MARKER SEQUENCES FOR THE DIAGNOSIS AND STRATIFICATION OF SYSTEMIC SCLEROSIS PATIENTS

Information

  • Patent Application
  • 20180017554
  • Publication Number
    20180017554
  • Date Filed
    May 11, 2015
    9 years ago
  • Date Published
    January 18, 2018
    6 years ago
Abstract
The present invention relates to methods for identifying markers for systemic sclerosis (also referred to as scleroderma; SSc) and the markers identified with the aid of this method, which can differentiate between SSc and other autoimmune diseases on the one hand and between different SSc subgroups on the other hand. The invention also relates to panels, diagnostic devices, and test kits which comprise these markers, and also to the use and application thereof, for example for the diagnosis, prognosis and therapy control of SSc. The invention also relates to methods for screening and for validating active substances for use in SSc subgroups.
Description

The present invention relates to methods for identifying markers for systemic sclerosis (SSc; also scleroderma or synonymously Progressive Systemic Sclerosis (PSS)) and to the markers identified with the aid of this method, which can differentiate between SSc and other autoimmune diseases on the one hand and between different SSc subgroups on the other hand. The invention also relates to panels, diagnostic devices and test kits which comprise these markers, and to the use and application thereof, for example for the diagnosis, prognosis and therapy control of SSc. The invention also relates to methods for screening and for validating active substances for use in SSc subgroups.


SSc is a chronic, inflammatory, rheumatic disease, which counts among the classic immunological connective tissue diseases (collagenoses).


SSc is a heterogeneous disease with excessive fibrosis of the skin. Further organ systems, such as the lungs, gastrointestinal area, kidneys, heart and blood vessels can also be affected. In addition, joint symptoms (arthritis) also occur.


SSc is a very rare disease. The incidence is approximately 0.5-1.5/100,000 individuals/year. It mostly occurs between the ages of 30 and 50. Women are 10-15 times more likely to be affected than men (LeRoy et al. 1988).


Clinically, a distinction can be made between limited and diffuse SSc in accordance with LeRoy et al. (1988). In earlier phases of the disease, it is often difficult to classify patients unambiguously, with this being referred to as undifferentiated SSc. If, in addition to scleroderma, fundamental symptoms of other rheumatic diseases also occur, reference is made to scleroderma overlap syndrome or overlap syndrome.


The limited form of SSc occurs at a frequency of up to 60%. This is characterised by fibrosis of the hands and feet, which spreads to below the elbows and knee joints. The Raynaud phenomenon often exists already for many years prior to the appearance of skin fibrosis. Gastrointestinal changes (difficulty in swallowing) and pulmonary arterial hypertony (PAH) also often occur. The limited form also includes CREST syndrome: calcinosis cutis, Raynaud phenomenon, oesophageal dysmotility, slerodactyly, and telangiectasia.


The diffuse form is the quicker and more severe form of SSc. In this case the fibrosis spreads past the elbows over the body and face. In contrast to the limited form, skin fibroses occur already 1-2 years after the appearance of the Raynaud phenomenon.


In the case of scleroderma overlap syndrome, symptoms of further non-organ-specific autoimmune diseases, such as myositis, lupus erythematodes/SLE, Sjögren's syndrome, and rheumatoid arthritis/RA, also occur in addition to the skin symptoms of scleroderma.


Patients with undifferentiated SSc have Raynaud's syndrome and have the swollen fingers typical for SSc and pulmonary arterial hypertony. Only some of the patients later actually develop diffuse or limited SSc.


The diagnosis of SSc can be provided on the basis of the clinical picture with the typical skin changes. This can be difficult, however, in the early stages of the disease. In addition, the detection of antinuclear antibodies (ANAs) is used. ANAs can be detected in approximately 90% of SSc patients. However, the ANA test is not specific for SSc, since other collagenoses and up to 20% of healthy individuals will test positively. The three most important autoantibodies in the case of SSc are anti-topoisomerase I (Sc1-70), anti-centromere (CENP), and anti-RNA polymerase III (anti-RNAP III). These autoantibodies have a high specificity for SSc and are often associated with a subform of SSc. However, these 3 autoantibodies are suitable only to a limited extent for subtyping of SSc, since they do not occur exclusively in one subtype and their frequency can deviate distinctly in different ethnicities. Anti-topomerase antibodies have a high specificity for SSc and are detectable in approximately 30% of patients having diffuse SSc. Anti-centomere antibodies are, by contrast, detectable in approximately 50-60% of patients having limited SSc and in 10% of patients having diffuse SSc. Both autoantibodies are mutually exclusive and are detectable jointly in patients only in very rare cases. Anti-RNAP III antibodies are detectable more frequently in the diffuse form and constitute a risk factor for renal crisis. On the whole, only approximately 70% of SSc patients can be identified diagnostically using the autoantibodies against anti-topoisomerase, anti-centromere and anti-RNAP (Mierau et al. 2011; Mehra et al. 2013).


Antibodies against U1-RNP and PM-Scl antibodies also occur more rarely. These, however, have only a low specificity for SSc: anti-PM-Scl antibodies are often detected in patients having polymyositis/SSc overlap syndrome. Antibodies against U1-RNP are detectable both in the case of SSc and in the case of mixed connective tissue diseases (MCTD) and SLE. In approximately one third of patients, antibodies against typical collagenosis antigens, such as Rho52/SS-A, Ro60/SS-B, and citrullinated peptide (ACPA) and rheumatoid factors are also detected.


In clinical practice, the diagnosis of an early form of SSc and classification thereof into the subgroups constituted by diffuse, limited or overlap syndrome is often difficult, since not all symptoms are yet present or approximately 10-30% of patients carry symptoms of a different collagenosis (connective tissue disease). Since the various subforms have a very different prognosis, there is a substantial need for biomarkers for improved diagnosis of SSc and for a classification into SSc subgroups. There is also a great need for prognostic and predictive biomarkers.


A further problem of the currently used diagnostic methods is that the suitability of the previously tested autoantigens for the diagnosis of organ involvement and complications is disputed, and partly conflicting data has been published.


There is thus also a need for new markers for SSc and also a need to improve the sensitivity and specificity of the previously most frequent diagnostically used autoantigens by the use of new autoantigens or markers.


The object has been achieved in accordance with the invention in that a differential method comprising a multiplicity of steps has been developed, in which serum samples of a large number of healthy individuals and patients with various autoimmune diseases were examined by comparison in respect of their reactivity with a multiplicity of potential antigens and these results were statistically evaluated. The selection of the serum samples and the sequence of the steps surprisingly made it possible to identify highly specific markers for SSc which are also suitable for identifying SSc subgroups and complications and for providing a differential diagnosis in respect of other autoimmune diseases, such as rheumatoid arthritis (RA), in particular early stages of RA (“early RA”), and ankylosing spondylitis or Bekhterev's disease (SPA).


The invention relates to a multi-stage method for identifying specific markers for SSc and also the markers for SSc identified with the aid of the method, and the use and/or specific therapeutic application of these markers for the diagnosis and/or differential diagnosis of systemic sclerosis and/or distinguishing of clinical subgroups of SSc.


One subject of the present invention is therefore a method for identifying markers for systemic sclerosis (SSc), said method comprising the following steps:

    • a) bringing serum samples of at least 50, preferably 100 SSc patients into contact with more than 5000 antigens coupled to beads, for example Luminex beads, measuring the binding of the individual antigens to proteins in the serum samples of the SSc patients by immunofluorescence assay, and determining the median fluorescence intensity (MFI) for each individual antigen;
    • b) bringing serum samples of at least 50, preferably 100 patients with lupus erythematodes (SLE) into contact with the same antigens coupled to beads, for example Luminex beads, measuring the binding of the individual antigens to proteins in the serum samples of the SLE patients by means of immunofluorescence assay, and determining from this the median fluorescence intensity (MFI) for each individual antigen;
    • c) bringing serum samples of at least 50, preferably 537 patients with early rheumatoid arthritis (RA) into contact with the same antigens coupled to beads, for example Luminex beads, measuring the binding of the individual antigens to proteins in the serum samples of the RA patients by means of immunofluorescence assay, and determining from this the median fluorescence intensity (MFI) for each individual antigen;
    • d) bringing serum samples of at least 50, preferably 82 patients with ankylosing spondylitis (SPA) into contact with the same antigens coupled to beads, for example Luminex beads, measuring the binding of the individual antigens to proteins in the serum samples of the SPA patients by means of immunofluorescence assay, and determining from this the median fluorescence intensity (MFI) for each individual antigen;
    • e) bringing serum samples of at least 50, preferably 343 healthy individuals into contact with the same antigens coupled to beads, for example Luminex beads, measuring the binding of the individual antigens to proteins in the serum samples of the healthy individuals by means of immunofluorescence assay, and determining from this the median fluorescence intensity (MFI) for each individual antigen;
    • f) statistically evaluating the MFI data of each individual antigen from a), b), c), d) and e) by means of univariate analysis and thus identifying markers with which SSc patients can be differentiated from patients with SLE, patients with early RA, patients with SPA, and from healthy individuals;
    • g) and wherein the markers are selected from the sequences


SEQ ID No. 1 to 955, homologues of sequences SEQ ID No. 1 to 955 with at least 95% homology, and subsequences of SEQ ID No. 1 to 955 and subsequences of homologues of SEQ ID No. 1 to 955 with at least 95% homology, and sequences coded by SEQ ID No. 1 to 319.


The beads used in the method according to the invention in steps a) to e) are preferably fluorescence-labelled.


The terms systemic sclerosis (SSc), RA or early RA, SLE, and SPA are defined for example in Pschyrembel, Clinical Dictionary, de Gruyter, 261st edition (2011).


In a preferred embodiment of the method, the markers are selected after univariate statistical analysis in that they have a threshold value of p less than 0.05 and a reactivity in the SSc group modified 1.5 times with respect to the control group. The control group comprises or consists of patients with SLE and/or patients with early RA and/or patients with SPA and/or healthy individuals. Healthy individuals are individuals in which no SSc, no SSc subform, no early RA, and no SPA has been detected or can be detected.


The invention also relates to a marker for SSc or one or more SSc subforms obtainable by the method according to the invention.


The invention also relates to a marker for SSc or one or more SSc subgroups selected from the sequences SEQ ID No. 1 to 955, homologues of sequences SEQ ID No. 1 to 955 with at least 95% homology, and subsequences of SEQ ID No. 1 to 955 and subsequences of homologues of SEQ ID No. 1 to 955 with at least 95% homology, and sequences coded by SEQ ID No. 1 to 319. The SSc subgroups are, for example, diffuse SSc (dSSc for short), limited SSc (1SSc for short) and/or overlap syndrome SSc (SSc-OS for short).


The invention also relates to a marker for SSc selected from the sequences SEQ ID No. 1, 3-5, 8-33, 320, 322-324, 327-352, 639, 641-643, 646-671, homologues of sequences SEQ ID No. 1, 3-5, 8-33, 320, 322-324, 327-352, 639, 641-643, 646-671 with at least 95% homology, and subsequences of SEQ ID No. 1, 3-5, 8-33, 320, 322-324, 327-352, 639, 641-643, 646-671, and subsequences of homologies of SEQ ID No. 1, 3-5, 8-33, 320, 322-324, 327-352, 639, 641-643, 646-671 with at least 95% homology, and sequences coded by SEQ ID No. 1, 3-5, 8-33.


The invention also relates to a marker for dSSc selected from the sequences SEQ ID No. 6, 7, 34-103, 325, 326, 353-422, 644, 645, 672-741, homologues of sequences SEQ ID No. 6, 7, 34-103, 325, 326, 353-422, 644, 645, 672-741 with at least 95% homology, and subsequences of SEQ ID No. 6, 7, 34-103, 325, 326, 353-422, 644, 645, 672-741, and subsequences of homologues of SEQ ID No. 6, 7, 34-103, 325, 326, 353-422, 644, 645, 672-741 with at least 95% homology, and sequences coded by SEQ ID No. 6, 7, 34-103.


The invention also relates to a marker for 1SSc selected from the sequences SEQ ID No. 2, 104-171, 321, 423-490, 640, 742-809, homologues of sequences SEQ ID No. 2, 104-171, 321, 423-490, 640, 742-809 with at least 95% homology, and subsequences of SEQ ID No. 2, 104-171, 321, 423-490, 640, 742-809, and subsequences of homologues of SEQ ID No. 2, 104-171, 321, 423-490, 640, 742-809 with at least 95% homology, and sequences coded by SEQ ID No. 2, 104-171.


The invention also relates to a marker for SSc-OS selected from the sequences SEQ ID No. 173-291, 492-610, 811-929, homologues of sequences SEQ ID No. 173-291, 492-610, 811-929 with at least 95% homology, and subsequences of SEQ ID No. 173-291, 492-610, 811-929, and subsequences of homologues of SEQ ID No. 173-291, 492-610, 811-929 with at least 95% homology, and sequences coded by SEQ ID No. 173-291.


The invention also relates to a panel (arrangement) of markers for SSc or SSc subgroups comprising at least two or three different markers selected independently of one another from the sequences SEQ ID No. 1 to 955, homologues of sequences SEQ ID No. 1 to 955 with at least 95% homology, and subsequences of SEQ ID No. 1 to 955 and subsequences of homologues of SEQ ID No. 1 to 955 with at least 95% homology and coded by the sequences SEQ ID No. 1 to 319. Preferred panels are also presented in the examples.


On account of the high clinical and serological heterogeneity of the SSc disease, it is difficult to diagnose SSc unambiguously using just one biomarker. It is therefore often necessary to combine (where possible) uncorrelated autoantigens to form what are known as panels of markers (“biomarker panels for SSc”). By way of example, within the scope of individualised medicine, corresponding panels of markers for SSc can be composed individually for the relevant SSc subtype (subgroup) for individual patients or patient groups. It is therefore also necessary to have available a multiplicity of potential markers for SSc in order to select suitable subgroups or subtypes of specific markers for SSc for the individual case in question. A corresponding panel can be embodied for example in the form of an arrangement, an array, or also one or more beads. The invention thus relates to an arrangement comprising one or more markers according to the invention, a protein array comprising one or more markers according to the invention, and a bead (pellet or platelet) comprising one or more markers according to the invention.


The invention also relates to diagnostic device or a test kit comprising at least one marker for SSc or SSc subgroups selected from the sequences SEQ ID No. 1 to 955, homologues of sequences SEQ ID No. 1 to 955 with at least 95% homology, and subsequences of SEQ ID No. 1 to 955 and subsequences of homologues of SEQ ID No. 1 to 955 with at least 95% homology and coded by the sequences SEQ ID No. 1 to 319.


The invention also relates to the use of at least one marker selected from the sequences SEQ ID No. 1 to 955, homologues of sequences SEQ ID No. 1 to 955 with at least 95% homology, and subsequences of SEQ ID No. 1 to 955 and subsequences of homologues of SEQ ID No. 1 to 955 with at least 95% homology and coded by the sequences SEQ ID No. 1 to 319 or at least one panel of markers or a diagnostic device or test kit for identifying subgroups of SSc patients, for diagnosis of SSc, for differential diagnosis of SSc or SSc subgroups, in particular for distinguishing SSc from other autoimmune diseases or rheumatic diseases, for diagnosis of dSSc, 1SSc or SSc-OS, for prognosis of SSc, for therapy control in SSc, for active substance selection in SSc, for therapy monitoring in SSc, and for aftercare in SSc.


The invention also relates to the use of at least one marker selected from the sequences SEQ ID No. 1, 3-5, 8-33, 320, 322-324, 327-352, 639, 641-643, 646-671, homologues of sequences SEQ ID No. 1, 3-5, 8-33, 320, 322-324, 327-352, 639, 641-643, 646-671 with at least 95% homology, and subsequences of SEQ ID No. 1, 3-5, 8-33, 320, 322-324, 327-352, 639, 641-643, 646-671, and subsequences of homologues of SEQ ID No. 1, 3-5, 8-33, 320, 322-324, 327-352, 639, 641-643, 646-671 with at least 95% homology, and sequences coded by SEQ ID No. 1, 3-5, 8-33 for diagnosis of SSc.


The invention also relates to the use of at least one marker selected from the sequences SEQ ID No. 6, 7, 34-103, 325, 326, 353-422, 644, 645, 672-741, homologues of sequences SEQ ID No. 6, 7, 34-103, 325, 326, 353-422, 644, 645, 672-741 with at least 95% homology, and subsequences of SEQ ID No. 6, 7, 34-103, 325, 326, 353-422, 644, 645, 672-741, and subsequences of homologues of SEQ ID No. 6, 7, 34-103, 325, 326, 353-422, 644, 645, 672-741 with at least 95% homology, and sequences coded by SEQ ID No. 6, 7, 34-103 for diagnosis of dSSc, for differential diagnosis of dSSc, in particular for distinguishing dSSc from other autoimmune diseases or rheumatic diseases or from 1SSc or SSc-OS, for prognosis of dSSc, for therapy control in dSSc, for active substance selection in dSSc, for therapy monitoring in dSSc, and for aftercare in dSSc.


The invention also relates to the use of at least one marker selected from the sequences SEQ ID No. 2, 104-171, 321, 423-490, 640, 742-809, homologues of sequences SEQ ID No. 2, 104-171, 321, 423-490, 640, 742-809 with at least 95% homology, and subsequences of SEQ ID No. 2, 104-171, 321, 423-490, 640, 742-809, and subsequences of homologues of SEQ ID No. 2, 104-171, 321, 423-490, 640, 742-809 with at least 95% homology, and sequences coded by SEQ ID No. 2, 104-171 for diagnosis of 1SSc, for differential diagnosis of 1SSc, in particular for distinguishing 1SSc from other autoimmune diseases or rheumatic diseases or from dSSc or SSc-OS, for prognosis of 1SSc, for therapy control in dSSc, for active substance selection in 1SSc, for therapy monitoring in 1SSc, and for aftercare in 1SSc.


The invention also relates to the use of at least one marker selected from the sequences SEQ ID No. 173-291, 492-610, 811-929, homologues of sequences SEQ ID No. 173-291, 492-610, 811-929 with at least 95% homology, and subsequences of SEQ ID No. 173-291, 492-610, 811-929, and subsequences of homologues of SEQ ID No. 173-291, 492-610, 811-929 with at least 95% homology, and sequences coded by SEQ ID No. 173-291 for diagnosis of SSc-OS, for differential diagnosis of SSc-OS from other autoimmune diseases or rheumatic diseases or from dSSc or 1SSc, for prognosis of SSc-OS, for therapy control in SSc-OS, for active substance selection in SSc-OS, for therapy monitoring in SSc-OS, and for aftercare in SSc-OS.


The invention also relates to a method for the early detection, diagnosis, differential diagnosis, prognosis, therapy control and/or aftercare of SSc or SSc subgroups, in which

    • a. at least one of the markers selected from the sequences SEQ ID No. 1 to 955, the homologues of sequences SEQ ID No. 1 to 955 with at least 95% homology, the subsequences of SEQ ID No. 1 to 955 or the subsequences of homologues of SEQ ID No. 1 to 955 with at least 95% homology, or coded by SEQ ID No. 1-319;
    • b. is brought into contact with bodily fluid or a tissue sample from an individual to be tested, and
    • c. an interaction of the bodily fluid or of the tissue sample with the one or more markers from a. is detected.


The invention also relates to a composition, preferably a pharmaceutical composition for specific application in the case of SSc or SSc subgroups, comprising at least one of the sequences SEQ ID No. 1 to 955, the homologues of sequences SEQ ID No. 1 to 955 with at least 95% homology, subsequences of SEQ ID No. 1 to 955 or the subsequence of the homologues of SEQ ID No. 1 to 955 with at least 95% homology, or the sequences coded by SEQ ID No. 1-319.


The invention also relates to a target for the therapy of SSC selected from the sequences SEQ ID No. 1 to 955, the homologues of sequences SEQ ID No. 1 to 955 with at least 95% homology, the subsequences of SEQ ID No. 1 to 955 and the subsequences of the homologues of SEQ ID No. 1 to 955 with at least 95% homology, and also the proteins coded by the sequences.


