EP1789798A4 - Marqueurs pour la détection de maladies auto-immunes - Google Patents

Marqueurs pour la détection de maladies auto-immunes

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Publication number
EP1789798A4
EP1789798A4 EP05786543A EP05786543A EP1789798A4 EP 1789798 A4 EP1789798 A4 EP 1789798A4 EP 05786543 A EP05786543 A EP 05786543A EP 05786543 A EP05786543 A EP 05786543A EP 1789798 A4 EP1789798 A4 EP 1789798A4
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EP
European Patent Office
Prior art keywords
genes
lupus
score score
score
patients
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EP05786543A
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German (de)
English (en)
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EP1789798A2 (fr
Inventor
Debra A Barnes
Adam Dempsey
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XCEED MOLECULAR Corp
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XCEED MOLECULAR CORP
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Publication of EP1789798A2 publication Critical patent/EP1789798A2/fr
Publication of EP1789798A4 publication Critical patent/EP1789798A4/fr
Withdrawn legal-status Critical Current

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/564—Immunoassay; Biospecific binding assay; Materials therefor for pre-existing immune complex or autoimmune disease, i.e. systemic lupus erythematosus, rheumatoid arthritis, multiple sclerosis, rheumatoid factors or complement components C1-C9
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/136—Screening for pharmacological compounds
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/10—Musculoskeletal or connective tissue disorders
    • G01N2800/101—Diffuse connective tissue disease, e.g. Sjögren, Wegener's granulomatosis
    • G01N2800/104—Lupus erythematosus [SLE]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/32—Cardiovascular disorders
    • G01N2800/328—Vasculitis, i.e. inflammation of blood vessels
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Definitions

  • the present invention relates to newly identified gene sets and their expression patterns and uses of the expression patterns in screening for and classifying autoimmune diseases.
  • systemic lupus erythematosus is known as a chronic, inflammatory autoimmune disease characterized by dysregulation of the immune system resulting in the production of antinuclear antibodies, the generation of circulating immune complexes, and the activation of the complement system.
  • the immune complexes build up in the tissues and joints causing inflammation, and degradation to both joints and tissues.
  • the body's immune system normally makes proteins called antibodies to protect the body against viruses, bacteria and other foreign materials (collectively referred to as antigens).
  • an autoimmune disorder such as SLE
  • the immune system loses its ability to tell the difference between foreign or non-self antigens and its own cells and tissues.
  • the immune system then makes antibodies directed against itself.
  • These antibodies called “auto-antibodies,” react with the "self autoantigens” to form immune complexes, which build up in the tissues, causing inflammation, injury to tissues, and pain.
  • Hargraves' discovery has enabled physicians to identify many more cases of SLE by using a simple blood test. The test is only positive, however, in about half of SLE patients and is no longer used routinely. Since 1954, the various unusual antibodies found to be associated with SLE have been used to study the disease. The above difficulty in identifying the disease, and those afflicted with it, has led to an effort to use the presence of these antibodies as a tool to diagnose the disease. However, the presence of these antibodies may be the result of factors other than SLE, and to date no single autoantibody has been found to be universal to all individuals with SLE.
  • U.S. Patent No. 6,177,254 to Rattner et al. discloses a nucleolus protein, named ASE-I, that has been found to be a reliable serum marker for SLE in 22% of patients.
  • the screening can be done using an ELISA assay, western blot techniques, or by binding the antigen to microspheres and identifying reactive sera by flow cytometry.
  • ASE-I has a molecular weight of about 55kDa and localizes to the nucleolus organizer regions of the chromosome during cell division.
  • U.S. Patent No. 6,280,941 to Tsao et al. discloses a genetic testing method for diagnosing SLE.
  • the method is related to amplifying nucleic acids from human tissue samples and analyzing for a variant allele of a gene encoding poly(ADP- ribosyl)transferase expression (PARP), which is diagnostic of SLE or indicates a genetic predisposition for developing SLE.
  • PARP poly(ADP- ribosyl)transferase expression
  • Also disclosed are useful oligonucleotide primers, primer sets and genetic testing kits for detecting a genetic predisposition for developing SLE.
  • U.S. Patent Application Publication No. 2004/0033498 to Behrens et al. discloses methods and materials involved in diagnosing SLE, diagnosing severe SLE, and assessing a mammal's susceptibility to develop severe SLE.
  • the application provides nucleic acid arrays that can be used to diagnose SLE but only in comparison with healthy individuals. Behrens does not distinguish or diagnose SLE specifically in comparison with other autoimmune diseases because such patient populations were not examined.
  • the application discloses a set of genes that are differentially expressed between SLE patients and healthy individuals. Further, the application discloses a set of fourteen genes that mark a predisposition to develop severe SLE or SLE-AIP (SLE accompanied by the activation of an interferon pathway).
  • This application also provides data from gene expression analysis of only isolated from peripheral blood mononuclear cells. The sample material of only one cell type may critically skew the expression level analysis.
  • the invention also provides methods for screening patients for SLE and WG.
  • the invention provides a method for differential diagnosis of SLE from other autoimmune diseases. The method can also be used to determine the severety of the disease.
  • the invention provides methods of classifying SLE and WG based on specific gene expression signatures or expression profiles using the discovered genes.
  • disease activity of WG and SLE has been measured either by the Birmingham Vasculitis Activity Score (BVAS) (Luqmani RA, Bacon, PA, Moots RJ, Janssen BA, Pall A, Emery P, Savage C, Adu, D. Birmingham Vasculitis Activity Score (BVAS) in systemic necrotizing vasculitis, QJM 1994;87(ll):671-8) for WG patients or SLE Disease Activity Index (SLEDAI) (Bombardier C, Gladman DD, Urowitz MB, Caron D, Chang CH.
  • BVAS Birmingham Vasculitis Activity Score
  • SLEDAI SLE Disease Activity Index
  • the present invention is based upon the discovery that expression of a defined set of genes is changed in biological samples from patients affected with different autoimmune diseases as compared to non-autoimmune diseases and even other autoimmune disease, such as SLE, WG, and RA and that detection of the expression profile of these genes provides a tool to screen for, diagnose, and also classify the disease activity of these autoimmune diseases.
  • the group of 1645 genes is set forth in Table 6.
  • the probe ID numbers in column 1 are from the June 2005 annotated Affymetrix Ul 33 +2 Gene Set.
  • the “scores” presented in columns 4-7 refer to a difference from an "average score” (centroid score) of all the measured samples in the four phenotype group (all-sample score), including healthy, SLE, RA, and WG samples, that was set to 0.
  • the difference towards positive from 0 score indicates that the expression of the corresponding gene is increased in the group when compared to the all- sample "average”.
  • the difference towards negative from 0 score indicates that the expression of the corresponding gene is decreased when compared to all-sample "average.” Accordingly, a gene that gives a well varied score for all the four groups is indicative of a gene useful in differentiating these four phenotypes based on the gene's expression profile.
  • Columns 8 and 9 in Table 6, represent scores differentiating SLE samples from average of all other samples (non-SLE samples). Accordingly, a difference in the score between SLE and "other 3" of about 0.1 or greater, alternatively about 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0 or even greater, is indicative of that gene being a good marker in differentiating between SLE and non-SLE samples. Accordingly a skilled artisan can easily select a smaller gene set for diagnostic and/or screening purposes.
  • Columns 10 and 11 in Table 6, represent scores differentiating SLE samples from WG samples. Accordingly, a difference in the score between SLE and WG samples of about 0.1 or greater, alternatively about 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0 or even greater, is indicative of that gene being a good marker in differentiating between SLE and WG samples.
  • the disease-specific gene expression signatures of the present invention provide substantially improved diagnostic power as compared to other methods that have been used in an attempt to diagnose autoimmune diseases such as SLE and WG.
  • the invention also provides a gene transcript groups the expression of which can differentiate between SLE and other autoimmune diseases such as rheumatoid arthritis (RA) and WG. Accordingly, we have identified a master gene set and several gene sub-sets that allow creation of diagnostic tools, such as diagnostic kits, diagnostic bead sets and diagnostic nucleic acid arrays, for autoimmune diseases.
  • diagnostic tools such as diagnostic kits, diagnostic bead sets and diagnostic nucleic acid arrays
  • a cut-off score difference between the expression of gene in one group such as SLE, see e.g. col 8, Table 6) and another group (such as the average or centroid score measured in a sample group consisting of healthy, WG and RA samples, see e.g. col.
  • Table 6 of about 0.1 or over, 0.2 or over, 0.3 or over, 0.4 or over, 0.5 or over, 0.6 or over, 0.7 or over, 0.8 or over, 0.9 or over, 1.0 or over, 1.1 or over, 1.2 or over, 1.3 or over, 1.4 or over, 1.5 or over, 1.6 or over, 1.7 or over, 1.8 or over, 1.9 or over, 2.0 or over as presented in Table 6 can be used to select a smalle sub-group of genes that can differentiate between samples from individuals with an autoimmune disease phenotype and samples between individuals with non-autoimmune disease phenotypes (normal, or control or healthy samples).
  • Transcription profile of fewer than 1645 preferably fewer than about 279, alternatively fewer than about 279-200, alternatively fewer than about 200-150, alternatively fewer than about 150-125, alternatively fewer than about 125-100, alternatively fewer than about 100-90, alternatively fewer than about 90-80, alternatively fewer than about 80-70, alternatively fewer than about 70-60, alternatively fewer than about 60-50, alternatively fewer than about 50-40, alternatively fewer than about 40-30, alternatively fewer than about 30-25, alternatively fewer than about 25-20, alternatively fewer than about 20-15, alternatively fewer than about 15-10, alternatively fewer than about 10-6, alternatively fewer than about 5 genes selected from the 1645 genes are used in diagnostic applications.
  • even analysis of expression of individual genes selected from the group of 1645 genes can be used in the diagnosis of the autoimmune diseases, particularly differentiating individuals with SLE, WG, RA and individuals with no autoimmune disease. In other embodiments, it may be preferable to analyze a larger gene set. In some embodiments, it may be preferable to analyze the expression of fewer genes. So, for example, if a two or more genes are selected from the interferon gene family or interferon inducible genes, also included can be, for example, genes that are not inducible by interferon. Such genes can be readily identified from the list of 1645 genesin Table 6 by a skilled artisan based on the score values provided in Table 6 and explained in more detail above.
