Protein biomarkers to predict progression to Alzheimer’s disease and companion diagnostic composition for discriminating adequate patients to early Alzheimer's therapies thereof

Abstract

One objective of the present invention is to provide a method for obtaining protein quantitative analysis data using blood, selecting a patient group with a high risk of dementia conversion, and recommending a treatment candidate group suitable for anti-amyloid antibody drug therapy.

Description

Technology Field

[0001] The present invention relates to a technology for selecting an optimal patient group for early dementia treatment using proteins that predict Alzheimer's dementia conversion or gene biomarkers encoding the same. Background Technology

[0002] To date, researchers of Alzheimer's dementia have focused on diagnosing the disease through brain imaging tests such as positron emission tomography (PET)-CT or through the advancement of protein quantitative analysis, such as amyloid-beta protein plaques or neurofibrillary tangles found in cerebrospinal fluid. PET contrast agents, such as Amyvid®, used in the screening of Alzheimer's disease, play a role in facilitating image-based diagnosis by binding to amyloid-beta protein plaques when a patient's brain is scanned via PET. However, there is a limitation in that amyloid plaques are detected even in elderly individuals with normal cognitive function, which does not correlate with actual clinical symptoms and disease progression. In addition, antibody diagnostic reagents that quantify the concentration of amyloid or tau proteins from cerebrospinal fluid collected via lumbar puncture are available in Europe; however, collecting cerebrospinal fluid is not only painful for the patient but can also cause other medical risks such as infection, so its clinical utility is limited. Protein biomarkers for Alzheimer's dementia using blood, such as the Aβ42 / Aβ40 ratio and items including Aβ42, phospho-Tau181, phospho-Tau217, and total-Tau, are being developed as diagnostic markers through ELISA and liquid-chromatography-mass spectrometry (LC-MS / MS). However, blood-based amyloid beta quantitative analysis has a disadvantage in that the dynamic range of the Aβ42 / Aβ40 ratio between amyloid-PET imaging-positive and negative patients is narrow, so errors in classifying beta-amyloid patients can occur with an allowable deviation of around 10% caused by batch effects, sample bias, etc. (Alzheimer's Dement. 2023 Apr;19(4):1393-1402. doi: 10.1002 / alz.12801). The problem to be solved

[0003] One objective of the present invention is to provide a method for obtaining protein quantitative analysis data using blood, selecting a patient group with a high risk of dementia conversion, and recommending a treatment candidate group suitable for anti-amyloid antibody drug therapy.

[0004] Another objective of the present invention is to provide a method, composition, diagnostic kit, or diagnostic device for diagnosing cognitive disorders (CD) by detecting specific proteins or gene biomarkers encoding the same in patients with cognitive disorders.

[0005] Another objective of the present invention is to provide a method, composition, diagnostic kit, or diagnostic device for predicting the risk of transition from cognitive disorders (CD) to dementia by detecting specific proteins or gene biomarkers encoding the same in patients with cognitive impairment.

[0006] However, the technical problems that the present invention aims to solve are not limited to those mentioned above, and other unmentioned problems will be clearly understood by those skilled in the art from the description below. means of solving the problem

[0007] Various embodiments of the present invention are described with reference to the drawings. In the following description, for a complete understanding of the present invention, various specific details, such as specific forms, compositions, and processes, are described. However, specific embodiments may be practiced without one or more of these specific details, or in combination with other known methods and forms. In other examples, known processes and manufacturing techniques are not described as specific details so as not to make the present invention unnecessary or obscure. Reference throughout this specification to one embodiment implies that a particular feature, form, composition, or characteristic described in association with the embodiment is included in one or more embodiments of the present invention. Accordingly, the circumstances of an embodiment expressed at various locations throughout this specification do not necessarily represent the same embodiment of the present invention. Additionally, a particular feature, form, composition, or characteristic may be combined in any suitable way in one or more embodiments.

[0009] In one embodiment of the present invention, a method is provided comprising: (a) centrifuging a blood sample of a subject to separate a plasma sample and a buffy coat; (b) analyzing a protein biomarker or a gene biomarker encoding the same from the plasma obtained from the above step; (c) determining the risk of transition from mild cognitive impairment (MCI) or cognitively unimpaired (CU) to Alzheimer's disease (AD) from the analysis data of the above step (b); and thereby diagnosing patients with early-stage dementia and selecting an optimal treatment candidate group for anti-amyloid antibody drug therapy.

[0010] The present invention relates to a method for providing a companion diagnostic composition for predicting the transition of mild cognitive impairment to Alzheimer's dementia using a protein biomarker and a gene biomarker encoding the same, and for selecting early-stage dementia patients who can expect the maximum therapeutic effect of an anti-amyloid therapeutic agent using the same.

[0011] More specifically, this relates to a protein quantitative analysis that predicts the transition from the mild cognitive impairment stage to Alzheimer's dementia up to 11 years in time. Through this, it can be used to select early dementia patients, that is, patients with mild cognitive impairment who are at high risk of transitioning to Alzheimer's dementia, for whom the most effective therapeutic effect of anti-amyloid treatment is predicted.

[0012] Additionally, a paper submitted by the inventors to Cells is incorporated herein by reference (Park MK, Ahn J, Kim YJ, Lee JW, Lee JC, Hwang SJ, Kim KC. Predicting Longitudinal Cognitive Decline and Alzheimer's Conversion in Mild Cognitive Impairment Patients Based on Plasma Biomarkers. Cells. 2024 Jun 22;13(13):1085. doi: 10.3390 / cells13131085. PMID: 38994939; PMCID: PMC11240497).

[0013] Currently, the primary goal of Alzheimer's dementia diagnostic technology focuses on securing minimally invasive, high-sensitivity quantitative analysis techniques. There is a demand for the development of technologies that achieve high concordance with diagnostic imaging results capable of identifying protein precipitation and entanglement of nerve bundles within brain tissue. Blood-based Alzheimer's diagnostic methods currently under development for minimally invasive diagnosis are often limited to amyloid or tau targets. These are protein-only modality diagnostic methods that cannot provide results linked to genomic, epigenomic, or transcriptomic diagnostic findings. In addition to amyloid and tau, there are various genetic and protein factors that influence mild cognitive impairment and Alzheimer's disease. The inventors of this invention have confirmed that multi-omics diagnostic technology capable of distinguishing between the influence of congenital and acquired factors exhibits higher concordance with diagnostic imaging results for Alzheimer's than protein-only omics technology.

[0014] In 2023, the U.S. FDA approved lecanemab, an antibody drug that binds to amyloid-beta profibril, as a disease-modifying therapy (DMT) for Alzheimer's dementia, and in July 2024, approved a second Alzheimer's dementia DMT (donanemab). The U.S. FDA restricted the indications for these antibody drugs to be prescribed to early-stage Alzheimer's patients, specifically those with amnestic mild cognitive impairment. To dramatically improve the therapeutic effects of these new antibody drugs, it is important to specifically select early-stage Alzheimer's patients, and in addition, treatment or intervention must be performed before the onset of Alzheimer's dementia symptoms. Accordingly, the present invention provides protein biomarkers that predict the transition from mild cognitive impairment to Alzheimer's dementia (MCI-to-AD conversion), which can be usefully applied to select and treat early-stage dementia patients—specifically, patients with mild cognitive impairment who are at high risk of transitioning to Alzheimer's dementia—where maximum therapeutic effects are predicted for anti-amyloid antibody drugs, i.e., clinical effects such as delaying or stopping the decline in cognitive function can be expected.

[0015] According to another embodiment of the present invention, the method comprises: (a) centrifuging a blood sample of a recipient to separate a plasma sample and a buffy coat; (b) purifying proteins or total RNA from the buffy coat obtained in step (a) and reverse transcribing them into single-stranded complementary DNA (cDNA); (c) analyzing protein biomarkers or gene biomarkers encoding the same from the plasma obtained in step (a); (d) analyzing at least one protein or gene expression biomarker encoding the same selected from the group consisting of the following using the protein or cDNA obtained in step (b): GFAP, NFL, pTau181, pTau217, Aβ40, and Aβ42; and (e) differentiating and diagnosing a patient with mild cognitive impairment from the analysis data of step (d). (f) a step of determining the risk of transition from mild cognitive impairment to Alzheimer's dementia from the analysis data of step (c) above; and a method for diagnosing early-stage dementia patients and selecting an optimal treatment candidate group for anti-amyloid antibody drug treatment through this may be provided.

[0016] Hereinafter, a diagnostic composition for diagnosing mild cognitive impairment using a gene expression biomarker according to the present invention and predicting the conversion of mild cognitive impairment to Alzheimer's dementia using a protein biomarker, and a method for identifying early-stage dementia patients who can expect the maximum therapeutic effect of an anti-amyloid therapeutic agent using the same will be described in detail.

[0017] The present invention includes a preparation for analyzing changes in gene expression and differences in protein concentration in blood according to one aspect of the invention.

[0018] Specifically, the preparation separates plasma and soft layer from the peripheral blood of a recipient, purifies protein or total RNA from the soft layer, reverse transcribes it into single-stranded complementary DNA, performs gene expression profiling through gene expression analysis, and simultaneously detects a protein biomarker or a gene biomarker encoding the same using a detection antibody conjugated to a paramagnetic bead coated with a target protein antibody from the plasma.

[0019] The composition for diagnosing cognitive impairment provided in the present invention may be one or more of the protein or the gene encoding it, or a combination thereof, and through this, it is possible to accurately diagnose cognitive impairment, specifically mild cognitive impairment (MCI), and predict the prognosis.

[0020] In one embodiment of the present invention, a composition for diagnosing cognitive disorders (CD) is provided, comprising a preparation that specifically detects any one of a group of proteins or genes encoding the same:

[0021] Glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), phosphorylated tau at residue 181 (pTau181), phosphorylated tau at residue 217 (pTau217), amyloid beta-42 (Aβ42) and amyloid beta-40 (Aβ40).

[0022] In another embodiment of the present invention, a composition for diagnosing cognitive impairment is provided, wherein the cognitive impairment is one or more selected from the group consisting of dementia, mild cognitive impairment (MCI), and pseudo-dementia.

