Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Journal of Laboratory Medicine

Official Journal of the German Society of Clinical Chemistry and Laboratory Medicine

Editor-in-Chief: Schuff-Werner, Peter

Ed. by Ahmad-Nejad, Parviz / Bidlingmaier, Martin / Bietenbeck, Andreas / Conrad, Karsten / Findeisen, Peter / Fraunberger, Peter / Ghebremedhin, Beniam / Holdenrieder, Stefan / Kiehntopf, Michael / Klein, Hanns-Georg / Kohse, Klaus P. / Kratzsch, Jürgen / Luppa, Peter B. / Meyer, Alexander von / Nebe, Carl Thomas / Orth, Matthias / Röhrig-Herzog, Gabriele / Sack, Ulrich / Steimer, Werner / Weber, Thomas / Wieland, Eberhard / Winter, Christoph / Zettl, Uwe K.

IMPACT FACTOR 2018: 0.389

CiteScore 2018: 0.22

SCImago Journal Rank (SJR) 2018: 0.156
Source Normalized Impact per Paper (SNIP) 2018: 0.089

See all formats and pricing
More options …
Volume 38, Issue 2


Laboratory diagnostics of systemic autoimmune diseases – Update 2013

Peter Härle
  • Corresponding author
  • Catholic Medical Center Mainz, Department of Rheumatology, Clinical Immunology and Physical Therapy, Mainz, Germany
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2015-04-16 | DOI: https://doi.org/10.1515/labmed-2014-0021


This article discusses relevant and up-to-date issues for the clinical laboratory concerning arthritis activity and monitoring of rheumatoid arthritis, details for the new disease entity of IgG4-related diseases and Sjogren’s syndrome. The article puts the focus on the data of 2013.

Reviewed publication


Keywords: IgG4-related diseases; rheumatoid arthritis; Sjogren’s syndrome

Rheumatoid arthritis


Clinical observation and clinical examination have always been there in medicine. In addition, the art of medicine, as a concept of experience and intuition, has a high priority in the process of diagnosis and treatment of diseases. It can be assumed that this will not change in the near future. Nevertheless, ever more chemical or technical lab-based tools need to be developed to provide an objective foundation for the art of medicine.

The classification criteria for rheumatoid arthritis were established in 1987 and continue to remain in effect. Clinical observation dominates among these classification criteria, and the presence of a positive rheumatic factor merely represents one additional aspect on an equal footing with the clinical criteria (Figure 1 ACR 1987). Over time, scoring methods have been developed to objectivize disease activity, such as the Disease Activity Score for the 28 most commonly affected joints (DAS28). However, since a purely clinical examination is too coarse for many patients to provide a correct diagnosis of the different varieties of RA or to control treatment involving ever more potent and more expensive drugs, magnetic resonance imaging and power Doppler sonography (by now ubiquitous in medical offices and hospitals) have come to play an important role. These equipment-based methods are suited, in particular, to diagnose chronic rheumatoid arthritis sooner. New equipment-based methods, such as in vivo fluorescence optical imaging, have been added to the arsenal [2]. Also, the classification criteria have changed towards greater objectivity by the addition of laboratory chemical parameters (Figure 1) [3].

Markers of the non-specific, systemic inflammation CRP, ESR and relatively specific markers of rheumatoid arthritis RF and ACPA have been included in the ACR/EULAR 2010 classification criteria. This means that in the current classification criteria, laboratory diagnostics have been given a much higher priority (modified from [1]).
Figure 1

Markers of the non-specific, systemic inflammation CRP, ESR and relatively specific markers of rheumatoid arthritis RF and ACPA have been included in the ACR/EULAR 2010 classification criteria.

This means that in the current classification criteria, laboratory diagnostics have been given a much higher priority (modified from [1]).

This development reflects the clinical and scientific observation that rheumatoid arthritis is a heterogeneous disease. Thus, we distinguish RF positive from RF negative and ACPA positive from ACPA negative variants with different progressions and prognoses. Now, there is also a third option, that of anti-carbamylated protein antibodies (anti-CarP AB). In the coming years, we will certainly gain further insights into this third autoantibody entity. The anti-CarP AB, similar to the anti-CCP AB, seem to have a predictive probability of about 30% for the clinical onset of rheumatoid arthritis in patients with arthralgia within the first year [4]. The level of the antibody titer appears to be independent of this. In addition, the autoantibodies anti-CCP and anti-CarP seem independently to determine the predictive probability of the occurrence of rheumatoid arthritis. This underlines at the present time the hypothesis of three different autoantibody systems in connection with rheumatoid arthritis.

