Alpha-1-microglobulin as an early biomarker in renal extrahepatic manifestations of hepatitis C virus infection

Abstract

BACKGROUND

Hepatitis C virus (HCV)-related nephropathy often progresses silently and is commonly underrecognized until chronic kidney disease or acute kidney injury occurs. Urinary alpha-1-microglobulin (Uα1M) is a promising early biomarker of proximal tubule dysfunction. It may help detect the subclinical renal extrahepatic manifestations of HCV earlier than traditional markers such as serum creatinine (SCr). The early renal manifestations of HCV include microalbuminuria, hematuria, tubular injury, and immune-mediated glomerulopathy.

AIM

To evaluate the efficacy of Uα1M in identifying the early kidney involvement in patients with HCV infection.

METHODS

A case-control study was conducted from February 2022 to February 2024 at the Clinic of Nephrology Outpatient, Department of Internal Medicine, and Clinic of El-Rajhy Hepatitis Outpatient at Assiut University Hospitals. This study involved 158 patients aged ≥ 18 years, divided into HCV and control groups. The HCV group included 79 patients diagnosed as HCV-positive by HCV + antibodies and positive real-time polymerase chain reaction for HCV-RNA. The control group included 79 participants who were age-matched and sex-matched, and HCV-negative healthy individuals. The primary outcome was the rate of increased level of Uα1M.

RESULTS

The two groups were comparable in age and sex distribution. The mean hemoglobin level and platelet count were significantly lower in HCV patients than in controls, respectively. Blood urea nitrogen (BUN), SCr, and estimated glomerular filtration rate (eGFR) showed no significant differences. The urinary albumin/creatinine ratio was significantly higher in HCV-positive patients, with increased prevalence of microalbuminuria and macroalbuminuria. Uα1M levels were markedly elevated in the HCV group. It correlated positively with BUN and SCr, and negatively with eGFR, aspartate aminotransferase, and alanine aminotransferase. Uα1M levels were significantly higher in patients with hematuria (P = 0.007) and those with impaired eGFR (P < 0.001) than those without these disorders. Only five HCV-positive patients underwent renal biopsy, and all showed membranoproliferative glomerulonephritis. The Uα1M levels higher than the 3.52 mg/L cutoff had strong diagnostic ability to distinguish HCV-positive from HCV-negative subjects, with an area under the curve of 0.864 (95% confidence interval: 0.801-0.913), 77.0% accuracy, 60.0% sensitivity, 93.7% specificity, 90.4% positive predictive value, and 69.8% negative predictive value (P < 0.001).

CONCLUSION

Uα1M served as a valuable early renal tubular biomarker for detecting subclinical kidney involvement in chronic HCV patients. It showed a moderate correlation to BUN and mild correlation to SCr and eGFR, with membranoproliferative glomerulonephritis pathology predominance in biopsied cases. In addition, it had a strong diagnostic accuracy at levels higher than a cutoff of 3.52 mg/L, reinforcing its potential for early diagnosis of renal involvement by HCV infection.

Key Words: Alpha-1-microglobulin; Hepatitis C virus; Kidney injury; Renal extrahepatic manifestations; Urinary biomarkers

Core Tip: Chronic hepatitis C virus (HCV) infection can lead to subclinical renal injury that often progresses unnoticed until chronic kidney disease develops. In this study, urinary alpha-1-microglobulin (Uα1M) proved to be a sensitive, early, and non-invasive biomarker for detecting tubular dysfunction in HCV-infected patients. The rate of elevated Uα1M levels correlated with subtle renal alterations and demonstrated strong diagnostic accuracy, even when traditional renal markers were within normal limits. Routine Uα1M assessment may facilitate early detection and intervention for HCV-related renal involvement, improving long-term renal outcomes.

INTRODUCTION

Hepatitis C virus (HCV) infection can cause kidney damage, often discovered late when chronic kidney disease (CKD) is already established[1]. This late stage is characterized by a faster annual decline in estimated glomerular filtration rate (eGFR) for HCV-positive patients compared to HCV-negative CKD patients. CKD is four times more prevalent in HCV patients, leading to twice the mortality and high treatment costs for those not receiving treatment[2]. HCV-related nephropathy can appear at any time, with varied patterns of glomerular and tubulointerstitial damage[3]. Kidney injury results from immune-mediated damage, direct viral effects, or unknown mechanisms. Subclinical issues such as microalbuminuria and hematuria are common[4].

