Urinary plasminogen as a marker of disease progression in human glomerular disease

Abstract

Disclosed is a method of managing glomerular disease in a subject in need thereof, by identifying a subject suffering from glomerular disease; measuring the urinary plasmin(ogen) level in the subject; predicting disease progression based on the urinary plasmin(ogen) level; and treating the subject to manage the glomerular disease. Also disclosed is a method of treating glomerular disease in a subject in need thereof, by identifying a subject suffering from glomerular disease and having a urinary plasmin(ogen) level exceeding a predetermined threshold; and treating the subject to reduce the urinary plasmin(ogen) level. Also disclosed is a method of determining risk of progression to ESKD based on the measured / expected uPlasminogen ratio with a ratio of > 1.1 demonstrating a higher risk of progression than the ratio between 0.8-1.1, and a ratio of < 0.8 demonstrating a lower risk of progression. Also disclosed is an assay for measuring plasmin(ogen) levels in a sample.

Description

Attorney Docket No.: 27527-0216WO1-MSSM.220806 URINARY PLASMINOGEN AS A MARKER OF DISEASE PROGRESSION IN HUMAN GLOMERULAR DISEASE STATEMENT REGARDING GOVERNMENT FUNDING

[0001] This invention was made with government support grant DK 126477 awarded by the National institute of Health. The government has certain rights in the invention. CROSS-REFERENCE TO RELATED APPLICATION

[0002] The present application claims priority to U.S. Provisional Application Serial No. 63 / 492,010, filed on March 24, 2023, the contents of which are hereby incorporated by reference in their entirety. TECHNICAL FIELD

[0003] This disclosure is directed to a method of determining and treating disease progression in glomerular disease. More particularly, this disclosure is directed to a method of determining disease progression in glomerular disease with urinary plasminogen as a biomarker and treating same. BACKGROUND

[0004] Glomerular disorders, whether primary or secondary, represent a major cause of end stage kidney disease (ESKD) worldwide and an important cause of morbidity and mortality among children and adults.1,2Diagnostic and treatment decisions in glomerular disorders are principally based on renal pathology and nonspecific clinical laboratory measurements. Using these classification approaches, patients have marked variability in the rate of progression and response to therapy, and biomarkers that reflect molecular mechanisms underlying the clinical- pathologic diagnoses are needed.3SUMMARY

[0005] The present disclosure is directed to a method of managing glomerular disease in a subject in need thereof, by identifying a subject suffering from glomerular disease; measuring the urinary plasmin(ogen) level (the combined level of plasminogen and plasmin) in the subject; predicting disease progression based on the urinary plasmin(ogen) level; and treating the subject to manage the glomerular disease. Also disclosed is a methodAttorney Docket No.: 27527-0216WO1-MSSM.220806 of treating glomerular disease in a subject in need thereof, by identifying a subject suffering from glomerular disease and having a urinary plasmin(ogen) level exceeding a predetermined threshold; and treating the subject to reduce the urinary plasmin(ogen) level. Also disclosed is a method of determining risk of progression to ESKD based on the measured / expected uPlasminogen ratio, with a ratio of > 1.1 demonstrating a higher risk of progression than the ratio between 0.8-1.1, and a ratio of < 0.8 demonstrating a lower risk of progression. Also disclosed is an assay for measuring plasmin(ogen) levels in a sample. BRIEF DESCRIPTION OF THE FIGURES

[0006] Figure 1. Scatterplots showing correlation between Log2uPlasminogen / Cr and Log2UPCR (A) and eGFR (B) in the CureGN cohort.

[0007] Figure 2. Unadjusted Kaplan-Meier curves of ESKD-free survival based on uPlasminogen / Cr quintiles. Log-rank test for equality of survivor functions: P < 0.001.

[0008] Figure 3. Hazard Ratio (HR) for the association between Log2uPlasminogen / Cr and risk of ESKD among all participants and stratified analysis in subgroups by UPCR levels, diagnosis and APOL1 genotype. APOL1 analysis was performed in the subcohort of patients whose genotype information was available (Non APOL1 high-risk genotype n = 850, APOL1 high-risk genotype n = 57).

[0009] Figure 4. Scatterplot showing measured Log2uPlasminogen / Cr and expected Log2uPlasminogen / Cr (based on eGFR and Log2UPCR). Color indicates measured / expected uPlasminogen tertiles.

[0010] Figure 5. Unadjusted Kaplan-Meier curves of ESKD-free survival based on uPlasminogen / Cr levels (<1183.1 ug / g and ? 1183.1 ug / g). DETAILED DESCRIPTION

[0011] Glomerular diseases are an important cause of morbidity and mortality in patients of all ages. Knowing the individual risk of progression to dialysis or transplantation would help to plan the follow-up and treatment of these patients. Our work studies the usefulness of urinary plasminogen as a marker of progression in this context, since previous studies indicate that plasminogen may be involved in the mechanisms responsible for the progression of theseAttorney Docket No.: 27527-0216WO1-MSSM.220806 disorders. Our work in a sample of 1010 patients with glomerular disease demonstrates that urinary plasminogen (as well as the ratio of measured to expected plasminogen) is associated with the risk of progression to end-stage kidney disease. Urine plasminogen exhibited good performance and, if further validated, could enable risk stratification for timely interventions in patients with proteinuria and glomerular disease.

[0012] Glomerular disorders, whether primary or secondary, represent a major cause of end stage kidney disease (ESKD) worldwide and an important cause of morbidity and mortality among children and adults.1, 2With the exception of certain pathologies such as anti-phospholipase A2 receptor (anti-PLA2R) associated membranous nephropathy (MN), at present, diagnostic and treatment decisions in glomerular disorders are principally based on kidney pathology and nonspecific clinical laboratory measurements. Using these classification approaches, patients have marked variability in the rate of progression and response to therapy, and biomarkers that reflect molecular mechanisms underlying the clinical-pathologic diagnoses are needed.3

[0013] Regardless of the etiology of glomerular injury, proteinuria is a marker of kidney damage and a strong predictor of progression to ESKD.4-7Moreover, increasing proteinuria in the setting of chronic kidney disease (CKD) correlates with increased risk of cardiovascular disease and all-cause mortality.8-11Proteinuria severity is part of all prognostic scores in kidney diseases and therapeutic decisions depend largely on its values.1, 12, 13Beyond its role as a surrogate marker, proteinuria is considered a driver of tubulointerstitial injury, kidney fibrosis and CKD progression, with therapies directed to its reduction.14-17Albuminuria, the major component of glomerular proteinuria, has been linked to both glomerulosclerosis and tubulointerstitial injury via direct and indirect mechanisms.18-20

