Skip to main content
  • Review
  • Published:

Autoantibody profiling for the study and treatment of autoimmune disease

Abstract

Proteomics technologies enable profiling of autoantibody responses using biological fluids derived from patients with autoimmune disease. They provide a powerful tool to characterize autoreactive B-cell responses in diseases including rheumatoid arthritis, multiple sclerosis, autoimmune diabetes, and systemic lupus erythematosus. Autoantibody profiling may serve purposes including classification of individual patients and subsets of patients based on their 'autoantibody fingerprint', examination of epitope spreading and antibody isotype usage, discovery and characterization of candidate autoantigens, and tailoring antigen-specific therapy. In the coming decades, proteomics technologies will broaden our understanding of the underlying mechanisms of and will further our ability to diagnose, prognosticate and treat autoimmune disease.

Introduction

'Proteomics' is the large-scale study of expression, function and interactions of proteins [1]. Recent advances in the field spawned miniaturized proteomics technologies capable of parallel detection of thousands of different antigens using submicroliter quantities of biological fluids. This review will focus on proteomics technologies that enable characterization of autoantibody responses (Table 1).

Table 1 Proteomics technologies for autoantibody profiling: selected published studies

Early immunoassays capable of multiplex analysis include: ELISAs, fluorescence-based immunoassays, and radio-immunoassays performed in microtiter plates; arrays of peptides synthesized on plastic pins [1, 2]; western blot analysis; and genetic plaque-based and colony-based assays. All of these technologies are limited by requirements for relatively large quantities of reagents and of clinical samples. Genetic plaque-based and colony-based assays are further limited by incomplete addressability; DNA sequence analysis is required to determine the identity of the antigens at each location on the array.

Ekins as well as Fodor et al. proposed, in the late 1980s, the use of miniaturized and addressable immunoassays, including 'multianalyte microspot immunoassays' and photolithography-generated peptide arrays [3, 4]. Another major advance was the development of robotic printing devices by Patrick Brown and colleagues for precise deposition of cDNA to fabricate DNA microarrays [5]. These devices are inexpensive and widely available, and several groups recently extended their use to generate ordered arrays of proteins [6, 7]. Major advances have been made in the past 2 years towards development and application of miniaturized, addressable arrays of proteins, peptides and other biomolecules.

Miniaturized proteomics technologies for autoantibody profiling

Although proteomics is in its infancy, a diverse and powerful set of proteomics technologies is under rapid development (Table 1). Planar surface arrays currently offer the greatest per-array complexities, but are limited by their methods of binding autoantigens and of drying at the time of array production, which can distort and/or sterically interfere with immunologic epitopes. A variety of fluid-phase bead, tag, nanoparticle, and microfluidic systems, which generally utilize minimally disruptive methods to label antigens, are under development.

Arrays of addressable beads

Bead arrays enable multiplexed analysis of biomolecular interactions. The LabMAPâ„¢ system of Luminex (Austin, Texas, USA) utilizes 64 sets of spectrally resolvable fluorescent beads. Each set can be conjugated to a distinct antigen (or antibody or oligonucleotide). Following incubation with the test sample, analysis is performed using a flow cytometer. Further multiplexing is achieved by analysis of multiple wells in microtiter plates, each with beads conjugated to different sets of antigens.

Arrays of addressable tags

The eTAGâ„¢ assay of Aclara (Mountain View, California, USA) utilizes eTAGâ„¢ reporters that are fluorescent labels with unique and well-defined electrophoretic mobilities. Each eTAGâ„¢ label is coupled to an antigen (or another biological probe) via cleavable linkages. When an autoantibody binds to an eTAGâ„¢ reporter-labeled antigen, the coupling linkage is cleaved and the eTAGâ„¢ is released. Mixtures of eTAGsâ„¢ are readily separated and analyzed by capillary electrophoresis.