Identifying patients early for prompt intervention is paramount[5]. Since HCV appears to affect both tubular and glomerular cells, tubular cell damage may be the earliest sign of renal dysfunction, potentially used to identify patients at risk for progression[5]. Traditional markers, such as serum creatinine (SCr) and blood urea nitrogen (BUN), are often delayed and have low sensitivity in detecting early kidney damage[6]. Novel biomarkers are needed. Established acute kidney injury (AKI) biomarkers include neutrophil gelatinase-associated lipocalin, urinary cystatin C, urinary kidney injury molecule-1, urinary interleukin-18, and glutathione-S-transferase. These biochemical factors are known early diagnostic markers for AKI in various settings, often appearing about 2 days before clinical AKI develops[7].

Urinary alpha-1-microglobulin (Uα1M) is a low-molecular-weight protein and a promising biomarker. It is synthesized by hepatocytes, freely filtered by the glomerulus, and completely reabsorbed by the proximal tubule[8]. Hence, it signals tubular dysfunctions. Higher Uα1m inversely correlates with tubular resorptive capacity[9]. Additionally, it is associated with early tubulointerstitial renal diseases in HCV-related glomerulopathy[10]. Reports of early kidney manifestations (before CKD onset) are rare[3]. Hence, this study was conducted to evaluate the efficacy of Uα1M in identifying early kidney involvement in patients with HCV infection.

MATERIALS AND METHODS

Study design

A case-control study was conducted to evaluate the efficacy of Uα1M in detecting the early kidney injury in patients with HCV. It was conducted from February 2022 to February 2024 at the Clinic of Nephrology Outpatient, Department of Internal Medicine, and the Clinic of El-Rajhy Hepatitis Outpatient at Assiut University Hospitals (Assiut, Egypt). This study comprised two groups: Patients who were diagnosed as HCV-positive and healthy individuals who were age-matched and sex-matched and HCV-negative as controls. Patients and controls were consecutively recruited. Specifically, the controls were recruited from individuals who attended the outpatient clinic for routine health checkups and from healthy relatives of the study patients.

Patient selection

The sample size estimation was performed using the Fleiss formula for two independent proportions (unmatched design). The calculation was based on a two-sided α = 0.05 and 80% power. According to prior literature and pilot observations, the expected prevalence of early renal involvement (biomarker positivity) was assumed to be 40% among HCV-positive patients and 20% among HCV-negative controls. Using these parameters, the minimum required sample size was 79 cases and 79 controls.

This study included adult patients aged 18 years and older who were HCV-positive, confirmed by both HCV antibody and HCV-RNA positivity, including those who were either treatment-naïve or had previously received treatment. The controls were HCV-negative healthy individuals. Patients were excluded if they were HIV-positive, hepatitis B surface antigen-positive, had previous renal diseases, or were alcoholics. In addition, patients with comorbidities such as diabetes mellitus, hypertension, systemic lupus erythematosus, rheumatoid arthritis, or active malignancy were excluded. Moreover, patients taking certain medications, such as angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, or drugs that can interfere with proximal tubular absorption, such as sodium-glucose co-transporter-2 inhibitors, were also excluded.

Clinical assessments

All participants underwent detailed history taking and clinical examination, with particular attention to the time and duration of HCV infection. The history of specific medications that may influence renal glomerular or tubular functions was assessed.

Laboratory investigations included routine tests such as urine analysis (morning sample) to assess proteinuria using dipstick grading (trace, +1 to +4), hematuria defined as red blood cells > 5/high power field, and the presence of casts (red blood cells and white blood cell casts). Blood tests included BUN, SCr, complete blood count, and liver function tests. Additional investigations included immunologic markers such as antinuclear antibodies, complement levels (C3 and C4), and rheumatoid factor. Abdominal ultrasonography was used to assess the liver for cirrhosis.

Renal function was assessed using eGFR. The latter was calculated using the CKD-Epidemiology Collaboration creatinine-based equation[11], and values were stratified by sex and SCr levels. eGFR equations were applied according to standardized formulas for males and females to ensure accurate assessment of kidney function in the studied population. Additional measurements included urinary albumin-to-creatinine ratio (UACR; < 30 mg/g), 24-hour urinary protein (< 150 mg/day), and protein-to-creatinine ratio.

Uα1M was measured in a morning spot urine sample using Abbott’s turbidimetry method (normal level is < 12 mg/L). The kidney biopsy was performed when renal findings met standard nephrology criteria.

