Protein markers for determining alzheimer's disease

Abstract

To provide methods and compositions useful for diagnosing AD, and methods and compositions useful for indicating the therapeutic effectiveness of agents for treating AD.SOLUTION: A method of assessing the risk that a subject will subsequently develop AD is provided. The method comprises the following steps: (1) comparing the level or concentration of any one protein selected from Tables 1-4 in the plasma or serum or whole blood of a subject to a standard control level of the same protein; (2) detecting that the level of the protein (having a positive β value in Table 1, Table 2, Table 3 or Table 4) in the plasma or serum or whole blood of the subject is higher than the standard control level or that the level of the protein (having a negative β value in Table 1, Table 2, Table 3 or Table 4) in the plasma or serum or whole blood of the subject is lower than the standard control level; and (3) determining that the subject has an increased risk of AD.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] Related Applications This application claims priority from U.S. Provisional Patent Application No. 63 / 024,940, filed May 14, 2020, the contents of which are incorporated by reference in their entirety into this disclosure for all purposes. [Background technology]

[0002] Brain diseases, such as neurodegenerative and neuroinflammatory disorders, are devastating conditions affecting a large subset of the population. Many are incurable, highly debilitating, and often result in progressive deterioration of brain structure and function over time. Furthermore, the prevalence of these conditions is rapidly increasing due to the aging of the global population, with older adults at higher risk of developing these conditions. Currently, many neurodegenerative and neuroinflammatory diseases are difficult to diagnose due to limited understanding of their pathophysiology. Meanwhile, current treatments are ineffective and fail to meet market demand, a demand that is increasing significantly each year due to the aging population. For example, Alzheimer's disease (AD), characterized by a gradual but progressive decline in learning and memory, is a leading cause of death among the elderly. The increasing prevalence of AD has driven the need and demand for better diagnostic methods. According to Alzheimer's Disease International, the disease currently affects 46.8 million people worldwide, and the number of cases is expected to triple over the next 30 years. China has one of the fastest-growing elderly populations. Population projections indicate that by 2030, one in four people will be over 60 years old, placing a significantly larger proportion at risk for developing AD. In fact, the number of AD cases in China doubled from 3.7 million to 9.2 million between 1990 and 2010, and the country is projected to have 2,250 cases by 2050. Hong Kong's population is also rapidly aging. It is estimated that those aged 65 years or older will account for 24% of the population in 2025 and 39.3% by 2050. The number of AD patients is projected to increase to 332,688 by 2039. This increase in AD is driving the need and demand for better diagnostic methods. According to Alzheimer's Disease International, the disease currently affects 46.8 million people worldwide, a number that is expected to triple over the next 30 years. China has one of the fastest-growing elderly populations. Population projections show that by 2030, one in four people will be over 60 years old, putting a huge proportion of them at risk of developing AD.Indeed, the number of AD patients in China doubled from 3.7 million to 9.2 million between 1990 and 2010 and is projected to reach 22.5 million by 2050. Hong Kong's population is also rapidly aging: by 2025, those aged 65 years and older are estimated to account for 24% of the population and 39.3% by 2050. The number of AD cases is projected to increase to 332,688 by 2039.

[0003] Even more worrying is that despite the increasing prevalence of AD, many people do not receive a correct diagnosis. According to Alzheimer's Disease International's World Alzheimer's Report 2015, in high-income countries, Only 20-50% of dementia cases are reported in medical care. The rest remain undiagnosed or incorrectly diagnosed. This "treatment gap" is even more pronounced in low- and middle-income countries. Without a formal diagnosis, patients do not receive the treatment and care they need, and patients or their caregivers are ineligible for important support programs. Early diagnosis and early intervention are two key means of narrowing the treatment gap. Therefore, early diagnostic tools that can quickly and accurately determine disease risk have great therapeutic value on many levels. AD is a condition where actual symptoms of memory loss or cognitive decline are actually present. Research has confirmed that Alzheimer's disease (AD) affects the brain long before symptoms appear. However, to date, there are no diagnostic tools for early detection; by the time AD is diagnosed using currently available methods, which involve subjective clinical assessment, pathology is often already in an advanced stage. Therefore, there is an urgent need to develop new and effective methods for early diagnosis of AD or for later detection of an increased risk of developing AD in patients, with the aim of improving treatment and long-term management of AD. The present invention addresses this and other related needs by disclosing novel methods and kits for the use of plasma, serum, or whole blood protein markers, or combinations thereof, to determine an individual's risk of developing Alzheimer's disease (AD). Summary of the Invention

[0004] The present invention relates to the discovery of novel plasma protein markers associated with Alzheimer's disease (AD). Accordingly, the present invention provides methods and compositions useful for diagnosing AD and for indicating the therapeutic efficacy of drugs for treating AD. Thus, in a first aspect, the present invention provides a method for assessing a subject's risk of subsequently developing AD. The method includes the following steps: (1) comparing the level or concentration of any one protein selected from Tables 1-4 in the plasma, serum, or whole blood of a subject with a standard control level of the same protein found in the plasma, serum, or whole blood of an average healthy subject not suffering from or at increased risk for AD; (2) detecting that the level of the protein (having a positive β value in Table 1, Table 2, Table 3, or Table 4) in the subject's plasma, serum, or whole blood is higher than the standard control level, or that the level of the protein (having a negative β value in Table 1, Table 2, Table 3, or Table 4) in the subject's plasma, serum, or whole blood is lower than the standard control level; and (3) determining that the subject is at increased risk for AD. While any of the 429 proteins listed in Table 2 are suitable for use in this method, in some cases, the protein is selected from the 74 proteins listed in Table 1, or from the 19 proteins listed in Table 4, or from the 12 proteins listed in Table 3. In some embodiments, the method also includes, prior to step (1), measuring the level of the protein in the plasma, serum, or whole blood. In some embodiments, the measuring step is preceded by a step of obtaining a plasma, serum, or whole blood sample from the subject. In some embodiments, if the subject is determined to be at increased risk for AD in step (3), the subject is then referred to increased follow-up monitoring (e.g., routine monitoring prescribed by a health care professional for no-risk or low-risk individuals of similar age and medical background) as described herein. Increased frequency of monitoring tests or treatment is provided.

[0005] In a second aspect, the present invention provides a method for assessing the risk of Alzheimer's disease (AD) between two subjects, comprising the steps of: (i) comparing the level of any one protein selected from Tables 1 to 4 in the plasma, serum, or whole blood of a first subject with the level of the same protein in the plasma, serum, or whole blood of a second subject, respectively; (ii) detecting that the level of the protein in the plasma, serum, or whole blood of the second subject is higher than the level of the protein in the plasma, serum, or whole blood of the first subject, respectively (having a positive β value in Table 1, Table 2, Table 3, or Table 4), or that the level of the protein in the plasma, serum, or whole blood of the second subject is lower than the level of the protein in the plasma, serum, or whole blood of the first subject, respectively (having a negative β value in Table 1, Table 2, Table 3, or Table 4); and (iii) determining that the second subject has a higher risk of subsequently developing AD than the first subject. 429 proteins listed in Table 2 While any quality of protein is suitable for use in the method, in some embodiments, the protein is selected from the 74 proteins listed in Table 1, or from the 19 proteins listed in Table 4, or from the 12 proteins listed in Table 3. In some embodiments, the method further comprises measuring the level of the protein in the plasma, serum, or whole blood. In some embodiments, the measuring step is preceded by a step of obtaining a plasma, serum, or whole blood sample from the subject. In some embodiments, if the subject is determined to be at higher risk for AD in step (iii), the subject is then subjected to increased follow-up monitoring (e.g., compared to routine monitoring prescribed by a health care professional for a no-risk or low-risk individual of similar age and medical background), as described herein. Subjects who are considered to be at lower risk for AD will be provided with increased frequency of monitoring tests or treatment compared to those with a similar age and medical background, while other subjects who are considered to be at lower risk for AD will be provided with treatment according to the schedule prescribed by a healthcare professional for no-risk or low-risk subjects. He is monitored by Chin.

[0006] In a third aspect, the present invention provides a kit for assessing the risk of Alzheimer's disease (AD) in a subject, or for assessing the therapeutic efficacy of a treatment regimen for AD, the kit being capable of determining the level or concentration of each of any 5, 10, 15, or 20 proteins independently selected from the 429 proteins listed in Table 2 in the plasma, serum, or whole blood of the subject. In some embodiments, the protein(s) are independently selected from the 74 proteins listed in Table 1, or the 19 proteins listed in Table 4, or the 12 proteins listed in Table 3. In some embodiments, the kit may further include reagents capable of determining the level or concentration of each of amyloid beta protein 42, amyloid beta protein 40, and neurofilament light polypeptide (NfL) in the subject's plasma, serum, or whole blood. In some embodiments, the kit may further comprise a standard control for each of the proteins that reflects the level / concentration of the same protein found in the plasma or serum or whole blood of an average healthy subject who does not suffer from or have an increased risk for AD.