The invention also relates to a method for screening active substances for SSc or SSc subgroups, in which

    • a. at least one of the markers selected from the sequences SEQ ID No. 1 to 955, the homologues of sequences SEQ ID No. 1 to 955 with at least 95% homology, the subsequences of SEQ ID No. 1 to 955 or the subsequences of homologues of SEQ ID No. 1 to 955 with at least 95% homology, or the sequences coded by SEQ ID No. 1-319;
    • b. is brought into contact with a substance to be tested, and
    • c. an interaction of the substance to be tested with the one or more markers from a. is detected.


The large clinical heterogeneity of SSc currently constitutes a big problem both for diagnosis and for active substance development.


The identification of specific antibody signatures in SSc patient subgroups therefore constitutes an important step for the improved definition of patient groups in clinical studies. By way of example, specific autoantibodies for dSSc, 1SSc or SSc-OS could be used to recruit this subgroup for drug studies.


The invention also relates to the use of one or more markers according to the invention for SSc or SSc subgroups, of an arrangement according to the invention (panel of markers for SSc), of a protein array according to the invention, of a bead according to the invention, of a diagnostic device according to the invention, or of a test kit according to the invention for the individually tailored diagnosis and/or therapy in individual patients, patient groups, cohorts, population groups, variants of SSc, and stages of SSc.


The invention also relates to the use of one or more markers according to the invention for SSc or SSc subgroups, of an arrangement according to the invention (panel of markers for SSc), of a protein array according to the invention, of a bead according to the invention, of a diagnostic device according to the invention, or of a test kit according to the invention for detecting and/or determining the amount of one or more autoantibodies associated with SSc or SSc subgroups, for example in bodily fluids such as serum, tissue or tissue samples of the patient.


The invention also relates to the use of one or more markers according to the invention, of an arrangement according to the invention, of a protein array according to the invention, of a bead according to the invention, of a diagnostic device according to the invention, or of a test kit according to the invention for the analysis of autoantibody profiles of patients, in particular for the qualitative and/or quantitative analysis of autoantibodies and/or for the monitoring of changes of autoantibody profiles associated with SSc or SSc subgroups, for example in bodily fluids such as serum, tissue or tissue samples of the patient.


A particular embodiment of the invention relates to methods for the early identification and diagnosis of SSc or SSc subgroups, in which the detection of an interaction of the bodily fluid or the tissue sample with the one or more markers indicates an SSc- or SSc-subgroup-associated autoantibody profile of the patient or of a cohort or of a population group or of a certain course of disease (prognosis) or of a certain response to a therapy/drug.


The invention therefore includes the use of at least one marker for SSc selected from the sequences SEQ ID No. 1 to 955, the homologues of sequences SEQ ID No. 1 to 955 with at least 95% homology, the subsequences of SEQ ID No. 1 to 955 or the subsequences of homologues of SEQ ID No. 1 to 955 with at least 95% homology, and the proteins coded by the sequences for the analysis of autoantibody profiles of patients, in particular for the quantitative analysis and/or for the monitoring of changes of autoantibody profiles of SSc patients.


An interaction of the bodily fluid or the tissue sample with the one or more SSc markers can be detected for example by a probe, in particular by an antibody.


In a preferred embodiment at least 2, for example 3, 4, 5, 6, 7, 8, 9, 10, preferably 15 to 20 markers for SSc or SSc subgroups or 30 to 50 or 100 or more markers are used together or in combination (what are known as “panels”), either simultaneously or in succession, wherein the markers for SSc are selected independently of one another from the sequences SEQ ID No. 1 to 955, the homologues of sequences SEQ ID No. 1 to 955 with at least 95% homology, the subsequences of SEQ ID No. 1 to 955 or the subsequences of homologues of SEQ ID No. 1 to 955 with at least 95% homology, and the proteins coded by the sequences. This embodiment is implemented preferably in the form of a panel according to the invention.


A particular embodiment of the invention relates to a method according to the invention, wherein the stratification or therapy control includes decisions relating to the treatment and therapy of the patient, in particular hospitalisation of the patient, use, efficacy and/or dosage of one or more drugs, a therapeutic measure, or the monitoring of the course of the disease and course of therapy, aetiology, or classification of a disease inclusive of prognosis. The invention also relates to a method for stratification, in particular for risk stratification and/or therapy control of a patient with SSc.


The stratification of the patient with SSc into new or established SSc subgroups as well as the expedient selection of patient groups for the clinical development of new therapeutic agents is also included. The term therapy control likewise includes the division of patients into responders and non-responders with regard to a therapy or course thereof.


The invention in particular also relates to the detection and determination of the amount of at least two different autoantibodies in a patient by means of the SSc markers according to the invention, wherein at least two different SSc markers are preferably used. The invention also relates to a use according to the invention of one or more SSc markers, wherein at least 2, for example 3 to 5 or 10, preferably 30 to 50, or 50 to 100 or more SSc markers or the relevant autoantibodies on or from a patient to be tested are determined.


The invention comprises the SSc markers on a solid substrate, for example a filter, a membrane, a small platelet or ball, for example a magnetic or fluorophore-labelled ball, a silicon wafer, a bead, a chip, a mass spectrometry target, or a matrix, or the like. Different materials are suitable as substrates and are known to a person skilled in the art, for example glass, metal, plastic, filter, PVDF, nitrocellulose, or nylon (for example Immobilon P Millipore, Protran Whatman, Hybond N+ Amersham).


The substrate for example can correspond to a grid with the dimensions of a microtitre plate (8-12 well strips, 96 wells, 384 wells or more), of a silicon wafer, of a chip, of a mass spectrometry target, or of a matrix.


In one embodiment of the invention markers for SSc are present in the form of clone sequences or clone(s).


The markers according to the invention can be combined, supplemented or extended with known biomarkers for SSc or biomarkers for other diseases. With a combination of this type, a proportion of markers for SSc according to the invention of preferably at least 50%, preferably 60%, and particularly preferably 70% or more is comprised.


In a preferred embodiment the use of the SSc markers is implemented outside the human or animal body, for example the diagnosis is performed ex vivo/in vitro.


In the sense of this invention, the term “diagnosis” means the positive determination of SSc with the aid of the markers according to the invention and the assignment of the patients or symptoms thereof to the disease SSc. The term “diagnosis” includes the medical diagnosis and tests in this respect, in particular in vitro diagnosis and laboratory diagnosis, and also proteomics and nucleic acid blots. Further tests may be necessary for assurance and in order to rule out other diseases. The term “diagnosis” therefore includes in particular the differential diagnosis of SSc by means of the markers according to the invention.


In the sense of this invention, “stratification or therapy control” means that, for example, the methods according to the invention allow decisions for the treatment and therapy of the patient, whether it is the hospitalisation of the patient, the use, efficacy and/or dosage of one or more drugs, a therapeutic measure or the monitoring of the course of a disease and the course of therapy or aetiology or classification of a disease, for example into a new or existing sub-type, or the differentiation of diseases and patients thereof. In a further embodiment of the invention, the term “stratification” in particular includes the risk stratification with the prognosis of an “outcome” of a negative health event.


“Prognosis” means the prediction of the course of a disease.


In accordance with the invention, “therapy control” means, for example, the prediction and monitoring of the response to a drug or a therapy as well as aftercare.


Within the scope of this invention, the term “patient” is understood to mean any test subject, any individual (human or mammal), with the provision that the test subject or individual is tested for SSc.


The term “marker for SSc” in the sense of this invention means that the nucleic acid, for example DNA, in particular cDNA or RNA or the coded amino acid sequence or the polypeptide or protein are significant (specific) for SSc and/or the autoantibody profiles associated with SSc. Markers according to the invention are nucleic acid sequences and/or amino acid sequences according to the definition in the appended sequence protocol (SEQ ID No. 1 to SEQ ID No. 955), homologues and subsequences thereof, wherein modified nucleic acid and amino acid sequences are also included. Here, marker for SSc means, for example, that the cDNA or RNA or the polypeptide or protein obtainable therefrom interacts with substances from the bodily fluid or tissue sample from a patient with SSc (for example antigen (epitope)/antibody (paratope) interaction). In a particularly preferred embodiment of the invention the marker for SSc is an (auto)antigen or part of an antigen or codes for an antigen or for part of an antigen.


The substances from the bodily fluid or tissue sample occur either only in an amplified manner or at least in an amplified manner in the case of SSc or are expressed, whereas these substances are not present in patients without SSc or healthy individuals, or at least are present to a lesser extent (smaller amount, lower concentration). Markers for SSc can also be characterised in that they interact with substances from the bodily fluid or tissue sample from patients with SSc, because these substances no longer occur or are no longer expressed or occur or are expressed at least in a much lower amount/concentration in the case of SSc, whereas these substances are present or are at least present to a much higher extent in patients without SSc. Markers for SSc can also be present in healthy test subjects, however the amount (concentration) thereof changes for example with the development, establishment and therapy of SSc. One or more markers can in this way map a profile of substances from bodily fluid and tissue sample, for example an SSc-associated autoantibody profile of the patient in question. Markers according to the invention are biomarkers for SSc.


Autoantibody profiles comprise the amount of one or more autoantibodies of which the occurrence/expression accompanies the development and/or establishment of SSc. Autoantibody profiles therefore include on the one hand the composition, i.e. one or more autoantibodies is/are expressed only in the case of SSc for example, and also the amount/concentration of individual autoantibodies, i.e. the amount/concentration of individual autoantibodies changes with the development and establishment of SSc. These changes can be detected with the aid of the marker (sequences) according to the invention.


In a particularly preferred embodiment the SSc marker identifies/binds to autoantibodies which are present (intensified) or are present to a lower extent (or no longer) during the course of the development, establishment and therapy of SSc. Autoantibodies are formed by the body against endogenous antigens which are formed for example in the case of SSc. Autoantibodies are formed by the body against different substances and pathogens. Within the scope of the present invention, the autoantibodies which are formed with the occurrence and during the course of the development of SSc and/or of which the expression is up-regulated or down-regulated are detected in particular. These autoantibodies can be detected with the aid of the methods and markers according to the invention, and the detection and monitoring (for example of the amount) thereof can be used for the early identification, diagnosis and/or therapy monitoring/therapy control and the prognosis and prediction of the risk of the re-occurrence of SSc within the scope of the aftercare.


The autoantibody profiles can be sufficiently characterised with use of just a single SSc marker. In other cases, two or more SSc markers are necessary in order to map an autoantibody profile which is specific for SSc.


In one embodiment of the invention autoantibodies which derive from another individual and which for example originate from a commercial cDNA bank can be detected using SSc markers.


In another embodiment of the invention these autoantibodies can be detected using SSc markers which derive from the same individual and which for example originate from a cDNA bank produced individually for the patient or a group of patients for example within the scope of individualised medicine. By way of example, homologues of the specified SSc markers with the sequences SEQ ID. No. 1 to 955 or subsequences thereof can be used.


Autoantibodies can be formed by the patient already many years prior to the occurrence of the first symptoms of disease. An early identification, diagnosis and also prognosis and preventative treatment or lifestyle change and other possibilities for prevention are therefore possible even years prior to the visible outbreak of the disease. The devices, means and methods according to the invention enable a very early intervention compared with known methods, which significantly improves the prevention, treatment possibilities and effects of SSc.


Since the SSc-associated autoantibody profiles change during the establishment and treatment/therapy of SSc, the invention also enables the detection and monitoring of SSc at any stage of the development and treatment and also monitoring within the scope of SSc aftercare. The means according to the invention, for example a corresponding diagnostic device or a test kit, also allow simple handling at home by the patient and an economical routine precautionary measure for early identification.


In particular due to the use of antigens as specific markers for SSc which derive from sequences already known, for example from commercial cDNA banks, test subjects can be tested and any present SSc-associated autoantibodies can be detected in these test subjects, even if the corresponding autoantigens are not (yet) known in these test subjects.


Different patients can have different SSc-associated autoantibody profiles, for example different cohorts or population groups can differ from one another. Here, any patient can form one or more different SSc-associated autoantibodies during the course of the development of SSc and the progression of the SSc disease, that is to say even different autoantibody profiles. In addition, the composition and/or the amount of formed autoantibodies can change during the course of the SSc development and progression of the disease, such that a quantitative evaluation is necessary. The therapy/treatment of SSc leads to changes in the composition and/or the amount of SSc-associated autoantibodies. The large selection of SSc markers according to the invention which are provided with this invention enables the individual compilation of SSc markers in an arrangement, i.e. a panel, for individual patients, groups of patients, certain cohorts, population groups and the like. In one individual case, the use of one SSc marker may therefore be sufficient, whereas in other cases at least two or more SSc markers must be used together or in combination in order to create a conclusive autoantibody profile.


Compared with other biomarkers, the detection of SSc-associated autoantibodies for example in the serum or plasma of patients has the advantage of high stability and storage capability and good detectability. The presence of autoantibodies also is not subject to a circadian rhythm, and therefore the sampling is independent of the time of day, food intake, and the like.


In addition, the SSc-associated autoantibodies can be detected with the aid of the corresponding antigens/autoantigens in known assays, such as ELISA or Western Blot, and the results can be checked in this way.


In the sense of the invention, an interaction between the SSc marker and the serum in question, for example an autoantibody of the patient, is detected. Such an interaction is, for example, a bond, in particular a binding substance on at least one SSc-specific marker, or, in the case that the SSc-specific marker is a nucleic acid, for example a cDNA, the hybridisation with a suitable substance under selected conditions, in particular stringent conditions (for example as defined conventionally in J. Sambrook, E. F. Fritsch, T. Maniatis (1989), Molecular cloning: A laboratory manual, 2nd Edition, Cold Spring Habor Laboratory Press, Cold Spring Habor, USA or Ausubel, “Current Protocols in Molecular Biology”, Green Publishing Associates and Wiley Interscience, N.Y. (1989)). One example of stringent hybridisation conditions is: hybridisation in 4×SSC at 65° C. (alternatively in 50% formamide and 4×SSC at 42° C.), followed by a number of washing steps in 0.1×SSC at 65° C. for a total of approximately one hour. An example of less stringent hybridisation conditions is hybridisation in 4×SSC at 37° C., followed by a number of washing steps in 1×SSC at room temperature. The interaction between the bodily fluid or tissue sample from a patient and the markers for SSc is preferably a protein-protein interaction.


In accordance with the invention, such substances, for example antigens, autoantigens and SSc-associated autoantibodies, are part of a bodily fluid, in particular blood, whole blood, blood plasma, blood serum, patient serum, urine, cerebrospinal fluid, synovial fluid or a tissue sample from the patient. The invention in particular relates to the use of these bodily fluids and tissue samples for early detection, diagnosis, prognosis, therapy control and aftercare.


The SSc-specific markers, in a further embodiment of the invention, have a recognition signal that is addressed to the substance to be bound (for example antibody, nucleic acid). In accordance with the invention, the recognition signal for a protein is preferably an epitope and/or paratope and/or hapten, and for a cDNA is preferably a hybridisation or binding region.


Homologues of the markers according to the invention SEQ ID No. 1 to 955, as presented in the claims for example, are also included. Within the sense of the invention, homologues are those with homology of the amino or nucleic acid sequence and those in which the corresponding sequence is modified, for example the protein variants, which indeed have the same amino acid sequence, but differ with regard to the modification, in particular the post-translational modification.


In accordance with the invention, modifications of the nucleic acid sequence and of the amino acid sequence, for example citrullination, acetylation, phosphorylation, glycosylation, ethylation, or polyA strand extensions and further modifications known as appropriate to a person skilled in the art are included.


Homologues also include sequence homologues of the markers and subsequences thereof. Sequence homologues are, for example, nucleic acid sequences and/or protein sequences that have an identity with the SSc markers of the sequences SEQ ID No. 1 to 955 of at least 70% or 80%, preferably 90% or 95%, particularly preferably 96% or 97% or more, for example 98% or 99%. In a particularly preferred embodiment of the invention, for the case in which the SSc markers are antigens, the homology in the sequence range in which the antigen-antibody or antigen-autoantibody interaction takes place, is at least 95%, preferably at least 97%, particularly preferably at least 99%. For example, mutations such as base exchange mutations, frameshift mutations, base insertion mutations, base loss mutations, point mutations and insertion mutations, are included in accordance with the invention.


The invention also relates to subsequences of the SSc markers with the sequence SEQ ID No. 1 to 955. Subsequences also include nucleic acid or amino acid sequences that are shortened compared with the entire nucleic acid or the entire protein/peptide. Here, the deletion may occur at the end or the ends and/or within the sequence. For example, subsequences and/or fragments that have 50 to 100 nucleotides or 70-120 nucleotides of the sequence SEQ ID No. 1 to 955 are included. Homologues of subsequences are also included in accordance with the invention. In a particular embodiment, the SSc markers are shortened compared with the sequences SEQ ID No. 1 to 955 to such an extent that they still consist only of the binding point(s) for the SSc-associated autoantibody in question. In accordance with the invention, SSc markers are also included that differ from the sequences SEQ ID No. 1 to 955 in that they contain one or more insertions, wherein the insertions for example are 1 to 100 or more nucleotide/amino acids long, preferably 5 to 50, particularly preferably 10 to 20 nucleotides/amino acids long and the sequences are otherwise identical however or homologous to sequences SEQ ID No. 1 to 955. Subsequences that have at least 90%, preferably at least 95%, particularly preferably 97% or 98%, of the length of the SSc markers according to the invention with sequences SEQ ID No. 1 to 955 are particularly preferred.


In a further embodiment, the respective SSc marker can be represented in different quantities in one or more regions in the arrangement or on the substrate or in a panel. This allows a variation of the sensitivity. The regions may each have a totality of SSc markers, that is to say a sufficient number of different SSc markers, in particular 2, 3, 4, 5, 6, 7, 8, 9 or 10 or more different SSc markers. By way of example, 20 to 50 (numerically) or more, preferably more than 100, particularly preferably 150 or more, for example 25,000 or 5,000 or 10,000 different or same SSc marker sequences and where applicable further nucleic acids and/or proteins, in particular other biomarkers can be represented on the substrate or in the panel.


Within the scope of this invention, “arrangement” is synonymous with “array” and “panel”. If this “array” is used to identify substances on SSc markers, this is to be understood preferably to be an “assay” or a bead or a diagnostic device or a screening assay. In a preferred embodiment, the arrangement is designed such that the markers represented on the arrangement are present in the form of a grid on a substrate. Furthermore, those arrangements are preferred that permit a high-density arrangement of SSc markers. The markers are preferably spotted. Such high-density spotted arrangements are disclosed for example in WO 99/57311 and WO 99/57312 and can be used advantageously in a robot-supported automated high-throughput method.


Within the scope of this invention, however, the term “assay” or diagnostic device likewise comprises those embodiments such as ELISA, bead-based assay, line assay, Western Blot, and immunochromatographic methods (for example what are known as lateral flow immunoassays) or similar immunological single or multiplex detection methods.


A “protein array” in the sense of this invention is the systematic arrangement of SSc markers on a solid substrate, wherein the substrate can have any shape and/or size, and wherein the substrate is preferably a solid substrate.


The SSc markers of the arrangement are fixed on the substrate, preferably spotted or immobilised, printed on or the like, in particular in a reproducible manner. One or more SSc markers can be present multiple times in the totality of all SSc markers and may be present in different quantities based on a spot. Furthermore, the SSc markers can be standardised on the substrate (for example by means of serial dilution series of, for example, human globulins as internal calibrators for data normalisation and quantitative evaluation). A standard (for example a gold standard) can also be applied to the substrate where necessary.


In a further embodiment, the SSc markers are present as clones. Such clones can be obtained for example by means of a cDNA expression library according to the invention. In a preferred embodiment, such expression libraries are obtained using expression vectors from a cDNA expression library comprising the cDNAs of the SSc-specific marker sequences. These expression vectors preferably contain inducible promoters. The induction of the expression can be carried out for example by means of an inducer, such as IPTG. Suitable expression vectors are described in Terpe et al. (Terpe T Appl Microbiol Biotechnol. 2003 Jan; 60(5):523-33).


Expression libraries are known to a person skilled in the art; they can be produced in accordance with standard works, such as Sambrook et al, “Molecular Cloning, A laboratory handbook, 2nd edition (1989), CSH press, Cold Spring Harbor, New York. Expression libraries that are tissue-specific (for example human tissue, in particular human organs) are furthermore preferable. Further, expression libraries that can be obtained by means of exon trapping are also included in accordance with the invention.


