WO2008047824A1

WO2008047824A1 - Method for determining presence or absence diabetes

Info

Publication number: WO2008047824A1
Application number: PCT/JP2007/070231
Authority: WO
Inventors: Shuichi Kaneko; Toshinari Takamura; Masao Honda; Yoshio Sakai; Kenichi Matsubara
Original assignee: Dna Chip Research Inc.
Priority date: 2006-10-19
Filing date: 2007-10-17
Publication date: 2008-04-24
Also published as: JPWO2008047824A1; JP4991745B2; JP2009207354A

Abstract

It is intended to provide a method for determining whether or not a subject has type II diabetes and a method for determining whether or not a therapeutic effect on diabetes is obtained using a sample which can be easily obtained. The method for determining whether or not a subject x is a diabetic patient or a potential diabetic patient comprising the steps of: (a) obtaining an expression profile x of a specific gene or gene group in human leukocytes derived from the subject x; (b) comparing the expression profile x obtained in the step (a) with an expression profile y of the same specific gene or gene group as in the step (a) in a gene group in human leukocytes derived from a non-diabetic subject y or an equivalent thereof; and (c) determining the subject x as a diabetic patient or a potential diabetic patient when the expression profile x is significantly different from the expression profile y in the step (b), etc. are adopted.

Description

Specification

How to determine the presence or absence of diabetes

Technical field

[0001] The present invention relates to (1) a method for determining whether or not a subject is a diabetic patient or a reserve army by analyzing the expression level of a gene in human leukocytes, and (2) a type 2 diabetic patient. The present invention relates to a method for determining the presence or absence of a therapeutic effect.

Background art

[0002] According to the latest medical statistics, the number of diabetic patients in Japan is 7.4 million even for those who are strongly suspected of having diabetes, and 16.2 million people who cannot deny the possibility of diabetes. It is believed that. In addition, medical expenses related to diabetes are estimated to be 1,115.5 billion yen per year, even with direct costs alone, and it is said that it will reach 3 trillion yen considering indirect economic losses. However, only biochemical tests useful for diagnosing whether or not there is diabetes are blood and urine sugar tests and glycohemoglobin (HbAlc) measurement. In addition, these test results show that arteriosclerosis, which is the biggest problem of diabetes, and complications such as blindness due to retinal damage and diabetic nephropathy cannot be fully evaluated and predicted. Yes. Despite numerous studies in Japan and overseas, no useful method has been developed for the diagnosis of diabetes using conventional biochemical 'immunological techniques'.

[0003] In addition, drugs that can reliably treat diabetes are still under development, and therefore, a method useful for diagnosis of diabetes and the like is also necessary for determining the effectiveness of such drugs.

[0004] On the other hand, the DNA microphone array (DNA chip) is known as a tool for simultaneously analyzing the expression of many types of genes, and let's diagnose glycouric disease from the results of gene analysis using these. Also known to try!

[0005] In Patent Document 1, a plurality of genes whose expression is significantly different between two different conditions are selected by obtaining gene expression data with a DNA microarray or DNA chip and performing multivariate analysis on the data. Or the expression of multiple genes selected in this way, whether the disease is affected or not, or the disease is improved by treatment It describes how to judge whether or not!

[0006] Example 1 of Patent Document 1 describes an analysis result of gene expression variation in the liver of a diabetes model mouse by administration of metformin, which is a therapeutic drug for diabetes, and correlates with the drug efficacy of metformin. Twenty-five probes (23 genes) have been identified as genes that show the expression fluctuation. In addition, in Example 4, as a result of searching for the gene groups affected by metformin administration in metabolic pathway units, the expression of the gene groups belonging to each pathway was affected in 12 pathways. Has been. In Example 4 as well, the specimen is the liver of a diabetes model mouse. Furthermore, in Example 5, focusing on the ALDH2 gene contained in a plurality of pathways in the above 12 pathways, expression fluctuations correlated with the drug efficacy of metformin based on the results of statistical analysis. Guess that it is a prominently important gene!

[0007] As described above, the examples described in Patent Document 1 are all performed using the liver of a diabetic model mouse. The invention related to humans in the invention described in Patent Document 1 can only be realized if the mouse data can be directly replaced with humans! / It has not been. As described above, it is not clear whether the gene specified in Patent Document 1 is useful for testing human diabetes.

[0008] Patent Documents 2 and 3 describe methods for diagnosing type 2 diabetes by analyzing the expression of a predetermined gene in leukocytes. Genes useful for diagnosing type 2 diabetes have also been disclosed. However, in this example, experimental methods and results using OLETF rats, which are model animals of spontaneous diabetes, exhibiting symptoms similar to type 2 diabetes, and LETO rats, which do not develop diabetes, are control animals. Is listed! /, Only. Patent Document 2 describes that as a result of analyzing gene expression levels in leukocytes, liver and muscle of rats, there was a significant difference in the expression of CAPN10 gene and IRS-1 gene in OLETF rats and LETO rats. In addition, in Patent Document 3, if the gene expression level in rat leukocytes is comprehensively analyzed using a cDNA microarray, the gene can be used as a gene useful for diagnosis of type 2 diabetes. Selected force S, identified as a gene useful for diagnosis of human type 2 diabetes. [0009] However, in both cases of Patent Document 2 and Patent Document 3, the examples all relate to experiments using samples obtained from model animals, and thus the data obtained is truly human diabetes. There is no guarantee, and it has been verified!

[0010] Furthermore, paragraph number 0164 of Patent Document 3 describes that the gene spotted on the microarray used here is not optimized for diabetes diagnosis! / ! / Therefore, paragraph number 0164 also states that “the gene found this time can be used as a candidate gene for constructing a micro'array optimized for diagnosis of diabetes gene expression,” Conversely, V, not spotted on the micro'array used here, suggests that there may be a suitable gene for diabetes diagnosis! /, Or even! /.

[0011] In Patent Documents 1 to 3 as described above, genes useful for diagnosis of human diabetes and the like are specified based on data obtained by experiments using model animals. The gene S of rat is said to be similar to the gene of human S, the identity of its function with human, and the identity of the behavior in the pathway with human is not guaranteed. Is reasonable. Diagnostic marker genes applied to humans should be determined only by examining gene expression in human patients.

Patent Document 1: Japanese Patent Application Laid-Open No. 2005-323573

Patent Document 2: International Publication WO2004 / 040301

Patent Document 3: JP 2005-253434

Disclosure of the invention

Problems to be solved by the invention

[0013] Hyperglycemia, obesity, and insulin resistance, which are the main pathologies of diabetes, are known to cause oxidative stress. In diabetic patients, organs such as liver, adipose tissue, and skeletal muscles produce and secrete physiologically active substances such as cytopower-in and hormones, and nutrients such as sugars and fatty acids. There is a possibility that a systemic pathology is formed by a network through these factors, and it has been shown one after another by various evidences! Therefore, the present inventors are exposed to such oxidative stress, physiologically active substances, and nutrients to dynamically change gene expression! To obtain knowledge about the relationship between various diseases and fluctuations in gene expression I thought it was possible. As such a tissue, attention was paid to leukocytes.

[0014] In addition, in studies of diseases, research using model animals is of course important. Knowledge gained from force model animals is often not applicable to humans. Therefore, it was considered necessary to clarify the relationship between disease and gene expression variation using human leukocytes as a specimen.

The object of the present invention is to obtain an expression profile of a gene or gene group derived from human leukocytes (for example, a gene group belonging to a specific pathway). Or (2) to provide a method for determining the presence or absence of a therapeutic effect in patients with type 2 diabetes.

Means for solving the problem

[0016] The present inventor diligently studied to solve the above problems and completed the present invention.

That is, the first invention (part 1) is a method for determining whether or not the subject X is a diabetic patient or a reserve army thereof,

(a) obtaining an expression profile X of a specific gene or group of genes in human leukocytes derived from subject X;

(b) The same specific gene or gene as in step (a) in the gene group or equivalent thereof in human leukocytes derived from non-diabetic subject y is expressed profile X obtained in step (a). Comparing the expression profile y of the group; and

(c) In step (b), when the expression profile X is significantly different from the expression profile y, the subject X is determined to be a diabetic patient or a reserve army.

Wherein the specific gene or gene group includes the following (A-1) to (A—

On a method characterized by being included in the gene group of 50)!

(A— 1) Virtual protein LOC54103 (registration number: AL079277)

(A-2) Leucine-rich repeating neuron unit 3 (registration number: AB060967)

(8-3) 13 kilodalton differentiation-related protein (registration number: 8 005936)

(A-4) Emopamyl-binding protein, Δ 8— Δ7 sterol isomerase-related protein (registration number: AF243433)

(A-5) Glycosyltransferase AD -017 (registration number: NM 018446) (A-6) Redoxin peroxide 3 (registration number: NM—006793)

(A-7) Fc fragment of IgE, high affinity I, α-polypeptide receptor (registration number: N Μ— 002001)

(Α-8) Signal peptidase 12 kilodalton (registration number: ENSG00000114902)

(Α-9) Octamer-binding non-POU domain (registration number: L32558)

(Α-10) ΝΡ220 nuclear protein (registration number: AF273049)

(Α—11) Virtual protein FLJ 10652 (registration number: NM—018169)

(A—12) Chromosome 14 open reading frame 109 (registration number: AL0801

18)

(A-13) Apoptosis-related protein 3 (Registration number: NM— 004632)

(A-14) AUT-like 1 cysteine endopeptidase (S. cerevisiae) (registration number: ENS G00000125703)

(A-15) Recombinant protein REC14 (registration number: AF309553)

(A-16) esterase D / formylglutathione hydrolase (registration number: AF11221)

9)

(A-17) Transmembrane protein 14B (registration number: NM—030969)

(A— 18) Myc-related protein (registration number: AF083244)

(A— 19) Eukaryotic translation initiation factor (elF) 2A (registration number: AF212241)

(A—20) B cell linker (¾ 參号: ENSG00000095585)

(A—21) Lymphocyte antigen 86 (registration number: NM— 004271)

(A-22) Malate dehydrogenase 1, NAD (soluble) (registration number: ENSG0000001 4641)

(A-23) Presumed membrane protein (registration number: AF070626)

(A—24) Cellular repressor of E1A-induced gene (Registration number: NM—003851) (A—25) Exportin 1 (CRM1 homolog, yeast) (Registration number: NM_003400) (A—26) Glutamylprolyl tRNA synthetase (registration number: NM_004446)

(A—27) Sorting nexin 13 (registration number: AL353943)

(A— 28) Virtual DKFZp451 J 1719 (registration number: AF 116608) (A— 29) ACN9 homolog (S. cerevisiae) (registration number: AF201933)

(A-30) Anaplastic lymphoma kinase (Ki-l) (Registration number: D45915)

(A—31) Centrosome protein 1 (registration number: NM—007018)

(A—32) Rigatine (registration number: AF220417)

(A-33) 8Pase, hydrogen transport, lysosomal protein 2 (registration number: AF248966)

(A—34) Intramembrane protein, mitochondrial (mitophylline) (registration number: NM—006839) (A—35) protein tyrosine phosphatase, non-receptor type 12 (registration number: NM —002835)

(A- 36) Pyruvate dehydrogenase (lipoamide) β (registration number: Μ34479)

(A—37) unc—50 homologue (C. elegans) (registration number: AF077038)

(A-38) Virtual protein FLJ20003 (registration number: NM— 017615)

(A-39) Virtual protein KIAA1109 (registration number: AB029032)

(A-40) Tabi Uniform Protein 3 (Registration Number: NM—003324)

(A— 41) Bispecific phosphatase 5 (registration number: NM— 004419)

(A—42) Mitogen-activated protein kinase kinase 7 (registration number: BC005365)

(A-43) B cell inhibitory factor Nuclear factor (registration number: fluorescent peptide gene enhancer in α)

ΝΜ— 020529)

(Α—44) Dentin Matritas acidic phosphoprotein (registration number: ΝΜ—004407)

(Α—45) Kurzpel-like factor 5 (intestine) (registration number: ΝΜ—001730)

(Α- 46) diuronate 2-sulfatase (Nonter syndrome) (registration number: ΝΜ- 0061

twenty three)

(A—47) CD83 antigen (activated sputum lymphocyte, immunoglobulin superfamily) (registration number: NM— 004233)

(A—48) Ring finger protein 121 (registration number: NM—018320)

(A-49) Core promoter factor binding protein (registration number: NM-001300) and

(A-50) Serum / Glucocorticoid-regulated kinase (registration number: NM—00562 [0018] The first invention (part 2) is a method for determining whether or not the subject X is a diabetic patient or a reserve army thereof,

(b) The same specific gene or gene as in step (a) in the gene group or equivalent thereof in human leukocytes derived from non-diabetic subject y is expressed profile X obtained in step (a). Comparing to the expression profile y!

Wherein the specific gene or gene group is included in a gene group belonging to a MAP kinase 'signaling' pathway and a P38 MAPK signaling pathway (hereinafter sometimes referred to as a "MAPK gene group"). It is related to a method characterized by that.

[0019] The gene belonging to the MAPK gene group includes all genes belonging to the MAP kinase 'signaling' pathway and genes belonging to the P38 MAPK signaling 'pathway in this technical field.

[0020] The specific gene or gene group used in the implementation of the first invention (part 2) is listed in Table 7 among genes specified as belonging to the MAPK gene group in BRB-ArrayTools (registered trademark). You may select from the 82 genes listed.

[0021] The specific gene or gene group used in carrying out the first method (part 2) is the following (B-1) to (B-) among the genes identified as belonging to the MAPK gene group in MAPPFinder: You can select from 31) genes! /):

(B— 1) Mitogen-activated protein kinase kinase kinase 6 (registration number: Aff. I D 1552631— a— at)

(B—2) Ribosomal protein S6 kinase, 90 kilodalton, polypeptide 2 (registration number: Aff. ID 1557970—s—at)

(B-3) Mitogen-activated protein kinase kinase kinase 2 (registration number: Aff. I D 1565130- at)

(B-4) Mitogen-activated protein kinase activated protein kinase 2 (registration number) : Aff. ID 201460—at)

(B—5) v—jun sarcoma virus 17 oncogene homolog (birds) (registration number: Aff. ID 201 464— x— at)

(B— 6) Nuclear factor of fluorescent peptide gene enhancer in B cell inhibitory factor α (registration number: Af f. ID 201502— s— at)

(B-7) v-raf murine sarcoma 3611 viral oncogene homolog (registration number: Aff. ID 2 01895—at)

(B—8) Rap guanine nucleotide exchange factor (GEF) 2 (registration number: Aff. ID 203096 one s one at;

(B-9) Mitogen-activated protein kinase kinase kinase 3 (registration number: Aff. I D 203514— at)

(B- lO) ELKl, a member of the ETS oncogene family (registration number: Aff. ID 203617 ― X― at

(B— 11) CCAAT / enhancer binding protein (C / EBP), α (registration number: Aff. ID 2 04039— at)

(B—12) TNF receptor-related factor 2 (registration number: Aff. ID 204413—at)

(B—13) Mitogen-activated protein kinase 4 (registration number: Aff. ID 204707—s

—At)

(B—14) Mitogen-activated protein kinase kinase 5 (registration number: Aff. ID 204 756—at)

(B-15) Mitogen-activated protein kinase kinase kinase 14 (registration number: Aff. ID 205192—at)

(B— 16) v— raf murine sarcoma viral oncogene homolog B1 (registration number: Aff. ID 20 6044— s— at)

(B—17) Mitogen-activated protein kinase kinase kinase 10 (registration number: Aff. ID 206362— x— at)

(B—18) Mitogen-activated protein kinase 6 (registration number: Aff. ID 207121—s at) (B-19) Mitogen-activated protein kinase kinase 3 (registration number: Aff. ID 207 6D7-s-at)

(B— 20) MADS box transcription enhancer factor 2, polypeptide A (myocyte enhancer factor 2 A) (registration number: Aff. ID 208328— s— at)

(B— 21) v— f osFBJ murine osteosarcoma virus oncogene homolog (registration number: Aff. ID 209189— at)

(B—22) Mitogen-activated protein kinase kinase 7 (registration number: Aff. ID 209 951—s—at)

(B-23) Mitogen-activated protein kinase 13 (registration number: Aff. ID 210058—at)

(B—24) v—Ha—ras Harvey rat sarcoma virus oncogene homolog (registration number: A ff. ID 212983—at)

(B—25) Growth factor receptor binding protein 2 (registration number: Aff. ID 215075—s—at) (B—26) MAP kinase interaction serine / threonine kinase 2 (registration number: Aff. ID 218205—s) — At)

(B—27) Cell division cycle 42 (GTP binding protein, 25 kilodalton) (Registration number: A ff. ID 1556931— at)

(B—28) Phospholipase A2, VI group (cytosolic, calcium-independent) (registration number: Aff. ID 204691— x— at)

(B—29) DNA damage-induced transcription 3 (Registration number: Aff. ID 209383—at)

(B—30) Early growth response 1 (Registration number: Aff. ID 201693—s—at) and

(B—31) Nerve growth factor, / 3 polypeptide (registration number: Aff. ID 206814—at). The first invention (part 3) is a method for determining whether or not the subject X is a diabetic patient or a reserve army thereof,

(b) The expression profile X obtained in step (a) is the same specific gene or gene as in step (a) in the gene group or equivalent thereof in human leukocytes derived from non-diabetic subject y. To the gene group! /, The process of comparing with the previous expression profile y, and

Wherein the specific gene or group of genes is included in a group of genes belonging to the ubiquinone biosynthesis system and the ATP synthesis system (hereinafter sometimes referred to as “OXPHOS gene group”). On how to do.