Not only the classification criteria are given additional support by laboratory medicine; therapy control on the basis of disease activity (treat to target) is also receiving increasing support from laboratory chemistry. In the United States, a lab-chemical arthritis activity score is already in use for rheumatoid arthritis, the Multi-Parameter Biomarker Disease Activity Score (MBDS). Perhaps this multi-parameter test will gain importance in Germany as well.

However, for practical purposes, this also means that both the classification and diagnosis, as well as the decision of therapeutic strategy, represent a clearly clinically dominated decision in the context of rheumatoid arthritis. Lab-chemical and imaging methods cannot take the place of the clinical decision process, but support it.

Table 1 gives an overview of the development of classification/diagnostics and therapy control over the last decades. This shows clearly that equipment-based and lab-chemical diagnostics are becoming increasingly more important in routine clinical practice.

Table 1

Experimental (i.e., not yet implemented in clinical routine) laboratory-chemical or equipment-based methods are not shown here.

New laboratory chemical Multi-Biomarker Disease Activity Score (MBDA)

For a more objective assessment of disease activity, a 12-parameter panel of biomarkers was examined as part of the CAMERA study (Table 2), and the results were compared with the previously recognized activity parameter, the DAS28 score, via a biomarker score [5].

Table 2

Listing the biomarkers used in the studies [5–9] and in the Vectra™ DA score (www.Vectra-DA.com).

Before that, the MBDA score had been validated [6]. In the Dutch CAMERA study (Computer Assisted Management in Early RA), patients with early rheumatoid arthritis were evaluated in relation to the treatment response to different treatment algorithms [10]. A classic clinical parameter for arthritis activity in the course of the study was the DAS28-CRP score. This includes the number of swollen joints (SJC=swollen joint count), painful joints (TJC=tender joint count) of 28 joints examined, the CRP value (C-reactive protein) and the patients’ assessment of their general health status (VAS-GH=visual analog scale of general health from 0 to 100 mm). Thus, the DAS28 score contains three relative subjective activity parameters: TJC, SJC and VAS-GH. In addition, 12 biomarkers were identified via ELISA single tests as part of the CAMERA study, which were used to obtain a more objective assessment of disease activity.

The MBDA score is based on the fact that a single marker cannot describe the different pathogenetic factors. By combining different markers that describe the corresponding biological processes in rheumatoid arthritis (Figure 2), the disease activity can be captured better in laboratory tests.

Biological network of rheumatoid arthritis. This shows a biological network of rheumatoid arthritis describing the interactions of the biomarkers of the Vectra™ DA score (modified from www.vectra-da.com, Crescendo Bioscience Clinical Laboratory, 341 Oyster Point Boulevard, South San Francisco, CA 94080).
Figure 2

Biological network of rheumatoid arthritis.

This shows a biological network of rheumatoid arthritis describing the interactions of the biomarkers of the Vectra™ DA score (modified from www.vectra-da.com, Crescendo Bioscience Clinical Laboratory, 341 Oyster Point Boulevard, South San Francisco, CA 94080).

The examination times in the CAMERA study were set to baseline and after 6 months. The parameters obtained are listed in Table 2.

Similar to the DAS28 score, the MBDA score was calculated from the results of the single tests [6]. The MBDA score ranges from 1 to 100 and is classified according to the clinical significance (activity), similar to the DAS28 score, as shown in Table 3.

Table 3

Evaluation of the MBDA score and comparison with clinical compound score DAS28-ESR.

It was possible to find a moderate to good correlation [κ (95% CI)=0.41 (0.21–0.61)] of the DAS28-CRP response to treatment with the 12-parameter MBDA score.

