Context.—

Galectin-9 reduces tissue damage in certain immune-mediated glomerular diseases. However, its role in structural and functional renal changes in patients with varying types of chronic kidney disease (CKD) is less clear.

Objective.—

To investigate the association between plasma galectin-9 levels, proteinuria, tubulointerstitial lesions, and renal function in different CKD stages.

Design.—

We measured plasma galectin-9 levels in 243 patients undergoing renal biopsy for determining the CKD etiology. mRNA and protein expression levels of intrarenal galectin-9 were assessed by quantitative real-time polymerase chain reaction and immunostaining. Relationships between plasma galectin-9, clinical characteristics, and tubulointerstitial damage were analyzed with logistic regression. We investigated galectin-9 expression patterns in vitro in murine J774 macrophages treated with differing stimuli.

Results.—

To analyze the relationship between galectin-9 and clinical features, we divided the patients into 2 groups according to median plasma galectin-9 levels. The high galectin-9 group tended to be older and to have decreased renal function, higher proteinuria, and greater interstitial fibrosis. After multivariable adjustment, elevated plasma galectin-9 levels were independently associated with stage 3b or higher CKD. An analysis of gene expression in the tubulointerstitial compartment in the biopsy samples showed a significant positive correlation between intrarenal galectin-9 mRNA expression and plasma galectin-9 levels. Immunohistochemistry confirmed increased galectin-9 expression in the renal interstitium of patients with advanced CKD, and most galectin-9–positive cells were macrophages, as determined by double-immunofluorescence staining. In vitro experiments showed that galectin-9 expression in macrophages was significantly increased after interferon-γ stimulation.

Conclusions.—

Our findings suggest that plasma galectin-9 is a good biomarker for diagnosing advanced CKD.

Chronic kidney disease (CKD) is a major public health problem worldwide that significantly impacts mortality and morbidity. CKD and CKD-related cardiovascular disease mortality has remained stable or even increased in recent decades after considering age distribution changes of the world's population.13  Early identification and intervention for those at risk of impaired renal function are therefore crucial for slowing CKD progression and preventing its complications. Renal function assessments have classically relied on measuring urinary protein and creatinine concentrations (urine protein/creatinine ratio) and serum creatinine levels to estimate glomerular filtration rates (GFRs). These tests tend to have lower sensitivity to minor injuries and do not directly indicate an underlying disease process.4,5  The current diagnosis of CKD has largely depended on certain predefined GFR thresholds; this CKD definition and classification system does not consider age-related loss of GFR and may lead to overdiagnosis and overtreatment of CKD in the elderly, who have only physiologic aging of the kidneys.6  Creatinine-based GFR estimating equations also tend to overestimate GFR in patients with malnutrition, liver cirrhosis, and other chronic illnesses, owing to reduced muscle mass, which may cause an inappropriate dosing of renally excreted drugs.7  Moreover, although tubulointerstitium plays an important role in normal renal function, the evaluation of renal tubulointerstitial injury has been notably absent in routine clinical practice. To address these limitations, studies have focused on identifying biomarkers of tubulointerstitial damage in urine or systemic circulation that are markedly abnormal after kidney injury.8,9  Although the utility of these molecules has yet to be validated in large clinical trials, several renal biomarkers implicated in the pathophysiology of kidney injury have potential for improving CKD management.10,11 

