WO2009122387A1

WO2009122387A1 - Method for the detection and prediction of obesity-related renal disease

Info

Publication number: WO2009122387A1
Application number: PCT/IE2008/000037
Authority: WO
Inventors: Mohammed Bashir; Thomas James Cawood; Cormac Gerard Kilty; Claire Victoria Mcgrath; Donal O'shea
Original assignee: Biotrin Group Ltd.
Priority date: 2008-04-04
Filing date: 2008-04-04
Publication date: 2009-10-08

Abstract

A method for the early identification and prediction of renal damage in a subject with obesity comprises contacting a urine sample from the subject with a capture molecule for a biomarker specific to a region of the kidney and which biomarker is released from said region when there is damage to said region, an elevated level of said biomarker relative to a normal level being indicative and predictive of renal damage. The biomarkers include αGST, πGST and Collagen IV. The method enables the detection of renal injury in obese patients who otherwise have been regarded as having normal renal function as measured by serum creatinine or estimated glomerular filtration rate, thereby facilitating early intervention in the treatment of such patients.

Description

Method for the detection and prediction of obesity-related renal disease

Technical Field

This invention relates to a method for the early identification and prediction of renal damage in a subject with obesity and to biomarkers therefor.

Background Art

Obesity is a growing epidemic. Currently a quarter of Europeans and a third of Americans are obese and these figures have doubled in the last 30 years IASO (International Obesity Task Force; Global Obesity Prevalence in Adults, http://www.iotf.org/ 2008). The world-wide prevalence of end-stage renal disease (ESRD) is also growing at an alarming rate. For example in the United States of America, the prevalence of ESRD has more than doubled in the last decade, and the population living with ESRD is projected to increase to 650,000 by 2010 (Hsu C.Y., et al (2006) Ann intern Med 144:21-8). One of the strongest emerging risk factors for ESRD is body mass index (BMI). The BMI is a person's weight in kilograms divided by his height in metres squared. A person is considered obese if he has a BMI greater than or equal to thirty. Numerous studies have shown a strong link between obesity and an increased risk of renal impairment and/or ESRD (Ejerblad E. et al, (2006) J Am Soc Nephrol; 17:1695-702), even when other co- morbidities such as hypertension and diabetes have been corrected for (Hsu C.Y., et al supra).

As it has become clear that obesity can contribute to progressive renal disease, the entity of obesity-related nephropathy (ORN) has consequently become more widely recognised. The pathological renal changes seen in obese patients that are affected has been well-described (Henegar J. et al, (2001) Am J Soc Nephrol; 12:1211-1217), and the disease entity is often termed obesity-related glomerulopathy (ORG). The likelihood of developing ORG appears to be linked to the severity of obesity and the total number of nephrons, with increased obesity and low nephron number appearing to be a synergistically damaging combination. This is thought to lead to glomerular hyperfiltration and other detrimental effects, which result in worsening renal function, proteinuria and sometimes ESRD (Praga M. (2005) Nephrol Dial Transplant; 20:2594-7).

However, there are likely to be more influences than simply BMI, nephron number, and hyperfiltration in the pathogenesis of ORN. A more complex aetiology of ORN is supported by the clinical observations that patients who undergo unilateral nephrectomy have a similar incidence of subsequent proteinuria as the general population (Riehl J. et al (1997) Nephrol Dial Transplant; 12:1615-1621), and that many patients with obesity do not develop renal disease. In addition, recent gene microarray data from the glomeruli of patients with biopsy- proven ORG, have shown an up-regulation of genes involved in inflammatory cytokine action, as well as other pathways such as lipid metabolism and leptin action (Wu Y. et al, (2006) Endocrinology; 147:44-50). Interest has grown in the possibility that leptin might contribute to ORN, possibly via actions such as increased Collagen I and IV and mesangial hypertrophy within the kidney, supported by the finding that leptin infusion in rats fosters the development of glomerulosclerosis and proteinuria (Wolf G. and Ziyadeh FN. (2006) Contrib Nephrol; 151:175-83). Taken together, it seems likely the aetiology of ORN is complex, and encompasses ORG (related at least in part to glomerular hyperfiltration), but also includes other mechanisms including inflammatory processes, which may affect not only the glomerulus but also other segments of the nephron.

The current methods for diagnosing ORN include urinary albumin excretion, serum creatinine measurements and renal biopsy. These investigations are sub-optimal with the non-invasive tests lacking specificity and sensitivity, and the invasive renal biopsy, with its inherent risks, only being justifiable once significant renal damage has occurred. It is currently not clear which patients with obesity will progress to clinically significant renal disease, including ESRD and the associated cardiovascular disease.

