Summary
This study aimed to assess whether routine nephrology examinations could predict renal amyloidosis in kidney disease patients with monoclonal gammopathy. A total of 356 consecutive hospitalized patients in the nephrology department with monoclonal gammopathy performed renal biopsies, including 50 renal amyloidosis patients and 306 non‐renal amyloidosis patients, were included after strict filtering. Laboratory and imaging data were collected for each patient. Renal amyloidosis patients exhibited significantly higher 24‐h proteinuria and estimated glomerular filtration rate and decreased serum creatinine (SCr), albumin and immunoglobin M, with lower κ light chain and κ/λ ratio in urine and serum. Higher 24‐h proteinuria and 24‐h microalbuminuria and lower random urine κ/λ ratio, serum κ light chain, serum κ/λ ratio and SCr were significant risk factors for renal amyloidosis. Nomogram model identified albumin, 24‐h urinary microalbumin excretion rate, 24‐h urine κ light chain, 24‐h urine κ/λ ratio and serum IgM as combined predictors of renal amyloidosis (area under the curve 0.781, 95% CI 0.718–0.854). Combined biomarkers (albumin, 24‐h urinary microalbumin excretion rate, 24 h urine κ light chain, 24‐h urine κ/λ ratio and serum IgM) effectively predicted renal amyloidosis in kidney disease patients with monoclonal gammopathy.
Keywords: diagnosis, monoclonal gammopathy, renal amyloidosis
INTRODUCTION
The M proteins in monoclonal gammopathy of undetermined significance (MGUS) are produced by malignant transformation of plasma cells or B lymphocytes. M proteins can be intact immunoglobulin G (IgG), A (IgA) or M (IgM) (or rarely immunoglobulin D (IgD) and E (IgE))—comprising heavy chains covalently bound to κ or λ light chains. 1 MGUS is typically divided into non‐IgM MGUS, which progresses to multiple myeloma (MM) or light chain amyloidosis (AL) at a rate of 1% annually; IgM MGUS, which progresses to the lymphoplasmacytic lymphoma Waldenström macroglobulinaemia (or rarely IgM MM) at a rate of 1.5% annually 2 ; and light‐chain MGUS, which progresses to AL amyloidosis or light‐chain MM. Evaluation for monoclonal gammopathy involves a trio of complementary tests: the serum protein electrophoresis (SPEP), immunofixation (IFE) and serum free light chain (FLC). Combined, these tests identify more than 97% of patients with a monoclonal gammopathy. 3 Monoclonal gammopathy of renal significance (MGRS) is a spectrum of kidney diseases associated with nephrotoxic monoclonal immunoglobulins secreted by B‐cell or plasma‐cell clones but does not meet any current haematological criteria, 4 including non‐organized deposits or inclusions such as monoclonal immunoglobulin deposition disease (MIDD) and proliferative glomerulonephritis with monoclonal immunoglobulin deposits (PGNMID) as well as organized deposits such as immunoglobulin light chain amyloidosis and light chain proximal tubulopathy (LCPT). 4 , 5 A kidney biopsy is usually indicated for significant proteinuria and/or renal insufficiency but is even more important when a monoclonal gammopathy is present. Immunofluorescence study should be performed on all suspected cases. Because MGRS may exhibit low levels of circulating monoclonal protein, immunofixation should be performed along with protein electrophoresis as well as serum free light chain assay to increase sensitivity. 3 Even when immunofixation is negative, an abnormal serum free light chain ratio can help identify the pathological light chain involved in the kidney disease. 6 , 7 In patients with MGRS, end‐stage renal disease stands to be the most severe complication. Twenty‐two per cent of patients with MGRS in a retrospective study of 37 patients went on to develop ESRD at a mean follow‐up of 30 months. 8 This shows the importance of proper diagnosis and management. Monoclonal protein studies should be performed on all patients with MGRS‐associated renal lesions, even those that are only occasionally associated with MGRS.