[0023] Genes belonging to the OXPHOS gene group include all genes belonging to the ubiquinone biosynthesis system and genes belonging to the ATP synthesis system in this technical field.

[0024] The specific gene or gene group used in the implementation of the first invention (part 3) is specified as belonging to the OXPHOS gene group in BRB-ArrayTools (registered trademark)! / You can select from the 70 gene groups described in 8! /.

[0025] The specific gene or gene group used in the implementation of the first invention (part 3) is specified as belonging to MAPPFinder! /, And as belonging to the OXPHOS gene group! / You can select from genes from C 1) to (C 42)! /,

(C— 1) Inorganic pyrophosphatase 2 (Registration number: Aff. ID 1554499— s— at)

(C 2) NADH dehydrogenase (ubiquinone) Fe- S protein 4, 18 kilodalton (NADH coenzyme Q reductase) (registration number: Aff. ID 1555057— at)

(C-3) ATP synthase, hydrogen transport, mitochondrial F0 complex, subunit d (registration number: Aff. ID 1555998— at)

(C-4) ATP synthase, hydrogen transport, mitochondrial F1 complex, O subunit (oligomycin sensitization protein) (registration number: Aff. ID 1564482— at)

(C 5) BCL2 1 (Registration number: Aff. ID 1569067_at)

(Ji-6) 1 containing Ding & 0 Dienase domain (registration number: Aff. ID 1569230—at)

(C 7) ATP synthase, hydrogen transport, mitochondrial F1 complex, α subunit, isoform 1, cardiac muscle (oligomycin sensitizing protein) (registration number: Aff. ID 156989 1—at)

(C 8) ATPase, hydrogen transport, lysosome 9 kilodalton, V0 subunit e /// A TPase, hydrogen transport, lysosome 9 kilodalton, VO subunit e (registration number: Aff. ID 200096— s— at)

(C 9) Superoxide Dismutase 1, Soluble (Amiot Mouth Fick Lateral Streak cis 1 (Adult)) (Registration Number: Aff. ID 200642— at)

(C-10) ubiquinol-cytochrome c reductase core protein II (registration number: Aff. ID 200883— at)

(C 1 1) Cytochrome coxidase subunit Via polypeptide 1 (registration number: Aff ID 200925—at)

(C-12) Cytochrome coxidase subunit VIIc (registration number: Aff. ID 201 134 ― X― at)

(C-13) Cytochrome coxidase subunit Vic (registration number: Aff. ID 201754 —at)

(C 14) NADH dehydrogenase (ubiquinone) Fe-S protein 2, 49 kilodalton (NADH coenzyme Q reductase) (registration number: Aff. ID 201966_at)

(C—15) ubiquinol-cytochrome c reductase hinge protein (registration number: Aff. ID 202233—s—at)

(C— 16) ATP synthase, hydrogen transport, mitochondrial F0 complex, subunit F6 (registration number: Aff. ID 202325_s_at)

(C— 1 7) ATPase, hydrogen transport, lysosome 42 kilodalton, VI subunit C, isoform 1 (registration number: Aff. ID 202872_at)

(C 18) NADH dehydrogenase (ubiquinone) 1/3 subcomplex, 3, 12 kilodalton (registration number: Aff. ID 203371_s_at)

(C 19) NADH dehydrogenase (ubiquinone) 1, subcomplex unknown, 1, 6 kilodalton (registration number: Aff. ID 203478_at)

(C 20) NADH dehydrogenase (ubiquinone) 1/3 subcomplex, 5, 16 kilodalton (registration number: Aff. ID 203621_at)

(C—21) Cytochrome coxidase subunit Va (registration number: Aff. ID 203663 s at) (C-22) COX10 homolog, cytochrome coxidase assembly protein, hem A: farnesyltransferase (yeast) (registration number: Aff. ID 203858_s_at) (C 23) NADH dehydrogenase (ubiquinone) 1 α subcomplex, assembly One factor 1 (registration number: Aff. ID 204125—at)

(C 24) Programmed cell death 8 (apoptosis inducer) (registration number: Aff. ID 20 5512— s— at)

(C—25) ATP synthase, hydrogen transport, mitochondrial F1 complex, γ polypeptide 1 (registration number: Aff. ID 205711— X—at)

(C—26) ATP synthase, hydrogen transport, mitochondrial F0 complex, subunit c (subunit 9) isoform 3 (registration number: Aff. ID 207507—s—at)

(C—27) ATP synthase, hydrogen transport, mitochondrial F0 complex, subunit c (subunit 9) isoform 2 (registration number: Aff. ID 207552—at)

(C—28) ATPase, hydrogen transport, lysosome 34 kilodalton, VI subunit D (registration number: Aff. ID 208898 one at)

(C—29) ATP synthase, hydrogen transport, mitochondrial F0 complex, subunit c (subunit 9) isoform 1 (registration number: Aff. ID 208972—s—at)

(C-30) Uncoupled protein 2 (mitochondrion, proton carrier) (registration number: Aff. ID 208997— s— at)

(C-31) NADH dehydrogenase (ubiquinone) Fe-S protein 7, 20 kilodalton (NADH coenzyme Q reductase) /// NADH dehydrogenase (ubiquinone) Fe S protein 7, 20 kilodalton (NADH coenzyme Q reductase) (registration number) : A ff. ID 211752— s— at)

(C-32) ATP synthase, hydrogen transport, mitochondrial F0 complex, subunit b, isoform 1 /// ATP synthase, hydrogen transport, mitochondrial F0 complex, subunit b, isoform 1 (registration number: Aff. ID 211755— s— at)

(C—33) ATP synthase, hydrogen transport, mitochondrial F1 complex, O subunit (oligomycin sensitizing protein) (registration number: Aff. ID 216954—x—at)

(C-34) ATP synthase, hydrogen transport, mitochondrial F1 complex, ε subunit (registration) Number: Aff. ID 217801_at)

(C 35) pyrophosphatase (inorganic) (registration number: Aff. ID 217848_s_at)

(C- 36) NADH dehydrogenase (ubiquinone) 1, subcomplex unknown, 2, 14.5 kilodaltons (registration number: Aff. ID 218101—s—at)

(C-37) NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 8, 19 kilodalton (registration number: Aff. ID 218160- at)

(C—38) ubiquinol-cytochrome c reductase complex (7.2 kilodaltons) (registration number: Aff. ID 218190—s—at)

(C-39) NADH dehydrogenase (ubiquinone) 1, / 3 subcomplex, 2, 8 kilodalton (registration number: Aff. ID 218200_s_at)

(C 40) NADH dehydrogenase (ubiquinone) 1, 3 subcomplex, 4, 15 kilodalton (registration number: Aff. ID 218226_s_at)

(C—41) inorganic pyrophosphatase 2 (registration number: Aff. ID 220741—s—at) and

(C42) KIAA1387 protein /// KIAA1387 protein (registration number: Aff. ID 224474—x—at).

The second invention (part 1) is a method for determining the presence or absence of therapeutic effect in patients with type 2 diabetes.

(A) obtaining an expression profile of a specific gene or gene group in human leukocytes collected before and after the start of treatment of a test diabetic patient;

(B) comparing the expression profile of the gene or gene group before the start of treatment measured in step (A) with the expression profile of the gene or gene group after the start of treatment; and

(C) The expression profile of the specific gene or gene group after the start of treatment is significantly different from the expression profile of the specific gene or gene group before the start of treatment, and the characteristics of the expression profile indicating diabetes are lost or The process of determining that there is a therapeutic effect when it is reduced

Wherein the specific gene or gene group is included in the following gene groups (D-1) to (D-50)! /:

(D-1) Fork head box P1 (registration number: NM 016477) (D-2) CD24 antigen (small cell lung cancer cluster 4 antigen) (registration number: NM_013230) (D-3) ribosomal protein L29 (registration number: NM-000992)

(D—4) Eukaryotic translation elongation factor 1 Δ (guanine nucleotide exchange protein) (registration number: NM— 032378)

(D-5) ELK3, ETS domain protein (SRF protein 2) (registration number: NM —005230)

(D-6) Nuclear receptor subfamily 3, group C, member 1 (Glucocorticoid receptor) (registration number: NM—000176)

(D-7) Neurotensin receptor 1 (high affinity) (registration number: NM—002531)

(D—8) integral membrane protein 2A (registration number: NM—004867)

(D 9) Genuine small tooth homolog 2 (Drosophila) (registration number: NM_021728)

(D-10) Esterase 2A (registration number: NM— 033440)

(D-11) External mitochondrial translocase 22 homolog (yeast) (registration number: NM-0-20243)

(D-12) Endosulfin α (Registration number: ΝΜ_004436)

(D-13) CD226 antigen (registration number: ΝΜ—006566)

(D—14) Transient receptor potential cation channel, subfamily V, member 4 (registration number: ΝΜ— 021625)

(D—15) ADP-ribosylation factor interacting protein 2 (erfaptin 2) (Registration number: ΝΜ— 012402)

(D—16) Bradykinin receptor Β2 (registration number: ΝΜ—000623)

(D-17) Ribosomal protein S3 (registration number: ΝΜ—001005)

(D-18) Contactin-related protein-like 2 (Registration number: ΝΜ—014141)

(D-19) Myosin, photopolypeptide kinase (registration number: ΝΜ-005965)

(D-20) Dipeptidase 1 (Nenseisei) (Registration number: ΝΜ_004413)

(D—21) Yolk macular dystrophy (best disease, bestrophin) (registration number: AF057170)

(D—22) Chemokine (C—C motif) ligand 5 (registration number: NM—002985)

(D23) 1-acylglycerol 1-phosphate O-acyltransferase 1 (Lysophosphatidic acid acyltransferase α) (registration number: NM— 032741)

(D—24) zinc finger protein, subfamily 1A, 4 (Eos) (registration number: NM—

022465)

(D-25) Benzodiazepine receptor (Ambient) (registration number: NM_000714)

(D—26) KIAA0174 gene product (registration number: NM—014761)

(D—27) Mortality factor 4 like 2 (Registration number: NM— 012286)

(D—28) Serine (or cysteine) proteinase inhibitor, clade B (ovoalbumin), member 13 (registration number: NM—012397)

(D—29) IK site force-in, HLA II down-regulator (registration number: AL050296) (D—30) lipopolysaccharide-derived TNF factor (registration number: ΝΜ—004862)

(D—31) ARF-binding protein 1-containing Golgi-related γ-adaptin (registration number: Ν Μ— 013365)

(D—32) —Time receptor potential cation channel, subfamily Μ, member 5 (registration number: NM_014555)

(D—33) High mobility group nucleosome binding domain 1 (registration number: NM—004965) (D-34) cyclin T1 (registration number: NM—001240)

(D—35) v—maf muscle aponeurosis fibrosarcoma oncogene homolog (birds) (registration number: NM—005 360)

(D—36) Family with sequence homology 18, member B (registration number: AF223467)

(D-37) Inhibitor of DNA binding 2, dominant negative helix loop one helix protein (registration number: NM_002166)

(D-38) TAF11 RNA polymerase II, TATA box binding protein (TBP) -related factor, 28 kilodalun (registration number: ENSG00000064995)

(D—39) Cadherin 11, type 2, OB cadherin (osteoblast) (registration number: D21255) (D—40) Thyroid hormone receptor, α (erythroblastosis leukemia virus (V erb—a) oncogene Child homologue, birds) (registration number: X55005)

(D—41) zinc finger protein 160 (registration number: X78928)

(D-42) Phospholinose A2, X group (registration number: ENSG00000069764) (D—43) Virtual tank FLJ23120 (registration number: AK026773)

(D—44) Phosphoinositide 3-kinase, class 2, γ polypeptide (registration number: AJ

000008)

(D-45) Virtual protein IMAGE: 4215339 (registration number: AC005328)

(D—46) Cathebsin E (registration number: AJ250716)

(D—47) Chemokine (C motif) receptor 1 (registration number: NM—005283)

(D—48) Cell Dedigator 9 (Registration Issue: ENSG00000088387)

(D-49) Ring finger protein 39 (registration number: AF238317) and

(D—50) Chromosome 17 Open Reading Frame 28 (Registration Number: AL137556)

Yes

[0027] The second invention (part 2) is a method for determining the presence or absence of a therapeutic effect in patients with type 2 diabetes.

[0028] The specific gene or gene group used in the implementation of the second invention (part 2) is shown in Table 7 among genes specified as belonging to the MAPK gene group in BRB-ArrayTools (registered trademark). You may select from the 82 genes listed.

[0029] The specific gene or gene group used in the implementation of the second invention (part 3) is a gene identified as belonging to the MAPK gene group in MAPPFinder. May be selected from the following gene groups (E-1) to (E-29):

(E-1) Mitogen-activated protein kinase kinase kinase 11 (registration number: Aff.

ID 1558984— at)

(E— 2) CREB binding protein (Rubinstein-Tybi syndrome) (registration number: Aff. I D 1559295— at)

(E-3) p21 / Cdc42 / Racl-activated kinase 1 (STE20 homolog, yeast) (registration number: Aff. ID 1565772— at)

(E—4) TNFRSF1A related Viades domain (registration number: Aff. ID 1729—at)

(E-5) Transcription 1 signal transducer and activator, 91 kilodalton (registration number: Aff. ID 200887_s_at)

(E-6) Mitogen-activated protein kinase Activated protein kinase 2 (Registration number: Aff. ID 201460—at)

(E—7) v—jun sarcoma virus 17 oncogene homolog (birds) (registration number: Aff. ID 201 464— x— at)

(E-8) v-raf murine sarcoma 3611 viral oncogene homolog (registration number: Aff. ID 2 01895—at)

(E—9) v—myc myelocytosis viral oncogene homolog (birds) (registration number: Aff. I D 202431—s—at)

(E-10) Mitogen-activated protein kinase Activated protein kinase 3 (registration number: Aff. ID 202787—s—at)

(E-11) Conversion growth factor, / 3 1 (Kamrach-Engelmann disease) (Registration number: Aff. ID 20 3084— at)

(E— 12) Rap guanine nucleotide exchange factor (GEF) 2 (registration number: Aff. ID 203097 one s one at;

(E-13) Mitogen-activated protein kinase kinase 4 (registration number: Aff. ID 203 265—s—at)

(E-14) Ribosomal protein S6 kinase, 90 kilodalton, polypeptide 1 (registration number: Aff. ID 203379 at) (E-15) Mitogen-activated protein kinase kinase kinase 3 (registration number: Aff. ID 203514- at)

(E-16) ELK1, ETS oncogene family member (registration number: Aff. ID 203617 ― x― at)

(E-17) Mitogen-activated protein kinase 4 (registration number: Aff. ID 204707— s —at)

(E—18) Mitogen-activated protein kinase 10 (registration number: Aff. ID 204813—at)

(E—19) Mitogen-activated protein kinase kinase kinase 10 (registration number: Aff. ID 206362— x— at)

(E-20) Mitogen-activated protein kinase 7 (registration number: Aff. ID 207292— s —at)

(E— 21) v— f osFBJ murine osteosarcoma virus oncogene homolog (registration number: Aff. ID 209189— at)

(E—22) Inhibitor of K photopeptide gene enhancer in B cells, kinase / 3 (Registration number: Aff. ID 209341—s—at)

(E-23) Mitogen-activated protein kinase 13 (registration number: Aff. ID 210058—at)

(E— 24) v— Ha— ras Harvey rat sarcoma virus oncogene homolog (registration number: A ff. ID 212983— at)

(E—25) Growth factor receptor binding protein 2 (registration number: Aff. ID 215075—s—at) (E—26) MAP kinase interaction serine / threonine kinase 2 (registration number: Aff. ID 218205—s) — At)

(E—27) High mobility group nucleosome binding domain 1 (registration number: Aff. ID 200943—at)

(E—28) DNA damage-induced transcription 3 (registration number: Aff. ID 209383—at) and

(E-29) Guanine nucleotide binding protein (G protein), q polypeptide (registration number: Aff. ID 202615 at). [0030] In this specification and the like, the "registration number" is generally used to specify a gene, such as a GenBank registration number, an Ensemble database registration number, and an Affymetrix ID number. Sign, number, and combinations thereof. The base sequence of each gene is registered by these codes and numbers.

The invention's effect

[0031] According to the present invention, there are provided a method for determining whether a subject is a diabetic patient or a reserve army using human leukocytes, and a method for determining the presence or absence of a therapeutic effect in a type 2 diabetic patient. . Since human leukocytes are contained in peripheral blood and can be obtained by means that can be easily obtained, blood collection, according to the present invention, whether or not a subject suffers from glycouria with only a small burden of blood collection, It is possible to receive a judgment as to whether or not the treatment effect has improved and what the prognosis will be.

Brief Description of Drawings

[0032] FIG. 1 is a photograph showing the results of scanning and quantifying the microchips for which the expression levels in diabetic patient samples and healthy subject samples were measured for the 50 genes shown in Table 3.

FIG. 2 is a photograph showing the results of scanning and quantifying the microchips for which the expression levels in the specimens before and after treatment for diabetes were measured for the 50 genes shown in Table 5.

