Method and kit for judging incidence possibility of IgA nephropathy

Abstract

The invention provides a method which is used for judging the incidence possibility of IgA nephropathy and is higher in accuracy. According to one aspect of the present invention, a method for determining the likelihood of onset of IgA nephropathy in a subject comprises a step for determining, in a sample collected from the subject, the level of a carbohydrate chain that binds to at least one selected from the group consisting of ACA, MAH, ABA, STL, LEL, WGA, MPA, artenin, MALI, PNA, ACG, GSLIA4, ConA, SSA, AOL, and GSLII.

Description

[0001] This application is a divisional application of an invention patent application with an application date of December 23, 2019, application number 201980059804.X, and invention name “Method and kit for determining the possibility of onset of IgA nephropathy”. Technical Field

[0002] The present invention relates to a method for judging the possibility of IgA nephropathy and a kit for judging the possibility of IgA nephropathy. Background Art

[0003] Currently, the number of patients with chronic kidney disease (CKD) has reached 13.3 million. This number means that 1 in 8 adults in Japan suffers from CKD, and it is no exaggeration to say that it is a national disease. CKD includes many diseases, and for one of them, chronic glomerulonephritis, there are 6,466 patients, accounting for 17.8% of CKD. Moreover, IgA nephropathy is the disease with the largest number of patients among chronic glomerulonephritis.

[0004] Since treatments for these kidney diseases have been established depending on the disease, it is important to have a diagnostic method that identifies which kidney disease a patient has. That is, (i) a diagnostic method that identifies patients with IgA nephropathy from a non-specific population, and (ii) a diagnostic method that identifies patients with IgA nephropathy from a group of patients with chronic glomerulonephritis are important. Usually, these kidney diseases are diagnosed by renal biopsy. However, in cases where the risk of renal biopsy is high, it is sometimes necessary to make a diagnosis based only on clinical information without performing a renal biopsy. In addition, since renal biopsy is an invasive examination, (i) there are cases where the urine observation results are very mild and the possibility of renal disease is ignored, and (ii) there are cases where a diagnosis of renal disease is not made in cases where a renal biopsy is not performed due to the risk to the body.

[0005] In this context, the method for diagnosing IgA nephropathy without renal biopsy has been studied and reported. For example, it is reported in non-patent literature 1 that, as a method for diagnosing IgA nephropathy, the ELISA using a monoclonal antibody combined with galactose-deficient abnormal IgA1 is more excellent in robustness than the conventional determination of a lectin called helix aspersa agglutinin (HAA). In addition, non-patent literature 2 has studied and reported a method for diagnosing IgA nephropathy by combining four types of clinical factors (hematuria, proteinuria, serum IgA value and serum IgA / C3 ratio).

[0006] Furthermore, as documents that may be related to the present invention, there are Patent Documents 1 to 4. The differences between each document and the present invention will be briefly described below.

[0007] Patent Document 1 discloses a technique for diagnosing diabetes, early diabetic nephropathy, and diabetic nephropathy. Patent Document 2 discloses a technique for analyzing the interaction between proteins and sugar chains, and does not mention the diagnosis of a specific disease. Patent Document 3 discloses a technique for diagnosing the degree of progression of diabetic nephropathy. Patent Document 4 discloses a technique for judging the possibility of future decline in renal function. The techniques disclosed in these documents differ from the present invention at least in that they are not diagnostic methods for IgA nephropathy. That is, Patent Documents 1 to 3 do not disclose IgA nephropathy, and Patent Document 4 does not disclose "diagnosis during examination" (the technique disclosed in Document 4 predicts future renal prognosis, not current diagnosis).

[0008] In addition, none of Patent Documents 1 to 4 discloses the kit disclosed in the present specification (kit in combination with a specific lectin).

[0009] Prior art literature

[0010] Patent Literature

[0011] Patent Document 1: Japanese Patent Publication "Tokkaihei No. 10-332690"

[0012] Patent Document 2: International Publication No. 2005 / 064333 Pamphlet

[0013] Patent Document 3: Japanese Patent Publication No. 2010-256132

[0014] Patent Document 4: International Publication No. 2018 / 181292 Pamphlet

[0015] Non-patent literature

[0016] Non-patent literature 1: Yasutake J, Suzuki Y, Suzuki H, et al. Novel lectin-independent approach to detect galactose-deficient IgA1 in IgAnephropathy. Nephrol Dial Transplant. 2015; 30: 1315-1321.

[0017] Non-patent literature 2: Nakayama K, Ohsawa I, Maeda-Ohtani A, et al. Prediction of diagnosis of immunoglobulin A nephropathy prior to renal biopsy and correlation with urinary sediment findings and prognostic grading. J Clin LabAnal. 2008; 22(2): 114-118. Summary of the invention

[0018] Problems to be solved by the invention

[0019] However, in the above-mentioned prior art, the diagnostic accuracy of IgA nephropathy still has room for improvement. That is, for the diagnostic method described in non-patent document 1, the actual diagnostic accuracy of IgA nephropathy has not been studied, and its usability is unknown. In addition, the diagnostic method described in non-patent document 2 is insufficient in sensitivity and specificity, and there is no report on studying the effectiveness of the diagnostic method.

[0020] One aspect of the present invention is to provide a method for determining the likelihood of developing IgA nephropathy with higher accuracy.

[0021] Means used to solve problems

[0022] The present invention comprises the following constitution:

[0023] <1>

[0024] A method for determining the likelihood of IgA nephropathy in a subject,

[0025] The method includes the step of determining the level of sugar chains bound to a lectin in a sample collected from the subject, wherein the lectin is selected from at least one of the group consisting of ACA, MAH, ABA, STL, LEL, WGA, MPA, Jacalin, MAL_I, PNA, ACG, GSL_I_A4, ConA, SSA, AOL and GSL_II.

[0026] <2>

[0027] A method for determining the likelihood of IgA nephropathy in a subject,

[0028] The method comprises: determining, in a first sample collected from the subject, a level of sugar chains bound to a lectin, wherein the lectin is selected from at least one of the group consisting of ACA, MAH, ABA, MPA, Jacalin, LEL, ACG, STL, GSL_I_A4, WGA, SSA, PNA, ConA, Calsepa, AOL, SNA, UDA, LCA, GSL_II, UEA_I, LTL, MAL_I, TJA_I, ECA, PWM, PSA, AAL, DSA, BPL, TJA_II, NPA, PHA_E, RCA120, EEL, SBA, HPA, GNA, HHL, PTL_I, TxLC_I, PHA_L, GSL_I_B4, DBA, WFA, and VVA; and

[0029] A step of measuring a biomarker other than the sugar chain level in a second sample collected from the subject.

[0030] <3>

[0031] A method for determining the likelihood of onset of IgA nephropathy in a subject having a primary glomerular disease or a subject suspected of having a primary glomerular disease,

[0032] The method includes the step of determining the level of sugar chains bound to a lectin in a sample collected from the subject, wherein the lectin is selected from at least one of the group consisting of ACA, MAH, ABA, MPA, Jacalin, LEL, ACG, STL, GSL_I_A4, WGA, SSA, PNA, ConA, Calsepa, AOL, SNA, UDA, LCA, GSL_II, UEA_I, LTL, MAL_I, TJA_I, ECA, PWM, PSA, AAL, DSA, BPL, TJA_II, NPA, PHA_E, RCA120, SBA, GNA, HHL, PTL_I, TxLC_I, PHA_L, DBA, WFA and VVA.

[0033] <4>

[0034] A method for determining the likelihood of onset of IgA nephropathy in a subject having a primary glomerular disease or a subject suspected of having a primary glomerular disease,

[0035] The method includes: determining the level of sugar chains bound to a lectin in a first sample collected from the subject, wherein the lectin is selected from at least one of the group consisting of ACA, MAH, ABA, MPA, Jacalin, LEL, ACG, STL, GSL_I_A4, WGA, SSA, PNA, ConA, Calsepa, AOL, SNA, UDA, LCA, GSL_II, UEA_I, LTL, MAL_I, TJA_I, ECA, PWM, PSA, AAL, DSA, BPL, TJA_II, NPA, PHA_E, RCA120, EEL, SBA, HPA, GNA, HHL, PTL_I, TxLC_I, PHA_L, GSL_I_B4, DBA, WFA and VVA; and

[0036] A step of measuring a biomarker other than the sugar chain level in a second sample collected from the subject.