[0023] In the present invention, the term “cognitive disorder” refers to a state in which memory, attention, language ability, visuospatial ability, and judgment are impaired. The degree of impairment varies from very mild to severe, and cases where cognitive impairment is severe enough to interfere with daily life or social life are referred to as dementia. On the other hand, cases in which cognitive function, particularly memory, is lower than that of the same age group but the ability to perform daily activities is preserved, and the condition is not yet severe enough to be called dementia, are referred to as mild cognitive impairment. This can be considered an intermediate stage between normal aging and dementia.

[0024] In the present invention, the term “Dementia” refers to a complex set of symptoms in which a brain that has once matured normally is damaged or destroyed by external factors, such as acquired trauma or disease, resulting in an overall decline in cognitive functions, such as intelligence, learning, and language, as well as higher mental functions. Dementia primarily occurs in old age and is a significant neurological disease, currently considered one of the four major causes of death following heart disease, cancer, and stroke. Dementia does not refer to a single disease in itself, but is a comprehensive term describing a state in which impaired cognitive functions, including memory, occur due to brain damage caused by various factors, making it impossible to maintain a previous level of daily life.

[0025] In this invention, the term “Mild Cognitive Impairment (MCI)” refers to the stage immediately preceding dementia. In the early stages of cognitive impairment, usually only the individual perceives the impairment, while those around them do not notice; however, as the symptoms progress further, it becomes noticeable to family members or close acquaintances. In the case of Mild Cognitive Impairment, the patient's cognitive impairment may become apparent to a spouse living together, but since there are no significant problems with daily life, family members living separately often do not notice at all; it is a stage that cannot yet be considered dementia. Mild Cognitive Impairment can manifest in various forms, similar to dementia. The first subtype is Amnestic MCI, which refers to cases where memory is impaired but daily living functions remain normal; this is the most frequent type. While approximately 1-2% of normal individuals progress to dementia annually, it is known that 10-15% of patients with Amnestic MCI progress to Alzheimer's disease dementia each year. Therefore, patients with Amnestic MCI require greater attention and care to prevent dementia. The protein biomarker provided in the present invention can predict with very high accuracy the likelihood that a patient with mild cognitive impairment with memory will transition to Alzheimer's dementia.

[0026] The clinical diagnostic criteria for amnestic mild cognitive impairment are as follows.

[0027] 1. Complaint of symptoms of memory loss (primarily presented by the patient or caregiver)

[0028] 2. When there is objective memory impairment on examination

[0029] 3. Functioning of daily living is normal or slightly impaired

[0030] 4. When not meeting the diagnostic criteria for dementia.

[0031] The second subtype is non-amnestic mild cognitive impairment (Non-amnestic MCI), which refers to cases where functional impairment occurs in areas other than memory, such as spatial orientation, visuospatial function, executive function, or language function. In such cases, it is necessary to differentiate between Alzheimer's disease and other underlying causes of dementia.

[0032] Determining the boundary between the decline in cognitive function that occurs as a normal aging process, mild cognitive impairment, and dementia is a difficult issue, and mild cognitive impairment is a syndrome that includes various clinical manifestations and various underlying diseases. Therefore, if you experience a significant decline in memory, or if other cognitive functions have weakened even if memory is fine, or if your personality has changed, or if your thinking or behavior has slowed down, or if others feel that you have changed, you need to get tested for dementia.

[0033] In the present invention, the term “pseudo-dementia” refers to a condition in which a person is not diagnosed with dementia but exhibits symptoms similar to dementia due to a decline in memory, usually exhibiting impaired mental function accompanied by a decline in memory due to depression, but without actual brain damage such as dementia.

[0034] In another embodiment of the present invention, a composition for diagnosing cognitive impairment is provided, wherein a preparation capable of specifically detecting the proteins or genes encoding them is one or more selected from the group consisting of antibodies, oligopeptides, ligands, PNA (peptide nucleic acid) and aptamers, primers, or probes that specifically bind to the biomarker.

[0035] In the present invention, the composition is intended to be applied to a biological sample isolated from a target individual, and the biological sample may include, but is not limited to, solid tissue samples, tissue culture media, liquid tissue samples, cells, or cell fragments. In addition, as non-limiting examples of biological samples, whole blood, leukocytes, peripheral blood mononuclear cells, buffy coat, plasma, serum, sputum, tears, mucus, nasal washes, nasal aspirate, breath, urine, semen, saliva, peritoneal washings, ascites, cystic fluid, meningeal fluid, amniotic fluid, glandular fluid, pancreatic fluid, lymph fluid, pleural fluid, nipple aspirate, bronchial aspirate, synovial fluid, joint aspirate It may include one or more selected from the group consisting of aspirate, organ secretions, cell, cell extract and cerebrospinal fluid, but is not limited thereto.

[0036] In the present invention, the term "intended individual" refers to an individual that has developed or is highly likely to develop a cognitive impairment, and may be a mammal including humans, and may be selected from the group consisting of, for example, humans, rats, mice, guinea pigs, hamsters, rabbits, monkeys, dogs, cats, cattle, horses, pigs, sheep, and goats, and preferably may be a human, but is not limited thereto.

[0037] When measuring the expression level of the biomarker according to the present invention from a biological sample isolated from the target individual in the present invention, the occurrence of or possibility of a disease can be confirmed very quickly and easily.

[0038] In the present invention, the term "diagnosis" refers to confirming the existence or characteristics of a pathological condition. For the purposes of the present invention, the diagnosis may be to predict the possibility of the onset, growth, progression, or metastasis of cognitive impairment.

[0039] In the present invention, the preparation for measuring the expression level of the proteins or genes encoding them may include one or more selected from the group consisting of antibodies, oligopeptides, ligands, PNA (peptide nucleic acid), and aptamers that specifically bind to the proteins or genes encoding them, but is not limited thereto.

[0040] In the present invention, the term "antibody" refers to a substance that specifically binds to an antigen and causes an antigen-antibody reaction. For the purposes of the present invention, an antibody means an antibody that specifically binds to the protein. The antibodies of the present invention include polyclonal antibodies, monoclonal antibodies, and recombinant antibodies. The antibodies can be easily manufactured using techniques widely known in the art. For example, polyclonal antibodies can be produced by a method widely known in the art that includes the process of injecting an antigen of the protein into an animal and collecting blood from the animal to obtain serum containing antibodies. Such polyclonal antibodies can be produced from any animal, such as a goat, rabbit, sheep, monkey, horse, pig, cattle, or dog. In addition, monoclonal antibodies may be prepared using the hybridoma method (see Kohler and Milstein (1976) European Journal of Immunology 6:511-519), which is widely known in the industry, or phage antibody library technology (see Clackson et al, Nature, 352:624-628, 1991; Marks et al, J. Mol. Biol., 222:58, 1-597, 1991). Antibodies prepared by the above methods may be separated and purified using methods such as gel electrophoresis, dialysis, salt precipitation, ion exchange chromatography, and affinity chromatography. Furthermore, the antibodies of the present invention comprise not only a complete form having two full-length light chains and two full-length heavy chains, but also functional fragments of the antibody molecule. A functional fragment of an antibody molecule refers to a fragment that possesses at least an antigen-binding function, and includes Fab, F(ab'), F(ab')2, and Fv.

[0041] In the present invention, the "oligopeptide" is a peptide composed of 2 to 20 amino acids and may include dipeptides, tripeptides, tetrapeptides, and pentapeptides, but is not limited thereto.

[0042] In the present invention, the "PNA (Peptide Nucleic Acid)" refers to an artificially synthesized polymer similar to DNA or RNA, which was first introduced in 1991 by Professors Nielsen, Egholm, Berg, and Buchardt of the University of Copenhagen, Denmark. While DNA has a phosphate-ribose sugar backbone, PNA has a repeating N-(2-aminoethyl)-glycine backbone connected by peptide bonds, which significantly increases its binding affinity and stability to DNA or RNA, and is therefore used in molecular biology, diagnostic analysis, and antisense therapy. PNA is disclosed in detail in the literature [Nielsen PE, Egholm M, Berg RH, Buchardt O (December 1991). "Sequence-selective recognition of DNA by strand displacement with a thymine-substituted polyamide". Science 254 (5037): 1497-1500].

[0043] In the present invention, the "aptamer" is an oligonucleotide or peptide molecule, and general information regarding aptamers is disclosed in detail in the literature [Bock LC et al., Nature 355(6360):5646(1992); Hoppe-Seyler F, Butz K "Peptide aptamers: powerful new tools for molecular medicine". J Mol Med. 78(8):42630(2000); Cohen BA, Colas P, Brent R. "An artificial cell-cycle inhibitor isolated from a combinatorial library". Proc Natl Acad Sci USA. 95(24): 142727(1998)].

[0044] In the present invention, the agent for measuring the expression level of the gene encoding the protein may include one or more selected from the group consisting of primers, probes, and antisense nucleotides that specifically bind to the gene encoding the protein, but is not limited thereto.

[0045] In the present invention, the "primer" is a fragment that recognizes a target gene sequence and includes a forward and reverse primer pair, but preferably is a primer pair that provides analysis results having specificity and sensitivity. High specificity can be conferred when the nucleic acid sequence of the primer is a sequence that is inconsistent with the non-target sequence present in the sample, so that it amplifies only the target gene sequence containing the complementary primer binding site and does not induce non-specific amplification.

[0046] In the present invention, the term "probe" refers to a substance capable of specifically binding to a target substance to be detected within a sample, and means a substance capable of specifically confirming the presence of the target substance within the sample through said binding. The type of probe is not limited to substances commonly used in the industry, but preferably may be PNA (peptide nucleic acid), LNA (locked nucleic acid), peptide, polypeptide, protein, RNA, or DNA, and most preferably PNA. More specifically, the probe may be a biomaterial derived from an organism or similar, or manufactured in vitro, and may be, for example, enzymes, proteins, antibodies, microorganisms, animal and plant cells and organs, nerve cells, DNA, and RNA; DNA may include cDNA, genomic DNA, and oligonucleotides; RNA may include genomic RNA, mRNA, and oligonucleotides; and examples of proteins may include antibodies, antigens, enzymes, peptides, etc.