[0007] In a fourth aspect, the present invention provides a detection chip for assessing AD risk in a subject or assessing the therapeutic efficacy of a treatment regimen for AD. The chip includes a solid substrate and reagents capable of determining the level of each of any 5, 10, 15, or 20 proteins independently selected from the 429 proteins listed in Table 2 in the plasma, serum, or whole blood of a subject, wherein each reagent is immobilized at an addressable location on the substrate. In some embodiments, the proteins are independently selected from the 74 proteins listed in Table 1, or the 19 proteins listed in Table 4, or the 12 proteins listed in Table 3.

[0008] In a fifth aspect, the present invention provides a method for assessing the risk of Alzheimer's disease (AD) in a subject, the method comprising the steps of: (1) calculating a function of the formula:

number

[0009] In some embodiments, the set of values ​​consists of the levels of each of the 12 proteins in Table 3 in plasma or serum or whole blood, along with the corresponding weighting coefficients (β i ) and intercept (ε) are given in Table 5, with subjects with a score between 0 and 0.25 having a low risk for AD, subjects with a score greater than 0.25 to 0.79 having a moderate risk for AD, and subjects with a score greater than 0.79 to 1 having a high risk for AD.

[0010] In some embodiments, the set of values ​​consists of the levels of each of the 19 proteins listed in Table 4 in plasma or serum or whole blood, along with the corresponding weighting coefficients (β i ) and intercept (ε) are given in Table 6, with subjects with a score of 0 to 0.21 having a low risk for AD, subjects with a score greater than 0.21 to 0.8 having a moderate risk for AD, and subjects with a score greater than 0.8 to 1 having a high risk for AD.

[0011] In some embodiments, the set of values ​​consists of the ratio of amyloid beta protein 42 level to amyloid beta protein 40 level in plasma or serum or whole blood, the level of NfL in plasma or serum or whole blood, and the level of each of the 12 proteins listed in Table 3 in plasma or serum or whole blood, with corresponding weighting factors (β i) and intercept (ε) are listed in Table 7, with subjects with a score of 0 to 0.20 having a low risk for AD, subjects with a score of greater than 0.20 to 0.80 having a moderate risk for AD, and subjects with a score of greater than 0.80 to 1 having a high risk for AD.

[0012] In some embodiments, the set of values ​​consists of the ratio of amyloid beta protein 42 level to amyloid beta protein 40 level in plasma or serum or whole blood, the level of NfL in plasma or serum or whole blood, and the level of each of the 19 proteins listed in Table 4 in plasma or serum or whole blood, with corresponding weighting factors (β i ) and intercept (ε) are listed in Table 8, with subjects with a score of 0 to 0.30 having a low risk for AD, subjects with a score of greater than 0.30 to 0.80 having a moderate risk for AD, and subjects with a score of greater than 0.80 to 1 having a high risk for AD.

[0013] In some embodiments, the method further comprises, prior to step (1), measuring the level of the protein in plasma, serum, or whole blood. In some embodiments, the method further comprises, prior to the measuring step, another step of obtaining a sample of plasma, serum, or whole blood from the subject. In some embodiments, if the subject is determined to be at high risk for AD in step (2), the subject is then administered increased follow-up monitoring (e.g., monitoring at an increased frequency compared to routine monitoring prescribed by a health care professional for a no-risk or low-risk individual of similar age and medical background) as described herein. If in step (2) the subject is determined to be at moderate risk for AD, the subject is then administered increased follow-up monitoring (e.g., as prescribed by a health care professional for no-risk or low-risk individuals of similar age and medical background) and treatment, as described herein. If the subject is determined to be at low risk for AD, the subject is then given a prognosis (monitoring tests at an increased frequency compared to routine monitoring) typically designated by a physician for no-risk or low-risk individuals for AD. Routine monitoring to determine the cause of the disease (e.g., serologic diagnosis, serologic evaluation, or serologic evaluation) is given.

[0014] In a sixth aspect, the present invention provides a method for determining the relative risk for Alzheimer's disease (AD) in two subjects, the method comprising the steps of: (i) calculating a set of values ​​based on the formula

number

[0015] In some embodiments, the set of values ​​comprises the ratio of amyloid beta protein 42 level to amyloid beta protein 40 level in plasma or serum or whole blood, the level of NfL in plasma or serum or whole blood, the level of any combination of proteins listed in Table 2 in plasma or serum or whole blood, and corresponding weighting factors (β i ) are given in Table 1, Table 2, Table 3, Table 4 and Table 9.

[0016] In some embodiments, the set of values ​​comprises a ratio of amyloid beta protein 42 level to amyloid beta protein 40 level in plasma or serum or whole blood, a level of NfL in plasma or serum or whole blood, a level of at least one of the proteins listed in Table 1, Table 3 or Table 4 in plasma or serum or whole blood, and a corresponding weighting factor (β i ) are given in Tables 1, 3, 4 and 9.

[0017] In some embodiments, the set of values ​​comprises a ratio of amyloid beta protein 42 level to amyloid beta protein 40 level in plasma or serum or whole blood, a level of NfL in plasma or serum or whole blood, and levels of at least five proteins independently selected from Table 1, Table 3, or Table 4 in plasma or serum or whole blood, with corresponding weighting factors (β i ) are given in Tables 1, 3, 4 and 9.

[0018] In some embodiments, the set of values ​​comprises a ratio of amyloid beta protein 42 level to amyloid beta protein 40 level in plasma or serum or whole blood, a level of NfL in plasma or serum or whole blood, and levels of at least 10 proteins independently selected from Table 1, Table 3, or Table 4 in plasma or serum or whole blood, with corresponding weighting factors (β i ) are given in Tables 1, 3, 4 and 9.

[0019] In some embodiments, the method further comprises, prior to step (i), measuring the level of each of said proteins in plasma or serum or whole blood. In some embodiments, the method further comprises, prior to said measuring step, obtaining a sample of plasma or serum or whole blood from said subject. In some embodiments, if the subject is determined to be at higher risk for AD in step (ii), then said subject is then referred to increased follow-up monitoring (e.g., similar follow-up monitoring) as described herein. Increased frequency of monitoring compared with routine monitoring prescribed by a healthcare professional for non-risk or low-risk individuals of a given age and medical background. One subject, considered to be at lower risk for AD, is given a steroid test or treatment, while the other subject, considered to be at lower risk for AD, undergoes routine monitoring as prescribed by a healthcare professional for those at no or low risk for AD.

[0020] In a seventh aspect, the present invention provides a method for assessing the effectiveness of a therapeutic agent for treating Alzheimer's disease (AD) in a subject diagnosed with AD. The method includes the following steps: (1) comparing the level of any one protein selected from Tables 1 to 4 in the subject's plasma, serum, or whole blood before administration of the therapeutic agent with the level of the protein in the subject's plasma, serum, or whole blood after administration of the therapeutic agent; (2) detecting a decrease in the level of the protein (having a positive β value in Table 1, Table 2, Table 3, or Table 4) in the subject's plasma, serum, or whole blood after administration of the therapeutic agent; and (3) determining that the therapeutic agent is effective for treating AD. In some embodiments, the protein is selected from Table 1. In some embodiments, the protein is selected from Table 3. In some embodiments, the protein is selected from Table 4. In some embodiments, the method further comprises, prior to step (1), measuring the level of the protein in plasma, serum, or whole blood before and after administration. In some embodiments, the method may also comprise, prior to the measuring step, obtaining plasma, serum, or whole blood samples from the subject before and after administration.

[0021] In some embodiments, if the therapeutic agent is deemed effective for treating AD in step (3), the subject continues their treatment by administering the therapeutic agent; if the therapeutic agent is deemed ineffective for treating AD in step (3), the subject discontinues treatment by administering the therapeutic agent, and the subject begins treatment for AD by administering a different therapeutic agent. [Brief explanation of the drawings]

[0022] [Figure 1] Prediction of AD risk based on a model using 12 plasma proteins. (a) Receiver operating characteristic (ROC) curve of the AD prediction model based on the plasma levels of 12 proteins (listed in Table 3) in the Hong Kong Chinese AD cohort. (b) Distribution of AD prediction scores stratified by phenotype (n = 71 and 101 for AD patients in the NC and Hong Kong Chinese AD cohorts, respectively). The predicted AD risk stage is defined by the distribution of the AD prediction score (low: 0-0.25; intermediate: 0.25-0.79; high: 0.79-1.0).

