Periodontitis diagnostic methods, uses and kits

Abstract

An in vitro method for assessing whether a human patient has periodontitis is disclosed. This method is based on insights into identifying biomarker proteins. Therefore, in a saliva sample from a patient with periodontitis, the concentrations of two or more proteins selected from matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK), and S100 calcium-binding protein A8 (S100A8) are measured. Based on the measured concentrations, a value reflecting the combined concentration of the protein is determined. This value is compared to a threshold that reflects the combined concentration associated with periodontitis in the same way. This comparison allows assessment of whether the test value indicates that the patient has periodontitis. Therefore, generally, a combined concentration reflected by the test value below the threshold indicates that the patient does not have periodontitis, and a combined concentration reflected by the test value equal to or higher than the threshold indicates that the patient has periodontitis.

Description

Technical Field

[0001] The present invention belongs to the field of oral care and relates to the diagnosis of periodontal diseases based on saliva. In particular, the present invention relates to a kit, use and method for diagnosing periodontitis. Background Art

[0002] Gum inflammation or gingivitis is a non-destructive periodontal disease caused primarily by the adhesion of dental bacterial biofilm or plaque to the tooth surface. If not detected and treated, reversible gingivitis usually leads to inflammation of the tissues surrounding the teeth (i.e., the periodontium), a condition defined as periodontitis, which is irreversible and leads to tissue destruction and alveolar bone loss, ultimately leading to tooth loss. As gum disease progresses, there are often clinical signs and symptoms associated with it, such as swollen gums, a change in color from pink to dark red, bleeding gums, bad breath, and gums becoming more tender or painful to the touch.

[0003] Periodontitis is a chronic, multifactorial, inflammatory disease caused by oral microorganisms and characterized by the progressive destruction of hard (bone) and soft (periodontal ligament) tissues, ultimately leading to tooth movement and loss. This is to be distinguished from gingivitis, which is a reversible infection and inflammation of the gum tissue. Inflammatory periodontitis is one of the most common chronic human diseases and is the leading cause of tooth loss in adults. In addition to its substantial negative impact on oral health, there is increasing evidence that periodontitis has systemic consequences and is a risk factor for several systemic diseases, including heart disease (e.g., atherosclerosis, stroke), diabetes, pregnancy complications, rheumatoid arthritis, and respiratory infections.

[0004] Therefore, early and accurate diagnosis of periodontal disease is important from both the perspective of oral and overall health.

[0005] In general dental practice, periodontal disease remains poorly diagnosed, resulting in relatively low rates of therapeutic intervention and a significant number of untreated cases. Current diagnosis relies on imprecise, subjective clinical examination of the condition of oral tissues (color, swelling, degree of bleeding on probing, depth of probing pockets; and bone loss found from oral X-rays) by dental professionals. These traditional methods are very time consuming, and some of the techniques used (pocket depth, X-rays) reflect historical events, such as past disease activity, rather than current disease activity or susceptibility to further disease. Therefore, a more objective, faster, more accurate, easier to use diagnosis that can preferably also be performed by non-professionals is desired. Therefore, it is desirable to measure the activity of the current disease and, possibly, the susceptibility of the subject to further periodontal disease.

[0006] Saliva or oral fluid has long been advocated as a diagnostic fluid for oral and general diseases, and with the advent of miniaturized biosensors (also known as labs on a chip), point of care diagnostics for rapid chairside testing have gained greater scientific and clinical attention. In particular, for periodontal disease detection, inflammatory biomarkers associated with tissue inflammation and decay may be easily terminated in saliva due to proximity, suggesting that saliva has great potential for periodontal disease detection. In fact, this field has therefore gained significant attention and has presented encouraging results. For example, Ramsier et al. (J Periodontol. 2009 Mar; 80 (3): 436-46) identified host and bacteria-derived biomarkers associated with periodontal disease. However, no clear test has yet emerged.

[0007] Biomarkers represent biological indicators that support clinical manifestations and are thus objective indicators of clinical outcome in diagnosing periodontal disease. Ultimately, proven biomarkers can be utilized to assess risk for future disease, identify disease at very early stages, identify response to initial therapy, and allow preventive strategies.

[0008] Factors that have previously limited the development of point-of-care tests for salivary biomarkers include the lack of technology suitable for chairside use and the inability to analyze multiple biomarkers in an individual sample. Furthermore, the choice of which multiple biomarkers to include in such tests has not been adequately addressed in the literature nor implemented in actual testing.