[0037] <5>

[0038] (i) a method for determining the possibility of developing IgA nephropathy in a subject, or (ii) a method for determining the possibility of developing IgA nephropathy in a subject having a primary glomerular disease or a subject suspected of having a primary glomerular disease,

[0039] The method includes the step of determining the level of one or more sugar chains selected from the group consisting of the following sugar chains in a sample collected from the subject:

[0040] (Galβ1-4GlcNAc) n ,

[0041] (GlcNAcβ1-4) n ,

[0042] (GlcNAcβ4MurNAc) n ,

[0043] Agalactosylated tri / tetra antennaryglycans,

[0044] Fucα1-2Galβ1-4GlcNAc,

[0045] Fucα1-6GlcNAc,

[0046] GalNAc,

[0047] Galβ1-3GalNAc,

[0048] GlcNAc,

[0049] High-Man including Manα1-6(Manα1-3)Man,

[0050] Siaα2-3Galβ1-3(Siaα2-6)GalNAc,

[0051] Siaα2-3Galβ1-4GlcNAc,

[0052] Siaα2-6Gal / GalNAc and

[0053] α-GalNAc.

[0054] <6>

[0055] according to <2> or <4> The method, wherein the biomarker other than the sugar chain level is one or more selected from urine occult blood, urine protein, serum IgA and serum IgA / C3 ratio.

[0056] <7>

[0057] according to <1> to <6> The method according to any one of the preceding claims, wherein the sample used in the step of determining the level of sugar chains is a urine sample.

[0058] <8>

[0059] (i) a kit for determining the likelihood of onset of IgA nephropathy in a subject, or (ii) a kit for determining the likelihood of onset of IgA nephropathy in a subject having a primary glomerular disease or a subject suspected of having a primary glomerular disease,

[0060] The kit comprises one or more lectins selected from the following groups A to C,

[0061] And does not contain any other types of lectins:

[0062] Group A: ACA, MAH, and ABA

[0063] Group B: GSL_I_A4

[0064] Group C: GSL_II, MAL_I, AOL, PNA, SNA and HPA.

[0065] <9>

[0066] (i) a kit for determining the likelihood of onset of IgA nephropathy in a subject, or (ii) a kit for determining the likelihood of onset of IgA nephropathy in a subject having a primary glomerular disease or a subject suspected of having a primary glomerular disease,

[0067] The kit comprises a lectin that binds to at least one sugar chain selected from each of the following groups a to c.

[0068] And does not contain other types of lectins:

[0069] Group a: Galβ1-3GalNAc and Siaα2-3Galβ1-3(Siaα2-6)GalNAc

[0070] Group b: α-GalNAc

[0071] Group c: galactosylated tri / tetraantennary glycans, Fucα1-2Galβ1-4GlcNAc, Fucα1-6GlcNAc, GlcNac, Galβ1-3GalNAc, Siaα2-3Galβ1-4GlcNAc, Siaα2-6Gal / GalNAc and α-GalNAc.

[0072] Effects of the Invention

[0073] According to one aspect of the present invention, a method for determining the likelihood of developing IgA nephropathy with higher accuracy is provided. DETAILED DESCRIPTION

[0074] An example of an embodiment of the present invention will be described in detail below, but the present invention is not limited thereto. Unless otherwise specified in the present specification, "A to B" indicating a numerical range means "A or more and B or less".

[0075] [1. Levels of sugar chains binding to lectins]

[0076] In a first aspect, the method of the present invention includes the step of determining the level of sugar chains bound to a specific lectin in a sample collected from a subject.

[0077] (Method for determining the level of sugar chains bound to lectins)

[0078] The inventors have found that the onset of IgA nephropathy can be determined based on the results of a test using a certain lectin (hereinafter referred to as a "lectin test") (i.e., based on the intensity of the lectin signal). Generally, it is known that a specific sugar chain specifically binds to a specific lectin. Therefore, the inventors' findings can be understood as "the onset of IgA nephropathy can be determined based on the level of sugar chains bound to certain lectins."

[0079] Therefore, as long as the "step of determining the level of sugar chains bound to lectin X" is the "step of determining the level of sugar chains having a specific structure that binds to lectin X", the method is not limited. That is, the "step of determining the level of sugar chains bound to lectin X" is not limited to the lectin test. Examples of methods other than the lectin test include liquid chromatography, mass spectrometry, ELISA, two-dimensional electrophoresis, protein array, bead assay, flow cytometry, Bioplex (registered trademark), and the like.

[0080] However, it is preferred to determine the sugar chain level by lectin test because it is easy to pre-treat the sample. In particular, when a urine sample is used as a sample, it is more preferred because it does not require steps such as concentration of the urine sample and removal of a large amount of protein (albumin, IgG, etc.) contained in the sample.

[0081] In one embodiment, "determining the level of sugar chains" may be accompanied by quantifying the amount of sugar chains contained in a sample. As a specific example, there may be mentioned measuring the concentration of sugar chains contained in a sample.

[0082] In other embodiments, "determining the level of sugar chains" can be comparing the amount of sugar chains contained in the sample with a predetermined reference value. As a specific example, it can be cited to determine whether the concentration of sugar chains contained in the sample is higher or lower than a predetermined reference value (cutoff value). In this case, the predetermined reference value can be appropriately determined by medical methods, statistical methods, etc. In addition, multiple reference values ​​can also be set as predetermined reference values.

[0083] The relationship between the level of sugar chains bound to lectins and the onset of IgA nephropathy can be determined, for example, by statistical methods (as an example, see the Examples of the present application). That is, for example, by statistical methods, it can be determined whether "high sugar chain levels are associated with the onset of IgA nephropathy" or "low sugar chain levels are associated with the onset of IgA nephropathy".

[0084] In one example, in the 1 sugar chain model (model (1)) and / or the 1 sugar chain + clinical factor model (model (2)) in the examples of the present application, for the 45 lectins studied, low levels of sugar chains bound to the lectin were associated with the onset of IgA nephropathy.

[0085] In addition, in the multiple sugar chain + clinical factor model (model 3) in the examples of the present application, regarding ACA, GSL_I_A4, MAH and ABA, low levels of sugar chains bound to these lectins are associated with the onset of IgA nephropathy. In contrast, regarding GSL_II, MAL_I, PNA, SNA and AOL, high levels of sugar chains bound to these lectins are associated with the onset of IgA nephropathy.

[0086] Therefore, the relationship between the level of sugar chains and the onset of IgA nephropathy may vary depending on the model used. However, those skilled in the art can determine the relationship between the level of sugar chains and the onset of IgA nephropathy in each model by performing routine operations with reference to the description of this specification.

[0087] (Subject)

[0088] In this specification, "subject" is not limited to humans. The method according to one embodiment of the present invention can also be applied to non-human mammals. As non-human mammals, even-toed ungulates (cattle, wild boars, pigs, sheep, goats, etc.), odd-toed ungulates (horses, etc.), rodents (mice, rats, hamsters, squirrels, etc.), lagomorphs (rabbits, etc.), carnivores (dogs, cats, ferrets, etc.) can be listed. In addition to livestock or companion animals (pets), the non-human mammals also include wild animals.

[0089] The present invention attempts to determine the onset of IgA nephropathy by the level of sugar chains in the sample. Sugar chains have smaller structural differences between species than proteins and nucleic acids. Therefore, if in the above-mentioned non-human mammals, the method according to one embodiment of the present invention is considered to be fully effective.

[0090] (sample)

[0091] In this specification, "sample" refers to all samples collected from subjects, and there is no particular limitation. The samples mentioned here include, in addition to blood, cerebrospinal fluid, lymph, breast milk, saliva, nasal mucus, sweat, urine, feces and exhaled air, tissue soluble substances, living tissue soluble substances, cell soluble substances, etc. from pathological specimens.

[0092] In one embodiment of the present invention, urine is used as a sample. Urine samples are suitable because urine is often used as biopsy material, other indicators related to renal function can be investigated simultaneously, and it is easy to collect (especially in the case of human subjects).

[0093] In one embodiment of the present invention, blood is used as a sample. A blood sample is preferred because blood is usually used as a biopsy material, other indicators related to renal function can be investigated simultaneously, and it is easy to collect (even in non-human subjects). The "blood" mentioned here includes, in addition to whole blood, parts that constitute whole blood (serum, plasma, blood clots, etc.).