Currently, the most sensitive test for renal disease in obesity is arguably urinary microalbumin excretion, but this has a number of drawbacks including problems with sample collection, and a high false- positive rate. The normal rate of albumin excretion is less than 30mg/day (20μg/min); persistent albumin excretion between 30 and 300mg/day (20 to 200μg/min) is called microalbuminuria. The previous gold-standard for urine collection was timed collections, either overnight or 24 hour collections, but these are cumbersome and incomplete collections are a common source of error. These timed collections have been replaced by measuring the albumin-to-creatinine ratio in an un-timed urine specimen. However, these spot urine tests also have limitations. The slope of the relationship between the spot urine and the 24-hour collection varies throughout the day and the correlation is best if samples are taken in the mid-morning, although mid-afternoon specimens are also relatively accurate (Ginsberg J.M. et al (1983). N Engl J Med; 309:1543-6). Establishing the diagnosis of microalbuminuria requires the demonstration of a persistent elevation in albumin excretion, hence these tests have to repeated in any individual. Fever, exercise, heart failure, and poor glycaemic control are among the factors that can cause transient microalbuminuria, and so can cause a false positive result when aiming to detect nephropathy due to conditions such as diabetes (Mogensen CE, et al (1995) Diabetes Care; 18:572-81). These factors are likely to cause similar false positive results when aiming to diagnose ORN. The ratio also varies with race/ethnicity as creatinine excretion is significantly higher among non-Hispanic blacks and Mexican Americans than among non-Hispanic whites (Mattix H.J., et al (2002). J Am Soc Nephrol; 13:1034-9).

These limitations of urinary microalbumin testing are not yet accurately quantified in ORN, but can be estimated from considering the limitations of microalbumin testing in diabetes. In patients with type 1 diabetes, microalbuminuria may revert to normoalbumunuria in 20 to 60% of patients over follow-up periods of 5 to 18 years (Hovind P, et al (2004) Bmj; 328: 1105), and among patients with type 1 diabetes and microalbuminuria, less than 50 percent are at risk for progression of nephropathy (Mogensen CE. (1987) Kidney Int; 31 :673-89). In patients with type 2 diabetes progression from microalbuminuria to overt nephropathy within a 10 year period occurs in 20 to 40% of Caucasian patients (Ismail N. et al (1999) Kidney Int; 55:1-28).

Therefore there is a clinical need for a simple, sensitive and specific test for nephropathy, that could detect early ORN (and possibly other causes of nephropathy) and allow appropriate further investigation and treatment strategies to be initiated.

A further object of the present invention is to characterise the regional damage in ORN using novel urinary biomarkers, to examine whether certain urinary biomarkers could identify renal injury that current non-invasive testing is unable to detect, and to determine the pattern of damage to the nephron indicated by these biomarkers.

Disclosure of the Invention

Accordingly, the invention provides a method for the early identification and prediction of renal damage in a subject with obesity, which method comprises contacting a urine sample from the subject with a capture molecule for a biomarker specific to a region of the kidney and which biomarker is released from said region when there is damage to said region, an elevated level of said biomarker relative to a normal level being indicative and predictive of renal damage.

The method according to the invention enables the detection of renal injury in obese patients who otherwise have been regarded as having normal renal function as measured by serum creatinine or estimated glomerular filtration rate as hereinafter described. Accordingly, the method according to the invention facilitates the early intervention and correction of potential renal injury.

By "capture molecule" herein is meant any molecule or portion thereof which binds reversibly or irreversibly to a said specific biomarker, so that said biomarker can be detected in the urine sample.

According to one embodiment of the invention, the biomarker is specific to the proximal region of the renal tubule.

A preferred biomarker is alpha glutathione S transferase (αGST). αGST is also referred to herein as alpha GST.

According to a second embodiment of the invention, the biomarker is specific to the distal region of the renal tubule.

A preferred biomarker is πGST. πGST is also referred to herein as Pi GST.

According to a third aspect of the invention, the biomarker is specific to the glomerular region of the kidney.

A preferred biomarker is Collagen IV.

The method according to the invention allows for the detection of one or more biomarkers simultaneously.

The invention also provides a method for characterising regional damage in obesity-related nephropathy which comprises carrying out a method as hereinabove defined. The invention also provides a method for determining the pattern of damage to the nephron in obesity-related nephropathy, which comprises carrying out a method as hereinabove defined.