[0009] It would be desirable to provide a simpler method and in particular a method which only requires the collection of a small saliva sample from the patient and which can be collected by the patient himself. It would be desirable to input such a sample into an in vitro diagnostic device which allows the saliva sample to be classified based on the measurement so that the device can return an indication as to the likelihood that the patient is classified as having periodontitis. Summary of the invention

[0010] In order to better meet the above expectations, on the one hand, the present invention relates to an in vitro method for assessing whether a human patient suffers from periodontitis, the method comprising detecting the concentration of at least two proteins selected from matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8) in a saliva sample of the human patient; determining a test value reflecting the combined concentration determined for the protein; and comparing the test value with a threshold value, the threshold value reflecting the combined concentration associated with periodontitis in the same manner, so as to assess whether the test value indicates periodontitis in the patient.

[0011] In another aspect, the present invention proposes the use of at least two of the following proteins in a saliva sample of a human patient as biomarkers for assessing whether the patient suffers from periodontitis: selected from matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8).

[0012] Optionally, the patient's age is also used as a biomarker.

[0013] In another aspect, the present invention is a system for assessing whether a human patient suffers from periodontitis, the system comprising:

[0014] - a detection device capable of and adapted to detect at least two proteins selected from the group consisting of matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8) in a saliva sample of a human patient; and

[0015] - a processor capable and adapted to determine, from the determined concentration of the protein, an indication that the patient suffers from periodontitis.

[0016] The system optionally comprises a data connection to an interface, in particular a graphical user interface, which enables information to be presented and preferably also enables input of information such as the age of the subject and optionally other information such as gender and / or BMI (body mass index), the interface being part of the system or being a remote interface.

[0017] Optionally, one or more of the aforementioned items, in particular the processor, is enabled to function “in the cloud”, ie not fixed on a machine, but by means of an Internet-based application.

[0018] In yet another aspect, the present invention provides a kit for detecting at least two periodontitis biomarkers for periodontitis in a saliva sample of a human patient, the kit comprising a detection agent for detecting at least two proteins selected from matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8).

[0019] Typically, two or more, or three or more, detection agents are used, each of which binds to a different biomarker. In one embodiment, the first detection agent is capable of detecting MMP-8 or MMP-9, the second detection agent is capable of detecting a different protein selected from MMP-8, MMP-9, pyruvate kinase (PK), and S100 calcium binding protein A8 (S100A8), and the optional third detection agent is capable of detecting a different protein selected from matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK), and S100 calcium binding protein A8 (S100A8). In other embodiments, separate detection agents are provided for each protein biomarker in the combination provided in Table 1 below.

[0020] In yet another aspect, the present invention provides a method for determining a time interval from a first time point t 1 At the second time point t 2 An in vitro method for determining changes in periodontitis status in human patients over a time interval of t 1 At least one saliva sample obtained from the patient at t 2 The method comprises detecting the concentration of at least two proteins selected from matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8) in at least one saliva sample obtained from the patient; and comparing the concentrations, whereby a difference in one, two or more of the concentrations reflects a change in state.

[0021] In another aspect, the present invention provides a method for diagnosing whether a human patient suffers from periodontitis, comprising detecting at least two proteins selected from matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8) in a saliva sample of the human patient; and assessing the presence of periodontitis in the patient based on the concentration of the protein in the sample. Optionally, the method of this aspect comprises the further step of treating the patient's periodontitis.

[0022] In yet another aspect, the present invention provides a method for detecting at least two proteins selected from matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8) in a human patient, comprising:

[0023] (a) obtaining a saliva sample from a human patient; and

[0024] (b) detecting the presence or absence of proteins in the sample by contacting the sample with one or more detection agents for two or more proteins and detecting binding between each protein and the one or more detection agents. Typically, at least a first and a second, and sometimes a third and a fourth detection agent are present, as described elsewhere herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A system for use in the method of the present disclosure is schematically shown.

[0026] Figure 2 is a plot of the number of study groups versus the minimum AUC LOOCV required performance. DETAILED DESCRIPTION

[0027] In a general sense, the present invention is based on the insight that periodontitis can be distinguished from a healthy or gingivitis oral cavity with sufficient accuracy based on the measurement of a small number of protein biomarkers. In particular, it has been found that as few as two proteins can act as biomarkers in saliva samples of human patients for identifying the presence or absence of periodontitis.