[0094] (Lectin)

[0095] The lectins listed in the following embodiments will be described as follows:

[0096] ACA: Amaranthus Caudatus Agglutinin

[0097] MAH:Maackia Amurensis Hemagglutitnin

[0098] ABA:Amaranthus Caudatus Agglutinin

[0099] MPA: Maclurapomifera Agglutinin

[0100] Jacalin:Jackfruit Lectin

[0101] LEL: Lycopersicon Esculentum Lectin (Tomato Lectin)

[0102] ACG: Agrocybe cylindracea Galectin

[0103] STL:Solanum tuberosum Lectin

[0104] GSL_I_A4:Griffonia Simplicifolia Lectin IA4 (Griffonia simplicifolia Lectin IA4)

[0105] WGA:Triticum Unlgaris Agglutinin(Wheat Germ Agglutinin)

[0106] SSA: Sambucus sieboldiana lectin

[0107] PNA: Peanut Agglutinin

[0108] ConA:Canavalia ensiformis Agglutinin

[0109] Calsepa: Calystega Sepiem Lectin

[0110] AOL: Aspergillus Oryzae Lectin

[0111] SNA: Sambucus nigra agglutinin

[0112] UDA: Urtica dioica Agglutinin

[0113] LCA: Lens Culinaris Agglutinin

[0114] GSL_II:Griffonia Simplicifolia Lectin II (Griffonia Simplicifolia Lectin II)

[0115] UEA_I:Ulex Europaeus Agglutinin I

[0116] LTL:Lotus Tetragonolobus Lectin

[0117] MAL_I:Maackia Amurensis Lectin I

[0118] TJA_I:Trichosanthes japonica agglutinin I lectin ECA:Erythrina Cristagalli Agglutinin

[0119] PWM: Phytolacca americana Agglutinin

[0120] PSA: Pisum Sativum Agglutinin

[0121] AAL:Aleuria Aurantia Lectin

[0122] DSA: Datura Stramonium Agglutinin

[0123] BPL: Bauhinia Purpurea Lectin

[0124] TJA_II:Trichosanthes aponica Agglutinin-II

[0125] NPA: Narcissus Pseudonarcissus Agglutinin

[0126] PHA_E:Phaseolus Vulgaris ErythroAgglutinin (Red Kidney Bean Lectin E)

[0127] RCA120: Ricinus Communis Agglutinin I

[0128] EEL: Euonymus europaeus Lectin

[0129] SBA:Glycine Max Agglutinin (soybean agglutinin)

[0130] HPA: Helix pomatia Agglutinin

[0131] GNA:Galanthus Nivalis Agglutinin

[0132] HHL: Hippeastrum Hybrid Lectin

[0133] PTL_I:Psophocarpus Tetragonolobus Lectin-I

[0134] TxLC_I:Tulipa gesneriana Lectin-I

[0135] PHA_L:Phaseolus Vulgaris LeucoAgglutin (Red kidney bean lectin L)

[0136] GSL_I_B4:Griffonia Simplicifolia Lectin I B4 (Griffonia Simplicifolia Lectin I B4)

[0137] DBA: Dolichos biflorus Agglutinin

[0138] WFA: Wisteria Floribunda Agglutinin

[0139] VVA:Vicia villosa Lectin

[0140] These lectins are conventionally known lectins, and their amino acid sequence information can be obtained from various databases. The relationship between the level of sugar chains bound to these lectins and the onset of IgA nephropathy is as described in the item "Method for determining the level of sugar chains bound to lectins".

[0141] In addition, in the method according to one embodiment of the present invention, when determining the levels of two or more sugar chains, it is preferred that the two or more sugar chains have different structures from each other (this also applies to other embodiments described later). That is, in the method according to one embodiment of the present invention, when determining the levels of sugar chain x bound to lectin X and sugar chain y bound to lectin Y, it is preferred that the structures of sugar chain x and sugar chain y are different from each other. This is to avoid the problem of multicollinearity when creating a diagnostic model.

[0142] [1-1. Judgment on non-specific groups of people]

[0143] One embodiment of the present invention is a method for determining the possibility of developing IgA nephropathy in a subject; the method comprises: a step of determining the level of sugar chains bound to a lectin in a sample collected from the subject, wherein the lectin is selected from at least one of the group consisting of ACA, MAH, ABA, STL, LEL, WGA, MPA, Jacalin, MAL_I, PNA, ACG, GSL_I_A4, ConA, SSA, AOL and GSL_II.

[0144] The method according to this embodiment is a method for determining the possibility of IgA nephropathy in a subject belonging to a non-specific group, that is, a method for determining the possibility of IgA nephropathy in a subject when it is unknown whether the subject suffers from a certain kidney disease.

[0145] [1-2. Determination of the patient population with primary glomerular disease]

[0146] Another embodiment of the present invention is a method for determining the possibility of IgA nephropathy in a subject having a primary glomerular disease or a subject suspected of having a primary glomerular disease; the method comprising: a step of determining the level of sugar chains bound to a lectin in a sample collected from the subject, the lectin being selected from at least one of the group consisting of ACA, MAH, ABA, MPA, Jacalin, LEL, ACG, STL, GSL_I_A4, WGA, SSA, PNA, ConA, Calsepa, AOL, SNA, UDA, LCA, GSL_II, UEA_I, LTL, MAL_I, TJA_I, ECA, PWM, PSA, AAL, DSA, BPL, TJA_II, NPA, PHA_E, RCA120, SBA, GNA, HHL, PTL_I, TxLC_I, PHA_L, DBA, WFA and VVA.

[0147] The method according to this embodiment is a method for determining the possibility of IgA nephropathy in a subject belonging to a subject group suffering from (suspected of suffering from) primary glomerular disease. That is, a method for determining the possibility of IgA nephropathy in a subject when it is clear that the subject suffers from (or is suspected of suffering from) primary kidney disease. Compared with the diagnostic method described in [1-1], the total population of this method is more limited.

[0148] According to known medical techniques, it can be known that "the subject suffers from primary glomerular disease" and "the subject may suffer from primary glomerular disease".

[0149] According to the method of this embodiment, it is sufficient to determine the possibility of IgA nephropathy in the subject. However, when the method according to this embodiment can determine that a subject with a primary glomerular disease or a subject suspected of having a primary glomerular disease will not develop the disease (low possibility of developing the disease), it can be determined that the subject has a primary glomerular disease other than IgA nephropathy (high possibility of developing the disease).

[0150] Here, in Japan, IgA nephropathy is generally included in the category of primary glomerular diseases, but according to the WHO classification, IgA nephropathy is included in the category of secondary glomerular diseases. The description of this specification follows the Japanese classification, and IgA nephropathy should be regarded as a type of primary glomerular disease.

[0151] Incidentally, when the WHO classification is adopted, "a method for determining the possibility of onset of IgA nephropathy in a subject having a primary glomerular disease or a subject suspected of having a primary glomerular disease" can be understood as "a method for determining the possibility of onset of IgA nephropathy in a subject having a primary glomerular disease or IgA nephropathy or a subject suspected of having a primary glomerular disease or IgA nephropathy". Even if understood in this way, the effect of the present embodiment of improving the accuracy of discrimination between IgA nephropathy and other primary glomerular diseases remains unchanged.

[0152] [2. Combination of the level of sugar chains bound to lectins and other biomarkers]

[0153] In a second aspect, the method of the present invention comprises: (i) a step of determining the level of sugar chains bound to a specific lectin in a first sample collected from a subject, and (ii) a step of determining a biomarker in a second sample collected from the subject. In this case, the biomarker determined in the second sample is different from the sugar chain bound to the specific lectin whose level is determined in the first sample.

[0154] According to the method of this embodiment, the possibility of onset of IgA nephropathy in a subject can be determined with higher accuracy. In particular, when combined with a biomarker previously used for diagnosis of IgA nephropathy, an effect of increased diagnostic accuracy can be easily expected.

[0155] Regarding the method, subject, sample and lectin for determining the level of sugar chains bound to a specific lectin, as described in Section [1].

[0156] (Method for determining biomarkers in the second sample)

[0157] The method for measuring the biomarker in the second sample can be appropriately set according to the type of sample and the type of biomarker. For the type of sample and the type of measurement method, please refer to the description of [1].