[0047] In the present invention, "LNA (Locked nucleic acids)" refers to nucleic acid analogs containing a 2'-O, 4'-C methylene bridge [J Weiler, J Hunziker and J Hall Gene Therapy (2006) 13, 496.502]. LNA nucleosides contain common nucleic acid bases of DNA and RNA and can form base pairs according to the Watson-Crick base pairing rule. However, due to the 'locking' of the molecule caused by the methylene bridge, LNAs are unable to form an ideal shape in Watson-Crick bonding. When LNAs are included in DNA or RNA oligonucleotides, LNAs can pair more quickly with complementary nucleotide chains, thereby increasing the stability of the double helix.

[0048] In the present invention, "antisense" refers to an oligomer having a backbone between nucleotide base sequences and subunits, wherein the antisense oligomer hybridizes with a target sequence within RNA by Watson-Crick base pairing, thereby allowing the formation of a mRNA and RNA:oligomer heterodimer within the target sequence. The oligomer may have exact sequence complementarity or approximate complementarity with respect to the target sequence.

[0049] In one embodiment of the present invention, a kit for diagnosing cognitive impairment is provided, comprising the above composition.

[0050] In the present invention, the "kit" refers to a tool capable of evaluating the expression level of a biomarker by labeling a probe or antibody that specifically binds to a biomarker component with a detectable label. It includes not only direct labeling of a detectable substance related to a probe or antibody through reaction with a substrate, but also indirect labeling in which a label that develops color through reactivity with another directly labeled reagent is conjugated. It may include a color-developing substrate solution, washing solution, and other solutions that react with the label for color development, and may be manufactured to include the reagent components used. In the present invention, the kit may be a kit containing essential elements necessary for performing RT-PCR, and in addition to specific primer pairs for the marker gene, it may include test tubes, reaction buffer, deoxyribonucleotides (dNTPs), Taq polymerase, reverse transcriptase, DNase, RNase inhibitor, sterile water, etc. Furthermore, the kit may be a kit for detecting genes for the diagnosis of cognitive impairment that includes essential elements necessary for performing DNA chip analysis. A DNA chip kit comprises a substrate to which cDNA corresponding to a gene or a fragment thereof is attached as a probe, and the substrate may comprise cDNA corresponding to a quantitative control gene or a fragment thereof. The kit of the present invention is not limited thereto, provided that it is known in the art.

[0051] In the present invention, the kit may be an RT-PCR kit, a DNA chip kit, an ELISA kit, a protein chip kit, a rapid kit, or an MRM (Multiple reaction monitoring) kit.

[0052] The kit of the present invention may further include one or more other component compositions, solutions, or devices suitable for the analysis method. For example, the kit of the present invention may further include essential elements necessary to perform a reverse transcription polymerase chain reaction. The reverse transcription polymerase chain reaction kit includes a primer pair specific to a gene encoding a marker protein. The primer is a nucleotide having a sequence specific to the nucleic acid sequence of the gene and may have a length of about 7 bp to 50 bp, more preferably about 10 bp to 30 bp. It may also include a primer specific to the nucleic acid sequence of a control gene. Furthermore, the reverse transcription polymerase chain reaction kit may include a test tube or other suitable container, a reaction buffer (with varying pH and magnesium concentration), deoxynucleotides (dNTPs), enzymes such as Taq-polymerase and reverse transcriptase, DNase, RNase inhibitor DEPC-water, sterile water, etc.

[0053] In addition, the diagnostic kit for cognitive impairment according to the present invention may include essential elements necessary for performing DNA chip operations. The DNA chip kit may include a substrate to which cDNA or oligonucleotides corresponding to a gene or a fragment thereof are attached, and reagents, preparations, enzymes, etc., for producing fluorescently labeled probes. Additionally, the substrate may include cDNA or oligonucleotides corresponding to a control gene or a fragment thereof.

[0054] In addition, the diagnostic kit for cognitive impairment according to the present invention may include essential elements necessary for performing ELISA. The ELISA kit includes an antibody specific to the protein. The antibody is an antibody that has high specificity and affinity for the marker protein and has little cross-reactivity with other proteins, and is a monoclonal antibody, a polyclonal antibody, or a recombinant antibody. Additionally, the ELISA kit may include an antibody specific to a control protein. Furthermore, the ELISA kit may include reagents capable of detecting the bound antibody, such as a labeled secondary antibody, chromophores, an enzyme (e.g., conjugated with the antibody) and its substrate, or other substances capable of binding to the antibody.

[0055] In the present invention, the immobilizer for the antigen-antibody binding reaction may be a nitrocellulose membrane, a PVDF membrane, a well plate synthesized from polyvinyl resin or polystyrene resin, a glass slide glass, etc., but is not limited thereto.

[0056] In addition, in the present invention, the label of the secondary antibody is preferably a conventional chromogenic agent that produces a color reaction, and labels such as fluorescein and dyes such as HRP (horseradish peroxidase), alkaline phosphatase, colloid gold, FITC (poly L-lysine-fluorescein isothiocyanate), and RITC (rhodamine-B-isothiocyanate) may be used, but are not limited thereto.

[0057] In addition, in the present invention, it is preferable to use a chromogenic substrate to induce color development depending on the label that performs the color reaction, and TMB (3,3',5,5'-tetramethylbezidine), ABTS [2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)], OPD (o-phenylenediamine), etc. may be used. At this time, it is more preferable that the chromogenic substrate be provided in a state dissolved in a buffer solution (0.1 M NaAc, pH 5.5). A chromogenic substrate such as TMB is degraded by HRP used as a label for the secondary antibody conjugate to produce a chromogenic precipitate, and the presence or absence of the marker proteins or the genes encoding them is detected by visually confirming the degree of precipitation of this chromogenic precipitate.

[0058] In the present invention, the washing solution preferably comprises a phosphate buffer solution, NaCl, and Tween 20, and a buffer solution (PBST) composed of 0.02 M phosphate buffer solution, 0.13 M NaCl, and 0.05% Tween 20 is more preferably used. After the antigen-antibody binding reaction, a secondary antibody is reacted with the antigen-antibody conjugate, and then an appropriate amount of the washing solution is added to the immobilizer to wash 3 to 6 times. A sulfuric acid solution (H2SO4) may preferably be used as the reaction stopping solution.

[0059] In the present invention, the measurement of the expression level of the protein or biomarker may be performed by protein chip analysis, immunoassay, ligand binding assay, MALDI-TOF (Matrix Assisted Laser Desorption / Ionization Time of Flight Mass Spectrometry) analysis, SELDI-TOF (Surface Enhanced Laser Desorption / Ionization Time of Flight Mass Spectrometry) analysis, radioimmunoassay, radioimmunodiffusion, Ouchteroni immunodiffusion, Rocket immunoelectrophoresis, tissue immunostaining, complement fixation assay, two-dimensional electrophoresis analysis, liquid chromatography-mass spectrometry (LC-MS), LC-MS / MS (liquid chromatography-mass spectrometry / mass spectrometry), Western blotting, or ELISA (enzyme-linked immunosorbent assay).

[0060] In addition, in the present invention, the measurement of the expression level of the protein or the gene biomarker encoding it may be performed by a multiple reaction monitoring (MRM) method.

[0061] In the present invention, for the multiple reaction monitoring method, the internal standard substance may be a synthetic peptide in which a specific amino acid constituting the target peptide is substituted with an isotope, or E. coli beta-galactosidase.

[0062] In the present invention, a preparation for measuring the expression level of a gene encoding the protein or biomarker may include one or more selected from the group consisting of a primer, a probe, and an antisense nucleotide that specifically binds to the gene encoding the protein.

[0063] In the present invention, the measurement of the expression level of the gene encoding the protein or biomarker may be performed by reverse transcription polymerase chain reaction (RT-PCR), competitive reverse transcription polymerase chain reaction (Competitive RT-PCR), real-time reverse transcription polymerase chain reaction (Real-time RT-PCR), RNase protection assay (RPA), Northern blotting, or DNA chip.

[0064] In one embodiment of the present invention, a method for providing information for diagnosing cognitive impairment is provided, comprising: (a) detecting any one of a group of proteins or genes encoding the same, with respect to a biological sample obtained from a target individual; GFAP, NFL, pTau181, pTau217, Aβ40, and Aβ42; and (b) determining that there is a high probability of cognitive impairment if the levels of the detected proteins or genes encoding the same are higher than those of a normal control group, which is a cognitively unimpaired (CU) group.

[0065] In another embodiment of the present invention, if the mutation, copy number change, expression level, or gene fusion level of the biomarker for diagnosing cognitive impairment according to the above is higher than that of the control group, it can be diagnosed as cognitive impairment or predicted to have a poor prognosis for cognitive impairment.

[0066] In the present invention, the term "control group" may refer to the average or median value of the expression level of the corresponding biomarker protein or the gene encoding said protein in a healthy normal control group, or the average or median value of the expression level of the corresponding marker protein or the gene encoding said protein in a biological sample derived from a patient with a cognitive impairment disease, preferably a patient with a cognitive impairment other than mild cognitive impairment, but is not limited thereto.

[0067] In the method of the present invention, predicting that the cognitive impairment has developed or is highly likely to develop includes not only predicting the possibility of the onset, growth, or progression of the cognitive impairment, but also predicting that the disease that has developed or is suspected to have developed in the target individual is mild cognitive impairment by distinguishing it from other diseases, particularly other cognitive impairment diseases.

[0068] In the present invention, "prognosis" refers to the act of predicting in advance the course of a disease and the outcome of death or survival. The aforementioned prognosis or prognostic diagnosis may be interpreted to mean any act of predicting the course of a disease before or after treatment by comprehensively considering the patient's condition, as the course of the disease may vary depending on the patient's physiological or environmental state. For the purposes of the present invention, the aforementioned prognosis may be interpreted as the act of determining whether a low survival rate or poor responsiveness to treatment is predicted after the onset of cognitive impairment.