[0028] These biomarker proteins are matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8). According to the present invention, two or more of these proteins are generally used. In some embodiments, MMP-8 and / or MMP-9 are present.

[0029] The age of the subject may optionally be included as an additional marker.

[0030] MMP is a family of enzymes responsible for the degradation of extracellular matrix components (such as collagen, proteoglycans, laminin, elastin and fibronectin). MMP plays an important role in the remodeling of periodontal ligament (PDL) under both physiological and pathological conditions. MMP-8, also known as neutrophil collagenase or PMNL collagenase (MNL-CL), is a collagenase present in the connective tissue of most mammals. MMP-9, also known as 92kDa type IV collagenase, 92kDa gelatinase or gelatinase B (GELB), is a matrix protein, belonging to a class of enzymes of the zinc-metalloproteinase family involved in the degradation of the extracellular matrix.

[0031] S100 calcium-binding protein A8 (S100A8) is a calcium-binding and zinc-binding protein that plays a significant role in regulating inflammatory processes and immune responses. S100 calcium-binding protein A8 can induce neutrophil chemotaxis and adhesion.

[0032] Pyruvate kinase catalyzes the final step of glycolysis. There are four tissue-specific isoenzymes of pyruvate kinase, each with specific kinetic properties required for different tissues.

[0033] The above proteins are known in the art. The skilled person knows the structures of the above proteins, as well as methods for detecting the above proteins in aqueous samples (such as saliva samples).

[0034] Table 1 in the examples provides 25 particularly preferred protein biomarker combinations according to the present invention. Age is included in each combination in the table, but can be optionally excluded if desired.

[0035] In one embodiment, the biomarker panel of the present invention can be composed of identified protein biomarkers. Preferably, the biomarker panel of the present invention is composed of no more than four protein biomarkers identified by the present invention, such as two, three or four protein biomarkers of the present invention. In addition to the biomarker panel of the present invention, other biomarkers and / or data, such as demographic data (e.g., age, gender), can be included in the data set for the determination of periodontitis. Additional protein biomarkers include IL-1β, HGF, FLCκ, FLCλ, A1AGP, Hb-β, Hb-δ, keratin 4, inhibitor protein and S100A9. One or more of these additional proteins are included in some preferred groups in the following examples.

[0036] IL-1β (interleukin-1-β) is a member of the interleukin 1 cytokine family. This cytokine is produced by activated macrophages as a proprotein and is proteolytically processed by caspase 1 (CASP1 / ICE) to its active form. This cytokine is an important mediator of inflammatory responses and is involved in a variety of cellular activities, including cell proliferation, differentiation, and apoptosis.

[0037] Hepatocyte growth factor (HGF) is a paracrine cell growth, motility and morphogenesis factor. HGF is secreted by mesenchymal cells, and mainly targets and acts on epithelial cells and endothelial cells, and also acts on hematopoietic progenitor cells. It has been shown that HGF plays an important role in myogenesis and in wound healing. The ability of HGF to stimulate mitosis, cell motility and matrix invasion makes it play a core role in angiogenesis, tumorigenesis and tissue regeneration. HGF stimulates the growth of epithelial cells, and prevents connective tissue from attaching and regenerating. HGF is a known serum marker indicating disease activity in various diseases.

[0038] Free light chain proteins are immunoglobulin light chains. Free light chain proteins are not associated with immunoglobulin heavy chains. Unlike typical complete immunoglobulin molecules, free light chain proteins are not covalently linked to immunoglobulin heavy chains, for example, free light chains are not disulfide bonded to heavy chains. Typically, free light chains include about 220 amino acids. Typically, free light chain proteins include a variable region (commonly referred to as a light chain variable region, V L ) and constant region (often called the light chain constant region, C L ). Humans produce two types of immunoglobulin light chains, named with the letters κ and λ. Each of these can be further divided into subgroups, of which there are four κ subtypes (Vκ1, Vκ2, Vκ3 and Vκ4) and six λ subtypes (Vλ1, Vλ2, Vλ3, Vλ4, Vλ5 and Vλ6), according to changes in the variable region. Free light chain κ is usually a monomer. Free light chain λ is usually a dimer, connected by a disulfide bond (to another free light chain λ). Polymeric forms of free light chain λ and free light chain κ have been identified. Free light chains are produced by bone marrow and lymph node cells, and locally by diffuse lymphocytes in periodontal tissues, and are rapidly cleared from the blood and degraded by the kidneys. Monomeric free light chains are cleared within 2-4 hours, and dimeric free light chains are cleared within 3-6 hours.