[0158] The second sample may be the same as or different from the first sample. In addition, when multiple biomarkers are determined from the second sample, each biomarker may be determined from different samples. For example, in an embodiment of the present application, the level of sugar chains is determined from the first sample (urine), and serum IgA, urine occult blood, and urine protein are determined from the second sample (serum and urine).

[0159] In addition, the biomarker measured from the second sample may be a sugar chain. That is, this embodiment also includes determining the level of sugar chain A that binds to a specific lectin in the first sample and determining the level of sugar chain B different from sugar chain A in the second sample.

[0160] Examples of biomarkers measured from the second sample include age, sex, BMI, mean arterial pressure, HbA1c, estimated glomerular filtration rate (eGFR), urine protein level, urine occult blood, serum IgA, complement C3, serum IgA / C3 ratio, etc. Among them, urine protein level, urine occult blood, serum IgA, and serum IgA / C3 ratio are considered to be biomarkers indicating the onset of IgA nephropathy (see Non-Patent Document 2), and it is easy to expect that the effect will be increased by combining with the sugar chain level.

[0161] [2-1. Judgment on the general population]

[0162] One embodiment of the present invention is a method for determining the possibility of developing IgA nephropathy in a subject; the method comprises: a step of determining the level of sugar chains bound to a lectin in a first sample collected from the subject, the lectin being selected from at least one of the group consisting of ACA, MAH, ABA, MPA, Jacalin, LEL, ACG, STL, GSL_I_A4, WGA, SSA, PNA, ConA, Calsepa, AOL, SNA, UDA, LCA, GSL_II, UEA_I, LTL, MAL_I, TJA_I, ECA, PWM, PSA, AAL, DSA, BPL, TJA_II, NPA, PHA_E, RCA120, EEL, SBA, HPA, GNA, HHL, PTL_I, TxLC_I, PHA_L, GSL_I_B4, DBA, WFA and VVA; and a step of measuring a biomarker other than the level of the sugar chain in a second sample collected from the subject.

[0163] The method according to the present embodiment is the same as the method described in Section [1-1], and is a method for judging the possibility of onset of IgA nephropathy in a subject belonging to a non-specific group.

[0164] In the step of determining the level of sugar chains bound to lectins, the levels of two or more sugar chains may be determined. For example,

[0165] (1) The levels of sugar chains bound to each of the ACA, GSL_I_A4, and GSL_II lectins can be determined;

[0166] (2) the levels of sugar chains bound to each of the MAH, GSL_I_A4, and MAL_I lectins can be determined;

[0167] (3) the levels of sugar chains bound to each of the lectins ABA, GSL_I_A4, and AOL can be determined;

[0168] (4) the levels of sugar chains bound to each of the MAH, GSL_I_A4, and PNA lectins can be determined;

[0169] (5) the levels of sugar chains bound to each of the MAH, GSL_I_A4, and SNA lectins can be determined;

[0170] (6) the levels of sugar chains bound to each of the ABA, GSL_I_A4, and MAL_I lectins can be determined;

[0171] (7) The levels of sugar chains bound to each of the ABA+GSL_I_A4+GSL_II lectins can be determined.

[0172] In the method according to this embodiment, in the step of determining the level of sugar chains bound to lectins, the level of sugar chains including the combination may be determined, or only the level of sugar chains of the combination may be determined. For example, (i) in addition to the level of sugar chains bound to each of ACA, GSL_I_A4 and GSL_II lectins, the level of sugar chains bound to other lectins may be determined, or (ii) only the level of sugar chains bound to each of ACA, GSL_I_A4 and GSL_II may be determined.

[0173] [2-2. Determination of the patient population with primary glomerular disease]

[0174] Another embodiment of the present invention is a method for determining the possibility of IgA nephropathy in a subject suffering from primary glomerular disease or a subject suspected of suffering from primary glomerular disease; the method comprises: determining the level of sugar chains bound to a lectin in a first sample collected from the subject, the lectin being selected from ACA, MAH, ABA, MPA, Jacalin, LEL, ACG, STL, GSL_I_A4, WGA, SSA, PNA, ConA, Calsepa, AOL, SNA , UDA, LCA, GSL_II, UEA_I, LTL, MAL_I, TJA_I, ECA, PWM, PSA, AAL, DSA, BPL, TJA_II, NPA, PHA_E, RCA120, EEL, SBA, HPA, GNA, HHL, PTL_I, TxLC_I, PHA_L, GSL_I_B4, DBA, WFA and VVA; and a step of determining a biomarker other than the level of the sugar chain in a second sample collected from the subject.

[0175] The method according to this embodiment is the same as the method described in Section [1-2], and is a method for determining the possibility of IgA nephropathy in a subject belonging to a subject group suffering from (suspected of suffering from) primary glomerular disease. In addition, the description of this embodiment refers to the description of Section [1-2].

[0176] In the step of determining the level of sugar chains bound to lectins, the levels of two or more sugar chains may be determined. For example, the levels of sugar chains bound to each of MAH, GSL_I_A4, and HPA lectins may be determined.

[0177] In the method according to the present embodiment, in the step of determining the level of sugar chains bound to lectins, the level of sugar chains including the combination may be determined, or only the level of sugar chains of the combination may be determined. For example, (i) in addition to the level of sugar chains bound to each of MAH, GSL_I_A4 and HPA lectins, the level of sugar chains bound to other lectins may be determined, or (ii) only the level of sugar chains bound to each of MAH, GSL_I_A4 and HPA lectins may be determined.

[0178] [3. Determination of specific sugar chain levels]

[0179] As described above, lectins have the property of specifically binding to sugar chains having a specific structure. Therefore, in this specification, "sugar chains that bind to lectin X" can also be determined by structure. Table 1 below shows examples of lectins and sugar chains that specifically bind to the lectins that appear in this specification.

[0180] [Table 1]

[0181] Table 1

[0182]

[0183]

[0184] Based on Table 1, in section [1-1], “the step of determining the level of sugar chains bound to a lectin in a sample collected from the subject, wherein the lectin is at least one selected from the group consisting of ACA, MAH, ABA, STL, LEL, WGA, MPA, jacalin, MAL_I, PNA, ACG, GSL_I_A4, ConA, SSA, AOL, and GSL_II” can be rewritten as “the step of determining the level of one or more sugar chains selected from the group consisting of the following sugar chains in a sample collected from the subject:

[0185] (Galβ1-4GlcNAc) n ,

[0186] (GlcNAcβ1-4) n ,

[0187] (GlcNAcβ4MurNAc) n ,

[0188] Agalactosylated tri / tetra antennaryglycans,

[0189] Fucα1-2Galβ1-4GlcNAc,

[0190] Fucα1-6GlcNAc,

[0191] GalNAc,

[0192] Galβ1-3GalNAc,

[0193] GlcNAc,

[0194] High-Man including Manα1-6(Manα1-3)Man,

[0195] Siaα2-3Galβ1-3(Siaα2-6)GalNAc,

[0196] Siaα2-3Galβ1-4GlcNAc,

[0197] Siaα2-6Gal / GalNAc, and

[0198] α-GalNAc".