FIG. 3 is a graph showing the presence or absence of a significant difference between the expression level of a diabetic patient sample and the expression level of a healthy subject for each gene belonging to the MAP kinase pathway.

FIG. 4 is a graph showing the presence or absence of a significant difference in the expression level of each gene belonging to the MAP kinase pathway before and after diabetes treatment (blood glucose control).

FIG. 5 is a graph showing the presence or absence of a significant difference between the expression level of a diabetic patient sample and the expression level of a healthy subject for each gene belonging to the mitochondrial OXPHOS pathway.

FIG. 6 is a graph showing the presence or absence of a significant difference in the expression level of each gene belonging to the mitochondrial OXPHOS pathway before and after diabetes treatment (blood glucose control).

FIG. 7 is a graph showing MAPK average centroid and OXPHOS average centroid for each case (diabetic patient, healthy subject, diabetic patient before treatment and diabetic patient after treatment).

FIG. 8 is a graph plotting MAPK average centroid and blood glycohemoglobin level (%) for each specimen. FIG. 9 is a graph plotting OXPHOS average centroid and blood glycohemoglobin (%) for each specimen.

FIG. 10 is a photograph showing the results of scanning and digitizing a microchip measuring the expression levels of 37 genes belonging to the MAP kinase pathway in diabetic patient samples and healthy subject samples.

[Fig. 11] Photographs showing the results of scanning and quantifying microchips that measured the expression level in samples before and after diabetes treatment for 40 genes belonging to the MAP kinase pathway.

[Fig. 12] A photograph showing the results of scanning and quantifying a microchip measuring the expression levels of 49 genes belonging to the mitochondrial OXPHOS pathway in diabetic patients and healthy subjects.

BEST MODE FOR CARRYING OUT THE INVENTION

Hereinafter, the present invention will be described based on the best mode for carrying out the invention.

[0034] In the present invention, RNA derived from human leukocytes is a target whose expression level, expression intensity, expression frequency, etc. are measured. Leukocytes include neutrophils, eosinophils, basophils, lymphocytes and monocytes.

[0035] The method for collecting leukocyte RNA from blood is not particularly limited, and for example, there is a Ficonore specific gravity centrifugation method and the following method. After collecting blood in a Baxgene RNA blood collection tube (Nippon Betaton, manufactured by Ditzkinson Co., Ltd.), RNA can be obtained directly without separating white blood cells according to the protocol specified by the manufacturer. In addition, whole blood is treated with a Ficoll specific gravity centrifuge to concentrate white blood cells, and then RNA is extracted.

[0036] In the present invention, various determinations are made by obtaining an expression profile of a specific gene or gene group in a gene group derived from human leukocytes or an equivalent thereof. Here, the “equivalent of a gene group derived from human white blood cells” is used in place of the gene group derived from leukocytes of a non-diabetic subject (preferably a healthy person) in the first invention. Specifically, for example, it is a mixture of artificial RNAs having a composition equivalent to that of healthy individuals. The “expression profile of a gene or gene group” refers to information on the level of gene expression. Therefore, the gene expression level itself, the expression intensity, The expression behavior of two or more gene groups as a whole (for example, a determination of the value calculated by substituting the expression intensities of multiple gene groups into a specific formula, or an image showing the expression intensities of multiple gene groups All information that can determine the expression state of a gene, such as the expression ratio of two or more gene groups.

[0037] In order to obtain an "expression profile of a gene or gene group", the transcription product (mRNA) or translation product (protein) of the gene is usually measured.

[0038] The method for measuring mRNA is not particularly limited. Measurement may be performed by a known gene analysis technique. Examples of measurement methods include those using hybridization technology (eg Northern 'Noise Hybridization Method, Dot' Blot Method, Micro 'Array (Micro' Chip) Method) , Using gene amplification technology (for example, RT-PCR method, real-time PCR method, ATAC-PCR method (Kato Κ, et al., Nucl. Acids Res., 25, 4694-4696, 1997), Taqman PCR method (Schmittgen TD, Methods 25, 3 83-385, 2001), Body Map method (Gene, 174, 151-158, 1996), SAGE (serial analysis of gene expression) method (JP 2001-155035, special 2001-145, 495, European Patent Publication No. 0761822, WO97 / 10363), MAGE (microanalysis of gene expression) method (Japanese Patent Laid-Open No. 2000-232232), etc.). Using these known methods, the amount of mRNA transcribed from all or part of the gene can be measured. In measuring the amount of mRNA, a nucleotide probe or primer that hybridizes to the mRNA can be used. The nucleotide length of the nucleotide 'probe or primer is about 10 to 60 bp, preferably 15 to 30 bp.

[0039] Here, the method for measuring the amount of mRNA for detecting the gene expression level will be described in more detail with an example.

[0040] First, the microarray method using the hybridization technology will be described. From the mRNA of the gene whose expression level is to be measured, a polynucleotide such as cDNA or aRNA (hereinafter referred to as “test polynucleotide”) having a corresponding base sequence is prepared, and a probe that hybridizes with such a polynucleotide is prepared. In general, the expression level of a gene is measured using a fixed DNA microarray (DNA chip) or the like.

[0041] First, a test polynucleotide and a pro gene corresponding to a specific gene on the micro'array. These are labeled in order to detect hybridization with the enzyme. For labeling, for example, radioisotopes, chemiluminescent compounds, heavy metal atoms, spectroscopic markers, magnetic force, related enzymes, fluorescent dyes, etc. are used. As a labeling method, a method suitable for each molecule to be labeled is known, but labeling using a fluorescent dye is most preferable. Examples of fluorescent dyes include fluorescein, dichlorofluorescein, BODITY ™, ROX, daramine, Cy2, Cy3, Cy5, and IRD40. Of these, Cy3 and Cy5 are particularly preferred. In order to label with Cy3 or Cy5, it is necessary to incorporate aminoallyl dUTP when preparing cDNA or aRNA.

[0042] The labeled cDNA or aRNA sample is hybridized on a microarray to which probes that specifically hybridize with the sample are immobilized.

[0043] As the DNA microarray (DNA chip), a commercially available product (for example, AceGene (registered trademark) Human Oligo Chip 30K manufactured by Hitachi Software Engineering Co., Ltd.) may be used. Lipshutz, RJ et al., Nature genet. 21, Sup pliment, 20-24 (1999)). Probes to be immobilized can be prepared by performing reverse transcriptase reaction or PCR using primers created based on the base sequence information of human genes, or based on the base sequence information of genes. These are chemically synthesized oligonucleotides.

[0044] Hybridization conditions and methods are known. For example, 5 × SSC (standard saline citrate), 0.5% SDS (sodium dodecyl sulfate) solution, and the like are known as hybridization buffers. The hybridization conditions are, for example, 35 to 60 ° C., preferably 42 to 50 ° C., more preferably 45 ° C., and 2 hours or more, preferably − 晚 or more. After hybridization, the DNA chip is washed, and the signal shown by the bound labeled molecule is visualized and quantified.

[0045] The intensity of the signal indicated by the labeled molecule can be measured by a known method. For example, when a radioisotope is used as a label, the radioactivity is measured using a liquid scintillation counter. When a fluorescent dye is used as a label, the fluorescence intensity is detected using a fluorescence microscope, a fluorescence plate reader, a fluorescence scanner, etc.

Yes [0046] When the signal intensity is measured, if there is a background influence, data processing may be performed by a method such as providing a cut-off value.

[0047] Next, a method using gene amplification technology will be described. The expression level of the gene can be measured by performing an amplification reaction using the test polynucleotide as a saddle type using a primer and detecting the specific amplification reaction.

[0048] As a method for amplifying a test polynucleotide, various methods using the principle of the polymerase chain reaction (PCR) method, for example, PCR method, RT-PCR method, real-time PCR method, ATA C-PCR method and the like are available. Can be mentioned. Other methods such as the LAMP method, ICAN method, RCA method, LCR method, and SDA method are also known. Amplification is performed until the amplification product is at a detectable level.

[0049] In order to determine whether or not a specific amplification reaction has occurred, a means capable of specifically recognizing the amplification product obtained by the amplification reaction is used. For example, using agarose gel electrophoresis or the like, it is confirmed whether or not a fragment of a specific size has been amplified. Alternatively, a labeling substance such as a radioisotope, a fluorescent dye or a luminescent substance is bound to dNTP or dUTP incorporated during the amplification reaction, and the signal emitted from the label is detected. As described above, the gene expression level can be measured using a specific amplification reaction.

[0050] Still another example of the method for measuring the gene expression level is the subtraction method (Sive, H.

L. and John, T. St., Nucleic Acids Research 16, 10937 (198 8), Wang, Z., and Brown, DD, Proc. Natl. Acad. Sci. U. SA 88, 11505— 11509 (1991) ), Differential Display Method (Liang, P., and Pardee, AB, Science 257, 967—971 (1992), Lian g, P., Averboukh, L., Keyomarsi, K., Sager, R., and Parde e, AB, Cancer Research 52, 6966— 6968 (1992) (1979)). ) The ability to raise)

[0051] In addition, a protein measurement method for measuring the gene expression level is not particularly limited. Known protein analysis techniques such as Western 'blotting, immunoprecipitation, ELISA, mass spectrometry and the like can be used.

[0052] The first invention is a method for determining whether subject X is a diabetic patient or a reserve army, and (a) a specific gene or gene group in human leukocytes derived from subject X (B) the expression profile X obtained in step (a) is converted into the expression group X in human leukocytes derived from non-glycouria subject y or the equivalent thereof in step (a) Comparing the expression profile y of the same specific gene or group of genes, and (c) if the expression profile X is significantly different from the expression profile y in step (b), the subject X is diabetic or It is a method including the process of determining with the army.

[0053] "Subject X is a diabetic patient" refers to a pathological condition diagnosed as having diabetes even with reference to the results of conventional biochemical tests, etc. If you are diabetic! /, You cannot make a definitive diagnosis! /, But if you are a healthy person, you are not!

[0054] In step (a), blood collected from subject X is used, and data such as the expression level of a specific gene or gene group in RNA derived from human leukocytes contained in the blood is used as the specific gene. Alternatively, it is a step of obtaining an expression profile of the specific gene or gene group by obtaining mRNA or protein derived from the gene group.

“To obtain an expression profile of a specific gene” means to measure mRNA and protein derived from a specific gene and obtain data such as the expression level, expression intensity, and expression frequency of the specific gene.

[0056] “Obtaining an expression profile of a specific gene group” means measuring mRNA and protein derived from two or more specific genes, and (1) the expression level and expression strength of each of two or more genes. (2) Obtain measured values such as the expression level of two or more genes, and use the measured values for statistical processing in the next step to obtain statistical values. It means obtaining the value after processing.

[0057] Measurement values such as gene expression levels are preferably corrected and then subjected to statistical processing.

Correction methods include: (1) a standardization method for the expression level of a gene, for example, the average of all measured values is 0 and the variance is 1, and (2) a gene whose expression level does not vary greatly (for example, housekeeping) Gene based on the measured value, based on the measured value. There is a method for correcting the measured value of a gene.

[0058] When the numerical value standardization processing method (1) is performed, the expression level data of the subject measured here is used as the gene expression level data derived from diabetic patients and healthy subjects measured in advance. Can be done in addition. In addition, genes with small difference in the expression level due to the presence or absence of diabetes include ensembl prediction gene (registration number: ENSGOOOOOl 35525; ENSG000001299103; ENSG00000130760; ENSG00000078177), seekl protein gene (registration number: NM—014068-1), prol048 gene ( Registration number: AF119842— 1), mdc protein gene (registration number: D17390-1), prol 87 3 gene (registration number: AF119859-1), cytochrome p450 subfamily xxviib polypeptide 1 (registration number: NM-000785-1), chromosome 16 open reading frame 7 (registration number: XM— 012545— 1).

[0059] "Statistical processing" may be any method as long as it can test whether there is a significant difference between the two groups. For example, a method for obtaining a regression line, a method for obtaining a correlation coefficient, analysis of variance, nonparametric analysis, and various analysis methods belonging to “multivariate analysis” can be used. Here, “multivariate analysis” is a statistical processing method that simultaneously analyzes multiple, usually three or more variables. Statistical analysis methods included in “multivariate analysis” include multiple regression analysis, discriminant analysis, principal component analysis, cluster analysis (including longest method, nearest neighbor method, median method, centroid method, etc.), etc. There is. The value obtained by “statistical processing” may include the result of “significance test”. The “significant difference test” is an analysis method (t test, F test, etc.) that tests the difference in the average value between the two groups to be compared, and such analysis method is extended to cases with many variables (multivariate). Analysis methods (LS Permutation, KS Permutation, Z-score, Wilkes' Λ, etc.). Details of these statistical processing methods are described in many books.

[0060] In step (b), the expression profile X of the specific gene or gene group in the gene group of subject X obtained in step (a) is derived from human leukocytes of non-diabetic subject y. This is a step of comparing the expression profile y of a specific gene or gene group in a gene group or its equivalent. The information of “expression profile χ” and the gene or gene group constituting the information of “expression profile y” are the same. In addition, to obtain an expression profile, m The measurement methods for RNA and protein are usually the same. However, in order to obtain “expression profile x” and “expression profile y”, mRNA and protein may be measured using different methods that correlate measured values! /.

[0061] Here, the expression profile y of a specific gene or gene group of a non-diabetic subject y (preferably healthy person) or in an artificial RNA mixture may be obtained in advance, When the expression profile X is obtained, it may be obtained by measurement at the same time. In addition, when using the expression profile y obtained in advance, if necessary, in addition to the target gene, for example, the gene whose expression level does not vary greatly is also measured at the same time. It is preferable to correct the measured value based on the expression level.

[0062] A comparison between "expression profile x" and "expression profile y" is performed, for example, in the following manner. When a subject is affected by diabetes or is a reserve arm, If it is clear that the expression level is significantly increased or attenuated, the expression level of the transcript of the gene (expression profile X)

[0064] An example of a method for comparing expression profiles of two gene groups is as follows. For example, if it is clear that the expression of gene a is significantly increased and the expression of gene b is significantly attenuated when the subject is afflicted with diabetes or is a reserve arm, compared to healthy subjects The expression level of the transcription product of gene a and gene b (expression profile X) is compared with the expression level of the transcription product of the gene in healthy individuals (expression profile y).

[0065] An example of a method for measuring the expression level of a gene transcription product is a real-time PCR method.

[0066] When comparing expression profiles of three or more gene groups, a real-time PCR method or the like can be employed. However, particularly when there are many types of genes to be measured, a technique capable of measuring a plurality of types of genes at the same time, for example, a method using a microchip is preferable. When measuring gene expression level using a micro chip The expression level or the expression intensity of each gene may be expressed as an image having a color. In this case, the entire image becomes an expression profile. There is also a method in which the expression level of three or more genes is substituted into a specific discriminant to obtain a solution. In this case, the solution (calculated value) is the expression profile.

[0067] In step (b), if the expression profile X is significantly different from the expression profile y based on the comparison result between the expression profile X and the expression profile y in step (b), the subject X is It is a step of determining that there is.

[0068] In order to determine whether or not there is a significant difference, for example, a significant difference test may be performed. The “significant difference test” includes an analysis method (t test, F test, etc.) that tests the difference in the average value between the two groups to be compared, and such analysis method is extended to cases with many variables (multivariate). Analysis methods (LS Permutation, KS Permutation, Z-score, Wilkes' Λ, etc.). Neural network analysis can also be used. The details of the significance test are described in many documents.

[0069] In order to determine whether or not there is a significant difference, it may be necessary to set some standard, but such a standard can be appropriately set by those skilled in the art. In addition, there is a standard value for determining whether there is a significant difference, such as ρ value!

[0070] In the present invention, the determination of the presence / absence of a significant difference is not limited to the significant difference test! / ,. For example, the presence or absence of a significant difference can be determined as follows.

[0071] For example, if the expression level of a gene measured by a specific method is diabetic or a reserve army, the expression level is more than X times that of a healthy person, and a plurality of healthy persons are selected. When the fluctuation range of the target measurement is significantly exceeded and the average value and fluctuation range of the expression level in the healthy subject are clear, subject X's expression level of the gene Determining that is a person with diabetes or its reserve, or a healthy person.

[0072] For example, when a subject suffers from diabetes or is a reserve army, it is clear that the expression level of gene a is increased by Sy% or more and attenuated to the level of expression level of gene b or less compared to healthy subjects. When the fluctuation range (i.e., y%, z%) significantly exceeds the measurement fluctuation range for multiple healthy subjects, the expression level of gene a in subject X is 100 compared to normal subjects. + It is determined that subject X is diabetic or a reserve army when two conditions are satisfied that the expression level of gene b of subject x is y% or more and z% or less compared to healthy subjects. .

[0073] When the expression levels of a plurality of genes analyzed by the microchip are expressed as images having colors, the expression pattern in the subject X of the genes expressed as the images is Significantly different from the expression pattern and close to the average expression pattern of diabetics! / In some cases, subject X is determined to be diabetic or its reserve.

[0074] Analytical methods suitable for statistical processing of data measured with microchips or microarrays have also been developed. For example, BRB—ArrayTools (registered trademark) and! /, Software (http: // linu s. Nci) developed by the Biometric Research Branch of the National Cancer Institute in the United States. nih.gov/BRB—ArrayTools.html), GenMAPP (Gene micro array Pathway Profiler; http / / www.genmapp.org) and MAPPFinder (SC), useful for deriving pathways with altered gene expression It is also preferable to use software such as Doniger et al .; http: Z www.pubmedcentral.nih.gov/articlerender.fcgi7artid=151291).