[0069] In addition, in the present invention, "diagnosis" means confirming the existence or characteristics of a pathological state, and in the present invention, "prognosis" means the act of predicting in advance the course of a disease and the outcome of death or survival, so they are clearly distinguished. More specifically, the diagnosis of cognitive impairment means confirming whether a patient is currently suffering from a cognitive impairment disease, and the prognosis of cognitive impairment means the act of predicting in advance the course of a patient suffering from a cognitive impairment disease and the outcome of death or survival, and more specifically, it means predicting or estimating the recurrence-free survival period and the overall survival period.

[0070] In one embodiment of the present invention, a diagnostic device for cognitive impairment is provided, comprising: (a) a step of detecting a group of proteins or genes encoding them, consisting of the following, for a biological sample obtained from a target individual; GFAP, NFL, pTau181, pTau217, Aβ40, and Aβ42; and (b) an output unit that outputs that there is a high probability of cognitive impairment when the levels of the detected proteins or genes encoding them are higher than those of a normal control group, which is a cognitively unimpaired (CU) group.

[0071] In one embodiment of the present invention, a diagnostic composition for predicting the risk of transition from a cognitive impairment stage to a dementia stage is provided, comprising a preparation that specifically detects any one of the following group of proteins or genes encoding them: neurofilament light chain (NFL), glial fibrillary acidic protein (GFAP), amyloid beta-42 (Aβ42), amyloid beta-40 (Aβ40), phosphorylated tau at residue 181 (pTau181), and phosphorylated tau at residue 217 (pTau217).

[0072] In the present invention, the term “predicting the risk of transition from the cognitive impairment stage to the dementia stage” refers to distinguishing between patients with mild cognitive impairment who are at high risk of progressing to dementia, specifically Alzheimer’s dementia, and patients who are not, and predicting the possibility or risk of a patient with mild cognitive impairment transitioning to dementia, specifically Alzheimer’s dementia.

[0073] In nature, it is difficult to distinguish between mild cognitive impairment and normal aging because patients and caregivers often misunderstand the subtle symptoms of aging. Although anti-amyloid beta (Aβ) therapies exist that can improve clinical cognitive decline in early Alzheimer's, these drugs are known to only delay disease progression; while the removal of Aβ plaques is beneficial, they are not known to cure Alzheimer's. Consequently, early detection of patients with mild cognitive impairment at high risk of transitioning to Alzheimer's is essential for optimizing therapeutic interventions, particularly in the context of anti-Aβ therapy.

[0074] In another embodiment of the present invention, a diagnostic composition for predicting the risk of transitioning from a cognitive impairment stage to a dementia stage is provided, wherein the proteins or genes encoding them further comprise ApoE ε4, a pTau217 / Aβ42 ratio, or a pTau181 / Aβ42 ratio.

[0075] In another embodiment of the present invention, a diagnostic composition for predicting the risk of transition from a cognitive impairment stage to a dementia stage is provided, wherein the preparation capable of specifically detecting the proteins or genes encoding them is one or more selected from the group consisting of antibodies, oligopeptides, ligands, PNA (peptide nucleic acid) and aptamers, primers, or probes that specifically bind to the biomarker.

[0076] In another embodiment of the present invention, the optimal cut-off of the biomarkers may be 100 pg / mL or more, 125 pg / mL or more, 150 pg / mL or more, 175 pg / mL or more, 180 pg / mL or more, 190 pg / mL or more, or 196 pg / mL or more for the GFAP biomarker; 10.0 pg / mL or more, 15.0 pg / mL or more, 17.0 pg / mL or more, 20.0 pg / mL or more, 21.0 pg / mL or more, or 23.0 pg / mL or more for the NFL biomarker; and 10.0 pg / mL or more, 13.0 pg / mL or more, 15.0 pg / mL or more, 17.0 pg / mL or more, 20.0 pg / mL or more, or 21.0 The present invention provides a diagnostic composition, a method for providing information for diagnosis, a diagnostic kit, or a diagnostic device for predicting the risk of transition from a cognitive impairment stage to a dementia stage, wherein the pTau217 biomarker may be 0.010 pg / mL or higher, 0.020 pg / mL or higher, 0.030 pg / mL or higher, 0.040 pg / mL or higher, 0.050 pg / mL or higher, or 0.057 pg / mL or higher, the pTau181 / Aβ42 ratio biomarker may be 2.00 or higher, 2.30 or higher, 2.50 or higher, 2.80 or higher, 3.00 or higher, 3.30 or higher, 3.50 or higher, or 3.73 or higher, and the pTau217 / Aβ42 ratio biomarker may be 0.01 or higher, 0.015 or higher, or 0.02 or higher. Although the combination of the above biomarkers can effectively predict Alzheimer's dementia transition, Alzheimer's dementia transition can be predicted more accurately and effectively by setting individual cut-off values ​​for the above biomarkers.

[0077] In another embodiment of the present invention, a diagnostic composition is provided for predicting the risk of transition from a cognitive impairment stage to a dementia stage, wherein the “dementia” is one or more selected from the group consisting of primary dementia, secondary dementia, and reversible dementia.

[0078] In another embodiment of the present invention, a diagnostic composition is provided for predicting the risk of transitioning from a cognitive impairment stage to a dementia stage, wherein the primary dementia is Alzheimer's dementia.

[0079] In another embodiment of the present invention, a diagnostic kit is provided that predicts the risk of transition from a cognitive impairment stage to a dementia stage, comprising the above composition.

[0080] In another embodiment of the present invention, a diagnostic kit for predicting the risk of transition from a cognitive impairment stage to a dementia stage is provided, wherein the kit is an RT-PCR kit, a DNA chip kit, an ELISA kit, a protein chip kit, a rapid kit, or an MRM (Multiple reaction monitoring) kit.

[0081] In one embodiment of the present invention, (a) detecting a group of proteins or a gene encoding therefrom, consisting of the following, with respect to a biological sample obtained from a target individual; neurofilament light chain (NFL), glial fibrillary acidic protein (GFAP), amyloid beta-42 (Aβ42), amyloid beta-40 (Aβ40), phosphorylated tau at residue 181 (pTau181), phosphorylated tau at residue 217 (pTau217); (b) A method for providing information for diagnosing the risk of transition from cognitive impairment to dementia, wherein if the expression level of the detected proteins or genes encoding them is higher than that of the normal control group, the cognitively unimpaired (CU) group, it is determined that there is a high possibility of transition from the cognitive impairment stage to dementia.

[0082] In one embodiment of the present invention, (a) detecting a group of proteins or genes encoding the following in a biological sample obtained from a target individual; neurofilament light chain (NFL), glial fibrillary acidic protein (GFAP), amyloid beta-42 (Aβ42), amyloid beta-40 (Aβ40), phosphorylated tau at residue 181 (pTau181), phosphorylated tau at residue 217 (pTau217); (b) Provides a method, device, or kit for selecting a group of patients with cognitive impairment who are at high risk of transitioning to dementia, in which the levels of the detected proteins or genes encoding them are higher than those of a normal control group, a cognitively unimpaired (CU) group, and are judged to have a high likelihood of transitioning to dementia in the cognitive impairment stage.

[0083] In another embodiment of the present invention, a method, device, or kit for screening a group of patients with cognitive impairment who are at high risk of transitioning to dementia is provided, wherein the proteins or genes encoding them further comprise ApoE ε4, a pTau217 / Aβ42 ratio, or a pTau181 / Aβ42 ratio.

[0084] The aforementioned method for identifying patient groups at high risk of transitioning to dementia is unrelated to "clinical judgment," which refers to the mental activity of medical professionals assessing diseases or health conditions based on medical knowledge or experience. In other words, it is not intended to provide a method for diagnosing patients with specific diseases, but merely to "predict" which patients already diagnosed with cognitive impairment are at high risk of transitioning to Alzheimer's disease in the future.

[0085] Furthermore, it is unrelated to medical practice, which refers to the act of diagnosing human diseases based on medical knowledge by medical professionals or those acting under their instructions. In other words, it is clear that the purpose is not to diagnose patients with a "specific disease." Specifically, it is not intended to diagnose patients with dementia or patients with cognitive impairment; rather, it is merely to "predict" which patients already diagnosed with cognitive impairment are at high risk of transitioning to Alzheimer's disease in the future.

[0086] Specifically, according to Examination Standard 3115, “a method of predicting cancer or providing information for cancer prediction by performing an artificial intelligence algorithm in a medical device” is specified as an invention applicable to industry as it does not involve clinical judgment. A person skilled in the art will clearly understand that the method of selecting a patient group at high risk of conversion to dementia according to the present invention does not involve clinical judgment, as it is intended to simply “predict” which patients are at high risk of future conversion to Alzheimer’s disease among patients already diagnosed with cognitive impairment.

[0087] In one embodiment of the present invention, (a) detecting a group of proteins or genes encoding the following in a biological sample obtained from a target individual; neurofilament light chain (NFL), glial fibrillary acidic protein (GFAP), amyloid beta-42 (Aβ42), amyloid beta-40 (Aβ40), phosphorylated tau at residue 181 (pTau181), phosphorylated tau at residue 217 (pTau217); (b) Provides a method, device, or kit for determining a patient group suitable for anti-amyloid drug treatment, wherein the levels of the detected proteins or genes encoding them are higher than those of a normal control group, a cognitively unimpaired (CU) group.

[0088] The method of determining or selecting patient groups suitable for the aforementioned anti-amyloid drug treatment is unrelated to "clinical judgment," which refers to the mental activity of medical professionals assessing diseases or health conditions based on medical knowledge or experience. In other words, it is merely a "prediction" that anti-amyloid drug treatment will be effective from a preventive perspective, given that patients with mild cognitive impairment are highly likely to progress to Alzheimer's dementia.