Galectins, a family of β-galactoside–binding lectins, play important roles in diverse physiologic and pathologic processes.1214  Galectins contain at least 1 conserved carbohydrate recognition domain consisting of approximately 130 amino acids responsible for carbohydrate binding.15  So far, 15 galectins have been found in mammals, classified into 3 structural types: proto (galectin-1, 2, 5, 7, 10, 11, 13, 14, and 15), chimera (galectin-3), and tandem repeat (galectin-4, 6, 8, 9, and 12).13,16,17  Galectin-9 is expressed by a variety of cell types including immune cells, epithelial cells, endothelial cells, and fibroblasts.18,19  A previous study demonstrated that galectin-9 selectively induced apoptosis of activated CD8+ T cells in Wistar Kyoto rats with nephrotoxic serum nephritis, suggesting a potential therapeutic role for galectin-9 in immune-mediated glomerular diseases.20  Galectin-9 administration can suppress toll-like receptor 7–mediated activation of plasmacytoid dendritic cells and B cells and thereby ameliorate kidney disease severity in murine lupus models.21  G1 phase cell cycle arrest and cellular hypertrophy in mesangial cells and podocytes are typically found in early diabetic nephropathy. Galectin-9 infusions into db/db mice were reported to be effective in attenuating glomerular hypertrophy and proteinuria via p27Kip1 and p21Cip1 downregulation.22  A recent Japanese study revealed that serum galectin-9 levels were elevated in patients with concomitant type 2 diabetes mellitus and CKD.23  Increased serum galectin-9 levels are positively correlated with age, creatinine, urea nitrogen, and osmotic pressure and are negatively correlated with eGFR.

The role of galectin-9 in structural and functional renal changes in patients with CKD remains unclear, however. The present study evaluated galectin-9 expression in the plasma and renal tissue of patients undergoing renal biopsy for CKD etiology determinations. We investigated the association between plasma galectin-9 levels, proteinuria, tubulointerstitial lesions, and renal function in these patients. The ability of circulating galectin-9 to predict the onset of advanced CKD stages was also assessed. We also sought to determine the major sources of renal galectin-9 during CKD progression. This study's findings should provide information on the utility of galectin-9 in diagnosing and managing this complex disease.

Patients

The study protocol was approved by the institutional review board, and all participants provided written informed consent in accordance with the Declaration of Helsinki. Between October 2018 and March 2021, a total of 259 adult patients undergoing clinically indicated percutaneous kidney biopsy in our department were recruited. The exclusion criteria included an age under 20 years (n = 2), refusal to sign the informed consent (n = 4), participation in other research studies (n = 2), and having undergone kidney transplant (n = 8). The study ultimately included 243 patients. Renal biopsy specimens were routinely processed for histologic examination, and an expert nephropathologist interpreted the test results. Urine and plasma were collected the day before kidney biopsy.

Biomarker Measurements

Plasma samples were stored at −80°C until analysis. Quantification of human plasma galectin-9, interleukin 6 (IL-6), and monocyte chemoattractant protein-1 (MCP-1) was performed with an in-house, multiplex, bead-based immunoassay as previously described.24,25  In brief, a set of fluorescent beads coated with capture antibody targeted to the biomarker of interest was used. Samples were then incubated with the beads at room temperature. After washing away unbound substances, the beads were incubated with a mixture of biotinylated secondary antibodies and a streptavidin-phycoerythrin conjugate. Plasma levels of human galectin-9, IL-6, and MCP-1 were measured and quantified with a Bio-Plex 200 analyzer (Bio-Rad, Hercules, California). All samples were tested in duplicate to ensure accuracy.

Clinical Laboratory Studies

The blood and urine samples were laboratory tested to assess renal function, proteinuria, and other baseline parameters. Renal function was estimated by using the Modification of Diet in Renal Disease Study equation,26  and proteinuria was corrected for urine creatinine concentration in spot urine.

Evaluation of Tubulointerstitial Damage Using Interstitial Fibrosis and Tubular Atrophy

The histopathologic abnormalities were assessed with digital images obtained from paraffin-embedded biopsy specimens stained with hematoxylin-eosin, periodic acid–Schiff, Jones methenamine silver, and Masson trichrome staining. Whole slide images were acquired with the Hamamatsu NanoZoomer S210 Digital Slide Scanner (Hamamatsu Photonics, Bridgewater, New Jersey). Images at ×100 magnification were viewed with NDP.view2 software (Hamamatsu, Japan), and the rates of renal cortical involvement by interstitial fibrosis and tubular atrophy (IFTA) were evaluated. The IFTA degree was determined semiquantitatively for each individual stain and averaged to obtain an overall mean, as described previously.27  We adopted the semiquantitative scoring system of Srivastava et al28  for assessing the severity of IFTA (none, ≤10%; mild, 11%–25%; moderate, 26%–50%; and severe, >50%). They found that moderate and severe versus minimal IFTA were independently associated with kidney disease progression across a diverse group of kidney diseases. All quantitative image analyses were performed blinded to avoid biases.