[0075] In addition, the expression level data of the subject X measured here is added to the expression level data of the diabetic patient and the healthy subject measured in advance, and the compound covariate predictor is calculated. Diagnostic linear 1—nearest neighbors ^ 3—nearest neighbors ^ neighest centroid, support-vector- Steps (b) and (c) may be performed by calculating with various algorithms such as Machines (support vector machines) to determine whether subject x is diabetic or its reserve army! / ,.

[0076] The "specific gene or gene group" to be measured in order to obtain an expression profile upon the implementation of the first invention (part 1) is selected from the genes (A-1) to (A-50) described above. One or more selected. These genes are also listed in Table 3. In Table 3, the genes (A-1) to (A-50) are divided into genes that are up-regulated in diabetics! /, And genes that are down-regulated. They are arranged in the order of (absolute value of t value). Therefore, " The gene selected as the “specific gene or gene group” is preferably a gene having a significant difference in Table 3. Among the genes listed in Table 3, (A-22) malate dehydrogenase gene, (A-26) glutamylprolyl tRNA synthase gene, (A-35) protein tyrosine phosphatase gene and (A-36) pyruvin A “specific gene or gene group” may be selected from 46 genes other than the acid dehydrogenase gene. Furthermore, as the “specific gene or gene group”, only the gene whose expression is enhanced may be selected, only the gene whose expression is attenuated may be selected, or both may be selected. May be. In addition, the “specific gene or gene group” may be one of the genes (A-1) to sol (A-50), two, or three or more. The number can be up to 50.

[0077] To give a specific example, in selecting a "specific gene or gene group", in Table 3,

(i) selecting a gene from (A-1) to (A-50) so as to include (A-1) and / or (A-2) where the absolute value of t value is 6 or more,

(ii) The absolute value of the t-value should include V, deviation, or all of the seven genes (A-1) to (A-6) and (A-50) that are 5.5 or more ( Select a gene from A-1) to (A-50), or

(iii) Including any or all of 37 genes (A-1) to (A-31) and (A-45) to (A-50) whose absolute value of t is 5.0 or more Thus, genes can be selected from (A-1) to (A-50).

[0078] The "specific gene or gene group" measured in order to obtain an expression profile in carrying out the first invention (part 2) is a gene group belonging to the MAP kinase 'signaling' pathway and the p38M APK signaling 'pathway Selected from (MAPK gene group).

[0079] Table 7 shows 82 genes among the genes that belong to the MAPK gene group in BRB-ArrayTools (registered trademark). The “specific gene or gene group” in the first invention (part 2) may be selected from these 82 genes! /.

[0080] Table 9 shows 31 genes (the above-mentioned (B-1) to (B-31)) among the genes identified as belonging to the MAPK gene group in MAPPFinder! / did . In diabetes, the expression of these 31 genes is increased compared to healthy individuals. The “specific gene or gene group” in the first invention (part 2) may be selected from these 31 genes. In addition, it is preferable to select a gene having a small p value from the genes listed in Table 9.

[0081] The "specific gene or gene group" in the first invention (part 2) may be one of the MAPK gene group, two of them, or 3 More than 82 species or 31 species may be used.

[0082] As a specific example, in selecting "a specific gene or gene group", in Table 9,

(i) To include any or all of the four genes of (Β-6), (B-7), (B-22) and (B-29) whose p-value is 1 X 1CT ³ or less Select a gene from (B-1) to (B-31), or

(ii) p value 1 X 1CT ² below (B- 2), (B- 4 ), (B- 5), (B- 6), (B- 7), (B- 11), (B — 13), (B—15), (B—16), (B—21), (B—22), (B—24), (B—25), (B 26), (B—29) In addition, a gene can be selected from among (B-1) to (B-31) so as to include! /, Any or all of 16 genes in (B-30).

[0083] The “specific gene or gene group” measured in order to obtain an expression profile in carrying out the first invention (part 3) is a gene group belonging to the ubiquinone biosynthesis system and the ATP synthesis system (OXPHOS gene). Group).

[0084] Table 8 shows 70 genes among genes that belong to the OXPHOS gene group in BRB-ArrayTools (registered trademark). The “specific gene or gene group” in the first invention (Part 3) may be selected from these 70 genes. In diabetes, these 70 genes are attenuated in expression compared to healthy individuals.

[0085] Table 11 lists 42 genes (the above (C-1) to (C-42)) among the genes that belong to the OXPHOS gene group in MAPPFinder. In diabetes, the expression of these 42 genes is attenuated compared to healthy individuals. The “specific gene or gene group” in the first invention (part 3) may be selected from these 42 genes. In Table 11, the expression intensity of each gene in diabetic patients and healthy subjects, measured using 44 oligonucleotides corresponding to the 42 genes, is described. Yes. Moreover, it is preferable to select a gene having a small p value from the genes listed in Table 11. Furthermore, among the genes listed in Table 11, ATPase gene, that is, a specific gene or gene group is selected from 39 genes other than (C 8), (C 17) and (C 28). May be.

[0086] The "specific gene or gene group" in the first invention (part 3) may be one type, two types, or three or more types in the OXPHOS gene group. Any number up to 70 or 42 species can be used.

[0087] As a specific example, in selecting "a specific gene or gene group", in Table 11,

(i) (C—l), (C 6), (C—10), (C 21), (C—25), (C—26), (C—29) with p value of 1 X 1CT ³ or less ), (C-37), (C-38) and (C-39) select genes from (C-1) to (C-42) to include any or all of the 10 genes Or

(ii) (C— 1), (C 6), (C 7), (C 9), (C— 10), (C 15), (C— 16) with p value of 1 X 10 ² or less , (C-19), (C20), (C21), (C22), (C-24), (C-25), (C26), (C27), (C28), ( C 29), (C 30), (C 32), (C 33), (C 34), (C- 37), (C- 38), (C- 39), (C-40) and (C — The ability to select a gene from (C 1) to (C 42) to include any or all of the 26 genes in 41).

[0088] The second invention is a method for determining the presence or absence of a therapeutic effect in a type 2 diabetic patient, comprising: (A) a specific gene in human leukocytes collected before and after the start of treatment of a test diabetic patient or A step of obtaining an expression profile of the gene group, (B) a step of comparing the expression profile of the gene or the gene group before the start of treatment measured in step (A) with the expression profile of the gene or the gene group after the start of the treatment, And (C) the expression profile of the specific gene or group of genes after the start of treatment is significantly different from the expression profile of the specific gene or group of genes before the start of treatment, indicating that the expression profile is diabetic. It is a method including a step of determining that a therapeutic effect has been obtained when disappeared or reduced.

[0089] In step (A), blood is collected from a test diabetic patient before and after the start of treatment, and expression of a specific gene or gene group in RNA derived from human leukocytes contained in the blood. This is a step of measuring the mRNA or protein derived from the specific gene or gene group, and obtaining the expression profile of the specific gene or gene group from the data such as quantity. The method for collecting RNA derived from human leukocytes, the method for measuring mRNA and protein, and the definition of the expression profile are as described above.

[0090] In step (B), the expression profile of the gene or gene group before the start of treatment (hereinafter referred to as “expression profile b”) and the expression profile of the gene or gene group after the start of treatment (hereinafter referred to as “expression profile a”). "). This step is the same as step (b) of the first invention except that the objects to be compared are “expression profile b” and “expression profile a”.

[0091] Step (C) is a step of determining that a therapeutic effect has been obtained when expression profile a is significantly different from expression profile b and the characteristics of the expression profile indicating diabetes are lost or reduced.

[0092] The determination of the significant difference in this step (C) is basically the first except that the target to be determined whether there is a significant difference is "expression profile b" and "expression profile _a ". This is the same as step (c) of the invention.

[0093] In addition, since there is a specific or characteristic profile of diabetes regarding the expression of a specific gene, in this step (C), the specific or characteristic profile of such diabetes disappears after treatment. The reduction is also a condition for determining that the therapeutic effect has been achieved. A “diabetes-specific or characteristic profile” means that expression of certain gene 1 is increased when suffering from diabetes compared to non-diabetes. Refers to information such as Here, it was defined that “the characteristics of the expression profile indicating diabetes have disappeared or reduced” because the gene expression profile in a state where a disease has been cured or relieved is the same as the gene expression profile of a healthy subject. This is because it is not always true. For example, there is a case where the attenuation of the expression of a certain gene is compensated for by the expression increase of another gene.

[0094] Therefore, in the second invention, there is a significant difference in the expression profile a (expression profile after the start of treatment) compared to the expression profile b (expression profile before the start of treatment). In addition, in the expression profile a, the characteristics of the expression profile indicating diabetes If the symptom disappears! /, Or such a feature is diminished! /, It is determined to be effective (ie, the feature has been reduced! /), It is determined to have a therapeutic effect.

[0095] The “specific gene or gene group” to be measured in order to obtain an expression profile in the implementation of the second invention (part 1) is selected from the genes (D-1) to (D-50) described above. One or more selected. These genes are also listed in Table 5. In Table 5, the genes (D-1) to (D-50) are divided into the gene whose expression level was reduced after treatment and the gene whose expression was enhanced after treatment. Are arranged in the order of significant difference (absolute value of t value). Therefore, the gene selected as the “specific gene or gene group” is preferably a gene having a significant difference in Table 5. In addition, among the genes listed in Table 5, 49 genes other than the (D-23) 1-acylglycerol-1-phosphate O-acyltransferase gene were identified as “specific genes or gene groups. May be selected. Furthermore, as a “specific gene or gene group”, only genes whose expression decreases after treatment may be selected, only genes whose expression is enhanced, or both may be selected. May be. In addition, the “specific gene or gene group” may be one of the genes (D-1) to (D-50), two, or three or more. It may be the number that can be stored until it is completely seeded.

[0096] As a specific example, in selecting a "specific gene or gene group", in Table 5,

(i) Select genes from (D-1) to (D-50) so that the absolute value of t-value includes 7 (D-1) and / or (D-2) ,

(ii) (D-1) to (D) so that the absolute value of the t value includes! /, or any or all of the 10 genes (D-1) to (D-10) of 6.5 or more. Select a gene from D-50), or

(iii) Includes any or all of the 25 genes from (D-1) to (D-18) and (D-44) to (D-50) whose absolute value of t is 6.0 or more Thus, genes can be selected from (D-1) to (D-50).

[0097] The “specific gene or gene group” measured in order to obtain an expression profile in carrying out the second invention (part 2) is a gene group belonging to the MAP kinase 'signaling' pathway and the p38M APK signaling 'pathway Selected from (MAPK gene group). [0098] Table 7 shows 82 genes among the genes that belong to the MAPK gene group in BRB-ArrayTools (registered trademark). The “specific gene or gene group” in the second invention (part 2) may be selected from these 82 genes. The expression levels of these 82 genes are reduced by force therapy in which the expression is increased in diabetes compared to healthy individuals.

[0099] Table 10 shows 29 genes (the above (E-1) to (E-29)) among the genes identified as belonging to the MAPK gene group in MAPPFinder! / did. (E-1) Mitogen-activated protein kinase kinase 11 gene and (E-2) CREB-binding protein (Rubinstein-Tybi syndrome) gene have the ability to increase expression by diabetes treatment. 27 other genes Is diminished by the treatment of diabetes. The “specific gene or gene group” in the second invention (part 2) may be selected from these 29 genes. In that case, you may select only genes whose expression is increased by treatment of diabetes! /, Or you may select only genes whose expression is attenuated! /, Or you may select both. . In addition, it is preferable to select a gene with a small p-value from the genes listed in Table 10.

[0100] The “specific gene or gene group” in the second invention (part 2) may be one of the MAPK gene group, two of them, or 3 There may be any number of varieties up to 82 or 29 species or more.

[0101] To give a specific example, in selecting a “specific gene or group of genes”, in Table 10,

(i) If the p-value is IX 10 ³ or less (10—6), (E—14), (E—22), (E—27), and (E—29) among 5 genes! Or select a gene from (E-1) to (E-29) to include everything, or

(Value 1 10 - ² following (£ -1), (E- 6 ), (E- 9), (E- 12), (E- 13), (E- 1 4), (E- 16 ), (E-19), (E-20), (E-21), (E-22), (E-24), (E-25), (E-27), (E-28) and A gene can be selected from (E-1) to (C-29) so as to include any or all of the 16 genes of (E-29).

Example 1

[0102] Gene expression in diabetics and healthy subjects, and before and after treatment of diabetes Examining fluctuations

1.Target

The subjects were 57 diabetic patients (type 2 diabetic patients: 49; type 1 diabetic patients: 8) and 16 healthy individuals. Table 1 shows the results of biochemical tests on the blood of these subjects as clinical background. In addition, the method of blood biochemical examination adopted the method generally performed clinically.

[Table 1] Clinical background of diabetics and healthy subjects

The numerical value is expressed as an average earth level deviation.

*: P <0. 05 (for healthy people)

* *: P <0. 01 (for healthy people)

[0104] In addition, in 24 of 57 diabetic patients, biochemical examination of blood was also performed after treatment for diabetes for the purpose of glycemic control (average after 355 days from the start of treatment; 18 to 896 days later). Went. Table 2 shows the blood biochemical test results before and after treatment of these subjects and the treatment methods (diabetes treatment method and hypertension and hyperlipidemia treatment method). Before and after glycemic control, fasting plasma glucose and glycohemoglobin decreased significantly, and there was no significant change in lipid metabolism or liver function.

[0105] [Table 2] Clinical background of diabetic patients before and after treatment (glycemic control)

The numerical value is represented by the average soil standard deviation.

There are patients who have been administered two or more types of confectionery.

* *: P <0. 01 (before treatment)

[0106] 2. Analysis of gene expression in peripheral blood leukocytes

(2-1) Preparation of RNA from peripheral blood leukocytes

(2-1-1) Method using Micro RNA Isolation Kit (Stratagene) and RNeasy Mini Spin Column (QIAGEN)

(i) Ten ml of collected blood (with heparin added) was subjected to the Ficoll-Hypaque method (density gradient centrifugation) to collect peripheral blood leukocytes.

(Ii) Peripheral blood leukocytes were dissolved in a denaturing buffer 170-1 containing / 3-mercaptoethanol 1.4 and extracted with phenol-chloroform to recover an aqueous layer 150 ^ 1. To prevent Genomic DNA contamination, the recovered aqueous layer is mixed with 525 μ 1 buffer RLT (buffer containing guanidine thiocyanate and / 3-mercaptoethanol), and the resulting mixture is mixed with 250〃1. Of 100% Ethanore.

[0108] (iii) Pour the mixture obtained in (ii) into the RNeasy Mini spin column to absorb the RNA. I wore it. After washing, RNA was eluted with 100 1 elution buffer.

[0109] (iv) After adding ethanol to the eluate to precipitate RNA, the RNA was dissolved in 20 µl of nuclease-free water.

[0110] (v) Use 1 μ 1 of RNA-free nuclease-free water using Bio Analyzer 2000 (Agilent)

V, electrophoresis, and RNA denaturation and quantification were performed by conventional methods.

[0111] (2- l-2) Using PAXgene Blood RNA Kit (QIAGEN; cat # 762134)

(i) Baxgene 2.5 ml of whole blood was collected into an RNA vacuum blood collection tube (QIAGEN; cat # 762105).

[0112] (ii) Incubate at room temperature for 2 hours, and then use a Baxgene RNA vacuum blood collection tube

Centrifuge for 10 minutes at 00 X g.

(Iii) The supernatant was decanted, and 5 ml of RNase-free water was added to the precipitate.

[0114] (iv) Using a vortex, the pellet was completely suspended in RNase-free water.

[0115] (V) The Vaxgene RNA vacuum blood collection tube containing the suspension was centrifuged at 3,000 X g for 10 minutes.

[0116] (vi) The supernatant was completely removed, and then buffer BR1 360 1 was added.

[0117] (vii) Using a vortex, the pellet was completely suspended in buffer BR1.

[0118] (viii) The suspension was transferred to a 2 ml microcentrifuge tube.

(Ix) 300-1 BR2 buffer and 40-1 protekin kinase K were added, and the mixture was stirred using a vortex.

[0120] (X) The microcentrifuge tube was incubated at 55 ° C for 10 minutes, and then centrifuged at 15, OOOrpm for 3 minutes.

[0121] (xi) The supernatant was transferred to a new 2 ml microcentrifuge tube.

[0122] (xii) 100% ethanolol 350 1 was added and stirred using a vortex.

[0123] (xiii) 700 μ1 of the sample obtained in (xii) was applied to a Baxgene column set on a 2 ml tube, and centrifuged at 8,000 X g for 1 minute.

(Xiv) The remaining samples were applied to the same Buxgene column and centrifuged in the same manner.

[0125] (XV) Noter BR3 was added to 7001 on the same column and centrifuged at 8,000 X g for 1 minute. [0126] (xvi) 500 1 buffer BR4 was added to the same column and centrifuged at 8,000 X g for 1 minute

[0127] (xvii) Carry out 500 1 of KIFFER BR4 on the same column, and centrifuge at 15,000 X g for 3 minutes.