  • Table 6 provides the set of 1645 genes and the corresponding scores the difference of which from the centroid value 0 indicate how useful they are in the diagnosis of any particular condition. Expression of any of these genes, any combination of these genes or all of these genes can be used in diagnostic methods according to this invention. Typically, in a diagnostic kit or array or bead set, one also uses also at least one, or more housekeeping genes as internal controls.
  • the genes are considered differentially expressed between the groups if the fold-change difference is > 1.8 and the p-value, as determined by a Welch's t-test, is ⁇ 0.01.
  • Table 7 provides the set or group of 279 genes the expression profile of which can differentiate between all four analyzed phenotypes: SLE, WG, RA and healthy individuals. Accordingly, one can select 1, 2, 3, 4, 5, 6, 7, 8, 9, 10-20, 20-30, 30-40, 40- 50, 50-100, 100-200, or up to 279 genes from this group to diagnose and /or screen for an individual for an autoimmune disease.
  • the genes can also be used to correctly classify the autoimmune disease in an individual as WG, SLE or RA based on the expression differences of thr genes from the all-sample average (0) as shown, for example, in Table 6, columns 4-7.
  • Table 1 provides 147 genes that are differentially expressed in SLE and non- SLE samples. The expression of these genes in SLE is increased as compared to non- SLE samples (including healthy individuals, individuals affected with RA and individuals affected with WG). Accordingly, one can select 1, 2, 3, 4, 5, 6, 7, 8, 9, 10-20, 20-30, 30- 40, 40-50, 50-100 or up to 147 genes from this group to diagnose an individual as having an autoimmune disease, as well as correctly classifying the autoimmune disease to WG, SLE or RA.
  • Table 4 provides 105 genes from which one can select 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10-20, 20-30, 30-40, 40-50, 50-100 or up to 105 that can be used as an alternative powerful set of genes the expression of these genes in SLE is increased as compared to non-SLE samples.
  • Table 8 provides 28 genes from which one can select to measure the expression of 1, 2, 3, 4, 5, 6, 7, ,8 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, or all 28, the expression changes of which can be used to differentiate SLE from other autoimmune samples as well as from normal samples.
  • the differential expression of the identified sets of genes provides a picture of disease activity.
  • the classification scores at Table 6 that are positive in individuals with a particular phenotype and negative in others are upregulated in that phenotype relative to other sample groups.
  • the classification scores at Table 6 that are negative in individuals with a particular phenotype positive in others are downregulated in that phenotype relative to other sample groups. Accordingly, one can readily select sub-groups from Table 6 based on the scores. The bigger the difference in the score, the better the expression change of that gene differentiates that phenotype from the other phenotypes.
  • the same gene set can also be used in monitoring disease activity, for example in response to treatment methods, such as pharmaceuticals and other therapies, including dietary interventions, herbal therapies, acupuncture, and mind-body relaxation techniques, such as meditation or hypnosis to control the autoimmune diseases.
  • Treatment methods such as pharmaceuticals and other therapies, including dietary interventions, herbal therapies, acupuncture, and mind-body relaxation techniques, such as meditation or hypnosis to control the autoimmune diseases.
  • Monitoring the gene expression profiles provided by the present invention also provides a way to assess effectiveness in clinical trials of new therapeutic interventions, such as pharmaceuticals to autoimmune diseases, such as SLE and WG. Accordingly, the invention provides methods for these described purposes.
  • Tables 1OA and 1OB provide gene sets the expression of which correlates with WG activity.
  • Tables 1OA and 1OB provide gene sets the expression of which correlates with WG activity.
  • the increased expression of the 33 genes in WG samples presented in Table 1OA was all associated with increased BVAS score, i.e. increased WG disease activity.
  • the decreased expression of the 61 genes presented in Table 1OB was also associated with increased BVAS score. Accordingly, measuring the expression of these genes in a patient affected with WG can classify these patients according the disease activity.
  • SLE patients can be classified intoat least two different groups based on the analysis of the 1645 genes.
  • Table 13 summarizes the data from 659 gene probes representing 279 genes that were able to classify individuals into SLE patients who also express higher levels of anti-ds-DNA antibodies, and thus have more active SLE disease, and SLE patients who have low levels or no anti-ds-DNA antibodies, and thus have less active disease, and healthy individuals, with no SLE. Expression was measured from whole blood sample.
  • Table 15 provides 186 genes (368 probes), a subset of the 279 genes of Table 13, which provides a more powerful set of genes the expression of which is most variable between the two above-mentioned SLE groups (anti-ds-DNA+ and anti-ds-DNA- groups) and can therefore best differentiate the two SLE classes with different disease activity.
  • Table 14 provides the results from the expression measurements and their comparisons between healthy and SLE patients.
  • the expression of the 69 genes represented by the 88 probes were able to differentiate SLE patients from healthy controls when expression was measured from whole blood.
  • Table 16 provides a sub-group of 53 genes, of the 69 genes of Table 14, the expression profile of which can be used to differentiate individuals into SLE, WG, RA and healthy phenotypes.
  • Table 17 provides a sub-set of 211 genes from the 1645 genes, the expression profile of which is corrected by gender (by moving male samples from the controls, to remove the female/male differences because all the SLE patient samples were female). Changes in the xpression profile of any of measured 1, 2, 3, 4, 5, 6, 7, 8, 9, 10-20, 20-30, 30-40, 40-50, 50-60, 60-70, 70-80, 80-90, 90-100, 100-200, 200-277, genes of the 277 genes can provide a diagnosis of SLE for a patient having autoimmune disease symptoms or can be used to screen SLE patients from a population.
  • the disease-specific gene expression signatures of the present invention provide substantially improved diagnostic power as compared to other methods that have been used in an attempt to diagnose autoimmune diseases such as SLE and WG.
  • analysis of the gene group of 279 genes of the 1645 in a biological sample from an individual, can result in a correct disease classification of the patient in about or over 60%, preferably over 75%, still more preferably over 77%, still more preferably over 78%, more preferably over 79%, more preferably over 80%, more preferably over 81%, more preferably over 82%, more preferably over 83%, more preferably over 84%, more preferably over 85%, more preferably over 86%, more preferably over 87%, still more preferably over 88%, still more preferably over 89%, still more preferably over 90% or even higher into groups of SLE, RA, WG or normal.
  • the diagnostic accuracy typically depends on the genetic background of the population that the individual belongs.
  • the present invention provides a powerful new tool to help in early diagnosis of these autoimmune diseases as well as tools for disease monitoring and monitoring of effects of new therapeutic interventions. Monitoring clinical trials of new autoimmune disease drugs can thus be vastly improved by the expression profiles of the present invention.
  • the present invention further provides a gene chip, or gene bead selection for the detection of autoimmune diseases, particularly for the diagnosis if SLE and WG, and classification of SLE and WG based on the disease activity.
  • the chip comprises probes for specifically binding with a selection of 1 to about 1645 sequences selected from Table 6.
  • Preferably the chip or the bead selection has fewer than 1645 genes. For each disease, as described in Table 6, one can select the best probe combination based on the score difference between the specific phenotype and the other phenotypes.
  • genes selected from Table 7 represent one preferred group of 279 genes the transcription of which is particularly useful in classification, screening and diagnosis of autoimmune diseases, such as SLE, WG, and RA.
  • Genes selected from Table 1 represent one alternative group of 147 genes the transcription of which is particularly useful in diagnosis of SLE.
  • Genes selected from Table 8 represent another alternative group of 28 genes the transcription of which is particularly useful in diagnosis of SLE.
  • the group of 6 top genes from Table 8 provide another alternative group of genes the transcription of which is useful in diagnosing SLE.
  • the control can be, for example, a mean expression of that gene in a group of healthy individuals when comparing SLE to non-SLE samples; mean expression in a group of RA, WG, and healthy individuals when comparing SLE to non-SLE samples; mean expression of the gene in any of the groups RA patients, WG patient or other autoimmune patients, when comparing SLE to non-SLE samples.
  • the SLE kidney-disease specific gene group is presented in Figure 4, and includes Intercellular adhesion molecule 2; Interferon induced with helicase C domain 1; Hypothetical protein FLJ38348; Hect domain and RLD 5; Hypothetical protein FLJ20035; Interferon-induced protein with tetratricopeptide repeats 1; Epithelial stromal interaction 1 breast; Zinc finger CCCH type domain containing 1 ; Interferon regulatory factor 7; Viperin; XIAP associated factor-1; Hect domain and RLD 6; Myxovirus influenza virus resistance 2 mouse; Interferon-induced protein 44; Chromosome 1 open reading frame 29; Myxovirus influenza virus resistance 1; Interferon alpha-inducible protein clone IFI- 15K; Interferon alpha-inducible protein clone IFI-6-16; Interferon alpha-inducible protein 27; Bone marrow stromal cell antigen 2; Hypothetical protein LOC 129607; Le
  • the invention also provides a group of genes for analyzing the disease activity in WG. For example, we found that change in the expression of certain of the 1645 genes was in linear correlation with the BVAS score. The score in Table 6 is positive if change is increased expression, and negative, if change is discreased expression as compared to the centroid score, which is zero. Centroid score represents roughly an average of epression in the entire group. For example, in columns 4-7, Table 6, the entire group "average" is determined by measuring expression of the gene in samples from all the analyzed phenotypes, and each individual class of individuals (SLE, WG, RA and healthy) is scored against the average.
  • One particular group of genes the expression of which linearly correlate with patient BVAS score consists of Serine hydroxymethyltransferase 2 mitochondrial; Lactate dehydrogenase B; Brix domain containing 1; Pyrophosphatase inorganic; Serine hydroxyltransferase 2 mitochondrial; Killer cell lectin-like receptor subfamily D, member 1; Hypothetical protein FLJ20315; Autism susceptibility candidate 2; Interleukin 7 receptor; LDL receptor adaptor protein; Chromosome 16 open reading frame 3; MEL- Like 2 chicken; T cell receptor alpha chain; T Cell receptor alpha locus; B-CeIl CLL/lymphoma HB zinc finger protein; IL2-inducible I-cell kinase; IDP-ribosylation factor-like 1; Mannosidase, alpha, class 1C, member 1; Bridging Integrator 1; Actin- binding LIM protein 1; Nuclear factor of activated T-cells, calcineuria-dependent 2
  • a group of 33 genes are used in determining the disease activity of WG, wherein the increased expression is indicative of higher BVAS score and therefore higher disease activity, the genes selected from the group consisting of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10-33 of the genes in Table 1OA.