In a continuation of the CAMERA study, data on the correlation of the DAS28-ESR activity score with the MBDA score were presented at the American College of Rheumatology meeting. In this context, monthly data of both scores were correlated with the baseline scores over a period of twelve months. An improvement in the DAS28-ESR correlated well with the MBDA score in both study arms, MTX-only (r=57, p<0.001, n=31) and MTX plus prednisolone (r=57, p<0.002, n=28) [7]. It has been shown, however, that the MBDA score is less sensitive than the DAS28-ESR score. According to Table 4, a DAS28-ESR score must improve by ≥–1.8 points in order to detect a significant improvement in the MBDA score. Changes in the DAS28-ESR score by ≥0.6 are considered to be clinically significant.

Table 4

Monthly, mean change in DAS28-ESR and MBDA scores during the observation period of 12 months of the two study arms MTX and MTX + prednisolone (modified from [7]).

As part of this study, Eastman and colleagues tested a multiplex assay for rheumatoid arthritis with respect to its clinical applicability [8]. In previous studies, the individual biomarkers had been measured separately and compared with clinical scores [5, 6]. The preparation and validation of multiplex assay methods, however, is much more complicated in comparison to individual tests, since each antibody requires different optimal test conditions for the antigen-antibody binding. The advantage of the multiplex assay is that it takes less time and costs less money as opposed to an analysis of all biomarkers, and an analysis of one and the same blood sample. This study looked at precision, parallelism, dynamic range, cross-reactivity and the effect of interference in a 12-biomarker test for the Multiplex Disease Activity algorithm. The test analyses demonstrate very good precision without significant cross-reactivity and interference factors. Based on the properties of 12-biomarker multiplex assay, a stable multiplex test for further clinical trials is available.

The pre-analysis is crucial to the evaluation of the MBDA score [11]. Zhao et al. [11] show that antibody levels and proteins that are not released from cells, such as VCAM-1, SSA and CRP, are relatively robust in the patient’s serum or plasma. However, the pre-analysis of proteins released from cells, such as EGF, VEGF, IL-6, YKL-40 and resistin, is much more susceptible to interference due to pre-analytical conditions. Pre-analysis plays a particularly prominent role in multi-biomarker tests, since errors in pre-analysis can lead to a shift in the clinical significance of the score result.

In practice, pre-analysis is of crucial importance for the MBDA test and the MBDA score calculation (temperature and transport time).

To what extent this test will actually have an additional benefit in the assessment of arthritis activity, is not yet fully understood. Furthermore, the question regarding its value in diagnostic monitoring for predicting a disease phase, erosivity, progression of the disease and disability has not been answered yet. Perhaps the MBDA score will evolve into a meaningful test for the progress evaluation of the activity of rheumatoid arthritis. By way of laboratory-chemical follow-up monitoring, the laboratory-chemical progression of arthritis could be checked by the family physician at shorter time intervals. If there is no reduction in the score, or if it increases considerably, the patient could see a rheumatologist sooner to have the treatment checked and adjusted. The test may well lighten the tight schedules of rheumatologists in Germany and bring about greater efficiency in terms of time and health care costs. The next few years will surely see further controlled clinical studies on rheumatoid arthritis on the basis of the MBDA score.

IgG4-related disease (IgG4-RD)

Laboratory diagnostics

The isolated determination of immunoglobulin IgG4 serum levels is not suitable to confirm or rule out an “IgG4-related disease” (IgG4-RD) [12, 13].

The new nomenclature, which combines many long-known diseases under the entity IgG4-RD, will not be discussed further here. At this point, it is sufficient to note that IgG4-RD can virtually affect any organ and is not limited to the pancreas, as is still commonly assumed.

The disease entity of IgG4-RD was first described as early as in 1961 [14], but it was not until 2001 that Hamano [15] described it as an entity in connection with autoimmune pancreatitis. Since then, the serum cut-off level of ≥135 mg/dL IgG4 has been accepted as the diagnostic level for the disease entity of IgG4-related pancreatitis.

Since the study by Hamano et al. [15], the number of publications on and the understanding of IgG4-RD have been increasing steadily, and the cut-off level of ≥135 mg/dL must be viewed from a differentiated angle today.

The publications by Ebbo et al. [12] and Ryu et al. [13] deal with the diagnostic significance of IgG4 serum levels. Across the two studies, 217 patients’ data were evaluated retrospectively.