[0199] Similarly, based on Table 1, in section [1-2], “a step of determining the level of a sugar chain bound to a lectin in a sample collected from the subject, wherein the lectin is at least one selected from the group consisting of ACA, MAH, ABA, MPA, jacalin, LEL, ACG, STL, GSL_I_A4, WGA, SSA, PNA, ConA, Calsepa, AOL, SNA, UDA, LCA, GSL_II, UEA_I, LTL, MAL_I, TJA_I, ECA, PWM, PSA, AAL, DSA, BPL, TJA_II, NPA, PHA_E, RCA120, SBA, GNA, HHL, PTL_I, TxLC_I, PHA_L, DBA, WFA, and VVA” can be rewritten as “a step of determining the level of one or more sugar chains selected from the group consisting of the following sugar chains in a sample collected from the subject:

[0200] (Galβ1-4GlcNAc) n ,

[0201] (GlcNAcβ1-4) n ,

[0202] (GlcNAcβ4) n ,

[0203] (GlcNAcβ4MurNAc) n ,

[0204] Agalactosylated tri / tetra antennaryglycans,

[0205] Bi- and tri-antennary N-glycans,

[0206] Blood group Aantigen,

[0207] Fucα1-2Galβ1-4GlcNAc,

[0208] Fucα1-6GlcNAc,

[0209] Fucα2(Galα3)Galβ1-4GlcNAc,

[0210] Fucα2Galβ1,

[0211] Fucα2Galβ4GlcNAc(H-2 type)

[0212] Fucα3(Galb4)GlcNAc(Lex),

[0213] Fucα3(Galβ4)GlcNAc(Lex),

[0214] Fucα6GlcNAc (core Fuc),

[0215] Fucα6GlcNAc,

[0216] GalNAc,

[0217] GalNAcα1-3Gal,

[0218] GalNAcα1-3GalNAc,

[0219] GalNAcβ1,

[0220] GalNAcβ1-4GlcNAc,

[0221] Galα1-3Galβ1-4GlcNAc,

[0222] Galβ1-3GalNAc,

[0223] Galβ1-4GlcNAc,

[0224] Galβ3(-6)GalNAc,

[0225] Galβ4GlcNAc,

[0226] GlcNAc,

[0227] GlcNAcβ4GlcNAc,

[0228] High-Man,

[0229] High-Man (Man2-6),

[0230] High-Man including Manα1-6(Manα1-3)Man,

[0231] High-Man including Manα3Man (High-Man including Manα3Man),

[0232] High-Man including Manα6Man (High-Man including Manα6Man),

[0233] Man3 core,

[0234] Man5~Man9,

[0235] N-glycans including bisecting GlcNAc, N-glycans with outer Gal and bisecting GlcNAc,

[0236] Siaα2-3Galβ1-3(Siaα2-6)GalNAc,

[0237] Siaα2-3Galβ1-4GlcNAc,

[0238] Siaα2-6Gal / GalNAc,

[0239] Tetraantennary N-glycans

[0240] Tri / tetra-antennary complex-type N-glycan,

[0241] triantennary

[0242] αGal,

[0243] α-GalNAc".

[0244] In addition, based on Table 1, in Sections [2-1] and [2-2], "a step of determining the level of sugar chains bound to a lectin in a first sample collected from the subject, the lectin being selected from the group consisting of ACA, MAH, ABA, MPA, Jacalin, LEL, ACG, STL, GSL_I_A4, WGA, SSA, PNA, ConA, Calsepa, AOL, SNA, UDA, LCA, GSL_II, UEA_I, LTL, M AL_I, TJA_I, ECA, PWM, PSA, AAL, DSA, BPL, TJA_II, NPA, PHA_E, RCA120, EEL, SBA, HPA, GNA, HHL, PTL_I, TxLC_I, PHA_L, GSL_I_B4, DBA, WFA and VVA” can be rewritten as “a step of determining the level of one or more sugar chains selected from the group consisting of the following sugar chains in a sample collected from the subject:

[0245] (Galβ1-4GlcNAc) n ,

[0246] (GlcNAcβ1-4) n ,

[0247] (GlcNAcβ4) n ,

[0248] (GlcNAcβ4MurNAc) n ,

[0249] Galactosylated tri / tetraantennary glycans,

[0250] Biantennary N-glycans and triantennary N-glycans,

[0251] A blood antigen,

[0252] Fucα1-2Galβ1-4GlcNAc,

[0253] Fucα1-6GlcNAc,

[0254] Fucα2Galβ1,

[0255] Fucα2Galβ4GlcNAc(H-2 type)

[0256] Fucα3(Gal4)GlcNAc(Lex),

[0257] Fucα6GlcNAc (core Fuc),

[0258] Fucα6GlcNAc,

[0259] GalNAc,

[0260] GalNAcα1-3Gal,

[0261] GalNAcα1-3GalNAc,

[0262] GalNAcβ1,

[0263] GalNAcβ1-4GlcNAc,

[0264] Galβ1-3GalNAc,

[0265] Galβ1-4GlcNAc,

[0266] Galβ3(-6)GalNAc,

[0267] Galβ4GlcNAc,

[0268] GlcNAc,

[0269] GlcNAcβ4GlcNAc,

[0270] High-Man,

[0271] High-Man (Man2-6),

[0272] High-Man including Manα1-6 (Manα1-3)Man,

[0273] High-Man including Manα3Man,

[0274] High-Man including Manα6Man,

[0275] Man3 core,

[0276] Man5~Man9,

[0277] N-glycans including bisected GlcNAc,

[0278] N-glycans with external Gal and bisecting GlcNAc,

[0279] Siaα2-3Galβ1-3(Siaα2-6)GalNAc,

[0280] Siaα2-3Galβ1-4GlcNAc,

[0281] Siaα2-6Gal / GalNAc,

[0282] Tetraantennary N-glycans,

[0283] Tri- / tetra-antennary complex N-glycans,

[0284] Three-tentacled,

[0285] α-GalNAc".

[0286] Further, based on Table 1, in Sections [2-1] and [2-2],

[0287] (1) “Sugar chains that bind to each of the ACA, GSL_I_A4 and GSL_II lectins” can be rewritten as “Galβ1-3GalNAc, α-GalNAc and galactosylated tri / tetraantennary glycans or GlcNAc”;

[0288] (2) “Sugar chains that bind to each of the MAH, GSL_I_A4 and MAL_I lectins” can be rewritten as “Siaα2-3Galβ1-3(Siaα2-6)GalNAc, α-GalNAc and Siaα2-3Galβ1-4GlcNAc”;

[0289] (3) “Sugar chains that bind to each of the lectins ABA, GSL_I_A4, and AOL” can be rewritten as “Galβ1-3GalNAc, α-GalNAc, and Fucα1-6GlcNAc or Fucα1-2Galβ1-4GlcNAc”;

[0290] (4) “Sugar chains that bind to each of MAH, GSL_I_A4 and PNA lectins” can be rewritten as “Siaα2-3Galβ1-3(Siaα2-6)GalNAc, α-GalNAc and Galβ1-3GalNAc”;

[0291] (5) “Sugar chains that bind to each of the MAH, GSL_I_A4 and SNA lectins” can be rewritten as “Siaα2-3Galβ1-3(Siaα2-6)GalNAc, α-GalNAc and Siaα2-6Gal / GalNAc”;

[0292] (6) “Sugar chains that bind to ABA, GSL_I_A4 and MAL_I lectins” can be rewritten as “Galβ1-3GalNAc, α-GalNAc and Siaα2-3Galβ1-4GlcNAc”;

[0293] (7) “Sugar chains that bind to each lectin of ABA+GSL_I_A4+GSL_II” can be rewritten as “Galβ1-3GalNAc, α-GalNAc, and galactosylated tri / tetraantennary glycans or GlcNAc”;

[0294] (8) “Sugar chains that bind to each of the MAH, GSL_I_A4 and HPA lectins” can be rewritten as “Siaα2-3Galβ1-3(Siaα2-6)GalNAc and α-GalNAc”;

[0295] (Putative biochemical mechanism)

[0296] In the examples described below, the AUC was the largest for the diagnostic model in which sugar chains that bind to lectins of ACA, GSL_I_A4 and GSL_II were added to the three clinical factors. As described above, the combination of these sugar chains is a combination of (i) Galβ1-3GalNAc, (ii) α-GalNAc and (iii) galactosylated tri / tetraantennary glycans or GlcNAc.

[0297] This fact is consistent with the known facts about IgA nephropathy. That is, in IgA nephropathy, it has been pointed out that the galactosylation of the O-type sugar chain of the IgA molecule is poor, and Galβ1-3GalNAc has a galactosylated O-type sugar chain structure. Therefore, even if the decrease in the level of Galβ1-3galnac is interpreted as related to IgA nephropathy, it has its validity.

[0298] Furthermore, from the above facts, it can be considered that since the activity of α2,3 sialyltransferase increases in IgA nephropathy, α-GalNAc is converted to Siaα2-3GalNAc, thereby reducing the level of α-GalNAc. In addition, since galactosylated tri / tetraantennary glycans have an N-type sugar chain structure with incomplete galactosylation, it is suggested that incomplete galactosylation also exists in the N-type sugar chain structure.

[0299] However, the above description is used to help understand the inferred mechanism of the present invention and does not limit the scope of the present invention.

