Method for analyzing subject-derived antibodies

Abstract

To provide a method for accurately analyzing an antibody contained in saliva by affinity chromatography using a column packed with an insoluble carrier immobilized with Fc binding protein.SOLUTION: Problems are solved by collecting saliva by using a sponge body.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a minimally invasive method for analyzing antibodies derived from a subject, and particularly to a minimally invasive method for accurately analyzing antibodies derived from a subject using saliva derived from the subject. [Background technology]

[0002] It is known that the sugar chain structures attached to antibodies contained in blood samples from subjects with diseases such as rheumatism differ from those of antibodies contained in blood samples from healthy individuals (Non-Patent Documents 1 and 2). This suggests that by detecting differences in the sugar chain structures attached to antibodies contained in blood samples from subjects, it is possible to detect the presence or absence of a disease in the subject, the risk of developing a disease, the degree of disease progression, etc.

[0003] LC-MS analysis, which includes cleavage of the glycans, has been used to analyze the sugar chain structures attached to antibodies (Patent Documents 1 and 2). However, LC-MS analysis requires very complicated procedures and is time-consuming. A simpler method for analyzing the sugar chain structures is affinity chromatography. For example, Patent Document 3 reports a method in which antibodies (gamma globulins) contained in a sample derived from a subject are separated based on differences in sugar chain structure by affinity chromatography using a column packed with an insoluble carrier on which an Fc-binding protein capable of specifically binding to the Fc region of an antibody is immobilized, and the obtained separation pattern is used to detect the presence or absence of a disease, the risk of developing a disease, the degree of disease progression, and / or the degree of aging in the subject.

[0004] In Patent Document 3, blood samples are mainly used as samples derived from subjects. However, collecting blood samples requires puncture, which is an invasive procedure. Therefore, it would be desirable to be able to analyze less invasive samples, such as saliva. However, saliva contains many impurities, and it has not been possible to analyze saliva with the same accuracy as blood samples. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2016-194500 A [Patent Document 2] Japanese Patent Application Laid-Open No. 2016-099304 [Patent Document 3] WO2019 / 244901 [Non-patent literature]

[0006] [Non-Patent Document 1] Science, 320, 373(2008) [Non-patent document 2] Nature Communication, 7, 11205(2016) Summary of the Invention [Problem to be solved by the invention]

[0007] An object of the present invention is to provide a method for accurately analyzing antibodies contained in saliva by affinity chromatography using a column packed with an insoluble carrier on which an Fc-binding protein has been immobilized. [Means for solving the problem]

[0008] As a result of intensive research conducted by the present inventors to solve the above-mentioned problems, they discovered a method that can accurately measure differences in the sugar chain structures of gamma globulins (antibodies) contained in a sample derived from a subject's saliva, and thus completed the present invention.

[0009] That is, the present invention can be exemplified as follows.

[0010] [1] A method for analyzing an antibody, comprising the steps of adding an antibody-containing sample from a subject to a column packed with an insoluble carrier to which an Fc-binding protein has been immobilized, thereby adsorbing the antibody onto the carrier, and eluting the antibody adsorbed onto the carrier using an eluent to obtain an antibody separation pattern, wherein the antibody-containing sample is a saliva sample, and the saliva sample is collected using a sponge.

[0011] [2] The method according to [1], wherein the Fc-binding protein is a human Fcγ receptor.

[0012] [3] The method according to [2], wherein the human Fcγ receptor is a polypeptide selected from any one of the following (i) to (iii): (i) a polypeptide comprising at least the amino acid residues from glycine at position 17 to glutamine at position 192 of the amino acid sequence set forth in SEQ ID NO: 1, with the proviso that at least valine at position 176 of SEQ ID NO: 1 is substituted with phenylalanine; (ii) A polypeptide comprising at least the amino acid residues from glycine at position 17 to glutamine at position 192 of the amino acid sequence set forth in SEQ ID NO: 1, with the proviso that at least valine at position 176 of SEQ ID NO: 1 is substituted with phenylalanine, and further having substitution, deletion, insertion, and / or addition of one or several amino acid residues at one or several positions other than position 176, and having antibody-binding activity; (iii) An amino acid sequence having 70% or more homology to the entire amino acid sequence set forth in SEQ ID NO: 1, in which the amino acid residue corresponding to valine at position 176 in SEQ ID NO: 1 is substituted with phenylalanine in the amino acid sequence from glycine at position 17 to glutamine at position 192, with the proviso that the substitution remains and the polypeptide has antibody-binding activity.

[0013] [4] A method for detecting the presence or absence of a disease, the risk of developing a disease, the degree of disease progression, and / or the degree of aging in a subject, using the characteristics of the separation pattern obtained by any of the methods described in [1] to [3] as an index.

[0014] [5] The method according to [4], wherein the feature of the separation pattern is the area and / or height of a peak present in the pattern, or the area % and / or height % of the peak. [Effects of the Invention]

[0015] The present invention relates to a method for analyzing antibodies, comprising the steps of adding a saliva sample from a subject to a column packed with an insoluble carrier on which an Fc-binding protein has been immobilized, allowing antibodies contained in the sample to adsorb to the carrier, and eluting the antibodies adsorbed to the carrier with an eluent to obtain an antibody separation pattern. The method is characterized in that the saliva sample is collected using a sponge, eliminating the need for pretreatment to remove contaminants and enabling antibody analysis of a saliva sample from a subject with the same accuracy as antibody analysis of a blood sample from a subject. Because subject-derived antibodies (gamma globulins) are closely associated with disease, the antibody analysis method of the present invention allows accurate determination of the presence or absence of disease, the risk of disease onset, the degree of disease progression, and / or the degree of aging in a subject, while minimizing the burden on the subject. [Brief explanation of the drawings]

[0016] [Figure 1] FIG. 1 shows an example of the separation patterns of a standard substance and a measurement sample obtained by analyzing an antibody using a column packed with an Fc-binding protein-immobilized gel. [Figure 2] Figure 1 shows the separation patterns obtained when antibodies were analyzed using a column packed with Fc-binding protein-immobilized gel, using serum collected from healthy individuals, saliva collected using sponge bodies, and saliva collected by salivation as measurement samples. a) shows the results when serum was used, b) when saliva was collected using sponge bodies, and c) when saliva was collected by salivation. DETAILED DESCRIPTION OF THE INVENTION

[0017] The present invention will be described in detail below.

[0018] The present invention provides a method for analyzing gamma globulins contained in a saliva sample, by adsorbing gamma globulins (hereinafter also referred to as "antibodies") contained in the saliva sample to an insoluble carrier onto which an Fc-binding protein has been immobilized, and then eluting the gamma globulins adsorbed to the carrier with an eluent to obtain a separation pattern of the gamma globulins.

[0019] Specifically, the method of the present invention comprises the following steps: <1> from <3> The method may be a method for analyzing gamma globulins (antibodies) contained in a sample derived from saliva of a subject, comprising: <1> collecting a saliva sample from a subject using a sponge body; <2> adding the collected saliva sample to a column packed with an insoluble carrier onto which an Fc-binding protein has been immobilized, and allowing the antibody contained in the sample to be adsorbed onto the carrier; <3> adding an equilibration solution to the column to equilibrate the column; <4> A step of adding an eluate to the column to elute the antibodies adsorbed to the carrier, thereby obtaining a separation pattern of the antibodies.

[0020] Furthermore, a method for detecting the presence or absence of a disease, the risk of developing a disease, the degree of progression of a disease, and / or the degree of progression of aging in a subject may be provided using the characteristics of the separation pattern as an index.

[0021] From the above, the method of the present invention comprises the steps described above <1> from <4> In addition, the following process <5> from <6> The method may further comprise the steps of: <5> determining a characteristic of said separation pattern; <6> A step of detecting the presence or absence of a disease, the risk of developing a disease, the degree of progression of a disease, and / or the degree of progression of aging in a subject using the above-mentioned characteristics as an index.

[0022] Below is the process <1> "Sample collection process", <2> "Adsorption process" <3> "Equilibration step", step <4> "Elution step" and step <5> "Analysis process" and "Process" <6> This is also called the "detection step."