Both studies have identified numerous non-IgG4-RDs, which were also associated with elevated IgG4 serum levels (see Table 5A and 5B).

Table 5A

Spectrum of diagnoses associated with IgG4 serum levels.

Table 5B

Final diagnosis in patients with elevated serum IgG4 level (>1.35 g/L).

In practice, the highest mean serum levels are measured in IgG4-RDs, but given the substantial variance, it is impossible to draw definitive diagnostic conclusions from the serum level alone (see Table 5A and 5B).

Particularly chronic B-cell stimulation, such as in connection with chronic infections of the lungs and sinuses, autoimmune diseases, neoplasias and other inflammatory diseases, are measured in significantly elevated IgG4 serum levels above the previously recognized cut-off serum level of ≥135 mg/dL.

This means that an increased IgG4 serum level is not specific for an IgG4-RD. Conversely, an IgG4-RD is relatively unlikely in connection with a IgG4 serum level in the normal range. Various studies have stated a sensitivity of 67%–95% and specificity of 90%–97% for elevated IgG4 serum levels in connection with IgG4-RD [16–21]. It is noteworthy that elevated IgG4 serum levels are found in about 5% of the healthy population [18, 22]. Elevated IgG4 serum levels are measured in 10% of patients even in the case of pancreatic cancer [18].

From the above it is clear that the diagnosis should always be confirmed by way of a biopsy.

The ratio of IgG4/IgG-total in the serum, too, shows overlapping values [12], so that it must be emphasized again that the IgG4 serum level is not suitable as a standalone parameter to confirm an IgG4-related disease; but if the patient has a standard IgG4 level, it can be largely ruled out (Figure 3).

The ratio of serum IgG4/IgG-total taken on its own is not meaningful (modified from [12]).
Figure 3

The ratio of serum IgG4/IgG-total taken on its own is not meaningful (modified from [12]).

Therefore, the following requirements apply to the diagnosis of an IgG4-RD [23]:

  1. Clinical or imaging evidence of a fibrotic, tumor-like lesion at one or more organs

  2. Histological confirmation


According to a pathology consensus paper by an international commission [24], the quantitative extent of the IgG4+ plasma cell infiltration and the ratio between IgG4+ and IgG+ plasma cells are not by themselves decisive with respect to an IgG4-RD diagnosis. It is discussed there in detail that, depending on the disease duration and the affected organ, there may be severely fibrotic changes with very few inflammatory cells. Furthermore, in the case of very early lesions, fibrosis may be weak or absent, coupled with immense inflammatory cell infiltration.

The main histopathological features are characteristic fibrosis, inflammatory cell infiltration and phlebitis at varying stages in the affected organs, depending on the age of the lesion. The ratio of the IgG4+/IgG+ plasma cells >40% may be helpful, and may be indicative of a diagnosis if the histopathological features described below present themselves [25]. The histological features are listed in Table 6.

Table 6

Histopathology of IgG4-related disease (modified from [24]).

Insights into and views of IgG4-RD evolve quickly for clinicians. This is also true of the therapeutic approach, which will not be discussed extensively in this context. When this disease entity is suspected, clinicians, laboratory physicians and pathologists must work together closely in order to arrive at a correct diagnosis. In summary, the new pathological nomenclature for the diagnosis of IgG4-RD requires clinical organ swelling/tumor with serum IgG4 analysis (if elevated, it raises the probability; if not, it is not an exclusionary factor) as well as histological confirmation. IgG4-RDs can affect any organ and are not limited, as thought initially, to the pancreas.

Sjogren’s syndrome

Laboratory diagnostics

A new ELISA test to detect IgA anti-M3 receptor autoantibodies holds out the promise of a possible future application in diagnosing Sjogren’s syndrome [26].