Immunohistochemical Analysis of Intrarenal Galectin-9

To determine the intrarenal galectin-9 expression, paraffin-embedded renal biopsy tissues (2-μm thick) from healthy individuals (n = 7) and patients (n = 35) were processed for immunostaining as described previously.29  The renal function was comparable in these patients and the remaining individuals in this cohort. The primary antibody was rabbit polyclonal anti–galectin-9 antibody, which detected amino acid residues within the aa 271–340 region (Atlas Antibodies; HPA047218). An isotype-matched irrelevant antibody served as a negative control. After incubation with horseradish peroxidase–conjugated secondary antibody, the color reaction was developed with diaminobenzidine. Sections were then counterstained with hematoxylin. The intensity and abundance of glomerular, tubular, and interstitial staining were estimated semiquantitatively from 0 to 3 (absent, weak, moderate, or strong). A mean score was calculated for each section from at least 10 high-power fields.

Double Staining by Immunofluorescence

Immunofluorescence staining was performed to identify cell types that produce galectin-9 in cryostat-cut sections of kidneys from the patients. A rabbit polyclonal antibody against galectin-9 (1:50; HPA047218, Atlas Antibodies) was used for detecting galectin-9 by indirect immunofluorescence staining with fluorescein isothiocyanate–conjugated secondary antibodies (1:100; 111-095-003, anti-rabbit immunoglobulin G [IgG], Jackson ImmunoResearch). Antibodies for CD68 (1:200; ab201340, Abcam), CD20 (1:200; ab215866, Abcam), and CD3 (1:10, ab17143, Abcam) were used for detecting macrophages, B cells, and T cells, respectively, by indirect immunofluorescence staining with rhodamine-conjugated goat anti-mouse IgG antibody (1:100; 115-025-146, Jackson ImmunoResearch). Nuclei were then counterstained with DAPI (4′,6-diamidino-2-phenylindole, Sigma-Aldrich). Images were viewed under a fluorescence microscope (Nikon ECLIPSE TS100, Nikon, Japan).

Cell Culture and Treatment

Murine macrophage J774A.1 cells (Bioresource Collection and Research Center, Hsinchu, Taiwan) were cultured in Dulbecco modified Eagle medium supplemented with 10% fetal bovine serum at 37°C in a humidified atmosphere containing 5% CO2. To characterize the expression pattern of endogenous galectin-9 in J774A.1 cells under varying pathologic conditions, J774A.1 cells were seeded in 6-well plates at a 5 × 106 cells/well density. The cells were then polarized into the M1 phenotype by treating with lipopolysaccharide (LPS, 100 ng/mL) or interferon-γ (20 ng/mL) or into the M2 phenotype by treating with IL-4 (20 ng/mL) + IL-13 (20 ng/mL), respectively. Cells were stimulated for the indicated periods before harvesting and stored at −80°C until further analysis.

RNA Extraction and Quantitative Real-Time Polymerase Chain Reaction

The kidney tissue for the analysis of gene expression was immediately stored in the RNA stabilization reagent RNAlater (Thermo Fisher Scientific) according to the manufacturer's recommendations. The tissue samples were manually microdissected into glomerular and tubulointerstitial compartments. Total RNA of the dissected tubulointerstitial compartments and J774 cells was extracted and then reverse transcribed into cDNA as previously reported.30  Quantitative real-time polymerase chain reaction (qPCR) assays were performed by using a 2× SYBR Green qPCR Master Mix (BioTools, New Taipei City, Taiwan) with a real-time PCR instrument (Applied Biosystems QuantStudio 3 Real-Time PCR System, Thermo Fisher Scientific). All reactions were run in triplicate. The relative mRNA expression levels of each sample's target genes were determined and normalized to the β-actin (ACTB) expression. Supplemental Table 1 (see supplemental digital content containing 3 tables and 5 figures at https://meridian.allenpress.com/aplm in the February 2023 table of contents) lists the primer sequences for the qPCR analysis.

