Detection of chronic kidney disease and disease progression

• US 9,689,826 B2
• Filed: 03/11/2013
• Issued: 06/27/2017
• Est. Priority Date: 03/11/2012
• Status: Active Grant

• Current Assignee: TECHNION RESEARCH AND DEVELOPMENT FOUNDATION, LTD.
• Original Assignee: TECHNION RESEARCH AND DEVELOPMENT FOUNDATION, LTD.
• Inventors: Marom, Ophir, Haick, Hossam
• Primary Examiner(s): Gakh, Yelena G
• Application Number:
  US13/793,833
• Publication Number:
  US 20130236981A1
• Time in Patent Office: 1,569 Days
• CPC Class Codes: G01N 27/06 of a liquid involving electrolysis G01N27/26
• CPC Class Codes: G01N 27/26 by investigating electrochemical variables; by using electrolysis or electrophoresis
• CPC Class Codes: G01N 2800/347 Renal failures; Glomerular diseases; Tubulointerstitial diseases, e.g. nephritic syndrome, glomerulonephritis; Renovascular diseases, e.g. renal artery occlusion, nephropathy
• CPC Class Codes: G01N 33/497 of gaseous biological material, e.g. breath

Abstract

The present invention provides a sensor or a system comprising gold nanoparticles coated with specific organic coatings for diagnosing, staging or monitoring chronic kidney disease.

Claims

1. A method of diagnosing or staging chronic kidney disease (CKD) in a subject, the method comprising the steps of:

(a) providing a system comprising a sensor array comprising at least two sensors comprising gold nanoparticles capped with an organic coating selected from the group consisting of 2-ethylhexanethiol, tert-dodecanethiol, hexanethiol and dibutyl disulfide; and

a processing unit comprising a pattern recognition algorithm;

(b) exposing the sensor array to a test exhaled breath sample;

(c) measuring a plurality of electric signals generated by detection of a plurality of volatile organic compounds (VOCs) indicative of chronic kidney disease and its stages in the test sample by the sensor array, wherein the VOC indicative of stage 2 CKD is selected from the group consisting of toluene, 2,2,6-trimethyl-octane 2-butanone, and combinations thereof;

wherein the VOC indicative of stage 2-3 CKD is acetone;

wherein the VOCs indicative of probability of stage 4 CKD is selected from the group consisting of ethylene glycol, acetoin and a combination thereof;

wherein the VOC indicative of stage 5 CKD is selected from the group consisting of ethylene glycol, acetoin and a combination thereof; and

wherein the VOC indicative of subject not afflicted with CKD is styrene, and the plurality of electric signals form a response pattern; and

(d) analyzing the response pattern obtained in step (c) using the pattern recognition algorithm by comparing the response pattern to stored data obtained from a set of control samples, the set of control samples being obtained from a control subject selected from the group consisting of a person who is not afflicted with CKD, a person known to be afflicted with stage 2 CKD, a person known to be afflicted with stage 3 CKD, a person known to be afflicted with stage 4 CKD, and a person known to be afflicted with stage 5 CKD, thereby providing the diagnosis or staging of chronic kidney disease.

2. The method of claim 1, wherein the gold nanoparticles have a morphology selected from a cubic, a spherical, and a spheroidal morphology.

3. The method of claim 1, wherein each sensor is configured in a form selected from the group consisting of a capacitive sensor, a resistive sensor, a chemiresistive sensor, an impedance sensor, and a field effect transistor sensor.

4. The method of claim 1, wherein the sensor array comprises four sensors of gold nanoparticles capped with an organic coating comprising 2-ethylhexanethiol, tert-dodecanethiol, hexanethiol and dibutyl disulfide.

5. The method of claim 1, comprising measuring a plurality of electric signals generated by detection of each volatile organic compound indicative of chronic kidney disease in the test sample.

6. The method of claim 1, wherein the system further comprises a detection device for measuring the plurality of electric signals, wherein the detection device measures a change in at least one of property of a sensor, selected from the group consisting of resistance, conductance, alternating current (AC), frequency, capacitance, impedance, inductance, electrical potential, and voltage threshold.

7. The system of claim 1, wherein the pattern recognition algorithm is selected from the group consisting of artificial neural network algorithm, support vector machine (SVM), principal component analysis (PCA), multi-layer perception (MLP), generalized regression neural network (GRNN), fuzzy inference system (FIS), self-organizing map (SOM), radial bias function (RBF), genetic algorithm (GAS), neuro-fuzzy system (NFS), adaptive resonance theory (ART), partial least squares (PLS), multiple linear regression (MLR), principal component regression (PCR), discriminant function analysis (DFA), linear discriminant analysis (LDA), cluster analysis, and nearest neighbor.

8. The method of claim 1, further comprising the step of concentrating the test exhaled breath sample prior to step (b) using at least one of a breath concentrator and a dehumidifying unit.

9. The method of claim 1 for differentiating between an unhealthy subject having chronic kidney disease (CKD) and a healthy subject, the method comprising measuring a signal generated by detection of styrene.

10. The method of claim 1 for diagnosing stage 5 CKD in a subject, the method comprising measuring a plurality of signals generated by detection of at least one VOCs selected from ethylene glycol and acetoin.

11. The method of claim 1 for diagnosing stage 2 CKD in a subject, the method comprising measuring a plurality of signals generated by detection of at least one VOC selected from the group consisting of toluene 2,2,6-trimethyl-octane, and 2-butanone.

12. The method of claim 1, comprising measuring a plurality of signals generated by detection of a plurality of VOCs selected from the group consisting of ethylene glycol, acetoin, acetone, styrene, toluene, 2-butanone and 2,2,6-trimethyl-octane.