[0300] [4. Test kit]

[0301] [4-1. Lectins included in the kit]

[0302] The kit according to one embodiment of the present invention comprises a lectin that binds to a specific sugar chain contained in a sample collected from a subject. For such sugar chains and lectins that bind to the sugar chains, see the description in Sections [1] to [3].

[0303] The kit according to one embodiment of the present invention is (i) a kit for determining the possibility of IgA nephropathy in a subject, or (ii) a kit for determining the possibility of IgA nephropathy in a subject suffering from a primary glomerular disease or a subject suspected of suffering from a primary glomerular disease; the kit comprises one or more lectins selected from the following groups A to C respectively; and does not comprise other types of lectins:

[0304] Group A: ACA, MAH, and ABA

[0305] Group B: GSL_I_A4

[0306] Group C: GSL_II, MAL_I, AOL, PNA, SNA and HPA.

[0307] Here, one or more lectins are selected from each of groups A to C. That is, one, two or three lectins are selected from group A. One lectin is selected from group B. One, two, three, four, five or six lectins are selected from group C.

[0308] In one embodiment, the lectin selected from each of Groups A to C is not (i) ACA and / or ABA selected from Group A, (ii) GSL_I_A4 selected from Group B, and (iii) PNA and / or HPA selected from Group C.

[0309] In one embodiment, the lectin selected from each group A to C is not (i) ACA and / or ABA selected from group A, (ii) GSL_I_A4 selected from group B, and (iii) PNA, SNA and / or HPA selected from group C.

[0310] A kit according to another embodiment of the present invention is (i) a kit for determining the possibility of IgA nephropathy in a subject, or (ii) a kit for determining the possibility of IgA nephropathy in a subject suffering from a primary glomerular disease or a subject suspected of suffering from a primary glomerular disease; comprising a lectin that binds to one or more sugar chains selected from each of the following groups a to c; and not comprising other types of lectins:

[0311] Group a: Galβ1-3GalNAc and Siaα2-3Galβ1-3(Siaα2-6)GalNAc

[0312] Group b: α-GalNAc

[0313] Group c: galactosylated tri / tetraantennary glycans, Fucα1-2Galβ1-4GlcNAc, Fucα1-6GlcNAc, GlcNac, Galβ1-3GalNAc, Siaα2-3Galβ1-4GlcNAc, Siaα2-6Gal / GalNAc and α-GalNAc.

[0314] Here, one or more sugar chains are selected from each of groups a to c. That is, one or two sugar chains are selected from group a. One sugar chain is selected from group b. One, two, three, four, five, six, seven or eight sugar chains are selected from group c.

[0315] In addition, the type of lectin that binds to each sugar chain may be one or more. For example, when galactosylated tri / tetraantennary glycans are selected from group c, the kit according to one embodiment of the present invention may have only one lectin that binds to galactosylated tri / tetraantennary glycans, or may have two or more lectins that bind to galactosylated tri / tetraantennary glycans.

[0316] In addition, the same sugar chain may be selected from two or more groups. For example, α-GalNAc may be selected from group b and group c. In this case, the kit according to one embodiment of the present invention may have only one lectin that binds to α-GalNAc, or may have two or more lectins that bind to α-GalNAc.

[0317] In one embodiment, the sugar chain selected from each of groups a to c is not (i) Galβ1-3GalNAc selected from group a, (ii) α-GalNAc selected from group b, and (iii) Galβ1-3GalNAc, Siaα2-6Gal / GalNAc and / or α-GalNAc selected from group c.

[0318] In one embodiment, the lectin that binds to the sugar chain selected from each of groups a to c is not a combination of at least one lectin selected from each of the following groups 1 and 2:

[0319] Group 1: BPL, ABA, japonin, PNA, ACA, MPA

[0320] Group 2: HPA, VVA, PTL_I, GSL_I_A4

[0321] If a kit having the above lectin combination is used, the possibility of IgA nephropathy in a subject can be determined with higher accuracy than the prior art. The subject may be a subject belonging to a non-specific group or a subject suffering from or suspected of suffering from a primary glomerular disease.

[0322] The above-mentioned lectin can be prepared by a known method, or a commercially available lectin can be used as appropriate.

[0323] [4-2. Other components]

[0324] In the kit according to one embodiment of the present invention, the lectin can be immobilized on any substrate. For example, the lectin can be immobilized on a substrate such as a microarray, an ELISA plate, latex beads or magnetic beads.

[0325] In the above description, the method of fixing the lectin on the microarray is preferred. In this method, when urine is used as a sample, there are the following advantages: (i) there is no need to concentrate the sample, and (ii) there is no need to remove the main proteins (albumin, IgG, etc.) in the sample. As a method for fixing the lectin on a substrate, a known method for fixing a protein on a substrate can be used.

[0326] In addition, the kit according to one embodiment of the present invention may also include drugs, tools, containers, instructions, etc. required for using the kit. In addition, the drugs, tools, containers, instructions, etc. may be obtained separately by the user through the market or communication lines.

[0327] [5. Other aspects]

[0328] The method for judging the possibility of onset of IgA nephropathy in a subject according to the present invention is not a diagnostic method of IgA nephropathy performed by a doctor, but is only an auxiliary method for diagnosing IgA nephropathy in a subject.

[0329] However, the method for determining the possibility of onset of IgA nephropathy in a subject according to the present invention can also be applied to the method for diagnosing IgA nephropathy. Therefore, the present invention also includes "a method for diagnosing IgA nephropathy". In addition, the description of "a method for diagnosing IgA nephropathy" can refer to the description of "a method for determining the possibility of onset of IgA nephropathy" in this specification. At this time, the phrase "a method for determining the possibility of onset of IgA nephropathy" can be understood as "a method for diagnosing IgA nephropathy".

[0330] The contents described in the above items may be appropriately incorporated into other items. The present invention is not limited to the above-mentioned various embodiments, and various modifications may be made within the scope indicated in the claims. Therefore, the embodiments obtained by appropriately combining the various technical means disclosed in different embodiments are also included in the technical scope of the present invention.

[0331] All academic documents and patent documents described in this specification are incorporated into this specification by reference.

[0332] The present invention will be described in more detail below by way of examples, but the present invention is not limited to the following examples.

[0333] Example

[0334] According to the method of one embodiment of the present invention, the following problems are studied: (i) the diagnostic accuracy of distinguishing IgA nephropathy patients from a group including healthy people, and (ii) the diagnostic accuracy of distinguishing patients with primary glomerular diseases and IgA nephropathy patients.

[0335] [method]

[0336] [Patient selection]

[0337] A total of 506 people were included in the analysis, excluding 19 patients with IgA nephropathy and other kidney diseases from a total of 525 people, including 510 kidney disease patients and 15 healthy people. In addition, prior consent was obtained from all participants through the prescribed procedures. The chronic kidney disease patients were all patients who had renal biopsies at Okayama University Hospital from December 2010 to September 2017 and had confirmed renal pathology.

[0338] [Measurement of sugar chain levels by lectin array analysis]

[0339] Using lectin arrays (GlycoStation (registered trademark, hereinafter the same) and LecChip (registered trademark, hereinafter the same), manufactured by GlycoTechnica), the signal intensity of sugar chains in urine bound to 45 types of lectins was quantified according to the following protocol. The urine sample used for the measurement was collected and stored before kidney biopsy or during a physical examination.

[0340] 1. Mix 20 μL of a 10-fold diluted urine sample and 100 μg of Cy3 single reactive dye label (manufactured by GE Healthcare Life Science) and react at room temperature in the dark for 1 hour.

[0341] 2. Centrifuge the desalting column at 1,500 × g for 1 minute at 4°C.

[0342] 3. Pass 300 μL of TBS through the desalting column. Then centrifuge the desalting column at 1,500 × g for 1 minute at 4°C and wash. Repeat this process three times.

[0343] 4. Pass the entire urine sample and 25 μL of TBS through a desalting column and then centrifuge at 1,500×g for 2 minutes at 4°C to remove unreacted Cy3.

[0344] 5. To the urine sample obtained in 4, 450 μL of Probing Solution (manufactured by GlycoTechnica) was added, and then 500 μL was measured.

[0345] 6. Wash the LecChip three times with the detection solution (100 mL / well each time). Then, inject the urine sample solution prepared in 5 into the wells (100 μL / well).

[0346] 7. Allow LecChip to react at 20°C for more than 16 hours.

