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WO2009122387A1 - Procédé de détection et de prédiction de maladie rénale associée à l’obésité - Google Patents

Procédé de détection et de prédiction de maladie rénale associée à l’obésité Download PDF

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Publication number
WO2009122387A1
WO2009122387A1 PCT/IE2008/000037 IE2008000037W WO2009122387A1 WO 2009122387 A1 WO2009122387 A1 WO 2009122387A1 IE 2008000037 W IE2008000037 W IE 2008000037W WO 2009122387 A1 WO2009122387 A1 WO 2009122387A1
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WO
WIPO (PCT)
Prior art keywords
biomarker
obesity
renal
damage
subject
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/IE2008/000037
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English (en)
Inventor
Mohammed Bashir
Thomas James Cawood
Cormac Gerard Kilty
Claire Victoria Mcgrath
Donal O'shea
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Biotrin Group Ltd
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Biotrin Group Ltd
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Filing date
Publication date
Application filed by Biotrin Group Ltd filed Critical Biotrin Group Ltd
Priority to PCT/IE2008/000037 priority Critical patent/WO2009122387A1/fr
Publication of WO2009122387A1 publication Critical patent/WO2009122387A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/573—Immunoassay; Biospecific binding assay; Materials therefor for enzymes or isoenzymes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6887—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids from muscle, cartilage or connective tissue
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/78—Connective tissue peptides, e.g. collagen, elastin, laminin, fibronectin, vitronectin, cold insoluble globulin [CIG]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/90—Enzymes; Proenzymes
    • G01N2333/91—Transferases (2.)
    • G01N2333/9116—Transferases (2.) transferring alkyl or aryl groups other than methyl groups (2.5)
    • G01N2333/91165—Transferases (2.) transferring alkyl or aryl groups other than methyl groups (2.5) general (2.5.1)
    • G01N2333/91171—Transferases (2.) transferring alkyl or aryl groups other than methyl groups (2.5) general (2.5.1) with definite EC number (2.5.1.-)
    • G01N2333/91177—Glutathione transferases (2.5.1.18)
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/04—Endocrine or metabolic disorders
    • G01N2800/044—Hyperlipemia or hypolipemia, e.g. dyslipidaemia, obesity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/50—Determining the risk of developing a disease

Definitions

  • This invention relates to a method for the early identification and prediction of renal damage in a subject with obesity and to biomarkers therefor.
  • ESRD end-stage renal disease
  • 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).
  • ORN obesity-related nephropathy
  • ORG obesity-related glomerulopathy
  • ORN nephron number
  • 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.
  • 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.
  • ORN 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.
  • 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).
  • 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).
  • 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).
  • 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.
  • 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.
  • 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.
  • the biomarker is specific to the proximal region of the renal tubule.
  • a preferred biomarker is alpha glutathione S transferase ( ⁇ GST).
  • ⁇ GST is also referred to herein as alpha GST.
  • the biomarker is specific to the distal region of the renal tubule.
  • a preferred biomarker is ⁇ GST.
  • ⁇ GST is also referred to herein as Pi GST.
  • 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.
  • the clinically significant renal disease can be End Stage Renal Disease (ESRD).
  • ESRD End Stage Renal Disease
  • biomarkers can be measured in accordance with the invention in a manner known per se.
  • 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.
  • 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.
  • 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.
  • the determination of the antibody-biomarker complex is carried out by a competition immunoassay.
  • the or each biomarker is detected enzymatically.
  • the capture molecule for ⁇ GST being an enzyme, can be a substrate or co-factor for ⁇ GST.
  • the capture molecule for ⁇ GST being an enzyme, can also be a substrate or co-factor for ⁇ GST.
  • 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 ⁇ GST as a biomarker for the early identification and prediction of renal damage in a subject with obesity.
  • the invention further provides ⁇ GST 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.
  • Fig 1. is a graph showing individual data points for urinary ⁇ GST corrected to urinary creatinine concentration, with subjects shown in rank order;
  • Fig. 2. is a graph showing individual data points for urinary ⁇ GST 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
  • Urin 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.
  • control group data are given in Table 1.
  • Ualb/creat urinary albumin / creatinine ratio.
  • 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.
  • 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 75.1 ⁇ mol/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).
  • the median biomarker levels were significantly higher in the obese group; for ⁇ GST 0.95 vs 0.46 (95% CI for difference of 0.3 to 0.9, P ⁇ 0.001), for ⁇ GST 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).
  • 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.
  • 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.
  • 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.
  • the biomarkers have the potential to detect renal disease in obesity before current tests show an abnormality.
  • finding a pattern of biomarker abnormality that is not typical of ORN i.e. a pattern other than elevated ⁇ GST

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  • Life Sciences & Earth Sciences (AREA)
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  • Engineering & Computer Science (AREA)
  • Immunology (AREA)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • Chemical & Material Sciences (AREA)
  • Hematology (AREA)
  • Urology & Nephrology (AREA)
  • Biotechnology (AREA)
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  • Physics & Mathematics (AREA)
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  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
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  • Investigating Or Analysing Biological Materials (AREA)