The invention also provides a method of determining the likelihood of an obese subject progressing to clinically significant renal disease, which comprises carrying out a method as hereinabove defined.

According to this embodiment of the invention, the clinically significant renal disease can be End Stage Renal Disease (ESRD).

The biomarkers can be measured in accordance with the invention in a manner known per se.

Accordingly, the biomarkers can be detected by immunoassay, enzymatically or other technique or by a combination thereof, for example, immunoturbidimetric assay.

Immunoassay techniques for use in accordance with the invention include sandwich, competitive, non-competitive, direct and indirect assays.

A detection enzyme may be linked directly to the primary antibody or introduced through the secondary antibody that recognises the primary antibody.

Preferably, the second antibody is a labelled antibody and the detection of the presence of biomarker-antibody complex is effected by detecting the label on the antibody. The label for the antibody may also be an entity detectable by biochemical, photochemical, immunological, spectroscopic, biophysical or any chemical means.

Preferably, the second antibody label is selected from the group consisting of an affinity label, biotin, a chromophore, a colloidal metal, dioxigenin, a dye, an enzyme, an enzyme substrate, a fluorophore, a lumiphore, a magnetic particle, a metabolite, a radioisotope and streptavidin.

The or each biomarker can be detected using an enzyme immunoassay, more especially a sandwich enzyme immunoassay.

The method according to the invention allows for any biomarker present in the sample to form a complex with its corresponding antibody. Unbound proteins are removed by washing, and a labelled second antibody is allowed to bind to its corresponding biomarker forming an antibody-biomarker complex, signalling the presence of a biomarker in the sample.

In one embodiment of the invention the determination of the antibody-biomarker complex is carried out by a competition immunoassay.

According to a further embodiment of the invention, the or each biomarker is detected enzymatically. It will be appreciated that the capture molecule for αGST, being an enzyme, can be a substrate or co-factor for αGST.

It will also be appreciated that the capture molecule for πGST, being an enzyme, can also be a substrate or co-factor for πGST.

Assays carried out in accordance with the invention can be multiplexed to simultaneously measure multiple biomarkers in a single sample in a manner known per se.

The invention also provides αGST as a biomarker for the early identification and prediction of renal damage in a subject with obesity.

The invention further provides πGST as a biomarker for the early identification and prediction of renal damage in a subject with obesity.

The invention still further provides Collagen IV as a biomarker for the early identification and prediction of renal damage in a subject with obesity.

Brief Description of the Drawings

Fig 1. is a graph showing individual data points for urinary αGST corrected to urinary creatinine concentration, with subjects shown in rank order;

Fig. 2. is a graph showing individual data points for urinary πGST corrected to urinary creatinine concentration, with subjects shown in rank order; and Fig. 3. is a graph showing individual data points for urinary Collagen IV corrected to urinary creatinine concentration, with subjects shown in rank order

Mode for Carrying Out the Invention:

The invention will be further illustrated by the following Example

Example

Subjects

A consecutive series of obese patients attending a hospital-based multidisciplinary weight management clinic over a 2-week period were invited to participate in the study. Those consenting to take part had clinical data collected, in addition to blood samples and a spot urine sample, as per routine clinic practise. Within 4 hours of collection, an aliquot of urine was taken and 4mls added to ImI of stabilisation buffer (BIO85STB, Biotrin International Limited, Dublin, Ireland) for subsequent αGST and πGST testing, a second aliquot of urine was taken and 4ml added to Collagen IV collection tubes (BIO84, Biotrin International Limited, Dublin, Ireland) and the remaining urine was stored in a plain tube. All samples were then frozen at -2O⁰C. Patients with a history of diabetes, or those found to have diabetes on the day of testing were excluded, in order to have a cohort of patients without diabetic nephropathy.

The patients investigated all had normal serum creatinine levels. Controls

In order to ascertain the normal range for the πGST, αGST and Collagen IV assays, spot urine samples were collected from 19 healthy volunteers, recruited anonymously from employees at Biotrin International Limited. Volunteers completed a numbered questionnaire, asking details such as age, weight, past medical history and medication usage, and gave a urine sample. No personal identifiers were recorded. Samples and questionnaires were deposited in a sealed box, in an anonymous fashion, with a non-Biotrin staff member collecting the box and processing samples and clinical details. Urine samples were aliquoted and frozen within 4 hours, in the same way as the test samples. Ethical approval was granted from the St Vincent's University Hospital Ethics committee, Dublin, Ireland.