Arrays of addressable nanoparticles

SurroMed (Mountain View, California, USA) is developing a system based on addressable multimetal microrods intrinsically encoded with submicrometer stripes [8], termed Nanobarcodesâ„¢ particle technology. Using three different metals, 80,000 distinctive striping patterns are possible [8]. This far exceeds the complexity of fluorescence-based bead and tag systems.

Microfluidics approaches

Microfluidics utilizes microchannels for analysis of antigen–autoantibody interactions. Small quantities of biomolecules are separately introduced into a network of microchannels and subjected to electrokinetic, electro-osmotic, electrophoretic or pressure-driven flow, mixing and separation. Binding events, reflected by changes in mobility, are measured by UV absorption or fluorescent detection. Real-time millisecond quantitation of binding kinetics and detection of low-affinity interactions are among the important advantages of this system.

Arrays of living cells

Several groups have described arrays of living cells expressing transformed or transfected cDNA [9, 10]. Such systems could be easily adapted for autoantibody profiling.

Arrays on planar surfaces

Methods to fabricate arrays on planar surfaces include stamping, ink jetting, capillary spotting, contact printing, and in situ synthesis. Commonly used solid supports include: nitrocellulose, nylon and polyvinylidene difluoride membranes; poly-L-lysine-coated, silane-treated, and other derivatized glass microscope slides; and glass microscope slides coated with gelatin, acrylamide and other coatings.

Membrane-based systems include low-density dot blot arrays on nitrocellulose membranes [11], autoantigens electrophoretically separated prior to transfer to membranes [12], and spotting of cDNA expression-library-produced proteins onto polyvinylidene difluoride filters [13, 14]. The generation of arrays of polypeptides derived from cDNA expression libraries by Büssow and colleagues provides an elegant system for autoantigen discovery [13, 14]. cDNAs are expressed and their protein products purified in vitro, following which purified proteins are robotically arrayed. On identification of autoantibody targets, their corresponding cDNAs are readily sequenced to genetically identify autoantigens. Walter et al. describe use of one such cDNA library, a human fetal brain cDNA expression library, for autoantigen discovery in inflammatory bowel disease [15].

Other workers are developing protein arrays on derivatized microscope slides. Joos et al. have demonstrated sensitive and specific autoantibody detection using microarrays containing serial dilutions of 18 antigens [16]. Haab et al. generated protein arrays to characterize 115 purified antigen–antibody pairs, demonstrating that 50% of the arrayed antigens and 20% of the arrayed antibodies where detectable when immobilized [7]. Some cognate ligands were detected at concentrations as low as 1 ng/dl [7].

We have modified and refined the experimental protocol introduced by Haab et al. [7] to develop spotted antigen arrays for analysis of autoantibody responses [17]. We applied this technology to analyze the autoreactive B-cell response in patients with autoimmune diseases including systemic lupus erythematosus (SLE), scleroderma, and mixed connective tissue disease [17].

Our antigen array technology utilizes a robotic arrayer to attach proteins, protein complexes, peptides, nucleic acids, and other biomolecules in an ordered array on poly-L-lysine-coated microscopic slides (Fig. 1) [17]. Approximately 1 nl of solution containing 200 pg antigen is deposited on each array to produce antigen features measuring 100–200μm in diameter. Individual arrays are incubated with serum from patients or controls, followed by fluorescently labeled secondary antibody. We typically use 1:150 dilutions of human or animal serum to probe arrays, requiring 2 μl serum per array under standard protocols and only 0.15 μl serum per array when employing cover slips [17]. Other biological fluids such as cerebrospinal fluid, synovial fluid, and tissue eluates may also be used (our unpublished observations).