[0089] Amyloid-beta (Amyloid-β) and Tau proteins are cited as the primary causes of the aforementioned Alzheimer's dementia. This is because patients with Alzheimer's disease characteristically exhibit lesions in brain tissue examinations, such as senile plaques formed by the deposition of amyloid-beta protein or neurofibrillary tangles formed by the hyperphosphorylation of Tau protein. In particular, senile plaques caused by amyloid-beta deposition are known to primarily accumulate in the temporal and parietal lobes, which are responsible for cognitive functions such as memory and language, thereby inducing typical dementia symptoms like memory decline. This mechanism of Alzheimer's disease development is known as the "amyloid cascade hypothesis." This hypothesis posits that when amyloid-beta protein is abnormally overproduced and fails to degrade, it accumulates in nerve cells in the form of plaques called senile plaques, inducing neurotoxicity and leading to neurodegeneration. Recently, anti-amyloid dementia treatments targeting this amyloid-beta mechanism have been attracting attention in the field of development. Anti-amyloid beta dementia treatments work by reducing plaques accumulated in the brain through anti-amyloid therapy, which decreases the production and aggregation of amyloid beta proteins that can cause neurotoxicity and increases their removal, thereby delaying the progression of Alzheimer's-type dementia. In particular, clinical trials for anti-amyloid beta dementia treatments currently under development are being conducted on patients whose dementia has not yet progressed significantly, such as those with mild cognitive impairment or early-stage dementia. This implies that in order for patients to better benefit from treatment when anti-amyloid beta dementia treatments become available in the future, it is necessary to provide aggressive treatment from an early stage to maintain dementia patients in a relatively healthy, early-stage state. Examples of the aforementioned anti-amyloid drugs include anti-amyloid antibody drugs such as aducanumab, recanemab, and donanemab.

[0090] In one embodiment of the present invention, (a) a measuring unit for detecting a group of proteins or genes encoding the following, with respect to a biological sample obtained from a target individual; neurofilament light chain (NFL), glial fibrillary acidic protein (GFAP), amyloid beta-42 (Aβ42), amyloid beta-40 (Aβ40), phosphorylated tau at residue 181 (pTau181), phosphorylated tau at residue 217 (pTau217); (b) a detection unit for outputting the possibility of transitioning from a cognitive impairment stage to dementia when the levels of the detected proteins or genes encoding the same are higher than those of a normal control group, which is a cognitively unimpaired (CU) group. A device is provided that outputs the risk of transition from the cognitive impairment stage to the dementia transition stage, including

[0091] In one embodiment of the present invention, (a) a measuring unit for detecting a group of proteins or genes encoding them, consisting of the following, with respect to a biological sample obtained from a target individual; neurofilament light chain (NFL), glial fibrillary acidic protein (GFAP), amyloid beta-42 (Aβ42), amyloid beta-40 (Aβ40), phosphorylated tau at residue 181 (pTau181), phosphorylated tau at residue 217 (pTau217); (b) an output unit for outputting that a patient group suitable for anti-amyloid drug treatment is a cognitively unimpaired (CU) group, which is a normal control group, when the expression level of the detected proteins or genes encoding them is higher than that of the normal control group. A device for determining a patient group suitable for anti-amyloid drug treatment, including

[0092] In another embodiment of the present invention, a device for determining a patient group suitable for anti-amyloid drug treatment is provided, wherein the biomarker further comprises one of the group consisting of ApoE ε4, pTau217 / Aβ42 ratio, and pTau181 / Aβ42 ratio. Effects of the invention

[0093] The present invention provides protein biomarkers that predict the transition from mild cognitive impairment or normal cognitive function stages to Alzheimer's dementia.

[0094] In addition, the diagnostic composition according to the present invention, which analyzes changes in protein concentration down to the picogram level, can provide grounds for selecting early-stage dementia patients who are expected to have the maximum therapeutic effect with anti-amyloid antibody drugs, that is, clinical effects such as delaying or stopping the decline in cognitive function.

[0095] Furthermore, the diagnostic composition according to the present invention can be utilized as an indicator for monitoring the therapeutic effect and evaluating the prognosis of a minimally invasive treatment by presenting data on changes in protein concentration from blood during the treatment process for Alzheimer's dementia. Brief explanation of the drawing

[0096] Figure 1 shows the results of a linear mixed effects model for the Mini-Mental State Exam (MMSE) of six protein biomarkers. Figure 2 shows the results of a linear mixed effects model for memory scores of six types of protein biomarkers. Figure 3 shows the results of a linear mixed effects model for the executive function scores of six types of protein biomarkers. Figure 4 shows the results of the Cox proportional hazards analysis of protein biomarkers GFAP, NFL, pTau181, and pTau217. Specific details for implementing the invention

[0097] The present invention will be described in more detail below through examples. These examples are intended solely to explain the present invention more specifically, and it will be obvious to those skilled in the art that the scope of the present invention is not limited by these examples according to the gist of the invention.

[0099] [Example]

[0100] [Example 1] Development of a Prediction Model for Alzheimer's Dementia Transition

[0101] [Example 1-1] Data acquisition for the development of a predictive model for the transition to Alzheimer's dementia

[0102] To develop a predictive model, protein data obtained through quantitative analysis from blood samples collected at baseline from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort were used. The dataset, obtained from the ADNI website (https: / / ida.loni.usc.edu / ), consisted of a total of 215 subjects: a non-converted Alzheimer's dementia group (n=191) and a converted Alzheimer's dementia group (n=24) (see Table 1). Table 1 below shows the baseline statistical values ​​of independent variables according to whether or not the individual converted to Alzheimer's dementia; the non-converted Alzheimer's dementia group includes subjects with normal cognitive function or mild cognitive impairment.

[0103] Alzheimer's Alzheimer's p -value * 　 Non-conversion conversion (Non-converters) (AD converters) (n=191) (n=24) years 69.8 [66.3;74.1] 74.5 [68.6;78.6] 0.041 gender 0.497 - female 106 (55.5%) 11 (45.8%) - Male 85 (44.5%) 13 (54.2%) Education period (years) 16.0 [14.5;18.0] 16.0 [14.5;18.0] 0.572 ApoE ε4 0.032 - Non-existence 129 (67.5%) 10 (41.7%) - existence 62 (32.5%) 14 (58.3%) Aa40 (pg / mL) 85.0 [75.1;104.0] 97.5[84.0;112.0] 0.08 Aa42 (pg / mL) 5.5 [4.7;6.7] 5.4 [4.8;6.3] 0.807 GFAP(pg / mL) 115.0 [82.7;153.0] 196.0 [130.0;271.0] <0.001 NFL(pg / mL) 16.1 [12.0;20.3] 25.8 [15.1;33.0] <0.001 pTau181(pg / mL) 16.6 [11.5;21.0] 28.2 [24.2;31.7] <0.001 pTau217(pg / mL) 0.3 [0.2;0.4] 0.8 [0.5;1.0] <0.001 MMSE 29.0 [28.0;30.0] 27.0 [26.0;29.0] <0.001 memory 1.1 [0.5;1.5] -0.0 [-0.4;0.7] <0.001 Executive function 0.9 [0.3;1.4] 0.1 [-0.4;0.6] <0.001 Language skills 0.8 [0.3;1.3] 0.1 [-0.5;0.5] <0.001 spatiotemporal function 0.7 [-0.1;0.7] -0.1 [-0.9;0.7] <0.01

[0104] Fisher's test was performed on the gender and ApoE variables, while the Wilcoxon rank sum test was performed on the other variables. Results were presented as the median [interquartile range] or as a number (%).

[0106] Amyloid beta 40 (Aβ40) is the most commonly produced form of amyloid beta of various lengths formed by the cleavage of amyloid precursor protein (APP) by the secretase enzyme, and it is highly soluble. Amyloid beta 42 (Aβ42) is a form of amyloid beta with a length of 42 amino acids produced by the cleavage of amyloid precursor protein; compared to Aβ40, it is more hydrophobic and aggregate-prone, and is more actively involved in plaque formation and is known as a major protein involved in the pathology of Alzheimer's disease. GFAP (Glial Fibrillary Acidic Protein) is an astrocyte-specific protein; as Alzheimer's pathological changes progress, inflammatory responses and glial cell activity increase in the brain, and since GFAP levels rise during this process, it was considered as an indicator of brain inflammation. NFL (Neurofilament Light Chain) is a light chain protein of neurofilaments that constitute the axons of neurons; it increases when axonal damage or neurodegenerative changes occur. It was considered as an indicator reflecting the rate of progression of overall brain neurological damage. pTau181 (Phosphorylated Tau at Threonine Residue 181) is known as an indicator of Alzheimer's dementia-specific taupathy, and pTau217 (Phosphorylated Tau at Threonine Residue 217) more sensitively reflects the interaction between amyloid beta and hyperphosphorylated tau, which is a key factor in Alzheimer's dementia pathology; therefore, we intended to evaluate these biomarkers as biomarkers that predict the risk of conversion to Alzheimer's dementia.

[0108] [Example 1-2] Analysis of the Predictive Power of Biomarkers on Cognitive Function Decline

[0109] Cognitive function test data were collected from the same specimens for up to 11 years at 6- or 12-month intervals starting from baseline. The predictive performance of biomarkers regarding cognitive decline was evaluated using the Mini-Mental State Exam (MMSE), Memory, and Executive Function as cognitive function test indices. A linear mixed effects model was used to assess whether the six plasma biomarkers had predictive power regarding cognitive decline over a follow-up period of up to 11 years (see Table 2 and Figures 1 to 3).