[0023] <1> Sampling process In the present invention, the term "subject" simply refers to a human individual who is the subject of measurement or risk detection. The subject may be male or female. The subject may be of any age, including children, adolescents, middle-aged people, and elderly people.

[0024] In the present invention, the term "saliva sample" refers to a sample derived from saliva that contains or may contain antibodies obtained from a subject. Examples of saliva samples include samples that may contain saliva-derived components such as saliva and gingival crevicular fluid, antibodies isolated from such samples, and samples that may contain antibodies contained in such samples.

[0025] The present invention is characterized in that a saliva sample is collected from a subject using a sponge. By using a sponge that can hold a saliva sample when placed in the mouth, gamma globulins (antibodies) derived from the sample can be analyzed with high accuracy. The material of the sponge is not particularly limited as long as it can be molded into a sponge shape. Examples of materials include plant-derived fibers such as cotton and hemp; animal-derived fibers such as silk, cashmere, and wool; synthetic fibers such as nylon, polyester, and polyamide; chemical fibers including regenerated cellulose fibers such as viscose rayon and cupra (cuprammonium rayon); and synthetic resins such as polyurethane, ethylene-propylene copolymer, and melamine.

[0026] The saliva samples collected by the above method can be used as they are or after appropriate pretreatment as described below. <2> The pretreatment may be carried out by a standard method such as centrifugation, column purification, or concentration. After purifying the gamma globulin (antibody) in the saliva sample, <2> The saliva sample may be used in the adsorption step in the form of a solution containing an antibody. That is, the saliva sample is appropriately prepared in the form of a solution containing an antibody. <2> For example, the saliva sample or a pre-treated sample thereof as exemplified above may be dissolved, suspended, dispersed, or solvent-exchanged in a liquid medium as appropriate, and then used as a solution containing an antibody. <2> Such liquid media may be used in the adsorption process. <3> The same description as for the equilibration liquid used in the equilibration step can be applied mutatis mutandis. The liquid medium may or may not be the same as the equilibration liquid. The saliva sample that has been subjected to the pretreatment and the solution containing the antibody are collectively referred to as the "saliva sample" in this specification.

[0027] <2> Adsorption process The adsorption step involves placing the Fc-binding protein in a column packed with an insoluble carrier onto which the Fc-binding protein has been immobilized. <1> This is a step in which the saliva sample from the subject collected in the sample collection step is added, and antibodies contained in the sample are adsorbed onto the carrier.

[0028] In the present invention, "antibody (gamma globulin)" refers to a molecule containing an Fc region. An antibody may consist of an Fc region, or may contain other regions in addition to the Fc region. An example of an Fc region is the Fc region of an immunoglobulin. An antibody may have a glycosylated chain. For example, an antibody may have a glycosylated chain at least in its Fc region. An antibody may be a monoclonal antibody or a polyclonal antibody. An example of an antibody is an immunoglobulin. An example of an immunoglobulin is IgG, IgM, IgA, IgD, and IgE. An example of an immunoglobulin is IgG, in particular. An example of an IgG is IgG1, IgG2, IgG3, and IgG4. Among the sugar chains attached to antibodies, those that may particularly contribute to antibody separation include G0, G0F, G1, G0F+GN, G1Fa, G1Fb, G1F+GN, G2, G2F, G1F+SA, G2F+SA, G2F+2SA, G2F+GN, G2+SA, G2+2SA, S1, S2, and S3 (GN stands for bisecting GlcNAc (N-acetylglucosamine), F for fucose, and SA for sialic acid).

[0029] Human-derived antibodies typically contain antibodies with sialic acid (SA). The content of sialic acid in human-derived antibodies can be, for example, about 0.1 to 20% by weight of the total antibody content. Human-derived antibodies often have two sialic acids bound to the terminal sugar chains. Furthermore, human-derived antibodies typically contain bisecting GlcNAc (GN) in an amount of about 1 to 20% by weight of the total antibody content. On the other hand, hamster- and mouse-derived antibodies typically do not contain bisecting GlcNAc and have zero or one sialic acid bond at the terminal sugar chains.

[0030] The antibody subjected to the adsorption step may be a mixture containing multiple types of antibody molecules. Specifically, the antibody subjected to the adsorption step may be a mixture containing multiple types of antibody molecules with different sugar chain structures. More specifically, the antibody subjected to the adsorption step may be a mixture containing multiple types of antibody molecules with different sugar chain structures attached to the Fc region.

[0031] In the present invention, the term "Fc-binding protein" is not particularly limited, as long as it is a polypeptide that has the ability to bind to the Fc region of an antibody contained in a sample and can recognize differences in the antibody's sugar chain structure (e.g., the sugar chain structure of the Fc region). For example, when the antibody is derived from a human, the Fc-binding protein can be a human Fc-binding protein. Preferred examples of human Fc-binding proteins include human Fc receptors. Human Fc receptors include the human Fcγ receptor, which is a receptor for human immunoglobulin G (IgG), the human Fcα receptor, which is a receptor for human immunoglobulin A (IgA), the human Fcδ receptor, which is a receptor for human immunoglobulin D (IgD), and the human Fcε receptor, which is a receptor for human immunoglobulin E (IgE), and any of these receptors can be used as the human Fc-binding protein in the present invention. As used herein, a "human-derived antibody" is any gamma globulin (antibody) that has at least a human-derived Fc region, and may be a human antibody, a humanized antibody, or a chimeric antibody between a human and a non-human animal.

[0032] Specific examples of human Fcγ receptors include polypeptides comprising at least a partial sequence of the extracellular region of human FcγRI (CD64), human FcγRIIa (CD32a), human FcγRIIb (CD32b), human FcγRIIc (CD32c), human FcγRIIIa (CD16a), or human FcγRIIIb (CD16b), as well as polypeptides in which some of the amino acid residues constituting the polypeptides have been substituted, deleted, inserted, and / or added. Among these, polypeptides comprising at least a partial sequence of the extracellular region of human FcγRIIIa and polypeptides in which some of the amino acid residues constituting the polypeptides have been substituted, deleted, inserted, and / or added are preferred as human Fcγ receptors used as human Fc-binding proteins in the present invention.

[0033] Specific examples of polypeptides comprising at least a partial sequence of the extracellular region of human FcγRIIIa, or polypeptides in which some of the amino acid residues constituting such polypeptides have been substituted, deleted, inserted, and / or added, include the polypeptides described in (i) to (iii) below. (i) a polypeptide comprising at least the amino acid residues from glycine at position 17 to glutamine at position 192 of the amino acid sequence set forth in SEQ ID NO: 1, with the proviso that at least valine at position 176 of SEQ ID NO: 1 is substituted with phenylalanine; (ii) A polypeptide comprising at least the amino acid residues from glycine at position 17 to glutamine at position 192 of the amino acid sequence set forth in SEQ ID NO: 1, with the proviso that at least valine at position 176 of SEQ ID NO: 1 is substituted with phenylalanine, and further having substitution, deletion, insertion, and / or addition of one or several amino acid residues at one or several positions other than position 176, and having antibody-binding activity; (iii) An amino acid sequence having 70% or more homology to the entire amino acid sequence set forth in SEQ ID NO: 1, in which the amino acid residue corresponding to valine at position 176 in SEQ ID NO: 1 is substituted with phenylalanine in the amino acid sequence from glycine at position 17 to glutamine at position 192, with the proviso that the substitution remains and the polypeptide has antibody-binding activity.

[0034] An example of the polypeptide described in (ii) above is: a polypeptide comprising at least the amino acid residues from glycine at position 24 to glutamine at position 199 in the amino acid sequence set forth in SEQ ID NO: 2; Fc-binding proteins disclosed in JP 2015-086216 A; Fc-binding proteins disclosed in JP 2016-169197 A; Fc-binding proteins disclosed in JP 2017-118871 A; Fc-binding proteins disclosed in JP 2018-197224 A; Fc-binding proteins disclosed in WO2019 / 083048; Examples include:

[0035] Examples of the substitution, deletion, insertion, and addition described in (ii) above include the amino acid residue substitutions disclosed in the aforementioned publications (JP 2015-086216 A, JP 2016-169197 A, JP 2017-118871 A, JP 2018-197224 A, and WO 2019 / 083048). The term "one or several" in (ii) above may mean, for example, 1 to 50, 1 to 40, 1 to 30, 1 to 20, or 1 to 10. The substitution of "one or several" amino acid residues may occur at positions other than those disclosed in the above-mentioned publications, for example, as long as the antibody has binding activity to the antibody.