Study outcomes

The primary outcome was the difference in the level of Uα1M between the patients and controls. However, the secondary outcomes included differences in renal function tests, including BUN, SCR, and UACR.

Ethical approval

This study was approved by the Ethics Committee of Faculty of Medicine of Assiut University (Approval No. 17200739). Additionally, it was registered in ClinicalTrials, and the registration number is NCT05276700. Written consent was obtained from patients for participation in the study.

Statistical analysis

The collected data were coded, processed, and analyzed using SPSS version 22 for Windows^® (IBM SPSS Inc., Chicago, IL, United States). The data were tested for normal distribution using the Shapiro-Wilk test. Qualitative data were presented as frequencies and relative percentages. Quantitative data were expressed as mean ± SD. The χ² test was used to compare the qualitative data between the two groups, while the independent t-test was used for the quantitative data. A paired t-test was used to compare baseline and follow-up laboratory data. A P < 0.05 was considered significant.

RESULTS

The demographic and laboratory characteristics of both groups are summarized in Table 1. There was no statistically significant difference between cases and controls in terms of age and gender. A history of HCV treatment was reported in only 27 patients (34.2%). In the HCV-positive group, the viral load was measured by polymerase chain reaction (PCR), with the titer above the detection limit in 41 patients (51.9%) and below the detection limit in 38 patients (48.1%). The median (range) was 250000.0 (439.0-3586722.0) in patients with a detectable titer.

Table 1 Demographic and laboratory characteristics of studied populations, mean ± SD (range)/n (%)/median (interquartile range).

Variables	Cases (n = 79)	Controls (n = 79)	P value (F1)1
Age	49.92 ± 17.23 (20-80)	45.92 ± 16.42 (20-88)	0.140
Gender			0.737
Male	53 (67.1)	51 (64.6)
Female	26 (32.9)	28 (35.4)
Blood picture
White blood cells	5 (2.0-10.0)	5 (2.4-10.0)	0.083
Hemoglobin	12.13 ± 1.77 (8.0-16.0)	12.90 ± 2.01 (6.5-17.0)	0.012
Platelets	191.00 (34-519)	275.00 (68-815)	< 0.001
Kidney functions
Blood urea	4.51 ± 1.43 (2.0-10.0)	4.60 ± 1.21 (2.6-9.0)	0.702
Serum creatinine	72.87 ± 26.48 (30-181)	72.51 ± 17.27 (30-120)	0.919
eGFR	103.92 ± 29.23 (32-175)	101.78 ± 21.80 (55-151)	0.605
Urinary alpha-one-microglobulin	4.11 ± 1.52 (2.11-9.18)	2.54 ± 0.78 (0.77-3.97)	< 0.001
Liver function tests
Total bilirubin	8.00 (3.0-136.0)	7.00 (1.0-19.0)	0.141
Direct bilirubin	5.50 (0.9-96.0)	4.00 (1.0-13.0)	< 0.001
Aspartate aminotransferase	40.00 (12-124)	26.00 (10-87)	< 0.001
Alanine aminotransferase	38.00 (10-130)	26.00 (7-130)	< 0.001
Alkaline phosphatase	67.00 (40-466)	55.00 (38-90)	< 0.001
Albumin	33.90 ± 7.17 (13.0-49.0)	36.87 ± 4.19 (28.0-46.0)	0.002
Coagulation profile
Prothrombin concentration			< 0.001
Normal	54 (70.1)	79 (100.0)
Impaired	23 (29.9)	0 (0.0)
INR			< 0.001
Normal	54 (70.1)	79 (100.0)
Impaired	23 (29.9)	0 (0.0)
Blood glucose			0.999
Normal	78 (98.7)	79 (100.0)
High	1 (1.3)	0 (0.0)
Hemoglobin A1C			0.999
Normal	78 (98.7)	79 (100.0)
Abnormal	1 (1.3)	0 (0.0)

¹F1: Independent t-test quantitative data between two groups. χ² test for qualitative data between the two groups.

eGFR: Estimated glomerular filtration rate; INR: International normalized ratio.

Laboratory investigations revealed significant hematological and hepatic differences between the two groups. The mean hemoglobin (Hb) level was significantly lower in HCV cases compared to controls (P = 0.012). Additionally, the platelet count was significantly lower among HCV patients compared with controls (P < 0.001), whereas no significant difference was found in white blood cell counts (P = 0.083; Table 1).