[0039] Alpha-1-acid glycoprotein (A1AGP) is a plasma alpha-globulin glycoprotein synthesized primarily by the liver. It is sometimes also referred to as serum mucoid. Alpha-1-acid glycoprotein (A1AGP) acts as a transport protein in the blood that acts as a carrier for alkaline and neutrally charged lipophilic compounds. It is also believed to regulate the interaction between blood cells and endothelial cells.

[0040] Hemoglobin (Hb) is an iron-oxygen transport metalloprotein present in almost all vertebrate red blood cells and in the tissues of some invertebrates. Hemoglobin-β (also known as β-globin, HBB, β-globin and hemoglobin subunit β) is a globin protein that, together with α-globin (HBA), constitutes the most common form of adult hemoglobin, HbA. Hb-β is typically 146 amino acids long and has a molecular weight of 15,867 Da. Normal adult HbA is a heterotetramer composed of two α chains and two β chains. Hb-β is encoded by the HBB gene on human chromosome 11.

[0041] Hemoglobin subunit delta (also known as delta globin, HBD, delta-globin and hemoglobin delta) is a globin protein that, together with alpha globin (HBA), makes up the less common form of adult hemoglobin, HbA-2. Hb-delta is normally 147 amino acids long and has a molecular weight of 16,055 Da. Adult HbA-2 is a heterotetramer composed of two alpha chains and two delta chains. Hb-delta is encoded by the HBD gene on human chromosome 11.

[0042] Keratin-4 (K-4), also known as cytoskeletal keratin-4 (CYK-4) or cytokeratin-4 (CK-4), is a protein encoded by the KRT4 gene in humans. Keratin-4 is a member of the keratin gene family. Type II cytokeratins consist of basic or neutral proteins that are paired in pairs of heterotypic keratin chains that are co-expressed during differentiation of simple and stratified epithelial tissues. Type II cytokeratin CK-4 is specifically expressed in the differentiated layers of mucosal and esophageal epithelial cells with family member KRT13. Mutations in these genes are associated with white sponge nevus, which is characterized by white patches of the mouth, esophagus, and anus. Type II cytokeratins are clustered in the region of chromosome 12q12-q13.

[0043] Arrestins are actin-binding proteins involved in the dynamic turnover and remodeling of the actin cytoskeleton and are found in most cells. Arrestins are important for the spatial and temporal controlled growth of actin filaments, a fundamental process for cell motility and cell shape change. Human arrestin-1 is normally expressed as 140 amino acids in length, but is often further processed to the mature form.

[0044] S100 calcium-binding protein A9 (S100A9), also known as calgranulin B, is a calcium-binding and zinc-binding protein that plays a significant role in the regulation of inflammatory processes and immune responses. S100 calcium-binding protein A9 can induce neutrophil chemotaxis and adhesion, promote phagocytosis through the activation of SYK, PI3K / AKT, and ERK1 / 2, thereby increasing the bactericidal activity of neutrophils, and can induce neutrophil degranulation through a MAPK-dependent mechanism.

[0045] When additional biomarkers are optionally included, the total number of biomarkers (ie, the biomarker panel of the invention plus the additional biomarkers) is typically 3, 4, 5, or 6.

[0046] However, one desired advantage of the present invention is that the classification of a patient's periodontitis can be determined by measuring preferably no more than four biomarkers, such as two, three or four protein biomarkers. In particular, this determination does not require the use of other data, thereby advantageously providing a simple and direct diagnostic test.

[0047] The following combinations of only two protein biomarkers were considered particularly advantageous: MMP-8 and MMP-9; MMP-8 and PK; MMP-8 and S100A8; or MMP-9 and pyruvate kinase.

[0048] As required, the method only requires obtaining a small amount (e.g., droplet-sized) of saliva sample from the subject. The size of the sample is typically 0.1 μl-2 ml, such as 1 ml-2 ml, whereby a smaller amount (e.g., 0.1 μl-100 μl) can be used for in vitro device processing, and thus, extracting a larger sample, such as up to 20 ml, such as 7.5 ml-17 ml, is also possible.