[0036] In (iii) above, "homology" refers to similarity or identity, and can be determined using an alignment program such as BLAST (Basic Local Alignment Search Tool) or FASTA. For example, "amino acid sequence identity" may refer to the identity between amino acid sequences calculated using blastp, specifically, the identity between amino acid sequences calculated using blastp with default parameters. The homology may be 70% or more, and may be 80% or more, 85% or more, 90% or more, or 95% or more (e.g., 96% or more, 97% or more, 98% or more, 99% or more).

[0037] Furthermore, in the present invention, the "position" of each amino acid residue refers to the order in which the first methionine is positioned as position 1 in the amino acid sequence set forth in each SEQ ID NO. Therefore, "position 176" according to the present invention refers to position 176 in the amino acid sequence set forth in SEQ ID NO: 1. Furthermore, "the amino acid residue corresponding to valine at position 176 in SEQ ID NO: 1" refers to an amino acid residue in the amino acid sequence having 70% or more homology, which is arranged at the same position as valine at position 176 in the amino acid sequence set forth in SEQ ID NO: 1, when the amino acid sequence is aligned with a sequence consisting of amino acid residues 17 to 192 in SEQ ID NO: 1.

[0038] An Fc-binding protein can be produced, for example, by expressing a gene encoding the Fc-binding protein in a host harboring the gene. The gene encoding the Fc-binding protein can be obtained, for example, by cloning, chemical synthesis, mutagenesis, or a combination thereof. The host is not particularly limited as long as it can express the Fc-binding protein. Examples of the host include animal cells, insect cells, and microorganisms. Examples of animal cells include COS cells, CHO cells, Hela cells, NIH3T3 cells, and HEK293 cells. Examples of insect cells include Sf9 cells and BTI-TN-5B1-4 cells. Examples of microorganisms include yeast and bacteria. Examples of yeast include yeasts of the genus Saccharomyces, such as Saccharomyces cerevisiae, yeasts of the genus Pichia, such as Pichia pastoris, and yeasts of the genus Schizosaccharomyces, such as Schizosaccharomyces pombe. Examples of bacteria include bacteria of the genus Escherichia, such as Escherichia coli. Examples of Escherichia coli include the W3110 strain, the JM109 strain, and the BL21(DE3) strain. Fc-binding proteins can also be produced, for example, by expressing a gene encoding the Fc-binding protein in a cell-free protein synthesis system.

[0039] In the present invention, the term "insoluble carrier" refers to a carrier that is insoluble in a liquid passed through a column (e.g., a liquid used for antibody adsorption or elution, such as an equilibration liquid or an elution liquid). The insoluble carrier may have a functional group (e.g., a hydroxy group) for covalently immobilizing an Fc-binding protein. Examples of insoluble carriers include carriers derived from inorganic substances such as zirconia, zeolite, silica, and coated silica; carriers derived from natural organic polymers such as cellulose, agarose, and dextran; and carriers derived from synthetic organic polymers such as polyacrylic acid, polystyrene, polyacrylamide, polymethacrylamide, polymethacrylate, and vinyl polymers.

[0040] The Fc-binding protein is immobilized on an insoluble carrier. The Fc-binding protein can be immobilized on the carrier by covalent bonding, for example, using a functional group (e.g., a hydroxyl group) possessed by the insoluble carrier for covalently immobilizing the Fc-binding protein. For example, if the insoluble carrier has hydroxyl groups on its surface, an activator can be used to form an activated group capable of covalently bonding to the Fc-binding protein, and the activated group can then be covalently bonded to the Fc-binding protein to achieve immobilization. Specific examples of activators for hydroxyl groups include epichlorohydrin (which forms an epoxy group as the activated group), 1,4-butanediol diglycidyl ether (which forms an epoxy group as the activated group), tresyl chloride (which forms a tresyl group as the activated group), and vinyl bromide (which forms a vinyl group as the activated group). Alternatively, the hydroxyl group can be converted to an amino group, carboxyl group, or the like, and then activated by the action of an activator. Specific examples of activators for amino groups, carboxyl groups, etc. include N-succinimidyl 3-maleimidopropionate (which forms a maleimide group as the activating group), 1,1'-carbonyldiimidazole (which forms a carbonylimidazole group as the activating group), and halogenated acetic acids (which form a haloacetyl group as the activating group).

[0041] A column (hereinafter also referred to as "antibody separation agent column") packed with an insoluble carrier (hereinafter also referred to as "antibody separation agent") on which an Fc-binding protein is immobilized is <1> When a saliva sample collected from a subject is added in the sample collection step, the antibodies contained in the sample are adsorbed to the antibody separating agent. The saliva sample can be added to the column using a liquid delivery device such as a pump. In this specification, adding a liquid to a column is also referred to as "delivering the liquid to the column." The adsorption step conditions, such as the amount of saliva sample added, the type of liquid phase, the liquid phase delivery rate, and the column temperature, are not particularly limited as long as the antibodies contained in the sample can be adsorbed to the antibody separating agent. The adsorption step conditions can be appropriately set depending on various conditions, such as the type of antibody, the type of Fc-binding protein, the type of insoluble carrier, and the column scale. Examples of liquid phases include the equilibration liquid described below. For example, when the column has an inner diameter of 4.6 mm, the delivery rate may be 0.1 mL / min to 2.0 mL / min, 0.2 mL / min to 1.5 mL / min, or 0.4 mL / min to 1.2 mL / min. The liquid flow rate may be set, for example, to be proportional to the square of the inner diameter of the column. The column temperature may be, for example, from 0°C to 50°C.

[0042] <3> Equilibration process The equilibration step is <2> This is a step of equilibrating the antibody separating agent column using an equilibration solution (which may also be referred to as "equilibration buffer" in the same sense) to remove the antibody adsorbed to the antibody separating agent in the adsorption step. Before adding the antibody-containing saliva sample to the column, the column may be equilibrated using the equilibration solution. That is, the present invention provides: <2> Before the adsorption step, a step of adding an equilibration solution to the column to equilibrate the column may be included.

[0043] By equilibrating, it does not bind to the Fc-binding protein immobilized on the insoluble carrier, or <2> In the adsorption step, antibodies that were adsorbed to the antibody separating agent but not to the equilibration buffer can be removed from the antibody separating agent column. The fraction containing antibodies that were not adsorbed (desorbed) to the antibody separating agent in the equilibration step is called the unadsorbed fraction, and this fraction corresponds, for example, to the fraction in the region where the peak detected after adding a saliva sample to the column reaches its minimum value during the equilibration step. It is preferable that the unadsorbed fraction and the peak region detected after adding the eluent are separated in separation time, as this increases separation accuracy. In particular, a constant detection value between the unadsorbed fraction and the peak region detected after adding the eluent is preferable, as it indicates that the unadsorbed fraction has been sufficiently removed from the column by the equilibration step. The "constant value" includes not only a constant value, but also a state in which the detection value changes with a constant slope.

[0044] Examples of the equilibration solution (equilibration buffer solution) include aqueous buffer solutions. The equilibration solution is a weakly acidic to weakly alkaline buffer solution with a pH greater than 5.0 and less than 9.0, preferably a buffer solution with a pH of 5.2 or greater and a pH of 8.0 or less, and more preferably a buffer solution with a pH of 5.4 or greater and a pH of 7.5 or less. The components of the buffer solution can be selected appropriately depending on various conditions, such as the pH of the buffer solution. Examples of buffer solution components include phosphoric acid, acetic acid, formic acid, MES (2-Morpholinoethanesulfonic acid), MOPS (3-Morpholinopropanesulfonic acid), citric acid, succinic acid, glycine, and piperazine. Furthermore, a salt may be further added to the buffer solution, and the salt is not particularly limited as long as it is a salt that can be easily imagined by a person skilled in the art, such as sodium chloride or potassium chloride.