Renal amyloidosis has specific features depending on the affected renal structures (e.g. glomeruli, tubulointerstitial and arteries) and the distribution of the renal deposits (diffuse or focal). 9 Conversely, the wide range of morphological alterations and corresponding clinical manifestations may be observed at the same amyloidosis type. 10 , 11 In addition to kidney abnormalities, patients often have extra‐renal disease manifestations. 12 , 13 Amyloid deposition in myocardium is associated with inferior patient survival 14 ; meanwhile, kidney amyloid deposition results in end‐stage kidney disease that requires renal replacement therapy. 13 , 15 Renal biopsy is the gold standard requirement for the diagnosis of renal amyloidosis while biomarkers and imaging studies can be suggestive. 16 Congo Red and Thioflavin S are the two major histological stains used to detect any form of amyloid. The biopsy is usually preceded by an extensive diagnostic workup including but not limited to: serum free light chain assay, serum and urine protein electrophoresis with immunofixation, a complete blood count, liver and renal function tests, 24‐h urine protein and quantitative immunoglobulin levels. 16 , 17 The serum FLC immunoassay used for calculating the FLC κ/λ ratio had less sensitivity (76%). 18 FLC κ/λ ratio outside of the physiological range (0.26–1.65) with high urine albumin levels implicates renal amyloidosis. 19
The diagnostic dilemma of renal amyloidosis is the paradox between high risk of post‐kidney biopsy bleeding and clinical demand for gold standard pathological diagnosis of kidney involvement with systemic amyloidosis. 20 , 21 Delayed diagnosis due to indecisiveness may cause patients to lose the opportunity for timely treatment. 20 Since the therapeutic efficacy of renal amyloidosis largely depends on the stage at which the treatment is initiated, a non‐invasive screening technique for renal amyloidosis might enable earlier detection of the disease and subsequent improvement of both renal prognosis and life prognosis in these patients.
In this regard, further study of functional and pathological properties of human amyloid proteins is essential for establishing a safer diagnostic strategy for renal amyloidosis, which includes an early non‐invasive screening followed by well‐prepared biopsy. Our study revealed that the combined biomarkers (albumin, 24‐h urinary microalbumin excretion rate, 24‐h urine κ light chain, 24‐h urine κ/λ ratio and serum IgM) effectively predicted renal amyloidosis in hospitalized kidney disease patients with monoclonal gammopathy, thereby providing valuable insights into the diagnostic process for renal amyloidosis.
METHODS
Definition
Bleeding complications were defined according to the International Society on Thrombosis and Haemostasis (ISTH)Uric Acid criteria as follows: (1) fatal bleeding; (2) gross haematuria occurred within 3 days of biopsy and haemostatic drugs were required; (3) decreased haemoglobin levels by at least 2.0 g/dL; and (4) required packed red blood cell transfusions of two or more units. 22
The others
Study design, clinical data source, laboratory assays, renal pathology and statistical analysis were shown in Supporting Information Materials.
RESULTS
Patients and clinical feature descriptions
In the cohort of 356 patients with monoclonal gammopathy, 50 of them were diagnosed as amyloidosis, the other patients had non‐amyloidosis MGRS partly (Figure 1). There were MIDD for 3, PGNMID for 1, LCPT for 3, cast nephropathy for 21 and C3 nephropathy for 2. At baseline, 356 patients (28.20% ≥ 65 years; 71.35% male and 28.65% female) were analysed. Compared to patients in the non‐renal amyloidosis group, patients in the renal amyloidosis group were more likely to be ≥64 years, without haematuria. In addition, patients in the renal amyloidosis group had significantly performances of oedema and λ light chain M protein, as well as a higher prevalence of hypertension compared to those in the non‐renal amyloidosis group. They were comparable in the remaining parameters, including sex, BMI and diabetes. Four patients (8.0%) diagnosed with renal amyloidosis and 29 patients (9.5%) not diagnosed with amyloidosis had bleeding complications during their renal biopsies. Patients diagnosed with renal amyloidosis did not have an increased incidence of bleeding complications compared to those without amyloidosis diagnoses (Tables 1 and 2).
FIGURE 1.