Protein arrays or corresponding expression libraries that do not exhibit any redundancy (what is known as a Uniclone® library) and that can be produced for example in accordance with the teaching of WO 99/57311 and WO 99/57312 are furthermore preferred. These preferred Uniclone® libraries have a high proportion of non-defective fully expressed proteins of a cDNA expression library.


Within the scope of this invention, the clones can also be, but are not limited to, transformed bacteria, recombinant phages or transformed cells of mammals, insects, fungi, yeasts or plants.


In addition, the SSc markers can be present in the respective form in the form of a fusion protein, which for example contains at least one affinity epitope or “tag”, wherein the tag is selected for example from c-myc, his tag, arg tag, FLAG, alkaline phosphatase, V5 tag, T7 tag or strep tag, HAT tag, NusA, S tag, SBP tag, thioredoxin, DsbA, or the fusion protein has one or more additional domains for example, such as a cellulose-binding domain, green fluorescent protein, maltose-binding protein, calmodulin-binding protein, glutathione S-transferase or lacZ.


In a further embodiment the invention relates to an assay, for example a multiplex assay, a bead-based assay, or protein array for identifying and characterising a substance, for example a hit, a lead substance, or an active substance for SSc. Here, a substance to be tested is used. This can be any native or non-native biomolecule, a (synthetic) chemical molecule, a natural substance, a mixture or a substance library. Once the substance to be tested has contacted an SSc marker, the binding success is evaluated, for example with use of commercially available image-analysis software (GenePix Pro (Axon Laboratories), Aida (Raytest), ScanArray (Packard Bioscience).


Binding according to the invention, binding success, interactions, for example protein-protein interactions (for example protein to SSc marker, such as antigen/antibody) or corresponding “means for detecting the binding success” can be visualised for example by means of fluorescence labelling, biotinylation, radio-isotope labelling or colloid gold or latex particle labelling in the conventional manner. Bound antibodies are detected with the aid of secondary antibodies, which are labelled using commercially available reporter molecules (for example Cy, Alexa, Dyomics, FITC or similar fluorescent dyes, colloidal gold or latex particles), or with reporter enzymes, such as alkaline phosphatase, horseradish peroxidase, etc. and the corresponding colorimetric, fluorescent or chemoluminescent substrates. A readout is performed for example by means of a microarray laser scanner, a CCD camera or visually.


In a further embodiment, the invention relates to a drug or an active substance or prodrug for SSc, developed and obtainable by the use of an SSc marker according to the invention.


The invention also relates to the use of an SSc marker selected from sequences SEQ ID No. 1 to 955 and subsequences of SEQ ID No. 1 to 955 with at least 90%, preferably at least 95% of the length of SEQ ID No. 1 to 955 and homologues of SEQ ID No. 1 to 955 and subsequences thereof with an identity of at least 95%, preferably at least 98% or more, to the corresponding sequences and proteins/peptides coded by the sequences SEQ ID No. 1 to 638, coded by the subsequences thereof and homologues as affinity material for carrying out an apheresis or blood washing for patients with SSc, i.e. apheresis of SSc autoantibodies. The invention thus relates to the use of the markers according to the invention, preferably in the form of an arrangement, as affinity material for carrying out an apheresis or a blood washing in the broader sense, wherein substances from bodily fluids from a patient with SSc, such as blood or plasma, bind to the markers according to the invention and consequently can be removed selectively from the bodily fluid. The application in blood washing is a special case of use of the SSc markers as a target.





The following examples and drawings explain the invention, but do not limit the invention to the examples. In the following drawings, systemic sclerosis is denoted by PPS (progressive systemic sclerosis).



FIG. 1 shows a volcano plot of the relative antigen reactivities of the SSc patients compared to healthy controls.



FIG. 2 shows a volcano plot of the antigen reactivities of the SSc patients compared to a combined group of patients with different autoimmune diseases such as SSC, SPA, early rheumatoid arthritis and SPA.



FIG. 3: shows autoantibody reactivities in SSc patient sera compared to healthy controls and SSC patients.



FIG. 4: shows the frequency of the autoantibody reactivities of selected antigens in SSc patients and healthy test subjects. A threshold value of 3 SD deviations above the mean value of the healthy test subject was applied.



FIG. 5: shows a volcano plot of the autoantibody reactivities of SSc patients with diffuse sub-form compared to healthy controls.



FIG. 6: shows the frequency of the autoantibody reactivities of selected antigens in the limited and diffuse SSc subform. A threshold value of 3 standard deviations above the mean value of the healthy test subject was applied.



FIG. 7: shows a volcano plot of the autoantibody reactivities of SSc patients with limited subform compared to healthy controls.



FIG. 8: shows a volcano plot of the autoantibody reactivities of SSc patients with overlap syndrome compared to healthy controls



FIG. 9: shows the frequency of the autoantibodies in anti-CENP- and anti-Sc170-negative patients.



FIG. 10: shows Receiver Operating Characteristic curves (ROCs) for the diagnosis of SSc compared to healthy test subjects; A) ROC curve panel I, B) ROC curve panel II.



FIG. 11: shows a boxplot based on the anti-KDM6B and anti-BICD2 ELISA measurements for the diagnosis of SSc compared to healthy controls.



FIG. 12: shows Receiver Operating Characteristic curves (ROCs) for the ELISA determination of anti-KDM6B and anti-BICD2 antibodies:

    • a) anti-KDM6B ELISA: SSc compared to healthy controls
    • b) Anti-BICD2 ELISA: SSc compared to healthy controls





EXAMPLES
Example 1
Selection of the SSc Patient and Control Samples Patients and Test Subjects

Selection of the patient groups to be tested: Blood samples were analysed from 100 SSc patients, 100 patients with SLS, 537 patients with early rheumatoid arthritis (“RA”; period of disease less than 6 months) and 82 patients with ankylosing spondylitis (SPA) or Bekhterev's disease. 343 blood samples from the Bavarian Red Cross (BRC) were used as control group. An informed consent of the Ethics Commission of the clinical partners and of the biobank of the BRC was received from all test subjects.









TABLE 1







Patient samples and clinical data




















SSc







SSc
SSc
SSc
no
early




Subgroup
Subgroup
Subgroup
specification
RA



SLE
lSSc
dSSc
SSc-OV
of the subgroup
(<6 months)
SPA
Healthy



















Number
100
50
32
9
9
537  
82  
343  


of


patients


or


samples


Average
39.8 +/− 11.9
61.53 +/− 16.97
53.88 +/− 14.75
51.78 +/− 9.18
47.56 +/− 16.97
56.8 +/− 14.3
43.7 +/− 10.1
47.7 +/− 11.7


age


(years)


Number
 83
50
32
8
9
62.2
15.9
58.3


of


female


patients


or


samples


ANA-
100
47
32
9
7
NA
NA
NA


positive


Anti-
NA
30
 4
2
2
NA
NA
NA


CENP


Anti-
NA
 9
20
1
2
NA
NA
NA


Scl70









Example 2
Antigen Production

Five cDNA libraries that had been produced from different human tissues (foetal brain, intestine, lung, liver and T-cells) were used for the production of the recombinant antigens. All cDNAs were expressed in E. coli under the transcriptional control of the lactose-inducible promoter. The resultant proteins carry, at their amino terminus, an additional sequence for a hexahistidine purification tag (His6 tag). Target antigens which were not present in the cDNA library were produced by chemical synthesis (Life Technologies) and cloned into the expression vector pQE30-NST, which already codes an amino-terminal His6 tag.


Following recombinant expression of the proteins, these were isolated in denaturising conditions and purified by means of metal affinity chromatography (IMAC). The proteins were lyophilised and stored at −20° C. until further use.


Example 3
Production of Bead-Based Arrays (BBAs)

The production of BBAs was adapted to a microtitre plate format, such that 384 coupling reactions could be assessed in parallel using automated pipette systems (Starlet, Hamilton Robotics, Evo Freedom 150, Tecan). For the use of automated pipette systems, the individual bead regions were transferred into coupling pates (96 well Greiner) and the antigens were transferred into 2D barcode vessels (Thermo Scientific). For each coupling reaction, 0.6 to 2.5 million beads and, depending on the antigen, 1 to 100 μg protein were used.


All washing and pipetting steps of the coupling reaction were carried out in coupling plates which were fixed on magnets. The beads were washed twice with 100 μl L×AP buffer (100 mM NaH2PO4, pH 6.2) and then received in 120 μl L×AP buffer. For the activation, 15 μl 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC; 50 mg/ml) and 15 μl N-hydroxysulfosuccinimide (sulfo-NHS; 50 mg/ml) were added by pipette to form a bead suspension, and these suspensions were then incubated for 20 minutes in the shaker (RT, 900 rpm, protected against light). The beads were then washed 3× with 150 μl L×KPT buffer and then the protein solution was added. Following an incubation period of two hours in the shaker (RT, 900 rpm, protected against light), the beads were then washed three times with 150 μl LxKPT buffer. To block free binding points, 100 μl L×CBSP buffer (PBS, 1% BSA, 0.05% ProClin300) were added, and these mixtures were then incubated for 20 min in the shaker (RT, 900 rpm, protected against light). This was followed by incubation over night at 4-8° C. The BBA was produced by the combination of beads coupled to antigens and was stored at 4-8° C., protected against light, until use.


Example 4
Application of BBAs

For application, BBAs were incubated with sera and all IgG-based autoantibodies bonded to antigens were detected with the aid of a secondary antibody. In order to enable a high throughput of measurements, the application of BBAs was adapted to a microtitre plate format so that either an 8-channel (Starlet, Hamilton Robotics) or a 96-channel (Evo Freedom 150, Tecan) automated pipetting system could be used. The sera to be examined were transferred into 2D barcode vessels and then diluted 1:100 with assay buffer (PBS, 0.5% BSA, 10% E. coli lysate, 50% low-cross buffer (Candor Technologies)). In order to neutralise human antibodies directed against E. coli, a pre-incubation of the sera dilutions was performed for 20 min. In this time, 500 beads per bead region were distributed in the assay plate. 50 μl of diluted serum were added to the beads in the coupling plate, and the reaction mixtures were incubated for 18-22 h in the shaker (4-8° C., 900 rpm, protected against light). After three washing steps in each case with 100 μl L×WPT buffer, 5 μg/ml of the detection antibody goat anti-human IgG-PE (Dianova) were added to the reaction mixtures and incubated for 1 h in the shaker (RT, 900 rpm). The beads were then washed three times with 100 μl L×WPT and incorporated in 100 μl carrier liquid (Luminex). The fluorescence signal of the beads was detected with the aid of the FlexMAP3D instrument. Here, the bead count on the one hand and the MFI value (median fluorescence intensity) on the other hand were measured.


Example 5
Biostatistical Analysis

The biostatistical analysis comprised univariate and multivariate methods for describing the statistical properties of individual antigens and of groups of antigens. In order to discover interesting candidates for panels, the key property was a good separation between the groups of samples based on the MFI values. In order to find antigen candidates for panel generation, univariate testing, receiver operating characteristic (ROC) analyses, correlation profiles, powered partial least squares discriminant analysis (PPLS-DA) and random forests were used as methods. Biostatistical analyses were subject to expert assessment in order to define final antigen panels.


Before the statistical analysis, the MFI values of log2-transformed antigens in which more than 20% of the values were missing were excluded from the analysis, and missing values were replaced by median imputation. A quantile normalisation was carried out under consideration of the reference sera in order to normalise, per BBA set, all measured samples on individual plates.


Besides descriptive standardisation for MFI values, non-parametric tests were also carried out with the aid of the two-sided Mann-Whitney-U test in order to uncover differences in the median values of the groups. The test level for multiple testing was corrected in accordance with the Bonferroni-Holm procedure. In addition, the Benjamin-Hochberg procedure inclusive of the determination of the False Discovery Rate (FDR, q-value) was applied. In addition, fold-change and effect size were determined. In order to assess the classification quality, an ROC analysis was carried out, within the scope of which sensitivity, specificity and the area under the ROC curve (AUC) were calculated, in each case inclusive of the 95% confidence interval on the basis of the bootstrap method. Boxplots and volcano plots were used for graphical representation. A scoring system was implemented on the basis of the univariate results.


By means of the application of a PPLS-DA, it was attempted to maximise the correlation between the components and the response matrix. A linear discriminant analysis with the latent component as predictors was used for the final classification. A random forest was applied, in which binary decision trees are combined. The decision trees were formed on the basis of a number of bootstrap samples of a training sample and by random selection of a subgroup of explaining variables at each node. The number of input variables, which was selected randomly with each division step, was determined as the square root of the total number of variables, and the number of trees in the random forest was set to 1000. A cross validation with 500 times throughput was implemented for both multi-variant approaches.


Example 6
Autoantibodies/Antigen Reactivities Differentiate SSc From Healthy Controls, SLE, Rheumatoid Arthritis and Other Autoimmune Diseases (AIDs)

In a first screening the antigen reactivities of 100 SSc patients, 537 patients with early RA, 82 patients with SPA, and 343 healthy controls categorised in accordance with age and sex were differentially tested. For this purpose, the autoantibody reactivities of these blood samples were tested on 5857 antigens coupled to Luminex beads.


In order to identify antigens with which the group of all SSc patients can be distinguished from different control groups consisting of healthy samples and patients with various rheumatic diseases, univariate statistical tests were carried out. The result of the statistical test is illustrated as a volcano plot for all 5857 antigens. In the volcano plot, the x-axis shows the relative change of the antigen reactivity in SSc patients compared with healthy controls (FIG. 1) and AID patients (FIG. 2). The y-axis presents the p-value of the statistical tests. FIGS. 1 and 2 show that specific autoantibody reactivities were found which are increased in the group of all SSc and which can distinguish both from healthy donors and from patients with rheumatic diseases.


Table 2 comprises all autoantigens identified in SSc patients (Table 2)).









TABLE 2







Summary of the (auto)antigens identified in SSc (also


referred to as “markers” or “biomarkers”)


What is specified is the sequential sequence ID, the gene ID,


gene symbol, and the gene name. The group denotes the use of


the biomarker for the identification of all SSc patients or


specific SSc subgroups on the basis of a statistical threshold


value of p < 0.05 and relatively higher reactivity (fold-change)


compared to the control group of greater than 1.5.


Group 1: Markers for identification of all SSc patients


regardless of the clinical subform;


Group 2: Markers for identification of diffuse SSc (dSSc);


Group 3: Markers for identification of limited SSc (lSSc);


Group 4: Markers for identification of SSc overlap syndrome


(overlap syndrome; SSc-OS) and


Group 5: additional markers which are not assigned to any


specific group.

















p < 0.05 and


SEQ




fold-change >


ID

Gene


1.5 in


No.
Gene ID
Symbol
Gene Name
Group
group










Primary antigens/Primary markers












1
23135
KDM6B
lysine (K)-specific
1
SSc; dSSc;





demethylase 6B

lSSc; SSc-







OS


2
23299
BICD2
bicaudal D homolog 2
3
lSSc





(Drosophila)




3
55695
NSUN5
NOL1/NOP2/Sun domain
1
SSc; lSSc





family, member 5




4
51750
RTEL1
regulator of telomere
1
SSc; lSSc





elongation helicase 1




5
11143
MYST2
MYST histone
1
SSc; dSSc





acetyltransferase 2




6
29968
PSAT1
phosphoserine
2
dSSc





aminotransferase 1




7
51368
TEX264
testis expressed 264
2
dSSc







Preferred antigens/preferred markers












8
6737
TRIM21
tripartite motif
1
SSc; dSSc;





containing 21

SSc-OS;







lSSc


9
11194
ABCB8
ATP-binding cassette,
1
SSc; lSSc





sub-family B (MDR/TAP),







member 8




10
57099
AVEN
apoptosis, caspase
1
SSc; lSSc





activation inhibitor




11
7423
VEGFB
vascular endothelial
1
SSc; dSSc;





growth factor B

lSSc; SSc-







OS


12
55049
C19orf60
chromosome 19 open
1
SSc





reading frame 60




13
1058
CENPA
centromere protein A
1
SSc; lSSc;


14
1060
CENPC1
centromere protein C 1
1
SSc; lSSc;







dSSc


15
80152
CENPT
centromere protein T
1
SSc; lSSc


16
1131
CHRM3
cholinergic receptor,
1
SSc; lSSc;





muscarinic 3

SSc-OS


17
64689
GORASP1
golgi reassembly
1
SSc; SSc-OS





stacking protein 1,







65 kDa




18
2997
GYS1
glycogen synthase 1
1
SSc; lSSc





(muscle)




19
10014
HDAC5
histone deacetylase 5
1
SSc


20
80895
ILKAP
integrin-linked kinase-
1
SSc; lSSc





associated







serine/threonine







phosphatase 2C




21
27257
LSM1
LSM1 homolog, U6 small
1
SSc





nuclear RNA associated







(S. cerevisiae)




22
153562
MARVELD2
MARVEL domain
1
SSc; lSSc





containing 2




23
4784
NFIX
nuclear factor I/X
1
SSc; lSSc





(CCAAT-binding







transcription factor)




24
23762
OSBP2
oxysterol binding
1
SSc; lSSc





protein 2




25
415116
PIM3
pim-3 oncogene
1
SSc


26
5364
PLXNB1
plexin B1
1
SSc;


27
11243
PMF1
polyamine-modulated
1
SSc; dSSc;





factor 1

lSSc


28
10450
PPIE
peptidylprolyl
1
SSc; dSSc;





isomerase E

SSc-OS





(cyclophilin E)




29
63976
PRDM16
PR domain containing 16
1
SSc


30
26140
TTLL3
tubulin tyrosine
1
SSc; dSSc;





ligase-like family,







member 3




31
84196
USP48
ubiquitin specific
1
SSc





peptidase 48




32
563
AZGP1
alpha-2-glycoprotein 1,
1
SSc; dSSc;





zinc-binding

lSSc; SSc-







OS


33
7791
ZYX
zyxin
1
SSc; dSSc;


34
55324
ABCF3
ATP-binding cassette,
2
dSSc





sub-family F (GCN20),







member 3




35
39
ACAT2
acetyl-Coenzyme A
2
dSSc





acetyltransferase 2




36
79921
TCEAL4
transcription
2
dSSc





elongation factor A







(SII)-like 4




37
81
ACTN4
actinin, alpha 4
2
dSSc


38
79913
ACTR5
ARP5 actin-related
2
dSSc





protein 5 homolog







(yeast)




39
216
ALDH1A1
aldehyde dehydrogenase
2
dSSc





1 family, member A1




40
80216
ALPK1
alpha-kinase 1
2
dSSc


41
321
APBA2
amyloid beta (A4)
2
dSSc





precursor protein-







binding, family A,







member 2




42
27237
ARHGEF16
Rho guanine exchange
2
dSSc





factor (GEF) 16




43
8623
ASMTL
acetylserotonin O-
2
dSSc





methyltransferase-like




44
23400
ATP13A2
ATPase type 13A2
2
dSSc


45
56946
C11orf30
chromosome 11 open
2
dSSc





reading frame 30




46
56912
C11orf60
chromosome 11 open
2
dSSc





reading frame 60




47
56985
C17orf48
chromosome 17 open
2
dSSc





reading frame 48




48
90580
C19orf52
chromosome 19 open
2
dSSc





reading frame 52




49
51507
C20orf43
chromosome 20 open
2
dSSc





reading frame 43




50
55755
CDK5RAP2
CDK5 regulatory subunit
2
dSSc





associated protein 2




51
51727
CMPK1
cytidine monophosphate
2
dSSc





(UMP-CMP) kinase 1,







cytosolic




52
10391
CORO2B
coronin, actin binding
2
dSSc





protein, 2B




53
9377
COX5A
cytochrome c oxidase
2
dSSc





subunit Va




54
1488
CTBP2
C-terminal binding
2
dSSc





protein 2




55
8529
CYP4F2
cytochrome P450, family
2
dSSc





4, subfamily F,







polypeptide 2




56
9909
DENND4B
DENN/MADD domain
2
dSSc





containing 4B




57
10901
DHRS4
dehydrogenase/reductase
2
dSSc





(SDR family) member 4




58
84062
DTNBP1
dystrobrevin binding
2
dSSc





protein 1




59
1936
EEF1D
eukaryotic translation
2
dSSc





elongation factor 1







delta (guanine







nucleotide exchange







protein)