  • a group of 61 genes are used in determining the disease activity of WG, wherein the decreased expression is indicative of higher BVAS score and therefore higher disease activity, the genes selected from the group consisting of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10-61 of the genes in Table 1OB.
  • a combination of genes with increased and decreased expression are used in determining the WG disease activity, the genes selected from the Tables 1OA and 1OB. Any of these genes combination may be used. Preferably at least 5 genes or more are analyzed.
  • the present invention further provides methods for distinguishing between SLE and other autoimmune diseases, such as WG, and Rlieumatoid Arthritis.
  • the methods comprise detecting the expression of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 and up to about 1645 gene products selected from the group consisting of gene products of Table 6, and correlating the expression pattern with SLE, or the other rheumatic autoimmune diseases.
  • 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 and up to about 279 of the gene group presented in Table 7 are used.
  • 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 and up to about 147 of the gene group presented in Table 1 are used.
  • the group of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 and up to about 105 gene described in Table 4 are used.
  • 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, and up to 46 genes of SLE kidney specific group as described above are used (see, also Figure 4).
  • the present invention further provides methods for monitoring the treatment of a patient with SLE.
  • the methods comprise administering the treatment, such as a pharmaceutical composition to the patient, obtaining a biological sample from the patient, and measuring the expression in the cells of the sample of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 and up to about 1645 gene products selected from the group consisting of gene products as presented in Table 6, Table 7, Table 8, Table 14, Table 15, Table 16, and Table 17, and determining whether the treatment results in partial or complete normalization of the expression profile thereby indicating that the treatment has had a clinical effect on the phenotype.
  • the present invention further provides methods for screening for an agent capable of modulating the onset or progression of SLE.
  • the methods comprise exposing a cell, for example, a cell isolated from an individual affected with SLE, to the agent, measuring expression of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or up to about 1645 gene products selected from the group consisting of gene products of Tables 6, 7, 8, 1OA, 1OB, 13, 14,
  • the present invention further provides methods for detecting drug induced SLE.
  • the methods comprise taking a biological sample from an individual exposed to a drug, for example a drug that is known to induce SLE in some individuals, or a drug that is suspected of causing SLE in some individuals, and analyzing the expression of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or up to 1645 genes selected from Tables 6, 7, 8, 1OA, 1OB, 13, 14, 15,
  • the method of the invention can be used to follow-up patients on drug therapies, that have been reported or that are suspected to induce SLE. Such follow-up can include taking several samples from the individual using the drug and determining whether the expression pattern of the genes changes. Also, one can determine a baseline expression pattern from a biological sample taken from the individual before she/he has been exposed to the drug and then determine if the expression pattern changes towards the SLE expression pattern during the continued use of the drug. Subtle changes in the expression pattern may be used as a warning sign and as a guide to discontinue use of the drug to prevent induction of drug induced SLE in the individual.
  • the present invention further provides methods for screening for an agent capable of causing SLE.
  • the methods comprise exposing a cell to the agent, measuring the expression of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or up to gene products selected from Tables 6, 7, 8, 1OA, 1OB, 13, 14, 15, 16, and 17, and comparing the expression pattern of the genes to a SLE or non-SLE expression pattern as provided by the scores in Table 6, wherein the expression pattern similar to a non-SLE sample, is indicative of agent that does not likely induce SLE, and wherein expression pattern similar to SLE-sample pattern is indicative of the agent being capable of inducing SLE.
  • the invention provides a method for classifying SLE patients into at least two groups based on the expression level of 279 genes listed in Table 13. We identified three major clusters 1) Healthy control samples, 2) SLE samples with a relatively high IFN-regulated gene signature and 3) SLE samples with a relatively low IFN-regulated gene signature. The group with relatively high IFN-regulated gene signature co-existed with the presence of anti-ds-DNA antibodies, and more active SLE disease. One or more of these genes can therefore now be used to predict SLE flares that are also known to be associated with increased anti-ds-DNA antibodies. Accordingly, the invention also provides a method for predicting SLE flares in SLE patients wherein the expression of one or more of these genes is analyzed and significant increase in the expression is indicative of impending SLE flare.
  • the gene products as recited herein can be RNA and/or proteins, preferably the gene products are RNA.
  • the gene products are RNA.
  • Figure IA shows cross-validation plots of the four sample classes. The results from ten fold cross-validation using nearest shrunken centroid classification performed using the PAM software. The overall misclassification error is reported for each of the four classes (healthy, lupus, RA, and ANCA) at increasing rates of centroid shrinkage (threshold values). The number of genes that significantly contribute to sample classification at each threshold value are indicated at the top of the plot. The vertical arrow indicates a centroid shrinkage threshold value of 3.75.
  • Figure IB shows cross-validation probabilities of each sample within the four sample classes.
  • the probability of belonging to each class centroid is indicated for each of the 153 samples using the top 279 genes (see Legend).
  • a sample was classified to a particular class as determined by the highest probability amongst the four classes.
  • the samples are arranged sequentially by class, as indicated by the header, and each sample-class group is separated by a solid vertical line.
  • a centroid shrinkage threshold of 3.75 identified 279 genes with the following classification rates: healthy 96.4% (27 of 28 samples), SLE 77.8% (56 of 72 samples), RA 23.1% (6 of 26 samples) and ANCA 85.2% (23 of 27 samples).
  • Figure 2 shows classification Probabilities of each SLE and "Other" non-SLE sample.
  • a sample was classified to a particular class as determined by the highest probability amongst the two classes.
  • the samples are arranged sequentially by class, as indicated by the header, and each sample-class group is separated by a solid vertical line.
  • a centroid shrinkage threshold value of 5.4 selected 28 gene features for sample classification Table 4).
  • Figure 3 shows Immune Cell Biology Gene expression that was determined for the SLE classification gene fragments. Expression intensities were converted to log 10 and normalized to the unit standard deviation using the Avadis software. Hierarchical clustering was performed using the Cluster Algorithms described by Eisen followed by visualization of the output using the program Tree View. Data is presented as a heat map where genes with higher expression are shown in reddarker grey and those with lower expression in lighter grey.
  • Figure 3 A Expression analysis of the SLE associated genes across numerous immune cell biology samples from healthy donors. The samples in the white box have been magnified in Figure 3B.
  • Figure 3B A magnified version of the region in 3 A showing expression of the top SLE classification genes in CD4+ T-cells stimulated with either anti-CD3 and anti-CD28 or ICAMl for 72 hours. Also shown are monocytes stimulated with LPS for 8 hours.
  • FIG. 4 shows expression analysis of kidney biopsies. Kidney biopsy material was processed for RNA and subjected to microsample amplification prior to hybridization to Affymetrix Ul 33 chips. The expression of genes differentially expressed in kidney samples was subjected to hierarchical clustering using Eisen 's method. Graphical representation in gene expression changes are shown with lighter grey corresponding to down-regulated and darker grey to up-regulated expression with the maximum intensity corresponding to a change of 0.16 based upon log 10.
  • Figures 5A and 5B show classification for each SLE and healthy control sample.
  • the probability of belonging to each class centroid is indicated for each of the samples in the reference or test data sets.
  • a sample was classified to a particular class as determined by the highest probability amongst the two classes.
  • a solid circle indicates the probability of being an SLE sample, while an unfilled circle indicates the probability of being a healthy control sample.
  • the samples are arranged sequentially by class, as indicated by the header, and each sample-class group is separated by a solid vertical line.
  • a centroid shrinkage threshold value of 4.2 selected 88 gene features for sample classification (Table 12).
  • the present invention provides a gene sets that are subsets of 1645 genes that we discovered were differentially expressed in autoimmune disease patients as.
  • the expression signatures or expression profiles of the identified genes are useful in diagnosis of and screening for autoimmune diseases, particularly in diagnosing systemic lupus erythematosus (SLE) and Wegeners granulomatosis anti-neutrophilic autoantibody (ANCA+) vasculitis (WG), and differentiating them from rheumatoid arthritis (RA) and each other.
  • the invention also provides methods for screening for SLE and WG.
  • the invention provides a method for differential diagnosis of SLE from other autoimmune diseases.
  • the invention provides methods of classifying SLE and WG based on specific gene expression signatures or expression profiles using the discovered genes.
  • the invention is based upon the discovery that expression of a defined set of genes is changed in biological samples from patients affected with different autoimmune diseases as compared to non-autoimmune diseases and even other autoimmune diseases, such as SLE and WG, and that detection of the expression profile of these genes provides a tool to diagnose and screen for these autoimmune diseases.
  • the invention provides a master set of genes consisting of 1645 genes that were found to be differentially expressed in autoimmune diseases as compared to non- autoimmune disease samples.
  • the group of 1645 genes is set forth in Table 6.
  • the increased expression of the identified sets of genes provides a picture of a more or less active disease. Therefore, the same gene set can also be used in monitoring disease activity, for example in response to treatment methods, such as pharmaceuticals and other therapies, including dietary interventions, herbal therapies, acupuncture, and mind-body relaxation techniques, such as meditation or hypnosis to control the autoimmune diseases.
  • Treatment methods such as pharmaceuticals and other therapies, including dietary interventions, herbal therapies, acupuncture, and mind-body relaxation techniques, such as meditation or hypnosis to control the autoimmune diseases.
  • Monitoring the gene expression profiles provided by the present invention also provides a way to assess effectiveness in clinical trials of new therapeutic interventions to autoimmune diseases, such as SLE and WG. Accordingly, the invention provides methods for these described purposes.
  • the invention provides a master set of genes consisting of 1645 genes that were found to be differentially expressed in autoimmune diseases as compared to non- autoimmune disease samples.
  • the group of 1645 genes are set forth in Table 6. Detailes of the scores for healthy donor samples, SLE white blood cell samples, RA samples and WG white blood cell samples are provided in Table 6.
  • the present invention provides a diagnostic/prognostic gene expression signature, i.e. a diagnostic/prognostic expression profile of a gene set of 279 or less genes, that is indicative of systemic lupus erythematosus (SLE).