[0110] Cognitive function indicators Biomarkers Beta coefficient Standard error t statistic p value MMSE Aβ40×time -0.065 0.096 -0.678 0.498 Aβ42×time -0.031 0.089 -0.341 0.733 GFAP×time -0.236 0.097 -2.438 0.015 NFL×time -0.297 0.098 -3.034 0.003 pTau181×time -0.405 0.089 -4.521 <0.01 pTau217×time -0.323 0.085 -3.765 <0.01 memory Aβ40×time -0.032 0.024 -1.346 0.179 Aβ42×time 0.002 0.022 0.089 0.928 GFAP×time -0.109 0.022 -4.833 <0.01 NFL×time -0.092 0.023 -3.978 <0.01 pTau181×time -0.094 0.021 -4.373 <0.01 pTau217×time -0.089 0.021 -4.327 <0.01 Executive function Aβ40×time -0.043 0.023 -1.806 0.072 Aβ42×time -0.006 0.022 -0.255 0.799 GFAP×time -0.104 0.021 -4.868 <0.01 NFL×time -0.102 0.021 -4.874 <0.01 pTau181×time -0.062 0.02 -3.018 0.003 　 pTau217×time -0.1 0.019 -5.027 <0.01

[0112] Linear mixed model analysis is a mixed model that considers both fixed effects of independent variables and random effects between individuals, providing a robust framework for longitudinal data analysis. It is a suitable analytical model for handling longitudinal repeated measures because it can account for covariance structures arising from data that are not perfectly aligned or are imbalanced at repeated measurement points. In this invention, a linear mixed model was applied using the lme4 package of R software to model the longitudinal decline in MMSE, memory, and executive function. Fixed effects included baseline plasma protein biomarker levels (divided into territories), time (number of years elapsed from baseline), and the interaction between protein biomarker levels and time. A random intercept was included to reflect differences in baseline cognitive function between individuals, and a random slope for time was considered to capture differences in trends of cognitive change among individuals during the study period. The dependent variables were neuropsychological cognitive function scores such as MMSE, memory, or executive function, and plasma biomarker levels, time, and their interactions were included as predictors. Age, sex, years of education, and ApoE ε4 possession were included as covariates in the model.

[0113] Meanwhile, the Mini-Mental State Examination (MMSE) is an overall cognitive assessment tool consisting of a total of 30 items evaluating domains such as orientation, concentration, attention, verbal learning (excluding delayed recall), naming, and visuospatial construction. The memory score was constructed based on various word lists from the Rey auditory verbal learning test and the cognitive sub-items of the Alzheimer's Disease Assessment Scale (ADAS-Cog), the 3-word recall items (ball, flag, tree) from the MMSE, and logical memory scores (immediate recall, delayed recall) (Brain Imaging Behav. 2012, 6:517-527). The executive function scores included the category fluency test for animals and vegetables, the digit span test (parts A and B), digit span backwards, and the digit-symbol substitution test of the Wechsler adult intelligence scale-revised, and also included five clock drawing items (circle, symbol, number, clock hands, time).

[0115] As a result, it was confirmed that protein biomarkers GFAP, NFL, pTau181, and pTau217 can effectively explain the longitudinal decline in cognitive function with negative beta coefficients in all indicators of MMSE, memory, and executive function in linear mixed model analysis, and that the significance level of their t-statistics is excellent (see Table 2 and Figures 1 to 3). In contrast, it was confirmed that although the beta coefficients of Aβ40 and Aβ42 proteins showed a negative sign, the t-statistics were small and not significant.

[0116] Meanwhile, regarding language function indicators, the GFAP protein indicator was able to significantly explain their longitudinal decline, but GFAP as a single biomarker was insufficient to expect desirable clinical utility, and no significant biomarker was identified for spatiotemporal function indicators.

[0118] [Examples 1-3] Assessment of Risk of Transition to Alzheimer's Dementia

[0119] Through the above Examples 1-2, the predictive performance of protein biomarkers GFAP, NFL, pTau181, and pTau217 regarding the longitudinal decline of cognitive function (MMSE, memory, and executive function) was confirmed. It was evaluated using a Cox proportional hazards model whether these protein biomarkers could differentiate the risk of conversion to Alzheimer's dementia in groups with normal cognitive function or mild cognitive impairment.

[0120] To analyze whether protein biomarkers GFAP, NFL, pTau181, pTau217, Aβ40, and Aβ42 are significantly associated with transition to Alzheimer's dementia, a total of 215 participants in the ADNI cohort were tracked for up to 11 years to determine if they transitioned to Alzheimer's dementia; of these, 24 participants transitioned to Alzheimer's dementia. The baseline event was defined as a diagnosis of normal cognitive function or mild cognitive impairment, and the endpoint of observation was set as the time of transition to Alzheimer's dementia. For participants who transitioned to Alzheimer's dementia, survival time was defined as the period from the baseline assessment to the diagnosis of Alzheimer's dementia. For participants who did not transition, data were right-censored at the final follow-up, and survival time was set at the final follow-up time.

[0122] Cox proportional hazards analysis including various covariates (age, sex, years of education, ApoE ε4 allele) was performed using the survival and survminer packages of R software and IBM SPSS version 27. It was confirmed that the risk of transition to Alzheimer's dementia increased statistically significantly when plasma protein biomarker levels at baseline corresponded to the highest tertile (see Table 3 and Figure 4).

[0123] In contrast, most cohort participants in the low or middle troughs of protein levels maintained a relatively stable non-converter status to Alzheimer's dementia until the final follow-up. On the other hand, participants in the highest trough group showed a faster rate of conversion to Alzheimer's dementia (see Figure 4).

[0124] Biomarkers Beta coefficient Standard error z statistic HR 95% confidence interval p-value Aβ40 0.240817 0.166586 1.445605 1.27 0.92-1.76 0.148 Aβ42 0.111224 0.171235 0.649539 1.12 0.80-1.56 0.516 GFAP 0.999725 0.212428 4.706189 2.72 1.79-4.12 <0.001 NFL 0.94708 0.20847 4.543007 2.58 1.71-3.88 <0.001 pTau181 1.344853 0.249823 5.383214 3.84 2.35-6.26 <0.001 pTau217 1.349061 0.238007 5.668168 3.85 2.42-6.14 <0.001

[0127] [Examples 1-4] Development of a Prediction Model for the Risk of Transition to Alzheimer's Dementia

[0128] As protein biomarkers Aβ40 and Aβ42 did not demonstrate significant performance in predicting conversion to Alzheimer's disease through Examples 1-2 and 1-3 above, they were excluded from the subsequent risk assessment model development process. A risk assessment model for conversion to Alzheimer's disease was developed using binary logistic regression analysis with combinations of protein biomarkers GFAP, NFL, pTau181, and pTau217 and covariates (age, sex, years of education, ApoE ε4 allele). With the conversion to dementia set as the binary dependent variable, the effect of the four protein biomarkers on the risk of conversion to Alzheimer's disease was analyzed. The regression coefficients (estimate), Wald statistics, odds ratio, and significance probability (Pr(>|z|)) were examined using the fmsb and resourceselection packages of R software and IBM SPSS version 27. With a log-likelihood of 74.278 and a significance level of 0.788 for the Hosmer and Lemeshow test for the regression model on the risk of conversion to Alzheimer's dementia including protein biomarkers GFAP, NFL, pTau181, and pTau217, it was confirmed that this logistic model is a goodness-of-fit and fits the observed data well. The variables of the regression equation are summarized in Table 4 below.

[0129] Biomarkers Beta coefficient Wald statistics Odds p-value constant term -6.142 34.082 0.002 <0.001 GFAP 0.043 3.242 1.045 0.028 NFL 0.066 6.164 1.068 0.013 pTau181 0.055 2.002 1.056 0.157 pTau217 37.783 12.039 2.54E+16 <0.001

[0132] The odds ratio of this logistic regression model is = log(p / 1-p) = β0 + β1 GFAP + β2 NFL + β3 pTau181 + β4 pTau217, and the regression equation is composed of -6.142 + (-0.009 × GFAP) + (0.066 × NFL) + (0.055 × pTau181) + (37.783 × pTau217). In addition, the classification accuracy of the regression model was checked using a confusion matrix. As a result, 151 out of 155 participants (97.4%) belonging to the dementia non-conversion group were accurately classified as the non-conversion group, and 8 out of 19 participants (42.1%) belonging to the dementia conversion group were classified as the dementia conversion group, and the overall classification accuracy was 91.4%. Therefore, this regression model means that the transition to Alzheimer's dementia up to 11 years later can be predicted with an accuracy of over 90% based on the protein biomarker concentration at baseline.

[0134] [Example 2] Verification of a Prediction Model for Alzheimer's Dementia Transition

[0135] [Example 2-1] Cohort for Validating the Prediction Model for Alzheimer's Dementia Transition

[0136] To verify the regression model for Alzheimer's dementia conversion according to Example 1 above, plasma samples extracted at baseline from the Korean Longitudinal Study on Cognitive Aging and Dementia cohort were used. The plasma samples obtained from the Human Resource Bank of Kangwon National University Hospital consisted of a normal cognitive function group (n=40), a mild cognitive impairment group (n=50), and an Alzheimer's dementia conversion group (n=21); a total of 111 plasma samples were obtained (see Table 5), and three cryovial tubes (0.3 ml) were obtained for each sample.

[0137] variable Normal cognitive function Mild cognitive impairment (Non-converters) Dementia conversion (AD converters) p -value * (n=40) (n=50) (n=21) years 68.0 [66.5;70.0] 71.0 [65.0;75.0] 74.0 [71.0;78.0] <0.001 gender 0.095 - female 20 (50.0%) 36 (72.0%) 12 (57.1%) - Male 20 (50.0%) 14 (28.0%) 9 (42.9%) Education period (years) 14.0 [12.0;16.0] 6.0 [ 2.0; 9.0] 6.0 [ 0.0; 9.0] <0.001 ApoE ε4 0.154 - Non-existence 34 (85.0%) 39 (78.0%) 14 (66.7%) - existence 6 (15.0%) 11 (22.0%) 7 (33.3%) tTau (pg / mL) 0.7 [ 0.2; 1.2] 0.6 [ 0.3; 1.2] 1.1 [ 0.3; 1.5] 0.606 pTau181 (pg / mL) 18.9 [13.8;25.1] 20.2 [11.5;27.2] 19.2 [14.2;39.4] 0.519 Aβ40 (pg / mL) 47.3 [25.5;70.9] 33.2 [16.9;66.2] 30.8 [11.3;62.3] 0.541 Aβ42 (pg / mL) 3.0 [ 1.6; 4.0] 2.8 [ 1.4; 3.7] 2.2 [ 1.0; 4.4] 0.849 GFAP (pg / mL) 105.4 [81.9;120.8] 102.0 [72.2;137.1] 157.5 [105.3;186.4] 0.021 NFL (pg / mL) 20.1 [16.2;23.9] 24.2 [17.2;30.9] 25.6 [19.8;41.4] 0.018 pTau217 (pg / mL) 0.1 [0.1;0.2] 0.2 [0.1;0.4] 0.4 [0.2;0.5] <0.001 pTau181 / Aβ42 7.1 [5.0;9.5] 9.0 [5.7;13.3] 8.9 [4.4;16.9] 0.261 pTau217 / Aβ42 0.0 [0.0;0.0] 0.1 [0.0;0.2] 0.3 [0.1;0.4] <0.001 MMSE_base 29.0 [28.0; 29.0] 24.0 [21.0; 26.0] 21.0 [19.0; 26.0] <0.001 MMSE_2 years 29.0 [28.0; 30.0] 23.5 [21.0; 25.0] 22.0 [18.0; 25.0] <0.001 MMSE_4 years 29.0 [27.0; 30.0] 23.0 [21.0; 25.0] 18.0 [16.0; 22.0] <0.001 MMSE_6 years 29.0 [28.0; 29.0] 23.0 [21.0; 25.0] 17.0 [13.0; 22.0] <0.001 CERAD-TS_base 74.5 [70.0; 80.0] 48.0 [41.0;54.0] 44.0 [39.0;54.0] <0.001 CERAD-TS_2 years 78.0 [74.5; 82.5] 47.0 [39.0;54.0] 45.0 [34.0;51.0] <0.001 CERAD-TS_4 years 78.5 [73.5; 82.5] 47.0 [39.0;55.0] 38.0 [34.0;44.0] <0.001 CERAD-TS_6 years 79.0 [74.0; 84.0] 45.0 [39.0;52.0] 38.0 [27.0;41.0] <0.001