[0023] [Figure 2] Prediction of AD risk based on a model using 19 plasma proteins. (a) Receiver operating characteristic (ROC) curve of the AD prediction model based on the plasma levels of 19 proteins (listed in Table 4) in the Hong Kong Chinese AD cohort. (b) Distribution of AD prediction scores stratified by phenotype (n = 71 and 101 for AD patients in the NC and Hong Kong Chinese AD cohorts, respectively). The predicted AD risk stage is defined by the distribution of the AD prediction score (low: 0-0.21; intermediate: 0.21-0.8; high: 0.8-1.0).

[0024] [Figure 3]Prediction of AD risk based on a model utilizing the plasma Aβ42 / 40 ratio, plasma NfL, and 12 plasma proteins. (a) Receiver operating characteristic (ROC) curves for the AD prediction model based on the plasma Aβ42 / 40 ratio, plasma NfL levels, and plasma levels of 12 proteins (listed in Table 3) in the Hong Kong Chinese AD cohort. (b) Distribution of AD prediction scores stratified by phenotype (n = 71 and 101 for AD patients in the NC and Hong Kong Chinese AD cohorts, respectively). The predicted AD risk stage is defined by the distribution of the AD prediction score (low: 0-0.2; intermediate: 0.2-0.8; high: 0.8-1.0).

[0025] [Figure 4] Prediction of AD risk based on a model utilizing the plasma Aβ42 / 40 ratio, plasma NfL, and 19 plasma proteins. (a) Receiver operating characteristic (ROC) curves for the AD prediction model based on the plasma Aβ42 / 40 ratio, plasma NfL levels, and plasma levels of 19 proteins (listed in Table 4) in the Hong Kong Chinese AD cohort. (b) Distribution of AD prediction scores stratified by phenotype (n = 71 and 101 for AD patients in the NC and Hong Kong Chinese AD cohorts, respectively). The predicted AD risk stage is defined by the distribution of the AD prediction score (low: 0-0.3; intermediate: 0.3-0.8; high: 0.8-1.0). DETAILED DESCRIPTION OF THE INVENTION

[0026] definition "Polypeptide," "peptide," and "protein" are used interchangeably in this disclosure to refer to a polymer of amino acid residues. All three terms apply to naturally occurring and unnatural amino acid polymers, as well as to amino acid polymers in which one or more amino acid residues are artificial chemical mimetics of a corresponding naturally occurring amino acid. As used in this disclosure, these terms encompass amino acid chains of any length in which the amino acid residues are linked by covalent peptide bonds, including full-length proteins.

[0027] In this disclosure, the term "biological sample" or "sample" includes sections of tissue such as biopsy and autopsy samples, frozen sections taken for histological purposes, or processed forms of any such samples. Biological samples include blood and blood fractions or blood products (e.g., whole blood, acellular fractions of blood (serum, plasma), and blood cells), sputum or saliva, lymphatic and tongue tissue, cultured cells, e.g., primary cultures, explants, and transformed cells, stool, urine, stomach biopsy tissue, etc. Biological samples are typically obtained from eukaryotic organisms and may be from mammals, primates, or human subjects.

[0028] The terms "immunoglobulin" or "antibody" (used interchangeably in this disclosure) refer to antigen-binding proteins with a basic four polypeptide chain structure consisting of two heavy chains and two light chains, which are stabilized, for example, by interchain disulfide bonds, and which have the ability to specifically bind to an antigen. Both the heavy and light chains are folded into domains.

[0029] The term "antibody" also refers to antigen- and epitope-binding fragments of antibodies, such as Fab fragments, which can be used in immunological affinity assays. Many well-characterized antibody fragments exist. Thus, for example, pepsin digests antibodies at the C-terminal side of the disulfide bond in the hinge region to produce F(ab)'2, which itself is bounded by disulfide bonds. H -C H F(ab)'2 is a dimer of Fab, a light chain bound to a Fab'1. F(ab)'2 can be reduced under mild conditions to cleave the disulfide bond in the hinge region, thereby converting the (Fab')2 dimer into a Fab' monomer. The Fab' monomer is essentially Fab with part of the hinge region (for a more detailed description of other antibody fragments, see, e.g., Fundamental Immunology, Paul, ed., Raven Press, NY (1993)). Various antibody fragments Although fragments are defined in the context of digestion of intact antibodies, one skilled in the art will understand that fragments can be synthesized de novo, either chemically or using recombinant DNA methodologies. Thus, the term antibody refers to antibody fragments made by modifications to whole antibodies or synthesized using recombinant DNA methodologies. This also includes the

[0030] When used in the context of describing the binding relationship between a particular molecule and a protein or peptide, the term "specifically binds" refers to a group of proteins and other biologics. Specific binding refers to a binding reaction that is determinative of the presence of that protein in a heterogeneous population. Thus, under specified binding assay conditions, a specified binding agent (e.g., an antibody) will bind to a specific protein at least twice as much as background and will not bind substantially in significant amounts to other proteins present in the sample. Specific binding of an antibody under such conditions may require an antibody selected for its specificity for a particular protein or a protein but not for its similar "sister" proteins. Various immunoassay formats can be used to select antibodies specifically immunoreactive with a particular protein or a particular form of a protein. For example, solid-phase ELISA immunoassays are routinely used to select antibodies specifically immunoreactive with a protein (see, e.g., Harlow & Lane, Antibodies, A Laboratory Manual (1988) for a description of immunoassay formats and conditions that can be used to determine specific immunoreactivity). Typically, a specific or selective binding reaction is characterized by a high level of background signal. The specificity of the polynucleotide hybridization method is at least twice the null or noise, and more typically more than 10 to 100 times the background. On the other hand, the term "specifically binds" when used in the context of referring to the formation of a double-stranded complex between a polynucleotide sequence and another polynucleotide sequence refers to "polynucleotide hybridization" based on Watson-Crick base pairing, as defined in the definition of the term "polynucleotide hybridization method."

[0031] As used in this application, "increase" or "decrease" refers to a detectable positive or negative quantitative change from a comparative control, e.g., an established standard control (such as the average level / amount of a particular protein found in samples from healthy subjects who have not been diagnosed with and do not have an increased risk for AD). An increase is a positive change that is typically 10% or more, or 20% or more, or 50% or more, or 100% or more; an increase may be 2-fold or more, or 5-fold or more, or even 10-fold higher than the control value. Similarly, a decrease is a negative change that is typically 10% or more, or 20% or more, 30% or more, or 50% or more, or even 80% or more, or even 90% or more higher than the control value. Terms such as "more," "less," "higher," and "lower" may be used to refer to a comparative group. Other terms indicating quantitative changes or differences from a standard are used herein in the same manner as above, whereas the terms "substantially the same" or "substantially unchanged" indicate little to no change in quantity from a standard control, typically within ±10% of the standard control, or within ±5%, ±2%, or even less variation from the standard control.

[0032] A "label," "detectable label," or "detectable moiety" is a composition detectable by spectroscopic, photochemical, biochemical, immunochemical, chemical, or other physical means. For example, useful labels include: 32Examples of detectable labels include proteins that can be used to detect P, fluorescent dyes, electron-dense reagents, enzymes (e.g., enzymes commonly used in ELISA), biotin, digoxigenin, or haptens, as well as antibodies that can be made detectable or that specifically react with the protein, for example, by incorporating an emissive moiety into the protein. Typically, a detectable label is attached to a probe or a molecule with defined binding properties (e.g., an antibody with known binding specificity for a polypeptide antigen) to allow the presence of the probe (and therefore its bound target) to be easily detected.

[0033] As used herein, the term "amount" refers to the amount of a substance of interest, e.g., a polypeptide of interest, present in a sample. Such amount may be expressed in absolute terms, i.e., the total amount of that substance in the sample, or in relative terms, i.e., the amount of that substance in the sample. It may be expressed as the concentration of the substance.

[0034] As used in this disclosure, the term "subject" or "subject in need of treatment" includes individuals who seek medical attention because they are at risk for AD (e.g., because they have a family history) or because they have been diagnosed with AD. Also included are individuals currently undergoing treatment who seek manipulation. Subjects or individuals in need of treatment include those who exhibit symptoms of AD or are at risk for developing AD or its symptoms. For example, subjects in need of treatment include those with a genetic predisposition or family history of AD, individuals who have previously suffered from associated symptoms, individuals who have been exposed to a triggering substance or event, and individuals who suffer from chronic or acute symptoms of the condition. A "subject in need of treatment" can be at any age throughout life.