The membrane of the column was completely dried.

[0128] The (xviii) column was placed on a 1.5 ml tube, 40 1 of elution buffer BR5 was added, and then centrifuged at 8,000 X g for 1 minute.

[0129] Step (xix) was repeated.

[0130] (XX) The mixture was incubated at 65 ° C for 5 minutes, and immediately cooled on ice.

[0131] (xxi) —Stored at 80 ° C.

[0132] (2-2) Analysis of gene expression on DNA chip

DNA Chip Laboratories Co., Ltd.// A micro chip (AceGene (registered trademark) Human Oligo Chip 30K) equipped with oligonucleotide probes (sense strands) corresponding to about 30,000 genes. ) Was used to analyze the gene expression level. Specifically, the following procedure was used.

[0133] (i) Amino Allyl MessageAmp (registered trademark) aRNA kit (# 1753: Ambion) was used to prepare an aminoallyl-labeled aRNA from an approximate RNA according to the protocol. The aminoallyl group was formed by incorporating aminoallyl UTP during aRNA synthesis.

[0134] (ii) Dissolve 5 〃g aminoallyl-labeled aRNA in Coupling 'buffer, add CyDye (GE Healthcare Science) dissolved in DMSO, and perform the coupling reaction at 40 ° C. I let them. When comparing the gene expression intensities of diabetic patients and healthy individuals, cy-5 was bound to RNA from diabetic patients and cy-3 was bound to RNA from healthy individuals.

[0135] (iii) After purification and concentration, add fragmentation to the solution containing CyDye-bound aRNA, add buffer, warm at 94 ° C for 15 minutes (fragmentation), then quench with crushed ice did.

[0136] (iv) Hybridization buffer and 10% SDS were added to the solution of (iii), heat-denatured at 95 ° C, and then rapidly cooled with crushed ice. [0137] (v) Formamide was added to prepare a hybridization solution, and then incubated at 50 ° C for 5 minutes.

[0138] (vi) The hybridization solution was poured into the microchip and incubated at 50 ° C for 16 to 20 hours to hybridize aRNA to the oligonucleotide on the microchip. . In addition, when comparing the gene expression intensities of diabetic patients and healthy individuals, RNAs combined with cy-5 and RNAs combined with cy-3 were mixed in equal amounts.

[0139] (vii) After completion of the hybridization, washing and drying were performed according to the protocol.

[0140] (viii) Slide (micro 'chip) was scanned with Scan Array Express (Perkin-Elmer), and each spot' signal (fluorescence intensity) was quantified and standardized using DNASIS Array. . When both cy-5 and cy-3 were used, these dyes had different measurement wavelengths, and thus were measured separately.

[0141] 3. Statistical analysis

Using the data obtained in 2 (all specimens! / All measured gene expression levels), cluster classification was performed based on the similarity of expression profiles. Details of the results are not shown, but diabetic cases and healthy subjects, and a large classification before and after diabetes treatment Example 2

[0142] Selection of gene groups useful for the determination of the presence or absence of diabetes (Part 1) Selection from all gene groups Expression data of about 30,000 genes whose gene expression levels were measured in Example 1 were used as BRB-ArrayTools Analyzed by software, we selected genes (absolute t values up to the top 50 in terms of absolute value of t) in which there was a significant difference in expression (P <0.00001; increase or decrease) between diabetics and healthy subjects. They are shown in Table 3.

[0143] From this result, one or more expression profiles of the genes (A-1) to (A-50) shown in Table 3 in the leukocyte RNA of the subject were obtained. It can be determined whether or not is diabetes or its reserve.

[0144] [Table 3] Table 3 Genes with significant differences in expression between diabetics and healthy individuals

t value / 《Parameter P Gene name Gene registration number

-7.5 P <0.000001 hypothetical protein LOC54103 AL079277

-6.94 P <0.000001 leucine rich repeat neuronal 3 AB060967

-5.68 P 0.000001 13kDa differentiation-associated protein BC005936

emopamil binding related protein, delta8 ^_ detta7 sterol

-5.61 P 0.000001 AF243433

isomerase related protein

-5.56 P 0.000001 glycosyltransf erase AD-017 N _018446

-5.55 P 0000001 peroxiredoxin 3 N .006793

Fc fragment of IgE, high affinity 【, eceptor for; alpha

-5.45 P <0.000001 N .002001 polypeptide

-5.43 P 0.000001 signal peptidase 12kDa ENSG000001 14902

-5.4 P <0.000001 non-POU domain containing, octamer— binding L32558

-5.38 P 0.000001 NP220 nuclear protein AF273049

-5.38 P 0.000001 hypothetical protein FLJ 10652 N .018169

-5.38 P 0.000001 chromosome 14 open reading frame 109 AL0801 18

-5.37 P 0.000001 death associated protein 3 MM

-5.37 P <0.000001 AUT-like 1, cysteine endopeptidase (S. cerevisiae) ENSG00000125703

-5.33 P <0.000001 recombination protein REC14 AF309553

-5.28 1.00E-06 esterase D / formylglutathione hydrolase AF112219

-5.28 1.00E-06 transmembrane protein 1 B N, 030969

-5.25 1.00E-06 protein associated with Myc AF083244

-5.21 2.00E-06 eukaryotic translation initiation factor (elF) 2A AF212241

-5.15 2.00E-06 B-cell linker ENSG00000095585

-5.13 2.00E-06 lymphocyte antigen 8b NM.004271

-5.12 2.00E-06 ma late dehydrogenase 1, AD (soluble) ENSG00000014641

-5.11 2.00E-06 putative membrane protein AF070626 i 5.08 3.00E-06 cellular repressor of El A-stimulated genes NM— 003851

-5.08 3.00E-06 exportin 1 (CR 1 homolog, yeast) N _003400

t value Parameter P Gene name Gene registration number

26 -5.07 3.00E-06 glutamvl ~ proly | -tRNA synthetase NM_004446

27 -5.06 3.00E-06 sorting nexin 13 AL353943

28 -5.04 3.00E-06 hypothetical DKFZp451J1719 AF1 16608

29 -5.03 3.00E-06 ACN9 homolog (S. cerevisiae) AF201933

30-5.03 3.00E-06 anaplastic lymphoma kinase (Ki— 1) D45915

31 -5.03 3.00E-06 centrosomal protein 1 亂 007018

32 -4.97 4.00E-06 I i gat in AF2204 7

33 -4.95 4.00E-06 ATPase, H + transporting, lysosomal accessory protein 2 AF248966

34 -4.94 5.00E-06 inner membrane protein, mitochondrial (mitofilin) NM.006839

35 -4.94 5.00E-06 protein tyrosine phosphatase, non-receptor type 12 NM.002835

36 -4.94 5.00E-06 pyruvate dehydrogenase (lipoannide) beta M34479

37 -4.94 5.00E-06 unc-50 homolog (C. elegans) AF077038

38 -4.9 5.00E-06 hypothetical protein FLJ20003 NM.017615

39 -4.9 5.00E-06 hypothetical protein KIAA1 109 AB029032

40 4.82 8.00E-06 tubby like protein 3 N .003324

41 4.86 7 0Ε-06 dual specificity phosphatase 5 N .004419

42 4.9 5.00E-06 mitogen-activated protein kinase kinase 7 BC005365

nuclear factor of kappa light polypeptide gene enhancer in

43 4.94 5.00E-06 N .020529

B-cells inhibitor, alpha

44 4.97 5 00E-06 dentin matrix acidic phosphoprotein NM-004407

45 5.04 3.00E-06 Kruppel-like factor 5 (intestinal) N .001 730

46 5.12 2 00E-06 iduronate 2-sulfatase (Hunter syndrome) NM.006123

CD83 antigen (activated B lymphocytes, immunoglobulin

47 5.18 2.00E-06 N _004233 super-family)

48 5.19 2.00E-06 ring finger protein 121 N _0 8320

49 5.4 p 0.000001 core promoter element binding protein N .001300

50 5.88 p 0.000001 serum / glucocorticoid regulated kinase NM.005627 Example 3

Verification of the validity of selection of genes that are useful for determining the presence or absence of diabetes (calculation of diagnostic prediction probability)

Using the gene expression levels measured in Example 1, the expression levels of the 50 genes selected in Example 2 in diabetic patients (57 samples) and healthy subjects (16 samples) were calculated using various algorithms (composite covariation, / Law, compound covariate preaictor), T-angle spring form additional ¹ J force, analysis (diagonal linear disc riminant analysis) ^ 丄 1 nearest neighbor method (1—nearest neighbor 8 3-neighbor method, d-near est neighbors) The specimens were divided into 2 groups (diabetes and healthy people) by statistical processing using the nearest centroid, support vector machines. Compare the results with the actual situation (whether it is a diabetic patient or a healthy person). The correct answer rate was calculated. The results are shown in Table 4. This corresponds to the calculation of the diagnostic prediction probability using the supervised learning method.

[0146] As is clear from Table 4, all of them had a high accuracy rate of 92% or more.

[0147] Although data are not shown, 10 genes were selected from the genes with the lowest p-value in the order shown in Table 3, and the same study was conducted. Judging by the rate S

[0148] In addition, the expression levels of the 50 genes (50 genes selected in Example 2) used in the supervised learning method for diabetic patients (57 samples) and healthy subjects (16 samples) are shown in Example 1. It was measured by the method described. Figure 1 shows the results of scanning slides (microchips) with Scan Array Express (Perkin-Elmer). This method corresponds to an unsupervised learning method, but it was revealed that the expression profiles of the 50 genes measured here differ greatly depending on the presence or absence of diabetes. Therefore, it is possible to determine whether or not the patient has diabetes from the expression profiles of these genes.

[0149] [Table 4]

n 蟾ノ ^ «l

Example 4

Selection of genes useful for determining the effectiveness of treatment (blood glucose control) (Part 1) Selection from all genes

The expression level data of about 30,000 genes whose gene expression levels were measured in Example 1 Analysis was performed with ArrayTools software, and genes (up to the 50th absolute value of the t value) that significantly changed expression before and after diabetes treatment (glycemic control) were selected. They are shown in Table 5.

[0151] From this result, for leukocyte RNA in blood collected before and after the start of treatment for diabetic patients, one of the genes (D-1) to (D-50) shown in Table 5 or It can be seen that by obtaining two or more expression profiles, it is possible to determine whether or not the therapeutic effect is enhanced.

[0152] [Table 5] Table 5 Genes with variable expression before and after glycemic control

tfit No., Fumeter P Gene name Gene registration number

1 -8.04 p 0.000001 forkhead box P1 NM— 016477

2 -7.31 p <0000001 CD 24 antigen (small cell lung carcinoma cluster 4 antigen) NM_013230

3-6.8 p 0.000001 ribosomal protein L29 NM.000992 eukaryotic translation elongation factor 1 delta (guanine

(4 -6.8 p 0.000001 NM.032378 nucleotide exchange protein)

5 -6.76 p 0.000001 ELK3, ETS-domain protein (SRF accessory protein 2) NM-005230 nuclear receptor subfamily 3, group C, member 1

6 -6.74 p 0.000001 NM— 000176

(glucocorticoid receptor)

7 -6.73 p 0.000001 neurotensin receptor 1 (high affinity) NM.002531

8 -6.67 p 0.000001 integral membrane protein 2A N .004867

9 -6.61 p <0.000001 orthodenticle homolog 2 (Drosophila) NM— 021728

10 -6.52 p <0.000001 elastase 2A NM— 033440 translocase of outer mitochondrial membrane 22 homolog

11 -6.46 p 0.000001 NM— 020243 iveast ^

12 -6.42 p 0 0 001 endosulfine alpha N .004436

13 -6.42 p 0.000001 CD226 antigen NM.006566 transient receptor potential cation channel, subfamily V,

14 -6.26 1.00E-06 NM.021625 member 4

15 -6.18 1.00E-06 ADP-ribosylation factor interacting protein 2 (arfaptin 2) NM_012402

16 -6.13 1.00E-06 bradykinin receptor B2 NM.000623

17 -6.03 2.00E-06 ribosomal protein S3 NM— 001005

18 -6 2.00E-06 contactin associated protein—like 2 N .014141

19 -5.99 2.0OE-06 myosin, light polypeptide kinase NM— 005965

20 -5.99 2.00E-06 dipeptidase 1 (renal) NM— 004413

21 -5.99 2.00E-06 vitelliform macular dystrophy (Best disease, bestrophin) AF057170

22 -5.95 2.00E-06 chemokine (C-C motif) ligand 5 NM_002985

1—acylglyceroto 3-phosphate O-acyltransferase 1

23 -5.9 2.00E-06 NM— 032741

(lysophosphatidic acid acyltransferase, alpha)

24 -5.89 3.00E-06 zinc finger protein, subfamily A, 4 (Eos) NM.022465

25 -5.88 3.00E-06 benzodiazapine receptor (peripheral) NM.000714 Parameter P Gene name Gene registration number

26 -5.84 3.00E-06 KIAA0174 gene product N _014761

27 -5.82 3.00E-06 mortality factor 4 like 2 NM_012286

serine (or cysteine) proteinase inhibitor, clade B (ovalbumin),

28 -5.81 3.00E-06 NM— 012397

member ι J

29-5.8 3.00E-06 IK cytokine, down-regulator of HLA II AL050296

30 -5.8 3.00E-06 lipopolysaccharide-induced TNF factor NM.004862

goigi associated, gamma adaptin ear containing, ARF binding

31 -5.78 3.00E-06 NM.013365

protein 1

transient receptor potential cation channel, subfamily M,

32 -5.77 4.00E-06 NM— 014555

member 5

33 -5.77 4.00E-06 high-mobility group nucleosome binding domain 1 NM.004965

34 -5.76 4.00E-06 cyclin Ί) N .001240

v-maf musculoaponeurotic fibrosarcoma oncogene homolog

35 -5.75 4.00E-06 NM 1 005360

(avian)

36 -5.74 4.00E-06 family with sequence similarity 18, member B AF223467

inhibitor of DNA binding 2, dominant negative helix-loop-helix

37-5.74 4.00E-06 NM.002166

protein

TAF1 1 RNA polymerase II, TATA box binding protein (TBP)-

38 5.71 4.00E-06 ENSG00000064995 associated factor, 28kDa

39 5.81 3.00E-06 cadherin 11, type 2, OB-cadherin (osteoblast) D21255

thyroid hormone receptor, alpha (erythroblastic leukemia viral

40 5.85 3.00E-06 X55005

(v-erb-a) oncogene homolog, avian)

41 5.86 3.00E-06 zinc finger protein 160 X78928

42 5.89 3.00E-06 phospholipase A2, group X ENSG00000069764

43 5.98 2.00E-06 hypothetical protein FLJ23120 AK026773

44 6.05 2.00E-06 phosphoinositide-3-kinase, class 2, gamma polypeptide AJ000008

45 6.07 2.00E-06 hypothetical protein I AGE: 4215339 AC005328

46 6.09 2.00E-06 cathepsin E AJ250716

47 6.11 1.00E-06 c emokine (C motif) receptor 1 NM.005283

48 6.16 1.00E-06 dedicator of cytokinesis 9 ENSG00000088387

49 6.19 1.00E-06 ring finger protein 39 AF238317

50 6.22 1.00E-06 chromosome l 7 open reading frame 28 AL137556 Example 5

Validation of selection of genes useful for determining the effectiveness of treatment (blood glucose control) (calculation of diagnosis prediction probability)

Using the gene expression levels measured in Example 1, the expression levels of the 50 genes selected in Example 4 before and after the start of treatment for diabetic patients were calculated using various algorithms (composite covariation prediction, / law, compound covariate predictor) ^ menu T SumiIzumi form-size另¹ J analysis (diagonal linear discri minant analysis) ^ 1- nearest neighbor method (1-nearest neighbor) ^ d- nearest neighbor method (3-neare st neighbors), nearest neighbor Statistical analysis with centroid (nearest Centroid), support vector 'support vector machines', 2 samples (diabetes treatment developed) It was divided into a group before the start and a group after the start of treatment). The results were compared with the actual situation (before or after the start of treatment for diabetes) to determine the correct answer rate. The results are shown in Table 6. This corresponds to a supervised learning method.

[0154] As is clear from Table 6, all of them had a high accuracy rate of 96%.

[0155] Although data are not shown, 10 genes were selected in order from the lowest p-value among the genes in Table 5 and the same study was conducted. 77% to 82% before and after the start of diabetes treatment. High! /, I was able to judge by probability.

[0156] In addition, the 50 genes used in the supervised learning method (50 genes selected in Example 4) before and after the treatment for diabetes (23 samples each) were used! The expression level was measured by the method described in Example 1. Figure 2 shows the results of scanning the slide (micro chip) with Scan Array Express (Perkin-Elmer). This method is equivalent to an unsupervised learning method. It was revealed that the expression profiles of the 50 genes measured here differ greatly before and after the start of diabetes treatment. Therefore, the presence or absence of a therapeutic effect for diabetes can be determined from the expression profile of these genes.

[0157] [Table 6]

Example 6

Analysis of gene expression characteristics in diabetic patients Gene expression analysis in pathway units

Oligonucleo on AceGene (registered trademark) Human Oligo Chip 30K Each gene with a tide was classified according to which pathway it belongs to (some genes may belong to more than one pathway). When the present inventors screened 535 human gene sets, these gene sets were included in one or more of 285 BioCarta pathways, 101 KEGG pathways, and 149 gene sets.