[0014] Less is known about other urinary components such us urinary serine proteases of which plasminogen and plasmin are significant contributors. Plasminogen is a 91 kDa glycoprotein zymogen synthesized primarily in the liver.21After its release into systemic circulation, plasminogen is cleaved into the serine protease plasmin. In its well described role in thrombolysis, plasmin degrades fibrin-containing clots, enabling thrombi dissolution.22In other processes, plasmin lyses protein barriers and contributes to extracellular matrixAttorney Docket No.: 27527-0216WO1-MSSM.220806 remodeling. In this latter context, plasmin activity is seen in inflammation, wound healing, tissue formation, angiogenesis, and embryogenesis.23-26

[0015] Different studies have shown significant quantities of urinary plasminogen / plasmin, or plasmin(ogen)uria, in proteinuric patients.27, 28The relationship described mainly focuses on the association between plasmin(ogen)uria and fluid retention through Na+ reabsorption via ENaC channels in the distal nephron. In these studies, the degree of plasmin(ogen)uria was shown to be clinically associated with volume overload in patients with CKD of diverse etiologies, though most reports have concentrated on a limited number of subjects and / or diagnoses.29-31In a cohort of 128 patients with glomerular disease, urinary excretion of plasmin(ogen) was reported as correlated with both proteinuria and albuminuria and inversely correlated with eGFR (estimated glomerular filtration rate) at the time of biopsy.32

[0016] In addition to these findings, plasmin(ogen) has been found to directly damage podocytes and potentiate glomerular injury experimentally. Prior studies by our group found that podocyte treatment with plasminogen results in direct podocyte injury via CD36 and oxidative stress dependent mechanisms as well as reduction in focal adhesion expression.33,32In vivo data also support this hypothesis in various rodent models of proteinuric kidney disease, in which plasmin(ogen)uria levels were correlated with an increased expression of CD36 and oxidative stress markers.33,32Of note, the ENaC inhibitor amiloride, a well-established inhibitor of uPA-mediated conversion of plasminogen to plasmin, ameliorated these effects in vitro and in vivo, highlighting the potential therapeutic options related to this pathway.32

[0017] In relation to the plasminogen and uPA pathway, uPA receptor (uPAR) and its soluble form suPAR have also been extensively studied in the context of CKD. uPAR is highly susceptible to proteolytic cleavage by several enzymes, including plasmin, which results in the release of suPAR. suPAR levels have been associated with incident CKD and progression of the disease in several studies and elevated plasma suPAR levels have been linked to podocyte integrin activation leading to injurious signaling and tubular mitochondrial function.36-38

[0018] Based on these overall findings, we hypothesized that in proteinuric subjects with biopsy-proven glomerular disease, excessive trans-glomerular plasminogen is converted to plasmin by the podocyte and that persistent exposure to plasmin serves as a “second hit” in glomerular diseases driving CKD progression independent of the initial insult. Therefore, we conducted the following study among a large well-defined cohort of patients with glomerularAttorney Docket No.: 27527-0216WO1-MSSM.220806 disease and a multicentric validation cohort to (i) explore the association of plasmin(ogen)uria with proteinuria and lower eGFR as well as other baseline characteristics and (ii) to investigate the potential independent value of plasmin(ogen)uria as a marker of disease progression. Example Study Data and Specimen Source:

[0019] CureGN is an ongoing international cohort study aiming to enroll 2400 adults and children with minimal change disease, focal segmental glomerulosclerosis, MN (membranous nephropathy), or IgA nephropathy, diagnosed by kidney biopsy within the 5 years before study enrollment. Institutionalized patients, those with end-stage renal disease at screening, or with diabetes, a prior organ / hematopoietic transplant, hepatitis B or C, HIV, malignancy, or systemic lupus erythematosus at time of biopsy, are excluded. Patients are recruited from 70 sites (65 in the United States, 3 in Canada, 1 in Italy, and 1 in Poland) and are identified either through receiving nephrology care at one of these sites or through referral from a primary treating nephrologist in the community. Enrollment and subsequent annual visits are conducted in person; interval 4-monthly study visits can be conducted in person or remotely (i.e., by telephone or e-mail). Research coordinators conduct all study visits and enter data, under the supervision of the site clinical principal investigator. All study subjects provided written informed consent. This study was approved by each institution’s review board in agreement with the Declaration of Helsinki.

[0020] All children and adults enrolled in CureGN by October, 2020 with a renal diagnosis of MN, FSGS (focal segmental glomerulosclerosis) or IgAN were considered for inclusion. The time from biopsy to plasmin(ogen) sample analysis was variable in each subject depending on the time of recruitment to CureGN and sample availability. Samples obtained were restricted to visits with eGFR value (either centrally or locally measured) available. Urine protein and creatinine were measured in the central laboratory from 24-hour or spot urine samples as available. Urine protein creatinine ratios (UPCR) were expressed as g / g. Urine plasminogen determination:

[0021] We developed a de novo electro-chemiluminescent immunoassay (ECLIA) method using a MSD (Meso Scale Discovery, Rockville, MD, USA) platform to measure urine plasmin(ogen) levels. Samples were stored at -80ºC prior to use. Human Plasminogen Protein,Attorney Docket No.: 27527-0216WO1-MSSM.220806 R&D (Item No: 1939-SE; R&D Systems, Inc., Minneapolis, MN) was used as a standard. Reproducibility with Human Plasminogen Total ELISA Kit (Item No: IHPLGKT-TOT; Innovative Research Novi, MI, USA), was confirmed. Samples were assessed in duplicates and concentrations were estimated from a standard curve. Intra- and inter-assay coefficient of variation values for the quality control samples were 4.3%, and 14.4% respectively. The average lower limit of detection obtained from multiple runs was 0.279 ng / ml. The laboratory personnel performing the biomarker assays were blinded to clinical information about the participants. Plasmin(ogen) levels were normalized to urinary creatinine to adjust for differences in urine concentration between participants. For the CureGN cohort, urine creatinine was measured in the central laboratory from specimens collected during study visits and if not available, it was measured by isotope dilution (LC-MSMS) at the UCSD O'Brien Core Center for Acute Kidney Injury Research (University of Alabama, Birmingham). Other analytical values were obtained from central laboratory measurements and enriched with data collected from local health records. Study Design:

[0022] The primary outcome was time to ESKD progression and the main predictor was plasmin(ogen)uria at baseline. Data analysis:

[0023] Descriptive analyses were performed using frequencies with percentages for categorical variables and medians with interquartile ranges (IQRs) for continuous variables. Unadjusted comparisons across groups were made using ?2, Kruskal-Wallis testing and non- parametric trend tests, as appropriate. Urinary markers were Log2 transformed to approximate normal distribution. Pearson correlations were calculated to examine potential associations between Log2uPlasminogen / Cr and Log2UPCR (urinary protein to creatinine ratio) or eGFR. The association between Log2uPlasminogen / Cr and the presence of edema was assessed by logistic regression. Multiple linear regression was used to study the association between plasminogen and baseline characteristics in the cohort and to develop an equation of expected plasminogen levels. Variables selected for inclusion in the model were selected by backwards stepwise multivariable model selection.

[0024] Cumulative incidence probabilities for progression to ESKD were estimated via the Kaplan-Meier method and survival curves by quintiles of urinary plasminogen / Cr wereAttorney Docket No.: 27527-0216WO1-MSSM.220806 compared by the log-rank test. The independent association between progression to ESKD and Log2uPlasminogen / Cr was evaluated by Cox proportional hazards regression. Data were censored at the date of death, ESKD or the date of last follow-up, whichever came first. Variables selected for adjustment were included in a backwards stepwise multivariable model selection. Covariates evaluated for inclusion were age, eGFR, Log2UPCR, prior disease duration (since renal biopsy), sex, race, ethnicity, kidney disease diagnosis, hypertension, diabetes, BMI, prior immunosuppressive therapy (y / n) and subsequent therapy at baseline. The predictive power of the different models was compared by calculating the AIC, BIC, C-index and R2.

[0025] The ratio between urine-measured plasmin(ogen) and predicted plasmin(ogen) (obtained by linear regression from eGFR and UPCR) was calculated in order to obtain a measure of plasmin(ogen) levels independent of these parameters. Once the ratio was calculated, analyses on the distribution of the parameter in the sample were obtained. Using Cox regression analysis, we analyzed whether the measured / expected urine plasmin(ogen) ratio organized by tertiles was associated with ESKD after adjustment for the clinical variables mentioned above.

[0026] To assess the ability of Log2uPlasminogen / Cr to discriminate between ESKD progressors and non-progressors at 3 years, logistic regression was performed and the area under the ROC (AUC) was calculated for different models. ROC curves were obtained for a Clinical model (age, sex, self-reported race, diagnosis and eGFR), Clinical model + Log2UPCR and Clinical model + Log2UPCR + Log2uPlasminogen / Cr. To test for the equality of the AUCs, the method suggested by DeLong was used.39To define a plasminogen / Cr threshold, we used the method described by Liu40to estimate the optimal cut-point that maximized the product of sensitivity and specificity for the prediction of 3-year rate progression to ESKD in the cohort. Statistical analyses were performed with Stata software, version 17, (www.stata.com). For analysis of all possible Cox regression models and AIC, BIC and Harrell´s C calculation and for cut-point definition user-written commands “allsets” and “cutpt” were used respectively. Plasminogen Assay protocol:

[0027] Plasminogen levels in urine samples were determined using DuoSet ELISA cat# DY1939-05, Human Plasminogen Protein, CF Catalog #: 1939-SE, Human PlasminogenAttorney Docket No.: 27527-0216WO1-MSSM.220806 Capture Antibody; Part Number 844974 (mouse anti-human): Human Plasminogen Detection Antibody, Part Number 844975 (biotinylated mouse anti-human); from Bio-techne R&D system combined with Meso Scale Diagnostics (MSD) products: 1. MULTI-ARRAY® 96-well Plate Pack (10 Plate) MSD cat# L15XB 2. MSD Blocker A Kit, cat# R93AA-2 3. MSD SULFO-TAG Streptavidin, cat# R32AD-1 4. MSD GOLD Read Buffer B, cat# R60AM Day 1 Step 1: Coat plate

[0028] Prepare 3.2 ml of the capture antibody at a concentration of 6 µg / mL diluted in PBS. Add 30 µL of the capture antibody to the bottom corner of each well of the MULTI-ARRAY® 96-well plates. Tap the sides to ensure the bottom is evenly coated. Seal the plate and incubate without shaking overnight at 4C. Day 2 Step 2: Block plate

[0029] Do not wash the plate. Add 150 µL of RT 1% Blocker A in PBS to each well of the MSD plate. Seal the plate and incubate with shaking for 1 h at RT. Step 3: Wash and add standards and samples

[0030] Wash the plate 3X with 150 uL of PBST. After washing, gently tap the plate to remove any residual wash buffer.

[0031] Add 50 µL per well of standards, specimens according to the plate map. Seal the plate and incubate with shaking for 2 h at RT. Standards: Diluent(1% Total C lib t Dil tiAttorney Docket No.: 27527-0216WO1-MSSM.220806 S003 33 3 280 140 S004 11 3 280 140Step 4: Wash and add detection Ab

[0032] Prepare 3 mL of the reconstituted detection antibody at 1 ug / mL concentration diluted in 1% Blocker A. Pipette 25 µL per well of detector antibody solution across the plate. Seal the plate and incubate with shaking for 1 h at RT. Step 5: Wash and add SULFO-TAG Streptavidin

[0033] Add 25 µL of MSD SULFO-TAG Streptavidin at 0.5 ug / mL in 1% Blocker A in PBS into each well of the plate. Seal the plate and incubate with shaking for 1 h at RT. Step 6: Wash and add read buffer

[0034] Wash the plate 3X with 150 uL of PBST. After washing, gently tap the plate to remove any residual wash buffer.

[0035] Pipette 150 µL per well of MSD GOLD Read Buffer B across the plate. No incubation is required before reading the plate. Read immediately on Meso Scale QuickPLex SQ120.

