.233 μg/mL and lower-risk CKD classification, adjusting for clinically relevant variables including age (≥65 years), sex, and comorbidities. In addition, an age-adjusted logistic regression model was performed to specifically examine whether the association between IS > 2.233 μg/mL and lower-risk CKD classification remained independent after adjustment for age. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for all models. Variables with limited variability were excluded to ensure model stability, and missing data were handled using complete-case analysis.
Results
Analytical performance studies
Linearity and recovery rate
Figure 1 shows a linear relationship between the expected values (verified by LC–MS/MS) and ELISA-measured values, with no noticeable outliers. The average measured values, expected values, standard deviations (SD), and coefficients of variation (%CV) for each sample were assessed. SD increased with higher sample concentrations, while %CV remained <10% (data not shown). Weighted Linear Regression analysis demonstrated %Deviation ranging from −2.130% to 1.714% across 11 samples, all within the acceptable deviation limits (ADL < 10%), confirming compliance with the specified criteria. The analyte’s linear measurement range was established as 1.5-100 μg/mL, with recovery rates between 97.583% and 101.949%, meeting the acceptance criteria. Linearity and recovery rate analyses show that the assay adhered to acceptable deviation limits and recovery criteria with a validated measurement range of 1.5-100 μg/mL.
Figure 1.
Linearity and recovery analysis of the IS ELISA Kit. Eleven serum samples with IS concentrations ranging from 0 to 100 µg/mL were analyzed in five replicates within the same batch. The recovery rate ranged from 97.6% to 101.9%, demonstrating excellent linearity and intra-assay precision.
High-dose hook effect
Both the Control and Test groups, as well as the human serum and blank (sample diluent buffer, DS18002) samples, exhibited a roughly linear distribution without any obvious outliers. The average measured values, expected values, standard deviations (SD), and coefficients of variation (%CV) for each sample were assessed. The SD was observed to increase with higher sample concentrations, while %CV consistently remained within 10% (data not shown). Weighted linear regression analysis was conducted to further evaluate the data. Deviation and %Deviation were calculated accordingly. It can be noted that the %Deviation of all concentrations falls within the allowable range of ADL. In human serum and blank samples, the %Deviation at IS concentrations up to 100 μg/mL was −2.287% and −1.063%, respectively, remaining within the acceptable 10% range, and confirming linearity. No hook effect was observed below 100 μg/mL.
Interference and specificity study
No interference was observed under any of the conditions listed in Table 1. The absence of interference from these common substances in human blood and potential interfering substances in specific patient populations ensures that the performance of the assay remains accurate and reliable under the specified conditions. The cross-reactivity data in Table 2 show that all IS analogs had less than 3% cross-reactivity, confirming that the ELISA kit was highly specific for IS.
Table 1.
Maximum concentrations of interfering substances without affecting is measurement.
| IS concentration | Interfering substances | Maximum concentration without interference |
|---|---|---|
| 1.9 μg/mL 80 μg/mL | Conjugated bilirubin | ≤342 μmol/L |
| Unconjugated bilirubin | ≤684 μmol/L | |
| Hemoglobin | ≤3 g/L | |
| Triglycerides | ≤50 mmol/L | |
| Uric acid | ≤2 mmol/L | |
| HAMA | ≤200 ng/mL | |
| RFs | ≤500 IU/mL |
Data represent the maximum concentrations of potential interfering substances that did not affect indoxyl sulfate (IS) measurement using the ELISA assay.
Interference testing was performed according to Clinical and Laboratory Standards Institute (CLSI) EP07-Ed3 guidelines.
No clinically significant interference was observed when the difference between test and control samples was within the predefined allowable difference (δ).
HAMA: human anti-mouse antibody; RF: rheumatoid factor.
Table 2.
Results of specificity test.
| IS analogues | Expected valuea | Measured valuea | %Cross-reaction |
|---|---|---|---|
| Indole | 128 | 0.00171 | 0.00133 |
| 3-indoleacetic acid | 128 | 0.00264 | 0.00206 |
| L-tryptophan | 128 | 0.00201 | 0.00157 |
| Serotonin hydrochloride | 128 | 0.00341 | 0.00267 |
| L-5-hydroxytryptophan | 128 | 0.00300 | 0.00234 |
Unit of IS-analogue conc.: μg/mL.