Abstract

La présente invention concerne un procédé d’identification et de prédiction précoce d’une maladie rénale chez un sujet obèse comprenant la mise en contact d’un échantillon d’urine prélevé du sujet avec une molécule de capture pour un biomarqueur spécifique à une région du rein et ledit biomarqueur est libéré depuis ladite région où ladite région est endommagée, un niveau élevé dudit biomarqueur par rapport à un niveau normal constituant une indication et une prédiction de maladie rénale. Les biomarqueurs comprennent αGST, πGST et le collagène IV. Le procédé permet la détection de lésion rénale chez des patients obèses qui autrement seraient considérés comme ayant une fonction rénale normale telle que mesurée par le taux de créatinine sérique ou de filtration glomérulaire estimée, facilitant ainsi une intervention précoce dans le traitement de tels patients.
PCT/IE2008/000037 2008-04-04 2008-04-04 Procédé de détection et de prédiction de maladie rénale associée à l’obésité Ceased WO2009122387A1 (fr)

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Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012012704A2 (fr) 2010-07-23 2012-01-26 President And Fellows Of Harvard College Procédés de détection de maladies ou d'états associés au rein
WO2012012725A2 (fr) 2010-07-23 2012-01-26 President And Fellows Of Harvard College Méthodes de dépistage de maladies ou d'affections à l'aide de cellules phagocytaires
US10494675B2 (en) 2013-03-09 2019-12-03 Cell Mdx, Llc Methods of detecting cancer
US10626464B2 (en) 2014-09-11 2020-04-21 Cell Mdx, Llc Methods of detecting prostate cancer
US10934589B2 (en) 2008-01-18 2021-03-02 President And Fellows Of Harvard College Methods of detecting signatures of disease or conditions in bodily fluids
US10961578B2 (en) 2010-07-23 2021-03-30 President And Fellows Of Harvard College Methods of detecting prenatal or pregnancy-related diseases or conditions
US11111537B2 (en) 2010-07-23 2021-09-07 President And Fellows Of Harvard College Methods of detecting autoimmune or immune-related diseases or conditions
US11585814B2 (en) 2013-03-09 2023-02-21 Immunis.Ai, Inc. Methods of detecting prostate cancer
EP4303584A2 (fr) 2010-07-23 2024-01-10 President and Fellows of Harvard College Procédés de détection de signatures de maladies ou pathologies dans des liquides biologiques

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BIOTRIN INTERNATIONAL: "How late do you want to detect preclinical kidney damage?", INTERNET ARTICLE, 29 August 2007 (2007-08-29), XP002517793, Retrieved from the Internet <URL:http://www.biotrin.com/pdf_upload/1Preclinical Kidney Damage.pdf> [retrieved on 20090304] *
EJERBLAD ELISABETH ET AL: "Obesity and risk for chronic renal failure", JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY, vol. 17, no. 6, June 2006 (2006-06-01), pages 1695 - 1702, XP002517794, ISSN: 1046-6673 *
HSU CHI-YUAN ET AL: "Body mass index and risk for end-stage renal disease", ANNALS OF INTERNAL MEDICINE, vol. 144, no. 1, January 2006 (2006-01-01), pages 21 - 28, XP002517795, ISSN: 0003-4819 *
SUNDBERG A G M: "URINARY PL-CLASS GLUTATHIONE TRANSFERASE AS AN INDICATOR OF TUBULARDAMAGE IN THE HUMAN KIDNEY", NEPHRON,, vol. 67, 1 January 1994 (1994-01-01), pages 308 - 316, XP000578885, ISSN: 0028-2766 *

Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10934589B2 (en) 2008-01-18 2021-03-02 President And Fellows Of Harvard College Methods of detecting signatures of disease or conditions in bodily fluids
US10934588B2 (en) 2008-01-18 2021-03-02 President And Fellows Of Harvard College Methods of detecting signatures of disease or conditions in bodily fluids
US11001894B2 (en) 2008-01-18 2021-05-11 President And Fellows Of Harvard College Methods of detecting signatures of disease or conditions in bodily fluids
US11111537B2 (en) 2010-07-23 2021-09-07 President And Fellows Of Harvard College Methods of detecting autoimmune or immune-related diseases or conditions
WO2012012725A2 (fr) 2010-07-23 2012-01-26 President And Fellows Of Harvard College Méthodes de dépistage de maladies ou d'affections à l'aide de cellules phagocytaires
EP4303584A2 (fr) 2010-07-23 2024-01-10 President and Fellows of Harvard College Procédés de détection de signatures de maladies ou pathologies dans des liquides biologiques
WO2012012704A2 (fr) 2010-07-23 2012-01-26 President And Fellows Of Harvard College Procédés de détection de maladies ou d'états associés au rein
US10961578B2 (en) 2010-07-23 2021-03-30 President And Fellows Of Harvard College Methods of detecting prenatal or pregnancy-related diseases or conditions
US11585814B2 (en) 2013-03-09 2023-02-21 Immunis.Ai, Inc. Methods of detecting prostate cancer
US10494675B2 (en) 2013-03-09 2019-12-03 Cell Mdx, Llc Methods of detecting cancer
US12037645B2 (en) 2013-03-09 2024-07-16 Immunis.Ai, Inc. Methods of detecting cancer
US12181477B2 (en) 2013-03-09 2024-12-31 Immunis.Ai, Inc. Methods of detecting prostate cancer
US10626464B2 (en) 2014-09-11 2020-04-21 Cell Mdx, Llc Methods of detecting prostate cancer

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