  • a diagnostic/prognostic gene expression signature i.e. a diagnostic/prognostic expression profile of a gene set of 279 or less genes, that is indicative of systemic lupus erythematosus (SLE).
  • the diagnostic gene expression signature or profile consists of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10-15, 15-20, 20-30, 30-40, 40-50, 50-60, 60-70, 70-80, 80-90, 90-100, 100-110, 110-120, 120-130, 130-140, 140-150, 150-160, 160-170, 170-180, 180- 190, 190-200, 210-220, 220-230, 230-240, 240-250, 250-260, 260-270, 270-279 genes selected from the group of genes set forth in Table 7, wherein altered expression of said genes is indicative of the individual being affected with SLE.
  • the invention provides a group of genes consisting of 147 genes or less selected from the group of genes consisting of genes set forth in Table 1, wherein altered expression of said genes is indicative of the individual being affected with SLE.
  • the invention provides a group of genes consisting of 105 genes or fewer selected from the group consisting of genes set forth in Table 4, wherein altered expression of said genes is indicative of the individual being affected with SLE.
  • the invention provides a gene group consisting of RSAD2/CIG5, Corf29, IFITl, IFIT3, GIP2, LY6E, wherein the expression of one or more of genes is altered in kidney biopsies or cells from urine sediment of SLE patients and thus can be used as a disgnostic gene group for determining SLE related kidney disease.
  • the invention provides an SLE kidney gene expression profile group as shown in Figure 4, wherein the expression of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10-15, 15-20, 20-30, 30-40, 40-46 of genes in Figure 4 are analyzed in a kidney biopsy sample or urine sediment cell sample and wherein changed expression in these genes in the biological sample is indicative of SLE kidney disease.
  • the analysis is non-invasive, and involves taking of a urine sample and sedimenting cells present in the urine sample and analyzing expression of the SLE kidney groups of genes in these cells, (see, e.g. Li, B. C. et al., N. Engl. J. Med, 344(13): 947-54).
  • the invention provides a gene group consisting of metallothionein, lactotransferrin, olfactomedin wherein the expression of one or more of these genes is altered in kidney tissue of WG patients and thus can be used as a diagnostic gene group for determining WG related kidney disease.
  • altered expression or “changed expression” or “differential expression” as used herein and throughout the specification refer to gene expression that is changed, i.e. either increased or decreased in a patient with autoimmune disease, particularly with an active autoimmune disease as compared to a control, that provides a baseline or alternatively "normal” expression level or expression level range for any of the genes that are part of the expression profile of the invention.
  • Gene expression in a disease sample is preferably at least comparable to another disease sample. Accordingly, similar levels of expression will also convey the type of disease classification, i.e., the gene is important to the disease because it is different from a control sample or control sample group, or it is similar to the disease sample, or disease sample group.
  • Housekeeping genes i.e. genes that are involved in basic functions needed for the sustenance of the cell.
  • Housekeeping genes are constitutively expressed (they are always turned “on”).
  • a skilled artisan can readily determine a baseline housekeeping gene, such as beta-actin or GAPDH.
  • Other examples of possible housekeeping genes useful according to the methods of the invention are provided, infra.
  • the expression can be compared to, for example, a simultaneously analyzed biological sample from one or more healthy, or non-SLE or non- WG patient of the same type as the sample to be diagnosed.
  • the baseline can be created using a median or average expression of separately analyzed more than one control samples of the same biological origin, i.e. kidney sample for analysis of kidney biopsy and blood leukocyte sample for analysis of blood leukocytes, and whole blood sample for analysis of whole blood.
  • kidney sample for analysis of kidney biopsy and blood leukocyte sample for analysis of blood leukocytes
  • whole blood sample for analysis of whole blood.
  • a control panel can be created with control samples from healthy non-autoimmune disease affected individuals, and/or samples from individuals with known autoimmune disease diagnosis.
  • the control panel may also comprise expression patterns of the genes of the invention that distinguish different disease activity within the autoimmune disease patient group, such as different stages or classes of SLE.
  • Such control panel provides a way to compare the expression level of the gene signature group and assess, which group the unknown sample belongs based on its expression profile of the selected genes. Therefore, for example, if the control is a positive control consisting of one or more samples from individuals affected with SLE, the expression similar to the SLE control is indicative of the individual being affected with SLE.
  • control signatures may also be collected and saved in a computer database, thereby allowing analysis of samples even without simultaneous analysis of a control sample.
  • the housekeeping gene expression is used to standardize the expression pattern.
  • the genes are selected from the group of 28 genes consisting of AI337069; AW189843; NM_006820; NM_001548; NM_001549; NM_005101; NM_002346; AI742057; AA781795; NM_016323; NM_002534; NM_006417; AA633203; NMJ302462; NM_006187; NM_017631; NMJH7414; AA131041; AI075407; BC002548; BE049439; NMJH7523; BE888744; NM_017654; NM_016817; AA142842; NMJH4314; and NMJ) 16816, the expression provides a diagnostic signature profile, wherein altered expression of these 28 genes is indicative of SLE diagnosis.
  • the invention also provides methods of diagnosing SLE and WG, comprising analyzing in a biological sample of an individual in need of autoimmune disease diagnosis, the expression of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10-15, 15-20, 20-30, 30-40, 40-50, 50-60, 60-70, 70-80, 80-90, 90-100, 100-110, 110-120, 120-130, 130-140, 140- 150, 150-160, 160-170, 170-180, 180-190, 190-200, 200-210, 210-220, 220-230, 230- 240, 240-250, 250-260, 260-270, 270-279, of genes selected from Table 7 or Table 17 wherein altered expression of the genes is indicative of the individual being affected with SLE.
  • the invention further provides a method of differential diagnosis of SLE from other autoimmune diseases such as rheumatoid arthritis (RA), and WG.
  • the method comprises analyzing the gene expression in an individual in need of autoimmune disease diagnosis, such as an individual in need of differential diagnosis for autoimmune disease, in a biological sample, of genes selected from Table 7, wherein altered expression of said genes as compared to an individual with other types of autoimmune diseases than SLE is indicative of the individual being affected with SLE.
  • the invention also provides methods for determining the classification of SLE or WG patients based on expression analysis of a gene set of at least 2, 3, 4, 5, 6, 7, 8, 19, 10 or more genes in a biological sample, such as peripheral lymphocytes or whole blood, or cells isolated from urine sediment or a tissue biopsy, such as kidney biopsy, comprising analysis of expression of genes that are differentially expressed in more severely affected individuals that have belong to different disease sub-group of SLE or WG that indicate different disease activity.
  • a biological sample such as peripheral lymphocytes or whole blood, or cells isolated from urine sediment or a tissue biopsy, such as kidney biopsy
  • genes that were found significantly upregulated in biological samples that typically also had increased amounts of anti-ds ⁇ DNA antibodies included AA056548; AA083478; AA083478; AA131041; AA142842; AA150460; AA195074; AA233374; AA523958; AA573502; AA577672; AA741307; AA781795; AA976354; AF043337; AF063612; AF093744; AF129536; AF134715; AF208043; AF218365; AF220028; AF220030; AF237916; AF240697; AF240698; AF280094; AF307338; AF312735; AF312735; AF317129; AF323540; AI064690; AI075407; AI143416; AI304317; AI337069; AI421071; AI539443; AI55
  • the increased expression of the genes listed above is considered indicative of high level if the expression is at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25 fold that of a control, such as the expression of moderate or low IFN gene expressing SLE patient samples.
  • Table 18 gives examples of the power of the genes to differentiate between low and high disease activity in SLE.
  • IFN-regulated genes are significantly correlated with ⁇ -dsDNA antibodies in SLE patients.
  • this particular signature is more useful than the antibody test because it is more sensitive and specific than the ⁇ -dsDNA antibody test for assessing SLE disease activity.
  • the invention provides a diagnostic/prognostic gene expression signature, or gene set as set forth in Table 13 and Table 15, that is indicative of two different classes of SLE patients: a high IFN-related gene expression group, wherein the patients typically also exhibit increase in anti-ds-DNA antibodies, and a low IFN-related gene expression group, wherein the patients typically exhibit decreased or no anti-ds- DNA antibodies.
  • Patients with higher expression of IFN-related genes either have more active disease or are at risk of developing or about to develop an SLE flare-up, i.e. increase in disease activity and accompanying clinical symptoms, whereas patients with low IFN-related gene expression, exhibit lower disease activity.
  • the invention provides a diagnostic/prognostic gene expression signature, that is indicative of different WG disease activity.
  • the higher increase in the expression of 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, and 33 of the genes corresponds in linear correlation with the higher BVAS WG diseaseactivity score.
  • the gene set comprises the group consisting of NM_007219; AL562528; AL575509; AI760166; U41070; NM_001706; AI538394; AW592242; NM_007246; AW264036; NM_001995; NM_003059; AK025534; AI768563; AW295340; L32185; L13974; NM_006931; NM_000717; NM_005384; W60806; AI084056; S67779; AI452715; NM_018324; NM_004668; AI374686; AL136944; AF177765; AI767388; NM_005239; BC004564; and AL049435, wherein the increased expression of the genes in a biological sample from an individual is indicative of the individual being affected with WG; and more active disease in WG.
  • genes in Table 1OB were decreased, the higher the BVAS score in patients with WG was. Accordingly, the expression of genes in Table 1OA correlated positively with increased BVAS sdisease activity score, and the expression of genes in Table 1OB correlated negatively with increased BVAS disease activity score. Therefore, expression of any one or all of these genes or any combination of these genes can be used to assess disease activity in an individual affected with WG.
  • interferon activation pathway genes included in the gene signature of the invention if one looks at the expression of interferon activation pathway genes included in the gene signature of the invention, the expression of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10-20 or more transcripts other than interferon activation pathway encoding genes is also measured.
  • genes that are not part of interferon activation pathway based on the list of genes presented in the tables, figures and text, set forth in this description.
  • the expression of at least one other than genes selected from the group consisting of M63835, X54486, L13210, M33882, AA203213, X99699, AJ225089, U22970, ABOOOl 15, AL047596, AB006746, AL022318, U66711, and X55988 is measured.
  • each sample is standardized against a housekeeping gene expression in that sample.