[0159] From the data obtained in Example 1, data on the expression level of the gene group belonging to the pathway was collected for each pathway. Those data were analyzed with BRB-ArrayTools software, and when gene expression was evaluated on a pathway basis, pathways that were significantly altered in expression compared to the healthy group were extracted from the diabetic group. In addition, analysis with MAPPFinder software was also performed! /, In the diabetic group! /, And pathways that were significantly up-regulated or attenuated compared to the healthy group were extracted.

[0160] As a result, in the diabetic group, genes (MAPK gene group) belonging to the MAPK cascade (MAP kinase 'signaling' pathway and P38MAPK signaling 'pathway) are up-regulated, and mitochondria involved in ATP production. The gene group (O XPHOS gene group) that constitutes the oxidative phosphorylation of the electron transfer system function (the ubiquinone biosynthesis system and the ATP synthesis system) was clearly expressed.

[0161] By the same method, pathways whose expression was significantly changed before and after the start of diabetes treatment were extracted.

[0162] As a result, expression of genes belonging to the MAPK cascade (MAP kinase. Signaling 'pathway and p38 MAPK signaling' pathway) was increased before the start of diabetes treatment! It became clear that it was significantly reduced by.

[0163] In the analysis with BRB-ArrayTools software, 82 genes shown in Table 7 were identified as MAP kinase 'signaling' pathway and p38 MAPK signaling 'pathway. The 70 genes shown in Table 8 were identified as genes belonging to the ATP synthesis system.

[0164] [Table 7] List of MAP K genes in BRB-ArrayT oo 1 s (A f ί.

209666— s a t 1 552263. a t 209951— s a t

1 554319— _a t 2071 21— s a t 203617— X at

1 552631. _a― a t 207292— s a t 209189— a t

21 1459— a t 210477— X a t 212983— a t

1559295._a t 206040— s a t 208328— s a t

206106— a t 203218— a t 1570439.

203096— s— a t 2048 13— a t 203836— s a t

209341— s— a t 210058— a t 203552— a t

1570076_ _a t 207667— s a t 1565130, a t

205027— s— a t 204756— a t 1567457.

202424— a t 205698— s a t 206296— X a t

203084— a t 1557675 a t 200887— s a t

202530— a t 203379— a t 203097— s a t

201763— s― a t 1556340. a t 218205— s a t

201895— a t 203265 one s a t 218181— s a t

1555146. _a t 201469— s a t 201502— s a t

215075— s— a t 2041 71— a t 1557970.s a t

201464— x― a t 206853— s a t 204413— at

203514— a t 2183 1 1— a t 201460— a t

1558984._a t 2 12871— at 212046— X at

206362— x― a t 1560720. a t 202787— s a t

202431_ s― a t 1729_a t 204707― s a t

1565772. —a t 204632— a t 202670— a t

1559052, s a t 203777— s a t 206943— at

204039_ t 205192— a t 214786— a t

2 1 3926— S― 1 t 209239— a t 1553685.s a t

204936— _a t 206044— s a t 208403— X at

1 560868 ― s― _a t

List of OX PHO S genes in BRB-A r ra y To o 1 s (A f f.

207335— x a t 202325— s a t 219547_a t

218200_s a t 201322_ a t 202298— at

201966— a t 203926— X a t 218226— s ― a t

218160— a t 211755— s a t 218101— s — a t

203606— a t 207507_ s a t 201740— a t

206790— s a t 202343— X a t 201256— at

201754— a t 204570— a t 201304— a t

201134— x a t 201597— a t 208969— a t

218484— a t 202 110— a t 202077— a t

217963— s a t 207843— X a t 201226— at

202839— s a t 201066— a t 205711— x ― a t

202090— s a t 217773— s a t 207552_a t

201568— a t 203621— a t 206353_a t

218563— a t 203478— a t 208909— a t

202026— a t 203189— s a t 217801— a t

218190— s a t 202675__ a t 220864— s one a t

202000— at 202004— X at 205 224— at

203371— s a t 204295— a t 208905— a t

211752_s a t 201903— a t 207573— x ― a t

205849— s a t 2011 19— s a t 208972— s ― a t

200883— a t 201093— X a t 201757_a t

203663— s a t 207618_ s a t 204300— at

202233— s a t 200925— a t

203858— s a t 203551— s a t Example 7

[0166] Expression analysis of MAPK and OXPHOS genes in diabetic patients

The data obtained in Example 1 was analyzed with MAPPFinder software.

[0167] (l) Analysis of genes in MAPK gene group whose expression changes in diabetic patients

For each gene covered by MAPPFinder in the MAPK gene group, standardize the data so that the average value of the data of all samples is 0 and the variance is 1, and then the standardized value is used. The average value and variance were obtained for each of the diabetic patient group and the healthy subject group, and then the mean value (X) in the diabetic patient group was divided by the mean value (Y) in the healthy subject group. [0168] The results are shown in Fig. 3 and Table 9.

[0169] In FIG. 3, the numerical value indicated on the right side of the gene symbol is the value of X / Y. When this is 1.2 or more, the expression is increased in diabetic patients, and when it is 0.8 or less, it can be said that the expression is attenuated. Thus, for genes whose expression was significantly varied, gene symbols were painted in black or gray. However, even if it is more than 0.8 and less than 1.2, if there is a significant difference in consideration of the variance value, the gene symbol outer frame is thick! /, Kuroizumi. It was.

[0170] Table 9 shows 31 genes whose expression is increased in diabetes. These 31 genes are the genes shown above as (B-1) to (B-31).

[0171] From these results, it can be seen that the genetic strength S described in FIG. 3 and Table 9 is useful for determining whether or not the subject is diabetic or its reserve army.

[0172] (2) Analysis of genes in the MAPK gene group whose expression changes before and after the start of diabetes treatment

For each gene covered by MAPPFinder in the MAPK gene group, standardize the data so that the average value of the data of all samples is 0 and the variance is 1, and then the standardized values! The mean value and variance were calculated for each group before and after treatment for diabetes, and then the mean value in the group after treatment was divided by the mean value in the group before treatment start.

[0173] The results are shown in Fig. 4 and Table 10.

[0174] In FIG. 4, the numerical values shown on the right side of the gene symbol are the values “after treatment / before treatment”. If this value is 1.2 or more or 0.8 or less, it can be said that there was a significant change in expression depending on the treatment. Thus, for genes whose expression varies significantly, gene symbols are black or gray.

[0175] Table 10 shows 29 genes whose expression was changed by treatment. These 29 genes are the genes previously indicated as (E-1) to (E-29).

[0176] From these results, it can be seen that it is useful for determining whether or not the gene effect and the therapeutic effect of diabetes described in FIG.

[0177] (3) Analysis of genes in OXPHOS gene group whose expression changes in diabetic patients

For each gene covered by MAPPFinder in the OXPHOS gene group, After standardizing the data so that the average value of the sample data is 0 and the variance is 1, the standardized value is obtained! /, And the average is obtained for each of the diabetic patient group and the healthy subject group! / The values and variances were determined, and then the average value (X) in the diabetic group was divided by the average value (in the healthy group).

[0178] The results are shown in Fig. 5 and Table 11.

[0179] In FIG. 5, the numerical value indicated on the right side of the gene symbol is the value of X / Y. When this is 1.2 or more, the expression is increased in diabetic patients, and when it is 0.8 or less, it can be said that the expression is attenuated. Thus, for genes whose expression was significantly varied, gene symbols were painted in black or gray.

[0180] Table 11 shows 42 genes whose expression is attenuated in diabetes. These 42 genes are the genes previously indicated as (C-1) to (C-42). Table 11 shows the measurement data of 44. This is because the (C-29) ATP synthase, hydrogen transport, mitochondrial F0 complex, subunit c (subunit 9) For the genes of isoform 1 and (C 40) NADH dehydrogenase (ubiquinone) 1, β subcomplex, 4, 15 kilodalton, the oligonucleotides used for the measurement (antigens corresponding to a part of these genes) This is because there were two types of sense strands).

[0181] From these results, it can be seen that the gene strength S described in FIG. 5 and Table 11 is useful for determining whether the subject is diabetic or a reserve army.

[0182] (4) Pre-cornering of genes that change in expression before and after the start of diabetes treatment in the OXPHOS gene group

For each gene covered by MAPPFinder in the OXPHOS gene group, standardize the data so that the average value of all specimen data is 0 and the variance is 1, and then the standardized values! / The mean value and variance were determined for each group before and after treatment for diabetes, and the mean value in the group after treatment was divided by the mean value in the group before treatment treatment.

[0183] The results are shown in FIG.

[0184] In FIG. 6, the numerical value indicated on the right side of the gene symbol is the value “after treatment / before treatment”. Figure 6 shows whether the OXPHOS gene group is effective in treating diabetes. Table 9 MAPK¾ gene with enhanced expression in white blood cells of diabetic patients

Prof's set inheritance in diabetic patients

Gene Name Gene Symbol Gene Expression Strength Geometry of Child Expression Strength X

(Aff. ID) p-value

Geometric mean (X) mean (Y)

mitogen-activated protein kinase kinase kinase 6 MAP3K6 1.1 0.9 1.222 0.02776 ribosomal protein S6 kinase, 90kDa, polypeptide 2 RPS6KA2 1.1 0.7 1.571 0.00921

Mitogen— activated protein kinase kinase kinase 2 MAP3K2 1.1 0.8 1.375 0.012 mitogen-activated protein kinase-activated protein kinase 2 MAPKAPK2 1.2 1 1.2 0.00209 v-jun sarcoma virus 17 oncogene homolog (avian) JUN 1.6 0.8 2 0.00402 nuclear factor of kappa light polypeptide gene enhancer in B- cells inhibitor, alpha NFKBIA 3 1.7 1.765 1.00E-05 v-raf murine sarcoma 3611 viral oncogene homolog ARAF 1 0.7 1.429 4.00E-04

Rap guanine nucleotide exchange factor (GEF) 2 RAPGEF2 1.1 0.9 1.222 001 194 mitogen— activated protein kinase kinase kinase 3 MAP3K3 0-9 0.7 1.286 0.01248

ELK1, member of ETS oncogene family ELK1 1.1 0.9 1.222 0.02117

CCAAT / enhancer binding protein (C / EBP), alpha CEBPA 1.1 0.8 1.375 000142

TNF receptor-associated factor 2 TRAF2 0.8 0.6 1.333 0.02723 mitogen— activated protein kinase 4 MAPK4 1 0.9 1.1 11 0.00647 mitogen-activated protein kinase kinase 5 MAP2K5 1 0.8 1.25 0.04616 mitogen-activated protein kinase kinase kinase 14 MAP3K14 1 0.6 1.667 0.00589 v- raf murine sarcoma viral oncogene homolog B1 BRAF 1.3 1 1.3 0.00574 mitogen-activated protein kinase kinase kinase 10 MAP3K10 0.9 0.8 1.125 0.03279 mitogen— activated protein kinase 6 APK6 1 0.8 1.25 0.02962 mitogen— activated protein kinase kinase 3 AP2K3 1 0.9 1.1 11 00424

MADS box transcription enhancer factor 2, polypeptide A

MEF2A 1.1 0.9 1.222 0.01871

(myocyte enhancer factor 2 A)

v-fos FBJ murine osteosarcoma viral oncogene homolog F05 1.4 1.1 1.273 0.00909 mitogen-activated protein kinase kinase 7 MAP2K7 1.7 1.1 1.545 1.00E-05 mitogen-activated protein kinase 13 MAPK13 1 0.9 1.11 1 0.01852 v-Ha ma as Harvey rat sarcoma viral oncogene homolog HRAS 1 0.7 1.429 000233 growth factor receptor-bound protein 2 GRB2 1.1 1 1.1 000221

MAP kinase interacting serine / threonine kinase 2 MKNK2 1 0.8 1.25 0.00153

Cell division cycle 42 (GTP binding protein, 25kDa) CDC42 1 0.9 1.1 1 1 0.02304 phospholipase A2, group VI (cytosolic, calcium-independent) PLA2G6 0.8 0.7 1.143 0.03728

DNA-damage-inducible transcript 3 DDIT3 1.9 1.2 1.583 0.00079 early growth response 1 EGR1 1 4 1.1 1.273 0.0073 nerve growth factor, beta polypeptide NGFB 1.1 0.8 1.375 0.04528

^ 0851 ] D¾ [87l01

Table 10 MAPK genes whose expression significantly changed after blood glucose control in leukocytes of diabetic patients

Probe set Geometric mean _{te of} expression intensity

/ „ _{Ir l} » fe Child name

^(Απ · ^ID) (after treatment / before treatment)

1558984 at mitogen-activated protein kinase kinase kinase 1 1 MAP3K1 1 1.2 0.00602

1559295 at CREB binding protein (Rubinstein-Taybi syndrome) CREBBP 1.2 0.03115

1565772 at p21 / Cdc42 / Rac 1 -activated kinase 1 (STE20 homolog, yeast) PAK1 0.9 0.01628

1729 at TNFRSF1 A— associated via death domain TRADD 0.8 0.02292

200887 s at signal transducer and activator of transcription 1, 91 kDa STAT1 0.9 0.02752

201460 at mitogen-activated protein Kinase-activated protein kinase 2 MAPKAPK2 0.8 4.00E-05

201464 x at v-jun sarcoma virus 17 oncogene homolog (avian) JUN 0.6 0.03183

201895 at v-raf murine sarcoma 3b 1 viral oncogene homolog ARAF 0.8 0.01601

202431 s at v-myc myelocytomatosis viral oncogene homolog (avian) MYC 0.8 0.0077

202787 s at mitogen— activated protein kinase-activated protein kinase 3 APKAPK3 0.9 0.01146

203084 at transforming growth factor, beta 1 (Camurati-Engelmann disease) TGFB1 0.8 0.02466

203097 s at Rap guanine nucleotide exchange factor (GEF) 2 RAPGEF2 0.9 0.00838

203265 s at mitogen-activated protein kinase kinase 4 MAP2K4 0.8 000135

203379 at ribosomal protein S6 kinase, 90kDa, polypeptide 1 RPS6KA1 0.7 7.00E-05

203514 at mitogen-activated protein kinase kinase kinase 3 MAP3K3 0.8 0.01386

203617 x at ELK1, member of ETS oncogene family ELK1 0.7 0.00234

204707 s at mitogen— activated protein kinase 4 APK4 0.9 0.01079

204813 at mitogen-activated protein kinase 10 APK10 0.9 0.01 147

206362 x at mitogen— activated protein kinase kinase kinase 10 MAP3K10 0.8 0.00556

207292 s at mitogen-activated protein kinase 7 MAPK7 0.8 0.00105

209189 at v— fos FBJ murine osteosarcoma viral oncogene homolog FOS 0.7 0.00501

209341 s at inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase beta IKBKB 0.7 5.00E-05

210058 at mitogen-activated protein kinase 13 MAPK13 0.9 0.02642

212983 at v-Ha— ras Harvey rat sarcoma viral oncogene homolog HRAS 0.8 0.00802

215075 s at growth factor receptor-bound protein 2 GRB2 0.9 0.00788

218205 s at MAP kinase interacting serine / threonine kinase 2 MKNK2 0-8 001533

200943 at high-mobility group nucleosome binding domain 1 HMGN1 0.6 1.00E-05

209383 at DNA-damage-inducible transcript 3 DDIT3 0.7 0.00835

202615 at Guanine nucleotide binding protein (G protein), q polypeptide GNAQ 0.8 5.00E-04

Table 1 1 OXPHOS gene whose expression was attenuated in leukocytes of diabetic patients

Probe set in diabetic patients

Gene expression gene expression intensity gene expression intensity

(Aff. ID)

Geometric mean (X) geometric mean (Y)

1554499 s at inorganic pyrophosphatase 2 PPA2 1 1.2 0.833 0.00035

NADH dehydrogenase (ubiquinone) Fe- S protein 4, 18kDa (NADH-coenzyme

1555057 at 0.8 1 0.8 0.03267

Q reductase) NDUFS4

1555998 at ATP synthase, H + transporting, mitochondrial F0 complex, subunit d ATP5H 0.8 1 0.8 0.02396

ATP synthase, H + transporting, mitochondrial F1 complex, O subunit

1564482 at ATP50 0.9 1.1 0.818 0.01387

(oligomycin sensitivity conferring protein;

1569067 at BCL2-like 1 BCL2L1 1 1.2 0.833 0.03673

1569230 at TatD DNase domain containing 1 TATDN1 1 1.2 0.833 0.00024

ATP synthase, H + transporting, mitochondrial F1 complex, alpha subunit,

1569891 at ATP5A1 0.9 1.1 0.818 0.00756 isoform 1, cardiac muscle

ATPase, H + transporting, lysosomal 9kDa, V0 subunit e /// ATPase, H +

200096 s at 0.8 0.875 0.02958 transporting, lysosomal 9kDa, V0 subunit e ATP6V0E 0.7

200642 at superoxide dismutase 1, soluble (amyotrophic lateral sclerosis 1 (adult)) SOD 1 0.8 1.1 0.727 0.00216

200883 at ubiquino 卜 cytochrome c reductase core protein II UQCRC2 0.8 1 0.8 000012