[0138] * Fisher's test was performed on the gender and ApoE variables, and the Kruskal-Wallis test was performed on other variables. Results are presented as the median [interquartile range] or a number (%).

[0140] [Example 2-2] Analysis of protein biomarkers for validation of Alzheimer's dementia conversion prediction model

[0141] Plasma samples obtained from the Human Resource Bank of Kangwon National University Hospital consisted of a normal cognitive function group (n=40), a mild cognitive impairment group (n=50), and a group transitioning to Alzheimer's disease (n=21), and digital immunoassay was performed for total tau (tTau), phosphorylated tau at residue 181 (pTau181), amyloid beta-42 (Aβ42), amyloid beta-40 (Aβ40), neurofilament light chain (NFL), and glial fibrillary acidic protein (GFAP) in the primary analysis. In addition, a Simoa assay was performed for phosphorylated tau at threonine residue 217 (pTau217) in the secondary analysis.

[0142] Protein quantification reagents were products from Quantarix, and the Simoa HD-1 was used as the analytical instrument. Specifically, plasma samples were removed from the freezer one hour prior to analysis to warm up to a room temperature suitable for analysis, and were prepared by diluting them 20-fold using a diluent. After preparing eight calibrators (A through H) and two analysis controls (1 and 2), 334 µL of each calibrator and 106 µL of each control were dispensed into the plates to be analyzed. After dispensing the diluted samples, the detector, SBG, and RGP (excluding the beads) were mixed by moving the threshold up and down 10 times to prevent foaming, the beads were prepared using a vortexer for 30 seconds, and the analysis was performed. For p-Tau181, the AT270 monoclonal antibody (MN1050, Invitrogen, USA), which is specific to phosphorylation site 27 of the tau protein's 181st threonine residue, was linked to a paramagnetic bead (103207, Quanterix, USA) and used as the capture antibody. This capture antibody can bind to the 176-PPAPKT(p)P-182 region of the tau protein and specifically recognizes the phosphorylation of the 181st threonine residue. As the detection antibody, the anti-tau monoclonal antibody Tau12 (806502, BioLegend, USA) was used. It specifically binds to the N-terminal epitope 6-QEFEVMEDHAGT-18 region of the human tau protein. The detection antibody was conjugated with biotin and used in the Immunorease, which was performed according to the manufacturer's (A3959, Thermo Fisher Scientific, USA) manual. For NFL protein, the mean deviation between analyses was 4.9%, the lowest concentration for quantitative analysis was 0.174 pg / mL, and concentration values ​​exceeding the upper limit of the 4-parameter calibration curve (500 pg / mL) were excluded from the analysis. For pTau217 protein (cat.no 104570, Quenterix, USA), the mean deviation between analyses was 6.3%, and the lowest concentration for quantitative analysis was 0.It was 0.03 pg / mL, and concentration values ​​exceeding the upper limit of the measured concentration (10 pg / mL) of the 4-parameter calibration curve were excluded from the analysis. After the analysis was completed, the quantitative analysis values ​​for each sample were checked to ensure there were no outliers, and it was confirmed whether the quantitative values ​​of the standard substances and the r-values ​​of the standard curve were within the normal range.

[0144] [Example 2-3] Optimization of Prediction Model for Risk of Alzheimer's Dementia Conversion

[0145] Through Examples 1-2 and 1-4 above, a risk prediction model capable of predicting Alzheimer's dementia conversion with 91.4% accuracy from baseline plasma levels of GFAP, NFL, pTau181, and pTau217 protein biomarkers was developed, and through Examples 2-1 and 2-2 above, the classification accuracy of this prediction model was verified using a validation cohort, while optimization was pursued. Dementia conversion status was designated as a binary dependent variable, and the effects on the risk of Alzheimer's dementia conversion were analyzed using combinations of GFAP, NFL, pTau181, and pTau217 protein biomarkers, the presence or absence of the ApoE ε4 allele, and the addition of the pTau217 / Aβ42 ratio or pTau181 / Aβ42 ratio to enhance the effectiveness of the prediction model. Regression coefficients (estimates), Wald statistics, odds ratios, and significance probabilities were examined.

[0146] The logistic regression model for the risk of conversion to Alzheimer's dementia, composed of six variables (GFAP, NFL, pTau181, pTau217, pTau181 / Aβ42, and ApoE ε4), had a log-likelihood of -2 and a significance probability of 68.966 and 0.226 for the Hosmer and Lemeshow tests, respectively, confirming that the model fits the observed data well (see Table 6). When the classification accuracy of the regression model was checked using a confusion matrix, 152 out of 155 participants (98.1%) belonging to the non-conversion group were accurately classified as the non-conversion group, and 10 out of 19 participants (52.6%) belonging to the conversion group were classified as the conversion group, with an overall classification accuracy of 93.1%.

[0147] Biomarkers Beta coefficient Wald statistics Odds p-value constant term -6.890 32.373 0.001 <0.001 GFAP -0.009 3.588 0.992 0.058 NFL 0.068 6.426 1.070 0.011 pTau181 0.069 2.856 1.072 0.041 pTau217 18.037 1.184 6.81E+7 0.027 ApoE4 1.033 2.273 2.809 0.132 pTau181 / Aβ42 92.993 1.978 2.43E+40 <0.001

[0149] In addition, the logistic regression model for the risk of conversion to Alzheimer's dementia composed of six variables (GFAP, NFL, pTau181, pTau217, pTau217 / Aβ42, and ApoE ε4) showed a -2 log likelihood and Hosmer and Lemeshow test significance probabilities of 69.135 and 0.801, respectively, confirming that this logistic model is a goodness-of-fit and fits the observed data well (see Table 7).

[0150] Biomarkers Beta coefficient Wald statistics Odds p-value constant term -6.761 31.671 0.001 <0.001 GFAP -0.010 5.058 0.990 0.025 NFL 0.069 6.691 1.071 0.010 pTau181 0.058 1.985 1.060 0.015 pTau217 27.225 4.521 6.67E+11 0.003 ApoE4 1.060 2.414 2.885 0.120 pTau217 / Aβ42 9.877 1.863 1.94E+4 0.017

[0152] The odds ratio of this logistic regression model is = log(p / 1-p) = β0 + β1 GFAP + β2 NFL + β3 pTau181 + β4 pTau217 + β5 ApoE4 + β6 pTau217 / Aβ42, and the regression equation is composed of -6.761 + (-0.010 × GFAP) + (0.069 × NFL) + (0.058 × pTau181) + (27.225 × pTau217) + (1.060 × ApoE4) + (9.877 × pTau217 / Aβ42). In addition, the classification accuracy of the regression model was verified using a confusion matrix. Of the 155 participants in the non-transition dementia group, 153 (98.7%) were accurately classified as the non-transition group, and of the 19 participants in the transition dementia group, 11 (57.9%) were classified as the transition dementia group, with an overall classification accuracy of 94.3%. This means that the regression model can predict the transition to Alzheimer's dementia up to 11 years later with an accuracy of over 94% based on the protein biomarker concentration at baseline.

[0154] [Examples 2-4] Setting Biomarker Cut-Offs for Predicting Alzheimer's Dementia Conversion Risk Model

[0155] Although it has already been confirmed through the preceding embodiments that the prediction model for the risk of Alzheimer's dementia conversion provided by the present invention can effectively predict Alzheimer's dementia conversion, the predictive performance of the prediction model was further improved by additionally setting cut-off values ​​for individual biomarkers of the prediction model for the risk of Alzheimer's dementia conversion provided by the present invention.

[0156] Specifically, to determine the cut-off levels for individual biomarkers to be used in the analysis of the risk of conversion to Alzheimer's dementia based on subjects' protein biomarkers (GFAP, NFL, pTau181, pTau217) analyzed from plasma samples and additional pTau217 / Aβ42 or pTau181 / Aβ42 ratio measurements, the pROC and multipleROC packages of R software were used, and changes in predictive performance were examined by including or excluding some covariates (age, sex, years of education, ApoE ε4 allele). In the multivariate logistic model described above, it was possible to find the predicted probability threshold that best separates the occurrence of Alzheimer's dementia conversion up to 11 years later using only baseline biomarker data (see Table 8), and the corresponding predictive performance was verified (see Table 9). The predictive performance in Table 9 is the metric value derived from the combination of GFAP, NFL, pTau181, pTau217, and pTau217 / Aβ42 ratio biomarkers. Table 10 is the predictive performance metric value derived from the combination of GFAP, NFL, pTau181, pTau217, and pTau181 / Aβ42 ratio biomarkers.