[0049] The sample is input into an in vitro diagnostic device which measures the concentration of the protein(s) of interest and returns a diagnosis, thereby categorizing the subject based on the likelihood of having periodontitis.

[0050] The ease of use of the invention allows for the testing of most dental patients who suffer from periodontitis or who are at high risk of periodontitis on a regular basis, for example as part of a regular dental check-up or even at home. This allows in particular the detection of the presence of periodontitis immediately after it has developed, and thereby enables more timely oral care measures to be taken to prevent the development of periodontitis. Alternatively, for example, for a patient who is known to be at high risk of periodontitis and is being tested for the first time, the method allows the identification of whether periodontitis has already developed. In particular, the method is also suitable for self-diagnosis, whereby the steps of obtaining a sample and inputting the sample into the device can be performed by the patient himself.

[0051] When performing the present invention to confirm the presence or absence of periodontitis, the patient may generally be known or suspected to have periodontitis. Thus, in certain embodiments, the present method is used to assess whether a human patient known or suspected to have periodontitis has periodontitis.

[0052] The methods of the present invention generally comprise detecting the above-mentioned proteins and optionally further other biomarker proteins constituting the biomarker panel of the present invention using one or more detection agents.

[0053] According to the present invention, the "saliva" tested can be undiluted saliva that can be obtained by spitting or wiping, or diluted saliva that can be obtained by flushing the mouth with a fluid. Diluted saliva can be obtained by the patient flushing the mouth or gargling for a few seconds with sterile water (e.g., 5 ml or 10 ml) or other appropriate fluid and spitting into a container. Diluted saliva can sometimes be referred to as an oral rinse.

[0054] "Detection" refers to measuring, quantifying, scoring or determining the concentration of a biomarker protein. Methods for evaluating biological compounds, including biomarker proteins, are known in the art. It is recognized that methods for detecting protein biomarkers include direct measurement and indirect measurement. Those skilled in the art are able to select appropriate methods for determining a particular biomarker protein.

[0055] The term "concentration" of a protein biomarker is given its usual meaning, i.e., the abundance of the protein in a volume. Protein concentration is usually measured in mass / volume, most commonly in mg / ml, μg / ml, or ng / ml, but sometimes as low as pg / ml. Another alternative measurement is molar concentration, mol / L, or "M". Concentration can be determined by measuring the amount of protein in a known, determined, or predetermined volume sample.

[0056] An alternative method to determining concentration is to determine the absolute amount of the protein biomarker in the sample, or to determine the mass fraction of the biomarker in the sample, such as the amount of the biomarker relative to the total amount of all other proteins in the sample.

[0057] A "detection agent" is an agent or compound that specifically (or selectively) binds to, interacts with, or detects a protein biomarker of interest. Such detection agents may include, but are not limited to, antibodies, polyclonal antibodies, or monoclonal antibodies that preferentially bind to a protein biomarker.

[0058] When referring to a detection agent, the phrase "specifically (or selectively) binds" or "specifically (or selectively) immunoreacts with..." refers to a binding reaction that determines the presence of a protein biomarker in a heterogeneous population of proteins and other biological agents. Thus, under specified immunoassay conditions, a particular detection agent (e.g., an antibody) binds to a particular protein at least twice the background and does not substantially bind to other proteins present in the sample in significant amounts. Specific binding under such conditions may require an antibody selected for its specificity for a particular protein. A variety of immunoassay formats can be used to select antibodies that specifically immunoreact with a particular protein. For example, solid phase ELISA immunoassays (enzyme-linked immunosorbent assays) are routinely used to select antibodies that specifically immunoreact with a protein (for a description of immunoassay formats and conditions that can be used to determine specific immunoreactions, see, e.g., Harlow & Lane, Antibodies, A Laboratory Manual (1988)). Typically, a specific or selective reaction will be at least twice the background signal or noise, and more typically 10 to 100 times or more of the background.