[0045] <4> Elution process The elution step is <3> This is the process in which an elution solution (hereinafter also referred to as "elution buffer") is added to the antibody separation agent column equilibrated in the equilibration process, and the antibodies adsorbed to the separation agent are eluted, thereby obtaining an antibody separation pattern.

[0046] That is, the antibodies adsorbed to the antibody separating agent can be eluted by adding an elution solution to the column. The conditions for the elution step, such as the type of elution solution, the elution solution delivery format, the liquid phase delivery rate, and the column temperature, are not particularly limited as long as the antibodies are separated in the desired manner, e.g., as long as the desired separation pattern is obtained. The conditions for the elution step can be appropriately set depending on various conditions, such as the type of antibody, the type of Fc-binding protein, the type of insoluble carrier, and the scale of the column. The elution solution can be a solution that weakens the affinity between the antibody and the Fc-binding protein. Examples of the elution solution include aqueous buffer solutions with a lower pH than the liquid phase before elution (e.g., the equilibration solution). Specific examples of the elution solution include acidic buffer solutions with a pH of 2.5 to 4.5. For example, if the liquid phase before elution (e.g., the equilibration solution) is a weakly acidic to weakly alkaline buffer solution with a pH of 5.0 to 8.0, the elution solution can be an acidic buffer solution with a pH of 2.5 to 4.5. The components of the buffer solution can be appropriately selected depending on various conditions, such as the pH of the buffer solution. Examples of buffer components include phosphate, acetic acid, formic acid, MES, MOPS, citric acid, succinic acid, glycine, and piperazine. The eluent delivery method may be, for example, a gradient or an isocratic method. The eluent delivery method may particularly be a gradient. That is, elution may be performed by increasing the ratio of the eluent in the liquid phase. The gradient may be, for example, a linear gradient, a stepwise gradient, or a combination thereof. Specifically, the gradient may be set so that the ratio of the eluent in the liquid phase increases from 0% (v / v) to 100% (v / v) over a period of 10 to 60 minutes, 15 to 50 minutes, or 20 to 40 minutes. For example, when the column has an inner diameter of 4.6 mm, the liquid flow rate may be 0.1 mL / min to 2.0 mL / min, 0.2 mL / min to 1.5 mL / min, or 0.4 mL / min to 1.2 mL / min. The liquid flow rate may be set, for example, to be proportional to the square of the inner diameter of the column. The column temperature may be, for example, 0°C to 50°C.

[0047] The elution step may result in the production of a separated antibody. The separated antibody may be obtained, for example, as an elution fraction containing the antibody. That is, the separated antibody is obtained by collecting the elution fraction containing the separated antibody. The elution fraction can be collected, for example, by a conventional method. Specifically, the elution fraction can be collected, for example, by an automatic fraction collector such as an autosampler. Furthermore, the separated antibody may be recovered from the elution fraction. The separated antibody can be recovered from the elution fraction, for example, by a conventional method. Specifically, the separated antibody can be recovered from the elution fraction by, for example, a known method used for separating and purifying proteins.

[0048] The antibody separation pattern can be obtained by detecting the antibody with a detector, such as an ultraviolet-visible detector or a mass detector. The antibody separation pattern can be a chromatogram of the antibody elution.

[0049] <5> Analysis process The analysis process is <4> This is a process of analyzing antibodies contained in a saliva sample derived from a subject (hereinafter also referred to as "test antibodies") based on the separation pattern of the antibodies obtained in the elution process. An example of analyzing the test antibodies is obtaining characteristics of the separation pattern of the test antibodies. Specifically, in the analysis process, for example, the separation pattern of the test antibodies may be divided at specific elution times, and the characteristics of the divided regions may be obtained. When obtaining the characteristics of the separation pattern, the separation pattern of a standard antibody may also be referenced.

[0050] The specific elution time (hereinafter also referred to as "division time") may be a specific elution time in the separation pattern of the test antibody. Furthermore, when the separation pattern of the test antibody is unclear, the division time may be the elution time at a characteristic point in the separation pattern of a standard antibody with a clear separation pattern, or a time obtained by adding or subtracting an arbitrary value from the elution time. The division time may be determined for each measurement of the test antibody, or the average or median of division times determined from the separation patterns of multiple test antibodies or standard antibodies may be used as the fixed division time.

[0051] It is preferable to use the elution time at a characteristic point that is common to the separation patterns of the standard antibody or the test antibody as the division time and obtain the characteristics from the area divided by that division time, as this allows for highly reproducible analysis of the test antibody.

[0052] The characteristics of the separation pattern are not particularly limited as long as they are values ​​that characterize the separation pattern, such as extreme values ​​(maximum or minimum values) in the regions divided by the division time, the elution times at which the extreme values ​​are obtained, values ​​at inflection points in the divided regions and the elution times at the inflection points, the number and heights of peaks present in the divided regions, the areas of the divided regions, etc. Note that, as the detected values, for example, values ​​obtained by the above-mentioned detector may be used as they are, or may be used after appropriate correction of the baseline, etc.

[0053] As an example of the above-mentioned feature, elution peaks may be extracted from the antibody separation pattern obtained in the elution step, and the area of ​​each extracted elution peak may be calculated, followed by calculating the peak area ratio. The antibody separation pattern used for elution peak detection may be used for elution peak extraction as is, or after appropriate correction such as baseline correction. The elution peak for which the peak area is to be calculated is hereinafter also referred to as the "target peak." Note that elution peaks with a peak area percentage of less than 1%, as described below, may be excluded from the target peaks.

[0054] The target peak can be selected appropriately depending on various conditions. For example, when an insoluble carrier on which a polypeptide comprising at least a partial sequence of the extracellular region of human FcγRIIIa or a polypeptide in which some of the amino acid residues constituting said polypeptide have been substituted, deleted, inserted, and / or added (hereinafter also referred to as a "human FcγRIIIa ligand") is immobilized is used as an antibody separation agent, three elution peaks are extracted from the antibody separation pattern (named the first, second, and third peaks in order of decreasing binding affinity to the human FcγRIIIa ligand), and any of the first to third peaks may be used as the target peak. Furthermore, when the aforementioned insoluble carrier onto which the human FcγRIIIa ligand has been immobilized is used as the antibody separation agent and the elution step is performed by gradient elution based on pH change, the first peak may be designated, for example, as the peak that first elutes when the liquid phase pH is 5.4 or less, 5.2 or less, 5.0 or less, or 4.8 or less, or the peak that elutes during the period when the liquid phase pH is 5.4 to 4.4, 5.2 to 4.5, or 5.0 to 4.6. The pH of the liquid phase is calculated using the following formula (I) when the pH of the liquid phase (e.g., equilibration solution) before the start of elution is X, the pH of the elution solution is Y, and the proportion of the elution solution in the liquid phase is Z%. The pH at which the peak elutes is appropriately corrected taking into account the volume of the flow path, such as the volume of the column.

[0055] pH of the liquid phase = X - ((XY) × Z [%]) (I) In the present invention, absolute or relative values ​​of the target peak area may be used. Examples of relative values ​​include the ratio of the area of ​​a specific target peak to the area of ​​another target peak, or the ratio of the area of ​​a specific target peak to the total area of ​​all target peaks. As the other target peak, one target peak may be used, or two or more target peaks may be used in combination. A specific example of a peak area ratio is peak area %. "Peak area %" refers to the area ratio (%) of a specific target peak to the total area of ​​all target peaks. It is preferable to use the peak area and / or peak height present in the separation pattern of the antibody, or the peak area % and / or peak height % as the characteristic, since this allows the test antibody to be analyzed with high reproducibility.