Sjogren’s syndrome is one of the most common autoimmune diseases [27]. Clinically speaking, the initial focus with Sjogren’s syndrome is on the sicca symptoms of the mucous membranes, particularly of the eyes and mouth. The exact pathogenic mechanism of the disease is not yet clear. It is believed that damage to the salivary gland tissue activates T- and B-cells, including intensive infiltration of the salivary glands. This leads to the formation of autoantibodies against SS-A, SS-B and α-fodrin. It has further been shown that antibodies against the external region of the muscarinic 3 receptor can block the production of saliva. The salivary glands are innervated intensively by nerve fibers of the parasympathetic nervous system and stimulated by the neurotransmitter acetylcholine. Overall, patients with primary Sjogren’s syndrome frequently exhibit autonomic dysfunction with a marked fatigue problem [28], possibly as a result of the interaction of anti-muscarinic receptor antibodies at the sympathetic and parasympathetic nervous systems. At least the treatment with muscarinic 3 receptor antagonists, such as pilocarpine, will increase secretion in patients whose salivary glands have not yet been fully destroyed.

Given the pathophysiological significance of muscarinic 3 receptors, as explained, several working groups have been set up to study the detection of anti-muscarinic 3 receptor antibodies. The data regarding the detectability of IgG autoantibodies and their significance in the diagnosis of Sjogren’s syndrome are heterogeneous in the literature [29–31]. Antibody diagnostics is of great importance to differentiate the more common, non-autoimmune sicca symptoms in the population [27] and the autoimmune pathogenesis in connection with Sjogren’s syndrome.

Li et al. [26] have developed a new ELISA test for the detection of the IgA instead of IgG anti-muscarinic 3 receptor (second loop of the extracellular region). Subsequently, the ELISA test was validated in a group of patients with primary and secondary Sjogren’s syndrome, systemic lupus and rheumatoid arthritis, as well as healthy individuals. Table 7 shows the sensitivity and specificity of the ELISA test in connection with the various autoimmune diseases. The test does not provide for effective differentiation between the autoimmune diseases examined. However, the IgA antibody is rather rare in healthy individuals.

Table 7

IgA anti-muscarinic receptor 3 sensitivity and specificity in inflammatory rheumatic diseases (modified from [26]).

By combining it with the antibodies SSA and SSB established for Sjogren’s syndrome, it was possible to calculate a significantly higher sensitivity, with the specificity remaining relatively unchanged, in the ROC analysis. Here, too, similar to the MBDA score for rheumatoid arthritis, a combined test has better diagnostic properties than any parameter on its own (Table 8). This may well be an important factor when it comes to considering a complex pathophysiological event in connection with autoimmune diseases. A single marker, therefore, is only of limited significance, because it can only represent a reflection of one possible facet of the disease.

Table 8

Sensitivity and specificity of antibodies in Sjogren’s syndrome (modified from [24]).

Conflict of interest statement

Authors’ conflict of interest disclosure: The authors stated that there are no conflicts of interest regarding the publication of this article.

Research funding: None declared.

Employment or leadership: None declared.

Honorarium: None declared.


  • 1.

    Willemze A, Toes RE, Huizinga TW, Trouw LA. New biomarkers in rheumatoid arthritis. Neth J Med 2012;70:392–9.Google Scholar

  • 2.

    Werner SG, Langer HE, Ohrndorf S, Bahner M, Schott P, Schwenke C, et al. Inflammation assessment in patients with arthritis using a novel in vivo fluorescence optical imaging technology. Ann Rheum Dis 2012;71:504–10.CrossrefWeb of ScienceGoogle Scholar

  • 3.

    Aletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, Bingham CO, 3rd, et al. 2010 rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Ann Rheum Dis 2010;69:1580–8.CrossrefGoogle Scholar

  • 4.

    Shi J, van de Stadt LA, Levarht EW, Huizinga TW, Toes RE, Trouw LA, et al. Anti Carbamylated Protein Antibodies (anti-CarP) are present in arthralgia patients and predict the development of rheumatoid arthritis. Arthritis Rheum 2012;21:37830.Google Scholar

  • 5.

    Bakker MF, Cavet G, Jacobs JW, Bijlsma JW, Haney DJ, Shen Y, et al. Performance of a multi-biomarker score measuring rheumatoid arthritis disease activity in the CAMERA tight control study. Ann Rheum Dis 2012;71:1692–7.CrossrefGoogle Scholar

  • 6.