Renal function parameters, including BUN, SCr, and eGFR, showed no statistically significant differences between the groups. However, liver function tests demonstrated substantial impairment in the HCV group. The median direct bilirubin (DB) level was significantly higher among cases than among controls (P < 0.001). Similarly, aspartate aminotransferase (AST; P < 0.001), alanine aminotransferase (ALT; P < 0.001), and alkaline phosphatase (ALP; P < 0.001) levels were all markedly elevated among HCV patients, while mean serum albumin was significantly lower (P = 0.002; Table 1). Abdominal ultrasonography revealed liver cirrhosis in 32 patients (40.5%) with HCV, while none of the controls showed this finding.

Urinary findings demonstrated notable renal involvement in the HCV group. As shown in Figure 1, the median UACR was significantly higher in HCV-positive patients compared with controls (P < 0.001). Both microalbuminuria (38.0%) and macroalbuminuria (48.1%) had higher prevalence among HCV cases compared to controls (32.9% and 27.8%, respectively). Uα1M levels were significantly higher in HCV patients compared with controls (P < 0.001; Table 1).

Figure 1  Distribution of urine albumin-to-creatinine ratio in the cases and controls.

Statistical analysis revealed a moderate positive correlation between Uα1M and BUN (P < 0.001) and a mild positive correlation with SCr (P = 0.003). Conversely, Uα1M correlated negatively with eGFR (P = 0.017), AST (P = 0.039), and ALT (P = 0.023), but not significantly with UACR or platelets (Table 2).

Table 2 Correlation between Urinary alpha one microglobulin and other variables among studied patients with hepatitis C virus.

Variables	Urinary alpha one microglobulin
	r	P value
Age	-0.122	0.291
Kidney functions
Blood urea nitrogen	0.456	< 0.001
Serum creatinine	0.355	0.003
Estimated glomerular filtration rate	-0.267	0.017
Urine albumin/creatinine ratio	0.050	0.659
Liver function tests
Total bilirubin	-0.050	0.664
Direct bilirubin	-0.023	0.843
Aspartate aminotransferase	-0.233	0.039
Alanine aminotransferase	-0.256	0.023
Alkaline phosphatase	-0.113	0.320
Albumin	-0.209	0.065
Polymerase chain reaction value	0.228	0.152
Blood picture
White blood cells	0.146	0.206
Hemoglobin	-0.022	0.847
Platelets	0.071	0.538

As shown in Table 3, Uα1M levels were significantly higher in patients with hematuria compared to those without (P = 0.007). Similarly, patients with impaired eGFR demonstrated substantially higher Uα1M levels compared to those with preserved eGFR (P < 0.001). No significant differences were observed in terms of proteinuria status or overall renal injury composite score.

Table 3 Difference in urinary alpha-one-microglobulin according to renal injury among patients with hepatitis C virus, mean ± SD (range).

Variables	Urinary alpha one microglobulin (n = 79)	P value
Hematuria		0.007
Normal	3.76 ± 1.34 (2.11-9.02)
Hematuria	4.71 ± 1.67 (2.50-9.18)
Proteinuria		0.311
Normal	3.67 ± 1.06 (2.34-5.33)
Proteinuria	4.18 ± 1.59 (2.11-9.18)
Estimated glomerular filtration rate		< 0.001
< 60 (impaired)	6.35 ± 2.54 (2.74-9.18)
≥ 60	3.89 ± 1.22 (2.11-7.00)
Renal injury		0.235
Yes	4.17 ± 1.56(2.11-9.18)
No	3.45 ± 1.01 (2.34-5.00)

Renal biopsy findings were available for five HCV-positive patients (Table 4). All biopsied cases revealed membranoproliferative glomerulonephritis (MPGN). Their mean age was 38.80 ± 14.85 years, 60% were female, and 60% exhibited impaired eGFR (< 60 mL/minute/1.73 m²). All biopsy-proven cases had macroalbuminuria, hematuria, and proteinuria, and 60% had abnormal C3/C4 levels. The descriptive data for the remaining HCV-positive patients are presented with those of patients with renal biopsy (Table 4).

Table 4 Characteristics of hepatitis c virus-positive patients groups based on presence or absence of a renal biopsy, mean ± SD (range)/n (%)/median (interquartile range).