[0056] The characteristics of the separation pattern may also be corrected based on the characteristics of the subject. An example of such a correction is correction based on the age of the subject. For example, if the characteristics of the separation pattern are affected by the age of the subject, the obtained characteristics are corrected based on the age of the subject before the following process. <6> The characteristics corrected based on the subject's age may be used, for example, to detect the risk of conditions other than those associated with aging.

[0057] The peak regions identified in this manner can be used to distinguish between differences in the glycan structures of the N-linked glycans bound to the antibodies contained in the sample (WO2019 / 244901).

[0058] <6> Detection process The present invention <5> When an analysis step is included, the analytical results obtained in the step (e.g., characteristics of the separation pattern) can be used as an indicator to detect the presence or absence of a disease, the risk of developing a disease, the degree of disease progression, and / or the degree of aging in a subject who provided an antibody-containing saliva sample. That is, one embodiment of the analysis method of the present invention may be a method for detecting the presence or absence of a disease, the risk of developing a disease, the degree of disease progression, and / or the degree of aging in a subject (specifically, a subject who provided a sample containing a test antibody) (hereinafter, also simply referred to as the "detection method of the present invention").

[0059] The following describes a case where risk in a subject is detected using the characteristics of a separation pattern as an index, but the same description can also be applied to a case where any analysis result is used as an index.

[0060] Examples of diseases include diseases affected by immune cell activity (e.g., damaging action and phagocytosis). Examples of immune cells include natural killer cells, monocytes, and macrophages. Specific examples of diseases affected by immune cell activity include cancer, autoimmune diseases, infectious diseases, allergies, and inflammatory diseases.

[0061] Examples of cancer include brain cancer, breast cancer, uterine cancer, cervical cancer, ovarian cancer, esophageal cancer, stomach cancer, appendix cancer, colon cancer, liver cancer, gallbladder cancer, bile duct cancer, pancreatic cancer, adrenal cancer, gastrointestinal stromal tumor (GIST), mesothelioma, head and neck cancer, kidney cancer, lung cancer, osteosarcoma, Ewing's sarcoma, chondrosarcoma, prostate cancer, testicular cancer, renal cell carcinoma, bladder cancer, rhabdomyosarcoma, skin cancer, and anal cancer.

[0062] Examples of autoimmune diseases include Guillain-Barre syndrome, myasthenia gravis, multiple sclerosis, chronic gastritis, chronic atrophic gastritis, autoimmune hepatitis, primary biliary cholangitis, ulcerative colitis, Crohn's disease, primary biliary cholangitis, autoimmune pancreatitis, Takayasu's arteritis, Goodpasture's syndrome, rapidly progressive glomerulonephritis, megaloblastic anemia, autoimmune hemolytic anemia, autoimmune neutropenia, idiopathic thrombocytopenic purpura, Graves' disease, Hashimoto's disease, primary hypothyroidism, idiopathic Addison's disease, type 1 diabetes, and chronic discoid erythema. These include erythematosus, localized scleroderma, pemphigus, pustular psoriasis, plaque psoriasis, pemphigoid, herpes gestationis, linear IgA bullous dermatosis, epidermolysis bullosa acquisita, alopecia areata, vitiligo vulgaris, Sutton nevus, Harada disease, autoimmune optic neuropathy, autoimmune inner ear disorder, idiopathic azoospermia, recurrent abortion, rheumatism, systemic lupus erythematosus (SLE), antiphospholipid syndrome, polymyositis, dermatomyositis, scleroderma, Sjogren's syndrome, IgG4-related disease, vasculitis syndrome, and mixed connective tissue disease.

[0063] Examples of infectious diseases include bacterial infections, fungal infections, parasitic protozoan infections, parasitic helminth infections, and viral infections. Examples of bacterial infections include streptococci, Staphylococcus aureus, Staphylococcus epidermidis, Enterococcus faecalis, Listeria, Neisseria meningitidis, Neisseria gonorrhoeae, pathogenic Escherichia coli, Klebsiella, Proteus, Bordetella pertussis, Pseudomonas aeruginosa, Serratia, Citrobacter, Acinetobacter, Enterobacter, and Mycoplasma. Examples of infectious diseases include infections caused by various bacteria such as Mycoplasma, Clostridium, Rickettsia, and Chlamydia; tuberculosis, nontuberculous mycobacteria, cholera, plague, diphtheria, dysentery, scarlet fever, anthrax, syphilis, tetanus, leprosy, Legionella pneumonia, leptospirosis, Lyme disease, tularemia, and Q fever; and examples of fungal infections include aspergillosis, candida infection, cryptococcosis, tinea, histoplasmosis, and Pneumocystis pneumonia (Pneumocystis carinii pneumonia). Examples of parasitic protozoan infections include amoebic dysentery, malaria, toxoplasmosis, leishmaniasis, and cryptosporidium infection. Examples of parasitic helminth infections include echinococcus, schistosomiasis Japanese, filariasis, ascariasis, and diphyllobothriasis.Examples of viral infections include influenza, viral hepatitis, viral meningitis, viral gastroenteritis, viral conjunctivitis, acquired immunodeficiency syndrome (AIDS), adult T-cell leukemia, Ebola hemorrhagic fever, yellow fever, common cold syndrome, rabies, cytomegalovirus infection, severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), coronavirus disease 2019 (COVID-19), and progressive multifocal influenza. Examples of infectious diseases include idiopathic leukoencephalopathy, chickenpox and shingles, herpes simplex, hand, foot, and mouth disease, dengue fever, Japanese encephalitis, erythema infectiosum, infectious mononucleosis, smallpox, rubella, polio (polio), measles, pharyngoconjunctival fever (swimming pool fever), Marburg hemorrhagic fever, hemorrhagic fever with renal syndrome, Lassa fever, mumps, West Nile fever, herpangina, and chikungunya fever. The infectious disease may be, for example, an opportunistic infection.

[0064] Examples of allergies include anaphylactic shock, allergic rhinitis, conjunctivitis, bronchial asthma, urticaria, atopic dermatitis, hemolytic anemia, idiopathic thrombocytopenic purpura, drug-induced hemolytic anemia, granulocytopenia, thrombocytopenia, Goodpasture's syndrome, serum sickness, systemic lupus erythematosus, rheumatism, glomerulonephritis, hypersensitivity pneumonitis, allergic bronchopulmonary aspergillosis (ABPA), contact dermatitis, allergic encephalitis, transplant rejection, tuberculous cavities, and epithelioid cell granuloma.

[0065] Examples of inflammatory diseases include diseases induced by inflammatory cytokines such as IL-6 (interleukin-6) and TNF (tumor necrosis factor) α. Specific examples of inflammatory diseases include encephalitis, osteomyelitis, meningitis, neuritis, eye inflammation (dacryoadenitis, scleritis, episcleritis, keratitis, chorioretinitis, retinitis, chorioretinitis, blepharitis, conjunctivitis, uveitis, etc.), ear inflammation (otitis externa, otitis media, otitis interna, etc.), mastitis, carditis (endocarditis, myocarditis, pericarditis, etc.), vasculitis (arteritis, phlebitis, capillaritis, etc.), respiratory inflammation (sinusitis, rhinitis, pharyngitis, laryngitis, tracheitis, bronchitis, bronchiolitis, pneumonia, pleuritis, mediastinitis, etc.), oral inflammation (stomatitis, gingivitis, gingivostomatitis, glossitis, tonsillitis, siladenitis, parotitis, cheilitis, pulpitis, rhinitis, etc.), and digestive inflammation (esophagitis, gastritis, gastroenteritis). Examples of age-related diseases include inflammatory bowel disease (inflammatory bowel disease, enteritis, enteritis, colitis, duodenitis, ileitis, appendicitis, proctitis, etc.), dermatitis, cellulitis, hidradenitis, arthritis, dermatomyositis, myositis, synovitis, tendonitis, panniculitis, osteitis, osteomyelitis, periostitis, nephritis, ureteritis, cystitis, ureteritis, oophoritis, salpingitis, endometritis, cervicitis, vaginitis, vulvitis, orchitis, epididymitis, prostatitis, seminal vesicle cystitis, balanitis, presitis, chorioamnionitis, omphalitis, omphalitis, hepatitis, ascending cholangitis, cholecystitis, pancreatitis, peritonitis, hypophysitis, thyroiditis, parathyroiditis, adrenalitis, lymphangitis, lymphadenitis, cachexia, frailty, sarcopenia, and locomotive syndrome.