60
8891
EIF2B3
eukaryotic translation
2
dSSc





initiation factor 2B,







subunit 3 gamma, 58 kDa




61
64787
EPS8L2
EPS8-like 2
2
dSSc


62
9638
FEZ1
fasciculation and
2
dSSc





elongation protein zeta







1 (zygin I)




63
2300
FOXL1
forkhead box L1
2
dSSc


64
2519
FUCA2
fucosidase, alpha-L-2,
2
dSSc





plasma




65
79690
GAL3ST4
galactose-3-O-
2
dSSc





sulfotransferase 4




66
54960
GEMIN8
gem (nuclear organelle)
2
dSSc





associated protein 8




67
51031
GLOD4
glyoxalase domain
2
dSSc





containing 4




68
2934
GSN
gelsolin (amyloidosis,
2
dSSc





Finnish type)




69
3157
HMGCS1
3-hydroxy-3-
2
dSSc





methylglutaryl-Coenzyme







A synthase 1 (soluble)




70
3320
HSP90AA1
heat shock protein
2
dSSc





90 kDa alpha







(cytosolic), class A







member 1




71
3633
INPP5B
inositol polyphosphate-
2
dSSc





5-phosphatase, 75 kDa




72
3654
IRAK1
interleukin-1 receptor-
2
dSSc





associated kinase 1




73
23479
ISCU
iron-sulfur cluster
2
dSSc





scaffold homolog (E.








coli)





74
51520
LARS
leucyl-tRNA synthetase
2
dSSc


75
4057
LTF
lactotransferrin
2
dSSc


76
10724
MGEA5
meningioma expressed
2
dSSc





antigen 5







(hyaluronidase)




77
84954
MPND
MPN domain containing
2
dSSc


78
4437
MSH3
mutS homolog 3 (E.
2
dSSc






coli)





79
23385
NCSTN
nicastrin
2
dSSc


80
4758
NEU1
sialidase 1 (lysosomal
2
dSSc





sialidase)




81
5034
P4HB
prolyl 4-hydroxylase,
2
dSSc





beta polypeptide




82
5187
PER1
period homolog 1
2
dSSc





(Drosophila)




83
5195
PEX14
peroxisomal biogenesis
2
dSSc





factor 14




84
10404
PGCP
plasma glutamate
2
dSSc





carboxypeptidase




85
5493
PPL
periplakin
2
dSSc


86
5575
PRKAR1B
protein kinase, cAMP-
2
dSSc





dependent, regulatory,







type I, beta




87
84867
PTPN5
protein tyrosine
2
dSSc





phosphatase, non-receptor type 5







(striatum-enriched)




88
9230
RAB11B
RAB11B, member RAS
2
dSSc





oncogene family




89
84440
RAB11FIP4
RAB11 family
2
dSSc





interacting protein 4







(class II)




90
10900
RUNDC3A
RUN domain containing
2
dSSc





3A




91
50861
STMN3
stathmin-like 3
2
dSSc


92
81551
STMN4
stathmin-like 4
2
dSSc


93
6814
STXBP3
syntaxin binding
2
dSSc





protein 3




94
93426
SYCE1
synaptonemal complex
2
dSSc





central element protein







1




95
6904
TBCD
tubulin folding
2
dSSc





cofactor D




96
7110
TMF1
TATA element modulatory
2
dSSc





factor 1




97
10102
TSFM
Ts translation
2
dSSc





elongation factor,







mitochondrial




98
7296
TXNRD1
thioredoxin reductase 1
2
dSSc


99
55585
UBE2Q1
ubiquitin-conjugating
2
dSSc





enzyme E2Q family







member 1




100
92912
UBE2Q2
ubiquitin-conjugating
2
dSSc





enzyme E2Q family







member 2




101
65264
UBE2Z
ubiquitin-conjugating
2
dSSc





enzyme E2Z




102
54915
YTHDF1
YTH domain family,
2
dSSc





member 1




103
7764
ZNF217
zinc finger protein 217
2
dSSc


104
10290
SPEG
SPEG complex locus
3
lSSc


105
84936
ZFYVE19
zinc finger, FYVE
3
lSSc





domain containing 19




106
26574
AATF
apoptosis antagonizing
3
lSSc





transcription factor




107
10152
ABI2
abl-interactor 2
3
lSSc


108
84320
ACBD6
acyl-Coenzyme A binding
3
lSSc





domain containing 6




109
9049
AIP
aryl hydrocarbon
3
lSSc





receptor interacting







protein




110
286
ANK1
ankyrin 1, erythrocytic
3
lSSc


111
396
ARHGDIA
Rho GDP dissociation
3
lSSc





inhibitor (GDI) alpha




112
51582
AZIN1
antizyme inhibitor 1
3
lSSc


113
128061
C1orf131
chromosome 1 open
3
lSSc





reading frame 131




114
79095
C9orf16
chromosome 9 open
3
lSSc





reading frame 16




115
11335
CBX3
chromobox homolog 3
3
lSSc





(HP1 gamma homolog,








Drosophila)





116
92922
CCDC102A
coiled-coil domain
3
lSSc





containing 102A




117
23582
CCNDBP1
cyclin D-type binding-
3
lSSc





protein 1




118
64946
CENPH
centromere protein H
3
lSSc


119
79585
CORO7
coronin 7
3
lSSc


120
1653
DDX1
DEAD (Asp-Glu-Ala-Asp)
3
lSSc





box polypeptide 1




121
23220
DTX4
deltex homolog 4
3
lSSc





(Drosophila)




122
51143
DYNC1LI1
dynein, cytoplasmic 1,
3
lSSc





light intermediate







chain 1




123
1977
EIF4E
eukaryotic translation
3
lSSc





initiation factor 4E




124
256364
EML3
echinoderm microtubule
3
lSSc





associated protein like







3




125
55740
ENAH
enabled homolog
3
lSSc





(Drosophila)




126
8320
EOMES
eomesodermin homolog
3
lSSc





(Xenopus laevis)




127
9130
FAM50A
family with sequence
3
lSSc





similarity 50, member A




128
89848
FCHSD1
FCH and double SH3
3
lSSc





domains 1




129
2549
GAB1
GRB2-associated binding
3
lSSc





protein 1




130
2653
GCSH
glycine cleavage system
3
lSSc





protein H (aminomethyl







carrier)




131
10755
GIPC1
GIPC PDZ domain
3
lSSc





containing family,







member 1




132
28964
GIT1
G protein-coupled
3
lSSc





receptor kinase







interacting ArfGAP 1




133
65056
GPBP1
GC-rich promoter
3
lSSc





binding protein 1




134
2962
GTF2F1
general transcription
3
lSSc





factor IIF, polypeptide







1, 74 kDa




135
3024
HIST1H1A
histone cluster 1, H1a
3
lSSc


136
3551
IKBKB
inhibitor of kappa
3
lSSc





light polypeptide gene







enhancer in B-cells,







kinase beta




137
57461
ISY1
ISY1 splicing factor
3
lSSc





homolog (S. cerevisiae)




138
3791
KDR
kinase insert domain
3
lSSc





receptor (a type III







receptor tyrosine







kinase)




139
22920
KIFAP3
kinesin-associated
3
lSSc





protein 3




140
4137
MAPT
microtubule-associated
3
lSSc





protein tau




141
9412
MED21
mediator complex
3
lSSc





subunit 21




142
55034
MOCOS
molybdenum cofactor
3
lSSc





sulfurase




143
64981
MRPL34
mitochondrial ribosomal
3
lSSc





protein L34




144
55968
NSFL1C
NSFL1 (p97) cofactor
3
lSSc





(p47)




145
10130
PDIA6
protein disulfide
3
lSSc





isomerase family A,







member 6




146
55857
PLK1S1
polo-like kinase 1
3
lSSc





substrate 1




147
23654
PLXNB2
plexin B2
3
lSSc


148
6004
RGS16
regulator of G-protein
3
lSSc





signaling 16




149
6047
RNF4
ring finger protein 4
3
lSSc


150
6125
RPL5
ribosomal protein L5
3
lSSc


151
6285
S100B
S100 calcium binding
3
lSSc





protein B




152
6418
SET
SET nuclear oncogene
3
lSSc


153
6421
SFPQ
splicing factor
3
lSSc





proline/glutamine-rich







(polypyrimidine tract







binding protein







associated)




154
6456
SH3GL2
SH3-domain GRB2-like 2
3
lSSc


155
1059
CENPB
centromere protein B,
3
lSSc





80 kDa




172
255626
HIST1H2BA
histone cluster 1, H2ba
5
lSSc; SSc-







OS


156
84501
SPIRE2
spire homolog 2
3
lSSc





(Drosophila)




157
6709
SPTAN1
spectrin, alpha, non-
3
lSSc





erythrocytic 1 (alpha-







fodrin)




158
6741
SSB
Sjogren syndrome
3
lSSc





antigen B (autoantigen







La)




159
25949
SYF2
SYF2 homolog, RNA
3
lSSc





splicing factor (S.







cerevisiae)




160
6880
TAF9
TAF9 RNA polymerase II,
3
lSSc





TATA box binding







protein (TBP)-







associated factor,







32 kDa




161
11022
TDRKH
tudor and KH domain
3
lSSc





containing




162
7265
TTC1
tetratricopeptide
3
lSSc





repeat domain 1




163
23331
TTC28
tetratricopeptide
3
lSSc





repeat domain 28




164
11344
TWF2
twinfilin, actin-
3
lSSc





binding protein,







homolog 2 (Drosophila)




165
55833
UBAP2
ubiquitin associated
3
lSSc





protein 2




166
9094
UNC119
unc-119 homolog (C.
3
lSSc





elegans)




167
58525
WIZ
widely interspaced zinc
3
lSSc





finger motifs




168
7494
XBP1
X-box binding protein 1
3
lSSc


169
56252
YLPM1
YLP motif containing 1
3
lSSc


170
51538
ZCCHC17
zinc finger, CCHC
3
lSSc





domain containing 17




171
84240
ZCCHC9
zinc finger, CCHC
3
lSSc





domain containing 9




173
11332
ACOT7
acyl-CoA thioesterase 7
4
SSc-OS


174
10120
ACTR1B
ARP1 actin-related
4
SSc-OS





protein 1 homolog B,







centractin beta (yeast)




175
118
ADD1
adducin 1 (alpha)
4
SSc-OS


176
9131
AIFM1
apoptosis-inducing
4
SSc-OS





factor, mitochondrion-







associated, 1




177
203
AK1
adenylate kinase 1
4
SSc-OS


178
8165
AKAP1
A kinase (PRKA) anchor
4
SSc-OS





protein 1




179
207
AKT1
v-akt murine thymoma
4
SSc-OS





viral oncogene homolog







1




180
29945
ANAPC4
anaphase promoting
4
SSc-OS





complex subunit 4




181
54522
ANKRD16
ankyrin repeat domain
4
SSc-OS





16




182
203286
ANKS6
ankyrin repeat and
4
SSc-OS





sterile alpha motif







domain containing 6




183
324
APC
adenomatous polyposis
4
SSc-OS





coli




184
397
ARHGDIB
Rho GDP dissociation
4
SSc-OS





inhibitor (GDI) beta




185
140459
ASB6
ankyrin repeat and SOCS
4
SSc-OS





box-containing 6




186
513
ATP5D
ATP synthase, H +
4
SSc-OS





transporting,







mitochondrial F1







complex, delta subunit




187
10476
ATP5H
ATP synthase, H +
4
SSc-OS





transporting,







mitochondrial F0







complex, subunit d




188
60370
AVPI1
arginine vasopressin-
4
SSc-OS





induced 1




189
146712
B3GNTL1
UDP-GlcNAc:betaGal
4
SSc-OS





beta-1,3-N-







acetylglucosaminyltransferase-







like 1




190
593
BCKDHA
branched chain keto
4
SSc-OS





acid dehydrogenase E1,







alpha polypeptide




191
27154
BRPF3
bromodomain and PHD
4
SSc-OS





finger containing, 3




192
64776
C11orf1
chromosome 11 open
4
SSc-OS





reading frame 1




193
144097
C11orf84
chromosome 11 open
4
SSc-OS





reading frame 84




194
55195
C14orf105
chromosome 14 open
4
SSc-OS





reading frame 105




195
55257
C20orf20
chromosome 20 open
4
SSc-OS





reading frame 20




196
51300
C3orf1
chromosome 3 open
4
SSc-OS





reading frame 1




197
763
CA5A
carbonic anhydrase VA,
4
SSc-OS





mitochondrial




198
794
CALB2
calbindin 2
4
SSc-OS


199
822
CAPG
capping protein (actin
4
SSc-OS





filament), gelsolin-







like




200
23624
CBLC
Cas-Br-M (murine)
4
SSc-OS





ecotropic retroviral







transforming sequence c




201
54862
CC2D1A
coiled-coil and C2
4
SSc-OS





domain containing 1A




202
339230
CCDC137
coiled-coil domain
4
SSc-OS





containing 137




203
55036
CCDC40
coiled-coil domain
4
SSc-OS





containing 40




204
124808
CCDC43
coiled-coil domain
4
SSc-OS





containing 43




205
728642
CDC2L2
cell division cycle 2-
4
SSc-OS





like 2 (PITSLRE







proteins)




206
79959
CEP76
centrosomal protein
4
SSc-OS





76 kDa




207
55748
CNDP2
CNDP dipeptidase 2
4
SSc-OS





(metallopeptidase M20







family)




208
116840
CNTROB
centrobin, centrosomal
4
SSc-OS





BRCA2 interacting







protein




209
8161
COIL
coilin
4
SSc-OS


210
1410
CRYAB
crystallin, alpha B
4
SSc-OS


211
1674
DES
desmin
4
SSc-OS


212
54505
DHX29
DEAH (Asp-Glu-Ala-His)
4
SSc-OS





box polypeptide 29




213
22982
DIP2C
DIP2 disco-interacting
4
SSc-OS





protein 2 homolog C







(Drosophila)




214
1810
DR1
down-regulator of
4
SSc-OS





transcription 1, TBP-







binding (negative







cofactor 2)




215
23741
EID1
EP300 interacting
4
SSc-OS





inhibitor of







differentiation 1




216
10613
ERLIN1
ER lipid raft
4
SSc-OS





associated 1




217
90736
FAM104B
family with sequence
4
SSc-OS





similarity 104, member







B




218
58516
FAM60A
family with sequence
4
SSc-OS





similarity 60, member A




219
2194
FASN
fatty acid synthase
4
SSc-OS


220
2209
FCGR1A
Fc fragment of IgG,
4
SSc-OS





high affinity Ia,







receptor (CD64)




221
23307
FKBP15
FK506 binding protein
4
SSc-OS





15, 133 kDa




222
23770
FKBP8
FK506 binding protein
4
SSc-OS





8, 38 kDa




223
8939
FUBP3
far upstream element
4
SSc-OS





(FUSE) binding protein







3




224
26515
FXC1
fracture callus 1
4
SSc-OS





homolog (rat)




225
2954
GSTZ1
glutathione transferase
4
SSc-OS





zeta 1




226
94239
H2AFV
H2A histone family,
4
SSc-OS





member V




227
3178
HNRNPA1
heterogeneous nuclear
4
SSc-OS





ribonucleoprotein A1




228
92906
HNRPLL
heterogeneous nuclear
4
SSc-OS





ribonucleoprotein L-







like




229
440498
HSBP1L1
heat shock factor
4
SSc-OS





binding protein 1-like







1




230
3312
HSPA8
heat shock 70 kDa
4
SSc-OS





protein 8




231
134728
IRAK1BP1
interleukin-1 receptor-
4
SSc-OS





associated kinase 1







binding protein 1




232
3735
KARS
lysyl-tRNA synthetase
4
SSc-OS


233
8645
KCNK5
potassium channel,
4
SSc-OS





subfamily K, member 5




234
91012
LASS5
LAG1 homolog, ceramide
4
SSc-OS





synthase 5




235
3991
LIPE
lipase, hormone-
4
SSc-OS





sensitive




236
100129119
LOC100129119
hypothetical
4
SSc-OS





LOC100129119




237
643733
L00643733
hypothetical LOC643733
4
SSc-OS


238
26065
LSM14A
LSM14A, SCD6 homolog A
4
SSc-OS





(S. cerevisiae)




239
149986
LSM14B
LSM14B, SCD6 homolog B
4
SSc-OS





(S. cerevisiae)




240
51599
LSR
lipolysis stimulated
4
SSc-OS





lipoprotein receptor




241
51631
LUC7L2
LUC7-like 2 (S.
4
SSc-OS





cerevisiae)




242
4128
MAOA
monoamine oxidase A
4
SSc-OS


243
23542
MAPK8IP2
mitogen-activated
4
SSc-OS





protein kinase 8







interacting protein 2




244
53615
MBD3
methyl-CpG binding
4
SSc-OS





domain protein 3




245
124995
MRPL10
mitochondrial ribosomal
4
SSc-OS





protein L10




246
65003
MRPL11
mitochondrial ribosomal
4
SSc-OS





protein L11




247
4478
MSN
moesin
4
SSc-OS


248
83463
MXD3
MAX dimerization
4
SSc-OS





protein 3




249
4601
MXI1
MAX interactor 1
4
SSc-OS


250
4780
NFE2L2
nuclear factor
4
SSc-OS





(erythroid-derived 2)-







like 2




251
57224
NHSL1
NHS-like 1
4
SSc-OS


252
4826
NNAT
neuronatin
4
SSc-OS


253
29959
NRBP1
nuclear receptor
4
SSc-OS





binding protein 1




254
129401
NUP35
nucleoporin 35 kDa
4
SSc-OS


255
23594
ORC6L
origin recognition
4
SSc-OS





complex, subunit 6 like







(yeast)




256
55229
PANK4
pantothenate kinase 4
4
SSc-OS


257
57326
PBXIP1
pre-B-cell leukemia
4
SSc-OS





homeobox interacting







protein 1




258
57060
PCBP4
poly(rC) binding
4
SSc-OS





protein 4




259
94274
PPP1R14A
protein phosphatase 1,
4
SSc-OS





regulatory (inhibitor)







subunit 14A




260
56978
PRDM8
PR domain containing 8
4
SSc-OS


261
5764
PTN
pleiotrophin
4
SSc-OS


262
6175
RPLP0
ribosomal protein,
4
SSc-OS





large, P0




263
6188
RPS3
ribosomal protein S3
4
SSc-OS


264
950
SCARB2
scavenger receptor
4
SSc-OS





class B, member 2




265
10806
SDCCAG8
serologically defined
4
SSc-OS





colon cancer antigen 8




266
56948
SDR39U1
short chain
4
SSc-OS





dehydrogenase/reductase







family 39U, member 1




267
10993
SDS
serine dehydratase
4
SSc-OS


268
22872
SEC31A
SEC31 homolog A (S.
4
SSc-OS





cerevisiae)




269
866
SERPINA6
serpin peptidase
4
SSc-OS





inhibitor, clade A







(alpha-1







antiproteinase,







antitrypsin), member 6




270
30011
SH3KBP1
SH3-domain kinase
4
SSc-OS





binding protein 1




271
4086
SMAD1
SMAD family member 1
4
SSc-OS


272
79856
SNX22
sorting nexin 22
4
SSc-OS


273
9580
SOX13
SRY (sex determining
4
SSc-OS





region Y)-box 13




274
6730
SRP68
signal recognition
4
SSc-OS





particle 68 kDa




275
140597
TCEAL2
transcription
4
SSc-OS





elongation factor A







(SII)-like 2




276
6924
TCEB3
transcription
4
SSc-OS





elongation factor B







(SIII), polypeptide 3







(110 kDa, elongin A)




277
10915
TCERG1
transcription
4
SSc-OS





elongation regulator 1




278
6949
TCOF1
Treacher Collins-
4
SSc-OS





Franceschetti syndrome







1




279
26517
TIMM13
translocase of inner
4
SSc-OS





mitochondrial membrane







13 homolog (yeast)