[0036] The uPlasminogen / Cr value is the ratio of urinary plasminogen and urinary creatinine. Results:

[0037] Based on inclusion criteria and sample availability, 1010 patients from CureGN Cohort were included in our analysis. Baseline characteristics of these patients are shown in Table 1. Median follow-up time was 36.6 months. During the period of study, 105 (10.4%) patients progressed to ESKD (median follow-up 23.8 and 38.1 months for ESKD and non- ESKD respectively). Comparing no ESKD and ESKD groups, patients differed by race (higherAttorney Docket No.: 27527-0216WO1-MSSM.220806 percentage of Black, multiracial and unknown race in ESKD group, P = 0.042) and diagnosis (higher percentage of FSGS in ESKD group P < 0.001). Additionally, median baseline eGFR varied by group (82.5 vs. 28.4 mL / min per 1.73 m2, P < 0.001), as did median baseline proteinuria (0.7 vs.2.7 g / g, P < 0.001) and uPlasminogen / Cr (108.1 vs.2362.8 µg / g, P < 0.001). Table 1. Baseline Characteristics of the study population at baseline. Comparison between patients that developed and did not develop end-stage kidney disease (ESKD) during follow- up. Continuous variables are reported as median (interquartile range) and use a Mann-Whitney U test for comparison; categorical variables are reported as n (%) and use a ?2 test for comparison. Bold face indicates statistical significance. TABLE 1 Baseline Total No ESKD ESKD characteristics (n = 1010) (n = 905)(n = 105)P valueAge at baseline (yr) 37.9 (17.8, 54.3) 37.9 (17.7, 54.7) 36.9 (20.7, 51.9)Sex (female) 425 (42.1) 383 (42.3) 42 (40.0) 0.6 Race Asian 75 (7.4) 67 (7.4) 8 (7.6) Black 133 (13.2) 111 (12.3) 22 (21.0) White 736 (72.9) 672 (74.3) 64 (71.0) Native American 9 (0.9) 7 (0.8) 2 (1.9) 0.04 Pacific Islander 3 (0.3) 3 (0.3) 0 (0.0) Multiracial 23 (2.3) 20 (2.2) 3 (2.9) Unknown 31 (3.1) 25 (2.8) 6 (5.7) Hispanic or Latino 138 (13.7) 118 (13.0) 20 (19.1) 0.1 Diagnosis FSGS 314 (31.1) 263 (29.1) 51 (48.6) MN 306 (30.3) 293 (32.4) 13 (12.4) < 0.001 IgAN 390 (38.6) 349 (38.6) 41 (39.1) BMI (kg / m2) 26.5 (22.3, 32.1) 26.4 (22.2, 31.9) 27.4 (22.9, 33.6) 0.3 Hypertension 569 (56.3) 488 (53.9) 81 (77.1) < 0.001 Diabetes 60 (5.9) 54 (6.0) 6 (5.7) 0.9 Time from biopsy to baseline (yr)1.8 (1.1, 1.8) 1.6 (0.8, 2.9) 1.5 (0.8, 3.1) 0.5Immunosuppression before baseline 510 (50.5) 450 (49.7) 60 (57.1) 0.2 (yes) Immunosuppression after baseline (yes)191 (18.9) 170 (18.8) 21 (20.0) 0.7Attorney Docket No.: 27527-0216WO1-MSSM.220806 eGFR at baseline (mL / min per 1.73 2 77.2 (45.7, 99.9) 82.5 (52.8, 102.2) 28.4 (19.3, 45.1) < 0.001 m ) UPCR at baseline (g / g)0.8 (0.2, 2.6) 0.7 (0.2, 2.2) 2.7 (1.3, 6.0) < 0.001uPlasminogen / Cr 145.1 (19.9, 108.1 (17.4, 2362.8 (567.0, (µg / g) 1213.4) 776.3)7403.0)< 0.001Abbreviations: ESKD, end-stage kidney disease; yr, year; FSGS, focal and segmental glomerulosclerosis; MN, membranous nephropathy; IgAN, IgA nephropathy; BMI, body mass index; eGFR, estimated glomerular filtration rate; UPCR, urine protein to creatinine ratio.

[0038] The median uPlasminogen / Cr in the cohort was 145.1 (IQR 19.9-1213.4) µg / g. Baseline characteristics organized by uPlasminogen / Cr quintiles are presented in Table S1. Log2uPlasminogen / Cr was strongly correlated with Log2UPCR (r = 0.69, P < 0.001) and was inversely correlated with eGFR (Figure 1, r = -0.39, P < 0.001). At baseline visit, 64 Patients (6.3%) presented with severe edema, which was associated with Log2uPlasminogen / Cr by logistic regression (OR 1.09 95% CI (1.02-1.16), P = 0.01). By multiple linear regression, eGFR, Log2UPCR, diabetes, race and histologic diagnosis were independently associated with urine plasmin(ogen) levels (Table 2).

[0039] Attorney Docket No.: 27527-0216WO1-MSSM.220806Attorney Docket No.: 27527-0216WO1-MSSM.220806

[0040] By univariable Cox regression analysis, Log2uPlasminogen / Cr was significantly associated with ESKD (HR 1.3095% CI (1.23-1.37), P < 0.001). When analyzed via quintiles, the 4thvs. 1st(HR 4.89, 95% CI 2.03-11.80) and 5thvs. 1st(HR 12.22, 95% CI 5.28-28.29) quintiles of uPlasminogen / Cr) were associated with ESKD. Kaplan-Meier curves representing the risk of ESKD by uPlasminogen / Cr quintiles are shown in Figure 2. Stratification by proteinuria levels, histological diagnosis and APOL-1 genotype (for those patients with available study) did not alter the association between Log2uPlasminogen / Cr and the kidney event (Figure 3). There was no evidence of effect modification by histologic diagnosis on the association of Log2uPlasminogen / Cr with risk of ESKD (interaction P value = 0.6).

[0041] After adjustment for age, sex, race, hypertension, diabetes, kidney diagnosis, BMI, eGFR and Log2UPCR, the adjusted hazard ratio between uPlasminogen / Cr and ESKD was 1.31 (95% CI 1.22-1.40) (Table 3). Variables tested for inclusion but excluded from the final model due to lack of significance (p value > 0.1 for exclusion in the backwards stepwise multivariable model selection) were ethnicity, time from kidney biopsy to baseline, prior immunosuppressive therapy (y / n), and subsequent therapy at baseline. Log2UPCR was included in the model despite not meeting this criterion for theoretical reasons and to compare with Log2uPlasminogen / Cr. Comparison of the predictive performance of the models including Log2uPlasminogen / Cr, Log2UPCR or both markers using AIC, BIC, C-index and R2showed the plasmin(ogen) model superiority (Table S2).