[0157] The reference values ​​for each biomarker or ratio are as shown in Table 8, and the optimal cut-off values ​​are as follows. More desirable optimal cut-off values ​​for plasma GFAP biomarkers are 196 pg / mL or higher, NFL is 23.0 pg / mL or higher, pTau181 is 21.0 pg / mL or higher, pTau217 is 0.057 pg / mL or higher, the pTau181 / Aβ42 ratio is 3.73 or higher, and the pTau217 / Aβ42 ratio is 0.02 or higher.

[0158] Biomarkers Individual AUC Z statistic p-value AD conversion predicted concentration or ratio GFAP 0.768 4.892 <0.001 >121 pg / mL NFL 0.734 3.677 <0.001 >15 pg / mL pTau181 0.880 12.013 <0.001 >15.60 pg / mL pTau217 0.865 7.892 <0.001 >0.05 pg / mL pTau181 / Aβ42 0.823 7.580 <0.001 >3.53 pTau217 / Aβ42 0.855 7.719 <0.001 >0.01

[0160] Performance indicators Performance figures AUC (area under the ROC curve) 0.944 responsiveness 0.905 Specificity 0.907 Precision or positive prediction rate 0.559 Voice prediction rate 0.987

[0162] Performance indicators Performance figures AUC (area under the ROC curve) 0.923 responsiveness 0.947 Specificity 0.871 Precision or positive prediction rate 0.457 Voice prediction rate 0.978

[0164] Foregoing, specific parts of the present invention have been described in detail. It is evident to those skilled in the art that such specific descriptions are merely preferred embodiments and do not limit the scope of the invention. Accordingly, the actual scope of the invention is defined by the appended claims and their equivalents.

Claims

Claim 1 A composition providing information necessary for assessing the occurrence or risk of cognitive disorders (CD), comprising a preparation for specifically detecting two or more proteins selected from the following groups or genes encoding them: glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), phosphorylated tau at residue 181 (pTau181), phosphorylated tau at residue 217 (pTau217), pTau217 / Aβ ratio and pTau181 / Aβ ratio. Claim 2 A composition for providing information necessary for assessing the occurrence of or risk of cognitive impairment, wherein, in claim 1, the cognitive impairment is one or more selected from the group consisting of Alzheimer's Dementia, Mild Cognitive Impairment (MCI), Vascular Dementia, Lewy Body Dementia, Mixed Dementia, and Pseudo-dementia. Claim 3 A composition that provides information necessary for assessing the occurrence of cognitive impairment or risk, wherein the preparation for specifically detecting the protein or the gene encoding it is one or more selected from the group consisting of antibodies, oligopeptides, ligands, PNA (peptide nucleic acid) and aptamers, primers, or probes that specifically bind to the protein or the gene encoding it. Claim 4 A kit for the analysis and detection of cognitive impairment comprising a composition of any one of claims 1 to 3. Claim 5 In paragraph 4, the kit is a kit for the analysis and detection of cognitive impairment, wherein the kit is an RT-PCR kit, a DNA chip kit, an ELISA kit, a protein chip kit, a rapid kit, or an MRM (Multiple reaction monitoring) kit. Claim 6 (a) a step of detecting two or more proteins or genes encoding them selected from a group consisting of GFAP, NFL, pTau181, pTau217, pTau217 / Aβ ratio and pTau181 / Aβ ratio in a biological sample obtained from a target individual; and (b) a step of comparing the levels of the detected proteins or genes encoding them with a normal control group, which is a cognitively unimpaired (CU) group, and / or a preset threshold, and determining that there is a high probability of cognitive impairment if the levels are higher than those of the CU group or exceed the threshold. A method for providing information for determining cognitive impairment. Claim 7 (a) a detection unit for detecting two or more proteins or genes encoding them selected from a group consisting of GFAP, NFL, pTau181, pTau217, pTau217 / Aβ ratio and pTau181 / Aβ ratio in a biological sample obtained from a target individual; and (b) an output unit for comparing the levels of the detected proteins or genes encoding them with a normal control group, a cognitively unimpaired (CU) group, and / or a preset reference value, and outputting that there is a high probability of cognitive impairment if the levels are higher than those of the CU group or exceed the reference value; an analysis device for cognitive impairment comprising: Claim 8 A composition for predicting the risk of transition from the cognitive impairment stage to the dementia stage, comprising a preparation for specifically detecting two or more proteins selected from the following groups or genes encoding the same: glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), phosphorylated tau at residue 181 (pTau181), phosphorylated tau at residue 217 (pTau217), pTau217 / Aβ ratio and pTau181 / Aβ ratio. Claim 9 In claim 8, the preparation for specifically detecting the protein or the gene encoding it is a composition for predicting the risk of transition from a cognitive impairment stage to a dementia stage, wherein the preparation is two or more selected from the group consisting of an antibody, oligopeptide, ligand, PNA (peptide nucleic acid), and aptamer, primer, or probe that specifically binds to the protein or the gene encoding it. Claim 10 A composition for predicting the risk of transition from a cognitive impairment stage to a dementia stage, wherein the optimal cut-off values ​​of the protein or the gene encoding it are 100 pg / mL or more for the GFAP biomarker, 10.0 pg / mL or more for the NFL biomarker, 10.0 pg / mL or more for the pTau181 biomarker, 0.010 pg / mL or more for the pTau217 biomarker, 2.00 or more for the pTau181 / Aβ42 ratio biomarker, and 0.01 or more for the pTau217 / Aβ42 ratio biomarker. Claim 11 A composition for predicting the risk of transition from a cognitive impairment stage to a dementia stage, wherein the optimal cut-off of the protein or the gene encoding it is greater than 121 pg / mL for the plasma GFAP biomarker, greater than 15 pg / mL for the plasma NFL biomarker, greater than 15.60 pg / mL for the plasma pTau181 biomarker, greater than 0.05 pg / mL for the plasma pTau217 biomarker, greater than 3.53 for the pTau181 / Aβ42 ratio biomarker, and greater than 0.01 for the pTau217 / Aβ42 ratio biomarker. Claim 12 A composition for predicting the risk of transition from a cognitive impairment stage to a dementia stage, wherein the optimal cut-off values ​​of the protein or the gene encoding it are at least 196 pg / mL for the plasma GFAP biomarker, at least 23.0 pg / mL for the NFL biomarker, at least 21.0 pg / mL for the pTau181 biomarker, at least 0.057 pg / mL for the pTau217 biomarker, at least 3.73 for the pTau181 / Aβ42 ratio biomarker, and at least 0.02 for the pTau217 / Aβ42 ratio biomarker. Claim 13 A composition for predicting the risk of transition from a cognitive impairment stage to a dementia stage, wherein, in any one of claims 8 to 12, the dementia is one or more selected from the group consisting of primary dementia, secondary dementia, and reversible dementia. Claim 14 In claim 13, the above primary dementia is a composition that predicts the risk of transition from a cognitive impairment stage to a dementia stage, wherein the primary dementia is Alzheimer's dementia. Claim 15 A kit for analysis and detection that predicts the risk of transition from a cognitive impairment stage to a dementia stage, comprising the composition of claim 8. Claim 16 In claim 15, the above kit is an RT-PCR kit, DNA chip kit, ELISA kit, protein chip kit, rapid kit, or MRM (Multiple reaction monitoring) kit, a kit for analysis and detection that predicts the risk of transition from the cognitive impairment stage to the dementia stage. Claim 17 (a) a measurement unit for detecting two or more proteins selected from a group consisting of GFAP, NFL, pTau181, pTau217, pTau217 / Aβ ratio and pTau181 / Aβ ratio, or genes encoding the same, for a biological sample obtained from a target individual; and (b) a detection unit for outputting the possibility of a mild cognitive impairment-to-Alzheimer's disease conversion when the levels of the detected proteins or genes encoding the same are compared to a normal (CU) group and / or a preset reference value and are higher than the CU group or exceed the reference value; comprising an analysis device for predicting the risk of conversion from a mild cognitive impairment stage to an Alzheimer's disease stage. Claim 18 (a) a step of detecting two or more proteins or genes encoding them selected from a group consisting of GFAP, NFL, pTau181, pTau217, pTau217 / Aβ ratio and pTau181 / Aβ ratio in a biological sample obtained from a target individual; and (b) a step of comparing the levels of the detected proteins or genes encoding them with a normal control group, a cognitively unimpaired (CU) group, and / or a preset threshold, and determining that there is a high probability of conversion from mild cognitive impairment to Alzheimer's disease converted if the levels are higher than those of the CU group or exceed the threshold. Claim 19 (a) a step of detecting two or more proteins or genes encoding them selected from a group consisting of GFAP, NFL, pTau181, pTau217, pTau217 / Aβ ratio and pTau181 / Aβ ratio in a biological sample obtained from a target individual; and (b) a method for selecting a group of patients with mild cognitive impairment who are at high risk of conversion to Alzheimer's disease, wherein the level of the detected proteins or genes encoding them is compared to a normal control group (cognitively unimpaired; CU) and / or a preset threshold, and if the level is higher than that of the CU group or exceeds the threshold, it is determined that there is a high probability of conversion to Alzheimer's disease. Claim 20 (a) a step of detecting two or more proteins or genes encoding them selected from a group consisting of GFAP, NFL, pTau181, pTau217, pTau217 / Aβ ratio and pTau181 / Aβ ratio in a biological sample obtained from a target individual; and (b) a method of determining that the level of the detected proteins or genes encoding them is likely to be a patient group suitable for anti-amyloid drug treatment by comparing the level of the detected proteins or genes encoding them with a normal control group, which is a cognitively unimpaired (CU) group, and / or a preset threshold, and if the level is higher than that of the CU group or exceeds the threshold. Claim 21 (a) a measuring unit for detecting two or more proteins or genes encoding them selected from a group consisting of GFAP, NFL, pTau181, pTau217, pTau217 / Aβ ratio and pTau181 / Aβ ratio in a biological sample obtained from a target individual; and (b) a processing unit for comparing the levels of the detected proteins or genes encoding them with a normal control group, a cognitively unimpaired (CU) group, and / or a preset reference value, and outputting that if the levels are higher than those of the CU group or exceed the reference value, there is a high probability that the patient group is suitable for anti-amyloid drug treatment; comprising a device for determining a patient group suitable for anti-amyloid drug treatment.

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