Statistical Analyses

The participants' baseline characteristics are expressed as means ± standard deviation, medians and interquartile range (IQR), or numbers and percentages. The study population was divided into 2 subgroups on the basis of median plasma galectin-9 values. The groups were compared with Student t and Mann-Whitney U tests for the continuous variables (for normal and nonnormal distributions, respectively) and with the χ2 test for the categorical variables. To compare 3 or more groups, we performed a 1-way analysis of variance followed by the Bonferroni post hoc test or the Kruskal-Wallis test followed by the Dunn test, based on the data distribution. Correlations between variables were determined by using the Spearman rank correlation coefficient. The multivariate logistic regression revealed the independent risk factors for high plasma galectin-9 levels and advanced CKD. Parameters with P values < .10 in the univariate analysis and those considered relevant were entered as covariates. A receiver operating characteristic (ROC) curve analysis was performed to assess the performance of plasma galectin-9 in diagnosing advanced CKD. We also evaluated the impact of plasma levels of galectin-9 on adverse kidney outcomes in this patient group. The adverse renal outcome was defined as a composite of an eGFR decline of 50% or more, end-stage renal disease, or mortality due to cardiovascular or renal etiologies. The cumulative risk of renal end points was calculated by using the Kaplan-Meier method and compared with the log-rank test. Additionally, Cox regression analysis was used to determine the prognostic role of galectin-9 in patients with CKD. An analysis with P < .05 was considered statistically significant. Data were analyzed with SPSS version 23.0 software (SPSS Inc, Chicago, Illinois) and GraphPad Prism 9 (GraphPad Software, San Diego, California).

Clinical Characteristics of the Study Participants

Table 1 presents the clinical characteristics of the 243 patients who underwent kidney biopsy (mean age, 56.4 ± 16.4 years; 39.1% women; median eGFR, 36 mL/min/1.73 m2 [IQR, 17–65 mL/min/1.73 m2]; proteinuria, 2.93 mg/mg creatinine [IQR, 1.05–7.68 mg/mg]). Hypertension, diabetes, and cardiovascular disease were present in 99 (40.7%), 62 (25.5%), and 27 (11.1%) participants, respectively. The patients were classified into 6 diagnostic categories on the basis of their clinical and histopathologic findings. The most common kidney disease categories were nonproliferative glomerulopathy, proliferative glomerulonephritis, and diabetic kidney disease. Supplemental Table 2 presents the histologic diagnoses of the renal biopsies included in each category. The median levels of plasma galectin-9, IL-6, and MCP-1 were 750.1 pg/mL, 8.2 pg/mL, and 145.9 pg/mL, respectively.

Circulating Galectin-9, Renal Function, and Tubulointerstitial Damage Among Participants Undergoing Renal Biopsy

To further assess the relationship between galectin-9 and clinical features, the patients undergoing native renal biopsy were divided into 2 groups on the basis of median plasma galectin-9 values (Table 1). The high galectin-9 group had a larger percentage of elderly patients and patients with hypertension and diabetes mellitus than the low galectin-9 group. The high galectin-9 group tended to have more severe anemia, lower eGFR values, a larger percentage of patients with proteinuria, and increased plasma IL-6 and MCP-1 levels. Compared with the low galectin-9 group, the high galectin-9 group was more likely to have diabetic kidney disease and less likely to have nonproliferative glomerulopathies. The high galectin-9 group had a greater degree of IFTA than the patients in the low galectin-9 group (Table 1).