Figure 1
figure 1

The 'connective tissue disease' array. A 48-feature collage derived from a 1536-feature 'connective tissue disease' array probed with serum from a patient with systemic lupus erythematosus (SLE) is presented. This array demonstrates specific detection of two representative autoantibody reactivities, against Ro52 (upper center box) and double-stranded DNA (dsDNA, lower right box). Antibodies against Candida skin test antigens (lower center box) are also detected, and serve as a positive control. This collage contains four features representing the reactive antigens (boxed) and control antigens (not boxed). Arrays were produced using a robotic microarrayer to attach putative connective tissue disease autoantigens (listed in text) to poly-L-lysine-coated microscopic slides. The depicted array was incubated with a 1:150 dilution of serum derived from a patient with SLE and with ELISA-confirmed reactivity against Ro and DNA. Antibody binding was detected by incubation with Cy-3-labeled antihuman IgG/IgM secondary antibody. Marker spots (spotted Cy-3-labeled IgG, left box) are used to orient the arrays. Detailed protocols for production, probing, and scanning antigen arrays are presented in our earlier work [17] and online [21].

Arrays are scanned using a fluorescence-based digital scanning device. Algorithms are available for nearest-neighbor (cluster) [18] and statistical analysis [19] of the data. Detailed protocols are presented both in our earlier work [17] and online [20]. Information for construction of robotic arrayers is also available [21].

Antigen arrays proved to be fourfold to eightfold more sensitive than conventional ELISA analysis for detection of autoantibodies specific for five recombinant autoantigens [17]. Moreover, antigen arrays demonstrated linear detection of antibody concentrations over a 3-log range [17].

Specialized proteomes for specific autoimmune diseases

We are developing specialized arrays representing the 'proteomes' of the tissue targets in various autoimmune diseases.

'Connective tissue disease' arrays

Our 'connective tissue disease' arrays contain 200 distinct proteins, peptides, nucleic acids, and protein complexes targeted in a host of autoimmune diseases, including SLE, polymyositis, limited and diffuse scleroderma, primary biliary sclerosis, and Sjögren's disease (Fig. 1) [17]. Specific antigens include Ro, La, histone proteins, Jo-1, heterogeneous nuclear ribonucleoproteins (hnRNPs), small nuclear ribonucleoproteins, Smith ribonucleoproteins (Sm/RNP), topoisomerase I, centromere protein B, thyroglobulin, thyroid peroxidase, RNA polymerase, cardiolipin, pyruvate dehydrogenase, serine–arginine splicing factors, and DNA.

'Synovial proteome' arrays

We developed 'synovial proteome' arrays to study autoimmune arthritis involving synovial joints, including rheumatoid arthritis (RA) and its animal models. Our 'synovial proteome' arrays contain 650 candidate RA autoantigens, including deiminated fibrin, citrulline-modified filaggrin and fibrinogen peptides, vimentin, the endoplasmic chaperone BiP, glucose-6-phosphate isomerase, hnRNP A2/B1, collagens and overlapping peptides derived from several of these proteins.

'Myelin proteome' arrays

Our 'myelin proteome' arrays contain 500 proteins and peptides derived from the myelin sheath, the target of the autoimmune response in multiple sclerosis and in experimental autoimmune encephalomyelitis (EAE). These myelin antigens include myelin basic protein, proteolipid protein, myelin-associated glycoprotein, myelin oligodendrocytic glycoprotein, golli-myelin basic protein, oligodendrocyte-specific protein, cyclic nucleotide phosphodiesterase and overlapping peptides derived from these proteins. We are utilizing our 'myelin proteome' arrays to characterize the autoantibody response in EAE serum, multiple sclerosis patient serum and cerebral spinal fluid, and to guide selection of antigen-specific therapies in relapsing EAE [22].

'Islet cell proteome' arrays

We are constructing 'islet cell proteome' arrays containing glutamic acid decarboxylase, IA-2, insulin and additional candidate autoantigens in insulin-dependent diabetes mellitus (IDDM).