280
22906
TRAK1
trafficking protein,
4
SSc-OS





kinesin binding 1




281
10107
TRIM10
tripartite motif-
4
SSc-OS





containing 10




282
81844
TRIM56
tripartite motif-
4
SSc-OS





containing 56




283
92181
UBTD2
ubiquitin domain
4
SSc-OS





containing 2




284
54576
UGT1A8
UDP
4
SSc-OS





glucuronosyltransferase







1 family, polypeptide







A8




285
23074
UHRF1BP1L
UHRF1 binding protein
4
SSc-OS





1-like




286
55031
USP47
ubiquitin specific
4
SSc-OS





peptidase 47




287
10493
VAT1
vesicle amine transport
4
SSc-OS





protein 1 homolog (T.







californica)




288
22911
WDR47
WD repeat domain 47
4
SSc-OS


289
23613
ZMYND8
zinc finger, MYND-type
4
SSc-OS





containing 8




290
170959
ZNF431
zinc finger protein 431
4
SSc-OS


291
147837
ZNF563
zinc finger protein 563
4
SSc-OS


292
4747
NEFL
neurofilament, light
5
lSSc; SSc-





polypeptide

OS; dSSc;


293
3925
STMN1
stathmin 1
5
lSSc; SSc-







OS; dSSC


294
1039
CDR2
cerebellar
5
lSSc; SSc-





degeneration-related

OS





protein 2, 62 kDa




295
5504
PPP1R2
protein phosphatase 1,
5
lSSc; SSc-





regulatory (inhibitor)

OS





subunit 2




296
55131
RBM28
RNA binding motif
5
lSSc; SSc-





protein 28

OS


297
6749
SSRP1
structure specific
5
lSSc; SSc-





recognition protein 1

OS


298
54969
C4orf27
chromosome 4 open
5
dSSc; lSSc





reading frame 27




299
784
CACNB3
calcium channel,
5
dSSc; lSSc





voltage-dependent, beta







3 subunit




300
842
CASP9
caspase 9, apoptosis-
5
dSSc; lSSc





related cysteine







peptidase




301
1105
CHD1
chromodomain helicase
5
dSSc; lSSc





DNA binding protein 1




302
1687
DFNA5
deafness, autosomal
5
dSSc; lSSc





dominant 5




303
2237
FEN1
flap structure-specific
5
dSSc; lSSc





endonuclease 1




304
2961
GTF2E2
general transcription
5
dSSc; lSSc





factor IIE, polypeptide







2, beta 34 kDa




305
4313
MMP2
matrix metallopeptidase
5
dSSc; lSSc





2 (gelatinase A, 72 kDa







gelatinase, 72 kDa type







IV collagenase)




306
64976
MRPL40
mitochondrial ribosomal
5
dSSc; lSSc





protein L40




307
8775
NAPA
N-ethylmaleimide-
5
dSSc; lSSc





sensitive factor







attachment protein,







alpha




308
100137049
PLA2G4B
phospholipase A2, group
5
dSSc; lSSc





IVB (cytosolic)




309
5515
PPP2CA
protein phosphatase 2
5
dSSc; lSSc





(formerly 2A),







catalytic subunit,







alpha isoform




310
5819
PVRL2
poliovirus receptor-
5
dSSc; lSSc





related 2 (herpesvirus







entry mediator B)




311
9400
RECQL5
RecQ protein-like 5
5
dSSc; lSSc


312
11124
FAF1
Fas (TNFRSF6)
5
SSc-OS;





associated factor 1

dSSc


313
54521
WDR44
WD repeat domain 44
5
dSSc; SSc-







OS


314
7150
TOP1
TOP1
1
SSc


315
23135
KDM6B
KDM6B
1
SSc; dSSc; SS







c-OS;


316
55695
NSUN5
NSUN5
1
SSc; lSSc


317
7644
ZNF91
ZNF91
2
dSSc


318
/
/
PGSScAg318
1
SSc


319
7
/
PGSScAg319
1
SSc










FIG. 3 shows the autoantibody reactivity of SSc patients compared to healthy donors and SLE patients. What is illustrated is what is known as a heatmap of the logarithmised MFI values, wherein the signal height has been reproduced in a black/white scale.


Following univariate statistical evaluation, a threshold value of p<0.05 and a reactivity modified 1.5 times compared with the control group were applied.


Group 1 comprises antigens which in the group of all SSc patients fall short of a threshold value of p<0.05 compared to healthy controls and/or other rheumatic diseases and achieve a reactivity modified by 1.5 times compared to the control group: KDM6B, NSUN5, RTEL1, MYST2, TRIM21, ABCB8, AVEN, VEGFB, C19orf60, CENPA, CENPC1, CENPT, CHRM3, GORASP1, GYS1, HDAC5, ILKAP, LSM1, MARVELD2, NFIX, OSBP2, PIM3, PLXNB1, PMF1, PPIE, PRDM16, TTLL3, USP48, AZGP1, AZGP1, ZYX.


Table 3 summarises the results of the statistical tests for 36 antigens from Table 2 which have a p-value of <0.05 compared to healthy samples.


What are specified are the p-value, the increase in reactivity compared to the control group (Fold-Change), the area under the curve (AUC), and the confidence interval (CI), and also sensitivity (Sens.) and specificity (Spec.).






















Gene
Gene


Fold-

AUC

Sens.

Spec


ID
Symbol
Test
p-value
change
AUC
CI
Sens.
CI
Spec.
CI

























23135
KDM6B
SSc vs
3.43E−13
2.88
0.74
0.65-0.84
0.63
0.52-0.75
0.76
0.71-0.79




HV


23135
KDM6B
SSc vs
5.30E−09
2.23
0.68
0.62-0.74
0.59
0.49-0.7 
0.70
0.66-0.74




AID


1060
CENPC1
SSc vs
8.68E−12
2.18
0.74
0.66-0.83
0.53
0.41-0.64
0.85
0.81-0.88




HV


1060
CENPC1
SSc vs
3.21E−13
2.15
0.71
0.63-0.8 
0.49
0.36-0.62
0.85
0.82-0.87




AID


6737
TRIM21
SSc vs
1.13E−14
3.04
0.74
0.66-0.83
0.59
0.48-0.69
0.76
0.72-0.79




HV


6737
TRIM21
SSc vs
4.44E−09
2.34
0.68
0.61-0.75
0.54
0.41-0.67
0.72
0.66-0.77




AID


55695
NSUN5
SSc vs
2.23E−08
1.57
0.70
0.63-0.78
0.53
0.44-0.62
0.81
0.77-0.85




HV


55695
NSUN5
SSc vs
1.92E−08
1.53
0.68
0.62-0.74
0.52
 0.4-0.63
0.82
0.79-0.86




AID


2997
GYS1
SSc vs
3.21E−08
1.76
0.69
0.64-0.73
0.57
0.45-0.69
0.72
0.66-0.79




HV


2997
GYS1
SSc vs
6.14E−07
1.59
0.65
0.58-0.71
0.52
0.41-0.63
0.70
0.68-0.73




AID


1058
CENPA
SSc vs
7.05E−09
2.20
0.68
0.63-0.73
0.49
0.43-0.56
0.80
0.77-0.83




AID


1058
CENPA
SSc vs
9.47E−08
2.13
0.69
0.63-0.75
0.50
0.37-0.63
0.81
0.75-0.87




HV


11194
ABCB8
SSc vs
9.59E−06
1.42
0.63
0.56-0.71
0.46
0.35-0.58
0.76
0.71-0.81




AID


11194
ABCB8
SSc vs
9.54E−06
1.54
0.64
0.57-0.71
0.46
0.32-0.6 
0.77
0.72-0.82




HV


51750
RTEL1
SSc vs
2.45E−05
2.55
0.64
0.57-0.71
0.53
0.43-0.63
0.67
0.61-0.73




HV


51750
RTEL1
SSc vs
1.28E−05
2.47
0.62
0.57-0.68
0.52
0.41-0.63
0.67
0.63-0.71




AID


7423
VEGFB
SSc vs
1.95E−04
2.41
0.63
0.55-0.7 
0.53
0.43-0.64
0.65
0.58-0.73




HV


7423
VEGFB
SSc vs
5.04E−03
2.23
0.59
0.51-0.66
0.53
0.43-0.63
0.63
0.58-0.67




AID


11243
PMF1
SSc vs
1.33E−04
2.51
0.61
0.52-0.7 
0.53
0.41-0.65
0.68
 0.6-0.75




HV


11243
PMF1
SSc vs
6.62E−05
2.51
0.62
0.53-0.7 
0.54
0.42-0.67
0.66
0.63-0.7 




AID


57099
AVEN
SSc vs
1.85E−04
2.09
0.62
0.57-0.66
0.55
0.48-0.62
0.64
 0.6-0.67




AID


57099
AVEN
SSc vs
4.48E−03
1.71
0.60
0.54-0.67
0.54
0.42-0.65
0.61
0.54-0.67




HV


1131
CHRM3
SSc vs
6.46E−03
1.41
0.58
0.51-0.64
0.51
 0.4-0.63
0.64
 0.6-0.68




AID


1131
CHRM3
SSc vs
1.64E−03
1.56
0.60
0.53-0.67
0.53
0.37-0.68
0.66
0.58-0.74




HV


4784
NFIX
SSc vs
1.47E−03
1.51
0.60
0.52-0.68
0.48
0.37-0.59
0.67
 0.6-0.74




HV


4784
NFIX
SSc vs
3.88E−02
1.30
0.55
0.46-0.64
0.44
0.28-0.59
0.64
0.61-0.67




AID


84196
USP48
SSc vs
4.11E−03
1.60
0.60
0.54-0.65
0.52
0.42-0.63
0.63
0.58-0.69




HV


84196
USP48
SSc vs
2.15E−01
1.21
0.53
0.46-0.6 
0.45
0.36-0.54
0.57
0.52-0.62




AID


11143
MYST2
SSc vs
4.21E−03
1.68
0.60
0.52-0.67
0.43
0.34-0.52
0.67
0.61-0.74




HV


11143
MYST2
SSc vs
2.75E−03
1.76
0.59
0.55-0.64
0.44
0.34-0.54
0.66
0.64-0.69




AID


5364
PLXNB1
SSc vs
6.60E−05
1.88
0.62
0.52-0.72
0.53
0.36-0.71
0.67
0.63-0.7 




AID


5364
PLXNB1
SSc vs
6.04E−03
1.67
0.59
0.53-0.66
0.52
0.45-0.6 
0.65
0.59-0.71




HV


10450
PPIE
SSc vs
1.96E−03
1.64
0.59
0.52-0.67
0.49
0.37-0.6 
0.69
0.66-0.72




HV


10450
PPIE
SSc vs
9.14E−02
1.33
0.56
0.48-0.64
0.45
0.35-0.55
0.63
0.59-0.68




AID


80152
CENPT
SSc vs
5.10E−03
1.60
0.59
0.53-0.64
0.48
0.34-0.62
0.67
0.63-0.72




AID


80152
CENPT
SSc vs
8.21E−03
1.57
0.59
0.51-0.67
0.49
0.35-0.63
0.65
0.61-0.69




HV


64689
GORASP1
SSc vs
5.03E−01
1.03
0.53
0.46-0.59
0.44
0.33-0.55
0.59
0.55-0.63




AID


64689
GORASP1
SSc vs
1.37E−02
1.55
0.58
0.52-0.65
0.47
0.37-0.57
0.64
0.59-0.69




HV


27257
LSM1
SSc vs
1.58E−04
1.58
0.61
0.56-0.66
0.59
 0.5-0.67
0.61
0.58-0.65




AID


27257
LSM1
SSc vs
1.46E−02
1.39
0.58
0.52-0.63
0.51
0.38-0.64
0.62
0.56-0.67




HV


153562
MARVELD2
SSc vs
1.82E−02
1.56
0.56
0.49-0.64
0.56
0.45-0.68
0.60
0.57-0.63




AID


153562
MARVELD2
SSc vs
1.39E−02
1.61
0.57
0.51-0.64
0.57
0.44-0.7 
0.62
0.56-0.67




HV


415116
PIM3
SSc vs
9.59E−02
1.53
0.56
0.52-0.6 
0.41
0.36-0.46
0.66
0.63-0.7 




AID


415116
PIM3
SSc vs
2.65E−02
1.68
0.57
 0.5-0.65
0.42
0.31-0.53
0.68
0.61-0.76




HV


23762
OSBP2
SSc vs
4.13E−03
1.52
0.59
0.51-0.67
0.49
0.39-0.6 
0.67
0.64-0.7 




AID


23762
OSBP2
SSc vs
5.45E−03
1.57
0.57
0.46-0.68
0.43
0.25-0.62
0.65
0.57-0.73




HV


26140
TTLL3
SSc vs
1.16E−02
1.50
0.57
0.46-0.68
0.48
0.32-0.64
0.64
0.58-0.71




HV


26140
TTLL3
SSc vs
1.14E−01
1.35
0.55
0.49-0.61
0.47
0.39-0.55
0.63
 0.6-0.66




AID


10014
HDAC5
SSc vs
1.36E−01
1.94
0.55
0.51-0.59
0.53
0.46-0.6 
0.50
0.46-0.55




AID


10014
HDAC5
SSc vs
4.32E−02
3.15
0.57
0.51-0.62
0.55
0.43-0.67
0.54
0.46-0.63




HV


7791
ZYX
SSc vs
1.75E−02
1.54
0.57
0.49-0.64
0.50
0.35-0.64
0.58
0.52-0.64




HV


7791
ZYX
SSc vs
2.79E−01
1.23
0.53
0.48-0.58
0.51
0.38-0.63
0.56
0.52-0.6 




AID


563
AZGP1
SSc vs
1.04E−02
1.55
0.57
0.51-0.63
0.46
0.37-0.55
0.62
0.58-0.65




AID


563
AZGP1
SSc vs
3.62E−02
1.72
0.57
0.48-0.65
0.45
0.29-0.6 
0.62
0.58-0.66




HV


63976
PRDM16
SSc vs
1.09E−01
1.35
0.54
0.42-0.65
0.47
0.27-0.68
0.60
0.56-0.63




AID


63976
PRDM16
SSc vs
4.52E−02
1.56
0.54
0.47-0.61
0.46
0.34-0.59
0.61
0.56-0.65




HV


80895
ILKAP
SSc vs
6.86E−04
1.53
0.60
0.52-0.69
0.52
0.43-0.61
0.69
0.66-0.73




AID


80895
ILKAP
SSc vs
1.52E−01
1.31
0.54
0.44-0.63
0.47
0.32-0.62
0.66
0.62-0.7 




HV


55049
C19orf60
SSc vs
6.48E−03
1.56
0.58
0.53-0.64
0.60
0.5-0.7
0.57
0.54-0.6 




AID


55049
C19orf60
SSc vs
3.59E−01
1.39
0.49
0.41-0.57
0.51
0.37-0.65
0.54
0.48-0.6 




HV


23299
BICD2
SSc vs
1.79E−03
1.45
0.59
0.53
0.66
0.53-0.66
0.44
0.37




HV


23299
BICD2
SSc vs
1.02E−02
1.28
0.57
0.49
0.65
0.49-0.65
0.43
0.34




AID


1059
CENPB
SSc vs
9.17E−08
1.37
0.69
0.62
0.75
0.62-0.75
0.46
0.34




HV


1059
CENPB
SSc vs
1.04E−08
1.35
0.67
0.6 
0.74
 0.6-0.74
0.46
0.36




AID


10290
SPEG
SSc vs
2.68E−04
1.31
0.61
0.55
0.68
0.55-0.68
0.47
0.36




HV


10290
SPEG
SSc vs
8.12E−05
1.42
0.62
0.53
0.72
0.53-0.72
0.51
0.35




AID


6749
SSRP1
SSc vs
6.26E−04
1.36
0.61
0.52
0.71
0.52-0.71
0.49
0.40




HV


6749
SSRP1
SSc vs
6.16E−04
1.31
0.60
0.55
0.65
0.55-0.65
0.48
0.40




AID


29968
PSAT1
SSc vs
1.83E−02
1.10
0.58
0.52
0.63
0.52-0.63
0.37
0.24




HV


29968
PSAT1
SSc vs
7.17E−02
1.06
0.57
0.47
0.67
0.47-0.67
0.39
0.23




AID


51368
TEX264
SSc vs
1.49E−02
1.42
0.57
0.51
0.64
0.51-0.64
0.42
0.33




HV


51368
TEX264
SSc vs
3.16E−01
1.18
0.54
0.47
0.60
0.47-0.6 
0.40
0.29




AID









In order to analyse the frequency of the newly identified antigens from Table 3 in comparison with known antigens, a threshold value of 3 standard deviations (SD) above the mean value of the healthy samples was defined.


Astonishingly, at least 6 additional antigens were identified of which the frequency under consideration of all SSc patients is greater than or equal to 10%. These are KDM6B, (21%), BICD2 (19%), RTEL1 (14%), NSUN5 (13%), SSRP1 (10%) and SPEG (10%). In addition, two further antigens with a frequency greater than or equal to 5% in SSc were found: VEGFB(9%) and PSAT1 (7%).



FIG. 4 shows the frequency of 8 new antigens in SSc patients compared to anti-centromere antibodies.


Example 7
Identification of Autoantibody Reactivities in Patients With Diffuse Subform

Only approximately 62.5% of the analysed patients with limited form have anti-Sc170 antibodies. A further 12.5% of patients showed anti-centromere antibodies. In order to identify further autoantibodies in patients with limited SSc, the serum samples of patients with diffuse SSc were compared with various control groups. These consisted of patients with limited SSc and patients with overlap syndrome. Autoantibodies which in the group of SSc patients with diffuse form have a p-value of less than 0.05 and a fold-change greater than 1.5 were selected. The result of the statistical tests is summarised in Table 2.


Group 2 comprises 72 additional antigens which are suitable for the identification of patients with diffuse SSc.


Group 2 antigen gene symbols: PSAT1, TEX264, ABCF3, ACAT2, TCEAL4, ACTN4, ACTR5, ALDH1A1, ALPK1, APBA2, ARHGEF16, ASMTL, ATP13A2, C11orf30, C11orf60, C17orf48, C19orf52, C20orf43, CDK5RAP2, CMPK1, CORO2B, COX5A, CTBP2, CYP4F2, DENND4B, DHRS4, DTNBP1, EEF1D, EIF2B3, EPS8L2, FEZ1, FOXL1, FUCA2, GAL3ST4, GEMIN8, GLOD4, GSN, HMGCS1, HSP90AA1, INPP5B, IRAK1, ISCU, LARS, LTF, MGEA5, MPND, MSH3, NCSTN, NEU1, P4HB, PERI, PEX14, PGCP, PPL, PRKAR1B, PTPN5, RAB11B, RAB11FIP4, RUNDC3A, STMN3, STMN4, STXBP3, SYCE1, TBCD, TMF1, TSFM, TXNRD1, UBE2Q1, UBE2Q2, UBE2Z, YTHDF1, ZNF217.



FIG. 5 shows the volcano plot of the autoantibody reactivities of SSc patients with diffuse subform compared to healthy controls.



FIG. 6 shows the frequency of the autoantibodies in the diffuse form compared to the limited form.


Patients with diffuse SSc more often have antibodies for the antigens PSAT1 (12.5%), VEGFB (12.5%), CMPK1 (9.4%), TEX264 (9.4%), WDR44 (9.4%), PPL (6.3%) and MYST2 (6.3%).


Table 4 summarises the results of the statistical tests for selected antigens of group 1 and 2. These antigens are suitable for identification and distinction of the limited and diffuse SSc subgroups.









TABLE 4







Summary of the p-values, AUC and fold-change reactivity


of the antigens in the limited and diffuse SSc subgroups.