Spearman correlation coefficient analysis was performed to determine the correlation between circulating galectin-9, renal function, proteinuria severity, degrees of IFTA, and systemic inflammatory markers in these patients. The correlation analysis revealed that galectin-9 levels were positively correlated with proteinuria, IFTA, IL-6, and MCP-1 and inversely correlated with eGFR, as presented in Figure 1, A and B. Our results also suggested that level of eGFR was significantly related to most of the variables listed here; however, there was no correlation between eGFR and plasma concentrations of MCP-1. These findings led to speculation that plasma galectin-9 levels may add value to assess and monitor the inflammatory status in patients with CKD.

Factors Associated With Increased Levels of Plasma Galectin-9 Among Patients Who Underwent Renal Biopsy

Logistic regression was used to determine the factors influencing plasma galectin-9 levels (Table 2). In the unadjusted analyses, older age, hypertension, diabetes mellitus, lower eGFR and hemoglobin levels, higher proteinuria, higher plasma IL-6 and MCP-1 levels, absence of nonproliferative glomerulopathy, and greater IFTA severity were associated with high circulating galectin-9 levels. After adjusting for age, sex, and variables with P values < .10 in the univariate analyses, only lower eGFR and higher plasma MCP-1 concentrations remained associated with increased plasma galectin-9 levels.

The Level of Galectin-9 in Plasma Was an Independent Predictor of Advanced CKD

There is an increased risk of CKD-related complications as eGFR falls below 45 mL/min/1.73 m2.31  We therefore used a logistic regression analysis to determine the factors that predicted the presence of CKD stage 3b or higher (Table 3). In the unadjusted analyses, plasma galectin-9 levels were significantly associated with more advanced CKD stage, and this association persisted after adjusting for potential confounders.

We used an ROC analysis to evaluate the ability of plasma galectin-9 to identify advanced CKD (Supplemental Figure 1, A). The optimal cutoff point for detecting advanced CKD was 689.6 pg/mL (sensitivity, 74.0%; specificity, 74.2%; AUC [area under the curve], 0.797; 95% CI, 0.742–0.852). Our analyses also demonstrated that plasma galectin-9 had a high accuracy for diagnosing the earliest stages of CKD (Supplemental Figure 1, B and C).

The prognostic ability of plasma galectin-9 to predict the risk of adverse renal outcome was evaluated. Among 193 patients who were followed up for at least 1 year, 52 composite renal outcomes occurred: 45 in the high galectin-9 group and 7 in the low galectin-9 group (hazard ratio, 6.441; 95% CI, 2.902–14.294; see Supplemental Figure 2 and Supplemental Table 3). After multivariate adjustment, a trend for increased risk of renal adverse events could be observed in patients with elevated plasma galectin-9 levels.

Galectin-9 Expression Upregulated in the Tubulointerstitial Compartment of Patients With CKD

Periodic acid–Schiff and Masson trichrome staining (Figure 2, A through D) showed morphologic changes in the renal cortex, including global glomerulosclerosis, interstitial inflammation, and IFTA in patients with CKD, compared with those without CKD. To identify the cell types producing galectin-9 during CKD progression, we analyzed the presence of galectin-9 protein from paraffin-embedded kidney biopsy samples, using immunohistochemistry (Figure 2, E through H). Galectin-9 was not detectable in the kidneys of healthy controls (Figure 2, E and F). For those with advanced CKD, galectin-9 expression was significantly upregulated, mainly in the interstitial cells, with very little expression in tubules or glomeruli (Figure 2, G and H; Supplemental Figure 3). We found no difference between the expression of galectin-9 in both the glomerular and tubular compartments of either the fibrotic or nonfibrotic kidneys.

Recently, a publicly available single-nucleus RNA sequencing data set on human diabetic kidney samples showed enhanced expression of LGALS9 mRNA, which encodes human galectin-9, in the leukocyte subsets and endothelial cells when compared with those of healthy controls (Supplemental Figure 4).32  Using double-immunofluorescence staining, we found that most galectin-9–positive leukocytes in the interstitial space of patients with CKD were macrophages (Figure 2, I through L). Galectin-9 expression was also detected in a small number of T and B cells (Supplemental Figure 5).