  • the expression is considered increased if it is increased by at least about 5%-10%, 10-20%, 20-30%, 30-40%, 40-50%, 50-60%, 60-70%, 70-80%, 80- 90%, 90-100%, 100-200%, 200-300%, 300-400%, 400-500% or even more as compared to a standard or baseline sample from another phenotype group, such as a healthy control, a median of healthy controls, an average of healthy controls, or an artificially created baseline control that is based on, for example the expression of the housekeeping gene in the cell or cell mixture of the biological sample.
  • Such cells or cell combinations can be whole blood; white blood cell mixture; purified cells from the blood, such as monocytes, T-cells, B-cells, neutrophils, NK-cells; kidney biopsy; cells isolated from the urine sediment; or cultured cells from such biological sources as blood, kidney, skin, urine sediment or the like.
  • the expression is considered similar or comparable to a positive control sample, if the level of expression is similarly elevated. Similar expression, as used herein means that expression is equal to the baseline control. Similar expression also refers to greater or less than the control by about 100-90%, 90-80%, 80-70%, 70-60%, 60-50%, 50-40%, 40-30%, 30-20%, 20-15%, 15-10%, or 10-5% similarity to the baseline sample.
  • the biological sample as defined herein can be any biological sample containing nucleic acids from an individual, preferably human.
  • biological samples include blood, tisse biopsies, such as kidney or skin biopsies, primary or cultured cells from blood or tissue biopsies, sputum samples, buccal cell samples, urine, particularly cells sedimented from urine, stool, hair follicles, frozen or otherwise preserved samples from any biological sources and so on.
  • the biological sample is a blood leukocyte sample.
  • the biological sample is a kidney biopsy sample.
  • the biological sample is cells present in the urine sediment.
  • the biological sample is whole blood.
  • Whole blood or total blood leukocytes, or white blood cells are preferred because they allow minimal handling of the sample. Handling, such as cell separation, may change the expression in the cells during the sample preparation. Accordingly, it is preferred, although not necessary, to use cells that have been manipulated as little as possible.
  • Whole blood or whole blood white blood cells or urine sediment cells provide thus one optimal biological sample material for analyzing the expression patterns of the present invention.
  • the biological sample is a kidney biopsy or cells from the urine sediment.
  • the sample is a kidney biopsy or cells from the urine sediment.
  • one preferred embodiment provides a gene transcript set, or a kidney gene set that comprises at least 1, 2, 3, 4, 5, or 6 transcripts from the group selected from the transcripts corresponding to genes RSAD2/CIG5, Corf29, IFITl, IFIT3, GIP2, and LY6E.
  • Transcript level detection methods The genes identified as being differentially expressed in autoimmune diseases according to the present invention may be used in a variety of nucleic acid detection assays to detect or quantify the expression level of a gene or multiple genes in a given sample. Any hybridization assay format may be used, including solution based and solid support based assay formats. Methods of detecting gene expression are well known to one skilled in the art and include, for example, Northern-blot hybridization, ribonuclease protection assay, and reverse transcriptase polymerase chain reaction (RT-PCR) based methods.
  • RT-PCR reverse transcriptase polymerase chain reaction
  • RT-PCR based techniques are the most suitable quantification method for diagnostic purposes of the present invention, because they are very sensitive and thus require only a small sample size which is desirable for a diagnostic test.
  • a number of quantitative RT-PCR based methods have been described and are useful in measuring the amount of transcripts according to the present invention. These methods include RNA quantification using PCR and complementary DNA (cDNA) arrays (Shalon et al., Genome Research 6(7):639- 45, 1996; Bernard et al., Nucleic Acids Research 24(8): 1435-42, 1996), and 5 'nuclease assay or real-time RT-PCR (Holland et al. Proc Natl Acad Sci USA 88: 7276-7280, 1991).
  • RNA quantification methods based on mass spectrometry such as MALDI- TOF, can also be used as well known by the skilled artisan (see, for example Sequenom, Inc, CA).
  • qNPA High Throughput Genomics Inc., Arlington, AZ
  • qNPA qNPA method
  • the qNPA produces a stoichiometric amount of the specific nuclease protection probe for each gene, or a quantative amount of a chemical mirror image.
  • the SENTRIX® Human-6 and HumanRef-8 Expression BeadChips enable generation of genome-wide expression profiles for multiple samples on a single BeadChip.
  • Methods and assays of the invention are most efficiently designed with array, chip, or bead hybridization based methods designed for detecting the expression levels of a large number of genes.
  • Assays and methods of the invention may utilize available formats to simultaneously screen from, for example, at least about 6 to about 100, preferably about 1000, more preferably about 10,000 and most preferably about 1,000,000 or more different nucleic acid hybridizations.
  • Preferred method of detecting the gene set expression signatures of the invention include nucleic acid chip- or bead- based technologies that are well suited in automation and screening of a large number of genes in a large number of individuals.
  • Nucleic acid arrays that are useful in the present invention include, but are not limited to those that are commercially available from Affymetrix (Santa Clara, CA) under the brand name GeneChip7. Example arrays are shown on the website at affymetrix.com.
  • the nucleic acids from the biological sample may be isolated and purified or analyzed directly.
  • the nucleic acids are isolated and/or purified using standard nucleic acid isolation and/or purification techniques that are well known and readily available to on skilled in the art. Direct analysis can be performed using, for example, microfluidic chips.
  • a FLOW-THRU® chip such as that disclosed in U.S. Patent No. 5,843,767, which disclosure in incorporated herein by reference in its entirety, is used with present invention.
  • the FLOW-THRU® chip generally comprises an array of micro-channels extending through a solid support. Each micro-channel contains a probe specific for a gene selected from Table 6; and different channels contain different probes for different genes or for the same gene. The hybridization and/or binding reactions take place by providing fluidic flow through of the sample through the chip.
  • the transcript expression assay can be conducted using microbeads labeled with different spectral property and/or fluorescent (or colorimetric). Technologies such as CYVERA technology (from ILLUMINA inc.) can be easily optimized to analyze the gene sets or sub-sets of the invention. For example, polystyrene microspheres are provided by Luminex Corp, Austin, Tex. that are internally dyed with two spectrally distinct fluorochromes. Using precise ratios of these fluorochromes, a large number of different fluorescent bead sets (e.g., 100 sets) can be produced.
  • Each set of the beads can be distinguished by its spectral address, a combination of which allows for measurement of a large number of analytes in a single reaction vessel.
  • a third fluorochrome coupled to a reporter molecule quantifies the biomolecular interaction that has occurred at the microsphere surface.
  • These different fluorescent bead sets can be used to label the reference nucleic acids targeting different SNP sites on a test DNA by using standard nucleic acid chemical synthesis methods or by PCR amplification using primers labeled with the beads (e.g., primers modified with 5' amine for coupling to carboxylated microsphere or bead).
  • protein and tissue arrays can also be used.
  • the probes are specific for protein products of the genes of Table 6 or fragments thereof.
  • These probes can be, but are not limited to, antibodies, cell surface receptors, secreted proteins, receptor ligands, irnmunoliposom.es, immunotoxins, cytosolic proteins, nuclear proteins, and functional motifs thereof that specifically bind to the protein products of the genes of Table 6 or fragments thereof.
  • the probes are immobilized on a solid support to form an array and provides a specific binding partner for the protein products of the genes of Table 6 or fragments thereof.
  • the supports can be either plates (glass, plastics, or silicon) or membranes made of nitrocellulose, nylon, or polyvinylidene difluoride (PVDF).
  • a protein array is incubated with a protein sample prepared under the conditions that native protein- protein interactions are minimized. After incubation, unbound or non-specific binding proteins can be removed with several washes. Proteins specifically bound to their respective binding partners on the array are then detected. Because the binding partners are immobilized in a predetermined order, the identity of the protein captured at each position is therefore known. Measurement of protein amount at all positions on the array thus reflects the protein expression pattern in the sample.
  • the quantities of the proteins trapped on the array can be measured in several ways.
  • the amount of proteins bound to each antibody represents the level of the specific protein in the sample. If a specific group of proteins are interested, they can be detected by agents which specifically recognize them. Other methods, like immunochemical staining, surface plasmon resonance, matrix-assisted laser desorption/ionization-time of flight, can also be used to detect the captured proteins.
  • Tissue arrays consist of regular arrays of cores of embedded biological tissue arranged in a sectionable block typically made of the same embedding material used originally for the tissue in the cores.
  • the new blocks may be sectioned by traditional means (microtomes etc.) to create multiple nearly identical sections each containing dozens, hundreds or even over a thousand different tissue types.
  • tissue array the tissue sample is assayed for differential expression of the protein products of the genes of Table 6.
  • standard cytoimmunostaining techniques known to skilled artisans can be employed. Cytoimmunostaining may be performed directly on frozen sections of cells or tissues or, preceded by fixing cells with a fixative that preserves the intracellular structures, followed by permeablization of the cell to ensure free access of the probes. The step of permeablization can be omitted when examining cell-surface antigens.
  • a probe such as an antibody specific for the target
  • unbound antibody is removed by washing, and the bound antibody is detected either directly (if the primary antibody is labeled) or, more commonly, indirectly visualized using a labeled secondary antibody.
  • co-staining with one or more marker antibodies specific for antigens differentially present in such structure is preferably performed.
  • a battery of organelle specific antibodies is available in the art.
  • Non-limiting examples include plasma membrane specific antibodies reactive with cell surface receptor Her2, endoplasmic reticulum (ER) specific antibodies directed to the ER resident protein Bip, Golgi specific antibody ⁇ -adaptin, and cytokeratin specific antibodies which will differentiate cytokeratins from different cell types (e.g. between epithelial and stromal cells) or in different species.
  • ER endoplasmic reticulum
  • Golgi specific antibody ⁇ -adaptin Golgi specific antibody ⁇ -adaptin
  • cytokeratin specific antibodies which will differentiate cytokeratins from different cell types (e.g. between epithelial and stromal cells) or in different species.
  • digital image analysis system coupled to conventional or confocal microscopy can be employed.
  • Assays to monitor the expression of a gene or genes of Table 6 may utilize any available means of monitoring for changes in the expression level of the nucleic acids of the invention.
  • an agent is said to modulate the expression of a nucleic acid of the invention if it is capable of up or down regulating expression of the nucleic acid in a cell.