Patients screened, excluded and included during the study period. *Biopsy‐negative patients received at least 18 months of follow‐up to rule out renal amyloidosis.
TABLE 1.
Epidemiological characteristics of kidney disease patients with monoclonal gammopathy.
| Category | Non‐renal amyloidosis (n = 306) | Renal amyloidosis (n = 50) | Statistic value | p value |
|---|---|---|---|---|
| Sex | ‐ | 0.142 b | ||
| Male | 222 (72.5) | 32 (64.0) | ||
| Female | 84 (27.5) | 18 (36.0) | ||
| Age (years) | 60.00 [49.00, 68.00] | 64.00 [56.75, 67.25] | −2.171 | 0.030 c |
| BMI (kg/m2) | 23.88 [21.28, 26.48] | 22.99 [20.14, 25.11] | −1.858 | 0.063 c |
| Hypertension | ‐ | 0.002 b | ||
| Yes | 138 (45.1) | 34 (68.0) | ||
| No | 168 (54.9) | 16 (32.0) | ||
| Diabetes | 4.559 | 0.102 a | ||
| Yes | 241 (78.8) | 45 (90.0) | ||
| No | 65 (21.2) | 5 (10.0) |
Pearson's chi‐square test.
Fisher's exact test.
Mann–Whitney U‐test.
TABLE 2.
Clinical characteristics of kidney disease patients with monoclonal gammopathy.
| Category | Non‐renal amyloidosis (n = 306) | Renal amyloidosis (n = 50) | Statistic value | p value |
|---|---|---|---|---|
| 24‐h proteinuria (g/24 h) | 3.07 [1.13, 7.58] | 4.55 [2.72, 7.33] | −2.135 | 0.033 c |
| 24‐h microalbuminuria (mg/24 h) | 1815.50 [332.00, 4962.00] | 3217.80 [1711.40, 5421.43] | −2.796 | 0.005 c |
| 24‐h urinary microalbumin excretion rate (%) | 67.00 [37.18, 80.09] | 76.54 [65.56, 83.64] | −2.907 | 0.004 c |
| 24‐h urine κ light chain (mg/24 h) | 96.00 [36.35, 212.00] | 58.55 [33.88, 98.55] | −2.079 | 0.038 c |
| 24‐h urine λ light chain (mg/24 h) | 74.99 [27.13, 195.20] | 67.62 [33.86, 261.15] | −1.159 | 0.246 c |
| 24‐h urine κ/λ ratio | 1.63 [1.16, 2.12] | 0.59 [0.32, 1.26] | −4.866 | <0.001 c |
| Random urine κ light chain (mg) | 52.00 [19.65, 134.50] | 33.55 [23.70, 65.75] | −1.900 | 0.057 c |
| Random urine λ light chain (mg) | 47.50 [15.05, 117.00] | 43.25 [21.75, 226.00] | −0.974 | 0.330 c |
| Random urine κ/λ ratio | 1.60 [1.15, 2.15] | 0.56 [0.31, 1.30] | −4.873 | <0.001 c |
| Serum κ light chain (mg/L) | 1.85 [1.04, 3.13] | 1.21 [0.60, 2.06] | −3.680 | <0.001 c |
| Serum λ light chain (mg/L) | 1.36 [0.70, 2.27] | 1.19 [0.82, 2.12] | −0.058 | 0.953 c |
| Serum κ/λ ratio | 1.45 [0.99, 2.11] | 1.13 [0.40, 1.70] | −3.355 | 0.001 c |
| eGFR (mL/min/1.73 m2) | 57.53 [24.45, 87.05] | 85.42 [56.68, 94.13] | −3.219 | 0.001 c |
| SCr (μmol/L) | 115.50 [80.75, 213.50] | 80.00 [69.75, 111.00] | −4.341 | <0.001 c |
| UrUA (μmol/L) | 408.00 [330.75, 483.25] | 392.00 [348.75, 463.75] | −0.805 | 0.421 c |
| Albumin (g/L) | 30.00 [22.00, 38.25] | 25.00 [20.00, 33.00] | −2.830 | 0.005 c |
| Serum IgA (g/L) | 1.79 [1.13, 2.90] | 1.36 [0.61, 3.36] | −1.284 | 0.199 c |
| Serum IgM (g/L) | 0.86 [0.51, 1.35] | 0.64 [0.40, 0.96] | −2.135 | 0.033 c |
| Serum IgG (g/L) | 8.13 [4.81, 12.47] | 6.87 [4.48, 11.20] | −0.956 | 0.339 c |
| Left kidney diameter (mm) | 106.00 [100.00, 113.00] | 103.00 [99.00, 111.00] | −1.241 | 0.215 c |
| Right kidney diameter (mm) | 105.00 [99.00, 112.00] | 103.00 [97.00, 111.00] | −1.313 | 0.189 c |
| Average kidney diameter (mm) | 105.50 [100.50, 111.50] | 103.50 [97.25, 110.25] | −1.339 | 0.180 c |
| Oedema | ‐ | 0.012 b | ||
| Yes | 173 (56.5) | 38 (76.0) | ||