Blood and urine measurements

Blood was taken for routine biochemistry, including creatinine, and samples were assayed in the hospital clinical laboratory as per routine practise. Urine was measured for albumin and creatinine in the hospital metabolism laboratory as per routine practise. Urinary creatinine was measured using a kinetic alkaline picrate method on the Cobas Mira (TM) analyser, with intra-assay and inter-assay CV of <0.9% and <0.8%, respectively. Urinary albumin was measured using an immunoturbidimetric method employing a commercially available antibody to human serum albumin (DAKO) and using Audit Diagnostics Albumin Calibrator (CE), with intra-assay and inter-assay CV of <3.5% and <3.0%, respectively. The lower limit of sensitivity of the urinary albumin assay is 4.0mg/L, and so values at or below this level were assigned the value of 4.0mg/L.

The quantitative analysis of the biomarkers πGST, αGST and Collagen IV in spot urine samples was performed by ELISA, using the standard protocol of the Pi GST EIA (BIO85), NEPHKIT^® Alpha GST EIA (BIO66NEPHA) and Collagen IV EIA (BIO83) from Biotrin International, Ireland. Assay performance parameters of these immunoassays are intra-assay CV 2% (n=24) and inter-assay CV < 9% (n=25) for Pi GST EIA, < 9.5 % (n=20) and < 13.5% (nlO) for NEPHKIT^® Alpha GST EIA and < 3% (n=8) and < 7.5% (n=4) for Collagen IV EIA, respectively.

To control for variable degrees of concentration of urine, all data are expressed corrected to the concentration of urinary creatinine. The highest level of biomarker found in the control group was taken to be the upper limit of normal for each biomarker.

Statistics

Summary data are expressed as mean when normally distributed, and as median when not normally distributed. The proportions of patients with abnormal results were compared using the Chi-square test. The biomarker levels in the control and obese patient groups were compared using the Mann- Whitney U test using Minitab ® 13 statistical software package, as data were not normally distributed. Results Control Group

The control group data are given in Table 1.

In Table 1 the abbreviations are as follows: U albumin = urinary albumin,

U creat = urinary creatinine,

Ualb/creat = urinary albumin / creatinine ratio.

Table 1.

Control data from healthy volunteers

U Collagen

Gender Age Weight U Creat Ualb/creat πGST αGST albumin IV ug/mmo ug/mmol ug/mmol m / f years kg mg/L mmol/L mg/mmol 1 Ucreat Ucreat Ucreat f 25 60 8.7 12.68 0.69 1.34 0.28 0.25 m 25 57 6.2 9.98 0.62 0.73 0.35 0.43 f 26 72 5.8 10.57 0.55 2.95 0.79 0.32 m 26 69 10.5 24.07 0.44 0.51 0.21 0.11 m 26 85 6.1 12.08 0.5 0.0 0.01 2.1 m 27 75 4.0 5.82 0.69 0.52 0.48 0.33 m 28 82 4.0 18.48 0.22 1.06 0.51 0.15 m 28 76 7.0 15.39 0.45 1.84 0.76 0.19 f 29 48 11.4 12.37 0.92 5.2 0.44 0.28 m 34 94 7.2 17.95 0.40 0.82 0.19 0.11 m 34 86 4.0 3.58 1.12 1.98 0.71 0.13 m 34 99 4.2 9.78 0.43 2.30 0.52 0.13 f 35 85 4.0 6.28 0.64 1.35 0.70 0.16 m 37 69 4.6 13.04 0.35 0.88 0.46 0.16 m 40 82 4.0 6.68 0.60 1.26 0.48 0.07 m 43 73 4.0 3.00 1.33 2.42 0.67 0.14 m 51 83 4.0 4.86 0.82 0.00 0.39 0.08 m 51 69 7.6 5.91 1.29 2.07 0.26 0.12 m 53 102 4.0 11.82 0.34 0.80 0.44 0.21

Mean 34 77 5.9 10.75 0.65 1.48 0.45 0.29

Median 34 76 4.6 10.57 0.60 1.26 0.46 0.16

As indicated above the lower limit of sensitivity of the urinary albumin assay is 4.0mg/L, and so values at or below this level were assigned the value of 4.0mg/L (8 of 19 healthy volunteers).

The control group had mean age 34years, 15/19 were male, mean weight 77.2kg. Height data were not recorded so BMI data were not available.

Obese subjects

Five of the 22 obese subjects had diabetes, and so were excluded. The data from the remaining 17 obese subjects are given in Table 2.