  • gene chips containing probes to at least two genes selected from Table 6 may be used to directly monitor or detect changes in gene expression in the treated or exposed cell.
  • High density gene chips and their uses are described in U.S. Patent No. 6,040,138 to Lockhart et al., which is incorporated herein by reference.
  • An alternative format to the gene chip is the flow-through chip disclosed in U.S. Patent No. 5,843,767 to Beattie, which is incorporated herein by reference.
  • Additional assay formats may be used to monitor the ability of the agent to modulate the expression of one or more genes identified in Table 6. For instance, as described above, mRNA expression may be monitored directly by hybridization of probes to the nucleic acids of Table 6. Cell lines are exposed to the agent to be tested under appropriate conditions and time and total RNA or mRNA is isolated by standard procedures such those disclosed in Sambrook et al. (1989), Molecular Cloning A Laboratory Manual, Cold Spring Harbor Laboratory Press.
  • the level of expression is also proportional to the severity of SLE.
  • the higher level of expression corresponds with a higher SLEDAI (Systematic Lupus Erythematosus Disease Activity Index) score which measures disease activity and severity.
  • the present inventor has examined tissue samples from normal individuals, SLE, and other autoimmune diseases, such as WG, and RA, to identify a gene set associated with SLE. Changes in gene expression, also referred to as expression profiles or expression pattern, provide useful markers for diagnostic uses as well as markers that can be used to monitor disease states, disease progression, drug toxicity, drug efficacy and drug metabolism.
  • the expression profiles of the genes of Table 6 may be used as diagnostic markers for the prediction or identification of autoimmune diseases, such as SLE and WG.
  • a tissue sample such as blood sample or kidney biopsy or cells from the urine sediment, or other sample from a patient may be assayed by any of the methods described herein or by any other method known to those skilled in the art, and the expression levels from a gene or genes from Table 6 may be compared to the expression levels found in normal sample.
  • Expression profiles generated from the tissue, blood, or other sample that substantially resemble an expression profile from normal or diseased tissue may be used, for instance, to aid in disease diagnosis.
  • the genes of Table 1 or Table 4 are upregulated specifically in SLE patients without being upregulated in other rheumatic autoimmune diseases, such as WG or RA. Comparison of the expression data, as well as available sequence or other information may be done by researcher or diagnostician or may be done with the aid of a computer and databases. [00128] Furthermore, the genes of Table 6, Table 7, Table 8, Table 13, Table 14, Table 15, Table 16 and Table 17 can also detect drug-induced lupus. Some drugs can induce a lupus like syndrome as a side effect resulting from long term use, which can be diagnosed with certainty only by resolution of symptoms and their failure to recur after stopping the medication. Lupus-inducing drugs are typically those used to treat chronic diseases.
  • lupus which includes medicines used to treat heart disease, thyroid disease, hypertension, neuropsychiatric disorders, certain anti-inflammatory agents and antibiotics.
  • At least eighty (80) drugs currently in use can cause drug-induced lupus.
  • procainamide Pronestyl
  • hydralazine Presoline
  • quinidine Quinidine
  • drugs that have been linked to drug-induced lupus include, but are not limited to, Enbrel, Remicade, Celebrex, beta-blockers, penicillin, tetracyclines, dilantin, INH, oral contraceptives, and various vaccines.
  • the genes and gene expression information of Table 6 can also be used as markers for the monitoring of disease activity.
  • a tissue, blood, or other sample from a patient may be assayed by any of the methods described above, and the expression levels in the sample from a gene or genes from Table 6 may be compared to the expression levels found in normal tissue.
  • the gene expression pattern can be monitored over time to track activity of the disease. Comparison of the expression pattern, as well as available sequence or other information may be done by researcher or diagnostician or may be done with the aid of a computer and databases.
  • the genes identified in Table 6 can be used as markers to evaluate the effects of a candidate drug or agent on a cell, particularly a cell from a SLE tissue sample.
  • a patient can be treated with a drag candidate and the activity of SLE is monitored over time. This method comprises treating the patient with an agent, obtaining a tissue sample from the patient, extracting a gene product sample from the tissue sample, contacting the gene product sample with probes which specifically bind with gene products of Table 6, and comparing the binding pattern over time to determine the effect of the agent on the activity of SLE.
  • the genes identified in Table 6 can be used as markers to screen agents that can cause SLE or SLE-like conditions.
  • the screening is accomplished on a tissue or cellular sample.
  • the method comprises exposing a cell to a test agent, extracting a gene product sample from the tissue sample, contacting the gene product sample with probes which specifically bind with gene products of Table 6, and comparing the binding pattern with normal and SLE cells to determine the effect of the agent on the cell or tissue samples.
  • the invention provides a personalized screen for an SLEAVG patient to select a drug that most effectively normalizes the SLE/WG specific gene expression profile.
  • patient's cells are cultured and exposed to medicines and the expression of the genes, selected from Table 6, are monitored and compared to control and disease samples.
  • the drag that induces improvement in the gene expression profile in the cultured cells from the patient, can then be selected to treat the SLEAVG patient.
  • a candidate drag or agent can be screened for the ability to stimulate the transcription or expression of a given marker or markers (drag targets) or to down regulate or counteract the transcription or expression of a marker or markers. According to the present invention, one can also compare the specificity of drags' effects by looking at the number of markers affected by different drags and comparing them. Similar sets of markers identified for two drags indicate similar effects.
  • the agents to be screened in the methods of the present invention can be, for example, peptides, small molecules, vitamin derivatives, as well as carbohydrates, dominant negative proteins, DNA encoding these proteins, antibodies to these proteins, peptide fragments of these proteins or mimics of these proteins may be introduced into cells to affect function.
  • "Mimic” as used herein refers to the modification of a region or several regions of a peptide molecule to provide a structure chemically different from the parent peptide but topographically and functionally similar to the parent peptide. A skilled artisan can readily recognize that there is no limit as to the structural nature of the agents of the present invention.
  • cells or cell lines are first identified which express the gene products of the invention physiologically.
  • Cell and/or cell lines so identified would be expected to comprise the necessary cellular machinery such that the fidelity of modulation of the transcriptional apparatus is maintained with regard to exogenous contact of a drug or agent with appropriate surface transduction mechanisms and/or the cytosolic cascades.
  • Such cell lines may be, but are not required to be, derived from tissue samples of individuals suffering from SLE.
  • such cells or cell lines may be transduced or transfected with an expression vehicle (e.g., a plasmid or viral vector) construct comprising an operable non translated 5' promoter containing end of the structural gene encoding the instant gene products fused to one or more antigenic fragments, which are peculiar to the instant gene products, wherein said fragments are under the transcriptional control of said promoter and are expressed as polypeptides whose molecular weight can be distinguished from the naturally occurring polypeptides or may further comprise an immunologically distinct tag.
  • an expression vehicle e.g., a plasmid or viral vector
  • the drug or agent comprises a pharmaceutically acceptable excipient and is contacted with cells in an aqueous physiological buffer such as phosphate buffered saline (PBS) at physiological pH, Eagles balanced salt solution (BSS) at physiological pH, PBS or BSS comprising serum or conditioned media comprising PBS or BSS and serum incubated at 37°C.
  • PBS phosphate buffered saline
  • BSS Eagles balanced salt solution
  • serum or conditioned media comprising PBS or BSS and serum incubated at 37°C.
  • Said conditions may be modulated as necessary by one of skill in the art.
  • Another embodiment of the present invention provides methods for identifying drugs or agents that modulate the levels, concentration or at least one activity of a protein(s) encoded by the genes of Table 6. Such methods or assays may utilize any means of monitoring or detecting the desired activity.
  • the relative amounts of a protein of the invention between a cell population that has been exposed to the drug or agent to be tested compared to an un exposed control cell population may be assayed.
  • probes such as specific antibodies are used to monitor the differential expression of the protein in the different cell populations.
  • Cell lines or populations are exposed to the drug or agent to be tested under appropriate conditions and time.
  • Cellular lysates may be prepared from the exposed cell line or population and a control, unexposed cell line or population. The cellular lysates are then analyzed with probes, such as specific antibodies.
  • the genes which are assayed according to the present invention are typically in the form of mRNA or reverse transcribed mRNA.
  • the genes may or may not be cloned; and the genes may or may not be amplified.
  • the cloning itself does not appear to bias the representation of genes within a population.
  • polyA+ RNA it may be preferable to use polyA+ RNA as a source, as it can be used with less processing steps.
  • Probes based on the sequences of the genes described herein may be prepared by any commonly available method. Oligonucleotide probes for assaying the tissue or cell sample are preferably of sufficient length to specifically hybridize only to appropriate, complementary genes or transcripts. Typically the oligonucleotide probes will be at least 10, 12, 14, 16, 18, 20 or 25 nucleotides in length. In some cases longer probes of at least 30, 40, 50, 60 or 70 nucleotides will be desirable. It is preferable that more than one probe specific for each gene is used in the assay.
  • the high density array will typically include a number of probes that specifically hybridize to the sequences of interest. Methods of producing probes for a given gene or genes are disclosed in WO 99/32660, which is incorporated herein by reference. In addition, in a preferred embodiment, the array will include one or more control probes. High density array chips of the invention include "test probes.” Test probes may be oligonucleotides that range from about 5 to about 500 or about 10 to about 100 nucleotides, more preferably from about 20 to about 80 nucleotides and most preferably from about 50 to about 70 nucleotides in length.
  • test probes are about 20 to about 25 nucleotides in length.
  • test probes are double or single strand DNA sequences. DNA sequences are isolated or cloned from natural sources or amplified from natural sources using natural nucleic acid as templates. These probes have sequences complementary to particular subsequences of the genes whose expression they are designed to detect. Thus, the test probes are capable of specifically hybridizing to the target nucleic acid they are to detect.
  • the high density array can contain a number of control probes.
  • the control probes fall into three categories referred to herein as (1) normalization controls; (2) expression level controls; and (3) mismatch controls.
  • Normalization controls are oligonucleotide or other nucleic acid probes that are complementary to labeled reference oligonucleotides or other nucleic acid sequences that are added to the nucleic acid sample.
  • the signals obtained from the normalization controls after hybridization provide a control for variations in hybridization conditions, label intensity, "reading" efficiency and other factors that may cause the signal of a perfect hybridization to vary between arrays.