[0042] A reduced model of expected Log2uPlasminogen / Cr was calculated from eGFR and proteinuria by multiple linear regression (Log2uPlasminogen / Cr = 9.87 – 0.03*eGFR (mL / min per 1.73 m2) + 0.89* Log2 UPCR (g / g)) and the ratio between measured / expected plasminogen was obtained. Median measured / expected uPlasminogen / Cr was 0.97 (0.75, 1.14) after exclusion of 15 negative values (negative expected Log2uPlasminogen / Cr). Scatterplot showing measured and expected Log2uPlasminogen / Cr organized by measured / expected uPlasminogen tertiles is shown in Figure 4. Adjusted cox regression analysis showed a significant association between the ratio of measured / expected uPlasminogen / Cr and ESKD (Table 4).

[0043] To evaluate the development of early kidney events, 3-year ESKD logistic regression was performed and the area under the ROC (AUC) was calculated for 3 modelsAttorney Docket No.: 27527-0216WO1-MSSM.220806 (Clinical model, Clinical model + Log2UPCR and Clinical model + Log2UPCR + Log2uPlasminogen / Cr). AUC for the Clinical model was 0.89 (0.86-0.93) and AUC for Clinical model + Log2UPCR was 0.91 (0.89-0.94). The addition of Log2uPlasminogen / Cr to the clinical model with proteinuria increased the AUC to 0.94 (95% CI 0.91-0.96), P = 0.01). The cut- point for the concentration of uPlasminogen / Cr that maximized the product of sensitivity and specificity to predict the 3-year cumulative incidence of progression to ESKD was 1183.1 µg / g with a sensitivity of 81% and specificity of 80%. Unadjusted Kaplan-Meier curves of ESKD- free survival based on this uPlasminogen / Cr threshold are shown in Figure 5.

[0044] Table 2. Multiple linear regression of Log2 uPlasminogen / Cr (µg / g). Complete model includes all significant variables by backwards stepwise multivariable model selection. Reduced model includes eGFR and proteinuria. Bold face indicates statistical significance. Complete modelReducedLomgodel (eGFR and2UPCR)Estimate (95% CI) P value Estimate (95% CI) P value eGFR at baseline 2 -0.02 (-0.03, -0.02) < 0.001 -0.03 (-0.03, -0.02) < 0.001 (mL / min per 1.73 m) Log2UPCR (g / g) 0.82 (0.76, 0.88) 0.008 0.89 (0.82, 0.95) < 0.001 Diabetes 0.93 (0.25, 1.61) 0.001 - - Race Asian vs. White 0.55 (-0.05, 1.15) 0.08 Black vs. White 0.34 (-0.15, 0.83) 0.2 - - Other vs. White 0.74 (0.10, 1.38) 0.02 Diagnosis FSGS vs. IgAN 0.71 (0.32, 1.11) < 0.001 - - MN vs. IgAN 1.22 (0.82, 1.61) < 0.001 Intercept 8.96 (8.51, 9.42) < 0.001 9.87 (9.49, 10.25) < 0.001 Abbreviations: eGFR, estimated glomerular filtration rate; UPCR, urine protein to creatinine ratio; CI, confidence interval; FSGS, focal and segmental glomerulosclerosis; MN, membranous nephropathy; IgAN, IgA nephropathy.Attorney Docket No.: 27527-0216WO1-MSSM.220806 Table 3. Adjusted Cox regression analysis for end-stage kidney disease (ESKD). Bold face indicates statistical significance. Model 1 Model 2 (Significant covariables) covariablesEstimate (95% CI) P value Estimate (95% CI) P value Age at baseline (yr) 0.97 (0.96-0.98) < 0.001 0.97 (0.96-0.98) < 0.001 eGFR at baseline 2 0.94 (0.93-0.95) < 0.001 0.94 (0.93-0.95) < 0.001 (mL / min per 1.73 m) Sex (male vs. female) 2.21 (1.42-3.45) 0.001 2.22 (1.42-3.46) 0.001 Race Asian vs. White 1.24 (0.58-2.65) 0.6 1.23 (0.57-2.63) 0.6 Black vs. White 1.14 (0.70-2.00) 0.6 1.15 (0.66-2.00) 0.6 Other vs. White 4.19 (2.04-8.60) < 0.001 4.28 (2.08-8.80) < 0.001 Diagnosis FSGS vs. IgAN 0.79 (0.50-1.25) 0.4 0.78 (0.49-1.24) 0.3 MN vs. IgAN 0.22 (0.11-0.44) < 0.001 0.22 (0.11-0.44) < 0.001 BMI (kg / m2) 0.96 (0.93-0.99) 0.003 0.96 (0.93-0.99) 0.004 Hypertension 1.61 (0.96-2.70) 0.07 1.60 (0.96-2.70) 0.07 Diabetes 0.31 (0.12-0.80) 0.02 0.31 (0.12-0.80) 0.02 Log2uPlasminogen / Cr 1.31 (1.22-1.40) < 0.001 1.28 (1.16-1.42) < 0.001 (µg / g) Log2 UPCR (g / g) - - 1.05 (0.90-1.23) 0.6 Abbrevations: UPCR, urine protein to creatinine ratio; CI, confidence interval; yr, year; eGFR, estimated glomerular filtration rate; FSGS, focal and segmental glomerulosclerosis;Attorney Docket No.: 27527-0216WO1-MSSM.220806 MN, membranous nephropathy; IgAN, IgA nephropathy; BMI, body mass index, Log2uPlasminogen / Cr, log2urine plasminogen to creatinine ratio. Table 4. Adjusted Cox Regression Model testing the association between ESKD and the ratio of measured / expected urine Plasminogen organized by tertiles. Bold face indicates statistical significance. Estimate (95% CI) P value Age at baseline (yr) 0.97 (0.96-0.98) < 0.001 2 eGFR at baseline (mL / min per 1.73 m)0.93 (0.92-0.94) < 0.001 Sex (male vs. female) 2.00 (1.30-3.09) 0.002 Race Asian vs. White 1.22 (0.60-2.74) 0.5 Black vs. White 1.18 (0.69-2.03) 0.5 Other vs. White 3.38 (1.72-6.64) < 0.001 Diagnosis FSGS vs. IgAN 0.95 (0.60-1.48) 0.8 MN vs. IgAN 0.35 (0.18-0.68) 0.002 BMI (kg / m2) 0.96 (0.93-0.99) 0.009 Hypertension 1.43 (0.87-2.36) 0.2 Diabetes 0.34 (0.14-0.87) 0.03 Ratio uPlasminogen measured / expected 1stvs 2ndtertile 0.41 (0.22-0.77) 0.005 3rdvs 2ndtertile 2.42 (1.54-3.78) < 0.001 Abbreviations: CI, confidence interval; yr, year; eGFR, estimated glomerular filtration rate; FSGS, focal and segmental glomerulosclerosis; MN, membranous nephropathy; IgAN, IgA nephropathy; BMI, body mass index.Attorney Docket No.: 27527-0216WO1-MSSM.220806