| No | 133 (43.5) | 12 (24.0) | ||
| Haematuria | ‐ | 0.014 b | ||
| Yes | 152 (49.7) | 15 (30.0) | ||
| No | 154 (50.3) | 35 (70.0) | ||
| M protein type | 8.501 | 0.014 a | ||
| κ light chain | 76 (37.1) | 6 (14.3) | ||
| λ light chain | 128 (62.4) | 36 (85.7) | ||
| Bleeding complications | ‐ |
1.000 b |
||
| Yes | 29 (9.5) | 4 (8.0) | ||
| No | 277 (90.5) | 46 (92.0) |
Abbreviations: SCr, serum creatinine; UA, uric acid.
Pearson's chi‐square test.
Fisher's exact test.
Mann–Whitney U‐test.
Renal amyloidosis patients exhibited significant differences in proteinuria levels. They were comparable in the remaining parameters, including λ light chains measured in 24‐h urine samples and blood serum, κ and λ light chains measured in random urine, uric acid, serum IgA, serum IgG and kidney diameter. More importantly, renal amyloidosis patients had significantly lower levels of the 24‐h urine κ light chain (p = 0.038), 24‐h urine κ/λ ratio (p < 0.001), random urine κ/λ ratio (p < 0.001), serum κ light chain (p < 0.001), serum κ/λ ratio (p = 0.001), serum creatinine (p < 0.001), albumin (p = 0.005) and serum IgM levels (p = 0.033) when compared with non‐renal amyloidosis patients. In contrast, renal amyloidosis patients showed significantly increased levels in 24‐h proteinuria (p = 0.033), 24‐h microalbuminuria (p = 0.005) and 24‐h urinary microalbumin excretion rate (p = 0.004) when compared with non‐renal amyloidosis patients. The estimated glomerular filtration rate (eGFR) in the renal amyloidosis group was consistently greater than in the other group (p = 0.001).
Univariate and multivariate analyses of risk factors for renal amyloidosis patients
The relationship between clinical manifestations and renal amyloidosis in kidney disease patients accompanied with monoclonal gammopathy was summarized in Table 3. In the univariate logistic regression model, the odds ratios (ORs) and 95% confidence intervals (CIs) for renal amyloidosis across the lowest to highest tertiles of 24‐h proteinuria (T1–T3) were 1.00 (reference), 2.82 (1.24–6.38) and 2.18 (0.94–5.08) respectively. Among the lowest to highest tertiles of 24‐h microalbuminuria (T1–T3), the ORs and 95% CIs for renal amyloidosis were 1.00 (reference), 5.04 (1.84–13.80) and 4.91 (1.78–13.52) respectively. As for 24‐h urinary microalbumin excretion rate, the ORs and 95% CIs for renal amyloidosis were 1.00 (reference), 2.78 (1.11–6.92) and 3.85 (1.58–9.38) respectively. The ORs and 95% CIs for renal amyloidosis across the lowest to highest tertiles of 24‐h urine κ light chain (T1–T3) were 3.57 (1.26–10.13), 6.59 (2.44–17.85) and 1.00 (reference) respectively. A significant association between 24‐h urine κ/λ ratio and renal amyloidosis was noted in T1 (OR: 7.91, 95% CI: 3.17–19.75, p < 0.001), as well as between random urine κ/λ ratio and renal amyloidosis in T1 (OR: 7.60, 95% CI: 3.04–18.99, p < 0.001). Serum κ light chain in T1 (OR = 3.93; 95% CI, 1.69–9.13, p < 0.001), serum κ/λ ratio in T1 (OR = 1.78, 95% CI 1.30–5.94, p = 0.009), eGFR in T3 (OR = 4.29, 95% CI 1.86–9.87, p = 0.001), serum creatinine in T3 (OR = 3.97, 95% CI 1.78–8.82, p = 0.001) and serum IgM in T3 (OR = 2.82, 95% CI 1.28–6.24, p = 0.010) were predictive factors for the renal amyloidosis patients.