Applications for proteomics profiling of autoantibody responses

Autoantibody profiling for diagnosis

Autoantibodies have diagnostic utility for several autoimmune diseases. Such diseases include myasthenia gravis (antiacetylcholine receptor antibody), Grave's disease (antithyroid hormone receptor antibody), and SLE (combination of antinuclear antibodies, plus anti-DNA or anti-Sm antibodies). Furthermore, in T-cell-mediated IDDM, the presence of combinations of autoantibodies against at least two islet antigens, including insulin, glutamic acid decarboxylase, and IA-2, are diagnostic for or predictive of future development of IDDM [23]. The presence of autoantibodies against a single islet antigen has minimal clinical value. The clinical utility of autoantibodies in IDDM suggests that autoantibody profiles may have diagnostic utility for other T-cell-mediated diseases, such as RA and multiple sclerosis.

Monitoring epitope spreading: potential prognostic value

Intermolecular and intramolecular epitope spreading of the autoreactive B-cell response is associated with progression to overt clinical disease in human and murine SLE [24, 25] and in IDDM [23]. Proteomics technologies are ideally suited to monitoring epitope spreading. Epitope spreading of the autoantibody response may represent a common harbinger of more severe and progressive autoimmunity, providing the clinician with valuable prognostic information to guide the use of nonspecific disease-modifying therapies.

Monitoring autoantibody isotype usage

Spotted antigen microarrays can identify antigen-specific autoantibody isotypes [17]. Th1-type immune responses, associated with production of interferon-γ and interleukin-12, generate antibodies of isotypes capable of fixing complement and causing tissue injury [26]. The ability to characterize isotype usage may facilitate the identification of offending autoantigens, based on determination of autoantigens against which autoantibodies of pathogenic isotypes are directed. Moreover, microarray isotype analysis may provide insight into both B-cell and T-cell autoimmunity because not only T cells, but also effector B cells, have been implicated in the reciprocal regulation of polarized Th1 versus Th2 cytokine production [27]. Therapeutic deviation of immune responses from Th1 to Th2 cytokine production has been associated with efficacious treatment of Th1-mediated immune disease [28, 29].

Autoantigen discovery and characterization

Proteomics technologies can be applied to discover novel autoantigens utilizing cDNA expression libraries [13, 14], peptide libraries, or arrayed fractions of autoimmune-target tissues. Once candidate autoantigens are identified, proteomics technologies can rigorously characterize the sensitivity and specificity of autoantibodies directed against candidate antigens in cohorts of autoimmune and control patients. Of note, post-translational modifications of antigens are amenable to detection using our antigen arrays and other proteomics technologies. This is important because such modifications are strongly associated with autoimmune diseases including SLE and RA [30–32].

Guiding development and selection of antigen-specific therapy

In addition to proteomics monitoring of epitope spreading and isotype usage to gauge need for nonspecific disease-modifying therapies (already described), determination of the specificity of the autoantibody response may enable tailored antigen-specific therapy. Such antigen-specific therapies can be peptide-based or protein-based tolerizing therapies. Alternatively, they can be specific DNA tolerizing vaccines, a strategy we termed 'reverse genomics' [22]. We discuss use of the autoantibody response to drive antigen-specific therapy elsewhere [22, 33].

Future directions: challenges and limitations

Although we have made significant progress developing proteomics technologies, major hurdles and significant work remain. Extensive validation of array results, using thousands of sera already characterized for antibody specificities by standard methods, will be essential for regulatory approval and entry into routine clinical practice.

A limitation of addressable microarray systems results from the attachment of antigens to surfaces, beads, nanoparticles, or tags, which may alter immunologic epitopes. Certain autoantigens are not amenable to detection using poly-L-lysine-coated glass slides [7, 17]. We are addressing this disadvantage using alternative surface chemistries, and linkers to orient and to serve as spacers between antigens and the surface, particle, or tag. Bead and tag systems are currently limited by the relatively small numbers of addressable elements available.

Autoantibody profiling using antigen microarray technology does not provide direct information about the specificity of the T cells that mediate autoimmunity. Although there are examples of discordance of the fine peptide epitope specificity of the autoreactive T-cell and B-cell responses, there is a high degree of concordance between autoreactive B-cell and T-cell responses at the macromolecular level [23, 34]. We believe the specificity of the autoantibody response is predictive of the specificity of the overall autoimmune response at the level of whole autoantigens. Further studies will be necessary to determine whether this powerful and enabling hypothesis is, in fact, valid.

