SG11201810261UA - Kidney disease prognosis prediction method and system - Google Patents

Kidney disease prognosis prediction method and system

Info

Publication number
SG11201810261UA
SG11201810261UA SG11201810261UA SG11201810261UA SG11201810261UA SG 11201810261U A SG11201810261U A SG 11201810261UA SG 11201810261U A SG11201810261U A SG 11201810261UA SG 11201810261U A SG11201810261U A SG 11201810261UA SG 11201810261U A SG11201810261U A SG 11201810261UA
Authority
SG
Singapore
Prior art keywords
kidney disease
prognosis
prediction method
prognosis prediction
disease prognosis
Prior art date
Application number
SG11201810261UA
Inventor
Yoshitaka Isaka
Tomonori Kimura
Keiko Yasuda
Kenji Hamase
Masashi Mita
Original Assignee
Univ Osaka
Shiseido Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Univ Osaka, Shiseido Co Ltd filed Critical Univ Osaka
Publication of SG11201810261UA publication Critical patent/SG11201810261UA/en

Links

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
    • 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
    • G01N33/6803—General methods of protein analysis not limited to specific proteins or families of proteins
    • G01N33/6806—Determination of free amino acids
    • G01N33/6812—Assays for specific amino acids
    • 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
    • G01N33/72—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving blood pigments, e.g. haemoglobin, bilirubin or other porphyrins; involving occult blood
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/34—Genitourinary disorders
    • G01N2800/347—Renal failures; Glomerular diseases; Tubulointerstitial diseases, e.g. nephritic syndrome, glomerulonephritis; Renovascular diseases, e.g. renal artery occlusion, nephropathy
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • G16B40/20—Supervised data analysis

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Molecular Biology (AREA)
  • Biomedical Technology (AREA)
  • Hematology (AREA)
  • Chemical & Material Sciences (AREA)
  • Immunology (AREA)
  • Urology & Nephrology (AREA)
  • Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Biotechnology (AREA)
  • Pathology (AREA)
  • Analytical Chemistry (AREA)
  • General Physics & Mathematics (AREA)
  • Biochemistry (AREA)
  • Food Science & Technology (AREA)
  • Microbiology (AREA)
  • Cell Biology (AREA)
  • Medicinal Chemistry (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Medical Informatics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Biophysics (AREA)
  • Public Health (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
  • Genetics & Genomics (AREA)
  • Epidemiology (AREA)
  • Primary Health Care (AREA)
  • Investigating Or Analysing Biological Materials (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Abstract

KIDNEY DISEASE PROGNOSIS PREDICTION METHOD AND SYSTEM The purpose of the present invention is to provide: a method for predicting the prognosis 5 for kidney disease for a subject on the basis of the amount of D- and L-amino acids, from a blood sample; and an analysis system that determines prognosis predictions. This purpose is achieved by using at least one amino acid to predict the prognosis for kidney disease, said amino acid being selected from the group consisting of D-serine, D-asparagine, D-proline, D-alanine, D-leucine, D-lysine, D-allo-isoleucine, L-glutamic acid, L-alanine, L-tryptophan, and L- 10 asparagine. [FIG. 1]
SG11201810261UA 2016-05-17 2017-05-17 Kidney disease prognosis prediction method and system SG11201810261UA (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2016099158 2016-05-17
PCT/JP2017/018591 WO2017200024A1 (en) 2016-05-17 2017-05-17 Kidney disease prognosis prediction method and system

Publications (1)

Publication Number Publication Date
SG11201810261UA true SG11201810261UA (en) 2018-12-28

Family

ID=60325935

Family Applications (1)

Application Number Title Priority Date Filing Date
SG11201810261UA SG11201810261UA (en) 2016-05-17 2017-05-17 Kidney disease prognosis prediction method and system

Country Status (8)

Country Link
US (2) US11099191B2 (en)
EP (1) EP3460477A4 (en)
JP (1) JP7123329B2 (en)
CN (1) CN109154621B (en)
AU (1) AU2017266330A1 (en)
IL (1) IL263025A (en)
SG (1) SG11201810261UA (en)
WO (1) WO2017200024A1 (en)

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111033637B (en) * 2017-08-08 2023-12-05 费森尤斯医疗保健控股公司 Systems and methods for treating and assessing the progression of chronic kidney disease
TW202022379A (en) * 2018-10-17 2020-06-16 日商資生堂股份有限公司 Method for assaying validity of renal function test result based on creatinine content in blood
JPWO2020080482A1 (en) * 2018-10-17 2021-09-09 Kagami株式会社 A method for validating renal function test results based on the amount of cystatin C in blood
EP3869202A4 (en) * 2018-10-17 2022-08-10 Kagami Inc. Method for determining glomerular filtration ability
WO2020196437A1 (en) * 2019-03-22 2020-10-01 Kagami株式会社 Method for assisting evaluation of renal pathological conditions, system for evaluating renal pathological conditions and program for evaluating renal pathological conditions
US20220252610A1 (en) * 2019-03-22 2022-08-11 Kagami Inc. Method for assisting evaluation of condition of kidneys, system for evaluating condition of kidneys, and program for evaluating condition of kidneys
US20230037869A1 (en) * 2019-12-27 2023-02-09 Kagami Inc. Method and system for estimating renal function
CN114636774B (en) * 2022-04-22 2024-05-17 苏州市疾病预防控制中心 Biological metabolism marker composition for predicting adolescent hypertension disease risk

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4378472B2 (en) 2001-12-27 2009-12-09 独立行政法人産業技術総合研究所 Neisseria gonorrhoeae daoC gene
EP1482310A1 (en) * 2003-05-30 2004-12-01 Bayer HealthCare AG Relaxin as an independent risk factor predicting mortality
WO2006060793A2 (en) * 2004-12-01 2006-06-08 Children's Hospital & Research Center At Oakland Diagnosis of conditions associated with decreased arginine bioavailability
US20070037232A1 (en) * 2005-03-31 2007-02-15 Barasch Jonathan M Detection of NGAL in chronic renal disease
TW201250248A (en) * 2011-04-25 2012-12-16 Kyowa Medex Co Ltd Prognostication method of renal failure
WO2013115283A1 (en) * 2012-01-31 2013-08-08 味の素株式会社 Method for evaluating early stage nephropathy, early stage nephropathy evaluation device, early stage nephropathy evaluation method, early stage nephropathy evaluation program, early stage nephropathy evaluation system and information communication terminal device
CN114966050A (en) 2012-03-18 2022-08-30 镜株式会社 Disease sample analysis device, disease sample analysis system, and disease sample analysis method
DK2904403T3 (en) * 2012-10-02 2018-07-16 Sphingotec Gmbh PROCEDURE FOR DIAGNOSTICATION OR MONITORING OF Kidney Function or Diagnosis of Kidney Function
EP3081939B1 (en) * 2013-12-11 2021-02-17 Kagami Inc. Marker for early diagnosis of kidney failure

Also Published As

Publication number Publication date
WO2017200024A1 (en) 2017-11-23
JP2017207489A (en) 2017-11-24
EP3460477A4 (en) 2020-01-08
US20190317106A1 (en) 2019-10-17
US11099191B2 (en) 2021-08-24
JP7123329B2 (en) 2022-08-23
AU2017266330A8 (en) 2019-01-03
CN109154621A (en) 2019-01-04
US20220003774A1 (en) 2022-01-06
IL263025A (en) 2018-12-31
EP3460477A1 (en) 2019-03-27
CN109154621B (en) 2022-08-05
AU2017266330A1 (en) 2018-12-06

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