[0035] "Inhibitors," "activators," and "modulators" of a target protein are used to refer to inhibitory, activating, or modulating molecules, respectively, identified using in vitro and in vivo assays for protein binding or signal transduction, such as ligands, agonists, antagonists, and their homologs and mimetics. The term "modulator" includes inhibitors and activators. Inhibitors are, for example, agents that partially or fully inhibit, reduce, prevent, delay activation, inactivate, desensitize, or downregulate the activity of a target protein. In some cases, inhibitors are also used, such as neutralizing antibodies. As used in this disclosure, inhibitors are synonymous with inactivators and antagonists. Activators are agents that stimulate, increase, promote, enhance activation, sensitize, or upregulate the activity of a target protein, for example. Modulators include ligands or binding partners of target proteins, including modified natural ligands and synthetically designed ligands, antibodies and antibody fragments, antagonists, agonists, small molecules such as carbohydrate-containing molecules, siRNAs, RNA aptamers, and the like.

[0036] As used in this application, the terms "treating" or "treatment" describe actions that lead to the elimination, reduction, alleviation, reversal, prevention, and / or delay of the onset or recurrence of any symptoms of a given medical condition. In other words, "treating" a condition encompasses both therapeutic and prophylactic interventions for that condition.

[0037] As used in this disclosure, the term "effective amount" refers to an amount of a substance that produces the therapeutic effect for which it is administered. This effect includes preventing, correcting, or inhibiting the progression of any detectable symptoms of the disease / condition and associated complications. The precise amount will depend on the purpose of the treatment and can be ascertained by one of ordinary skill in the art using known techniques (see, e.g., Lieberman, Pharmaceutical Dosage Forms (vols. 1-3, 1992); Lloyd, The Art, Science and Technology of Pharmaceutical Compounding (1999); and Pickar, Dosage Calculations (1999)).

[0038] As used in this disclosure, the term "standard control" refers to a sample containing a predetermined amount of an analyte (e.g., a predetermined DNA / mRNA or protein) to indicate the amount or concentration of that analyte present in such a sample taken from an average healthy subject who does not suffer from or is not at risk of developing a given disease or condition (e.g., Alzheimer's disease). When used in the context of describing a value, the term may also be used to simply refer to the amount or concentration of that analyte present in a "standard control" sample.

[0039] The term "average" used in the context of describing healthy subjects who are not afflicted with and not at risk of developing a relevant disease or disorder (e.g., AD) refers to a randomly selected population of healthy humans who are not afflicted with and not at risk of developing the disease or disorder. " refers to a particular characteristic representative of a person, such as the level of a relevant protein in a sample (e.g., serum, plasma, or whole blood) from that person. This selected group should include a sufficient number of human subjects so that the average amount or concentration of the analyte of interest among these individuals reflects with reasonable accuracy the corresponding profile in the general population of healthy people. Optionally, the selected group of subjects can be chosen to have a background similar to that of the person being tested for exhibiting or being at risk for the relevant disease or disorder, such as a matched or comparable age, gender, ethnicity, medical history, etc.

[0040] As used in this disclosure, the terms "inhibit" or "inhibition" refer to any detectable negative effect on a biological process of interest or on the level of a biomarker (e.g., a protein). Typically, inhibition is reflected in a decrease of 10% or more, 20% or more, 30% or more, 40% or more, or 50% or more in one or more parameters indicative of said biological process or its downstream effect, or in the level of said biomarker, compared to a control in the absence of such inhibition. The terms "enhance" or "enhance" are defined in a similar manner, except that they indicate a positive effect, i.e., a positive change of at least 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 80% or more, 100% or more, 200% or more, 300% or more, or more, compared to a control. The terms "inhibitor" and "enhancement" are used, respectively, to refer to agents that exhibit such inhibitory or enhancing effects. The terms "increase," "decrease," "greater than," and "less than" are also used in a similar manner in this disclosure and are intended to represent a positive change in one or more predetermined parameters of 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 80% or more, 100% or more, 200% or more, 300% or more, or more, or a negative change in one or more predetermined parameters of 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 80% or more.

[0041] As used in this disclosure, the term "Chinese" refers to ethnic Chinese who themselves and their ancestors have resided in the historical territory of China, including mainland China and Hong Kong, for a period of time, such as the last three or more generations, four or more generations, five or more generations, six or more generations, seven or more generations, or eight or more generations, or the last 100, 150, 200, 250, or 300 years. (Detailed Description of the Invention)

[0042] I. Introduction Alzheimer's disease (AD) is one of the most common forms of dementia worldwide, accounting for 60-70% of all dementia cases. It is an irreversible degenerative brain disorder and a leading cause of death among older adults. The hallmarks of the disease are the deposition of extracellular beta-amyloid (Aβ) plaques and intracellular neurofibrillary tangles, resulting in declines in memory, reasoning, judgment, and motor skills, with symptoms worsening over time.

[0043] Currently, an estimated 35 million people worldwide are affected by AD. This number is expected to increase significantly to 100 million by 2050 due to longer life expectancies. There is no cure for AD, and the pathophysiology of the disease remains relatively unknown. There are only five drugs approved by the U.S. Food and Drug Administration (FDA) to treat AD, but these only alleviate symptoms rather than altering the pathology of the disease. This is because they cannot reverse the condition or prevent further deterioration, and are ineffective in severe cases. Therefore, early diagnosis and early therapeutic intervention are crucial for managing AD. AD affects the brain long before actual symptoms of memory loss or cognitive decline actually appear. Studies have confirmed that AD is a risk factor for AD. However, to date, there are no effective and reliable diagnostic tools for early detection of AD, and by the time patients are diagnosed with AD using currently used standard methods that involve subjective clinical assessment, the pathological symptoms are already at an advanced stage. The present disclosure provides a high-performance diagnostic method that utilizes one or more protein markers to determine AD risk to aid in early diagnosis.

[0044] II. Quantification of Marker Proteins A. Obtaining samples The first step in carrying out the present invention is to obtain a blood sample from a subject to be tested for determining the risk of developing AD or for monitoring the severity or progression of AD. The same type of sample should be collected from both the control group (normal individuals who are not affected by AD and do not have an increased risk for AD) and the test group (e.g., subjects to be tested for the possibility of AD or an increased risk for AD). For this purpose, standard procedures routinely used in hospitals or clinics are typically followed.

[0045] To detect the presence / amount of marker proteins or determine the risk of developing AD in a test subject, a blood sample from an individual patient may be collected, and the levels of relevant marker proteins (e.g., amyloid beta protein 40, amyloid beta protein 42, NfL, or one or more proteins listed in Tables 1-4) in serum / plasma or whole blood may be measured and compared with standard controls. If an increase or decrease in the levels of one or more of these marker proteins (according to the β values ​​of the proteins given in Tables 1-4) compared to the control levels is observed, the test subject is considered to have AD or to be at elevated risk for later development of the condition. To monitor disease progression or determine treatment effectiveness in AD patients, blood samples from an individual patient may be collected at different time points, so that measuring the levels of individual marker proteins can provide information indicative of the disease state. For example, if a patient's marker protein levels show a general trend of increasing or decreasing over time, the patient is considered to be improving in the severity of AD, or the treatment the patient has received is considered to be effective (according to the specific β values ​​of the protein markers shown in the tables). The absence of a substantial change in the marker protein levels in a patient indicates that the pathology of AD has not changed and that the treatment administered to the patient is ineffective.

[0046] Furthermore, the present inventors have devised a novel calculation method for creating a composite risk score based on levels of multiple marker proteins (e.g., amyloid beta protein 40, amyloid beta protein 42, NfL, or one or more proteins listed in Tables 1-4) to determine an individual's risk of AD or to determine the relative risk of AD between two or more individuals.

[0047] B. Sample Preparation for Protein Detection Blood samples from subjects are suitable for the present invention and can be obtained by well-known methods and as described in standard medical literature. In certain applications of the present invention, serum or plasma or whole blood may be the preferred sample type. In other cases, a whole blood sample may be used.

[0048] A blood sample is obtained from a subject to be tested or monitored for AD using the method of the present invention. Collection of blood samples from individuals is performed according to standard protocols commonly followed by hospitals or clinics. An appropriate amount of blood is collected and may be stored according to standard procedures before further preparation.