Variables	Patients with renal biopsy (n = 5)	Patients without renal biopsy (n = 74)
Age	38.80 ± 14.85 (26-59)	50.80 ± 16.987 (20-80)
Sex
Male	2 (40.0)	23 (31.1)
Female	3 (60.0)	51 (68.9)
Kidney functions
Blood urea nitrogen	7.60 ± 2.51 (4.0-10.0)	4.3 ± 1.7 (2-10)
Serum creatinine	125.80 ± 42.72 (67-181)	75.8 ± 26.9 (43-146)
Estimated glomerular filtration rate (mL/minute/1.73 m2)	58.20 ± 26.65 (32-100)	106.32 ± 27.017 (44-175)
< 60 (impaired)	3 (60.0)	4 (5.4)
≥ 60	2 (40.0)	70 (94.6)
Urine albumin-to-creatinine ratio	2300.00 (1500.0-3500.0)	553.23 (13.40-1131.8)
Macroalbuminuria	5 (100.0)	34 (45.9)
Hematuria	5 (100.0)	39 (52.7)
C3/C4
Normal	2 (40.0)	68 (91.9)
Abnormal	3 (60.0)	6 (8.1)
PCR for HCV
Detectable	0 (0)	41 (55.4)
Below detection limit	5 (100.0)	33 (44.6)
Uα1M	6.12 ± 2.36 (4.33-9.187)	3.976 ± 1.383 (2.116-9.022)

C3: Complement 3; C4: Complement 4; PCR: Polymerase chain reaction; HCV: Hepatitis C virus; Uα1M: Urinary alpha-one microglobulin.

The mean Uα1M among these patients was 6.12 ± 2.36 mg/L, and all were PCR negative at the time of sampling. The diagnostic performance of Uα1M in differentiating HCV-positive from HCV-negative individuals is presented in Figure 2 and Table 5.

Figure 2 Receiver operating characteristic curve for the diagnostic ability of urinary alpha-one-microglobulin to differentiate between patients with hepatitis C virus and controls. AUC: Area under the curve.

Table 5 Diagnostic ability of Urinary alpha-one-microglobulin to differentiate between patients with hepatitis C virus and controls.

Indices	Urinary alpha-one-microglobulin
AUC (95%CI)	0.864 (0.801-0.913)
Optimal cut off	> 3.52 mg/L
Accuracy	77.0%
Sensitivity	60.0%
Specificity	93.7%
Positive predictive value	90.4%
Negative predictive value	69.8%
P value	< 0.001

AUC: Area under the curve; CI: Confidence interval.

DISCUSSION

HCV infection causes kidney damage, which is often discovered late with established CKD[1]. In the current study, we investigated the role of Uα1M in identifying the kidney manifestations in HCV patients.

The current study found that both groups had comparable demographic data as regards age. It found no statistically significant difference in mean age or gender distribution. This finding was parallel to the findings of Saxena et al[12] and Sonbol et al[13]. In contrast, Niu et al[14] observed that HCV prevalence was higher in females before the age of 60 but higher in males after the age of 60. This highlights the potential for large, prospective studies to reveal age-dependent demographic shifts not captured in smaller cohorts. This may be due to different genotypes of the virus studied. In addition, Abdelhamid et al[15] reported a predominance of females (56.7%), suggesting that gender balance in HCV cohorts can vary, potentially due to differences in immune response or population selection.

This study showed significantly lower mean Hb levels and median platelet counts. However, there was no statistically significant difference in routine kidney functions (BUN and SCr) among HCV cases, which was well-supported by the literature. Bagheri et al[16] reported a similar low mean Hb in their HCV cases, and Rasheed et al[17] confirmed both low mean Hb and median platelet levels. This aligns with the common understanding that chronic HCV infection can lead to cytopenia, often via mechanisms like chronic inflammation and splenic sequestration (hypersplenism) due to liver disease. This study showed significantly lower mean Hb level and median platelet count. However, routine kidney functions (BUN and SCr) among HCV cases showed insignificant differences, and the literature supports these findings. Bagheri et al[16] reported a similar low mean Hb in their HCV cases, and Rasheed et al[17] confirmed both low mean Hb and median platelet levels. This aligns with the common understanding that chronic HCV infection can lead to cytopenia, often via mechanisms like chronic inflammation and splenic sequestration (hypersplenism) due to liver disease.