Conclusion

The development of miniaturized proteomics technologies heralds the beginning of an era of multiplex, high-throughput analysis of autoantibody specificities and isotype usage. Spotted antigen arrays on derivatized microscope slides offer a fluorescence-based proteomics platform utilizing simple protocols and widely available equipment. In the future, fluid-phase arrays based on addressable particles and tags are likely to supplant planar arrays, due to their lower propensity to distort and to sterically interfere with immunologic epitopes. We anticipate that proteomics monitoring of autoantibody responses will have a major impact on the diagnosis, monitoring, and therapy of autoimmune disease.

Abbreviations

EAE:

experimental autoimmune encephalomyelitis

ELISA:

enzyme-linked immunosorbent assay

hnRNP:

heterogeneous nuclear ribonucleoproteins

IDDM:

insulin-dependent diabetes mellitus

RA:

rheumatoid arthritis

SLE:

systemic lupus erythematosus

Sm/RNP:

Smith ribonucleo-proteins

Th:

T helper cell.

References

  1. Geysen HM, Meloen RH, Barteling SJ: Use of peptide synthesis to probe viral antigens for epitopes to a resolution of a single amino acid. Proc Natl Acad Sci USA. 1984, 81: 3998-4002.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  2. James J, Harley J: Linear epitope mapping of an Sm B/B' polypeptide. J Immunol. 1992, 148: 2074-2079.

    PubMed  CAS  Google Scholar 

  3. Ekins RP: Multi-analyte immunoassay. J Pharm Biomed Anal. 1989, 7: 155-168. 10.1016/0731-7085(89)80079-2.

    Article  PubMed  CAS  Google Scholar 

  4. Fodor SP, Read JL, Pirrung MC, Stryer L, Lu AT, Solas D: Light-directed, spatially addressable parallel chemical synthesis. Science. 1991, 251: 767-773.

    Article  PubMed  CAS  Google Scholar 

  5. Schena M, Shalon D, Davis RW, Brown PO: Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science. 1995, 270: 467-470.

    Article  PubMed  CAS  Google Scholar 

  6. MacBeath G, Schreiber SL: Printing proteins as microarrays for high-throughput function determination. Science. 2000, 289: 1760-1763.

    PubMed  CAS  Google Scholar 

  7. Haab BB, Dunham MJ, Brown PO: Protein microarrays for highly parallel detection and quantitation of specific proteins and antibodies in complex solutions. Genome Biol. 2001, 2: research0004-10.1186/gb-2001-2-2-research0004.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  8. Nicewarner-Pena SR, Freeman RG, Reiss BD, He L, Pena DJ, Walton ID, Cromer R, Keating CD, Natan MJ: Submicrometer metallic barcodes. Science. 2001, 294: 137-141. 10.1126/science.294.5540.137.

    Article  PubMed  CAS  Google Scholar 

  9. Ziauddin J, Sabatini DM: Microarrays of cells expressing defined cDNAs. Nature. 2001, 411: 107-110. 10.1016/S0370-2693(97)01015-0.

    Article  PubMed  CAS  Google Scholar 

  10. Uetz P, Giot L, Cagney G, Mansfield TA, Judson RS, Knight JR, Lockshon D, Narayan V, Srinivasan M, Pochart P, Qureshi-Emili A, Li Y, Godwin B, Conover D, Kalbfleisch T, Vijayadamodar G, Yang M, Johnston M, Fields S, Rothberg JM: A comprehensive analysis of protein–protein interactions in Saccaromyces cerevisiae. Nature. 2000, 403: 623-627. 10.1038/35001009.