[0045] ROC curves based on predicted probability of logistic regression comparing the three models (Clinical model, Clinical model + Log2UPCR and Clinical model + Log2UPCR + Log2uPlasminogen / Cr) are shown in Figure 3. Clinical model + Log2UPCR + Log2uPlasminogen / Cr AUC was significantly higher than Clinical model + Log2UPCR AUC (0.85 (0.81-0.89) vs. 0.89 (0.85-0.92), P = 0.033). The cut-point for the concentration of uPlasminogen / Cr that maximized the product of sensitivity and specificity to predict the 36- month cumulative incidence of progression to ESKD was 1183.1 µg / g with a sensitivity of 81% and specificity of 80%. Discussion

[0046] In the present study, we assessed the value of urinary plasmin(ogen) as a prognostic marker of kidney disease progression. The cohort studied was obtained from CureGN (N=1010), and included patients with IgAN, FSGS and MN. We found that adjusted urinary plasminogen was significantly associated with ESKD (Log2uPlasminogen / Cr HR 1.31 (95% CI 1.22-1.40)). More interestingly, the addition of urinary plasmin(ogen) to the traditional predictive demographic and clinical laboratory findings improved the prediction of ESKD regardless of the time from biopsy to plasmin(ogen) assessment and treatment received. When directly comparing proteinuria and urinary plasmin(ogen) as predictors of progression to ESKD, plasmin(ogen) had significantly better performance than proteinuria, both in the survival analysis and in the 3-year risk logistic regression.Attorney Docket No.: 27527-0216WO1-MSSM.220806

[0047] In line with previously reported findings, our study provides confirmation of a strong correlation between proteinuria and urinary plasmin(ogen) levels. Additionally, a moderate negative correlation between plasminogen levels and eGFR was found, finding that had been previously described in a cohort of patients with lupus nephritis (besides showing that urine plasmin discriminated active LN from inactive disease).41Using a multiple linear regression model, FSGS and MN were associated with higher levels of urinary plasmin(ogen) compared to IgAN, independently of eGFR and proteinuria. These differences could be attributed to different patterns of permeability depending on the underlying disease or differences in the production (systemic or local) in the context of these disorders. Further studies would be needed to investigate how urinary plasmin(ogen) levels differ among a broader group of kidney disorders and patterns of injury as well as defining mechanistic or therapeutic implications.

[0048] Additionally, the measured / expected uPlasminogen ratio (in an equation derived from eGFR and proteinuria) showed that patients with disproportionately elevated uPlasminogen levels had a higher risk of progression to ESKD (ratio > 1.1 presented a 2.4 higher risk of progression than the ratio between 0.8-1.1). This result suggests the predictive value of plasminogen beyond its close (and expected) biological relationship with proteinuria, and if these results are confirmed, this ratio could be used in the development of clinical applications. The relationship between plasminogenuria, proteinuria and other clinical parameters along the evolution of CKD should be the basis for future investigation.

[0049] The present findings suggest that urinary plasmin(ogen) may be an independent marker of kidney disease in addition to traditional demographic and clinical laboratory findings. Recent reports that plasminogen / plasmin inhibition could be an attractive therapeutic strategy for glomerular disease42, 43increases the potential clinical value of urinary plasmino(ogen) as a biomarker. Plasmin is an active and pleiotropic protein usually present at low concentrations in the urinary space. As previously mentioned, our in vitro and in vivo studies have shown that plasmin(ogen) can directly damage podocytes via CD36 and oxidative stress mechanisms.34, 35These effects were partially restored with amiloride, a potassium- sparing diuretic with known off-target anti-proteinuric effects43through plasminogen inhibition. If higher urine plasmin(ogen) levels are related to kidney disease progression and enable “second hit” cascades after damage, its value could be used not only as a prognosticAttorney Docket No.: 27527-0216WO1-MSSM.220806 marker, but also as a potential target for the development of personalized therapeutic strategies in those patients with higher urine plasmin(ogen) levels.

[0050] The strengths of the study include (i) the use of a high quality prospective multicentric cohort such as CureGN, (ii) the size of the cohort taking into account the population studied, (iii) the use of cases with biopsy-confirmed diagnosis. Additionally, plasmin(ogen) levels were measured with a novel electro-chemiluminescent immunoassay (ECLIA), whose technology allows detection of lower levels of plasmin(ogen) due to better sensitivity and broader dynamic range than commercialized assays available based on ELISA technology.

[0051] The present findings suggest that urinary plasmin(ogen) may be an independent marker of renal disease in addition to traditional demographic and clinical laboratory findings. The importance of this study is based on the possible role of urinary plasmin(ogen) as both a marker and a mediator of disease pathogenesis. Plasmin is an active and pleiotropic protein usually present at low concentrations in the urinary space. As previously mentioned, in vitro and in vivo studies have shown that plasmin(ogen) can directly damage podocytes via CD36 and oxidative stress mechanisms.32,33These effects were partially restored with amiloride, a potassium-sparing diuretic with known off-target anti-proteinuric effects39through plasminogen inhibition. If higher urine plasmin(ogen) levels are related to kidney disease progression and enable “second hit” cascades after damage, its value could be used not only as a prognostic marker, but also as a potential target for the development of personalized therapeutic strategies in those patients with higher urine plasmin(ogen) levels.

[0052] The strengths of the study include (i) the use of a high quality prospective multicentric cohort such as CureGN, (ii) the size of the cohort taking into account the population studied, (iii) the use of cases with biopsy-confirmed diagnosis. Additionally, plasmin(ogen) levels were measured with a novel electro-chemiluminescent immunoassay (ECLIA), whose technology allows detection of lower levels of plasmin(ogen) due to better sensitivity and broader dynamic range than commercialized assays available based on ELISA technology.