  • signals (e.g., fluorescence intensity) read from all other probes in the array are divided by the signal (e.g., fluorescence intensity) from the control probes thereby normalizing the measurements.
  • any probe may serve as a normalization control.
  • Preferred normalization probes are selected to reflect the average length of the other probes present in the array, however, they can be selected to cover a range of lengths.
  • the normalization controls can also be selected to reflect the (average) base composition of the other probes in the array, however in a preferred embodiment, only one or a few probes are used and they are selected such that they hybridize well (i. e., no secondary structure) and have minimal cross match with non-specific targets.
  • Typical expression level control probes have sequences complementary to subsequences of constitutively expressed housekeeping genes including, but not limited to the 3 actin gene, the transferrin receptor gene, the GAPDH gene, and the like. Examples of other useful housekeeping genes are provided elsewhere in this spacification.
  • Mismatch controls are generally not required when using probes of about 60 to about 70 nucleotides. However, when using shorter probes, mismatch controls may also be provided for the probes to the target genes, for expression level controls or for normalization controls. Mismatch controls are oligonucleotide probes or other nucleic acid probes identical to their corresponding test or control probes except for the presence of one or more mismatched bases. A mismatched base is a base selected so that it is not complementary to the corresponding base in the target sequence to which the probe would otherwise specifically hybridize.
  • mismatch probes are selected such that under appropriate hybridization conditions (e.g., stringent conditions) the test or control probe would be expected to hybridize with its target sequence, but the mismatch probe would not hybridize (or would hybridize to a significantly lesser extent).
  • Preferred mismatch probes contain a central mismatch.
  • a corresponding mismatch probe will have the identical sequence except for a single base mismatch (e.g., substituting a G, a C or a T for an A) at any of positions 6 through 14 (the central mismatch).
  • Mismatch probes thus provide a control for non specific binding or cross hybridization to a nucleic acid in the sample other than the target to which the probe is directed. Mismatch probes also indicate whether a hybridization is specific or not. For example, if the target is present the perfect match probes should be consistently brighter than the mismatch probes. In addition, if all central mismatches are present, the mismatch probes can be used to detect a mutation. The difference in intensity between the perfect match and the mismatch probe provides a good measure of the concentration of the hybridized material.
  • mismatch probes are not required as the probes are sufficiently long that a single mismatch does not effect an appreciable difference in binding efficiency.
  • nucleic acid samples used in the methods and assays of the invention may be prepared by any available method or process. Methods of isolating total RNA are also well known to those of skill in the art. For example, methods of isolation and purification of nucleic acids are described in detail in Chapter 3 of Laboratory Techniques in Biochemistry and Molecular Biology: Hybridization With Nucleic Acid Probes, Part I - Theory and Nucleic Acid Preparation, Tijssen, (1993) (editor) Elsevier Press. Such samples include RNA samples, but also include cDNA synthesized from a mRNA sample isolated from a cell or tissue of interest. Such samples also include DNA amplified from the cDNA, and an RNA transcribed from the amplified DNA. One of skill in the art would appreciate that it is desirable to inhibit or destroy RNase present in homogenates before homogenates can be used.
  • Biological samples may be of any biological tissue or fluid or cells from any organism as well as cells raised in vitro, such as cell lines and tissue culture cells. Frequently the sample will be a "clinical sample" which is a sample derived from a patient. Typical clinical samples include, but are not limited to, sputum, blood, blood cells (e.g., white blood cells or leukocytes), tissue or fine needle biopsy samples, urine, peritoneal fluid, and pleural fluid, or cells therefrom.
  • sputum blood
  • blood cells e.g., white blood cells or leukocytes
  • tissue or fine needle biopsy samples e.g., fine needle biopsy samples
  • urine e.g., peritoneal fluid, and pleural fluid, or cells therefrom.
  • Biological samples may also include sections of tissues, such as frozen sections or formalin fixed sections taken for histological purposes.
  • Solid supports containing oligonucleotide probes for differentially expressed genes of the invention can be filters, polyvinyl chloride dishes, silicon or glass based chips, etc. Such wafers and hybridization methods are widely available, for example, those disclosed by U.S. Patent No. 6,040,138 to Lockhart et al. and U.S. Patent No. 5,843,767 to Beattie. Any solid surface to which oligonucleotides can be bound, either directly or indirectly, either covalently or non covalently, can be used.
  • a preferred solid support is a high density array or DNA chip. These contain a particular oligonucleotide probe in a predetermined location on the array.
  • Each predetermined location may contain more than one molecule of the probe, but each molecule within the predetermined location has an identical sequence.
  • Such predetermined locations are termed features. There may be, for example, about 2, 10, 100, 1000 to 10,000; 100,000 or 400,000 of such features on a single solid support.
  • the solid support, or the area within which the probes are attached may be on the order of a square centimeter (see, e.g., FLOW-THRU CHIPTM, Metrigenix Corporation, Toronto, Canada).
  • Oligonucleotide probe arrays for expression monitoring can be made and used according to any techniques known in the art (see for example, Lockhart et al. (1996), Nat. Biotechnol., 14: 1675 1680; McGaIl et al. (1996), PNAS USA, 93:13555-13460).
  • Such probe arrays may contain at least two or more oligonucleotides that are complementary to or hybridize to two or more of the genes described herein.
  • Such arrays may also contain oligonucleotides that are complementary or hybridize to at least about 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 50, 70, 100 or more the genes described herein.
  • oligonucleotide analogue array can be synthesized on a solid substrate by a variety of methods, including, but not limited to, light directed chemical coupling, and mechanically directed coupling (U.S. Patent No. 5,143, 854 to Pirrung et al.; U.S. Patent No. 5,800,992 to Fodor et al.; U.S. Patent No. 5,837,832 to Chee et al; which are incorporated herein by reference).
  • a glass surface is derivatized with a silane reagent containing a functional group, e.g., a hydroxyl or amine group blocked by a photolabile protecting group.
  • a functional group e.g., a hydroxyl or amine group blocked by a photolabile protecting group.
  • Photolysis through a photolithogaphic mask is used selectively to expose functional groups which are then ready to react with incoming 5' photoprotected nucleoside phosphoramidites.
  • the phosphoramidites react only with those sites which are illuminated (and thus exposed by removal of the photolabile blocking group).
  • the phosphoramidites only add to those areas selectively exposed from the preceding step. These steps are repeated until the desired array of sequences has been synthesized on the solid surface. Combinatorial synthesis of different oligonucleotide analogues at different locations on the array is determined by the pattern of illumination during synthesis and the order of addition of coupling reagents.
  • High density nucleic acid arrays can also be fabricated by depositing premade or natural nucleic acids in predetermined positions. Synthesized or natural nucleic acids are deposited on specific locations of a substrate by light directed targeting and oligonucleotide directed targeting. Another embodiment uses a dispenser that moves from region to region to deposit nucleic acids in specific spots.
  • Nucleic acid hybridization simply involves contacting a probe and target nucleic acid under conditions where the probe and its complementary target can form stable hybrid duplexes through complementary base pairing (see U.S. Patent No. 6,333,155 to Lockhart et al, which is incorporated herein by reference). The nucleic acids that do not form hybrid duplexes are then washed away leaving the hybridized nucleic acids to be detected, typically through detection of an attached detectable label. It is generally recognized that nucleic acids are denatured by increasing the temperature or decreasing the salt concentration of the buffer containing the nucleic acids.
  • hybrid duplexes e.g., DNA DNA, RNA RNA or RNA DNA
  • RNA RNA or RNA DNA will form even where the annealed sequences are not perfectly complementary.
  • hybridization conditions may be selected to provide any degree of stringency.
  • hybridization is performed at low stringency, in this case in 6x SSPE T at 37°C (0.005% Triton x 100) to ensure hybridization and then subsequent washes are performed at higher stringency (e.g., 1 x SSPE T at 37 0 C) to eliminate mismatched hybrid duplexes.
  • Successive washes maybe performed at increasingly higher stringency (e.g., down to as low as 0.25x SSPE-T at 37°C to 50°C) until a desired level of hybridization specificity is obtained.
  • Stringency can also be increased by addition of agents such as formamide.
  • Hybridization specificity may be evaluated by comparison of hybridization to the test probes with hybridization to the various controls that can be present (e.g., expression level control, normalization control, mismatch controls, etc.).
  • the wash is performed at the highest stringency that produces consistent results and that provides signal intensity greater than approximately 10% of the background intensity.
  • the hybridized array may be washed at successively higher stringency solutions and read between each wash. Analysis of the data sets thus produced will reveal a wash stringency above which the hybridization pattern is not appreciably altered and which provides adequate signal for the particular oligonucleotide probes of interest.
  • the hybridized nucleic acids are typically detected by detecting one or more labels attached to the sample nucleic acids.
  • the labels may be incorporated by any of a number of means well known to those of skill in the art (see U.S. Patent No. 6,333,155 to Lockhart et al, which is incorporated herein by reference). Commonly employed labels include, but are not limited to, biotin, fluorescent molecules, radioactive molecules, chromogenic substrates, chemiluminescent labels, enzymes, and the like.
  • the methods for biotinylating nucleic acids are well known in the art, as are methods for introducing fluorescent molecules and radioactive molecules into oligonucleotides and nucleotides.
  • biotin When biotin is employed, it is detected by avidin, streptavidin or the like, which is conjugated to a detectable marker, such as an enzyme (e.g., horseradish peroxidase) or radioactive label (e.g., 32P, 35S, 33P). Enzyme conjugates are commercially available from, for example, Vector Laboratories, Burlingame, CA. Steptavidin binds with high affinity to biotin, unbound stretavidin is washed away, and the presence of horseradish peroxidase enzyme is then detected using a substrate in the presence of peroxide and appropriate buffers. The binding reaction may be detected using a microscope equipped with a visible light source and a CCD camera (Princeton Instruments, Princeton, N.J.).
  • a detectable marker such as an enzyme (e.g., horseradish peroxidase) or radioactive label (e.g., 32P, 35S, 33P).
  • Enzyme conjugates are commercially
  • Detection methods are well known for fluorescent, radioactive, chemiluminescent, chromogenic labels, as well as other commonly used labels. Briefly, fluorescent labels can be identified and quantified most directly by their absorption and fluorescence emission wavelengths and intensity. A microscope/camera setup using a light source of the appropriate wavelength is a convenient means for detecting fluorescent label. Radioactive labels may be visualized by standard autoradiography, phosphor image analysis or CCD detector. Other detection systems are available and known in the art.
