Biomarkers for cognitive dysfunction diseases and method for detecting cognitive dysfunction disease using biomarkers

a cognitive dysfunction and biomarker technology, applied in the field of biomarkers for cognitive dysfunction diseases and methods for detecting cognitive dysfunction diseases using biomarkers, can solve problems such as memory impairment, impairment of ability, and pain in the social life function of patients

Inactive Publication Date: 2020-10-01
MCBI +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

The use of these biomarkers enables highly accurate and objective detection of cognitive dysfunction diseases, including mild cognitive impairment and Alzheimer's, with high specificity and sensitivity, facilitating early diagnosis and monitoring of disease progression.

Problems solved by technology

This disease is becoming a social problem because it makes a patient suffer not only from loss of memory but also from destruction of personality, thereby impairing the social life function of the patient.
In Alzheimer's disease, an early diagnosis is a greatest challenge for achieving the effectiveness of current therapeutic methods or drugs which will be developed in future.
(1) memory impairment (impaired ability to learn new information or to recall previously learned information)
Nevertheless, these image-based diagnostic methods have drawbacks due to difficulty in being conducted in every medical facility because of special devices required for them.
In addition, they are not sufficient for give an objective decision because the decision differs from physician to physician who observes the image.
As discussed above, the diagnosis of the cognitive disease depends currently on a method which is less objective and requires expensive instruments, and is not successful in screening for identifying the disease.

Method used

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  • Biomarkers for cognitive dysfunction diseases and method for detecting cognitive dysfunction disease using biomarkers
  • Biomarkers for cognitive dysfunction diseases and method for detecting cognitive dysfunction disease using biomarkers
  • Biomarkers for cognitive dysfunction diseases and method for detecting cognitive dysfunction disease using biomarkers

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Experimental program
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experiment example 1

[0140]Among the marker proteins associated to neurodegenerative diseases including Alzheimer's disease, those of the complement system, namely, complement C3, complement C4, and complement factor H and those involved in suppressing the formation of Aβ fibers responsible for cerebral amyloidosis, namely, transthyretin and alpha-2-macroglobulin are employed as markers, and the biological samples obtained from study subjects were examined by an immunoassay method, thereby detecting cognitive dysfunction diseases based on the existence or the level of the marker as an index.

[0141]As a method for detection, a multiplex immunoassay method which simultaneously detects multiple markers (analytes) in the biological samples was employed.

(1) Serum Samples

[0142]The term in each parenthesis is abbreviated hereinafter as indicated just before the parenthesis.

[0143]The serum samples obtained from 37 AD (Alzheimer's disease) cases, 22 NDC(subjects having no mental diseases) cases, and 39 MCI (mild ...

experiment example 2

(1) Principle of Logistic Regression Analysis

[0162]This method allows the coefficient of each parameter relevant to a biomarker to be obtained from a data set to give the discrimination probability on the patient basis in the two disease categories (normal and disease). A relatively detailed explanation relating to the logistic regression can be obtained from the followings: Non-Patent Document 3: Czepiel, S A, http: / / czep.net / stat / mlelr.pdf, 2010, Maximum likelihood estimation of logistic regression models: theory and implementation. This explanation includes the analysis based on Newton-Raphson method.

[0163]The principle of this analytical procedure is as follows. When assuming the probability of occurrence of a certain event as P, then Equation 1:

F(Z)=p=11+e-Z(1)

is known to be approximated to a cumulative standard normal distribution (Non-Patent Document 4: Bowling, S R, et al. JIEM, 2009, 2: 114-127, A logistic approximation to the cumulative normal distribution.). Using this ap...

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Abstract

Biomarkers for detecting cognitive dysfunction diseases and methods for detecting cognitive dysfunction diseases using the biomarkers are provided. A method for detecting cognitive dysfunction diseases comprising measuring one or more biomarkers for detecting cognitive dysfunction diseases selected from the following (a), (b), and (c) in a biological sample simultaneously or separately: (a) a biomarker for detecting cognitive dysfunction diseases consisting of an intact protein of apolipoprotein A1 comprising the amino acid sequence represented by SEQ ID NO:1 or a partial peptide thereof; (b) a biomarker for detecting cognitive dysfunction diseases consisting of an intact protein of transthyretin comprising the amino acid sequence represented by SEQ ID NO:2 or a partial peptide thereof; and (c) a biomarker for detecting cognitive dysfunction diseases consisting of an intact protein of complement C3 comprising the amino acid sequence represented by SEQ ID NO:3 or a partial peptide thereof.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application is a Divisional of application Ser. No. 14 / 901,275, filed on Dec. 28, 2015, which is the National Phase under 35 U.S.C. § 371 of International Application No. PCT / JP2013 / 067785, filed on Jun. 28, 2013, all of which are hereby expressly incorporated by reference into the present application.TECHNICAL FIELD[0002]The present invention relates to biomarkers which are novel proteins and peptides capable of being employed for detecting cognitive dysfunction diseases including mild cognitive impairment and Alzheimer's disease, and methods for detecting cognitive dysfunction diseases using the biomarkers.BACKGROUND ART[0003]A major prior art as a means for using samples exhibiting in vivo conditions which are normal and are not normal for determining a difference between them is a technology employed generally in extracorporeal diagnostic agents.[0004]Most of the extracorporeal diagnostic agents are employed in diagnosis in which...

Claims

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Application Information

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Patent Type & AuthorityApplications(United States)
IPC IPC(8): G01N33/68C07K14/47
CPCG01N2333/775G01N2333/76G01N2333/96433G01N2800/2814G01N33/6893C07K14/47G01N33/6896C12N15/115G06F17/18C12N2310/16G01N2800/2821
InventorUCHIDAMENO, KOHJISUZUKI, HIDEAKINISHIMURA, YOSHINORI
OwnerMCBI