TABLE 3.
Influencing factor identification for renal amyloidosis patients.
| Category | Univariable | Multivariate | ||
|---|---|---|---|---|
| OR (95% CI) | p value | OR (95% CI) | p value | |
| 24‐h proteinuria (g/24 h) | ||||
| T1 (<1.79) | Reference | |||
| T2 (1.79–5.74) | 2.82 (1.24–6.38) | 0.013 | ||
| T3 (>5.74) | 2.18 (0.94–5.08) | 0.007 | ||
| 24‐h microalbuminuria (mg/24 h) | ||||
| T1 (<884.49) | Reference | |||
| T2 (884.49–3891.38) | 5.04 (1.84–13.80) | 0.002 | ||
| T3 (>3891.38) | 4.91 (1.78–13.52) | 0.002 | ||
| 24‐h urinary microalbumin excretion rate (%) | ||||
| T1 (<55.63) | Reference | Reference | ||
| T2 (55.63–76.88) | 2.78 (1.11–6.92) | 0.020 | 3.72 (1.23–11.21) | 0.020 |
| T3 (>76.88) | 3.85 (1.58–9.38) | 0.003 | 5.16 (1.64–16.25) | 0.005 |
| 24‐h urine κ light chain (mg/24 h) | ||||
| T1 (<49.59) | 3.57 (1.26–10.13) | 0.017 | 5.27 (1.43–19.44) | 0.013 |
| T2 (49.59–141.82) | 6.59 (2.44–17.85) | <0.001 | 7.49 (2.32–24.18) | 0.001 |
| T3 (>141.82) | Reference | Reference | ||
| 24 h urine κ/λ ratio | ||||
| T1 (<1.19) | 7.91 (3.17–19.75) | <0.001 | 5.14 (1.81–14.61) | 0.002 |
| T2 (1.19–1.82) | 1.17 (0.38–3.59) | 0.788 | 0.69 (0.20–2.39) | 0.563 |
| T3 (>1.82) | Reference | Reference | ||
| Random urine κ/λ ratio | ||||
| T1 (<1.20) | 7.60 (3.04–18.99) | <0.001 | ||
| T2 (1.20–1.82) | 1.31 (0.44–3.90) | 0.629 | ||
| T3 (>1.82) | Reference | |||
| Serum κ light chain (mg/L) | ||||
| T1 (<1.22) | 3.93 (1.69–9.13) | 0.001 | ||
| T2 (1.22–2.60) | 2.08 (0.85–5.08) | 0.108 | ||
| T3 (>2.60) | Reference | |||
| Serum κ/λ ratio | ||||
| T1 (<1.14) | 1.78 (1.30–5.94) | 0.009 | ||
| T2 (1.14–1.80) | 1.56 (0.50–2.71) | 0.733 | ||
| T3 (>1.80) | Reference | |||
| eGFR (mL/min/1.73 m2) | ||||
| T1 (<42.27) | Reference | |||
| T2 (42.27–81.88) | 1.77 (0.71–4.38) | 0.220 | ||
| T3 (>81.88) | 4.29 (1.86–9.87) | 0.001 | ||
| SCr (μmol/L) | ||||
| T1 (<86) | 3.97 (1.78–8.82) | 0.001 | ||
| T2 (85–154) | 1.27 (0.52–3.15) | 0.600 | ||
| T3 (>154) | Reference | |||
| Albumin (g/L) | ||||
| T1 (<24) | 8.52 (2.47–29.36) | 0.001 | 15.44 (3.70–64.45) | <0.001 |
| T2 (24–35) | 8.57 (2.51–29.25) | 0.001 | 7.34 (1.96–27.54) | 0.003 |
| T3 (>35) | Reference | Reference | ||
| Serum IgM (g/L) | ||||
| T1 (<0.60) | 2.82 (1.28–6.24) | 0.010 | 3.58 (1.28–10.03) | 0.010 |
| T2 (0.60–1.12) | 1.57 (0.68–3.62) | 0.292 | 1.03 (0.36–2.93) | 0.955 |
| T3 (>1.12) | Reference | Reference | ||
Abbreviations: CI, confidence interval; OR, unadjusted odds ratio; SCr, serum creatinine.