Cross-reactivity (%) was calculated as: .
All indoxyl sulfate analogues were tested at a concentration of 128 μg/mL.
Cross-reactivity <3% was considered acceptable specificity.
Values represent the mean of triplicate measurements.
IS: indoxyl sulfate.
Method comparison and bias
A total of 153 samples were tested using both the ELISA kit and the reference method, with concentrations ranging from 0.1 μg/mL to 61.4 μg/mL. Forty-five data points below the Lower Limit of Quantification (LLoQ) were excluded from further analysis. Data and difference plots (data not shown) indicated a roughly linear relationship with increasing differences at higher concentrations. Regression analysis following CLSI EP09c, 3rd edition, showed that all methods, except Weighted Ordinary Linear Regression (WLinReg Fit), met the criteria of a slope with a 95% CI containing 1 and an intercept with a 95% CI containing 0 (data not shown). Weighted Deming Regression (WDeming Fit), which provided the smallest 95% CIs for both slope and intercept, was selected as the best method, with Pearson’s r of 0.964 (Figure 2). The accuracy (Bias) at the medical decision-making concentration (2.233 μg/mL) using this method was −0.521%, meeting the acceptance criteria. These results confirmed that the ELISA kit and the reference method exhibited a high degree of comparability.
Figure 2.
Method comparison between ELISA and LC–MS/MS. A total of 153 clinical specimens were tested using both methods. The correlation plot showed a Pearson correlation coefficient (r = 0.964), confirming strong agreement between ELISA and LC–MS/MS. LC–MS/MS, liquid chromatography–tandem mass spectrometry; ELISA: enzyme-linked immunosorbent assay.
Clinical performance studies
Primary cohort
A total of 254 specimens were collected, including 67 individuals with normal renal function or mild CKD (normal renal function and CKD stages G1–G2) and 187 individuals with moderate-to-severe CKD (CKD stage G3a and above, including patients undergoing hemodialysis and those with ESRD). Baseline demographic and clinical characteristics of the study population are summarized in Table 3. Serum IS concentrations were measured using the Leadgene® IS ELISA Kit. The diagnostic performance of serum IS is illustrated in Figure 3. The area under the receiver operating characteristic (ROC) curve was 0.96, with an optimal cutoff value of 2.233 μg/mL, which maximized the Youden index at 0.812. At this cutoff value, sensitivity and specificity were 0.872 (95% CI: 0.816–0.912) and 0.940 (95% CI: 0.856–0.977), respectively. A serum total IS concentration exceeding 2.233 μg/mL was associated with CKD stage G3a and above (eGFR <60 mL/min/1.73 m2), providing complementary information associated with CKD severity and uremic toxin burden. The distribution of serum IS levels across CKD severity groups is shown in Figure 4.
Table 3.
The demographic between the low-risk and high-risk group in the cohort.
| Low-risk group (n = 79) | High-risk group (n = 109) | p-value | |||
|---|---|---|---|---|---|
| Group (n, %) | |||||
| Non-CKD (Healthy) | 28 | 35.44% | -- | -- | -- |
| CKD I | 11 | 13.92% | -- | -- | -- |
| CKD II | 40 | 50.63% | -- | -- | -- |
| CKD III | -- | -- | 53 | 48.62% | -- |
| CKD IV | -- | -- | 16 | 14.68% | -- |
| CKD V | -- | -- | 7 | 6.42% | -- |
| Hemodialysis | -- | -- | 33 | 30.28% | -- |
| Demographics | |||||
| Age, y | 57.96 ± 13.88 | 65.17 ± 11.66 | <0.001*** | ||
| Sex, Male/Female | 48/31 | 76/33 | 0.261 | ||
| Comorbidity (n, %) | |||||
| Diabetes | 23 | 29.11% | 70 | 64.22% | <0.001*** |
| Hypertension | 33 | 41.77% | 65 | 59.63% | 0.016 |
| Hyperlipidemia | 15 | 18.99% | 7 | 6.42% | 0.023 |