[0049] Analysis of marker proteins found in patient samples according to the present invention may be carried out using, for example, serum or plasma or whole blood. The preparation methods are well known to those skilled in the art.

[0050] C. Determination of Marker Protein Levels Any specific protein entity, such as amyloid-beta protein 40, amyloid-beta protein 42, NfL, or any of those listed in Tables 1-4, can be detected using a variety of immunological assays. In some embodiments, a sandwich assay can be performed by capturing the protein from a test sample using an antibody with specific binding affinity for the protein. The protein can then be detected using a labeled antibody with specific binding affinity for the protein. Such immunological assays can be performed using a microfluidic device, such as a microarray protein chip. A protein of interest (e.g., amyloid-beta protein 40, amyloid-beta protein 42, NfL, or one or more proteins listed in Tables 1-4) can also be detected by gel electrophoresis (e.g., two-dimensional gel electrophoresis) and Western blot analysis using specific antibodies. Alternatively, standard immunohistochemical techniques can be used to detect a given protein (e.g., amyloid-beta protein 40, amyloid-beta protein 42, NfL, or one or more proteins listed in Tables 1-4) using an appropriate antibody. Both monoclonal and polyclonal antibodies (including antibody fragments with the desired binding specificity) can be used to specifically detect polypeptides. Such antibodies and binding fragments thereof with specific binding affinity for a particular protein (e.g., amyloid beta protein 40, amyloid beta protein 42, NfL, or one or more proteins listed in Tables 1-4) can be generated by known techniques.

[0051] Other methods may also be employed to measure the levels of marker proteins in the practice of the present invention. For example, various methods based on mass spectrometry have been developed to rapidly and accurately quantify target proteins even in a large number of samples. These methods include triple quadrupole (Triple Q) instruments using multiple reaction monitoring (MRM) techniques, matrix-assisted laser desorption / ionization time-of-flight tandem mass spectrometry (MALDI), and the like. These involve highly sophisticated instruments such as time-of-flight (TOF / TOF), ion trap instruments using selective ion detection (SIM) mode, and electrospray ionization (ESI)-based QTOP mass spectrometers. See, for example, Pan et al., J Proteome Res. 2009 February; 8(2):787-797. Please refer to.

[0052] III. Establishing standard controls To establish a standard control for carrying out the method of the present invention, first select a group of healthy individuals who do not have AD or are not at increased risk of developing AD, as conventionally defined. These individuals, if applicable, fall within appropriate parameter ranges for the purpose of screening and / or monitoring AD using the method of the present invention. Optionally, these individuals have the same gender, age, or ethnic background as the test subject.

[0053] The health status of selected individuals is ascertained by well-established and routinely used methods, including, but not limited to, a general physical examination of the individuals and a general review of their medical history.

[0054] Furthermore, the selected group of healthy individuals should be of a reasonable size so that the average amount / average concentration of the marker protein(s) in serum or plasma or whole blood samples obtained from the group can reasonably be considered representative of normal or average levels in the general population of healthy people who do not have AD or are not at increased risk for AD. Preferably, the selected group is 10 or more, 20 or more, 30 or more. It includes more than 50 human subjects.

[0055] Once the average value of the marker protein is established based on the individual values ​​of each subject in the selected healthy control group, this average, median, or representative value or profile is considered as the standard control. The standard deviation is also determined in the same process. In some cases, separate standard controls may be established for separately defined groups with different characteristics such as age, gender, ethnic background, etc.

[0056] IV. Monitoring and Treatment In a related aspect, the present invention also provides methods of treatment for patients with AD upon detecting AD in the patient or detecting an increased risk of later developing AD in the patient. In some embodiments, the methods include providing a treatment to the subject upon determining that the subject has an increased risk for AD, such as an acetylcholinesterase inhibitor (such as donepezil, galantamine, or rivastigmine), memantine, a glutamate receptor blocker, citalopram, fluoxetine, paroxeine, sertraline, trazodone, lorazepam, oxazepam, or aripiprazole. ol, clozapine, haloperidol, olanzapine, quetiapine, risperidone, ziprasidone, nortriptyline, tricyclic antidepressants, benzodiazepines, temazepam, zolpidem, zaleplon, chloral hydrate, coenzyme Q10, ubiquinone, coral calcium, ginkgo biloba, huperzine A, omega-3 fatty acids, phosphatidylcholine serine, or any combination thereof.

[0057] In some cases, once the diagnostic method steps described above and in this disclosure are completed, and additional diagnostic tests are optionally performed to provide further confirmatory information (e.g., brain imaging via CT scan or other imaging techniques showing excessive loss of brain volume, or tests of cognitive ability showing accelerated decline), and if the patient is determined to already have AD or to be at significantly increased risk for later developing AD, an appropriate therapeutic or preventative regimen may be prescribed by a physician or other healthcare professional to treat the patient, manage / alleviate ongoing symptoms, or delay future disease onset. The U.S. Food and Drug Administration (FDA) has granted approval for a number of cholinesterase inhibitors, including donepezil (Aricept™, the only cholinesterase inhibitor approved to treat all stages of AD, including moderate to severe), rivastigmine (Exelon™, approved to treat mild to moderate AD), galantamine (Razadyne™, for mild to moderate patients), and memantine (Namenda™). Donepezil is the only cholinesterase inhibitor approved for treating all stages of AD, including moderate to severe. One or more of these drugs can be prescribed to treat patients diagnosed with AD according to the methods of the present invention. Another treatment option is the administration of trazodone, which is currently approved for use as an antidepressant and has been reported to be an effective drug for ameliorating AD symptoms.

[0058] For patients who are considered to be at high or increased risk for developing AD in the future but who have not yet shown any clinical symptoms, continuous monitoring, particularly at increased frequency, is also appropriate. For example, the patient may undergo more frequently scheduled periodic examinations (e.g., once every six months, once a year, or once every two years) to detect accelerated changes in cognitive ability. Suitable methods for such periodic monitoring include the General Practitioner Assessment of Cognition (GPCOG), Mini-Cog, Eight-item Informant Interview to Differentiate Aging and Dementia (AD8), and Short Scale Cognitive Assessment (SSCA). There are also other useful questionnaires, such as the Short Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). In addition, preventive treatment with trazodone may be recommended. do.

[0059] V. Kits and Devices The present invention provides compositions and kits for carrying out the methods disclosed herein to determine the level of a suitable marker protein in a subject's serum / plasma or whole blood. The compositions and kits can be used for a variety of purposes, such as detecting or diagnosing the presence of AD, determining the risk of developing the condition, and monitoring the progression of the condition in a patient, including determining the therapeutic efficacy of therapies administered for the condition among patients diagnosed with and treated for the disease.

[0060] Kits for performing assays to measure marker protein levels typically include at least one antibody useful for specific binding to the marker protein amino acid sequence. Optionally, the antibody is labeled with a detectable moiety. The antibody may be a monoclonal or polyclonal antibody. In some cases, the kit may include at least two different antibodies, one for specifically binding to the marker protein (i.e., a primary antibody) and another for detecting the primary antibody (i.e., a secondary antibody), which is often attached to a detectable moiety.

[0061] Typically, the kit also includes a suitable standard control, which represents the average value of the marker protein in serum, plasma, or whole blood of healthy subjects who do not suffer from or are not at increased risk of developing AD. In some cases, such a standard control may be provided in the form of a set value. Additionally, the kits of the present invention may provide instructions to guide the user in analyzing the test substance and determining the presence or risk of AD or disease status / progression in the test subject.

[0062] In further aspects, the present invention may be embodied in a device or a system including one or more such devices, capable of performing all or some of the method steps described in this disclosure. For example, in some cases, the device or system, upon receiving a serum, plasma, or whole blood sample collected from a subject being tested for detecting AD, assessing the risk of developing AD, or assessing disease state / progression, performs the following steps: (a) determine the amount or concentration of a marker protein in the sample, (b) compare the amount / concentration with a standard control, and (c) provide an output indicating whether AD is present in the subject, whether the subject has an increased risk of developing AD, or whether the patient has a higher risk of subsequently developing AD compared to another patient being tested. In other cases, the device or system of the present invention performs the tasks of steps (b) and (c) after step (a) is performed and the amount or concentration from (a) is input into the device. Preferably, the device or system is partially or fully automated. [Example]

[0063] The following examples are offered by way of illustration only, and not by way of limitation. Those of ordinary skill in the art will readily recognize a variety of non-critical parameters that could be changed or modified to yield essentially the same or similar results.