A multivariate logistic regression model was constructed to explore the independent association between clinic performances and renal amyloidosis. After adjusting for multiple variables, the ORs and 95% CIs for renal amyloidosis across the lowest to highest tertiles of 24‐h urinary microalbumin excretion rate (T1–T3) were 1.00 (reference), 3.72 (1.23–11.21) and 5.16 (1.64–16.25) respectively. For renal amyloidosis across the lowest to highest tertiles of 24‐h urine κ light chain (T1–T3), the ORs and 95% CIs were 5.27 (1.43–19.44), 7.49 (2.32–24.18) and 1.00 (reference) respectively. The ORs and 95% CIs for renal amyloidosis across the lowest to highest tertiles of albumin were 15.44 (3.70–64.45), 7.34 (1.96–27.54) and 1.00 (reference) respectively. A significant association between 24‐h urine κ/λ ratio and renal amyloidosis was noted in T1 (OR: 5.14, 95% CI: 1.81–14.61, p = 0.002) as well as between serum IgM and renal amyloidosis in T1 (OR: 3.58, 95% CI: 1.28–10.03, p = 0.010).
Multivariable verification of risk factors for renal amyloidosis patients
This part we employed nomogram to investigate the association between renal amyloidosis and multiple clinical indicators mentioned in Table 3 (Figure 2A). Specifically, albumin level (β = −0.93, SE = 0.29, Wald Z = −3.20, p = 0.001), 24‐h urinary microalbumin excretion rate (β = 0.78, SE = 0.24, Wald Z = 3.20, p = 0.001), 24‐h urine κ light chain (β = −0.74, SE = 0.28, Wald Z = −2.69, p = 0.007), 24‐h urine κ/λ ratio (β = −1.14, SE = 0.29, Wald Z = −3.92, p < 0.001) and serum IgM level (β = −0.60, SE = 0.25, Wald Z = −2.43, p = 0.0151) all showed significant effects. Notably, the 24‐h urine κ/λ ratio exhibited the most significant effect, while 24‐h urinary microalbumin excretion rate was the only factor positively associated with renal amyloidosis. The calibration curve showed a close alignment with the nomogram, while the decision curve analysis (DCA) demonstrated favourable clinical utility (Figure 2B).
FIGURE 2.
The prognostic model for prediction of renal amyloidosis. (A) Nomogram predicting renal amyloidosis. (B) The calibration curves of the model. (C) The area under receiver operating characteristic curve (AUROC) curves of the model. [Colour figure can be viewed at wileyonlinelibrary.com]
Diagnostic efficiency of the nomogram for renal amyloidosis
We then evaluated the diagnostic performance of multiple biomarkers (albumin, 24‐h urinary microalbumin excretion rate, 24‐h urine κ light chain, 24‐h urine κ/λ ratio and serum IgM) in combination for predicting renal amyloidosis by ROC curve analysis (Figure 2C). Based on 500 bootstrap replications, the combined model showed an area under curve (AUC) of 0.781 (95% CI: 0.718–0.845), indicating moderate diagnostic accuracy. At the optimal predicted probability threshold of 0.146, the specificity was 0.685 and sensitivity was 0.830, with a Youden index of 0.515.