Gene
Gene


Fold-





ID
Symbol
Test
p-value
change
AUC
Sensitivity
Specificity

















57099
AVEN
Diffuse vs
6.04E−01
−1.46
0.44
0.48
0.56




HV


57099
AVEN
Limited vs
1.74E−06
4.00
0.70
0.63
0.67




HV


23299
BICD2
Diffuse vs
7.98E−01
1.05
0.45
0.30
0.56




HV


23299
BICD2
Limited vs
2.53E−05
2.10
0.71
0.59
0.71




HV


1058
CENPA
Diffuse vs
3.21E−01
1.26
0.55
0.35
0.70




HV


1058
CENPA
Limited vs
9.49E−11
31.39
0.79
0.70
0.85




HV


1059
CENPB
Diffuse vs
8.87E−01
−1.05
0.50
0.36
0.63




HV


1059
CENPB
Limited vs
7.69E−12
28.22
0.82
0.72
0.91




HV


1060
CENPC1
Diffuse vs
2.96E−02
1.51
0.63
0.45
0.77




HV


1060
CENPC1
Limited vs
7.42E−16
12.12
0.84
0.63
0.90




HV


51727
CMPK1
Diffuse vs
1.14E−01
1.73
0.60
0.55
0.60




HV


51727
CMPK1
Limited vs
5.98E−02
−1.51
0.60
0.64
0.48




HV


23135
KDM6B
Diffuse vs
2.82E−03
2.06
0.65
0.63
0.67




HV


23135
KDM6B
Limited vs
1.82E−14
7.15
0.84
0.70
0.82




HV


11143
MYST2
Diffuse vs
3.44E−03
3.32
0.65
0.55
0.71




HV


11143
MYST2
Limited vs
1.95E−01
1.33
0.56
0.45
0.63




HV


4796
NFKBIL2
Diffuse vs
1.21E−01
1.47
0.57
0.39
0.69




HV


4796
NFKBIL2
Limited vs
9.90E−03
2.42
0.64
0.56
0.73




HV


55695
NSUN5
Diffuse vs
2.02E−01
1.05
0.58
0.42
0.75




HV


55695
NSUN5
Limited vs
4.07E−12
2.69
0.81
0.71
0.87




HV


55857
PLK1S1
Diffuse vs
2.01E−01
−1.39
0.55
0.61
0.55




HV


55857
PLK1S1
Limited vs
9.02E−03
1.65
0.60
0.49
0.61




HV


11243
PMF1
Diffuse vs
2.89E−02
2.45
0.64
0.60
0.67




HV


11243
PMF1
Limited vs
5.75E−04
3.29
0.64
0.55
0.69




HV


5493
PPL
Diffuse vs
1.53E−03
2.05
0.65
0.53
0.68




HV


5493
PPL
Limited vs
8.45E−02
1.30
0.58
0.50
0.64




HV


29968
PSAT1
Diffuse vs
2.46E−03
2.24
0.66
0.52
0.80




HV


29968
PSAT1
Limited vs
6.76E−01
1.01
0.52
0.33
0.75




HV


51750
RTEL1
Diffuse vs
3.30E−01
−1.35
0.45
0.49
0.48




HV


51750
RTEL1
Limited vs
5.56E−10
5.97
0.78
0.74
0.75




HV


10290
SPEG
Diffuse vs
2.46E−01
1.02
0.54
0.33
0.55




HV


10290
SPEG
Limited vs
7.89E−04
2.34
0.69
0.61
0.62




HV


6749
SSRP1
Diffuse vs
2.45E−01
−1.15
0.47
0.40
0.54




HV


6749
SSRP1
Limited vs
1.37E−05
2.11
0.71
0.62
0.73




HV


51368
TEX264
Diffuse vs
1.66E−02
2.02
0.63
0.52
0.70




HV


51368
TEX264
Limited vs
1.12E−01
1.31
0.57
0.36
0.64




HV


7423
VEGFB
Diffuse vs
1.77E−02
2.46
0.62
0.54
0.66




HV


7423
VEGFB
Limited vs
8.40E−03
2.15
0.61
0.56
0.64




HV


54521
WDR44
Diffuse vs
5.07E−02
2.37
0.64
0.57
0.61




HV


54521
WDR44
Limited vs
3.00E−01
−1.21
0.56
0.58
0.44




HV









Example 8
Identification of Autoantibody Reactivities in Patients With Limited Subform

Only approximately 60% of the analysed patients with limited form have anti-centromere antibodies. A further 18% of the patients showed anti-Sc170 antibodies. In order to identify further antibodies in patients with limited SSc, the serum samples of the patients with limited SSc were compared with different control groups. These consisted of patients with diffuse SSc and patients with overlap syndrome. Autoantibodies which in the group of SSc patients with limited form had a p-value of less than 0.05 and a fold-change of greater than 1.5 were selected. The result of the statistical tests is summarised in Table 2.



FIG. 7 shows the volcano plot of the autoantibody reactivities of patients with limited SSc compared to healthy test subjects.


Table 4 summarises the results of the statistical tests of the limited and diffuse SSc subgroups.


Group 3 comprises 69 additional antigens which are suitable for the identification of patients with limited SSc.


Group 3: antigen gene symbols:


BICD2, SPEG, ZFYVE19, AATF, ABI2, ACBD6, AIP, ANK1, ARHGDIA, AZIN1, C1orf131, C9orf16, CBX3, CCDC102A, CCNDBP1, CENPH, CORO7, DDX1, DTX4, DYNC1LI1, EIF4E, EML3, ENAH, EOMES, FAM50A, FCHSD1, GAB1, GCSH, GIPC1, GIT1, GPBP1, GTF2F1, HIST1H1A, IKBKB, ISY1, KDR, KIFAP3, MAPT, MED21, MOCOS, MRPL34, NSFL1C, PDIA6, PLK1S1, PLXNB2, RGS16, RNF4, RPL5, S100B, SET, SFPQ, SH3GL2, CENPB, SPIRE2, SPTAN1, SSB, SYF2, TAF9, TDRKH, TTC1, TTC28, TWF2, UBAP2, UNC119, WIZ, XBP1, YLPM1, ZCCHC17, ZCCHC9



FIG. 8 shows the frequency of the autoantibodies in the diffuse form compared to the limited form.


Besides anti-centromere and anti-Ro52 (TRIM21) antibodies, antibodies against the antigens KDM6B (38%), BICD2 (26%), RTEL1 (22%), NSUN5 (20%), SSRP1 (14%), AVEN (12%), PMF1 (10%), NFKBIL2 (10%), SPEG (10%) and PLK1S1 (10%) were found with a frequency of greater than or equal to 10% in patients with limited SSc.


Example 9
Identification of Autoantibody Reactivities in Patients With Overlap Syndrome

A common progressive form of SSc is what is known as overlap syndrome. In clinical practice, the delimitation of this form with respect to other collagenoses is often difficult.


Group 4 comprises 119 antigens which are suitable for the identification of patients with overlap syndrome:


Group 4 antigen gene symbols: ACOT7, ACTR1B, ADD1, AIFM1, AK1, AKAP1, AKT1, ANAPC4, ANKRD16, ANKS6, APC, ARHGDIB, ASB6, ATP5D, ATP5H, AVPI1, B3GNTL1, BCKDHA, BRPF3, C11orf1, C11orf84, C14orf105, C20orf20, C3orf1, CASA, CALB2, CAPG, CBLC, CC2D1A, CCDC137, CCDC40, CCDC43, CDC2L2, CEP76, CNDP2, CNTROB, COIL, CRYAB, DES, DHX29, DIP2C, DR1, EID1, ERLIN1, FAM104B, FAM60A, FASN, FCGR1A, FKBP15, FKBP8, FUBP3, FXC1, GSTZ1, H2AFV, HNRNPA1, HNRPLL, HSBP1L1, HSPA8, IRAK1BP1, KARS, KCNK5, LASS5, LIPE, LOC100129119, LOC643733, LSM14A, LSM14B, LSR, LUC7L2, MAOA, MAPK8IP2, MBD3, MRPL10, MRPL11, MSN, MXD3, MXI1, NFE2L2, NHSL1, NNAT, NRBP1, NUP35, ORC6L, PANK4, PBXIP1, PCBP4, PPP1R14A, PRDM8, PTN, RPLP0, RPS3, SCARB2, SDCCAG8, SDR39U1, SDS, SEC31A, SERPINA6, SH3KBP1, SMAD1, SNX22, SOX13, SRP68, TCEAL2, TCEB3, TCERG1, TCOF1, TIMM13, TRAK1, TRIM10, TRIM56, UBTD2, UGT1A8, UHRF1BP1L, USP47, VAT1, WDR47, ZMYND8, ZNF431, ZNF563.


Group 5 in Table 2 contains further statistically significant antigens which can be used for the diagnosis and differential diagnosis of SSc compared to healthy test subjects and other autoimmune diseases.


Group 5: antigen gene symbols: HIST1H2BA, NEFL, STMN1, STMN1, CDR2, PPP1R2, RBM28, SSRP1, C4orf27, CACNB3, CASP9, CHD1, DFNA5, FEN1, GTF2E2, MMP2, MRPL40, NAPA, PLA2G4B, PPP2CA, PVRL2, RECQLS, FAF1, WDR44.


Example 10
Application of Antigen Panels, Moreover for Improved Diagnosis of SSc

On account of the clinical and serological heterogeneity of the SSc disease, it is not possible to diagnose this disease using just one biomarker. According to Mierau et al. (2011), only approximately 35.9% of SSc patients have autoantibodies against centromere proteins and only 30.1% have autoantibodies against anti-topomerase I (anti-Sc170). There is thus also a great need for specific diagnostic and prognostic markers.


In order to develop an improved diagnostic antigen panel for SSc, antigens from Tables 3 and 4 were selected.


The narrower selection initially included five of the antigens represented most frequently in SSc: KDM6B, BICD2, RTEL1 and NSUNS) (FIG. 4).


In addition, the frequency of autoantibodies in diffuse SSc, which progresses particularly severely, was also taken into consideration. Here, two of the most frequent reactive antigens BICD2 (12.5) and PSAT1 (12.5) were selected.


In addition, antigens to which anti-Sc170-negative and anti-centromere-negative patients react were selected.



FIG. 9 shows the frequency of autoantibodies compared with a selection of antigens from Tables 3 and 4 in anti-centromere-negative and anti-Sc170-negative patients.


In particular, the antigens MARVELD2 (19%), MYST2 (19%), VEGFB (19%).PSAT1 (14%). NSUN5 (14%) and TEX264 (14%) have a frequency of more than 10% in anti-centromere- and anti-Sc170-negative SSc patients. These antigens are therefore particularly suitable for improving the diagnosis.


Four of the most frequently reactive antigens in doubly negative SSc patients (MYST2, PSAT1, NSUN5 and TEX264) were therefore selected for the development of an improved diagnostic test.


The final composition of the panel is illustrated in Table 5.









TABLE 5







Composition of the improved diagnostic panel.











Gene
Gene

Panel
Panel


ID
Symbol
Gene Name
I
II














1059
CENPB
centromere protein B, 80 kDa
x
x


7250
TOP1
topoisomerase (DNA) I
x
x


23135
KDM6B
lysine (K)-specific demethylase 6B

x


23299
BICD2
bicaudal D homolog 2 (Drosophila)

x


55695
NSUN5
NOL1/NOP2/Sun domain family,

x




member 5




51750
RTEL1
regulator of telomere elongation

x




helicase 1




11143
MYST2
MYST histone acetyltransferase 2

x


29968
PSAT1
phosphoserine aminotransferase 1

x









The first 7 antigens in Table 2 include the most important antigens used for the compilation of biomarker panels for the diagnosis of SSc: KDM6B, NSUN5, BICD2, RTEL1, MYST2, PSAT1 and TEX264


For validation of the antigens from panel I and panel II specified in table 5, 100 SSc patients and 100 healthy samples were measured using antigen-coupled Luminex beads.


The MFI values of the antigens TOP1, CENPB, KDM6B, NSUN5, BICD2, RTEL1, MYST2, PSAT1 and TEX264 were used to calculate the area under the curve (AUC), sensitivity, and specificity.



FIG. 10a shows the receiver operator curves (ROC) for a logistic regression model based on panel I consisting of anti-CENPB and anti-Sc170.



FIG. 10b shows the ROC curve for the improved panel consisting of anti-CENPB and anti-Sc170 and the five new antigens KDM6B, NSUN5, BICD2, RTEL1, MYST2, PSAT1 and TEX264.


It was possible to increase the sensitivity by 7% from 72% to 79% due to the inclusion of the 5 antigens KDM6B, NSUN5, BICD2, RTEL1, MYST2, PSAT1 and TEX264.


On the basis of the example, it is clear how the prediction quality of a biomarker model can be increased with inclusion of the additional markers so as to achieve a better classification of patients.


The inclusion of additional markers besides the known markers improves the prediction quality in the applied method significantly with approximately 7% ROC.









TABLE 6







AUC, sensitivity, and specificity of the SSc panel













SSc vs Healthy








Control
AUC
CI (AUC)
Sens.
CI (Sens.)
Spec.
CI (Spec)
















panel I
0.91
[0.862, 0.965]
0.72
[0.621, 0.823]
0.97
[0.935, 1]


panel II
0.94
[0.891, 0.98] 
0.79
 [0.71, 0.868]
0.94
 [0.88, 1]




















TABLE 7








Gene
RNA_nucleotide_SEQ



GeneID
Symbol
(pbplus & manuell)




