[0064] introduction Alzheimer's disease (AD) is the most common neurodegenerative disease that primarily affects individuals over the age of 65. AD is caused by the accumulation of amyloid-β (Aβ) plaques and tau in the brain. Characterized by the accumulation of proteinaceous neurofibrillary tangles, as well as synaptic dysfunction and neuronal loss 2 Symptoms of the disease include memory loss, impaired reasoning and judgment, and decreased motor skills. 3 An estimated 47 million people worldwide suffer from the disease, a number that is expected to rise to 132 million by 2050.4 However, due to an incomplete understanding of the disease and delayed diagnosis, no cure exists to date, making AD one of the greatest threats to public health worldwide.

[0065] Currently, the diagnosis of AD is mostly based on reviewing the medical history, standardized memory tests, and The adoption of imaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET), which detect structural changes in the brain and the presence of AD-related biomarkers Aβ and tau, as well as proteomic techniques that measure cerebrospinal fluid (CSF) levels of Aβ, tau, and neurofilament light polypeptide (NfL), has enabled more accurate diagnosis and disease classification. 5 However, the high costs of MRI and PET, and the invasiveness of lumbar puncture for cerebrospinal fluid collection, preclude their use in routine clinical testing and hinder their use for the early diagnosis of AD. With the number of AD cases increasing worldwide, it is important to develop less invasive and cost-effective diagnostic techniques to facilitate efficient AD screening and patient classification on a population scale.

[0066] Under these circumstances, a blood-based test for AD would be an ideal solution. Recent studies have shown that the levels of AD-related biomarkers (Aβ) in the blood of AD patients are significantly higher than those of other AD patients. 42 / 40 It was shown that changes in the ratio, tau, and NfL indicate pathological conditions and can be used for diagnostic purposes. 6 However, none of these biomarkers have sufficient diagnostic accuracy, which limits their potential for clinical use. 7One essential reason is that the peripheral blood system has a more complex structure and is not only influenced by the brain but also by other bodily systems, including the peripheral, immune, circulatory, and metabolic systems. Therefore, existing AD-related biomarkers cannot adequately capture disease-related phenotypic changes in the blood. In fact, studies have shown that cytokines and angiogenic proteins also have altered plasma levels in AD, and some of them have been experimentally validated for their contribution to the pathology of AD. 8 Therefore, to develop an accurate and sensitive blood-based diagnostic test for AD, more comprehensive proteomic studies are needed to fully capture the plasma signature of AD.

[0067] In this study, we measured plasma levels of AD-related biomarkers (Aβ and NfL) and also measured the levels of 429 plasma proteins in samples collected from 180 elderly individuals from the Hong Kong Chinese AD cohort. By integrating the plasma levels of these AD-related proteins, we developed an AD prediction model that largely distinguished AD patients from normal controls (NCs). Collectively, these findings provide a sophisticated blood-based strategy for determining AD risk.

[0068] Materials and Methods <Recruitment of Hong Kong Chinese AD Cohort> A cohort of Hong Kong Chinese participants was recruited from the Specialized Outpatient Department at The Chinese University of Hong Kong, Prince of Wales Hospital (n=106 and n=74 for AD and normal controls [NC], respectively). All participants were aged 60 years or older. Clinical diagnosis of AD was confirmed by the American Psychiatric Association (APA) [Academic Journal]. Association's Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) 9All participants underwent a medical history assessment, the Montreal Cognitive Assessment (MoCA) for cognitive function evaluation, and MRI neuroimaging. 10 Age, gender, educational background, illness Data for each individual were recorded, including history of cardiovascular disease, brain area volume, and white blood cell count. Patients with medical or psychiatric disorders were excluded. This study was conducted at the Prince of Wales Hospital of The Chinese University of Hong Kong and the Hong Kong University Hospital. The study was approved by the Department of Science and Technology. All participants provided written informed consent for both study participation and sample collection.

[0069] <Extraction of DNA and plasma from blood samples> Whole blood (3 mL) was collected from participants using K3EDTA tubes (VACUETTE). Blood samples were centrifuged at 2000 × g for 15 minutes to separate cell pellets and plasma. Plasma was collected, aliquoted, and stored at -80°C until use. The cell pellets were analyzed using a QIAsymphony SP platform. For genomic DNA extraction using the QIAsymphony DSP DNA Midi Kit (QIAGEN), a separate kit was prepared at the Center for Panoromics Science (Genomics and Bioinformatics Cores, University of California, San Diego, CA). The DNA was then sent to the University of Hong Kong (University of Hong Kong, Hong Kong, China). Genomic DNA was eluted with water or Elution Buffer ATE (QIAGEN) and stored at 4°C. DNA concentration was measured using a BioDrop μLITE+ (BioDrop).

[0070] Plasma protein detection: Plasma levels of 429 proteins were measured using the Olink biomarker panel, including Cardiometabolic, Cardiovascular II, Cardiovascular III, Cell regulation, Development, Immune response, Inflammation, Metabolism, Neuroexploratory, Neurology, Oncology II, Oncology III, and Organ damage. The "ATN" biomarker (i.e., Aβ) 40 / 42 Plasma levels of NF-light, tau, and neurofilament light polypeptide [NfL] were measured by the Quanterix NF-light Simoa Assay Advantage Kit and Neurology 3-Plex A Kit.

[0071] Whole-genome sequencing, variant calling, and principal component analysis Participants' DNA samples were submitted to Novogene for library construction and whole genome sequencing (WGS). Samples were sequenced on an Illumina Hiseq X (average depth: 5x). Genomic regions covering 500 kilobases upstream and downstream of candidate variants were analyzed using the GotCloud pipeline. 11 The genotype results, stored in a VCF file, were used for principal component analysis. The top five principal components were generated using PLINK software with the following parameters: -pca header tabs, --maf 0.05, --hwe 0.00001, and --not-chr xy.

[0072] <Analysis of the Association between Plasma Proteins and AD>: Using the R rntransform function of the GenABEL package, plasma protein levels were normalized based on rank. Changes in plasma proteins in AD were determined using the following linear model (βi is the weighting coefficient of the corresponding factor; ε is the intercept of the linear form) based on the association between the normalized protein levels and the AD phenotype: Normalized protein level ≒ β1AD + β2Age + β3Gender + β i Disease i + β j Principal Component (PC) j + ε and adjusting for age, gender, disease history, and population structure (i.e., the top 5 principal components).

[0073] <AD Prediction Score Generation>: For each prediction model, the plasma levels of candidate proteins and the AD phenotype information of participants in the discovery cohort were fitted into a logistic regression model using the following formula [Number] to generate the weighting coefficient (βi) and intercept (ε) of the corresponding candidate protein. Individual AD prediction scores were calculated using the following linear model based on the plasma levels of candidate proteins and the corresponding weighting coefficient (βi) and intercept (ε): [Number] The predicted AD risk stage was defined by the distribution of AD prediction scores and divided into a low-risk group, a medium-risk group, and a high-risk group.

[0074] <Evaluation of Prediction Accuracy>: Using the plot.roc function and auc function in R, the receiver operating characteristic (ROC) curve and the corresponding area under the curve (AUC) of the prediction model for AD risk prediction were created. The prediction accuracy of the model was indicated by the value of AUC.

[0075] ​Statistical analysis and data visualization: Investigators performing protein detection were blinded to the phenotypes of human participants. The significance of associations between candidate factors in human participants was assessed by linear regression analysis adjusting for age, sex, disease history, and population structure (i.e., the top five principal components obtained from principal component analysis using whole-genome sequence data). The significance level was set at P<0.05. All other statistical plots were generated using GraphPad Prism version 8.0.

[0076] Example I. Models Using Individual Plasma Proteins to Determine AD Risk The levels of 429 plasma proteins (Table 2) were measured in samples collected from the Hong Kong Chinese AD cohort (n = 180). All 429 plasma proteins showed significant changes in AD compared with NC (p < 0.05; Table 2). In particular, 74 novel plasma proteins showed strong changes in AD (Table 1). Based on the altered plasma levels of the 74 or 429 plasma proteins in AD patients, a diagnostic tool was developed to compare AD risk between individuals using information from plasma proteins. If an individual has higher plasma levels of proteins that are elevated in the blood of AD (β > 0) or lower plasma levels of proteins that are decreased in the blood of AD (β < 0; Tables 1 and 2), that individual is at higher risk of AD.