DISCUSSION
Patients diagnosed with AL amyloidosis had a higher level of proteinuria compared to the other monoclonal gammopathies. 23 , 24 The clinical manifestations of MGRS depend mainly on the affected nephron segment. 8 Yavuz Ayar et al. found that serum creatinine levels increased and eGFR values decreased after treatment in both the poor outcome group and the good outcome group. 25 Our study found that, compared with the non‐renal amyloidosis group, the renal amyloidosis group had lower serum creatinine and higher eGFR, which was suspected to be related to varied diseases in the non‐renal amyloidosis group, such as cast nephropathy. Kidney dysfunction (elevated creatinine or proteinuria) can also occur due to light‐chain cast nephropathy. 26 Renal injury is not only limited to glomerular lesions but also may be combined with tubular injury. There may be more complex and unknown factors of rapidly progressive injury. MGUS patients may be more variable.
Radiologically, kidney enlargement was observed in <15% of patients with renal amyloidosis, and this probably occurred in the early stage of disease, according to one study. 27 In internal medicine textbooks in China, if the kidney diameter was longer, it was necessary to differentiate from renal amyloidosis. While, in our retrospective study, there was no significant difference in kidney diameter between the renal amyloidosis group and the non‐renal amyloidosis group. It was considered that there might be diabetic nephropathy and acute kidney injury in the non‐renal amyloidosis group. It might also be related to the measurement methods of different ultrasound doctors.
Recent studies have proven that the size, type and the number of M proteins; the bone marrow plasmacytosis; and the free light chain ratio help identify patients at higher risk of progression. 28 Based on the heavy chain, the IgG subtype has been proven to be the most prevalent in detecting MGUS. 8 This subtype was seen in approximately 70% of patients, followed by the IgM subtype in 15% of patients, then the IgA subtype in 12%, and finally, the polyclonal gammopathy seen in 3% of patients with MGUS. 8 A prospective study by Landgren et al. in 2009 proved that patients with the IgM subtype would go on to have an increased risk of developing serious malignant conditions like non‐Hodgkin lymphoma, chronic lymphocytic leukaemia, amyloidosis and Waldenström macroglobulinaemia (WM) at a rate of 1.5% per year. 29 According to our research, patients in the renal amyloidosis group had significantly performances of oedema and λ light chain M protein compared to the non‐renal amyloidosis group. Through univariate and multivariate logistic regression analyses, we found that lower serum IgM level correlated with a higher risk of renal amyloidosis. Our study confirmed that 24‐h proteinuria and 24‐h microalbuminuria were higher in the renal amyloidosis group, indicating that glomerular podocyte space was larger, and basement membrane barrier damage was more serious. The normal serum level of IgM is the lowest while IgA and IgG are relatively higher, and the contents of IgD and IgE are too low to be routinely detected. Under the condition of losing the same quantification of immunoglobulin, the remaining IgA and IgG in serum should be more while IgM will be relatively less.
Patients with AL amyloidosis sometimes suffer from abnormal bleeding, which may occur in cutaneous/subcutaneous tissue, the gastrointestinal tract, renal tract, spleen, liver and others. 30 , 31 , 32 Many pathological theories for the cause of a bleeding tendency and haemostatic abnormalities have been previously reported, such as acquired coagulation factor deficiencies, especially factor X, 30 a thrombin inhibitor, 33 acquired hyperfibrinolysis, 34 acquired platelet dysfunction, 35 acquired von Willebrand syndrome 36 and amyloid angiopathy with increased fragility of blood vessels and impaired vasoconstriction. 30 Renal biopsy is an invasive examination, which may lead to a certain risk of bleeding. In addition, for patients with cirrhosis, end‐stage renal disease (ESRD), Henoch Schonlein purpura and those who take anticoagulants and antiplatelet drugs, there is also a higher risk of bleeding if renal biopsy is performed. Although patients diagnosed with renal amyloidosis did not have an increased incidence of bleeding complications compared to those without amyloidosis diagnoses in our study, we provided a fairly accurate prediction model, which was statistically significant, for patients accompanied with monoclonal gammopathy as well as high risk of bleeding through non‐invasive examination. Similarly, our prediction model could help medical units those are not qualified for renal biopsy to carry out relevant diagnosis and treatment. For patients with absolute contraindications of renal biopsy, such as solitary kidney, rectal mucosa biopsy or fatty biopsy can be performed instead of renal biopsy.