    Article  PubMed  CAS  Google Scholar 

  11. Ge H: UPA, a universal protein array system for quantitative detection of protein–protein, protein–DNA, protein–RNA, and protein–ligand interactions. Nucleic Acids Res. 2000, 28: e3i-vii. 10.1093/nar/28.2.e3.

    Article  Google Scholar 

  12. Meheus L, van Venrooij WJ, Wiik A, Charles PJ, Tzioufas AG, Meyer O, Steiner G, Gianola D, Bombardieri S, Union A, De Keyser S, Veys E, De Keyser F: Multicenter validation of recombinant, natural and synthetic antigens used in a single multi-parameter assay for the detection of specific anti-nuclear autoantibodies in connective tissue disorders. Clin Exp Rheumatol. 1999, 17: 205-214.

    PubMed  CAS  Google Scholar 

  13. Büssow K, Cahill D, Nietfeld W, Bancroft D, Scherzinger E, Lehrach H, Walter G: A method for global protein expression and antibody screening on high-density filters of an arrayed cDNA library. Nucleic Acids Res. 1998, 26: 5007-5008. 10.1093/nar/26.21.5007.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Lueking A, Horn M, Eickhoff H, Büssow K, Lehrach H, Walter G: Protein microarrays for gene expression and antibody screening. Anal Biochem. 1999, 270: 103-111. 10.1006/abio.1999.4063.

    Article  PubMed  CAS  Google Scholar 

  15. Walter G, Büssow K, Cahill D, Lueking A, Lehrach H: Protein arrays for gene expression and molecular interaction screening. Curr Opin Microbiol. 2000, 3: 298-302. 10.1016/S1369-5274(00)00093-X.

    Article  PubMed  CAS  Google Scholar 

  16. Joos TO, Schrenk M, Hopfl P, Kroger K, Chowdhury U, Stoll D, Schorner D, Durr M, Herick K, Rupp S, Sohn K, Hammerle H: A microarray enzyme-linked immunosorbent assay for auto-immune diagnostics. Electrophoresis. 2000, 21: 2641-2650. 10.1002/1522-2683(20000701)21:13<2641::AID-ELPS2641>3.3.CO;2-X.

    Article  PubMed  CAS  Google Scholar 

  17. Robinson WH, DiGennaro C, Hueber W, Haab BB, Kamachi M, Dean EJ, Fournel S, Fong D, Genovese MC, Neuman de Vegvar HE, Skriner K, Hirschberg DL, Morris RI, Muller S, Pruijn GJ, van Venrooij WJ, Smolen JS, Brown PO, Steinman L, Utz PJ: Autoantigen microarrays for multiplex characterization of autoantibody responses. Nat Med. 2002, 8: 295-301. 10.1038/nm0302-295.

    Article  PubMed  CAS  Google Scholar 

  18. Emest Orlando Lawrence Berkeley National Laboratory. [http://rana.lbl.gov]

  19. Stanford University School of Medicine. [http://www-stat.Stanford.edu/~tibs/]

  20. Stanford University School of Medicine. [http://www.Stanford.edu/group/antigenarrays]

  21. Stanford University School of Medicine. [http://cmgm.Stanford.edu/pbrown]

  22. Robinson WH, Garren H, Utz PJ, Steinman L: Reverse genomics: proteomics to drive DNA tolerizing vaccines to treat autoimmune disease. Clin Immunol. 2002,

    Google Scholar 

  23. Pietropaolo M, Eisenbarth GS: Autoantibodies in human diabetes. Curr Dir Autoimmun. 2001, 4: 252-282.

    Article  PubMed  CAS  Google Scholar 

  24. Craft J, Fatenejad S: Self antigens and epitope spreading in systemic autoimmunity. Arthritis Rheum. 1997, 40: 1374-1382.

    Article  PubMed  CAS  Google Scholar 

  25. James J, Harley J: B-cell epitope spreading in autoimmunity. Immunol Rev. 1998, 164: 185-200.

    Article  PubMed  CAS  Google Scholar 

  26. Abbas A, Murphy K, Sher A: Functional diversity of helper T lymphocytes. Nature. 1996, 383: 789-793. 10.1038/383787a0.