[0077] Example II: Models by integrating 12 or 19 plasma proteins in predicting AD risk By integrating the plasma levels of 12 proteins (i.e., CD164, CETN2, GAMT, GSAP, hK14, LGMN, NELL1, PRDX1, PRKCQ, TMSB10, VAMP5, and VPS37A; Table 3), we developed a composite prediction model that accurately predicted AD risk (AUC = 0.8916; Figure 1A). An AD risk scoring system was constructed by assigning an AD prediction score to individuals. The resulting score distinguished between NC and AD patients (Table 5 and Figure 1B). Based on the prediction score, three AD risk stages were further proposed to predict disease risk. Individuals with an AD prediction score below 0.25 are considered to have a low risk for AD. In contrast, individuals with a score between 0.25 and 0.79 or a score greater than 0.79 are considered to have a moderate or high risk for AD, respectively.

[0078] By further integrating the plasma levels of seven plasma proteins (i.e., AOC3, CASP-3, CD8A, KLK4, LIF-R, LYN, and NFKBIE) into the 12-protein model (Table 4), we developed a mixed prediction model that further improved the prediction of AD risk (AUC = 0.9661; Figure 2a). This AD prediction score better distinguished NC from AD patients (Table 6 and Figure 2b). Individuals with an AD prediction score below 0.21 are considered to have low AD risk. In contrast, individuals with scores between 0.21 and 0.8 or greater than 0.8 are considered to have moderate or high risk for AD, respectively.

[0079] Example III: Combined Models of Plasma AN Biomarkers and 12 or 19 Plasma Proteins in Predicting AD Risk Then, plasma Aβ 42 / 40We developed a combined prediction model by integrating the ratio and plasma NfL levels (AN) into the 12-protein model or the 19-protein model. Both integrated models improved AD prediction (AUC = 0.9456 and 0.9855 for AN + 12 proteins and AN + 19 proteins, respectively; Figures 3a and 4a). Furthermore, these two combined models produced AD prediction scores that clearly separated NC and AD patients (Tables 7-8 and Figures 3b and 4b). For the models utilizing AN and the 12 proteins, individuals with AD prediction scores below 0.2, between 0.2 and 0.8, and above 0.8 were considered to have low, moderate, and high AD risk, respectively. For the AN and 19-protein model, individuals with AD prediction scores below 0.3, between 0.3 and 0.8, and above 0.8 were considered to have low, moderate, and high AD risk, respectively. Collectively, these results demonstrate that our AD risk prediction model maximizes the impact of each candidate plasma protein on pathogenesis and functions as a high-performance strategy for predicting AD risk.

[0080] All patents, patent applications, and related documents cited in this application, including GenBank Accession Numbers and equivalents, are hereby incorporated by reference. Applications and other publications are incorporated by reference in their entirety for all purposes.

[0081] Table 1. List of 74 plasma proteins associated with Alzheimer's disease phenotypes β: effect size [Table 1-1]

[0082] [Table 1-2]

[0083] Table 2. List of 429 plasma proteins associated with Alzheimer's disease phenotypes β: effect size [Table 2-1]

[0084] [Table 2-2]

[0085] [Table 2-3]

[0086] [Table 2-4]

[0087] [Table 2-5]

[0088] [Table 2-6]

[0089] [Table 2-7]

[0090] [Table 2-8]

[0091] [Table 2-9]

[0092] [Table 2-10]

[0093] [Table 2-11]

[0094] Table 3. List of 12 plasma proteins used to predict and assess Alzheimer's disease risk β: effect size [Table 3]

[0095] Table 4. List of 19 plasma proteins used to predict and assess Alzheimer's disease risk. β: effect size [Table 4]

[0096] Table 5. Weighting coefficients (β) for the model using 12 plasma proteins i ) and intercept (ε) [Table 5]

[0097] Table 6. Weighting coefficients (β) for the model using 19 plasma proteins i ) and intercept (ε) [Table 6]

[0098] Table 7. Plasma Aβ 42 / 40 The ratio, plasma NfL, and weighting coefficients (β) for the model using 12 plasma proteins i ) and intercept (ε) [Table 7]

[0099] Table 8. Plasma Aβ 42 / 40 The weighting coefficients (β) for the model using the ratio, plasma NfL, and 19 plasma proteins were calculated. i ) and intercept (ε) [Table 8]

[0100] Table 9. Aβ in plasma 42 / 40 Weighting factors (β i ) [Table 9]

[0101] Reference materials 1. Alzheimer's Association. (2016). 2016 Alzheimer's disease facts and figures. Alzheimer's & Dementia, 12(4), 459-509. 2. McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, EM (1984). Clinical diagnosis of Alzheimer's disease: Report of the NINCDS-ADRDA Work Group* under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology, 34(7), 939-939. 3. Carrillo, Maria C., et al. "Revisiting the Framework of the National Institute on Aging-Alzheimer's Association Diagnostic Criteria." Alzheimer's & Dementia 9.5 (2013): 594-601. 4. Prince, MJ (2015). World Alzheimer's Report 2015: the global impact of dementia tia: an analysis of prevalence, incidence, cost and trends. Alzheimer's Disease International. 5. Jack Jr , CR , Bennett , DA , Blennow , K , Carrillo , MC , Dunn , B , Haeberlein , SB , ... & Liu , E (2018). NIA‐AA research framework: toward a biological definition of Alzheimer's disease. Alzheimer's & Dementia, 14(4), 535-562. 6. Nakamura, A., Kaneko, N., Villemagne, VL, Kato, T., Doecke, J., Dore(eは). Baker, V., … & Tomita, T. (2018). High performance plasma amyloid-β biomarkers for Alzheimer's disease. Nature, 554(7691), 249. 7. Preische, O., Schultz, S. A., Apel, A., Kuhle, J., Kaeser, S. A., Barro, C.,... & Voglein, J. (2019). Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer’s disease. Nature medicine, 25(2), 277-283. 8. Religa, P., Cao, R., Religa, D., Xue, Y., Bogdanovic, N., Westaway, D.,... & Cao, Y. (2013). VEGF significantly restores impaired memory behavior in Alzheimer's mice by improvement of vascular survival. Scientific reports, 3, 2053. 9. American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5(registered trademark)). (Washington, DC, 2013). 10. Pangman, Verna C., Jeff Sloan, and Lorna Guse. "An examination of psychometric properties of the mini-mental state examination and the standardized mini-mental state examination: implications for clinical practice." Applied Nursing Research 13.4 (2000): 209-213. 11. Zhou, Xiaopu, et al. "Non-coding variability at the APOE locus contributes to the Alzheimer’s risk." Nature communications 10.1 (2019): 1-16.

Claims

1. (1) comparing the level of any one protein selected from Tables 1-4 in the plasma or serum or whole blood of a subject with a standard control level of the same protein found in the plasma or serum or whole blood of an average healthy subject who is not afflicted with or at increased risk for AD; (2) detecting an increase in the level of the protein (having a positive β value in Table 1, Table 2, Table 3, or Table 4) in the subject's plasma, serum, or whole blood from the standard control level, or detecting a decrease in the level of the protein (having a negative β value in Table 1, Table 2, Table 3, or Table 4) in the subject's plasma, serum, or whole blood from the standard control level; and (3) determining that the subject has an increased risk for AD; 1. A method for determining the risk of Alzheimer's disease (AD) in a subject, comprising:

2. 2. The method of claim 1, wherein the protein is selected from Table 1.

3. 3. The method of claim 2, wherein the protein is selected from Table 3.

4. 4. The method of claim 3, wherein the protein is selected from Table 4.

5. The method of any one of claims 1 to 4, further comprising, prior to step (1), measuring the level of said protein in said plasma or serum or whole blood.

6. 6. The method of claim 5, further comprising obtaining a sample of plasma, serum or whole blood from the subject prior to said measuring step.

7. (i) comparing the level of any one of the proteins selected from Tables 1-4 in the plasma or serum or whole blood of a first subject with the level of the same protein in the plasma or serum or whole blood of a second subject; (ii) detecting that the level of the protein in the plasma or serum or whole blood of the second subject is higher than the level of the protein in the plasma or serum or whole blood of the first subject (having a positive β value in Table 1, Table 2, Table 3 or Table 4), or that the level of the protein in the plasma or serum or whole blood of the second subject is lower than the level of the protein in the plasma or serum or whole blood of the first subject (having a negative β value in Table 1, Table 2, Table 3 or Table 4); and (iii) determining that the second subject has a higher risk of AD than the first subject; 1. A method for determining the risk of Alzheimer's disease (AD) in two subjects, comprising:

8. 8. The method of claim 7, wherein the protein is selected from Table 1.

9. 9. The method of claim 8, wherein the protein is selected from Table 3.

