**Application of Novel Quantitative Proteomic Technologies to Identify New Serological Biomarkers in Autoimmune Diseases**

Soyoung Lee, Satoshi Serada, Minoru Fujimoto and Tetsuji Naka *National Institute of Biomedical Innovation, Laboratory of Immune Signal Japan* 

#### **1. Introduction**

222 Autoimmune Disorders – Current Concepts and Advances from Bedside to Mechanistic Insights

Svejgaard, A. (2008) The immunogenetics of multiple sclerosis. Immunogenetics, Vol.60,

Taniyama, M.; Maruyama, T.; Tozaki, T.; Nakano, Y. & Ban, Y. (2010) Association of PTPN22

Tavares, R.M.; Turer, E.E.; Liu, C.L.; Advincula, R.; Scapini, P.; Rhee, L.; Barrera, J.; Lowell,

Thrower, B.W. (2007) Clinically isolated syndromes: predicting and delaying multiple

Tsai, S.J.; Sen, U.; Zhao, L.; Greenleaf, W.B.; Dasgupta, J.; Fiorillo, E.; Orrú, V.; Bottini, N. &

Valdes, A.M. & Thomson, G. (2006). Several loci in the HLA class III region are associated

Viken, M.K.; Blomhoff, A.; Olsson, M.; Akselsen, H.E.; Pociot, F.; Nerup, J.; Kockum, I.;

Villano, M.J.; Huber, A.K.; Greenberg, D.A.; Golden, B.K.; Concepcion, E. & Tomer, Y. (2009)

Werner, S.L.; Barken, D. & Hoffmann, A. (2005) Stimulus specificity of gene expression

Wertz, I.E.; O'Rourke, K.M.; Zhou, H.; Eby, M.; Aravind, L.; Seshagiri, S.; Wu, P.; Wiesmann,

Williams, A.J.; Bingley, P.J.; Moore, W.P. & Gale, E.A. (2002) Islet auto-Abs, nationality and

Yamaji, K.; Ikegami, H.; Fujisawa, T.; Noso, S.; Nojima, K.; Babaya, N.; Itoi-Babaya, M.;

Type I diabetes. Diabetologia, Vol.45, No.2 (February 2002) ISSN 217-23 Witas, H.W.; Jedrychowska-Dańska, K. & Zawicki, P. (2010) Changes in frequency of IDDM-

signaling. , Nature. Vol. 430, No.7000 (August 2004) ISSN 694-9

sclerosis. Neurology, Vol.68, No.24 (June 2007) ISSN S12-5

(March 2010)

No.6 (June 2008) ISSN 275-86

(August 2010) ISSN 181-91

2009) ISSN 4838-45

323-33

Vol.71, No.8 (August 2010) ISSN 795-8

Vol.11, No.1, (February 2006) ISSN 46-52

No.5742 (September 2005) ISSN 1857-61

metabolism, Vol.94, No.4 (April 2009) ISSN 1458-66

immunogenetics, Vol.37, No.3 (June 2010) ISSN 155-8

York Academy of Sciences, (October 2006) ISSN 114-7

Paltsev (2010) On the prospects of preclinical diagnostics within the objectives of preventive and predictive medicine. Efferent and Physico-Chemical medicine.;

haplotypes with type 1 diabetes in the Japanese population. Human immunology,

C.A.; Utz, P.J.; Malynn, B.A & Ma, A. (2010) The ubiquitin modifying enzyme A20 restricts B cell survival and prevents autoimmunity. Immunity, Vol.33, No.2

Chen, X.S. (2009) Crystal structure of the human lymphoid tyrosine phosphatase catalytic domain: insights into redox regulation. Biochemistry, Vol.48, No.22 (June

with T1D risk after adjusting for DRB1-DQB1. Diabetes, obesity & metabolism,

Cambon-Thomsen, A.; Thorsby, E.; Undlien, D.E. & Lie, B.A. (2009) Reproducible association with type 1 diabetes in the extended class I region of the major histocompatibility complex. Genes and immunity, Vol.10, No.4 (June 2009) ISSN