In Table 2 the boxes represent biomarker results above the upper limit of the range of results from the control group. The patient aged 50 years required temporary renal dialysis 3 months prior to the study. Blank data points represent missing data.

In Table 2 the abbreviations are as follows:

BMI = body mass index,

U alb/creat = urinary albumin / creatinine ratio.

U creat = urinary creatinine. Table 2 Obese Subjects

Calculated U Collagen

Gender Age Weight BMl Creat U Creat Ualb/creat Pi GST Alpha

GFR albumin GST IV ug/mmol ug/mmol m / f years kg kg/m² umol/L rπL/min mg/L mmol/L mg/mmol ug/mmol Ucreat Ucreat Ucreat

m 40 155 49.0 73 109.8 11.6 9.14 1.27 3.12 0.77 0.32 f 43 121 45.4 75 77.9 7.6 13.53 0.56 3.41 1.51 0.30 f 43 155 54.9 69 85.7 16.6 6.09 2.73 2.28 0.96 0.37 Os f 44 152 48.4 72 81.2 16.1 8.04 2.00 31.11 1.39 0.29 f 47 133 54.7 89 62.8 59.2 22.08 2.68 2.69 1.29 0.61 m 50 231 69.9 83 90.5 13.3 18.22 0.73 11.17 0.41 0.67 m 55 218 78.2 79 94.0 10.1 11.27 0.90 2.34 1.99 0.63 f 56 108 42.1 72 77.3 5.4 12.15 0.44 0.56 0.53 0.22 m 57 103 44.0 52 151.2 14.1 6.14 2.30 6.54 0.95 0.69 m 60 107 34.9 87 82.6 8.9 17.97 0.50 0.74 0.20 0.24 m 64 135 41.7 96 72.8 4.6 9.42 0.49 1.71 1.93 0.26

Mean 44 144 51 75 90.9 12.1 10.46 1.32 5.50 1.13 0.36

Median 43 135 47 74 86.6 8.9 9.34 0.90 3.02 0.95 0.32

Estimated GFR = calculated glomerular filtration rate (using MDMR equation) where eGFR = 186 * [(Serum Creatinine x 0.0113) - 1.154] * (age -0.203) * F, where F = 1 if male, and 0.742 if female.

As indicated above, the lower limit of sensitivity of the urinary albumin assay is 4.0mg/L, and so values at or below this level were assigned the value of 4.0mg/L (3 of 17 obese subjects).

The mean age was 44 years, 7/17 were male, median BMI was 47kg/m (range 35-78), all had normal serum creatinine (mean 75.1μmol/l) and eGFR (mean 90.9mls/min). Three of the 17 obese patients had microalbuminuria (18%), with values albumin/creatinine ratios of of 2.7, 2.7 and 3.3mg/mmol (with microalbuminuria defined as urinary albumin/creatinine ratio of 2.5 to 25mg/mmol). All of these patients had at least one urinary biomarker abnormality. The median urinary albumin/creatinine ratio for the group was 0.90 (range 0.4- 3.3mg/mol).

Compared to the control group, the majority (10/17, 59%) of obese patients had elevated urinary αGST (median 0.95, range 0.2-2.98, control 0.46, range 0.01-0.79, P<0.0005). Five of the 17 obese patients (29%) had elevated urinary πGST (median 3.0, range 0.56-31.1, control 1.26, range 0.0-5.2, PO.001), whilst 4/17 obese patients (24%) had elevated urinary Collagen IV (median 0.32, range 0.11-0.69, control 0.16, range 0.07-0.43, P<0.05). Individual data points are shown in Figs. 1-3.

When directly comparing the obese patients with the control group, the median biomarker levels were significantly higher in the obese group; for αGST 0.95 vs 0.46 (95% CI for difference of 0.3 to 0.9, P<0.001), for πGST 3.0 vs 1.3 (95% CI for difference of 0.8 to 3.1, PO.005), and for Collagen IV 0.32 vs 0.16 (95% CI for difference of 0.07 to 0.24, PO.005).

One patient had acute renal failure requiring temporary renal dialysis 3 months prior to the study. In contrast to the pattern in the majority of the obese group, this patient did not have elevated αGST, but instead had elevated Collagen IV (0.67, control<0.43) and elevated πGST (11.2, control<5.2).