| Cardiovascular diseases | 9 | 11.39% | 19 | 17.43% | 0.347 |
| Metabolic arthritis | 6 | 7.59% | 5 | 4.59% | 0.581 |
| Laboratory tests | |||||
| Weight, kg | 71.32 ± 14.33 | 70.33 ± 14.43 | 0.645# | ||
| SBP, mmHg | 127.33 ± 14.44 | 136.21 ± 19.74 | <0.001# | ||
| DBP, mmHg | 76.97 ± 9.53 | 76.27 ± 13.49 | 0.675# | ||
| Hemoglobin (Hb), g/dL | 13.78 ± 1.72 | 12.15 ± 1.62 | <0.001# | ||
| Hematocrit (Hct), % | 40.24 ± 4.67 | 35.35 ± 4.62 | <0.001# | ||
| Albumin, g/dL | 4.05 ± 4.40 | 4.02 ± 0.38 | 0.177# | ||
| BUN, mg/dL | 16.06 ± 4.88 | 45.50 ± 25.69 | <0.001# | ||
| Serum creatinine, mg/dL | 0.87 ± 0.23 | 5.68 ± 10.87 | <0.001# | ||
| eGFR, mL/min/1.73m2 | 92.05 ± 26.41 | 28.07 ± 18.96 | <0.001# | ||
| Triglycerides (TG), mg/dL | 158.96 ± 189.17 | 133.63 ± 70.22 | 0.274# | ||
| LDL cholesterol, mg/dL | 102.42 ± 36.59 | 87.46 ± 31.98 | 0.009# | ||
| UPCR, mg/gm | 271.37 ± 450.71 | 817.47 ± 1198.86 | 0.002# | ||
Continuous variables are expressed as mean ± standard deviation (SD).
Categorical variables are presented as number (percentage).
Between-group comparisons were performed using.
Student’s t-test for normally distributed continuous variables.
Mann–Whitney U test for non-normally distributed variables.
Chi-square test or Fisher’s exact test for categorical variables.
CKD: chronic kidney disease; SBP: systolic blood pressure; DBP: diastolic blood pressure; Hb: hemoglobin; Hct: hematocrit; BUN: blood urea nitrogen; eGFR: estimated glomerular filtration rate; TG: triglycerides; LDL: low-density lipoprotein; UPCR: urine protein-to-creatinine ratio.
p < 0.05.
p < 0.01.
p < 0.001.
Figure 3.
Receiver operating characteristic (ROC) curve for IS concentration. ROC analysis yielded an area under the curve (AUC) of 0.96, and the optimal cutoff concentration of 2.233 µg/mL achieved a sensitivity of 0.872 (95% confidence interval [CI] 0.816–0.912) and a specificity of 0.940 (95% CI 0.856–0.977) for distinguishing CKD stage G3a and above (estimated glomerular filtration rate [eGFR] < 60 mL/min/1.73 m2).
Figure 4.
Clinical risk stratification using the Leadgene® IS ELISA Kit. Application of the ELISA assay enabled visual discrimination between low-risk (CKD ≤ stage 2) and high-risk (CKD ≥ stage 3) groups.
To further evaluate the independent association between the IS cutoff and clinical classification, logistic regression analyses were performed. In the multivariable model, IS > 2.233 μg/mL was significantly associated with a lower likelihood of being classified as lower risk (OR 0.016, 95% CI 0.004–0.061, p < 0.001). Age ≥65 years showed a borderline association with lower-risk CKD classification (OR 2.46, 95% CI 0.96–6.31, p = 0.060), while other clinical variables, including comorbidities and sex, were not significantly associated with the outcome (Supplementary Table 1). In the age-adjusted model, IS > 2.233 μg/mL remained significantly associated with a reduced likelihood of lower-risk CKD classification (OR 0.018, 95% CI 0.005–0.067, p < 0.001). The inverse association indicates that higher IS levels are strongly linked to increased CKD severity rather than lower-risk status (Supplementary Table 2).
Correlation analysis demonstrated a strong inverse association between serum IS concentration and GFR in subjects with GFR < 60 mL/min/1.73m2. Spearman’s rank correlation analysis demonstrated a similarly strong inverse association (ρ = −0.810, p < 0.001). ROC curve analysis demonstrated good discriminatory performance of serum IS concentration for identifying higher-risk CKD patients with GFR <60 mL/min/1.73 m2. The area under the curve (AUC) was 0.952 (95% CI: 0.914–0.991, p < 0.001).