[0059] "Antibody" refers to a polypeptide ligand that is substantially encoded by one or more immunoglobulin genes or fragments of immunoglobulin genes, and the polypeptide ligand specifically binds to and recognizes an epitope (e.g., an antigen). The recognized immunoglobulin genes include kappa and lambda light chain constant region genes, alpha, gamma, delta, epsilon, and mu heavy chain constant region genes, and a large number of immunoglobulin variable region genes. Antibodies exist, for example, as complete immunoglobulins, or as several well-characterized fragments produced by digestion with various peptidases. This includes, for example, Fab' and F(ab)'2 fragments. The term "antibody" as used herein also includes modifications of antibody fragments produced by complete antibodies or modified antibody fragments synthesized de novo using recombinant DNA methods. Antibodies also include polyclonal antibodies, monoclonal antibodies, chimeric antibodies, humanized antibodies, or single-chain antibodies. The "Fc" portion of an antibody refers to a portion of an immunoglobulin heavy chain, including one or more heavy chain constant region domains CH1, CH2, and CH3, but not including a heavy chain variable region. An antibody can be a bispecific antibody, such as an antibody having a first variable region that specifically binds to a first antigen and a second variable region that specifically binds to another different second antigen. The use of at least one bispecific antibody can reduce the number of detection agents required.

[0060] Diagnostic methods differ in the sensitivity and specificity of the diagnostic method. The "sensitivity" of a diagnostic assay refers to the percentage of sick individuals that test positive (the percentage of "true positives"). Sick individuals that are not detected by the assay are "false negatives." Subjects who are not sick and test negative in the assay are called "true negatives." The "specificity" of a diagnostic assay is 1 minus the false positive rate, where the "false positive" rate is defined as the proportion of individuals who are not sick but test positive.

[0061] The (one or more) biomarker proteins of the present invention can be detected in a sample by any means. The preferred method for biomarker detection is based on the determination of antibodies, the determination of protein arrays, the determination based on mass spectrometry (MS) and the determination based on (near) infrared spectroscopy. For example, immunoassays include, but are not limited to, competitive and non-competitive determination systems using technologies such as protein immunoblots (western blots), radioimmunoassays, ELISA, "sandwich" immunoassays, immunoprecipitation assays, precipitation reactions, gel diffusion precipitation reactions, immunodiffusion assays, fluorescent immunoassays, etc. This determination is conventional and well known in the art. Exemplary immunoassays will be briefly described below (but are not intended to be limiting).

[0062] Immunoprecipitation protocols generally include lysing a cell population in a lysis buffer supplemented with protein phosphatases and / or protease inhibitors (e.g., EDTA, PMSF, aprotinin, sodium vanadate), such as RIPA buffer (1% NP-40 or TritonX-100, 1% sodium deoxycholate, 0.1% SDS, 0.15M NaCl, 0.01M sodium phosphate at pH 7.2, 1% trehalose), adding an antibody of interest to the cell lysate, incubating for a period of time (e.g., 1-4 hours) at 4°C, adding protein A and / or protein G agarose beads to the cell lysate, incubating for about one hour or longer at 4°C, washing the beads in the lysis buffer, and resuspending the beads in SDS / sample buffer. The ability of an antibody to immunoprecipitate a specific antigen can be assessed by, for example, Western blot analysis. Those skilled in the art are familiar with parameters that can be modified to increase antibody binding to the antigen and reduce background (e.g., pre-cleaning of the cell lysate with agarose beads).

[0063] Western blot analysis generally includes preparing protein samples in polyacrylamide gels (e.g., 8%-20% SDS-PAGE depending on the molecular weight of the antigen), electrophoresing the protein samples, transferring the protein samples from the polyacrylamide gel to a membrane, such as nitrocellulose, PVDF or nylon, blocking the membrane in a blocking solution (e.g., PBS or non-fat milk with 3% BSA), washing the membrane in a washing buffer (e.g., PBS-Tween20), blocking the membrane with a primary antibody (antibody of interest) diluted in a blocking buffer, washing the membrane in a washing buffer, blocking the membrane with a secondary antibody (which recognizes the primary antibody, e.g., an anti-human antibody), conjugating the secondary antibody to an enzyme substrate (e.g., horseradish peroxidase or alkaline phosphatase) or a radioactive molecule (e.g., 32P or 125I) diluted in a blocking buffer, washing the membrane in a washing buffer, and detecting the presence of the antigen. Those skilled in the art are well aware of the parameters that can be modified to increase the detection signal and reduce the background.