The pattern of biomarker abnormality found in the majority of the obese patients in this study was more that of proximal tubular injury (elevated αGST), as shown in Fig. 1. In contrast the πGST levels were similar between obese patients and controls except for the patients with the 5 highest measurements as shown in Fig. 2. There was early apparent divergence in the Collagen IV levels between the obese and control groups as shown in Fig. 3, but there was considerable overlap between the groups, hence only four patients had a clearly abnormal result.

An exception to the predominant αGST abnormality was the subject who had suffered acute renal failure requiring dialysis three months prior to sample collection. This subject had the second lowest αGST, but the second highest πGST and Collagen IV. The study suggests that different aetiologies of renal injury (obesity and acute renal failure) cause different patterns of biomarker abnormality, which may reflect the differing pathogenesis of renal disease in these conditions. With regard to ORN, the result might be considered to be somewhat surprising, as one of the leading theories for the pathogenesis of ORN is that of glomerular hyperfϊltration. The data presented herein is consistent with the concept mentioned hereinabove, that the aetiology of ORN is complex, and encompasses ORG, but also other mechanisms that include inflammatory processes affecting other segments of the nephron.

The above Example shows that the use of urinary biomarkers in accordance with the invention demonstrated evidence of renal injury in between 24% and 59% of subjects, with proximal tubular injury being the more commonly found abnormality. The patients tested had obesity without diabetes, in whom conventional serum testing indicated that they had normal renal function.

The control group reflects a group of controls from the general working adult population, rather than a lean or exclusively normal- weight population. However, the clear differences between the control group and the obese group, does suggest that these biomarkers are able to identify real differences in the urine of these two groups, although the control and obese groups studied were small.

From a clinical perspective the biomarkers used in accordance with the invention detected renal injury in between 24% and 59% of obese patients who would otherwise have been regarded as having normal renal function, as measured by serum creatinine or estimated glomerular filtration rate. The 24-59% of patients with abnormal urine biomarker levels is considerably greater than the 18% of obese patients that had urinary albumin/creatinine ratios in the microalbuminuria range. It is currently not known how many of those patients with either microalbuminuria or urinary biomarker abnormalities are likely to go on to progress to clinically important renal disease. However, the biomarkers have the potential to detect renal disease in obesity before current tests show an abnormality. Furthermore, finding a pattern of biomarker abnormality that is not typical of ORN (i.e. a pattern other than elevated αGST) may indicate the presence of an alternative cause of renal disease in a patient with obesity, and could help target appropriate patients for further investigation.

Claims

Claims: -

1. A method for the early identification and prediction of renal damage in a subject with obesity, which method comprises contacting a urine sample from the subject with a capture molecule for a biomarker specific to a region of the kidney and which biomarker is released from said region when there is damage to said region, an elevated level of said biomarker relative to a normal level being indicative and predictive of renal damage.

2. A method according to Claim 1, wherein the biomarker is specific to the proximal region of the renal tubule.

3. A method according to Claim 2, wherein the biomarker is alpha glutathione S transferase (αGST).

4. A method according to any preceding claim, wherein the biomarker is specific to the distal region of the renal tubule.

5. A method according to Claim 4, wherein the biomarker is πGST.

6. A method according to any preceding claim, wherein the biomarker is specific to the glomerular region of the kidney.

7. A method according to Claim 6, wherein the biomarker is Collagen IV.

8. A method for characterising regional damage in obesity- related nephropathy, which comprises carrying out a method according to any one of Claims 1-7.

9. A method for determining the pattern of damage to the nephron in obesity-related nephropathy, which comprises carrying out a method according to any one of Claims 1-7

10. A method of determining the likelihood of an obese subject progressing to clinically significant renal disease, which comprises carrying out a method according to any one of Claims 1-7.

11. A method according to Claim 10, wherein the clinically significant renal disease is End Stage Renal Disease (ESRD).

12. A method according to Claim 1 for the early identification and prediction of renal damage in a subject with obesity, substantially as hereinbefore described and exemplified.

13. A method according to Claim 8 for characterising regional damage in obesity-related nephropathy, substantially as hereinbefore described and exemplified.

14. A method according to Claim 9 for determining the pattern of damage to the nephron in obesity-related nephropathy, substantially as hereinbefore described and exemplified.

15. A method according to Claim 10 of determining the likelihood of an obese subject progressing to clinically significant renal disease, substantially as hereinbefore described and exemplified.

16. αGST as a biomarker for the early identification and prediction of renal damage in a subject with obesity.

17. πGST as a biomarker for the early identification and prediction of renal damage in a subject with obesity.

18. Collagen IV as a biomarker for the early identification and prediction of renal damage in a subject with obesity.