From these results, we quantified LGALS9 mRNA expression in the renal tubulointerstitial compartment in the patients with paired plasma and kidney biopsy samples and evaluated its associations with the clinical and laboratory parameters. Intrarenal LGALS9 RNA expression correlated significantly with the plasma galectin-9 concentrations in 58 patients who underwent percutaneous kidney biopsy (rs = 0.55; P < .001) (Figure 3, A). We found that LGALS9 expression was positively correlated with gene expression levels of various extracellular matrix molecules and was inversely correlated with eGFR (Figure 3, B through F), suggesting the intimate relationship between galectin-9 and renal fibrosis in CKD progression.

Endogenous Galectin-9 Expression in Murine J774 Macrophages Was Increased in Response to Interferon-γ Stimulation

To determine which factors might upregulate galectin-9 expression by monocytes/macrophages, murine J774 cells were treated with various stimulants, including LPS, interferon-γ, and IL-4 + IL-13. Cells were then confirmed to be polarized into corresponding states 24 hours after stimulation by using qPCR to assess the expression of M1- and M2-related genes (Figure 4, A through D). Galectin-9 expression from macrophages was significantly increased by interferon-γ but not by LPS or IL-4 + IL-13, suggesting that interferon-γ–activated macrophages might be the main source of galectin-9 production under pathophysiologic conditions (Figure 4, E).

In this study, we observed a significant increase in plasma galectin-9 concentrations in the patients with renal impairment who underwent kidney biopsy, which correlated inversely with renal function and directly with proteinuria and IFTA extent. Lower eGFRs and higher plasma MCP-1 concentrations appeared to be linked to elevated circulating galectin-9 levels. We showed that increased plasma galectin-9 levels were associated with the presence and severity of renal dysfunction. The immunohistochemical and qPCR analysis of microdissected tubulointerstitial components of human renal biopsy samples showed increased galectin-9 expression in the interstitial space of fibrotic kidneys compared with that of histologically normal controls, and the major source of galectin-9 within the injured kidney appeared to be macrophages. The in vitro studies demonstrated that galectin-9 production in monocytes/macrophages was significantly enhanced by interferon-γ. Our findings therefore suggest that plasma galectin-9 can be considered a good biomarker for diagnosing CKD and that it might play a key role in the pathogenesis of kidney disease progression.

There are numerous possible mechanisms that might explain the higher plasma galectin-9 levels in the patients with CKD than in those with normal renal function. Galectin-9 has a molecular weight of approximately 36 kDa, and a decreased GFR might result in its accumulation in the systemic circulation. The current study also showed that plasma galectin-9 levels correlated significantly with the intrarenal mRNA expression of the LGALS9 gene in the patients with paired plasma and kidney biopsy samples. This finding suggests that injured kidneys could be a potential source of circulating galectin-9. Plasma galectin-9 concentrations might also reflect a delicate balance between the immune response and host. Studies have noted that galectin-9 is involved in the macrophage polarization process, thereby influencing the pathogenesis of numerous diseases.3335  Our study also demonstrated that MCP-1, an important mediator regulating migration and infiltration of monocytes/macrophages into inflammation sites, is an independent predictor for plasma galectin-9 levels after accounting for other confounding variables. Given that activation of kidney-resident macrophages and circulating monocytes is common in CKD, these cells might be an important contributor to elevated plasma galectin-9 levels in this population.3638 

Histopathologic lesions on native kidney biopsies in kidney disease of diverse etiology have recently been shown to provide prognostic information independent of clinical parameters, such as comorbid conditions, proteinuria, and eGFR.28,39  Regardless of the underlying cause, tubulointerstitial injury is always present as kidney disease progresses. Several studies have suggested that, even among patients with chronic glomerulonephritis, the extent of tubulointerstitial damage has more impact on the subsequent decline in renal function than the degree of glomerular injury.40,41  Tubulointerstitial injury causes infiltration of inflammatory cells in the interstitium, leading to IFTA and CKD progression. This study found that increasing IFTA severity was associated with lower eGFR after a multivariable adjustment. Our data confirm the importance of IFTA, which is consistent with previous findings.