200925 at cytochrome c oxidase subunit Via polypeptide 1 COX6A1 0.9 1 0.9 0.0229

201 134 x at cytochrome c oxidase subunit VII c COX7C 1.2 1.4 0.857 0.01 163

201754 at cytochrome c oxidase subunit Vic COX6C 0.9 1.1 0.818 0.03691

NADH dehydrogenase (ubiquinone) Fe-S protein 2, 49kDa (NADH-coenzyme

201966 at NDUFS2 0.7 0.8 0.875 0.01758

Q reductase)

202233 s at ubiquino cytochrome c reductase hinge protein UQCRH 0.9 1.1 0.818 0.00475

202325 s at ATP synthase, H + transporting, mitochondrial FO complex, subunit F6 ATP5J 0.7 0.9 0.778 0.00306

202872 at ATPase, H + transporting, lysosomal 42kDa, VI subunit C, isoform 1 ATP6V1 C 1 0.4 0.6 0.667 0.03159

203371 s at NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 3, 12kDa NDUFB3 0.7 0.8 0.875 0.01089

203478 at NADH dehydrogenase (ubiquinone) 1, subcomplex unknown, 1, 6kDa NDUFC1 0.9 1.1 0.818 0.00143

203621 at NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 5, 16kDa NDUFB5 0.7 0-8 0.875 0.00124

203663 s at cytochrome c oxidase subunit Va COX5A 0.9 1.2 0.75 0.00015

COX10 homolog, cytochrome c oxidase assembly protein, heme A:

203858 s at COX10 1 1.2 0.833 0.00303 farnesyltransferase (yeast)

204125 at NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, assembly factor 1 NDUFAF1 0.5 0.6 0.833 0.03243

'Probe' set in diabetics

value

(Aff. ID) Gene name Gene symbol Gene expression intensity of gene expression intensity

Geometric mean (X) geometric mean (Y)

205512:; programmed cell death 8 (apoptosis-inducing factor) PDCD8 0.7 1 0.7 0.00147

ATP synthase, H + transporting, mitochondrial r l complex, gamma

20571 1) <at ATP5C 1 0.8 1.1 0.727 0.00079 polypeptide 1

ATP synthase, H + transporting, mitochondrial FO complex, subunit c (subunit

207507 ί; at

9 ATP5G3 0.9 1.1 0.818 0.00062) isoform 3

ATP synthase, H + transporting, mitochondrial F0 complex, subunit c (subunit

207552 at ATP5G2 0.8 1 0.8 0.00744

9) .isoform 2

208898 at ATPase, H + transporting, lysosomal 34kDa, VI subunit D ATP6V1 D 0.6 0.8 0.75 0.00942

ATP synthase, H + transporting, mitochondrial FO complex, subunit c (subunit

208972 s at ATP5Q1 0.9 1.1 0.818 0.02651

9), isoform 1

ATP synthase, H + transporting, mitochondrial FO complex, subunit c (subunit

208972 s at ATP5G1 0.9 0.818 0.00038

9), isoform 1

208997 s at uncoupling protein 2 (mitochondrial, proton carrier) UCP2 0.8 0.8 0.00512

NADH dehydrogenase (ubiquinone) Fe-S protein 7, 20kDa (NADH-coenzyme

21 1752 s at Q reductase) /// NADH dehydrogenase (ubiquinone) Fe—S protein 7, 20kDa NDUFS7 0.8 0.8 0.04203

(NADH-coenzyme Q reductase)

ATP synthase, H + transporting, mitochondrial FO complex, subunit b, isoform

21 1755 s at 1 /// ATP synthase, H + transporting, mitochondrial F0 complex, subunit b, ATP5F1 0.8 0.8 0.00787 isoform 1

ATP synthase, H + transporting, mitochondrial l complex, O subunit

216954 x at ATP5Q 0.8 1 0.8 0.00388

(oligomycin sensitivity conferring protein)

217801 at ATP synthase, H + transporting, mitochondrial F1 complex, epsilon subunit ATP5E 1 1.2 0.833 0 00144 217848 s at pyrophosphatase (inorganic) PP 1 1.2 0.833 0.02099 218101 s at NADH dehydrogenase (ubiquinone) 1, subcomplex unknown, 2, 14.5kDa NDUFC2 0.9 1 0.9 0.01263 218160 at NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 8, 19kDa NDUFA8 0.7 0.9 0.778 0.00077 218190 s at ubiquino cytochrome c reductase complex (7.2 kD) UCRC 0.8 1.1 0.727 0.0001 1 218200 s at NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 2, 8kDa NDUFB2 0.9 1.1 0.818 0.00043 218226 s at NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 4, 15kDa NDUFB4 0.9 1.2 0.75 0.00101 218226 s at NADH dehydrogenase (ubiquinone) 1 eta subcomplex, 4, 15kDa NDUFB4 1.1 1.3 0.846 0.0072 220741 s at inorganic pyrophosphatase 2 PPA2 0.7 1 0.7 0.00456 224474 x at KIAA1387 protein /// KIAA1387 protein KIAA1 387 0.8 0.9 0.889 0.0372

Example 8

[0188] Analysis of expression dynamics of MAPK and OXPHOS genes

In order to clarify the expression kinetics of genes belonging to these pathways, BRB—Array Tool software was used to determine the MAPK gene group (82 genes) and OXPHOS gene group (70 genes) for each gene in each sample. Scores (MAPK mean Centroid) for each case (MAPK mean Centroid) for each case (diabetic, healthy, pre-treatment and post-treatment diabetic) OXPHOS mean centroid) was determined.

[0189] However, for the actual measurement !, 99 kinds of MAPK gene group and 77 kinds of oligonucleotide probe were used for OXPHOS gene group. More specifically, for the MAPK gene group, Aff. ID Nos. 209951—s-at, 209341—s—at, 1570439—at, 203514—at, 202670—at, 203218—at, 202530 — At, 2150 75— s— at, 208403— x—at, 1558984— at, 204813— at, 206943— at, 156 7457 one at and 1553685 one s one ati trick (two each, Aff. Since there were 4 oligonucleotides (antisense strands corresponding to a part of these genes) for ID No. 15592 95—at, 99 data were obtained, while the OXPHOS gene group was measured. ID Nos. 218190_s_at, 201304 1 at, 205849 — s— at, 218563— at, 201093— x—at, 218226— s— at and 208972— s— at 2 each! Since there were seed oligonucleotides (antisense strands corresponding to some of these genes), 77 data were obtained, It was used.

[0190] The results are shown in FIG.

[0191] As is apparent from FIG. 7, the MAPK average centroid was improved by the force blood glucose control, which showed a significantly higher value in the diabetic group than in the healthy group. On the other hand, OXPHOS mean centroid was significantly lower in the diabetic group than in the healthy group, and this condition was not changed by blood glucose control.

Example 9

[0192] Relationship between the expression dynamics of MAPK and OXPHOS genes and the pathology of diabetes The MAPK average centroid for each specimen used in the calculation of the MAPK average centroid for each case in Example 8, the pathology of diabetes (obesity (BMI value), fasting blood glucose level (fasting plasma glucose)), and glycohemoglobin level ) Was determined by Pyason's r.

[0193] In addition, the OXPHOS average centroid for each specimen used in Example 8 to calculate the OXPHOS average centroid, and the pathology of diabetes (obesity (BMI value), fasting blood glucose level (fasting plasma) The presence or absence of correlation with glucose) and glycohemoglobin amount was determined by Pyason's r.

[0194] The results are shown in Table 12. Fig. 8 shows a graph plotting MAPK average centroid for each sample and blood daricohemoglobin (HbAlc) (%), and Fig. 9 shows OXP HOS average centroid for each sample and blood. A graph plotting the amount (%) of glycated hemoglobin (HbAlc) is shown.

As is clear from Table 12, FIG. 8, and FIG. 9, the MAPK average centroid showed a significant positive correlation with fasting blood glucose level and glycated hemoglobin level. On the other hand, OXPHOS mean centroids were not associated with any data indicating diabetes status.

[0196] [Table 12]

5 SS¾ 雜 () ¾ i 屮 ¾ 屮 ^ έ ^ ≤≤7∞ MAP ^: Relationship between clinical parameters of diabetes and mean centroid of expression level of MAPK gene or OXPHOS gene i01 BMI value Fasting blood glucose -Glycohemoglobin

MAPK average centroid Pearson's r 0.074 0.362 0.384

P value 0.535 0.0003 0.0004

OXPHOS Average Centroid Pearson's -0.157 -0.137 0.127

P value 0.184 0.184 0.257

There was a significant difference in the expression level between diabetics and healthy subjects, and there was also a significant difference before and after treatment. On the other hand, the expression level of the OXPHOS gene group (70 genes) shown in Table 8 was significantly different between diabetic patients and healthy subjects as a whole. Therefore, we examined whether the same significant difference was observed even when expression profiles were obtained using fewer types of genes.

[0198] (1 1) Among the MAPK gene groups listed in Table 9, 10 genes with low p-values were selected, and using the gene expression levels measured in Example 1, diabetic patients (57 samples) and healthy subjects The expression levels of those 10 genes in (16 samples) can be calculated using various algorithms (compound covaria te predictor ^ mejkakusen Izumi additional ¹ J; ndiagonal linear discriminant analysis) ^ nearest neighbor ( 1—nearest neighbors, 3—nearest neighbors, nearest centroid, support vector machines (support vector machines) It was divided into a group and a group of healthy subjects. The results were compared with the actual situation (whether diabetic patient or healthy person) to obtain the correct answer rate. The results are shown in Table 13.

[0199] As is apparent from Table 13, classification, that is, diagnosis could be performed with a high probability of 81% or higher.

[0200] (1 2) From the MAPK gene group listed in Table 10, 10 genes with low p-values were selected, and the gene expression levels measured in Example 1 were used to examine the pre- and post-treatment in diabetic patients. body the expression level of these 10 genes in (27 samples), various algorithms (complex covariant prediction Compound covariate predictor T angle 'fe shaped semi ¹ J另¹ J analysis (diagonal linear discrimi nant analysis) 1- nearest neighbor (1 —Nearest neighbor) ^ 3—Statistical processing using nearest neighbors, nearest centroid, support vector machines), and 2 specimens (before treatment started) Group and group after treatment). The results were compared with the actual situation (whether it was before treatment started or after treatment started), and the correct answer rate was obtained. The results are shown in Table 14.

[0201] As is clear from Table 14, classification was possible with a high probability of 77% or more.

[0202] (1 3) From the OXPHOS gene group listed in Table 11, 10 genes with low p-values were selected, and using the gene expression levels measured in Example 1, diabetic patients (57 samples) and healthy subjects The expression levels of those 10 genes in (16 specimens) were calculated using various algorithms (compound covariance prediction (compound c ovariate predictor) diagonal linear discriminant analysis, 1—nearest neighbors ^ 3—nearest neighbors ^ nearest centroid, support Statistical processing was performed by 'vector' machines (support v ector machines), and the samples were divided into two groups (diabetes group and healthy group). The correctness rate was calculated by comparing the results with the actual situation (whether it is diabetic or healthy). The results are shown in Table 15.

[0203] As is clear from Table 15, classification, that is, diagnosis could be performed with a high probability of 77% or more.

[0204] [Table 13]

1 Cross-validation between diabetics and healthy individuals using 10 MAPK genes Compound covariance prediction Diagonal linear discriminant analysis 1 -Nearest neighbor method 3-Nearest neighbor method Nearest centroid Sabo ^ Number correctly classified

Diabetes Number of 57 samples 53 54 56 57

Healthy subjects 1 Number in 6 samples 14 1 4 1 5 14

Misclassified number

Diabetes Number in 57 samples 4 3 1 0

Number of healthy subjects in 16 samples 2 2 1 2

Probability of classification correctly (%) 81 82 88 84

[0205] [Table 14]

Cross-validation before and after treatment of diabetes

Complex Covariant Prediction Diagonal Linear Discriminant Analysis 1-Nearest Neighbor Method 3-Nearest Neighbor Method

Number correctly classified 26 26 26 26 26 26 Number incorrectly classified 1 1 1 1 1 1 Probability of correctly classified (%) 79 85 83 88 77 90

Cross-validation between diabetics and healthy individuals using 10 OXPHOS genes

Compound Covariant Prediction Diagonal Linear Discriminant Analysis l-isiife Method 3-Nearest Neighbor Method Nearest Centroid Support: _ ^ Q ^ — ■ Probability of correctly classified

S star D5S [0207] (2) 37 genes were selected from the gene group belonging to the MAP kinase pathway, and the expression level was measured by the method described in Example 1 for diabetic patients (57 samples) and healthy subjects (16 samples). I went. Figure 10 shows the results of scanning the slide (micro chip) with Scan Array Express (Perkin-Elmer). In addition, 40 genes were selected from the gene group belonging to the MAP kinase pathway, and the expression level of the same patient after treatment (24 specimens) before treatment (24 specimens) of diabetic patients (24 specimens) was determined by the method described in Example 1. Measurements were made. The results of scanning the slide (microchip) with Scan Array Express (Perkin—Elmer) are shown in Fig. 11. Further, 49 genes were selected from the gene group belonging to the mitochondrial OXPHOS pathway, and the expression level was measured by the method described in Example 1 for diabetic patients (57 samples) and healthy subjects (16 samples). The results of scanning the slide (micro 'chip) with Scan Array Express (Perkin-Elmer) are shown in Fig. 12 as numerical values.

In both FIG. 10 and FIG. 12, it was found that there was a difference in the expression profiles of the measured gene groups between diabetic patients (DM) and healthy individuals (nonDM).

[0209] From Fig. 11, it can be seen that there is a difference in the expression profile of the measured gene group between the pre-treatment sample and the post-treatment sample of a diabetic patient, and the gene expression profile after treatment is typical for diabetes. It was found that it was a departure from the proper expression profile.

[0210] As described above, the expression of 37 genes shown in FIG. 10 derived from the leukocyte RNA of the test subject was measured with a mouthpiece'chip and imaged, and the data was compared with FIG. Can determine whether or not he is diabetic or his reserve.

[0211] In addition, the expression of 49 genes shown in Fig. 12 derived from the leukocyte RNA of the subject was measured with a microphone'chip and the imaged data was compared with Fig. 12, so that the subject It can be determined whether or not it is the reserve army.

[0212] In addition, the expression of 40 genes shown in Fig. 11 derived from leukocyte RNA before and after the start of treatment of diabetic patients was measured with a microchip and imaged data was compared with Fig. 11. It can be determined whether or not a therapeutic effect has been achieved.

Example 11

[0213] Measurement of gene expression level in samples with unknown diabetes and determination of results

(1) Use of MAPK genes In the method described in Example 1, two types of MAPK genes derived from leukocyte RNA of one test subject 8 (listed in Table 7; provided, however, as described in Example 8, there are 99 types of measurement data) ) Gene expression level was measured. Next, using the data in Example 8, the expression level of each gene in this subject was standardized. Using the normalized data, the MAPK average centroid of this subject was calculated to be 0.176. Therefore, this subject was determined to have diabetes. This decision was correct.

[0214] (2) Use of OXPHOS gene

In the method described in Example 1, 70 OXPHOS genes derived from leukocytes of the same subject as in (1) above (listed in Table 8; provided that, as described in Example 8, 77 types of measurement data were obtained. ) Was measured. Next, using the data in Example 8, the expression level of each gene in this subject was standardized. Using the standardized data, the OXPHOS mean centroid for this subject was calculated to be -0.507. Therefore, this subject was determined to be diabetic. This decision was correct.

Example 12

[0215] Measurement of gene expression level in specimens for which it is unknown whether blood glucose control is effective or not, and determination of the results

After subjecting the subject measured in Example 11 (1) to the treatment for controlling blood glucose, the MAPK average centroid was calculated in the same manner. The result was -0.361. From this data, it was determined that this subject had a therapeutic effect. Actually, clinical parameters such as blood glucose levels also confirmed that diabetes was relieving.