10. 10. The method of claim 9, wherein the protein is selected from Table 4.

11. The method of any one of claims 7 to 10, further comprising, prior to step (i), measuring the level of said protein in said plasma or serum or whole blood.

12. and obtaining a sample of plasma, serum, or whole blood from said subject prior to said measuring step. The method of claim 11 , comprising:

13. A kit for determining the risk of Alzheimer's disease (AD) in a subject, comprising reagents capable of measuring the level of each of any 5, 10, 15, or 20 proteins independently selected from Table 2 in the subject's plasma, serum, or whole blood.

14. 14. The kit of claim 13, wherein the protein is selected from Table 1.

15. 15. The kit of claim 14, wherein the protein is selected from Table 3.

16. 16. The kit of claim 15, wherein the protein is selected from Table 4.

17. The kit of claim 13, further comprising reagents capable of measuring the levels of each of amyloid beta protein 42, amyloid beta protein 40, and neurofilament light polypeptide (NfL) in the subject's plasma, serum, or whole blood.

18. 14. The kit of claim 13, further comprising a standard control for each of the proteins that reflects the level of the same protein found in plasma, serum, or whole blood of an average healthy subject who is not afflicted with or at increased risk for AD.

19. 1. A detection chip for determining the risk of Alzheimer's disease (AD) in a subject, comprising: a solid substrate; and reagents capable of determining the level of each of any 5, 10, 15, or 20 proteins independently selected from Table 2 in the subject's plasma, serum, or whole blood, wherein each reagent is immobilized at an addressable location on the substrate.

20. 20. The chip of claim 19, wherein the protein is selected from Table 1.

21. 21. The chip of claim 20, wherein the protein is selected from Table 3.

22. 22. The chip of claim 21, wherein the protein is selected from Table 4.

23. (1) Formula: [Equation 1] calculating a prediction score by inputting a set of values ​​into (2) determining that subjects with a score of 0 to 0.25±0.05 have a low risk of AD, determining that subjects with a score of more than 0.25±0.05 to 0.80±0.01 have a moderate risk of AD, and determining that subjects with a score of more than 0.80±0.01 to 1 have a high risk of AD; Including, The set of values ​​includes the levels of each of the 12 proteins listed in Table 3 in plasma, serum, or whole blood, and the weighting coefficients (β ｉ ) and intercept (ε) are given in Tables 5-8. A method for determining the risk of Alzheimer's disease (AD) in a subject.

24. The set of values ​​consists of the levels of each of the 12 proteins in Table 3 in plasma or serum or whole blood, with corresponding weighting coefficients (β ｉ ) and intercept (ε) are given in Table 5, 24. The method of claim 23, wherein subjects with a score between 0 and 0.25 have a low risk for AD, subjects with a score between greater than 0.25 and 0.79 have a moderate risk for AD, and subjects with a score between greater than 0.79 and 1 have a high risk for AD.

25. The set of values ​​consists of the levels of each of the 19 proteins in Table 4 in plasma or serum or whole blood, with corresponding weighting coefficients (β ｉ ) and intercept (ε) are given in Table 6, 24. The method of claim 23, wherein subjects with a score between 0 and 0.21 have a low risk for AD, subjects with a score between greater than 0.21 and 0.8 have a moderate risk for AD, and subjects with a score between greater than 0.8 and 1 have a high risk for AD.

26. The set of values ​​consists of the ratio of amyloid β protein 42 level to amyloid β protein 40 level in plasma, serum, or whole blood, the level of NfL in plasma, serum, or whole blood, and the level of each of the 12 proteins listed in Table 3 in plasma, serum, or whole blood, with corresponding weighting coefficients (β ｉ ) and intercept (ε) are set forth in Table 7, wherein subjects with a score between 0 and 0.20 have a low risk for AD, subjects with a score greater than 0.20 to 0.80 have a moderate risk for AD, and subjects with a score greater than 0.80 to 1 have a high risk for AD.

27. The set of values ​​consists of the ratio between the amyloid beta protein 42 level and the amyloid beta protein 40 level in plasma or serum or whole blood, the level of NfL in plasma or serum or whole blood, and the level of each of the 19 proteins listed in Table 4 in plasma or serum or whole blood, with corresponding weighting coefficients (β ｉ ) and intercept (ε) are set forth in Table 8, wherein the subjects with a score between 0 and 0.30 have a low risk for AD, the subjects with a score between greater than 0.30 and 0.80 have a moderate risk for AD, and the subjects with a score between greater than 0.80 and 1 have a high risk for AD.

28. The method of any one of claims 23 to 27, further comprising, prior to step (1), measuring the level of said protein in plasma or serum or whole blood.

29. 30. The method of claim 28, further comprising obtaining a sample of plasma or serum or whole blood from the subject prior to said measuring step.

30. (i) The set of values ​​is expressed as [Equation 2] Calculating a prediction score for each of the two subjects by inputting (ii) determining that subjects with higher scores are at higher risk for AD than other subjects; Including, The set of values ​​may include a ratio of amyloid beta protein 42 level to amyloid beta protein 40 level in plasma, serum, or whole blood, a level of NfL in plasma, serum, or whole blood, a level of at least one of the proteins listed in Table 2 in plasma, serum, or whole blood, It contains three levels with corresponding weighting factors (β ｉ ) are given in Table 1, Table 2, Table 3, Table 4 and Table 9, A method for determining the risk of Alzheimer's disease (AD) between two subjects.

31. The set of values ​​includes the ratio of amyloid beta protein 42 level to amyloid beta protein 40 level in plasma or serum or whole blood, the level of NfL in plasma or serum or whole blood, the level of any combination of proteins listed in Table 2 in plasma or serum or whole blood, and the corresponding weighting factors (β ｉ 31. The method of claim 30, wherein the .alpha.-to- ...

32. The set of values ​​includes a ratio of amyloid beta protein 42 level to amyloid beta protein 40 level in plasma or serum or whole blood, a level of NfL in plasma or serum or whole blood, a level of at least one of the proteins listed in Table 1, Table 3 or Table 4 in plasma or serum or whole blood, and a corresponding weighting factor (β ｉ 31. The method of claim 30, wherein the .alpha.-to- ...

33. The set of values ​​includes a ratio of amyloid beta protein 42 level to amyloid beta protein 40 level in plasma, serum, or whole blood, a level of NfL in plasma, serum, or whole blood, and levels of at least five proteins independently selected from Table 1, Table 3, or Table 4 in plasma, serum, or whole blood, with corresponding weighting factors (β ｉ 31. The method of claim 30, wherein the .alpha.-to- ...

34. The set of values ​​includes a ratio of amyloid beta protein 42 level to amyloid beta protein 40 level in plasma, serum, or whole blood, a level of NfL in plasma, serum, or whole blood, and levels of at least 10 proteins independently selected from Table 1, Table 3, or Table 4 in plasma, serum, or whole blood, with corresponding weighting factors (β ｉ 31. The method of claim 30, wherein the .alpha.-to- ...

35. 35. The method of any one of claims 30 to 34, further comprising, prior to step (i), measuring the level of each of said proteins in plasma or serum or whole blood.

36. 36. The method of claim 35, further comprising obtaining a sample of plasma or serum or whole blood from the subject prior to said measuring step.

37. 1. A method for determining the efficacy of a therapeutic agent for treating Alzheimer's disease (AD) in a subject, comprising: (1) comparing the level of any one of proteins selected from Tables 1 to 4 in the plasma, serum, or whole blood of the subject before and after administration of the therapeutic agent to the subject; (2) detecting a decrease in the level of the protein (having a positive β value in Table 1, Table 2, Table 3, or Table 4) in the plasma, serum, or whole blood of the subject after administration of the therapeutic agent, or an increase in the level of the protein (having a negative β value in Table 1, Table 2, Table 3, or Table 4) in the plasma, serum, or whole blood of the subject; and (3) determining that the therapeutic agent is effective for treating AD; The method comprising:

38. 38. The method of claim 37, wherein the protein is selected from Table 1.

39. 38. The method of claim 37, wherein the protein is selected from Table 3.

40. 38. The method of claim 37, wherein the protein is selected from Table 4.

41. 41. The method of any one of claims 37 to 40, further comprising, prior to step (1), measuring the level of said protein in plasma or serum or whole blood before and after administration.

42. 42. The method of claim 41, further comprising obtaining plasma or serum or whole blood samples from the subject before and after administration prior to said measuring step.

43. The method of any one of claims 1 to 12 and claims 23 to 42, wherein the subject is of Chinese descent.

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