Galectin-9 exerts pleiotropic effects on numerous tissues by regulating cellular processes such as proliferation, differentiation, apoptosis, and immunomodulation.42,43  Beyond its role in normal physiologic processes, several studies have found that the circulating galectin-9 was elevated in certain medical conditions, such as infectious disease, autoimmune disease, malignancy, and renal disease.19  Although galectin-9 affects glomerular injury in certain immune-mediated glomerular diseases,20,21  less is known about the relationship between this protein and renal tubulointerstitial damage during CKD progression. Researchers have recently demonstrated the importance of galectin-9 in fibrotic remodeling in various organ systems, including the liver, skin, and lungs.4446  Galectin-9 is highly expressed in the liver and systemic circulation in chronic hepatitis C, and an excess of galectin-9 can enhance the production of proinflammatory and profibrotic cytokines from Kupffer cells, which might result in liver damage and fibrosis.44  Galectin-9 expression has also been reported as upregulated in dermal fibroblasts of skin sections in systemic sclerosis.46  Increased galectin-9 expression led to a dysregulated balance of T helper 1/T helper 2 (TH1/TH2) immune responses that promoted skin fibrosis in these patients. Our results indicate that human galectin-9 is strongly expressed in interstitial macrophages at sites of tubulointerstitial injury and fibrosis. Galectin-9 expression correlates with the extent of tubulointerstitial fibrosis and tubular cell damage. In vitro experiments have shown that galectin-9 expression in macrophages is significantly upregulated by interferon-γ, which participates in the pathogenesis of renal fibrosis.47  Collectively, these findings suggest that galectin-9 might be involved in CKD progression, partly via immune system modulation.

Several limitations to this study need to be acknowledged. First, our preliminary investigation has revealed that elevated plasma galectin-9 is linked to poor outcome in patients with CKD. Further studies using a larger population are still needed to validate these findings. Second, although appropriate adjustments were performed in the multivariable model, unmeasured and residual confounding factors might still exist. A third limitation is that the study population had only a small proportion of patients with diabetic kidney disease, who constitute most cases of CKD worldwide. Given that the patients exhibited a broad mix of renal pathologies, the results are more likely to be applicable to patients with kidney disease of diverse etiology. Fourth, although only a few patients with a pathologic diagnosis of acute kidney injury were included in the cohort, this may influence the association between galectin-9 expression and investigated parameters. Lastly, we acknowledge the limitations of this work that failed to elucidate the role of galectin-9 in renal immune homeostasis and tubulointerstitial fibrosis. Well-designed studies using genetically modified animals are needed to clarify these questions.

In summary, this study showed that galectin-9 expression in kidneys and peripheral blood was significantly increased in the patients with CKD when compared with healthy controls. Plasma galectin-9 levels were negatively correlated with renal function and positively correlated with proteinuria and IFTA severity. The in vitro study showed that interferon-γ–stimulated macrophages might contribute to galectin-9 production within damaged kidneys. These findings provide valuable information for further investigation of galectin-9 as a prognostic biomarker and therapeutic target in patients with CKD.

We thank the Academia Sinica Inflammation Core Facility, IBMS for technical support.

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Author notes

Supplemental digital content is available for this article at https://meridian.allenpress.com/aplm in the February 2023 table of contents.

The core facility is funded by the Academia Sinica Core Facility and Innovative Instrument Project (AS-CFII-108-118). This study was financially supported in part by funding from the Ministry of Science and Technology R.O.C. (MOST 109-2314-B-075-071, 109-2314-B-010-056-MY3, and 110-2628-B-075-011-), Taipei Veterans General Hospital (V109B-020, V110C-149, V110C-151, VTA110-V1-3-1, VTA 110-V1-3-2, V108D42-001-MY3-3, and V108D42-004-MY3-3), and Institute of Biomedical Sciences, Academia Sinica (IBMS-CRC110-P04 and AS-VTA-110-03). This study was also supported by the Foundation for Poison Control (FPC-111-003).

The authors have no relevant financial interest in the products or companies described in this article.

Supplementary data