Validation cohort
A total of 188 cases were evaluated, including 109 in the high-risk group for renal damage (patients with CKD stage G3a and above (eGFR <60 mL/min/1.73 m2), those undergoing hemodialysis, and those with ESRD and 79 in the low-risk group (healthy individuals and those with CKD stages 1/2). At the selected cutoff value of 2.233 μg/mL, the sensitivity was 0.817 (95% CI: 0.734–0.878) and the specificity was 0.937 (95% CI: 0.860–0.973). These results confirmed the supportive clinical performance of the optimal cutoff value for distinguishing CKD patients with moderate-to-severe kidney impairment. Detailed clinical performance data are presented in Table 4.
Table 4.
Clinical performance of the optimal cutoff value, is concentration 2.233 μg/mL.
| IS conc. (μg/mL) | CKD stage | Total number | |
|---|---|---|---|
| ≥ stage 3a (eGFR < 60 mL/min/1.73 m²) | <stage 3a (eGFR ≥ 60 mL/min/1.73 m²) | ||
| >2.233 | 89 (47.34%) TP | 5 (2.66%) FP | 94 |
| ≤2.233 | 20 (10.64%) FN | 74 (39.36%) TN | 94 |
| Total number | 109 | 79 | 188 |
| Test clinical performance characteristics | |||
| Statistic | Value | 95% CI | |
| Sensitivity (TPR) | 0.817 | 0.734–0.878 | |
| Specificity (TNR) | 0.937 | 0.860–0.973 | |
| Positive Likelihood Ratio | 12.90 | 5.50 − 30.27 | |
| Negative Likelihood Ratio | 0.20 | 0.13 − 0.29 | |
IS: indoxyl sulfate; CKD: chronic kidney disease; eGFR: estimated glomerular filtration rate; TP: true positive; FP: false positive; FN: false negative; TN: true negative; TPR: true positive rate; TNR: true negative rate; CI: confidence interval.
Discussion
In this study, a total of 188 participants were enrolled and categorized into low-risk (CKD ≤ stage 2, n = 79) and high-risk (CKD ≥ stage 3, n = 109) groups. The Leadgene® IS ELISA Kit demonstrated diagnostic accuracy for identifying individuals with renal impairment. The area under the ROC curve (AUC) reached 0.96, indicating high discriminative power. Using a cutoff value of 2.233 µg/mL, the assay achieved a sensitivity of 0.872 (95% CI 0.816–0.912) and specificity of 0.940 (95% CI 0.856–0.977), with an overall accuracy of 86.7%. Analytical precision was confirmed by a nested-ANOVA total %CV below 10%, and the correlation with LC-MS/MS results was remarkably strong (Pearson’s r = 0.964), validating the assay’s reliability and reproducibility.
HPLC or ultra-performance liquid chromatography-tandem mass spectrometry is currently the most common method for measuring IS [15,24]. Leadgene has developed a competitive enzyme-linked immunosorbent assay (ELISA) kit for quantifying IS in serum. Here, we present the analytical performance of this assay kit and propose an optimal clinical cutoff value for IS associated with CKD severity classification and uremic toxin burden. The assay may facilitate accessible IS monitoring and provide complementary biological information associated with CKD severity and systemic uremic toxicity.
Linearity and recovery tests demonstrated satisfactory results, confirming that the reliability of the assay measurement range (AMR) is reliable. No hook effect was observed for IS concentrations, even at relatively high levels in patients, including those with ESRD, thus preventing assay failure and ensuring that the observed values were not falsely lowered. Interference and specificity studies confirmed that the detected values were free from interference and were specific to the IS. Furthermore, method comparison and bias analyses validated the accuracy of this assay, ensuring that it accurately reflected the true clinical conditions.
Traditional analytical methods are hindered by their low batch processing efficiencies and need for expensive and sophisticated instruments and skilled operators. In contrast, the Leadgene® IS ELISA Kit presents a user-friendly alternative, capable of analyzing more than 30 samples per plate with high throughput. This method does not require specialized skills or advanced analytical instruments, thus enabling more comprehensive data collection from a single assessment and facilitating accessible IS measurement in both clinical and research settings.