[0066] In the detection step, <5> The presence or absence of a disease, the risk of developing a disease, the degree of disease progression, and / or the degree of aging in a subject may be detected using the feature of the separation pattern obtained in the analysis step as an index. That is, the feature value may be considered to be data used as an index for detecting the presence or absence of a disease, the risk of developing a disease, the degree of disease progression, and / or the degree of aging in a subject. Specifically, the presence or absence of a disease, the risk of developing a disease, the degree of disease progression, and / or the degree of aging in a subject can be detected using the feature value obtained based on the separation pattern obtained by separating an antibody obtained from the subject (test antibody) using an FcR column as an index. That is, the analysis method or detection method of the present invention may be provided as a method for accurately detecting the presence or absence of a disease, the risk of developing a disease, the degree of disease progression, and / or the degree of aging in a subject using the feature value obtained by separating the test antibody using an FcR column as an index. In this specification, the presence or absence of a disease, the risk of developing a disease, the degree of progression of a disease, and / or the degree of progression of aging are collectively referred to simply as "risk." Furthermore, in this specification, "risk detection" and "risk assessment" may be used synonymously.

[0067] Detection of the risk of onset in a subject includes detection of whether or not the subject is at risk of onset (qualitative detection) and detection of whether or not the subject is at high risk (quantitative detection).

[0068] Detection of the presence or absence of a disease includes detection of whether or not a subject is currently likely to have the disease (qualitative detection), and detection of whether or not a subject is currently likely to have the disease (quantitative detection).

[0069] Detection of the risk of developing a disease can be done by detecting whether or not a subject is likely to develop a disease in the future or if it does develop, the disease will become severe (qualitative detection), or by detecting whether or not a subject is likely to develop a disease in the future or if it does develop, the disease will become severe (quantitative detection).

[0070] Detection of the degree of progression of a disease includes detection (quantitative detection) of whether the degree of progression (for example, severity) of the current disease in a subject is large or small.

[0071] Examples of detecting the degree of progression of aging include detecting whether the current degree of progression (for example, severity) of aging in a subject is large or small (quantitative detection).

[0072] That is, "a subject is at risk of developing" may mean, for example, that the subject may currently have the disease, that the subject may develop the disease in the future, and / or that if the subject develops the disease in the future, the disease may become severe. On the other hand, "a subject is not at risk of developing" may mean, for example, that the subject is not currently at risk of developing the disease, that the subject is not likely to develop the disease in the future, and / or that if the subject develops the disease in the future, the disease may not become severe.

[0073] Furthermore, "a high risk of developing a disease in a subject" may mean, for example, that the subject is likely to currently have a disease, that the subject is likely to develop a disease in the future, that the subject is likely to develop a disease if the subject develops a disease in the future, that the disease will likely become severe if the subject develops a disease in the future, that the subject's current disease is rapidly progressing, and / or that the subject is currently aging rapidly. On the other hand, "a low risk of developing a disease in a subject" may mean, for example, that the subject is unlikely to currently have a disease, that the subject is unlikely to develop a disease in the future, that the subject is unlikely to develop a disease if the subject develops a disease in the future, that the subject's current disease is slowly progressing, and / or that the subject is currently aging slowly.

[0074] The detection step can be carried out, for example, using the magnitude of a feature value obtained from the features of the separation pattern as an index. The magnitude of the feature value can be determined, for example, by comparing it with a predetermined threshold. In other words, the detection step may include, for example, a step of comparing the feature value obtained from the features of the separation pattern with a threshold.

[0075] That is, "a high feature value" may mean, for example, that the feature value is high relative to a threshold. Furthermore, "a high feature value relative to a threshold" may mean, for example, that the feature value is equal to or greater than the threshold, that the feature value exceeds the threshold, or that the feature value is statistically significantly higher than the threshold. Specific examples of "a high feature value relative to a threshold" include a feature value that is 1.01 times or more, 1.02 times or more, 1.03 times or more, 1.05 times or more, 1.07 times or more, 1.1 times or more, 1.2 times or more, 1.3 times or more, 1.5 times or more, 1.7 times or more, 2 times or more, 2.5 times or more, or 3 times or more of the threshold.

[0076] On the other hand, "a low feature value" may mean, for example, that the feature value is low relative to a threshold. Furthermore, "a low feature value relative to a threshold" may mean, for example, that the feature value is equal to or less than the threshold, that the feature value is less than the threshold, or that the feature value is statistically significantly lower than the threshold. Specific examples of "a low feature value relative to a threshold" include a feature value that is 0.99 times or less, 0.98 times or less, 0.97 times or less, 0.95 times or less, 0.93 times or less, 0.9 times or less, 0.85 times or less, 0.8 times or less, 0.7 times or less, 0.6 times or less, 0.5 times or less, 0.4 times or less, or 0.3 times or less of the threshold.

[0077] The feature value may be divided into a risk range based on, for example, a threshold value. The feature value may be divided into a non-risk range based on, for example, a threshold value. Specifically, the feature value may be divided into a risk range and a non-risk range based on, for example, a threshold value. The "risk range" may mean a range in which the subject is likely to be at risk for the feature value. The "non-risk range" may mean a range in which the subject is likely to be at no risk for the feature value. In other words, if the feature value is in the risk range, it may be detected that the subject is at risk or at high risk. On the other hand, if the feature value is in the non-risk range, it may be detected that the subject is at no risk or at low risk.

[0078] Note that "detecting whether a subject is at risk, absent, high, or low when a specific feature value meets a certain criterion (e.g., low or high, or within a specific range)" means detecting whether a subject is at risk, absent, high, or low at least within the range that meets the criterion, and does not require that risk be detected in a subject that does not meet the criterion. However, in one embodiment, "detecting whether a subject is at risk, absent, high, or low when a specific feature value meets a certain criterion (e.g., low or high, or within a specific range)" may also detect whether a subject is at risk, absent, present, low, or high, respectively, within the range that does not meet the criterion.

[0079] The threshold can be appropriately set by a person skilled in the art depending on various conditions, such as the type of feature value and the desired accuracy of determination. The threshold may be set for each symptom to be determined, such as disease or aging. The means for determining the threshold is not particularly limited. The threshold can be determined, for example, according to a known method used in data analysis for dividing a population into two groups.

[0080] The threshold can be determined, for example, based on a feature value obtained from the features of the separation pattern of the test antibody obtained from a control subject (herein, the separation pattern of the test antibody obtained from the control subject is also referred to as a "control separation pattern"). That is, the threshold may be determined based on the feature value obtained from the features of the control separation pattern, and the detection step may be carried out. Specifically, the feature value obtained from the features of the control separation pattern may be used to determine the threshold, which may then be used for comparison with the feature value. In other words, the detection step may involve, for example, comparing the feature value with the feature value of the control separation pattern.

[0081] The control subject may be a positive control or a negative control. A "positive control" may refer to a subject who can be detected as having or being at high risk. A "negative control" may refer to a subject who can be detected as having no or low risk. Positive controls include individuals who are suffering from or have previously suffered from the diseases exemplified above (particularly the same disease as the target disease for risk detection), individuals who have progressed in aging, and individuals with a combination thereof. Negative controls include individuals who are not suffering from or have never suffered from the diseases exemplified above (particularly the same disease as the target disease for risk detection), individuals who have not progressed in aging, and individuals with a combination thereof. The threshold may be determined solely based on the feature value determined by analyzing the positive control, solely based on the feature value determined by analyzing the negative control, or based on the feature value calculated by analyzing both the positive and negative controls. The threshold is typically determined based on the feature value determined by analyzing both the positive and negative controls. The number of positive and negative controls is not particularly limited as long as a threshold that enables risk determination with the desired accuracy is obtained. The number of positive controls and negative controls may each be one, two, or more. The number of positive controls and negative controls may each typically be multiple. The number of positive controls and negative controls may each be, for example, 5 or more, 10 or more, 20 or more, or 50 or more. The number of positive controls and negative controls may each be, for example, 10,000 or less, 1,000 or less, or 100 or less.