This study revealed that the median levels of DB, AST, ALT, and ALP were significantly higher in HCV-positive patients than in controls. However, the mean serum albumin was significantly lower in the HCV group. The elevation of AST and ALT may reflect ongoing hepatic inflammation and hepatocellular injury. However, the reduction in albumin may indicate impaired hepatic synthetic capacity. These findings are in agreement with those of Bagheri et al[16] and Halim et al[18], who both reported significantly elevated DB, ALT, and ALP levels and decreased albumin concentrations in HCV-infected individuals. Furthermore, Halim et al[18] and Tsui et al[19] confirmed the consistent elevation of AST and ALT among HCV patients. In contrast, Bagheri et al[16] did not observe a significant difference in AST levels, which they attributed to their study’s focus on early HCV detection, suggesting that AST elevation may not be pronounced during the initial phase of infection.

Also, this study found no significant difference in total bilirubin (TB). However, Mahmoud et al[20] reported significantly high TB in HCV cases, but their mean albumin and ALP levels were within the normal range. These differences are likely due to variations in sample size. Patients in the study by Mahmoud et al[20] were all HCV treatment-naïve. This underscores that while AST and ALT reflect active inflammation, albumin and TB are more reflective of the liver's overall synthetic and excretory capacity, which can vary widely depending on the stage of HCV disease and nutritional status[21].

This study found a statistically significant prolonged prothrombin concentration (prothrombin time) and impaired international normalized ratio (INR) among HCV cases compared to controls. This was consistent with the understanding that chronic HCV infection compromises the liver’s ability to synthesize essential coagulation factors. Leticia et al[22] supported this, reporting significant changes in coagulation parameters - including prolonged prothrombin time and activated partial thromboplastin time - in subjects with various hepatitis infections, including HCV. In contrast, Mahmoud et al[20] reported a statistically insignificant difference in prothrombin time concentration and INR among their chronic HCV cases. This difference is likely due to the composition of the study populations: Mahmoud et al’s patients[20] were all HCV treatment-naïve, while the current study included a significant proportion of cirrhotic patients (40.5%). Prothrombin time and INR are markers of the liver's synthetic function, and their impairment (prolongation) is directly correlated with the severity of liver damage, particularly the progression to cirrhosis.

This study demonstrated a statistically significant increase in the median UACR among HCV-positive patients compared to the controls. This was accompanied by a higher prevalence of both microalbuminuria and macroalbuminuria in the HCV group. These findings are consistent with the results of Kurbanova and Qayyum[23], who conducted a large-scale study involving more than 33000 participants. Their results similarly showed a significantly higher median UACR in HCV-positive patients than in HCV-negative subjects. In addition, a greater proportion of cases with microalbuminuria and macroalbuminuria (defined as UACR > 30 mg/g) were found among patients with HCV[23].

Moreover, the present study found a significantly higher frequency of proteinuria in HCV-infected cases compared with controls. However, there were no significant differences between the two groups regarding isolated hematuria or reduced eGFR. When renal injury was defined as the presence of any abnormal component (hematuria, proteinuria, or impaired eGFR), its overall prevalence was significantly higher in the HCV group. This occurred despite the generally normal eGFR values. These results are supported by Sohal et al[24], who specifically noted in their analysis of HCV renal manifestations that infected patients frequently experience complications like proteinuria and nephrotic syndrome, which can occur with or without a reduction in glomerular filtration rate[23]. Additionally, Fabrizi et al[25] assessed the serologic status of HCV in the adult general population and confirmed a definitive relationship between HCV infection and the risk of proteinuria.

This study demonstrated a significantly higher mean Uα1M level in HCV-positive patients than in healthy controls. Similarly, Kaartinen et al[5] reported that tubular proteinuria represents the most common early renal manifestation among HCV-positive individuals. In addition, the systematic review by Penders and Delanghe[26] supported the broader understanding that elevated Uα1M levels often indicate impaired kidney or liver function, which aligns with the increased Uα1M concentrations observed in patients with chronic liver disease in the current study.

Uα1M showed a statistically significant moderate positive correlation with BUN and a mild positive correlation with SCr. Conversely, a mild negative correlation was observed with eGFR. This pattern of correlation suggests that Uα1M levels are tied to the overall deterioration of kidney function. The moderate correlation with BUN specifically highlights that tubular damage and the kidney’s waste filtration capacity decline in an interconnected manner in HCV patients[27]. These results align with previous studies, such as Penders and Delanghe[26], who found a significant positive correlation with SCr, and Kusano et al[28], who noted that Uα1M inversely correlated with eGFR, reflecting increasing tubular injury as filtration decreased. Although Ayatse and Kwan[29] reported Uα1M increasing with decreased kidney function, they noted a weaker overall correlation.