The IS concentrations reported in prior studies [24–26] align closely with our findings, with CKD G2 patients exhibiting IS levels around 1.5 μg/mL and CKD G3 patients around 2.4 μg/mL. We included subjects from two independent, non-overlapping prospective cohort studies, and propose an IS cutoff value of 2.233 μg/mL to differentiate CKD patients with moderate to severe kidney impairment (CKD G3 and above). There are currently no established physiological or pathological reference standards for serum indoxyl sulfate from major organizations such as the World Health Organization. These findings provide preliminary clinical reference data for serum IS measurement in CKD populations. Further research and standardization are necessary to validate these results and further clarify the clinical utility of IS measurement in multidimensional CKD risk assessment and uremic toxin monitoring.
In addition to its utility as a marker of renal impairment, IS is increasingly being recognized as a significant risk factor for complications associated with CKD. Elevated IS levels are associated with a higher incidence of cardiovascular diseases [27–31]. Unlike conventional filtration markers, elevated IS levels may reflect additional pathophysiological dimensions of protein-bound uremic toxicity. It is associated with an increased risk of all-cause mortality in CKD patients [25,32–34], making it a critical target for monitoring and therapeutic intervention to mitigate serious health outcomes.
Several limitations of this study should be acknowledged. First, this study was conducted at a single center in Taiwan, which may limit the generalizability of the findings across different ethnic populations and healthcare settings. Second, although the ELISA assay showed excellent analytical performance and strong correlation with LC–MS/MS, the method comparison was performed using a finite number of samples, and performance at extreme analyte concentrations requires further validation. Third, clinical validation was based on a cross-sectional design, and therefore, the longitudinal utility of serial serum indoxyl sulfate measurements for therapeutic monitoring, disease progression assessment, or clinical outcome prediction could not be determined. Fourth, while interference testing was conducted in accordance with CLSI EP07 guidelines, the range of tested interfering substances may not fully represent the complexity of real-world clinical samples, particularly in patients receiving multiple medications. Fifth, the proposed cutoff value (2.233 μg/mL) was derived and validated within the same study framework, and independent external validation is necessary before widespread clinical implementation. Finally, although the assay provides a practical and accessible platform for serum IS identification, real-world clinical impact was not evaluated in this study. In addition, because IS is predominantly handled through tubular secretion rather than glomerular filtration alone, its biological interpretation differs from conventional filtration-based renal biomarkers.
Conclusion
In summary, the Leadgene® IS ELISA Kit demonstrated strong fundamental analytical performance and exhibited excellent correlation with the traditional HPLC method for analyzing serum samples. This innovative reagent offers a user-friendly and efficient solution for the rapid measurement of large sample volumes. By streamlining and accelerating the measurement process, this method can significantly advance clinical applications related to IS, potentially facilitating broader accessibility for serum IS measurement in clinical and research settings.
Supplementary Material
Acknowledgment
The authors sincerely thank the lead gene research and technical teams for their invaluable assistance with assay development, validation, and data analysis. Their commitment to innovation and quality enabled this study. Yi-Chou Hou: Conceptualization, Methodology, Investigation, Writing – original draft, Writing – review & editing.; Yung-Chun Chuang: Conceptualization, Methodology, Formal analysis, Supervision; Yu-Wei Cheng: Data curation, Formal analysis, Project administration; Hsin-Yi Huang: Investigation, Data curation; Li-Yin Chen: Investigation, Project administration, Writing – original draft; Tzu-Ling Tseng: Investigation, Validation.; Kuo-Cheng Lu: Conceptualization, Methodology, Supervision, Validation, Writing – review & editing, Project administration.
Funding Statement
This study was supported by Leadgene Biomedical Inc and Cardinal Tien Hospital (CTH-115-AK-NDMC-2220).
Disclosure statement
Several authors (Y.-W.C., Y.-C.C., L.-Y.C.) are employees of Leadgene Biomedical Inc., the manufacturer of the ELISA kit evaluated in this study. The remaining authors declare no competing interests. The funder had no role in study design, data interpretation, or manuscript preparation.
Data availability statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
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Supplementary Materials
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.