Claims

Claims A method for determining whether or not subject X is a diabetic patient or a reserve army, and (a) obtaining an expression profile X of a specific gene or gene group in human leukocytes derived from subject X (B) The expression profile X obtained in step (a) is the same specific gene or gene as in step (a) in the gene group or equivalent thereof in human leukocytes derived from non-diabetic subject y. (C) In step (b), if expression profile X is significantly different from expression profile y, subject X is diabetic or A step of determining that it is military, wherein the specific gene or gene group is included in the following gene groups (A-1) to (A-50)! / Method:

(A— 1) Virtual protein LOC54103 (registration number: AL079277)

(A-2) Leucine-rich repeating neuron unit 3 (registration number: AB060967)

(A-5) Glycosyltransferase AD -017 (registration number: NM—018446)

(A-6) Redoxin peroxide 3 (registration number: NM—006793)

(Α-8) Signal peptidase 12 kilodalton (registration number: ENSG00000114902)

(Α-9) Octamer-binding non-POU domain (registration number: L32558)

(Α-10) ΝΡ220 nuclear protein (registration number: AF273049)

(Α—11) Virtual protein FLJ 10652 (registration number: NM—018169)

(A—12) Chromosome 14 open reading frame 109 (registration number: AL0801

18)

(A-13) Apoptosis-related protein 3 (Registration number: NM— 004632)

(A—14) AUT-like 1 cysteine endopeptidase (S. cerevisiae) (registration number: ENS G00000125703)

(A-15) Recombinant protein REC14 (registration number: AF309553)

(A-16) esterase D / formylglutathione hydrolase (registration number: AF11221)

9)

(A-17) Transmembrane protein 14B (registration number: NM—030969)

(A— 18) Myc-related protein (registration number: AF083244)

(A—20) B cell linker (¾ 參号: ENSG00000095585)

(A—21) Lymphocyte antigen 86 (registration number: NM— 004271)

(A-23) Presumed membrane protein (registration number: AF070626)

(A-24) Cellular repressor of gene induced by E1A (registration number: NM—003851)

(A-25) Exportin 1 (CRM1 homolog, yeast) (registration number: NM_003400)

(A—26) Glutamylprolyl tRNA synthetase (registration number: NM_004446)

(A—27) Sorting nexin 13 (registration number: AL353943)

(A— 28) Virtual DKFZp451 J 1719 (registration number: AF 116608)

(A- 29) ACN9 homolog (S. cerevisiae) (registration number: AF201933)

(A-30) Anaplastic lymphoma kinase (Ki-l) (Registration number: D45915)

(A—31) Centrosome protein 1 (registration number: NM—007018)

(A—32) Rigatine (registration number: AF220417)

(A—34) Intramembrane protein, mitochondrial (mitophylline) (registration number: NM—006839) (A—35) protein tyrosine phosphatase, non-receptor type 12 (registration number: NM— 0 02835)

(A- 36) Pyruvate dehydrogenase (lipoamide) β (registration number: Μ34479)

(A—37) unc—50 homologue (C. elegans) (registration number: AF077038) (A—38) Virtual protein FLJ20003 (registration number: NM—017615)

(A—39) Virtual protein KIAA1109 (registration number: AB029032)

(A-40) Tabi Uniform Protein 3 (Registration Number: NM—003324)

(A— 41) Bispecific phosphatase 5 (registration number: NM— 004419)

ΝΜ— 020529)

twenty three)

(A—48) Ring finger protein 121 (registration number: NM—018320)

(A-50) Serum / Glucocorticoid-regulated kinase (registration number: NM—00562

7).

A method for determining whether subject X is a diabetic patient or a reserve thereof,

Wherein the specific gene or group of genes is included in a group of genes belonging to the MAP kinase 'signaling' pathway and the P38 MAPK signaling 'pathway! The method according to claim 2, wherein the gene groups belonging to the MAP kinase signaling 'pathway' and the p38 MAPK signaling 'pathway are included in the following 82 gene groups belonging to these pathways in BRB—ArrayTools (registered trademark):

Aff. ID Nos. 209666— s—at, 1554319— at, 209341— s—at, 1552631 — a— at, 1570439— at, 211459— at, 1559295— at, 206106— at, 203096 — s— at, 209951 — S—at, 203514—at, 1570076—at, 205027—s—at, 202 424—at, 202670—at, 203218—at, 203084—at, 202530—at, 201763—s—at, 201895—at, 1555146—at, 215075—s—at, 201464—x—at, 2084 03—x—at, 1558984—at, 206362—x—at, 202431—s—at, 1565772—at, 1559052—s—at, 1552263 — At, 207121— s—at, 207292— s—at, 21047 7— x— at, 206040— s—at, 204813— at, 210058— at, 207667— s—at, 20 4756— at, 205698— s —At, 1557675—at, 203379—at, 1556340—at, 20 3265—s—at, 201469—s—at, 204171—at, 206853—s—at, 218311—at, 212871—at, 1560720—at, 1729—at, 204632—at, 203777—s—at, 205 192—at, 209239—at, 20604 4—s—at, 204039—at, 213926—s—at, 204 936—at, 206943—at, 1560868—s—at, 203617—x—at, 209189—at, 21 2983—at, 208328—s— at, 203836—s—at, 203552—at, 1565130—at, 1 567457—at, 206296— x—at, 200887—s—at, 203097—s—at, 218205—s—at, 218181—s—at , 201502—s—at, 1557970—s—at, 204413—at, 20 1460—at, 212046—x—at, 202787—s—at, 204707—s—at, 214786—at and 1553685—s—at.

The gene group belonging to the MAP kinase.signaling 'pathway and p38MAPK signaling' pathway is included in the following gene groups (B-1) to (B-31) belonging to these pathways in MAPPFinder: the method of:

(B-2) Ribosomal protein S6 kinase, 90 kilodalton, polypeptide 2 (registration number: Aff. ID 1557970 s at) (B 3) Mitogen-activated protein kinase kinase kinase 2 (registration number: Aff. ID 1565130—at)

(B-4) Mitogen-activated protein kinase Activated protein kinase 2 (Registration number: Aff. ID 201460—at)

(B— 8) Rap guanine nucleotide exchange factor (GEF) 2 (registration number: Aff. ID 203096 s at;

(B- lO) ELKl, a member of the ETS oncogene family (registration number: Aff. ID 203617 ― X― at)

—At)

(B-17) Mitogen-activated protein kinase kinase kinase 10 (registration number: Aff

ID 206362— x— at)

(B-18) Mitogen-activated protein kinase 6 (registration number: Aff. ID 207121— s —at)

(B-19) Mitogen-activated protein kinase kinase 3 (registration number: Aff. ID 207 6D7-s-at)

(B—31) Nerve growth factor, / 3 polypeptide (registration number: Aff. ID 206814—at). A method for determining whether subject x is a diabetic patient or a reserve thereof,

(a) obtaining an expression profile X of a specific gene or group of genes in human leukocytes derived from subject X; (b) The same specific gene or gene as in step (a) in the gene group or equivalent thereof in human leukocytes derived from non-diabetic subject y is expressed profile x obtained in step (a). Comparing to the expression profile y!

Wherein the specific gene or gene group is included in a gene group belonging to a ubiquinone biosynthesis system and an ATP synthesis system.

The method according to claim 5, wherein the gene group belonging to the ubiquinone biosynthesis system and the ATP synthesis system is included in the following 70 gene groups belonging to these pathways in BRB-ArrayTools (registered trademark):

ID Nos. 207335—x—at, 218200—s—at, 201966—at, 218160—at, 203606—at, 206790—s—at, 201754—at, 201134—x—at, 218190—s—at , 218484— at, 217963— s—at, 202839— s—at, 201304— at, 20209 0— s— at, 201568— at, 205849— s—at, 218563— at, 202026— at, 20109

3—x—at, 211752—s—at, 200883—at, 203663—s—at, 202233—s—at, 203858—s—at, 202325—s—at, 201322—at, 203926—x—at, 211755—s—at, 207507—s—at, 202343—x—at, 204570—at, 201597—at, 20211

0— at, 207843— x—at, 201066— at, 217773— s—at, 202000— at, 20337

1— s— at, 203621— at, 203478— at, 203189— s—at, 202675— at, 20200

4—x—at, 204295—at, 201903—at, 201119—s—at, 207618—s—at, 20 0925—at, 203551—s—at, 219547—at, 202298—at, 218226—s—at , 21 8 dishes— s— at, 201740— at, 201757— at, 204300— at, 201256— at, 2089 69— at, 202077— at, 201226— at, 205711— x one at, 207552— at, 206353 — at, 208909—at, 217801—at, 220864—s—at, 205224—at, 208905—at, 207573—x—at and 208972—s—at.

The method according to claim 5, wherein the genes belonging to the ubiquinone biosynthesis system and the ATP synthesis system are included in the following gene groups (C-1) to (C-42) belonging to these pathways in MAPPFinder: (C l) Inorganic pyrophosphatase 2 (registration number: Aff. ID 1554499— s— at)

(C 2) NADH dehydrogenase (ubiquinone) Fe-S protein 4, 18 kilodalton (

NADH Coenzyme Q reductase) (Registration number: Aff. ID 1555057—at)

(C 5) BCL2 1 (Registration number: Aff. ID 1569067—at)

(C—7) ATP synthase, hydrogen transport, mitochondrial F1 complex, α subunit, isoform 1, myocardium (oligomycin sensitizing protein) (registration number: Aff. ID 156989 1—at)

(C—8) ATPase, hydrogen transport, lysosome 9 kilodalton, V0 subunit e /// A TPase, hydrogen transport, lysosome 9 kilodalton, V0 subunit e (registration number: Aff. ID 200096—s— at)

(C11) Cytochrome coxidase subunit Via polypeptide 1 (registration number: Aff ID 200925—at)

(C-12) Cytochrome coxidase subunit VIIc (registration number: Aff. ID 201134 ― X― at)

(C 14) NADH dehydrogenase (ubiquinone) Fe-S protein 2, 49 kilodalton (NADH coenzyme Q reductase) (registration number: Aff. ID 201966 at) (C—15) ubiquinol-cytochrome c reductase hinge protein (registration number: Aff. ID 202233—s—at)

(C—17) ATPase, hydrogen transport, lysosome 42 kilodalton, VI subunit C, isoform 1 (registration number: Aff. ID 202872_at)

(C—21) cytochrome coxidase subunit Va (registration number: Aff. ID 203663 one s one at)

(C—22) COX10 homolog, cytochrome coxidase assembly protein, hem A: farnesyltransferase (yeast) (registration number: Aff. ID 203858_s_at) (C 23) NADH dehydrogenase (ubiquinone) 1 α subcomplex, assembly One factor 1 (registration number: Aff. ID 204125—at)

(C—28) ATPase, hydrogen transport, lysosome 34 kilodalton, VI subunit D (registration number: Aff. ID 208898 at) (C—29) ATP synthase, hydrogen transport, mitochondrial F0 complex, subunit c (subunit 9) isoform 1 (registration number: Aff. ID 208972—s—at)

(C-31) NADH dehydrogenase (ubiquinone) Fe-S protein 7,20 kilodalton (one S protein 7,20 kilodalton (NADH coenzyme Q reductase) (registration number: A ff. ID 21 1752—s one at)

(C-32) ATP synthase, hydrogen transport, mitochondrial F0 complex, subunit b, isoform 1 /// ATP synthase, hydrogen transport, mitochondrial F0 complex, subunit b, isoform 1 (registration number: Aff. ID 21 1755—s—at)

(C-33) ATP synthase, hydrogen transport, mitochondrial F1 complex, O subunit (oligomycin sensitization protein) (registration number: Aff. ID 216954—x—at)

(C-34) ATP synthase, hydrogen transport, mitochondrial F1 complex, ε subunit (registration number: Aff. ID 217801—at)

(C—35) Pyrophosphatase (inorganic) (registration number: Aff. ID 217848_s_at)

(C-36) NADH dehydrogenase (ubiquinone) 1, subcomplex unknown, 2, 14.5 kilodalton (registration number: Aff. ID 218101_s_at)

(C—38) ubiquinol-cytochrome c reductase complex (7.2 kilodaltons) (registration number: Aff. ID 218 190—s—at)

(C-39) NADH dehydrogenase (ubiquinone) 1, 3 subcomplex, 2, 8 kilodalton (registration number: Aff. ID 218200_s_at)

(C—40) NADH dehydrogenase (ubiquinone) 1, 3 subcomplex, 4, 15 kilodalton (registration number: Aff. ID 218226—s—at)

(C-41) Inorganic pyrophosphatase 2 (registration number: Aff. ID 220741—s—at) and (C—42) KIAA1387 protein /// KIAA1387 protein (registration number: Aff. I D 224474—x—at).

A method for determining the presence or absence of therapeutic effects in patients with type 2 diabetes,

Wherein the specific gene or gene group includes the following (D-1) to (D—

A method characterized in that it is included in the gene group of 50)!

(D—1) Fork head box P1 (registration number: NM—016477)

(D-2) CD24 antigen (small cell lung cancer cluster 4 antigen) (registration number: NM_013230)

(D-3) Ribosomal protein L29 (registration number: NM—000992)

(D-7) Neurotensin receptor 1 (high affinity) (registration number: NM—002531)

(D—8) integral membrane protein 2A (registration number: NM—004867)

(D-10) Esterase 2A (registration number: NM— 033440)

(D-12) Endosulfin α (Registration number: ΝΜ 004436) (D-13) CD226 antigen (registration number: NM-006566)

(D—14) Transient receptor potential cation channel, subfamily V, member 4 (registration number: NM— 021625)

(D—15) ADP—ribosylation factor interacting protein 2 (erfaptin 2) (registration number: NM—012402)

(D-16) Bradykinin receptor B2 (registration number: NM—000623)

(D-17) Ribosomal protein S3 (registration number: NM—001005)

(D-18) Contactin-related protein-like 2 (Registration number: NM—014141)

(D-19) Myosin, photopolypeptide kinase (registration number: NM-005965)

(D-20) Dipeptidase 1 (Nenseisei) (Registration number: NM_004413)

(D—22) Chemokine (C—C motif) ligand 5 (registration number: NM—002985)

(D-23) 1-acylglycerol 1-phosphate O-acyltransferase 1

(Lysophosphatidic acid acyltransferase α) (registration number: NM— 032741)

(D—24) zinc finger protein, subfamily 1A, 4 (Eos) (registration number: NM—

022465)

(D-25) Benzodiazepine receptor (Ambient) (registration number: NM_000714)

(D—26) KIAA0174 gene product (registration number: NM—014761)

(D—27) Mortality factor 4 like 2 (Registration number: NM— 012286)

(D—33) High mobility group nucleosome binding domain 1 (registration number: ΝΜ 004965) (D-34) Cyclin Tl (registration number: NM—001240)

(D-37) Inhibitor of DNA binding 2, dominant negative helix loop helix protein (registration number: NM_002166)

(D—41) zinc finger protein 160 (registration number: X78928)

(D-42) Phospholinose A2, X group (registration number: ENSG00000069764)

(D—43) Virtual tank FLJ23120 (registration number: AK026773)

(D—44) Phosphoinositide 1-3 kinase, class 2, γ polypeptide (registration number: AJ

000008)

(D-45) Virtual protein IMAGE: 4215339 (registration number: AC005328)

(D—46) Cathebsin E (registration number: AJ250716)

(D—47) Chemokine (C motif) receptor 1 (registration number: NM—005283)

(D—48) Cell Dedigator 9 (Registration Issue: ENSG00000088387)

(D-49) Ring finger protein 39 (registration number: AF238317) and

(D—50) Chromosome 17 Open Reading Frame 28 (Registration Number: AL137556)

(B) comparing the expression profile of the gene or gene group before the start of treatment measured in step (A) with the expression profile of the gene or gene group after the start of treatment; and (c) The expression profile of the specific gene or gene group after the start of treatment is significantly different from the expression profile of the specific gene or gene group before the start of treatment, and the characteristics of the expression profile indicating diabetes are lost or The process of determining that there is a therapeutic effect when it is reduced

Wherein the specific gene or gene group is included in a gene group belonging to the MAP kinase 'signaling' pathway and the p38 MAPK signaling 'pathway! /

10. The method according to claim 9, wherein the genes belonging to the MAP kinase signaling “pathway” and the p38 MAPK signaling “pathway” are included in the following 82 genes belonging to these pathways in BRB—ArrayTools (registered trademark):

Aff. ID Nos. 209666— s—at, 1554319— at, 209341— s—at, 1552631 — a— at, 1570439— at, 211459— at, 1559295— at, 206106— at, 203096 — s— at, 209951 — S—at, 203514—at, 1570076—at, 205027—s—at, 202 424—at, 202670—at, 203218—at, 203084—at, 202530—at, 201763—s—at, 201895—at, 1555146—at, 215075—s—at, 201464—x—at, 2084 03—x—at, 1558984—at, 206362—x—at, 202431—s—at, 1565772—at, 1559052—s—at, 1552263 — At, 207121— s—at, 207292— s—at, 21047 7— x— at, 206040— s—at, 204813— at, 210058— at, 207667— s—at, 20 4756— at, 205698— s —At, 1557675—at, 203379—at, 1556340—at, 20 3265—s—at, 201469—s—at, 204171—at, 206853—s—at, 218311—at, 212871—at, 1560720—at, 1729—at, 204632—at, 203777—s—at, 205 192—at, 209239—at, 20604 4—s—at, 204039—at, 213926—s—at, 204 936—at, 206943—at, 1560868—s—at, 203617—x—at, 209189—at, 21 2983—at, 208328—s— at, 203836—s—at, 203552—at, 1565130—at, 1 567457—at, 206296— x—at, 200887—s—at, 203097—s—at, 218205—s—at, 218181—s—at , 201502—s—at, 1557970—s—at, 204413—at, 20 1460 at, 212046 x at, 202787 s—at, 204707 s at, 214786 at and 1553685 s at, Gene groups belonging to the MAP kinase.signaling 'pathway and p38MAPK signaling' pathway are included in MAPPFinder! /, And the following (E-1) to (E-29) gene groups belonging to these pathways. The method of claim 9:

ID 1558984— at)

(E—4) TNFRSF1A related Viades domain (registration number: Aff. ID 1729—at)

(E-13) Mitogen-activated protein kinase kinase 4 (registration number: Aff. ID 203 265 s at) (E—14) Ribosomal protein S6 kinase, 90 kilodalton, polypeptide 1 (registration number: Aff. ID 203379— at)

(E—15) Mitogen-activated protein kinase kinase kinase 3 (registration number: Aff. ID 203514—at)

(E-28) DNA damage-induced transcription 3 (registration number: Aff. ID 209383 at) and — 29) Guayun nucleotide binding protein (G protein), q polypeptide (registration number Aff. ID 202615 at).