  • the present invention includes relational databases containing sequence information, for instance for the genes of Table 6, as well as gene expression information for SLE, other rheumatic autoimmune diseases, such as Wegener's Granulomatosus, Rheumatoid Arthritis, and Inflammatory Bowel Disease (Crohn's and Ulcerative Colitis), and normal tissue.
  • Databases may also contain information associated with a given sequence or tissue sample such as descriptive information about the gene associated with the sequence information, or descriptive information concerning the clinical status of the tissue sample, or the patient from which the sample was derived.
  • the database may be designed to include different parts, for instance a sequences database and a gene expression database.
  • the databases of the invention may be linked to an outside or external database.
  • the external database is GenBank and the associated databases maintained by the National Center for Biotechnology Information (NCBI).
  • Any appropriate computer platform may be used to perform the necessary comparisons between sequence information, gene expression information and any other information in the database or provided as an input.
  • a large number of computer workstations are available from a variety of manufacturers, such has those available from Silicon Graphics.
  • Client server environments, database servers and networks are also widely available and appropriate platforms for the databases of the invention.
  • the databases of the invention may be used to produce, among other things, electronic Northerns to allow the user to determine the cell type or tissue in which a given gene is expressed and to allow determination of the abundance or expression level of a given gene in a particular tissue or cell.
  • the databases of the invention may also be used to present information identifying the expression level in a tissue or cell of a set of genes comprising at least one gene in Table 6 comprising the step of comparing the expression level of at least one gene in Table 6 in the tissue to the level of expression of the gene in the database.
  • Such methods may be used to predict the physiological state of a given tissue by comparing the level of expression of a gene or genes in Table 6 from a sample to the expression levels found in normal tissue or tissues of other rheumatic autoimmune diseases.
  • Such methods may also be used in the drug or agent screening assays as described above.
  • a non- limiting list of examples of housekeeping genes include NM_001101; *NM_000034; *NM_002046; *NM_000291; *NM_005566; *NM_002954; *NM_000981; *NM_000975; *NM_007363; *NMJ)04309; *NM_000994; *NM_022551; *NM_007355; NM_004515; NM_004651; NM_004888; NM_003334; NM_001320; NM_003915; NM_001250; NM_001904; NM_003753; NM_004541; NM_001654; NM_002967; NMJ)Ol 183; NM_003526; NM_004718; NM_004436; NM_001207; NM_004907; NM_004889; NM_003769; NM_003910; NMJ)OOlOO
  • NM_005698 NM_024011; NMJ3O51O5; NM_006013; NM_005786; NM_ 007104; NM_005762; NM_012138; NM_015318; NM_012423; NM_021128; NM_ . 032635; NM_005080; NM_006389; NM_024112; NM_006817; NM_022830; NM_ 019884; NM_021107; NM_021074; NM_014944; NMJ) 14764; NM_015343; NM_ .
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors. SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • 200692_ 9B (mortalin- NM_0041 s_at 2) 34 0.3754 0.01 -0.0131 0.4035 0.009 -0.008 0.1072 -0.2859 0.0815 -0.3805 eukaryotic translation
  • 200705_ elongation NMJ 019 s_at factor 1 beta 2 59 0.4497 -0.0883 0.1137 0.3405 -0.0782 0.0696 0.0634 -0.169 0.0668 -0.3117 protein tyrosine
  • Table 6 Group of 1645 genes that are differentially expressed in. healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors. SLE patients (lupus score), RA patients ⁇ and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors. SLE patients (topes score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients. and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, i 3LE patients (lupus score), RA patients, and WG patients *
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.-
  • 201328_ homolog 2 at (avian) A ALL5577555500 ⁇ 9 -0.5219 0.0647 -0.0648 0.4312 0.0567 -0.0504 -0.0912 0.2432 -0.0848 0.3956 v-ets
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients. and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients. and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (hiptis score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients. and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors. SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients *
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLB patients (lupus soore), RA patients. and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors. SLE patients (lupus score), RA patients, and WG patients.
  • TaWe 6 Group of 1645 genes that are differentially expressedia healthy d ⁇ n ⁇ r ⁇ , SLE pafeats (luptts score) * RA patients and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in liealfhy donors * SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors » SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors* SLE patients (lupus score), RA patients, and WG patients. ⁇
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients. "
  • TaMe 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus scored RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WO patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (tup ⁇ ts score), RA patients, and, WG patients.
  • Table 6 Group of 1645 genes that are differential y expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors. SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors. SLE patients (hipus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLB patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed i ⁇ i healthy donors. SLB patients (lupus score), RA patients, aacl WG patients *
  • Table 6 Group of 1645 genes that are differentially expressed in liealtliy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLB patients (lupus score), RA patients, and WG patients. ⁇
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (tojras score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score),, RA patients, and WG patients *
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLB patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients ? and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (luptis score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed iii healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • G protein gamma 11 tyrosylprotein
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donorSj SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SJLE patients (lupus score), RA patients., and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed unhealthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • NM_0030 s_at member 5 39 -0.3123 0.022 -0.2752 0.5301 0.0202 -0.018 -0.1254 0.3343 -0.1096 0.5114
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • alpha non A4 s at component of BG260394 0.4849 -0.1741 -0.1119 0.0693 -0.1604 0.1426 -0.0664 0.177 -0.0135 0.063
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients. and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • CD52 antigen (CAMPATH-I antigen) /// CD52 antigen
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • ring finger NM_0072 s_at protein 24 19 -0.8744 0.2582 0.1358 0.0874 0.2261 -0.201 0.0479 -0.1277 -0.0159 0.0743
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), MA patients.. and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy d ⁇ n ⁇ r ⁇ , SLE patients (lupus score), RA patients,, and WG patients,
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), JRA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLB patients (Itjpus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients * and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors. SLE patients (hipm score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors , SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed ia healthy d ⁇ aots, SLE patients (tapis score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • HMG- AW02735 x_at box 9 0.2419 0.0419 0.1412 0.4985 0.0377 -0.0335 0.1376 -0.3669 0.1025 -0.4782
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus se ⁇ re) > RA patients, and WG patients. ,
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients. and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors , SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors. SEE patients (lupus score), RA patients, and WG patients.
  • Table 6 Group of 1645 genes that are differentially expressed in healthy donors, SLB patients (lupus score), RA patients, and WG patients.

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Abstract

La présente invention a trait à des gènes et leurs modèles d'expression, les modèles d'expression étant associés à des maladies auto-immunes, notamment le lupus érythémateux systémique (SLE), et la granulomatose de Wegener, l'angéite ANCA+ granulomateuse de Wegener (WG). L'invention a trait à un groupe de 1645 gènes et une pluralité de sous-groupes des 1645 gènes dont les modèles d'expression sont utiles dans des procédés d'identification de maladies auto-immunes, de diagnostic différentiel de maladie auto-immune, notamment le SLE, et la classification de maladies, telles que le SLE et la WG en sous-groupes de maladies qui sont associées à l'activité morbide. L'invention a également trait $ des procédés permettant la différenciation de SLE d'autres maladies auto-immunes. L'invention a également trait en outre à un procédé permettant la prédiction de poussées actives de SLE par l'analyse du modèle d'expression d'un groupe de gènes. L'invention fournit un procédé rapide, précis et peu coûteux pour le suivi continu de patients atteints de SLE durant toute leur vie pour la prédiction de poussées actives. Enfin, l'invention a trait en outre à une technique rapide, efficace et peu coûteuse permettant la détection de lupus induit par la médication.
EP05786543A 2004-08-13 2005-08-12 Marqueurs pour la détection de maladies auto-immunes Withdrawn EP1789798A4 (fr)

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PL2327792T3 (pl) * 2005-08-05 2014-03-31 Genentech Inc Sposoby i kompozycje do wykrywania zaburzeń autoimmunologicznych
ES2503621T3 (es) * 2006-04-24 2014-10-07 Genentech, Inc. Métodos para detectar trastornos autoinmunitarios
BRPI0719912A2 (pt) * 2006-12-06 2014-03-04 Medimmune Llc Método para tratar lupus eritematoso sistêmico, e, método para reduzir elevações passageiras de índice de atividade da doença lupus eritematoso sistêmico
WO2008091708A2 (fr) * 2007-01-25 2008-07-31 Source Precision Medicine, Inc. Etablissement de profils de l'expression des gènes pour identifier, suivre et traiter le lupus érythémateux
US20100273671A1 (en) * 2007-03-01 2010-10-28 Universite Catholique De Louvain Method for the determination and the classification of rheumatic conditions
ES2809171T3 (es) 2008-01-18 2021-03-03 Harvard College Métodos para detectar distintivos de enfermedades o afecciones en fluidos corporales
CA2806304A1 (fr) 2010-07-23 2012-01-26 President And Fellows Of Harvard College Methodes de depistage de maladies ou d'affections prenatales ou liees a la grossesse
SG10201505723UA (en) 2010-07-23 2015-09-29 Harvard College Methods for detecting signatures of disease or conditions in bodily fluids
CN103124795A (zh) 2010-07-23 2013-05-29 哈佛大学校长及研究员协会 利用吞噬细胞检测疾病或病症的方法
AU2011280997A1 (en) 2010-07-23 2013-02-28 President And Fellows Of Harvard College Methods of detecting autoimmune or immune-related diseases or conditions
WO2013036833A1 (fr) * 2011-09-09 2013-03-14 Mayo Foundation For Medical Education And Research Détection de démence fronto-temporale et de sclérose latérale amyotrophique
EP2965086A4 (fr) 2013-03-09 2017-02-08 Harry Stylli Procédés de détection du cancer de la prostate
WO2014164366A1 (fr) 2013-03-09 2014-10-09 Harry Stylli Procédés de détection de cancer
EP3693742B1 (fr) 2014-09-11 2022-04-06 Harry Stylli Procédés pour détecter le cancer de la prostate
CN106520970B (zh) * 2016-11-24 2018-08-07 汕头大学医学院第一附属医院 用于诊断脑卒中的标志物

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