    Curtis JR, van der Helm-van Mil AH, Knevel R, Huizinga TW, Haney DJ, Shen Y, et al. Validation of a novel multibiomarker test to assess rheumatoid arthritis disease activity. Arthritis Care Res (Hoboken) 2012;64:1794–803.Google Scholar

  • 7.

    Bijlsma JW, Verhoef-Jürgens M, Badder MF, Jacobs JW, Lafeber FP, Welsing PM, et al. Response to Methotrexate plus Prednisone in CAMERA II Using a Multi-Biomarker Disease Assay (Vectra DA) Test and DAS28-BSG. Arthritis & Rheumatism 2012;65(Supplement S10):S899.Google Scholar

  • 8.

    Eastman PS, Manning WC, Qureshi F, Haney D, Cavet G, Alexander C, et al. Characterization of a multiplex, 12-biomarker test for rheumatoid arthritis. J Pharm Biomed Anal 2012;70: 415–24.CrossrefWeb of ScienceGoogle Scholar

  • 9.

    Cavet G, Centola M, Shen Y, Haney D, Smith DR, Hesterberg LK. Development of a mulit-biomarker test for rheumatoid arthritis disease activity. Ann Rheum Dis 2010;69(Supplement):S148.Google Scholar

  • 10.

    Bakker MF, Jacobs JW, Verstappen SM, Bijlsma JW. Tight control in the treatment of rheumatoid arthritis: efficacy and feasibility. Ann Rheum Dis 2007;66(Suppl 3):iii56–60.CrossrefGoogle Scholar

  • 11.

    Zhao X, Qureshi F, Eastman PS, Manning WC, Alexander C, Robinson WH, et al. Pre-analytical effects of blood sampling and handling in quantitative immunoassays for rheumatoid arthritis. J Immunol Methods 2012;378:72–80.CrossrefWeb of ScienceGoogle Scholar

  • 12.

    Ebbo M, Grados A, Bernit E, Vely F, Boucraut J, Harle JR, et al. Pathologies Associated with Serum IgG4 Elevation. Int J Rheumatol 2012;2012:602809.Google Scholar

  • 13.

    Ryu JH, Horie R, Sekiguchi H, Peikert T, Yi ES. Spectrum of disorders associated with elevated serum IgG4 levels encountered in clinical practice. Int J Rheumatol 2012;2012:232960.Google Scholar

  • 14.

    Sarles H, Sarles JC, Muratore R, Guien C. Chronic inflammatory sclerosis of the pancreas – an autonomous pancreatic disease? Am J Dig Dis 1961;6:688–98.CrossrefGoogle Scholar

  • 15.

    Hamano H, Kawa S, Horiuchi A, Unno H, Furuya N, Akamatsu T, et al. High serum IgG4 concentrations in patients with sclerosing pancreatitis. N Engl J Med 2001;344:732–8.CrossrefGoogle Scholar

  • 16.

    Zen Y, Nakanuma Y. IgG4-related disease: a cross-sectional study of 114 cases. Am J Surg Pathol 2010;34:1812–9.CrossrefGoogle Scholar

  • 17.

    Tabata T, Kamisawa T, Takuma K, Anjiki H, Egawa N, Kurata M, et al. Serum IgG4 concentrations and IgG4-related sclerosing disease. Clin Chim Acta 2009;408:25–8.Web of ScienceGoogle Scholar

  • 18.

    Sah RP, Chari ST. Serologic issues in IgG4-related systemic disease and autoimmune pancreatitis. Curr Opin Rheumatol 2011;23:108–13.Web of ScienceCrossrefGoogle Scholar

  • 19.

    Sadler R, Chapman RW, Simpson D, Soonawalla ZF, Waldegrave EL, Burden JM, et al. The diagnostic significance of serum IgG4 levels in patients with autoimmune pancreatitis: a UK study. Eur J Gastroenterol Hepatol 2011;23:139–45.CrossrefGoogle Scholar

  • 20.

    Kamisawa T, Okamoto A. IgG4-related sclerosing disease. World J Gastroenterol 2008;14:3948–55.CrossrefGoogle Scholar

  • 21.

    Naitoh I, Nakazawa T, Ohara H, Ando T, Hayashi K, Okumura F, et al. Comparative evaluation of the Japanese diagnostic criteria for autoimmune pancreatitis. Pancreas 2010;39:1173–9.CrossrefWeb of ScienceGoogle Scholar

  • 22.