[0347] 8. LecChip was measured using GlycoStationReader 1200. The measurement was performed in a liquid phase in which the urine sample was reacted. The cumulative number of measurements was 4, the exposure time was 299 milliseconds, and the camera gains were 85, 95, 105, 115, and 125.

[0348] 9. The measured values ​​were quantified by GlycoStation ToolsPro Suite 1.5.

[0349] 10. The value obtained by subtracting the background signal value from the signal intensity corresponding to each lectin was defined as the sugar chain signal of each lectin and used for analysis.

[0350] [Clinical factors]

[0351] The following items were measured as clinical factors: age at renal biopsy, sex, BMI, blood pressure, serum Cr, serum IgA, complement C3, presence of diabetic complications, HbA1c (NGSP value), presence of urine occult blood, and daily urine protein amount (g / day).

[0352] The presence or absence of urine occult blood was determined according to the Hematuria Diagnosis Guidelines 2013 (Japanese Society of Clinical Laboratory Medicine). Specifically, when urine sedimentation was examined several times in the early morning before kidney biopsy, (i) the number of red blood cells in urine was observed to be 5 / HPF or more twice, and (ii) the morphology of red blood cells in urine was judged to be glomerular urine occult blood, and thus the patient was judged to have "urine occult blood".

[0353] eGFR (ml / min / 1.73m 2 ) was calculated from serum Cr value using the CKD-EPI formula.

[0354] The value of each sugar chain signal was subjected to 1 / 1000-fold, 1 / 10000-fold or logarithmic transformation according to its distribution and value for analysis. Similarly, the daily urine protein amount was used for analysis after natural logarithmic transformation.

[0355] [end]

[0356] The primary endpoint was the differential diagnosis between IgA nephropathy and non-IgA nephropathy (however, cases where IgA nephropathy coexisted with other renal diseases were excluded). That is, a diagnosis was performed to distinguish whether the subject was (i) a subject with only IgA nephropathy, or (ii) a subject with a renal disease other than IgA nephropathy or a healthy person.

[0357] In addition, the differential diagnosis between IgA nephropathy and primary glomerular disease was used as a secondary endpoint. That is, a diagnosis was performed to distinguish whether a subject with a primary glomerular disease was (i) a subject with only IgA nephropathy or (ii) a subject with a primary glomerular disease other than IgA nephropathy.

[0358] [analyze]

[0359] The ROC-AUCs of the following four models were compared by univariate logistic regression analysis or multivariate logistic regression analysis, and their effectiveness was investigated.

[0360] Model (1): ROC-AUC by multivariate logistic regression analysis using serum IgA (315 mg / dL or more vs. less than 315 mg / dL), the presence of urine occult blood, and daily urine protein (0.3 g / day or more vs. less than 0.3 g / day). This model corresponds to the prior art.

[0361] Model (2): ROC-AUC of each of the 45 lectin signals using a univariate logistic regression model.

[0362] Model (3): ROC-AUC performed by a complex multivariate logistic regression model consisting of one lectin signal and three clinical factors in model (1).

[0363] Model (4): ROC-AUC performed by a complex multivariate logistic regression model consisting of multiple lectin signals and the three clinical factors in model (1).

[0364] Regarding model (1), in Japan's "IgA Nephropathy Guidelines 2017 (IgA Nephropathy Guidelines 2017)", serum IgA / complement C3 (≥3.01 vs <3.01) is proposed as a predictive model for diagnosis in addition to the above three clinical factors. However, in the population used in this study, the correlation between serum IgA and serum IgA / complement C3 was very strong. Therefore, considering the problem of multicollinearity, serum IgA / complement C3 was excluded from the variables of model (1). In addition, in the above guidelines, it is also pointed out that serum IgA is more important than serum IgA / complement C3, and serum IgA is considered to be a factor that better reflects the pathology of IgA nephropathy. Therefore, it can be inferred that model (1) as a clinical factor model also has a certain degree of validity.

[0365] For models (3) and (4), serum IgA and daily urine protein were treated as continuous variables rather than categorical variables with cutoff values. This is because there is no empirical evidence or report on whether the routinely used cutoff values ​​(reference model (1)) can also be promoted in Japanese IgA nephropathy patients.

[0366] Regarding model (4), when multiple lectin signals were input into the model, the correlation between each lectin signal and clinical factors was studied, and those with weak correlations were selected and input. This was to avoid the problem of multicollinearity. The factors that were finally input into the model were determined by variable addition and subtraction. The P value level of the variable addition and subtraction method was set to 0.1.

[0367] For the model finally considered useful, sensitivity, specificity, and matching rate were calculated by Youden Index and Optimum Distance. All analyses described in this project were performed using SAS (versions 9.3, 9.4).

[0368] result

[0369] [Result 1: Distribution of analysis objects]

[0370] The distribution of renal diseases among the subjects analyzed is shown in Tables 2 and 3. Table 2 is for all subjects analyzed, and Table 3 is for all patients with primary glomerular diseases other than IgA nephropathy.

[0371] [Table 2]

[0372] Table 2: Distribution of renal diseases and proportion of healthy people among 506 subjects analyzed

[0373]

[0374] The number of individual cases of any one kind.

[0375] However, regarding the analysis subjects, cases in which two or more diseases co-existed included cases in which a disease other than IgA nephropathy co-existed.

[0376] [Table 3]

[0377] Table 3: Distribution and proportion of primary glomerular diseases

[0378]

[0379]

[0380] The number of individual cases of any one kind.

[0381] According to Table 2, regarding the primary endpoint, among the 506 analyzed subjects, the number of cases with IgA nephropathy alone was 157 (31%), and the number of cases corresponding to non-IgA nephropathy was 349 (69%).

[0382] According to Table 3, regarding the secondary endpoints, among the 246 analyzed subjects, the number of cases with IgA nephropathy alone was 157 (31%), and the number of cases corresponding to primary glomerular diseases other than IgA nephropathy was 89 (36%). Among the latter, membranous nephropathy was the most common (31 cases), followed by minimal change nephrotic syndrome (29 cases).

[0383] Table 4 shows the main clinical factors at the time of renal biopsy.

[0384] [Table 4]

[0385] Table 4: Main clinical factors at the time of renal biopsy

[0386]

[0387]

[0388] Abbreviation: BMI = body mass index

[0389] *Median value (within 4 quartiles)

[0390] **Defined as patients who (i) are taking at least one antihypertensive agent, and (ii) have a baseline systolic blood pressure >140 or a diastolic blood pressure >90.

[0391] The P value is the significant rate for the comparison study between the IgA nephropathy group (n=157) and the non-IgA nephropathy group (n=349).

[0392] The χ2 was used to compare categorical variables. 2For comparison of continuous variables, t-test or Mann-Whitney test was used, depending on the distribution of the variables.

[0393] According to Table 4, the proportion of males in all analyzed subjects was 51%, the average age at the time of renal biopsy was 51 years old, and the average BMI was 22.6 (kg / m 2 ). In addition, the average values ​​of systolic blood pressure, diastolic blood pressure, and mean arterial pressure were 126.8 mmHg, 78.5 mmHg, and 94.6 mmHg, respectively, and the proportion of people with hypertension was 44%. As a clinical factor related to kidney function, the average value of eGFR was 61.9 ml / min / 1.73 m 2 The median daily urine protein was 0.92 (g / day, quartile: 0.35-3.00), urine occult blood was observed in 62% of the analyzed subjects, and the mean serum IgA value was 283.6 mg / dL.

[0394] Comparing the clinical factors between the IgA nephropathy group and the non-IgA nephropathy group, the IgA nephropathy group was statistically significantly younger, had a lower proportion of patients with hypertension, a higher eGFR, lower urine protein, a larger proportion of patients with positive urine occult blood, and a higher serum IgA value. This result confirms the validity of the conventional IgA nephropathy prediction model using serum IgA, the presence or absence of urine occult blood, and the daily urine protein amount.

[0395] [Result 2: Identification of IgA nephropathy patients in a non-specific population]

[0396] Table 5 shows the analysis results of model (2) and model (3) in the primary endpoint. In addition, the AUC of model (1) in the primary endpoint was 0.617. That is, in the case of distinguishing patients with only IgA nephropathy from a group that also includes healthy people, the AUC of the diagnostic method corresponding to the prior art is 0.617.