[0053] However, limitations of our study should be considered. The findings in this study are based on a single determination of urinary plasmin(ogen), and an assessment of its changesAttorney Docket No.: 27527-0216WO1-MSSM.220806 over time would provide data on its usefulness as a biomarker and therapeutic target. Given their similarities, current assays do not allow to distinguish between plasminogen and plasmin (active form). Further confirmatory studies and evaluation of whether elevation of the active form has a higher predictive value would be needed to explore this hypothesis. The use of a cohort of mostly white patients and the restriction to patients with 3 glomerular disorders limits the external validity of our analysis and will need further study, as well as the inclusion of other variables such as the level of albuminuria or use of medications such as RAAS blockade or amiloride.

[0054] Collectively, this study points to urinary plasmin(ogen) as a potentially useful noninvasive biomarker that can assist in prognosticating kidney disease progression. The data supports the hypothesis that urinary plasmin(ogen) is elevated under conditions of glomerular filtration barrier disruption. Despite the established value of proteinuria as a maker of renal progression, the underlying mechanisms remain to be fully defined, and thus potential therapeutic targets remain largely unexplored. In combination with previous experimental findings, urinary plasmin(ogen) could be a useful biomarker in prognostic decision making and a target for the development of novel therapies in patients with proteinuria and glomerular disease.Attorney Docket No.: 27527-0216WO1-MSSM.220806 References Kidney Disease: Improving Global Outcomes Glomerular Diseases Work G. KDIGO 2021 Clinical Practice Guideline for the Management of Glomerular Diseases. Kidney Int.2021;100(4S): S1-S276. Wiggins RC. The spectrum of podocytopathies: a unifying view of glomerular diseases. Kidney Int.2007;71(12): 1205-1214. Mariani LH, Kretzler M. Pro: 'The usefulness of biomarkers in glomerular diseases'. The problem: moving from syndrome to mechanism--individual patient variability in disease presentation, course and response to therapy. Nephrol Dial Transplant. 2015;30(6): 892-898. Webster AC, Nagler EV, Morton RL, Masson P. Chronic Kidney Disease. Lancet. 2017;389(10075): 1238-1252. Zhong J, Yang HC, Fogo AB. A perspective on chronic kidney disease progression. Am J Physiol Renal Physiol.2017;312(3): F375-F384. Cravedi P, Ruggenenti P, Remuzzi G. Proteinuria should be used as a surrogate in CKD. Nat Rev Nephrol.2012;8(5): 301-306. Avasare RS, Radhakrishnan J. Proteinuria as a surrogate marker for renal outcome: are we there yet? Kidney Int.2015;88(6): 1228-1230. Culleton BF, Larson MG, Parfrey PS, Kannel WB, Levy D. Proteinuria as a risk factor for cardiovascular disease and mortality in older people: a prospective study. Am J Med.2000;109(1): 1-8. Matsushita K, van der Velde M, Astor BC, et al. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet. 2010;375(9731): 2073- 2081. Bello AK, Hemmelgarn B, Lloyd A, et al. Associations among estimated glomerular filtration rate, proteinuria, and adverse cardiovascular outcomes. Clin J Am Soc Nephrol.2011;6(6): 1418-1426. Harrison TG, Tam-Tham H, Hemmelgarn BR, et al. Change in Proteinuria or Albuminuria as a Surrogate for Cardiovascular and Other Major Clinical Outcomes: A Systematic Review and Meta-analysis. Can J Cardiol.2019;35(1): 77-91. Inker LA, Astor BC, Fox CH, et al. KDOQI US commentary on the 2012 KDIGO clinical practice guideline for the evaluation and management of CKD. Am J Kidney Dis. 2014;63(5): 713-735.Attorney Docket No.: 27527-0216WO1-MSSM.220806 Kidney Disease: Improving Global Outcomes Blood Pressure Work G. KDIGO 2021 Clinical Practice Guideline for the Management of Blood Pressure in Chronic Kidney Disease. Kidney Int.2021;99(3S): S1-S87. Sharma S, Smyth B. From Proteinuria to Fibrosis: An Update on Pathophysiology and Treatment Options. Kidney Blood Press Res.2021;46(4): 411-420. Benzing T, Salant D. Insights into Glomerular Filtration and Albuminuria. N Engl J Med. 2021;384(15): 1437-1446. Hirschberg R, Wang S. Proteinuria and growth factors in the development of tubulointerstitial injury and scarring in kidney disease. Curr Opin Nephrol Hypertens. 2005;14(1): 43-52. Thompson A, Carroll K, L AI, et al. Proteinuria Reduction as a Surrogate End Point in Trials of IgA Nephropathy. Clin J Am Soc Nephrol.2019;14(3): 469-481. Jia Y, Zheng Z, Xue M, et al. Extracellular Vesicles from Albumin-Induced Tubular Epithelial Cells Promote the M1 Macrophage Phenotype by Targeting Klotho. Mol Ther.2019;27(8): 1452-1466. Chung JJ, Huber TB, Godel M, et al. Albumin-associated free fatty acids induce macropinocytosis in podocytes. J Clin Invest.2015;125(6): 2307-2316. Kinugasa S, Tojo A, Sakai T, et al. Selective albuminuria via podocyte albumin transport in puromycin nephrotic rats is attenuated by an inhibitor of NADPH oxidase. Kidney Int.2011;80(12): 1328-1338. Raum D, Marcus D, Alper CA, Levey R, Taylor PD, Starzl TE. Synthesis of human plasminogen by the liver. Science.1980;208(4447): 1036-1037. Castellino FJ, Ploplis VA. Structure and function of the plasminogen / plasmin system. Thromb Haemost.2005;93(4): 647-654. Baker SK, Strickland S. A critical role for plasminogen in inflammation. J Exp Med. 2020;217(4). Sulniute R, Shen Y, Guo YZ, et al. Plasminogen is a critical regulator of cutaneous wound healing. Thromb Haemost.2016;115(5): 1001-1009. Ismail AA, Shaker BT, Bajou K. The Plasminogen-Activator Plasmin System in Physiological and Pathophysiological Angiogenesis. Int J Mol Sci.2021;23(1). Sappino AP, Wohlwend A, Huarte J, Belin D, Vassalli JD. The PA-plasmin system during murine embryogenesis. Ann N Y Acad Sci.1992;667: 41. Andersen RF, Buhl KB, Jensen BL, et al. Remission of nephrotic syndrome diminishes urinary plasmin content and abolishes activation of ENaC. Pediatr Nephrol. 2013;28(8): 1227-1234.Attorney Docket No.: 27527-0216WO1-MSSM.220806 Buhl KB, Friis UG, Svenningsen P, et al. Urinary plasmin activates collecting duct ENaC current in preeclampsia. Hypertension (Dallas, Tex. : 1979).2012;60(5): 1346- 1351. Xiao M, Bohnert BN, Grahammer F, Artunc F. Rodent models to study sodium retention in experimental nephrotic syndrome. Acta Physiol (Oxf). 2022;235(3): e13844. Chen JL, Wang L, Yao XM, et al. Association of Urinary Plasminogen-Plasmin with Edema and Epithelial Sodium Channel Activation in Patients with Nephrotic Syndrome. Am J Nephrol.2019;50(2): 92-104. Svenningsen P, Andersen H, Nielsen LH, Jensen BL. Urinary serine proteases and activation of ENaC in kidney--implications for physiological renal salt handling and hypertensive disorders with albuminuria. Pflugers Archiv : European journal of physiology.2015;467(3): 531-542. Zachar RM, Skjodt K, Marcussen N, et al. The epithelial sodium channel gamma- subunit is processed proteolytically in human kidney. J Am Soc Nephrol.2015;26(1): 95-106. Schork A, Woern M, Kalbacher H, et al. Association of Plasminuria with Overhydration in Patients with CKD. Clin J Am Soc Nephrol.2016;11(5): 761-769. Egerman MA, Wong JS, Runxia T, et al. Plasminogenuria is associated with podocyte injury, edema, and kidney dysfunction in incident glomerular disease. FASEB J. 2020;34(12): 16191-16204. Raij L, Tian R, Wong JS, He JC, Campbell KN. Podocyte injury: the role of proteinuria, urinary plasminogen, and oxidative stress. Am J Physiol Renal Physiol.2016;311(6): F1308-F1317. Hayek SS, Sever S, Ko YA, et al. Soluble Urokinase Receptor and Chronic Kidney Disease. N Engl J Med.2015;373(20): 1916-1925. Iversen E, Kallemose T, Hornum M, et al. Soluble urokinase plasminogen activator receptor and decline in kidney function among patients without kidney disease. Clin Kidney J.2022;15(8): 1534-1541. Hayek SS, Koh KH, Grams ME, et al. A tripartite complex of suPAR, APOL1 risk variants and alphavbeta3 integrin on podocytes mediates chronic kidney disease. Nat Med.2017;23(8): 945-953. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics.1988;44(3): 837-845. Liu X. Classification accuracy and cut point selection. Stat Med.2012;31(23): 2676- 2686.Attorney Docket No.: 27527-0216WO1-MSSM.220806 Qin L, Stanley S, Ding H, et al. Urinary pro-thrombotic, anti-thrombotic, and fibrinolytic molecules as biomarkers of lupus nephritis. Arthritis Res Ther.2019;21(1): 176. Deng Q, Kakizoe Y, Iwata Y, et al. The serine protease plasmin plays detrimental roles in epithelial sodium channel activation and podocyte injury in Dahl salt-sensitive rats. Hypertens Res.2023;46(1): 50-62. Shen W, Alshehri M, Desale S, Wilcox C. The Effect of Amiloride on Proteinuria in Patients with Proteinuric Kidney Disease. Am J Nephrol.2021;52(5): 368-377.