[0082] When determining the threshold based solely on the feature value determined by analyzing a positive control, the threshold may be set to, for example, a value selected from the range of feature values ​​determined by analyzing multiple positive control individuals, e.g., the average value. Alternatively, the threshold may be determined so that a predetermined percentage of the positive control falls within the risk range in the distribution of feature values ​​determined by analyzing multiple positive control individuals. The predetermined percentage may be, for example, 70% or more, 80% or more, 90% or more, 95% or more, 97% or more, or 100%.

[0083] When determining the threshold based solely on the feature values ​​determined by analyzing negative controls, the threshold may be set to, for example, a value selected from the range of feature values ​​determined by analyzing multiple negative control individuals, e.g., the average value. Alternatively, the threshold may be determined so that a predetermined percentage of the negative controls falls within the non-risk range in the distribution of feature values ​​determined by analyzing multiple negative control individuals. The predetermined percentage may be, for example, 70% or more, 80% or more, 90% or more, 95% or more, 97% or more, or 100%.

[0084] When determining the threshold based on both the feature values ​​obtained by analyzing a positive control and the feature values ​​obtained by analyzing a negative control, the threshold may be determined, for example, so that a predetermined percentage of the positive controls falls within the risk range and a predetermined percentage of the negative controls falls within the non-risk range. It is preferable that both the percentage of positive controls falling within the risk range and the percentage of negative controls falling within the non-risk range are high. These percentages may be, for example, 70% or more, 80% or more, 90% or more, 95% or more, 97% or more, or 100%. If it is difficult to increase both of these percentages, the threshold may be set so that one of the percentages is preferentially increased depending on various conditions, such as the intended use of the detection results according to the present invention. For example, to reduce the false negative rate, the threshold may be set so that the percentage of positive controls falling within the risk range is preferentially increased.

[0085] The threshold may be determined, for example, using software. For example, statistical analysis software may be used to determine a threshold that allows for the most appropriate statistical discrimination between the negative control and the positive control. Examples of such software include statistical analysis software such as "R."

[0086] The control subject may also be the target subject itself. That is, for example, a risk in a subject may be detected using a change in a feature value in the subject as an index. As used herein, a "high feature value" may also encompass an increase in the feature value. As used herein, an "increased feature value" may specifically mean that the feature value has increased compared to a previous value. As used herein, a "low feature value" may also encompass a decrease in the feature value. As used herein, a "decreased feature value" may specifically mean that the feature value has decreased compared to a previous feature value. That is, a previous feature value may also be used as the threshold. As used herein, a "past feature value" refers to a feature value of a test antibody obtained from a target subject at a specific time point in the past. The target subject at a specific time point in the past may be, for example, a positive control or a negative control.

[0087] The fluctuation of the characteristic value in the subject may be used as an index to detect an increase or decrease in the risk in the subject. As used herein, "being at or at high risk" may also include cases where the risk has increased. As used herein, "increased risk" may specifically mean that the risk has increased compared to a specific time point in the past. On the other hand, as used herein, "no or low risk" may also include cases where the risk has decreased. As used herein, "reduced risk" may specifically mean that the risk has decreased compared to a specific time point in the past.

[0088] In this specification, "obtaining a feature value and using it as an index for risk detection" is not limited to obtaining the feature value itself and using it as an index for risk detection, but also includes obtaining another value that reflects the feature value and using it as an index for detection.

[0089] The risk detection result may be used as an indicator for determining whether to implement a risk-reducing treatment (hereinafter also referred to as "risk reduction treatment") on a subject. In other words, by performing this detection process, an indicator for determining whether to implement risk reduction treatment on a subject can be obtained. That is, for example, if this detection process detects that a subject is at risk or at high risk, a decision may be made to implement risk reduction treatment on the subject. This detection process may be used, for example, alone or in combination with other means, as an indicator for determining whether to implement risk reduction treatment on a subject. For example, for a symptom detected as at risk or at high risk in a subject by this detection process, a definitive diagnosis may be made by other means, and then a decision may be made to implement risk reduction treatment on the subject. The risk reduction treatment may be a medical or non-medical procedure. Examples of risk reduction treatment include the prevention and treatment of diseases and aging, as exemplified above. That is, the present invention may provide, for example, a method for preventing or treating symptoms such as diseases and aging. The prevention or treatment method may be, for example, a method for preventing or treating a symptom such as a disease or aging, which includes a step of implementing prevention or treatment for the subject when the subject is detected as being at risk or at high risk by this detection step. Specifically, prevention or treatment may be implemented for the symptom for which the subject is detected as being at risk or at high risk by this detection step. Prevention or treatment can be implemented, for example, by a general means for each symptom (e.g., medication or surgery). [Example]

[0090] The present invention will be described in more detail below with reference to examples and comparative examples, but the present invention is not limited to these examples. Note that the reference examples do not constitute the present invention.

[0091] Example 1 Preparation of antibody separation column (FcR9_F column) The Fc-binding protein FcR9_F_Cys (SEQ ID NO: 2) obtained by the method of JP 2018-197224 A was immobilized on an insoluble carrier (gel) by the method described below to prepare an FcR9_F column. In FcR9_F_Cys (SEQ ID NO: 2), the portion from the first methionine (Met) to the 22nd alanine (Ala) is the improved PelB signal peptide, the portion from the 24th glycine (Gly) to the 199th glutamine (Gln) is the amino acid sequence of the Fc-binding protein FcR9_F (JP 2018-197224 A) (corresponding to the region from the 17th to the 192nd of SEQ ID NO: 1), and the portion from the 200th glycine (Gly) to the 207th glycine (Gly) is the cysteine ​​tag sequence. Furthermore, the FcR9_F is a polypeptide consisting of the amino acid residues 17 to 192 of native human FcγRIIIa shown in SEQ ID NO: 1, with the following 10 amino acid substitutions: Substitution of valine (Val) at position 27 of SEQ ID NO: 1 (position 34 of SEQ ID NO: 2) with glutamic acid (Glu) Substitution of phenylalanine (Phe) at position 29 of SEQ ID NO: 1 (position 36 of SEQ ID NO: 2) with isoleucine (Ile) Tyrosine (Tyr) at position 35 of SEQ ID NO: 1 (position 42 of SEQ ID NO: 2) is replaced with asparagine (Asn) Substitution of glutamine (Gln) at position 48 of SEQ ID NO: 1 (position 55 of SEQ ID NO: 2) with arginine (Arg) Phenylalanine (Phe) at position 75 of SEQ ID NO: 1 (position 82 of SEQ ID NO: 2) is replaced with leucine (Leu) Substitution of asparagine (Asn) at position 92 of SEQ ID NO: 1 (position 99 of SEQ ID NO: 2) with serine (Ser) Substitution of valine (Val) at position 117 of SEQ ID NO: 1 (position 124 of SEQ ID NO: 2) with glutamic acid (Glu) Substitution of glutamic acid (Glu) at position 121 of SEQ ID NO: 1 (position 128 of SEQ ID NO: 2) with glycine (Gly) Substitution of phenylalanine (Phe) at position 171 of SEQ ID NO: 1 (position 178 of SEQ ID NO: 2) with serine (Ser) Valine (Val) at position 176 of SEQ ID NO: 1 (position 183 of SEQ ID NO: 2) was substituted with phenylalanine (Phe).

[0092] (1) The hydroxyl groups on the surface of 2 mL of hydrophilic vinyl polymer for separation agent (manufactured by Tosoh Corporation: packing material for liquid chromatography) were activated with iodoacetyl groups, and then 4 mg of FcR9_F_Cys obtained by the method of JP 2018-197224 A was reacted to obtain an FcR9_F immobilized gel.

[0093] (2) 1.2 mL of the FcR9_F-immobilized gel prepared in (1) was packed into a φ4.6 mm × 50 mm stainless steel column to prepare an FcR9_F column.