Our study showed that the combined biomarkers (albumin, 24‐h urinary microalbumin excretion rate, 24‐h urine κ light chain, 24‐h urine κ/λ ratio and serum IgM) had good discriminatory power for renal amyloidosis, particularly with high sensitivity, though the specificity was relatively low. Further validation in independent cohorts will be recommended, along with exploration of additional biomarkers to improve specificity. Our clinical data were partly missing, such as free light chain and M protein type, while there was a lack of monoclonal gammopathy of undetermined significance after kidney transplantation, 37 which was caused by imperfect early detection methods and high detection prices. Our study was a single‐centre retrospective study. In the future, we will co‐operate with multiple centres and include the follow‐up data to further explore the diagnostic model and prognosis of kidney disease patients accompanied with monoclonal gammopathy.
CONCLUSION
Unlike the traditional notion that considers Congo red staining a valuable measurement for renal amyloidosis, we found that higher 24‐h proteinuria, 24‐h microalbuminuria, 24‐h urinary microalbumin excretion rate and eGFR and lower 24 h urine κ light chain, 24 h urine κ/λ ratio, random urine κ/λ ratio, serum κ light chain, serum κ/λ ratio, SCr, serum IgM and albumin were independent risk factors for renal amyloidosis. In particular, the combined biomarkers (albumin, 24‐h urinary microalbumin excretion rate, 24‐h urine κ light chain, 24‐h urine κ/λ ratio and serum IgM) yielded better diagnostic efficiency and represented an effective parameter to sufficiently predict the possibility of renal amyloidosis for patients with kidney disease and monoclonal gammopathy. Our data suggested that patients with suspected renal amyloidosis could be screened out by measuring protein and light chain in both serum and urine through non‐invasive examination.
AUTHOR CONTRIBUTIONS
Yi Fang: Funding acquisition; writing – review and editing; project administration; conceptualization. Daxi Wang: Data curation. Siyu Bao: Data curation; writing – original draft; writing – review and editing; investigation; visualization. Hong Liu: Resources; validation. Wensi Bian: Data curation. Zixuan Xun: Data curation. Xiaoqiang Ding: Supervision; methodology. Yang Li: Software; funding acquisition; formal analysis. Zheng Wei: Project administration; funding acquisition; writing – review and editing; conceptualization.
FUNDING INFORMATION
This work was supported by the Science and Technology Commission of Shanghai Municipality (22410714200, International Science and Technology Cooperation Projects; 20DZ2271600, the project of Shanghai Key Laboratory of Kidney and Blood Purification; and 25SF1905500, Shanghai Science and Technology Commission's New Drug and Medical Device Application Demonstration Project) and Shanghai Municipal Key Clinical Specialty (shslczdzk02501).
CONFLICT OF INTEREST STATEMENT
The authors declare no competing interests.
ETHICS STATEMENT
This study was conducted in accordance with the Declaration of Helsinki. All patients gave written informed consent, and the Ethics Committee of Zhongshan Hospital approved the study (Approval number: B2025‐534).
PATIENT CONSENT STATEMENT
All patients gave written informed consent.
Supporting information
Data S1.
ACKNOWLEDGEMENTS
We would like to acknowledge the contributions of all the authors.
Contributor Information
Yi Fang, Email: fang.yi@zs-hospital.sh.cn.
Zheng Wei, Email: wei.zheng@zs-hospital.sh.cn.
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
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data S1.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.