    Article  Google Scholar 

  27. Harris D, Haynes L, Sayles P, Duso D, Eaton S, Lepak N, Johnson L, Swain S, Lund F: Reciprocal regulation of polarized cytokine production by effector B and T cells. Nat Immunol. 2000, 1: 475-482. 10.1038/82717.

    Article  PubMed  CAS  Google Scholar 

  28. Raz I, Elias D, Avron A, Tamir M, Metzger M, Cohen IR: Beta-cell function in new-onset type 1 diabetes and immunomodulation with a heat-shock protein peptide (DiaPep277): a randomised, double-blind, phase II trial. Lancet. 2001, 358: 1749-1753. 10.1016/S0140-6736(01)06801-5.

    Article  PubMed  CAS  Google Scholar 

  29. Gran B, Tranquill LR, Chen M, Bielekova B, Zhou W, Dhib-Jalbut S, Martin R: Mechanisms of immunomodulation by glatiramer acetate. Neurology. 2000, 55: 1704-1714.

    Article  PubMed  CAS  Google Scholar 

  30. Casciola-Rosen L, Andrade F, Ulanet D, Wong W, Rosen A: Cleavage by granzyme B is strongly predictive of autoantigen status. Implications for initiation of autoimmunity. J Exp Med. 1999, 190: 815-826. 10.1084/jem.190.6.815.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  31. Utz PJ, Gensler TJ, Anderson P: Death, autoantigen modifications, and tolerance. Arthritis Res. 2000, 2: 101-114. 10.1186/ar75.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  32. van Venrooij WJ, Pruijn GJ: Citrullination: a small change for a protein with great consequences for rheumatoid arthritis. Arthritis Res. 2000, 2: 249-251. 10.1186/ar95.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  33. Robinson WH, Steinman L, Utz PJ: Proteomics technology for the study of autoimmune disease. Arthritis Rheum. 2002, 46: 885-893. 10.1002/art.10129.

    Article  PubMed  CAS  Google Scholar 

  34. Datta SK: Production of pathogenic antibodies: cognate interactions between autoimmune T and B cells. Lupus. 1998, 7: 591-596. 10.1191/096120398678920703.

    Article  PubMed  CAS  Google Scholar 

  35. Fulton RJ, McDade RL, Smith PL, Kienker LJ, Kettman JR: Advanced multiplexed analysis with the FlowMetrix system. Clin Chem. 1997, 43: 1749-1756.

    PubMed  CAS  Google Scholar 

  36. He M, Taussig MJ: Single step generation of protein arrays from DNA by cell-free expression and in situ immobilisation (PISA method). Nucleic Acids Res. 2001, 29: e73i-vi. 10.1093/nar/29.15.e73.

    Article  Google Scholar 

  37. Santiago JG, Wereley ST, Meinhart CD, Beebee DJ, Adrian RJ: A particle image velocimetry system for microfluidics. Exp Fluids. 1998, 25: 316-319. 10.1007/s003480050235.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors thank Dr H de Vegvar, J Tom and other members of the Utz and Steinman laboratories for scientific input. This work was supported by NIH K08 AR02133 and an Arthritis Foundation Chapter Grant to WHR, by NIH K08 AI01521, NIH U19 DK61934, an Arthritis Foundation Investigator Award, a Bio-X grant, and a Baxter Foundation Career Development Award to PJU, by NIH/NINDS 5R01NS18235 and NIH U19 DK61934 to LS, and by a James Klinenberg Memorial Fellowship from the Arthritis National Research Foundation to WH.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to William H Robinson.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hueber, W., Utz, P.J., Steinman, L. et al. Autoantibody profiling for the study and treatment of autoimmune disease. Arthritis Res Ther 4, 290 (2002). https://doi.org/10.1186/ar426

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/ar426

Keywords