    Nirula A, Glaser SM, Kalled SL, Taylor FR. What is IgG4? A review of the biology of a unique immunoglobulin subtype. Curr Opin Rheumatol 2011;23:119–24.CrossrefWeb of ScienceGoogle Scholar

  • 23.

    Umehara H, Okazaki K, Masaki Y, Kawano M, Yamamoto M, Saeki T, et al. Comprehensive diagnostic criteria for IgG4-related disease (IgG4-RD), 2011. Mod Rheumatol 2012;22:21–30.Google Scholar

  • 24.

    Deshpande V, Zen Y, Chan JK, Yi EE, Sato Y, Yoshino T, et al. Consensus statement on the pathology of IgG4-related disease. Mod Pathol 2012;25:1181–92.CrossrefGoogle Scholar

  • 25.

    Cheuk W, Chan JK. IgG4-related sclerosing disease: a critical appraisal of an evolving clinicopathologic entity. Adv Anat Pathol 2010;17:303–32.CrossrefWeb of ScienceGoogle Scholar

  • 26.

    Li YN, Guo JP, He J, Liu X, Yin FR, Ding Y, et al. Serum IgA against type 3 muscarinic acetylcholine receptor is a novel marker in diagnosis of Sjogren’s syndrome. Chin Med J (Engl) 2011;124:2490–5.Google Scholar

  • 27.

    Gabriel SE, Michaud K. Epidemiological studies in incidence, prevalence, mortality, and comorbidity of the rheumatic diseases. Arthritis Res Ther 2009;11:229.CrossrefGoogle Scholar

  • 28.

    Newton JL, Frith J, Powell D, Hackett K, Wilton K, Bowman S, et al. Autonomic symptoms are common and are associated with overall symptom burden and disease activity in primary Sjogren’s syndrome. Ann Rheum Dis 2012;71:1973–9.CrossrefWeb of ScienceGoogle Scholar

  • 29.

    Cavill D, Waterman SA, Gordon TP. Antibodies raised against the second extracellular loop of the human muscarinic M3 receptor mimic functional autoantibodies in Sjogren’s syndrome. Scand J Immunol 2004;59:261–6.CrossrefGoogle Scholar

  • 30.

    Zigon P, Bozic B, Cucnik S, Rozman B, Tomsic M, Kveder T. Are autoantibodies against a 25-mer synthetic peptide of M3 muscarinic acetylcholine receptor a new diagnostic marker for Sjogren’s syndrome? Ann Rheum Dis 2005;64:1247; author reply 1247.Google Scholar

  • 31.

    Roescher N, Kingman A, Shirota Y, Chiorini JA, Illei GG. Peptide-based ELISAs are not sensitive and specific enough to detect muscarinic receptor type 3 autoantibodies in serum from patients with Sjogren’s syndrome. Ann Rheum Dis 2011;70:235–6.CrossrefWeb of ScienceGoogle Scholar

Article note

This article is based on a presentation/manuscript, held on the occasion of the second DiagnostikUpdate in Mannheim, Germany, 08–09 March 2013. Original German online version http://www.degruyter.com/view/j/labm.2014.38.issue-2/labmed-2013-0065/labmed-2013-0065.xml?format=INT. The German article was translated by Compuscript Ltd. and authorized by the authors.

About the article

Correspondence: Prof. Dr. med. Peter Härle, Katholisches Klinikum Mainz, Klinik für Rheumatologie, Klinische Immunologie und Physikalische Therapie, An der Goldgrube 11, 55131 Mainz, Germany, Tel.: +49 6131 575 1750, Fax: +49 6131 575 1760, E-Mail:

Received: 2014-06-29

Accepted: 2014-07-09

Published Online: 2015-04-16

Citation Information: LaboratoriumsMedizin, Volume 38, Issue 2, ISSN (Online) 1439-0477, ISSN (Print) 0342-3026, DOI: https://doi.org/10.1515/labmed-2014-0021.

Export Citation

©2014 by De Gruyter.Get Permission

Comments (0)

Please log in or register to comment.
Log in