23135
KDM6B
NM_001080424.1



23299
BICD2
NM_001003800.1



55695
NSUN5
NM_001168347.2



51750
RTEL1
NM_016434.3



11143
MYST2
NM_001199155.1



29968
PSAT1
NM_021154.4



51368
TEX264
NM_001129884.2



6737
TRIM21
NM_003141.3



11194
ABCB8
NM_007188.4



57099
AVEN
NM_020371.2



7423
VEGFB
NM_001243733.1



55049
C19orf60
NM_001100418.1



1058
CENPA
NM_001042426.1



1060
CENPC1
NM_001812.2



80152
CENPT
NM_025082.3



1131
CHRM3
NM_000740.2



64689
GORASP1
NM_031899.3



2997
GYS1
NM_001161587.1



10014
HDAC5
NM_001015053.1



80895
ILKAP
NM_030768.2



27257
LSM1
NM_014462.2



153562
MARVELD2
NM_001038603.2



4784
NFIX
NM_002501.3



23762
OSBP2
NM_030758.3



415116
PIM3
NM_001001852.3



5364
PLXNB1
NM_001130082.2



11243
PMF1
NM_001199653.1



10450
PPIE
NM_001195007.1



63976
PRDM16
NM_022114.3



26140
TTLL3
NM_001025930.3



84196
USP48
NM_001032730.1



563
AZGP1
NM_001185.3



7791
ZYX
NM_001010972.1



55324
ABCF3
NM_018358.2



39
ACAT2
NM_005891.2



79921
TCEAL4
NM_001006935.1



81
ACTN4
NM_004924.4



79913
ACTR5
NM_024855.3



216
ALDH1A1
NM_000689.4



80216
ALPK1
NM_001102406.1



321
APBA2
NM_001130414.1



27237
ARHGEF16
NM_014448.3



8623
ASMTL
NM_001173473.1



23400
ATP13A2
NM_001141973.1



56946
C11orf30
NM_020193.3



56912
C11orf60
NM_001168618.1



56985
C17orf48
NM_020233.4



90580
C19orf52
NM_138358.2



51507
C20orf43
NM_016407.4



55755
CDK5RAP2
NM_001011649.2



51727
CMPK1
NM_001136140.1



10391
CORO2B
NM_001190456.1



9377
COX5A
NM_004255.3



1488
CTBP2
NM_001083914.1



8529
CYP4F2
NM_001082.4



9909
DENND4B
NM_014856.2



10901
DHRS4
NM_021004.3



84062
DTNBP1
NM_032122.4



1936
EEF1D
NM_001130053.2



8891
EIF2B3
NM_001166588.2



64787
EPS8L2
NM_022772.3



9638
FEZ1
NM_005103.4



2300
FOXL1
NM_005250.2



2519
FUCA2
NM_032020.4



79690
GAL3ST4
NM_024637.4



54960
GEMIN8
NM_001042479.1



51031
GLOD4
NM_016080.3



2934
GSN
NM_000177.4



3157
HMGCS1
NM_001098272.2



3320
HSP90AA1
NM_001017963.2



3633
INPP5B
NM_005540.2



3654
IRAK1
NM_001025242.1



23479
ISCU
NM_014301.3



51520
LARS
NM_020117.9



4057
LTF
NM_001199149.1



10724
MGEA5
NM_001142434.1



84954
MPND
NM_001159846.1



4437
MSH3
NM_002439.4



23385
NCSTN
NM_015331.2



4758
NEU1
NM_000434.3



5034
P4HB
NM_000918.3



5187
PER1
NM_002616.2



5195
PEX14
NM_004565.2



10404
PGCP
XM_006716498.1



5493
PPL
NM_002705.4



5575
PRKAR1B
NM_001164758.1



84867
PTPN5
NM_001039970.1



9230
RAB11B
NM_004218.3



84440
RAB11FIP4
NM_032932.3



10900
RUNDC3A
NM_001144825.1



50861
STMN3
NM_015894.3



81551
STMN4
NM_030795.3



6814
STXBP3
NM_007269.2



93426
SYCE1
NM_001143763.1



6904
TBCD
NM_005993.4



7110
TMF1
NM_007114.2



10102
TSFM
NM_001172695.1



7296
TXNRD1
NM_001093771.2



55585
UBE2Q1
NM_017582.6



92912
UBE2Q2
NM_001145335.1



65264
UBE2Z
NM_023079.4



54915
YTHDF1
NM_017798.3



7764
ZNF217
NM_006526.2



10290
SPEG
NM_001173476.1



84936
ZFYVE19
NM_001077268.1



26574
AATF
NM_012138.3



10152
ABI2
NM_005759.5



84320
ACBD6
NM_032360.3



9049
AIP
NM_003977.2



286
ANK1
NM_000037.3



396
ARHGDIA
NM_001185077.1



51582
AZIN1
NM_015878.4



128061
C1orf131
NM_152379.2



79095
C9orf16
NM_024112.3



11335
CBX3
NM_007276.4



92922
CCDC102A
NM_033212.3



23582
CCNDBP1
NM_012142.4



64946
CENPH
NM_022909.3



79585
CORO7
NM_001201472.1



1653
DDX1
NM_004939.2



23220
DTX4
NM_015177.1



51143
DYNC1LI1
NM_016141.3



1977
EIF4E
NM_001130678.1



256364
EML3
NM_153265.2



55740
ENAH
NM_001008493.1



8320
EOMES
NM_005442.3



9130
FAM50A
NM_004699.3



89848
FCHSD1
NM_033449.2



2549
GAB1
NM_002039.3



2653
GCSH
NM_004483.4



10755
GIPC1
NM_005716.3



28964
GIT1
NM_001085454.1



65056
GPBP1
NM_001127235.2



2962
GTF2F1
NM_002096.2



3024
HIST1H1A
NM_005325.3



3551
IKBKB
NM_001190720.2



57461
ISY1
NM_001199469.1



3791
KDR
NM_002253.2



22920
KIFAP3
NM_001204514.1



4137
MAPT
NM_001123066.3



9412
MED21
NM_004264.4



55034
MOCOS
NM_017947.2



64981
MRPL34
NM_023937.3



55968
NSFL1C
NM_001206736.1



10130
PDIA6
NM_005742.3



55857
PLK1S1
NM_001163022.1



23654
PLXNB2
NM_012401.3



6004
RGS16
NM_002928.3



6047
RNF4
NM_001185009.2



6125
RPL5
NM_000969.3



6285
S100B
NM_006272.2



6418
SET
NM_001122821.1



6421
SFPQ
NM_005066.2



6456
SH3GL2
NM_003026.2



1059
CENPB
NM_001810.5



84501
SPIRE2
NM_032451.1



6709
SPTAN1
NM_001130438.2



6741
SSB
NM_003142.4



25949
SYF2
NM_015484.4



6880
TAF9
NM_001015891.1



11022
TDRKH
NM_001083963.1



7265
TTC1
NM_003314.2



23331
TTC28
NM_001145418.1



11344
TWF2
NM_007284.3



55833
UBAP2
NM_018449.3



9094
UNC119
NM_005148.3



58525
WIZ
NM_021241.2



7494
XBP1
NM_001079539.1



56252
YLPM1
NM_019589.2



51538
ZCCHC17
NM_016505.3



84240
ZCCHC9
NM_001131035.1



255626
HIST1H2BA
NM_170610.2



11332
ACOT7
NM_007274.3



10120
ACTR1B
NM_005735.3



118
ADD1
NM_001119.4



9131
AIFM1
NM_001130846.2



203
AK1
NM_000476.2



8165
AKAP1
NM_001242902.1



207
AKT1
NM_001014431.1



29945
ANAPC4
NM_013367.2



54522
ANKRD16
NM_001009941.2



203286
ANKS6
NM_173551.3



324
APC
NM_000038.5



397
ARHGDIB
NM_001175.5



140459
ASB6
NM_001202403.1



513
ATP5D
NM_001001975.1



10476
ATP5H
NM_001003785.1



60370
AVPI1
NM_021732.2



146712
B3GNTL1
NM_001009905.1



593
BCKDHA
NM_000709.3



27154
BRPF3
NM_015695.2



64776
C11orf1
NM_022761.2



144097
C11orf84
NM_138471.1



55195
C14orf105
NM_018168.3



55257
C20orf20
NM_018270.4



51300
C3orf1
NM_016589.3



763
CA5A
NM_001739.1



794
CALB2
NM_001740.4



822
CAPG
NM_001256139.1



23624
CBLC
NM_001130852.1



54862
CC2D1A
NM_017721.4



339230
CCDC137
NM_199287.2



55036
CCDC40
NM_001243342.1



124808
CCDC43
NM_001099225.1



728642
CDC2L2
NM_024011.2



79959
CEP76
NM_024899.3



55748
CNDP2
NM_001168499.1



116840
CNTROB
NM_001037144.5



8161
COIL
NM_004645.2



1410
CRYAB
NM_001885.2



1674
DES
NM_001927.3



54505
DHX29
NM_019030.2



22982
DIP2C
NM_014974.2



1810
DR1
NM_001938.2



23741
EID1
NM_014335.2



10613
ERLIN1
NM_001100626.1



90736
FAM104B
NM_001166699.1



58516
FAM60A
NM_001135811.1



2194
FASN
NM_004104.4



2209
FCGR1A
NM_000566.3



23307
FKBP15
NM_015258.1



23770
FKBP8
NM_012181.3



8939
FUBP3
NM_003934.1



26515
FXC1
NM_012192.3



2954
GSTZ1
NM_001513.3



94239
H2AFV
NM_012412.4



3178
HNRNPA1
NM_002136.2



92906
HNRPLL
NM_001142650.1



440498
HSBP1L1
NM_001136180.1



3312
HSPA8
NM_006597.5



134728
IRAK1BP1
NM_001010844.3



3735
KARS
NM_001130089.1



8645
KCNK5
NM_003740.3



91012
LASS5
NM_147190.3



3991
LIPE
NM_005357.3



100129119
LOC100129119




643733
LOC643733




26065
LSM14A
NM_001114093.1



149986
LSM14B
NM_144703.2



51599
LSR
NM_015925.6



51631
LUC7L2
NM_001244584.2



4128
MAOA
NM_000240.3



23542
MAPK8IP2
NM_012324.4



53615
MBD3
NM_003926.5



124995
MRPL10
NM_145255.3



65003
MRPL11
NM_016050.3



4478
MSN
NM_002444.2



83463
MXD3
NM_001142935.1



4601
MXI1
NM_001008541.1



4780
NFE2L2
NM_001145412.2



57224
NHSL1
NM_001144060.1



4826
NNAT
NM_005386.2



29959
NRBP1
NM_013392.2



129401
NUP35
NM_138285.4



23594
ORC6L
NM_014321.3



55229
PANK4
NM_018216.1



57326
PBXIP1
NM_020524.2



57060
PCBP4
NM_001174100.1



94274
PPP1R14A
NM_001243947.1



56978
PRDM8
NM_001099403.1



5764
PTN
NM_002825.5



6175
RPLP0
NM_001002.3



6188
RPS3
NM_001005.4



950
SCARB2
NM_001204255.1



10806
SDCCAG8
NM_006642.3



56948
SDR39U1
NM_020195.2



10993
SDS
NM_006843.2



22872
SEC31A
NM_001077206.2



866
SERPINA6
NM_001756.3



30011
SH3KBP1
NM_001024666.2



4086
SMAD1
NM_001003688.1



79856
SNX22
NM_024798.2



9580
SOX13
NM_005686.2



6730
SRP68
NM_014230.3



140597
TCEAL2
NM_080390.3



6924
TCEB3
NM_003198.2



10915
TCERG1
NM_001040006.1



6949
TCOF1
NM_000356.3



26517
TIMM13
NM_012458.3



22906
TRAK1
NM_001042646.2



10107
TRIM10
NM_006778.3



81844
TRIM56
NM_030961.1



92181
UBTD2
NM_152277.2



54576
UGT1A8
NM_019076.4



23074
UHRF1BP1L
NM_001006947.1



55031
USP47
NM_017944.3



10493
VAT1
NM_006373.3



22911
WDR47
NM_001142550.1



23613
ZMYND8
NM_012408.5



170959
ZNF431
NM_133473.2



147837
ZNF563
NM_145276.2



4747
NEFL
NM_006158.4



3925
STMN1
NM_001145454.1



1039
CDR2
NM_001802.1



5504
PPP1R2
NM_006241.6



55131
RBM28
NM_001166135.1



6749
SSRP1
NM_003146.2



54969
C4orf27
NM_017867.2



784
CACNB3
NM_000725.3



842
CASP9
NM_001229.4



1105
CHD1
NM_001270.2



1687
DFNA5
NM_001127453.1



2237
FEN1
NM_004111.5



2961
GTF2E2
NM_002095.4



4313
MMP2
NM_001127891.1



64976
MRPL40
NM_003776.2



8775
NAPA
NM_003827.3



100137049
PLA2G4B
NM_001114633.1



5515
PPP2CA
NM_002715.2



5819
PVRL2
NM_001042724.1



9400
RECQL5
NM_001003715.3



11124
FAF1
NM_007051.2



54521
WDR44
NM_001184965.1










Example 11
Validation of SSc-Associated Autoantibodies in an Independent Sample Collective

The markers specified in table 2 were tested in a second independent sample collective (SSc cohort II). In total, 180 serum samples from SSc patients were analysed, of which the demographic and clinical data were taken from the EUSTAR database. EISTAR is a multi-centre, prospective cohort of the European League Against Rheumatism (EULAR) Scleroderma Trials and Research (EUSTAR) group. As control groups, n=99 serum samples from healthy controls and n=110 serum samples from patients with rheumatic autoimmune diseases (ADs) were used.


These were composed of serum samples from patients with a diagnosis of SLE, myositis, arthritis and Sjögren's syndrome.









TABLE 6







Demographic, clinical and serological data of the SSc


cohort II.










Total SSc



Number (%); mean value
SSc
Main participation










(%)
(n = 180)
dSSc(n = 57)
lSSc (n = 83)





Female n (%)
142 (79.9)
 42 (737) 
  67 (80.7)


Male n (%)
 38 (21.1)
 15 (26.3)
  16 (19.3)


Age mean value (SD)
56.5
52.9 (12.2) 
58.2 (15.1)



(13.8)




Average duration of the
8.2 (9.7) 
6.98 (6.8)  
9.9 (11.9)


disease in years (SD)





ANA positive n (%)
176 (97.8)
 55 (96.5)
  82 (98.8)


anti-CENPB positive n
 66 (36.7)
 5 (8.8)
34 (41)


(%)





anti-Sc170 positive n
 50 (27.8)
 21 (36.8)
  21 (25.3)


(%)












For this purpose, the human proteins specified in Table 2 were coupled to Luminex beads and the protein-coupled beads were measured in a multiplex assay with the patient samples. The binding of autoantibodies was measured by means of a PE-conjugated autoantibody in a Luminex instrument.


A univariate statistical evaluation was carried out using the Wilcoxon rank sum test. The predefined significance level was set at 0.05. Table 7 contains 41 antigens, which, both in SSc cohort I, which was used for discovery of the markers (Example 6), and in SSc cohort II, achieved a p-value less than the set significance level of 0.05. For the comparison of all SSc samples against healthy controls (HC), 31 markers achieved a p-value of less than 0.05. For the comparison of all SSc samples against a combined group of serum samples of various rheumatoid diseases (ADs), 24 markers achieved a p-value of less than 0.05.









TABLE 7







Summary of the p-values (Wilcoxon rank sum test) for


41 markers for the diagnosis of SSc in SSc cohort II










SSc vs HC

















Scl70 &





Marker


CENPB


SSc vs AD


Nr
Gene Symbol
SSc
neg
dSSc
lSSc
SSc
















1
KDM6B
3.09E−10
1.33E−03
6.13E−05
2.02E−08
2.25E−02


2
BICD2
4.19E−03
6.48E−01
7.77E−01
5.11E−04
7.37E−01


3
NSUN5
1.62E−05
4.06E−01
9.41E−01
4.30E−06
5.04E−03


4
RTEL1
1.28E−03
3.69E−01
4.16E−01
4.32E−04
7.74E−02


8
TRIM21
5.30E−09
1.51E−05
1.65E−06
5.90E−07
3.88E−01


9
ABCB8
1.81E−03
8.10E−01
3.37E−01
1.13E−02
1.02E−02


10
AVEN
2.06E−03
7.33E−01
4.37E−01
1.83E−03
7.88E−02


13
CENPA
2.31E−04
3.02E−01
3.03E−01
8.03E−05
1.92E−03


14
CENPC
4.17E−11
5.64E−03
2.25E−02
5.14E−10
5.01E−07


15
CENPT
7.50E−02
4.61E−01
8.25E−01
1.05E−02
1.98E−02


18
GYS1
1.99E−02
2.91E−02
3.40E−01
2.07E−02
8.24E−01


22
MARVELD2
3.77E−02
1.84E−01
1.26E−01
1.71E−01
1.78E−02


27
PMF1
4.96E−02
9.77E−01
3.39E−01
3.28E−01
3.60E−02


30
TTLL3
2.01E−02
1.30E−01
9.82E−01
2.04E−02
9.67E−01


40
ALPK1
1.07E−02
1.90E−03
5.15E−02
5.65E−02
7.13E−01


44
ATP13A2
1.83E−02
7.52E−02
6.30E−01
1.61E−02
3.62E−01


48
C19orf52
8.67E−03
1.70E−01
7.77E−01
3.51E−02
5.48E−03


75
LTF
7.97E−03
4.52E−01
7.16E−01
3.10E−03
9.21E−01


92
STMN4
5.50E−05
6.47E−04
3.64E−03
7.59E−04
3.06E−02


108
ACBD6
4.17E−03
3.71E−01
2.99E−01
6.41E−03
4.02E−02


115
CBX3
2.66E−03
5.41E−01
2.33E−01
3.48E−02
4.45E−03


118
CENPH
2.27E−01
1.78E−01
5.44E−01
4.22E−02
2.19E−02


123
EIF4E
2.78E−02
9.74E−01
6.72E−01
1.52E−02
2.54E−04


134
GTF2F1
1.07E−04
4.08E−02
3.28E−02
6.88E−05
2.30E−01


137
ISY1
2.19E−02
2.06E−02
4.30E−02
1.35E−01
3.65E−01


138
KDR
3.68E−02
1.77E−01
4.65E−02
4.22E−01
3.39E−04


140
MAPT
2.50E−04
5.34E−01
2.76E−01
2.63E−05
4.82E−01


155
CENPB
4.27E−12
7.99E−01
8.41E−03
6.90E−11
2.91E−09


158
SSB
9.04E−02
1.56E−01
6.06E−01
3.07E−02
2.61E−01


213
DIP2C
2.44E−02
5.27E−02
5.08E−01
8.26E−03
1.87E−01


224
TIMM10B
4.05E−02
5.16E−03
3.86E−02
2.42E−01
3.51E−01


227
HNRNPA1
1.48E−02
2.54E−02
1.67E−03
1.28E−01
7.77E−01


229
HSBP1L1
2.45E−02
1.03E−01
1.91E−02
2.88E−01
1.05E−01


232
KARS
1.25E−02
5.71E−03
2.85E−02
1.12E−01
8.70E−03


257
PBXIP1
6.43E−06
2.08E−01
2.49E−01
8.61E−05
3.83E−01


290
ZNF431
3.94E−02
3.68E−02
1.59E−01
9.45E−02
4.67E−02


292
NEFL
6.97E−03
6.01E−02
9.19E−02
3.95E−02
8.50E−01


293
STMN1
6.11E−05
6.13E−04
3.69E−03
8.75E−04
4.19E−03


295
PPP1R2
1.19E−02
7.79E−01
3.69E−01
6.39E−02
1.98E−01


297
SSRP1
4.79E−02
7.17E−01
7.91E−01
2.02E−02
4.19E−03


314
TOP1
6.19E−07
4.23E−01
6.94E−05
4.10E−05
4.96E−07









Example 12
Application of Autoantibody Panels for the Diagnosis of SSc

From the markers contained in Table 2 and Table 7, various marker combinations were tested by means of logistic regression models. Here, the specificity compared to the control group was set to at least 95% as a requirement. An overview of the antigens used in panels 1 and 3-8 is contained in Table 8. In addition, a diagnostic panel 9 was compiled with use of all markers from Table 2. The panels 1, 3, 4, 5 and 9 are preferably suitable for the diagnosis of all SSc patients, regardless of the particular subtype. The AUC (area under the curve) of panels 1, 3, 4, 6 and 9 is specified in Table 8 for 2 independent SSc sample collectives (cohort I and cohort II).


Panel 1 consists of the antigens Sc170(Topl) and CENPB used conventionally for diagnosis and achieves an AUC of 0.81 in cohort I and 0.85 in cohort II for the comparison SSc versus healthy test subject (HC).


Panel 3 consists of two diagnostic antigens CEPNB and SC170, and two new SSc antigens KDM6B and BICD2. Compared to the usually used markers of panel 1, a logistic model for panel 3 shows a much higher AUC for the comparison SSc versus healthy test subject (HC): 0.88 for cohort I compared to 0.81, and 0.87 for cohort II compared to 0.85.


Panel 4 is based on panel 3 and contains two further new markers NSUNS and PPP1R2. For the diagnosis of SSc compared to healthy test samples, a logistic regression model for panel 4 achieves an AUC of 0.9 for cohort I and an AUC of 0.85 for cohort II.


Panel 5 is based on panel 4 and, in addition to the diagnostic markers CENPB and Sc170, also contains the markersKDM6B, BICD2, NSUNS, PPP1R2, RTEL1, TRIM21, ABCB8, AVEN, CENPA,CENPC1, GYS1, MARVELD2, PMF1, TTLL3, ATP13A2, LTF, STMN4, ACBD6, GTF2F1, KDR, DIP2C, FXC1, HNRNPA1, HSBP1L1, KARS, PBXIP1, ZNF431, STMN1 and SSRP1.









TABLE 8







Composition of the marker panels










CENPB &
















Scl70





Gene
SSc diagnosis
neg.
dSSc
lSSc















#
Symbol
P1
P3
P4
P5
P6
P7
P8


















155
CENPB
x
x
x
x


x


314
TOP1
x
x
x
x

x
x


1
KDM6B

x
x
x
x
x
x


2
BICD2

x
x
x


x


3
NSUN5


x
x


x


4
RTEL1



x


x


8
TRIM21



x
x
x
x


9
ABCB8



x


x


10
AVEN



x


x


13
CENPA



x


x


14
CENPC1



x

x
x


15
CENPT






x


18
GYS1



x
x

x


22
MARVELD2



x


27
PMF1



x


30
TTLL3



x


40
ALPK1




x


44
ATP13A2



x


48
C19orf52






x


75
LTF



x


92
STMN4



x
x

x


108
ACBD6



x


x


115
CBX3






x


118
CENPH






x


123
EIF4E






x


134
GTF2F1



x


x


137
ISY1





x


138
KDR



x


140
MAPT






x


158
SSB






x


213
DIP2C



x


x


224
FXC1



x


227
HNRNPA1



x
x
X


229
HSBP1L1



x


232
KARS



x


257
PBXIP1



x


x


290
ZNF431



x


292
NEFL






x


293
STMN1



x
x

x


295
PPP1R2


x
x


297
SSRP1



x


x









Example 13
Application of Autoantibody Panels for Identification of Patients With Absent Detection of Anti-Centromere and Anti-Sc170 (Top1) Autoantibodies

As presented in Table 6, only approximately 41% of the SSc patients from the SSc cohort II tested positively for anti-CENPB antibodies, and 25.3% tested positively for anti-Sc170 antibodies. Since very few patients with doubly positive reactivity have been described in the literature, the proportion of anti-CENPB- and anti-Sc170-negative patients was specified at approximately 30%. In order to close these diagnostic gaps, a logistic regression model was created for panel 6, which consists of 7 markers.


Panel 6 contains the markers KDM6B, TRIM21, GYS1, ALPK1, STMN4, HNRNPA1 and STMN1.


As summarised in Table 6, an AUC of 0.91 was achieved in cohort I, and an AUC of 0.84 was achieved for cohort II with the markers of panel 6.


Example 14
Application of Autoantibody Panels for Identification of SSc Patients With Diffuse Form

As presented in table 6, 36.8% of the SSc patients with diffuse SSc (dSSc) and 25.3% of the patients with limited form were positively tested for autoantibodies against Sc170 (Top1). This shows that anti-Sc170 antibodies are indeed associated with the diffuse form, but are not specific. Additional markers are therefore required for diagnosis of the diffuse form. Panel 7 comprises 6 markers which are particularly suitable for the diagnosis of diffuse SSc.


Panel 7 contains the markers KDM6B, TOP1, TRIM21, CENPC1, ISY1 and HNRNPA1.


For panel 7 an AUC of 0.81 for cohort I and 0.87 for cohort II were calculated by means of a logistic regression.


Example 15
Application of Autoantibody Panels for Identification of SSc Patients With Limited Form

As presented in Table 6, 41% of SSc patients with limited SSc (1SSc) and 8.8% of patients with diffuse form tested positively for autoantibodies against CENPB. This shows that anti-CENPB antibodies are indeed associated with the limited form, but are not specific. Additional markers are therefore required for diagnosis of the limited form. Panel 8 comprises 27 markers which are particularly suitable for the diagnosis of limited SSc.


Panel 8 comprises the markers KDM6B, BICD2, NSUNS, CENPB, TOP1, RTEL1, TRIM21, ABCB8, AVEN, CENPA, CENPC1, CENPT, GYS1, C19orf52, STMN4, ACBD6, CBX3, CENPH, EIF4E, GTF2F1, MAPT, SPTAN1, DIP2C, PBXIP1, NEFL, STMN1 and SSRP1.


For panel 8, an AUC of 0.97 for cohort I and 0.99 for cohort II were calculated by means of a logistic regression.









TABLE 9







AUC of the SSc panels in SSc cohort I and cohort II










Panel
SSc Cohort
Comparison
AUC













Panel 1
Cohort I
SSc vs HC
0.81


Panel 1
Cohort I
SSc vs SLE
0.84


Panel 3
Cohort I
SSc vs HC
0.88


Panel 3
Cohort I
SSc vs SLE
0.84


Panel 4
Cohort I
SSc vs HC
0.90


Panel 4
Cohort I
SSc vs SLE
0.84


Panel 5
Cohort I
SSc vs HC
0.93


Panel 6
Cohort I
SSc CENPB & Sc170 neg vs HC
0.91


Panel 7
Cohort I
dSSc vs HC
0.81


Panel 8
Cohort I
lSSc vs HC
0.97


Panel 9
Cohort I
SSc vs HC
0.99


Panel 1
Cohort II
SSc vs HC
0.85


Panel 1
Cohort II
SSc vs AI
0.84


Panel 3
Cohort II
SSc vs HC
0.87


Panel 3
Cohort II
SSc vs AI
0.85


Panel 4
Cohort II
SSc vs HC
0.88


Panel 4
Cohort II
SSc vs AI
0.85


Panel 5
Cohort II
SSc vs HC
0.96


Panel 6
Cohort II
SSc CENPB & Sc170 neg vs HC
0.84


Panel 7
Cohort II
dSSc vs HC
0.87


Panel 8
Cohort II
lSSc vs HC
0.99


Panel 9
Cohort II
SSc vs HC
0.99









Example 16
ELISA for the Determination of Anti-KDM6B Antibodies in Systemic Sclerosis

In accordance with the invention, recombinantly produced and improved KDM6B protein (Seq ID 315) comprising amino acids 42-421 of the Uniprot Database Entry 015054 was used. KDM6B is purified over a number of stages by means of nickel chelate affinity chromatography, size exclusion chromatography, and ion exchanger chromatography. The purified KDM6B was then applied in a concentration of 1 μg per millilitre in an Na carbonate buffer pH 9.0 to a flat-bottom ELISA plate (for example NUNC) with 100 μl per cavity, and was incubated for 4h at room temperature (RT).