[0094] Reference example 1 (1) Serum obtained from healthy individuals who provided informed consent was diluted 20-fold with PBS (Phosphate Buffered Saline) (pH 7.4) and passed through a 0.2 μm filter (Merck Millipore) to prepare a measurement sample.

[0095] (2) The FcR9_F column prepared in Example 1 was connected to a high-performance liquid chromatography system (manufactured by Tosoh Corporation) and equilibrated with 10 mM citrate buffer (pH 6.5) containing 100 mM sodium chloride (hereinafter also referred to as "equilibration solution"), after which 10 μL of a 1 mg / mL rituximab (manufactured by Zenyaku Kogyo, trade name: Rituxan Intravenous Infusion 100 mg) antibody solution was added as a standard substance at a flow rate of 1.2 mL / min. The detector was used to acquire data every 1 / 5 second.

[0096] (3) After washing with the equilibration solution for 7 minutes at a flow rate of 1.2 mL / min, the adsorbed gamma globulin was eluted with a pH gradient (a gradient in which the eluate reached 100% in 11 minutes) using 10 mM citrate buffer (pH 4.5) containing 500 mM sodium chloride (hereinafter also referred to as the "eluate"), and a separation pattern was obtained.

[0097] (4) After the analysis of the standard substance, the same procedure as in (2) and (3) was followed by adding 10 μL of the measurement sample prepared in (1), and the separation pattern of gamma globulin was obtained.

[0098] (5) The separation patterns obtained in (3) and (4) were baseline corrected so that the detection values ​​were 0 at both the time when the pH gradient started (7 min after the start of elution) and the time when the pH gradient ended (i.e., the eluate reached 100%) (18 min after the start of elution).

[0099] (6) From the baseline-corrected separation pattern of the reference standard (Figure 1), the peak regions were defined as the two elution time regions where the derivative of the valley region between the three peaks detected between 7 and 18 minutes after the start of elution (Peak 1, Peak 2, and Peak 3, in order of shortest elution time (lowest binding ability to FcR9_F) was zero. That is, the peak region was defined as the range from 7 minutes after the start of elution to the elution time where the derivative of the valley region between Peak 1 and Peak 2 was zero. The peak region was defined as the range from the elution time where the derivative of the valley region between Peak 1 and Peak 2 was zero to the elution time where the derivative of the valley region between Peak 2 and Peak 3 was zero. The peak region was defined as the range from the elution time where the derivative of the valley region between Peak 2 and Peak 3 was zero to 18 minutes after the start of elution. The peak regions of the measured sample based on the reference standard (rituximab) were defined by applying the peak regions defined for the reference standard to the sample measured immediately after the analysis of the reference standard (Figure 1).

[0100] (7) The peak area of ​​each peak region of the measurement sample defined in (6) was calculated, and the peak area was divided by the total peak area between 7 and 18 minutes after the start of elution (i.e., the sum of the first peak area, the second peak area, and the third peak area) to calculate the percentage of each peak area (first peak area (area 1)%, second peak area (area 2)%, and third peak area (area 3)%).

[0101] Example 2 Separation of gamma globulin from saliva samples (collected using sponge bodies) (1) 2 mL of saliva was collected from the same healthy subject as in Reference Example 1(1) by placing a cotton sponge (Sarstedt) in the mouth. The sponge was centrifuged to collect saliva, which was then passed through a 0.45 μm filter (Merck Millipore) and concentrated to 100 μL using an ultrafiltration membrane with a molecular weight cutoff of 30,000 (Merck Millipore), to prepare a saliva sample.

[0102] (2) The antibodies contained in the saliva sample were analyzed in the same manner as in Reference Example 1 (2) to (7), except that 50 μL of the saliva sample prepared in (1) was used as the sample to be applied to the FcR9_F column, and the area percentage of each peak was calculated from the resulting separation pattern.

[0103] (3) The serum sample was measured and the area % of each peak calculated from the resulting separation pattern (Reference Example 1) was calculated, and the ratio of the peak area % in the saliva sample calculated in (2) was calculated.

[0104] (4) Based on the integral value of the peak (detection value) detected between 7 and 18 minutes after the start of elution of the standard substance (rituximab), a calibration curve of the antibody concentration versus the integral value was created, and based on this calibration curve, the amount of gamma globulin (antibody) adsorbed to the FcR9_F column was calculated from the integral value of the separation pattern obtained in (2).

[0105] Comparative Example 1 Separation of gamma globulin from saliva sample (collected by salivation) Except for collecting saliva by salivation, the same method as in Example 2 was used to calculate each peak area %, the ratio of each peak area % to the peak area % in serum (Reference Example 1), and the amount of gamma globulin (antibody) adsorbed to the FcR9_F column.

[0106] The results of Reference Example 1, Example 2 and Comparative Example 1 are shown in FIG. From Figure 2, it can be seen that the separation pattern of gamma globulin obtained from serum (Reference Example 1, Figure 2a) is similar to the separation pattern of gamma globulin obtained from saliva collected using a sponge body (Example 2, Figure 2b). On the other hand, the separation pattern of gamma globulin obtained from saliva collected by salivation (Comparative Example 1, Figure 2c) was significantly different. From these results, it can be seen that by collecting saliva using a sponge body, it is possible to obtain a separation pattern of gamma globulin similar to that of serum.

[0107] In Table 1, the ratio of each peak area % to the peak area % in the serum sample (Reference Example 1) shows that the saliva collected using the sponge in Example 2 showed a variation of less than 10% in the area % of all peaks (area 1, area 2, and area 3), resulting in values ​​nearly identical to those of serum. In contrast, the saliva collected by salivation in Comparative Example 1 showed a variation of approximately 40% depending on the peak area %. Furthermore, the adsorption amount was 5.45 μg in the saliva collected using the sponge in Example 2, while it was 3.72 μg in the saliva collected by salivation in Comparative Example 1, resulting in a reduced adsorption amount. These results demonstrate that collecting saliva using a sponge increases the amount of gamma globulin (antibody) detected, and furthermore, a highly accurate separation pattern comparable to that obtained with serum can be obtained.

[0108] [Table 1] [Industrial Applicability]

[0109] As described above, the present invention enables accurate analysis of gamma globulins (antibodies) contained in a saliva sample derived from a subject without the need for pretreatment to remove contaminants. The gamma globulin separation pattern obtained by the present invention is closely related to disease and therefore serves as a useful indicator for clinical diagnosis. In particular, saliva samples can be collected less invasively than blood samples, thereby reducing the risk of specimen collection for the subject. Furthermore, saliva samples can be self-collected by individual subjects, allowing collection outside of medical facilities. Since no pretreatment is required, analysis can be simplified. Therefore, the present invention enables antibody analysis without the intervention of a doctor or nurse, even in cases where blood collection is difficult. Therefore, the present invention is particularly useful for health management applications in healthy individuals, as well as for the development of pharmaceuticals and medical devices used therein.

Claims

1. adding a subject-derived antibody-containing sample to a column packed with an insoluble carrier onto which an Fc-binding protein has been immobilized, and allowing the antibody to be adsorbed onto the carrier; and a step of eluting the antibody adsorbed on the carrier with an eluent to obtain a separation pattern of the antibody, The method as described above, wherein the antibody-containing sample is a saliva sample, the saliva sample is collected using a sponge, and the saliva sample impregnated in the sponge is centrifuged and ultrafiltered to prepare a concentrated sample.

2. The method of claim 1, wherein the Fc binding protein is a human Fcγ receptor.

3. The method according to claim 2, wherein the human Fcγ receptor is a polypeptide described in (ii) below: (ii) A polypeptide having antibody-binding activity, comprising at least the amino acid residues from glycine at position 17 to glutamine at position 192 of the amino acid sequence set forth in SEQ ID NO: 1, with the proviso that at least valine at position 176 of SEQ ID NO: 1 is replaced with phenylalanine, and further having substitution, deletion, insertion and / or addition of one or several amino acid residues at one or several positions other than position 176, and having the amino acid sequence set forth in SEQ ID NO: 2.

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