Claims

Attorney Docket No.: 27527-0216WO1-MSSM.220806 CLAIMS 1. A method of managing glomerular disease in a subject in need thereof, comprising: identifying a subject suffering from glomerular disease; measuring the urinary plasmin(ogen) level in the subject; predicting disease progression based on the urinary plasmin(ogen) level; and treating the subject to manage the glomerular disease.

2. The method of claim 1, wherein the glomerular disease is focal segmental glomerulosclerosis, membranous nephropathy or IgA nephropathy.

3. A method of treating glomerular disease in a subject in need thereof, comprising: identifying a subject suffering from glomerular disease and having a urinary plasmin(ogen) level exceeding a predetermined threshold; and treating the subject to reduce the urinary plasmin(ogen) level.

4. The method of claim 3, wherein the glomerular disease is focal segmental glomerulosclerosis, membranous nephropathy or IgA nephropathy.

5. The method of claim 1, wherein the urinary plasmin(ogen) level is measured as the ratio the level of urinary plasmin(ogen) and creatinine (uPlasminogen / Cr).

6. The method of claim 1, wherein the subject is treated by administration of amiloride.

7. The method of claim 1, wherein the subject is treated by administration of RAAS blockade.Attorney Docket No.: 27527-0216WO1-MSSM.220806 8. A method of managing glomerular disease in a subject in need thereof, comprising: identifying a subject suffering from glomerular disease; determining risk of progression to ESKD based on the measured / calculated uPlasminogen ratio measuring the urinary plasmin(ogen) level in the subject; determining the measured / expected uPlasminogen ratio; determining the risk of disease progression based on the measured / expected uPLasminogen ratio; and treating the subject to manage the glomerular disease.

9. The method of claim 8, wherein a measured / expected uPlasminogen ratio of 1.1 or greater is associated with a higher risk of disease progression than a ratio less than 1.

1.

10. The method of claim 8, wherein a measured / expected uPlasminogen ratio of 0.8 or less is associated with a lower risk of disease progression than a ratio greater than 0.

8.

11. The method of claim 8, wherein the expected uPlasminogen was calculated from eGFR and proteinuria by multiple linear regression (Log2uPlasminogen / Cr = 9.87 – 0.03*eGFR (mL / min per 1.73 m2) + 0.89* Log2 UPCR (g / g)).

12. An immunoassay for measuring plasminogen concentration in a sample, comprising immobilizing an anti-plasminogen capture antibody to a substrate; contacting an analyte containing plasminogen with the capture antibody, to bind the plasminogen to the capture antibody; contacting a biotinylated plasminogen detection antibody with the plasminogen bound to the capture antibody; and detecting the biotinylated detection antibody with a conjugated streptavidin.

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