The current study also found a statistically significant, mild negative correlation with AST and ALT, but no statistically significant correlation with UACR. The lack of correlation between Uα1M (as a tubular marker) and UACR (as a glomerular marker) suggests that the tubular damage and glomerular damage are distinct or sequential processes. This contrasts with Hong et al[30], who reported a direct relationship between Uα1M and albuminuria severity, potentially due to the selection of diabetic patients in their study, a condition in which both glomerular and tubular damage are simultaneously advanced.

The current study showed a significantly higher mean level of Uα1M among patients with hematuria and those with impaired eGFR compared to normal controls. However, there was no statistically significant difference in Uα1M based on the presence of proteinuria or the overall composite definition of renal injury. The elevated levels of Uα1M observed in patients with reduced eGFR support its role as a sensitive indicator of kidney injury, as impaired renal function compromises its tubular reabsorption. The absence of a significant correlation between Uα1M and proteinuria is consistent with the fact that Uα1M primarily reflects tubular dysfunction, whereas proteinuria (particularly albuminuria) indicates glomerular permeability[5,26]. Since these two entities represent distinct pathological processes, their markers may not necessarily correlate, especially in the early stages of HCV-related nephropathy. Similarly, Kaartinen et al[5] demonstrated that Uα1M serves mainly as a marker of tubular function rather than glomerular leakage. In their study population, Uα1M levels were independent of, or only weakly associated with, conventional glomerular markers, such as the UACR and total proteinuria[5].

Furthermore, the presence of hematuria - indicative of glomerular or urinary tract bleeding - did not show a significant correlation with tubular proteinuria as assessed by Uα1M level. The current study showed no statistically significant difference in Uα1M levels based on PCR results (viral load or HCV RNA levels). This result is consistent with Kaartinen et al[5], who found that Uα1M was not significantly correlated with variables related to chronic HCV infection, such as viral load. This suggests that the kidney damage indicated by Uα1M is likely due to the chronic immune response and inflammation triggered by the HCV infection over time, rather than being directly dependent on the absolute quantity or genotype of the virus currently present.

In the current study, 5 patients underwent a renal biopsy: All of them had MPGN. All cases were below the detection limit of PCR; the mean Uα1M was 6.12 ± 2.36. Supporting our findings, Sohal et al[24] mentioned that the primary glomerular lesion associated with HCV infection is cryoglobulinemic MPGN. Additionally, membranous glomerulonephritis may occur in cases of HCV infection, but it is more commonly associated with non-HCV infections. Additionally, Angeletti et al[31] reviewed the literature to assess HCV-associated nephropathies in the era of direct-acting antiviral agents. They illustrated that renal impairment in chronic HCV infection is mostly related to mixed cryoglobulinemia, which is a systemic vasculitis that mainly affects small-sized vessels and that in the kidney generally leads to MPGN[31].

Our findings showed that the diagnostic ability of Uα1M to differentiate between patients with HCV and controls. At the cut-off point > 3.52 mg/L, Uα1M has an accuracy of 77.0%, sensitivity of 60.0%, specificity of 93.7%, PPV of 90.4%, and negative predictive value of 69.8%, area under the curve = 0.864 to differentiate between patients with HCV and controls. Similarly, Kaartinen et al[5] reported that tubular cell damage may be the earliest sign of renal dysfunction caused by HCV, indicating that Uα1M can be used as a biomarker for detecting damaged renal tubules.

Limitations of the current study were the small number of patients with renal biopsy and the single-center design. The former hindered the confirmation of renal damage in patients with HCV and comparative analysis with the remaining HCV-positive patients. However, the latter character may limit the generalizability of the current results. Additionally, cryoglobulin levels were not measured for either the patients or the controls in the current study. Furthermore, the long-term follow-up of the patients was not feasible with the current study design and aim, representing a further limitation.

CONCLUSION

Uα1M serves as a valuable early renal tubular biomarker for detecting subclinical kidney involvement in chronic HCV patients, highlighting its potential for early diagnosis before overt renal impairment occurs. HCV-positive patients exhibited higher Uα1M levels, with a higher prevalence of proteinuria, microalbuminuria, and renal injury (hematuria, proteinuria, or impaired eGFR) compared to HCV-negative individuals.