After incubation, the excess buffer was removed and the free binding points of the ELISA plate were blocked using an inert protein (cold water fish gelatin) in PBS for lh at room temperature.


Serum or plasma samples were diluted 1:101 in HBS-T buffer, applied to the cavities and incubated for 30 min at room temperature. During this time, the KD6MB specific IgG autoantibodies from the serum or plasma sample bind to the bound protein.


Non-specifically-bound antibodies are removed after the incubation by washing twice with a PBS Tween buffer. Incubation is then performed for half an hour with an HRP (horseradish-peroxidase-conjugated) anti-human IgG detection antibody. After the incubation, non-specific binding partners are again removed by washing twice with PBS tween buffer.


The colorimetric detection reaction is performed by addition of a TMB (tetramethylbenzidine) substrate. This reaction is stopped after 15 minutes by addition of a 1M sulphuric acid and is evaluated in an ELISA measuring device (TECAN) at a wavelength of 450 nm vs 620 nm. The colour intensity (optical density, OD) of the detection reaction is directly proportional to the concentration of the KDM6B-specific IgG autoantibodies in the serum or plasma sample.


The test is evaluated semi-quantitatively via one-point calibration.


The OD values of the anti-KDM6B ELISA were used for the calculation of the p-values by means of Wilcoxon rank sum test and the calculation of a logistic regression model with ROC analysis for the comparison of SSc against HC. Since the group of SSc patients is greater than that of the control group HC, a random under-sampling is carried out for the logistic regression, such that the SSc cohort II has groups of identical size. The ROC analysis was calculated by using 75% of this reduced data set of SSc cohort II for training and 25% for testing the model. This approach is repeated 100 times.


Table 10 shows the p-values for the comparison of SSc versus healthy controls and SSc versus autoimmune controls calculated from samples of SSc cohort II.


Table 11 shows the empirically calculated area under the curve (AUC), sensitivity, and specificity of the anti-KDM6B ELISA for the diagnosis of SSc (SSc cohort II) compared to healthy samples.



FIG. 12 shows ROC curve for a logistic regression model on the basis of the ELISA OD values of KDM6B for the diagnosis of SSc compared to healthy controls.


Example 17
ELISA for the Determination of Anti-BICD2 Antibodies in Systemic sclerosis

In accordance with the invention, recombinantly produced BICD2 protein was purified over a number of stages by means of nickel chelate affinity chromatography, size exclusion chromatography, and ion exchanger chromatography. The purified BICD2 was then applied in a concentration of 1.7 μg per millilitre in an Na carbonate buffer pH 9.0 to a flat-bottom ELISA plate (for example NUNC) with 100 μl per cavity, and was incubated for 4 h at room temperature (RT).


After incubation, the excess buffer was removed and the free binding points of the ELISA plate were blocked using an inert protein (cold water fish gelatin) in PBS for 1 h at room temperature.


Serum or plasma samples were diluted 1:101 in HBS-T buffer, applied to the cavities and incubated for 30 min at room temperature. During this time, the BICD2-specific IgG autoantibodies from the serum or plasma sample bind to the bound protein.


Non-specifically-bound antibodies are removed after the incubation by washing twice with a PBS Tween buffer. Incubation is then performed for half an hour with an HRP (horseradish-peroxidase-conjugated) anti-human IgG detection antibody. After the incubation, non-specific binding partners are again removed by washing twice with PBS tween buffer.


The colorimetric detection reaction is performed by addition of a TMB (tetramethylbenzidine) substrate. This reaction is stopped after 15 minutes by addition of a 1M sulphuric acid and is evaluated in an ELISA measuring device (TECAN) at a wavelength of 450 nm vs 620 nm. The colour intensity of the detection reaction is directly proportional to the concentration of the BICD2-specific IgG autoantibodies in the serum or plasma sample.


The OD values of the BICD2 antigen were used for the calculation of the p-values by means of Wilcoxon rank sum test and the calculation of the receiver operator curves (ROC).


The OD values of the anti-BICD2 ELISA were used for the calculation of the p-values by means of Wilcoxon rank sum test and the calculation of a logistic regression model with ROC analysis for the comparison of SSc against HC. Since the group of SSc patients is greater than that of the control group HC, a random under-sampling is carried out for the logistic regression, such that the SSc cohort II has groups of identical size. The ROC analysis was calculated by using 75% of this reduced data set of SSc cohort II for training and 25% for testing the model. This approach is repeated 100 times.


Table 10 shows the p-values for the comparison of SSc versus healthy controls (HC) and SSc versus autoimmune controls (AD) calculated from samples of SSc cohort II.









TABLE 10







Wilcoxon rank sum test (p-value) for anti-KDM6B and


anti-BICD2 ELISA for the diagnosis of SSc compared to healthy


controls.











Comparison
KDM6B
BICD2







SSc vs HC
1.05E−04
1.13E−04











FIG. 11 shows the boxplot of the BICD2 ELISA for SSc samples compared to healthy samples.


Table 11 shows the empirically calculated sensitivity and specificity of the anti-KDM6B and anti-BICD2 ELISA for SSc cohort II for the diagnosis of SSc compared to healthy controls

















ELISA
Test
Value









anti-KDM6B
AUC
0.63




Sensitivity
0.19




Specificity
0.90



anti-BICD2
AUC
0.64




Sensitivity
0.19




Specificity
0.95











FIG. 12 shows ROC curve with confidence bands for a logistic regression model based on the ELISA OD values of BICD2 for the diagnosis of SSc compared to healthy controls.


LITERATURE



  • Mehra S, Walker J, Patterson K, Fritzler M J (2013). Autoantibodies in systemic sclerosis. Autoimmun Rev. 12(3):340-54.

  • Mierau R, Moinzadeh P, Riemekasten G, Melchers I, Meurer M, Reichenberger F, Buslau M, Worm M, Blank N, Hein R, Müller-Ladner U, Kuhn A, Sunderkötter C, Juche A, Pfeiffer C, Fiehn C, Sticherling M, Lehmann P, Stadler R, Schulze-Lohoff E,Seitz C, Foeldvari I, Krieg T, Genth E, Hunzelmann N (2011). Frequency of disease-associated and other nuclear autoantibodies in patients of the German Network for Systemic Scleroderma: correlation with characteristic clinical features. Arthritis Res Ther. 13(5):R172

  • LeRoy E C, Black C, Fleischmajer R, Jablonska S, Krieg T, Medsger T A Jr, Rowell N, Wollheim F (1988). Scleroderma (systemic sclerosis): classification, subsets and pathogenesis. J Rheumatol. 15(2):202-5.

  • Watts R., (2006). Autoantibodies in the autoimmune rheumatic diseases, Medicine, 34 (11): 441-444


Claims
  • 1-18. (canceled)
  • 19. A method for identifying markers for systemic sclerosis (SSc), said method comprising the following steps: a) bringing serum samples of at least 50, preferably 100 SSc patients into contact with more than 5000 antigens coupled to fluorescence-labelled beads, measuring the binding of the individual antigens to proteins in the serum samples of the SSc patients by immunofluorescence assay, and determining the median fluorescence intensity (MFI) for each individual antigen;b) bringing serum samples of at least 50, preferably 100 patients with lupus erythematodes (SLE) into contact with the same antigens coupled to fluorescence-labelled beads, measuring the binding of the individual antigens to proteins in the serum samples of the SLE patients by means of immunofluorescence assay, and determining from this the median fluorescence intensity (MFI) for each individual antigen;c) bringing serum samples of at least 50, preferably 537 patients with early rheumatoid arthritis (RA) into contact with the same antigens coupled to fluorescence-labelled beads, measuring the binding of the individual antigens to proteins in the serum samples of the RA patients by means of immunofluorescence assay, and determining from this the median fluorescence intensity (MFI) for each individual antigen;d) bringing serum samples of at least 50, preferably 82 patients with ankylosing spondylitis (SPA) into contact with the same antigens coupled to fluorescence-labelled beads, measuring the binding of the individual antigens to proteins in the serum samples of the SPA patients by means of immunofluorescence assay, and determining from this the median fluorescence intensity (MFI) for each individual antigen;e) bringing serum samples of at least 50, preferably 343 healthy individuals into contact with the same antigens coupled to fluorescence-labelled beads, measuring the binding of the individual antigens to proteins in the serum samples of the healthy individuals by means of immunofluorescence assay, and determining from this the median fluorescence intensity (MFI) for each individual antigen; andf) statistically evaluating the MFI data of each individual antigen from a), b), c), d) and e) by means of univariate analysis and thus identifying markers with which SSc patients can be differentiated from patients with SLE, patients with early RA, patients with SPA, and from healthy individuals;wherein the markers are selected from the sequences of SEQ ID NO: 1 to 955, homologues of SEQ ID NO: 1 to 955 with at least 95% homology, subsequences of SEQ ID NO: 1 to 955, subsequences of homologues of SEQ ID NO: 1 to 955 with at least 95% homology, and sequences coded by SEQ ID NO: 1 to 319.
  • 20. The method according to claim 19, wherein the markers after univariate statistical analysis have a threshold value of p less than 0.05 and a reactivity in the SSc group modified 1.5 times with respect to the control group, and wherein the control group comprises the patients with SLE and/or patients with early RA and/or patients with SPA and/or healthy individuals.
  • 21. Markers for SSc or SSc subgroups obtained by the method according to claim 19, wherein the SSc subgroups comprise diffuse SSc (dSSc), limited SSc (1SSc) and SSc overlap syndrome (SSc-OS).
  • 22. Markers for SSc or SSc subgroups selected from the sequences of SEQ ID NO: 1 to 955, homologues of SEQ ID NO: 1 to 955 with at least 95% homology, subsequences of SEQ ID NO: 1 to 955, subsequences of homologues of SEQ ID NO: 1 to 955 with at least 95% homology, and sequences coded by SEQ ID NO: 1 to 319, wherein the SSc subgroups comprise diffuse SSc (dSSc), limited SSc (1SSc) and SSc overlap syndrome (SSc-OS).
  • 23. Markers for SSc according to claim 21 selected from the sequences of SEQ ID NO: 1, 3-5, 8-33, 320, 322-324, 327-352, 639, 641-643 and 646-671, homologues of SEQ ID NO: 1, 3-5, 8-33, 320, 322-324, 327-352, 639, 641-643 and 646-671 with at least 95% homology, subsequences of SEQ ID NO: 1, 3-5, 8-33, 320, 322-324, 327-352, 639, 641-643 and 646-671, subsequences of homologues of SEQ ID NO: 1, 3-5, 8-33, 320, 322-324, 327-352, 639, 641-643 and 646-671 with at least 95% homology, and sequences coded by SEQ ID NO: 1, 3-5 and 8-33.
  • 24. Markers for dSSc according to claim 21 selected from the sequences of SEQ ID NO: 6, 7, 34-103, 325, 326, 353-422, 644, 645 and 672-741, homologues of SEQ ID NO: 6, 7, 34-103, 325, 326, 353-422, 644, 645 and 672-741 with at least 95% homology, subsequences of SEQ ID NO: 6, 7, 34-103, 325, 326, 353-422, 644, 645 and 672-741, subsequences of homologues of SEQ ID NO: 6, 7, 34-103, 325, 326, 353-422, 644, 645 and 672-741 with at least 95% homology, and sequences coded by SEQ ID NO: 6, 7 and 34-103.
  • 25. Markers for 1SSc according to claim 21 selected from the sequences of SEQ ID NO: 2, 104-171, 321, 423-490, 640 and 742-809, homologues of SEQ ID NO: 2, 104-171, 321, 423-490, 640 and 742-809 with at least 95% homology, subsequences of SEQ ID NO: 2, 104-171, 321, 423-490, 640 and 742-809, subsequences of homologues of SEQ ID NO: 2, 104-171, 321, 423-490, 640 and 742-809 with at least 95% homology, and sequences coded by SEQ ID No. 2 and 104-171.
  • 26. Markers for SSc-OS according to claim 21 selected from the sequences of SEQ ID NO: 173-291, 492-610 and 811-929, homologues of SEQ ID NO: 173-291, 492-610 and 811-929 with at least 95% homology, subsequences of SEQ ID NO: 173-291, 492-610 and 811-929, subsequences of homologues of SEQ ID NO: 173-291, 492-610 and 811-929 with at least 95% homology, and sequences coded by SEQ ID No. 173-291.
  • 27. A panel of markers for SSc or SSc subgroups comprising at least two or three different markers selected independently of one another from the sequences of SEQ ID NO: 1 to 955, homologues of SEQ ID NO: 1 to 955 with at least 95% homology, subsequences of SEQ ID NO: 1 to 955, subsequences of homologues of SEQ ID NO: 1 to 955 with at least 95% homology, and sequences coded by SEQ ID NO: 1 to 319, wherein the SSc subgroups comprise diffuse SSc (dSSc), limited SSc (1SSc) and SSc overlap syndrome (SSc-OS).
  • 28. The panel of markers for SSc or SSc subgroups according to claim 27, selected from the group containing, besides CENPB (SEQ ID NO: 155, 474, 793), TOP1 (SEQ ID NO: 314, 633, 952),i) KDM6B (SEQ ID NO: 1, 320, 639), BICD2 (SEQ ID NO: 2, 321, 640),ii) additionally to i.), NSUNS (SEQ ID NO: 155, 474, 793) and/or PPP1R2 (SEQ ID NO: 295, 614, 933),iii) additionally to i) or ii), at least one marker selected from the group RTEL1 (SEQ ID NO: 4, 323, 642), MYST2 (SEQ ID NO: 5, 324, 643), PSAT1 (SEQ ID NO: 6, 325, 644), TEX264 (SEQ ID NO: 7, 326, 645), TRIM21 (SEQ ID NO: 8, 327, 646), ABCB8 (SEQ ID NO: 9, 328, 647), AVEN (SEQ ID NO: 10, 329, 648), CENPA (SEQ ID NO: 13, 332, 651), CENPC1 (SEQ ID NO: 14, 333, 652), GYS1 (SEQ ID NO: 18, 337, 656), MARVELD2 (SEQ ID NO: 21, 340, 659), PMF1 (SEQ ID NO: 27, 346, 665), TTLL3 (SEQ ID NO: 30, 349, 668), ATP13A2 (SEQ ID NO: 44, 363, 682), LTF (SEQ ID NO: 75, 394, 713), STMN4 (SEQ ID NO: 92, 411, 730), ACBD6 (SEQ ID NO: 108, 427, 746), GTF2F1 (SEQ ID NO: 134, 453, 772), KDR (SEQ ID NO: 138, 457, 776), DIP2C (SEQ ID NO: 213, 532, 851), FXC1 (SEQ ID NO: 224, 543, 862), HNRNPA1 (SEQ ID NO: 227, 546, 865), HSBP1L1 (SEQ ID NO: 229, 548, 867), KARS (SEQ ID NO: 232, 551, 870), PBXIP1 (SEQ ID NO: 257, 576, 895), ZNF431 (SEQ ID NO: 290, 609, 928), STMN1 (SEQ ID NO: 293, 612, 931), SSRP1 (SEQ ID NO: 297, 616, 935).
  • 29. A panel of markers containing at least three markers for the diagnosis of dSSc according to claim 27 selected from the group KDM6B (SEQ ID NO: 1, 320, 639), TOP1 (SEQ ID NO: 314, 633, 952), TRIM21 (SEQ ID NO: 8, 327, 646), CENPC1 (SEQ ID NO: 14, 333, 652), ISY1 (SEQ ID NO: 137, 456, 775), HNRNPA1 (SEQ ID NO: 227, 546, 865).
  • 30. A panel of markers containing at least three markers for the diagnosis of 1SSc according to claim 27 selected from the group KDM6B (SEQ ID NO: 1, 320, 639), BICD2 (SEQ ID NO: 2, 321, 640), NSUNS (SEQ ID NO: 155, 474, 793), CENPB (SEQ ID NO: 155, 474, 793), TOP1 (SEQ ID NO: 314, 633, 952), RTEL1 (SEQ ID NO: 4, 323, 642), TRIM21 (SEQ ID NO: 8, 327, 646), ABCB8 (SEQ ID NO: 9, 328, 647), AVEN (SEQ ID NO: 10, 329, 648), CENPA (SEQ ID NO: 13, 332, 651), CENPC1 (SEQ ID NO: 14, 333, 652), CENPT (SEQ ID NO: 15, 334, 653), GYS1 (SEQ ID NO: 18, 337, 656), C19orf52 (SEQ ID NO: 48, 367, 686), STMN4 (SEQ ID NO: 92, 411, 730), ACBD6 (SEQ ID NO: 108, 427, 746), CBX3 (SEQ ID NO: 115, 434, 753), CENPH (SEQ ID NO: 118, 437, 756), EIF4E (SEQ ID NO: 123, 442, 761), GTF2F1 (SEQ ID NO: 134, 453, 772), MAPT (SEQ ID NO: 140, 459, 778), DIP2C (SEQ ID NO: 213, 532, 851), PBXIP1 (SEQ ID NO: 257, 576, 895), NEFL (SEQ ID NO: 292, 611, 930), STMN1 (SEQ ID NO: 293, 612, 931), SSRP1 (SEQ ID NO: 297, 616, 935).
  • 31. A diagnostic device or test kit comprising at least one marker for SSc or SSc subgroups as defined in claim 22, wherein the SSc subgroups comprise diffuse SSc (dSSc), limited SSc (1SSc) and SSc overlap syndrome (SSc-OS).
  • 32. A method for identifying subgroups of SSc patients, for diagnosis of SSc, for differential diagnosis of SSc or SSc subgroups, for distinguishing SSc from other autoimmune diseases or rheumatic diseases, for diagnosis of dSSc, 1SSc or SSc-OS, for prognosis of SSc, for therapy control in SSc, for active substance selection in SSc, for therapy monitoring in SSc, and/or for aftercare in SSc, comprising utilizing: a) at least one marker as defined in claim 22;b) a panel of markers comprising said at least one marker of a) and at least one or two different markers as defined in claim 22; orc) a diagnostic device or test kit comprising said at least one marker of a), wherein the SSc subgroups comprise diffuse SSc (dSSc), limited SSc (1SSc) and SSc overlap syndrome (SSc-OS).
  • 33. A method for diagnosis of dSSc, for differential diagnosis of dSSc, for distinguishing dSSc from other autoimmune diseases or rheumatic diseases, or from 1SSc or SSc-OS, for prognosis of dSSc, for therapy control in dSSc, for active substance selection in dSSc, for therapy monitoring in dSSc, and/or for aftercare in dSSc, comprising utilizing at least one marker as defined in claim 24.
  • 34. A method for diagnosis of 1SSc, for differential diagnosis of 1SSc, for distinguishing 1SSc from other autoimmune diseases or rheumatic diseases, or from dSSc or SSc-OS, for prognosis of 1SSc, for therapy control in 1SSc, for active substance selection in 1SSc, for therapy monitoring in 1SSc, and/or for aftercare in 1SSc, comprising utilizing at least one marker as defined in claim 25.
  • 35. A method for diagnosis of SSc-OS, for differential diagnosis of SSc-OS, for distinguishing SSc-OS from other autoimmune diseases or rheumatic diseases, or from dSSc or 1SSc, for prognosis of SSc-OS, for therapy control in SSc-OS, for active substance selection in SSc-OS, for therapy monitoring in SSc-OS, and/or for aftercare in SSc-OS, comprising utilizing at least one marker as defined in claim 26.
  • 36. A method for the early detection, diagnosis, prognosis, therapy control and/or aftercare of SSc or SSc subgroups, comprising: a) bringing a bodily fluid or tissue sample from an individual to be tested into contact with at least one of the markers as defined in claim 22; andb) detecting an interaction of the bodily fluid or tissue sample with the at least one marker.
  • 37. A composition or a pharmaceutical composition for specific application in SSc or SSc subgroups comprising at least one of the marker as defined in claim 22.
  • 38. A method for screening active substances for SSc or SSc subgroups, comprising: a) bringing a substance to be tested into contact with at least one of the markers as defined in claim 22; andb) detecting an interaction of the substance to be tested with the at least one marker.
Priority Claims (1)
Number Date Country Kind
14167807.8 May 2014 EP regional
PCT Information
Filing Document Filing Date Country Kind
PCT/EP2015/060396 5/11/2015 WO 00