[0397] [Table 5]

[0398] Table 5: Logistic regression analysis results of 1 sugar chain model and 1 sugar chain + clinical factor model

[0399]

[0400]

[0401] *: A sugar chain model with a higher AUC (0.617) than the clinical factor model

[0402] According to Table 5, in model (2), regarding 16 lectins, the AUC of the model in which the lectin signal was input exceeded 0.617. Specifically, in the model in which the sugar chain signal bound to ACA, MAH, ABA, STL, LEL, WGA, MPA, japanese, MAL_I, PNA, ACG, GSL_I_A4, ConA, SSA, AOL or GSL_II was input, the AUC exceeded the conventional technology. Among them, the model with the largest AUC was the model in which the ACA-bound sugar chain signal was input. Then, in the model in which the sugar chain signal of the sugar chain bound to MAH, ABA or STL was input, the AUC exceeded 0.660. Next, in the model in which the LEL, WGA, MPA or japanese sugar chain signal was input, the AUC exceeded 0.640.

[0403] Also according to Table 5, in model (3), for 45 lectins, the AUC of the model in which the lectin signal was input exceeded 0.617. In other words, for all 45 lectins used in the study, additional effects relative to conventional diagnostic methods were observed. Among them, the model with the largest AUC was the model in which the ACA-bound sugar chain signal was input into the clinical factors (0.801). In the model in which the ACA, MAH or ABA-bound sugar chain signal was input into the clinical factors, the AUC exceeded 0.790. Next, in the model in which the MPA, japanese pineapple, LEL, ACG, STL, GSL_I_A4, WGA, SSA, PNA or ConA-bound sugar chain signal was input into the clinical factors, the AUC exceeded 0.790 (in addition, Table 5 is sorted in descending order according to the AUC in model (3)).

[0404] Table 6 shows the analysis results of model (4) in the primary endpoint.

[0405] [Table 6]

[0406] Table 6: AUC and diagnostic accuracy based on multiple sugar chain + clinical factor models

[0407]

[0408]

[0409] When analyzing model (4), it was found that the following seven types existed in the model that exceeded the highest AUC (0.801) in model (3):

[0410] ACA+GSL_I_A4+GSL_II;

[0411] MAH+GSL_I_A4+MAL_I;

[0412] ABA+GSL_I_A4+AOL;

[0413] MAH+GSL_I_A4+PNA;

[0414] MAH+GSL_I_A4+SNA;

[0415] ABA+GSL_I_A4+MAL_I;

[0416] ABA+GSL_I_A4+GSL_II.

[0417] Among them, the highest AUC was 0.807 when ACA, GSL_I_A4 and GSL_II were input into the sugar chain model. The sensitivity of this model was 0.764, the specificity was 0.754, and the matching rate was 0.758, which was the same as the results of Youden index and optimal distance.

[0418] Among the above seven combinations, for the lectin signals of ACA, MAH, ABA, and GSL_I_A4, low signal intensity was associated with the onset of IgA nephropathy. On the other hand, for the lectin signals of GSL_II, MAL_I, AOL, PNA, and SNA, high signal intensity was associated with the onset of IgA nephropathy.

[0419] [Result 3: Identification of patients with IgA nephropathy from patients with primary glomerular disease]

[0420] Table 7 shows the analysis results of model (2) and model (3) in the secondary endpoint. In addition, the AUC of model (1) in the secondary endpoint was 0.620. That is, in the case of distinguishing patients with only IgA nephropathy from a group with primary glomerular diseases, the AUC of the diagnostic method corresponding to the prior art was 0.620.

[0421] [Table 7]

[0422] Table 7: Logistic regression analysis results of the model with 1 sugar chain and the model with 1 sugar chain + clinical factors

[0423]

[0424]

[0425]

[0426] *: A sugar chain model with a higher AUC (0.620) than the clinical factor model

[0427] According to Table 7, in model (2), the AUC of the model that input the lectin signal for 42 lectins exceeded 0.617. Specifically, in the model that input the sugar chain signal bound to lectins other than HPA, EEL, or GSL_I_B4, the AUC exceeded the conventional technology. Among them, the model that input the ConA binding sugar chain signal had the largest AUC.

[0428] According to Table 7, in model (3), for the 45 lectins, the AUC of the model in which the lectin signal was input exceeded 0.620. That is, for all 45 lectins used in the study, additional effects were observed relative to conventional diagnostic methods. Among them, the model with the largest AUC was the model in which the ABA-binding sugar chain signal was input into the clinical factors (0.884). In Table 7, in the model in which any of the 30 lectin signals from ABA-binding sugar chain signals to PHA_L-binding sugar chain signals were input into the clinical factors, the AUC exceeded 0.873. (In addition, Table 7 is arranged in descending order of AUC in model (3).)

[0429] Table 8 shows the analysis results of model (4) in the secondary endpoints.

[0430] [Table 8]

[0431] Table 8: AUC and diagnostic accuracy based on multiple sugar chain + clinical factor models

[0432]

[0433] When analyzing model (4), among the models that exceeded the highest AUC (0.884) in model (3), there was a model that input MAH, GSL_I_A4, and HPA combined sugar chain model into clinical factors, and the AUC was 0.889. The sensitivity of this model was 0.860, the specificity was 0.841, and the matching rate was 0.853, which were the same as the results of Youden index and optimal distance.

[0434] In the above combination, for the lectin signals of MAH and GSL_I_A4, low signal intensity was associated with the onset of IgA nephropathy. On the other hand, for the lectin signal of HPA, high signal intensity was associated with the onset of IgA nephropathy.

[0435] Industrial Applicability

[0436] The present invention can be used, for example, for the diagnosis of IgA nephropathy.

Claims

1. Use of a lectin in determining the level of sugar chains in a sample collected from a subject, the subject being: (i) healthy subjects or subjects with IgA nephropathy; or (ii) subjects with or suspected of having primary glomerular disease; in, The lectin is at least one selected from the group consisting of ABA, MAH and ACA.

2. The use according to claim 1, wherein The determination of the sugar chain level is combined with the measurement of a biomarker other than the sugar chain level in a second sample collected from the subject.

3. The use according to claim 2, wherein The biomarker other than the sugar chain level is selected from at least one of urine occult blood, urine protein, serum IgA and serum IgA / C3 ratio.

4. The use according to any one of claims 1 to 3, wherein The sample used in the determination of the sugar chain level is a urine sample. 5 . A kit for use according to any one of claims 1 to 4 , comprising a lectin, wherein the lectin is at least one selected from the group consisting of ABA, MAH and ACA.

6. (i) a kit for determining the likelihood of onset of IgA nephropathy in a subject, or (ii) a kit for determining the likelihood of onset of IgA nephropathy in a subject having a primary glomerular disease or a subject suspected of having a primary glomerular disease, in, The kit comprises at least one lectin selected from the group consisting of ABA, MAH, ACA, MPA, japanese pineapple, LEL, ACG, STL, GSL_I_A4, WGA, SSA, PNA, ConA, Calsepa, AOL, SNA, UDA, LCA, GSL_II, UEA_I, LTL, MAL_I, TJA_I, ECA, PWM, PSA, AAL, DSA, BPL, TJA_II, NPA, PHA_E, RCA120, EEL, SBA, HPA, GNA, HHL, PTL_I, TxLC_I, PHA_L, GSL_I_B4, DBA, WFA and VVA, and the kit does not comprise other lectins.

7. (i) a kit for determining the likelihood of onset of IgA nephropathy in a subject, or (ii) a kit for determining the likelihood of onset of IgA nephropathy in a subject having a primary glomerular disease or a subject suspected of having a primary glomerular disease, in, The kit comprises at least one lectin that binds to a sugar chain, wherein the sugar chain is selected from Galβ1-3GalNAc, Siaα2-3Galβ1-3(Siaα2-6)GalNAc, (Galβ1-4GlcNAc) n 、(GlcNAcβ1-4) n 、(GlcNAcβ4MurNAc) n , galactosylated tri / tetraantennary glycans, Fucα1-2Galβ1-4GlcNAc, Fucα1-6GlcNAc, GalNAc, GlcNAc, High-Man including Manα1-6(Manα1-3)Man, Siaα2-3Galβ1-4GlcNAc, Siaα2-6Gal / GalNAc and α-GalNAc, and the kit does not contain other lectins.

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