Autoimmune thyroiditis and diabetes: dissecting the joint genetic susceptibility in a large cohort of multiplex families. The Journal of clinical endocrinology and

programs determined by temporal control of IKK activity. Science, Vol.309,

C.; Baker, R.; Boone, D.L.; Ma, A.; Koonin, E.V. & Dixit, V.M. (2004) Deubiquitination and ubiquitin ligase domains of A20 downregulate NF-kappaB

gender: a multinational screening study in first-degree relatives of patients with

associated HLA DQB, CTLA4 and INS alleles. International journal of

Kobayashi, M.; Hiromine, Y.; Makino, S. & Ogihara. T. (2006). Contribution of class III MHC to susceptibility to type 1 diabetes in the NOD mouse. Annals of the New Autoimmune diseases comprise a wide variety of systemic or organ-specific inflammatory diseases, characterized by aberrant activation of immune cells that target self tissues due to misrecognizing tissue-derived proteins as foreign antigens (Hueber and Robinson, 2006; Prince, 2005). The prevalence of autoimmune diseases is approximately 2,000 ~ 3,000 per 100,000, although the prevalence varies depending on the diseases, ethnic groups and regions (Prieto and Grau, 2010). The etiology and exact pathogenesis of autoimmune diseases remain poorly understood. However, both genetic factors and environmental triggers are profoundly involved in the pathogenesis of autoimmune diseases. Notably, clinical manifestations of autoimmune disease may be different among patients, even though they have the same diagnosis, depending on the affected organs of each patient. Therefore, careful evaluation of the clinical manifestations combined with the examination of laboratory tests is required for proper diagnosis of autoimmune diseases and subsequent monitoring of the disease activity during therapy. In addition, therapeutic choices for these diseases have been limited so far and conventional therapeutics include non-steroidal antiinflammatory drugs (NSAID), glucocorticoids, cytotoxic drugs and disease modifying anti rheumatoid drugs (DMARDs). For these reasons, autoimmune diseases have been considered to be intractable and the goal of the treatment is to control disease activity rather than to achieve remission or cure.

Recently, however, the advent of biological agents has led to the marked improvement in the treatment of rheumatoid arthritis (RA) and other inflammatory autoimmune diseases. These agents greatly contribute to improve health-related quality or daily life of patients with autoimmune diseases (Han et al., 2007; Keystone et al., 2008; Laas et al., 2009; Strand and Singh, 2007). Nevertheless, biological agents are not effective for all patients with autoimmune diseases and current biomarkers are not helpful to select an effective biological agent for individual patients. In addition, conventional inflammatory biomarkers are often inadequate to evaluate the disease activity in patients treated with biological agents. Thus, there is a growing need for the development of new biomarkers that can predict individual treatment response before starting biological therapy and evaluate the disease activity and therapeutic efficacy during therapy. In this chapter, we first outline the clinical usage and

Application of Novel Quantitative Proteomic Technologies to

Table 1. Summary of biological agents

Identify New Serological Biomarkers in Autoimmune Diseases 225

Every biological agent used in clinics today has its own specific targets and can be grouped as follows according to its aims: 1) tolerance induction, 2) inhibition of MHC, antigen, and T cell receptor interaction, 3) Inhibition of cellular function and cell-cell interaction, 4) Interference with cytokines, 5) apoptosis (Table 1). Among them, the anticytokine biological

AS: Ankylosing spondylitis, CAPS: Cryopri

Rheumatology, 6th ed. 2011, Saunders)

n-associated periodic syndrome, CD: Crohn's disease, ds-DNA: double strand-DNA,

IBD: Inflammatory bowel disease, JIA: Juvenile idiopathic arthritis, mAb: Monoclonal antibody, Ps: Psoriasis, PsA: Psoriatic

arthritis, RA: Rheumatoid arthritis, sJIA: Systemic-typed JIA, SLE: Systemic lupus erythematosus. (Textbook of Pediatric

current understanding of biological agents for the treatment with autoimmune diseases and then describe our attempt to identify new biomarkers in autoimmune diseases by taking advantage of a new proteomic approach.