[0064] ELISA generally includes preparing an antigen (i.e., a biomarker protein or a fragment of a biomarker protein of interest), coating the wells of a "96-well" microtiter plate with the antigen, adding an antibody of interest conjugated to a detectable compound such as an enzyme substrate (e.g., horseradish peroxidase or alkaline phosphatase) to the wells, incubating for a period of time, and detecting the presence of the antigen. In ELISA, the antibody of interest does not have to be conjugated to a detectable compound; instead, a secondary antibody (which recognizes the antibody of interest) conjugated to a detectable compound can be added to the well. In addition, the antibody can be coated into the well instead of coating the well with the antigen. In this case, after the antigen of interest is added to the coated well, a secondary antibody conjugated to the detectable compound can be added. Those skilled in the art are familiar with the parameters that can be modified to increase the detection signal and other variations of ELISA known in the art.

[0065] Since multiple markers are used, a threshold is determined based on the combined concentrations of these biomarkers (and optionally age). This threshold determines whether a patient is classified as having periodontitis or not. The present invention reflects the insight that periodontitis can be detected with sufficient accuracy based on the measurement of a combination of biomarkers as shown above.

[0066] This insight supports another aspect of the present invention, namely, the use of at least two proteins selected from matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8) in saliva samples of human patients as biomarkers for assessing whether the patient suffers from periodontitis.

[0067] Such use may be achieved in a method substantially as described above and below.

[0068] The method of the present invention includes determining a test value reflecting the measured combined concentration of the protein. The combined concentration value can be any value obtained by inputting the determined concentrations and performing arithmetic operations on these values. The combined concentration value can be, for example, a simple addition of the concentrations. The combined concentration value can also involve multiplying each concentration by a factor reflecting the desired weight of the concentration, and then adding the results. The combined concentration value can also involve multiplying the concentrations by one another, or any combination of multiplication, division, subtraction, exponentiation, and addition. The combined concentration value can also involve raising the concentrations to several powers.

[0069] Optionally, the test value, combined with the age of the subject, reflects the concentration for the combined concentration of the protein(s) determined.

[0070] The resulting combined concentration value is compared to a threshold value that reflects in the same manner the combined concentration associated with the presence of periodontitis. This comparison allows an assessment of whether the test value indicates that the patient whose saliva was tested suffers from periodontitis.

[0071] The threshold value can, for example, be based on a combined concentration value and is obtained in the same manner based on the concentration (s) of the same (s) protein(s) determined in a reference sample associated with the presence of periodontitis, for example in a patient diagnosed with periodontitis. Typically, thereby, a value reflecting the same or higher combined concentration indicates the presence of periodontitis in the patient tested. Similarly, a value reflecting a lower combined concentration in the saliva of a patient with periodontitis tested indicates the absence of periodontitis. However, it should be understood that the threshold value can also be calculated (for example by using a negative multiplier) so that a test value indicating periodontitis is below the threshold value and a test value indicating the absence of periodontitis is above the threshold value.

[0072] The threshold value can also be determined based on measuring the concentration (one or more) of the biomarker protein (s) present in a sample group, the sample group including patients with a known diagnosis of periodontitis and "without" periodontitis. Thus, the measured concentration values ​​can be statistically analyzed, possibly including machine learning methods, allowing patients classified as having periodontitis and patients not having periodontitis to be distinguished with the desired sensitivity and specificity. Thus, the desired threshold value can be obtained. Based on the threshold value, the sample to be tested can be subjected to the same concentration measurement, and the concentration values ​​are then processed in the same manner as the threshold value is obtained, so as to determine a joint concentration value that can be compared with the threshold value, thereby allowing the test sample to be classified as having periodontitis and not having periodontitis.

[0073] In an interesting embodiment, the combined concentration value is obtained in the form of a score as follows. A numerical value (protein concentration value, e.g., ng / ml) is assigned to each measurement, and these values ​​are used in linear or nonlinear combination to calculate a score between 0 and 1. In the case where the threshold is determined based on a group of subjects as described above, the score between 0 and 1 is typically calculated using a sigmoid function that takes the combined concentration as input (as further shown).

[0074] When the score exceeds a certain threshold, the method indicates that the patient has periodontitis. The threshold can be selected based on the desired sensitivity and specificity.

[0075] It should be understood that, according to the present invention, when "classifying periodontitis" for a subject, it can be for a subject who has no knowledge or awareness of his or her periodontitis status, or it can be for a subject who is assumed to be at risk of or suffering from periodontitis. Such prior knowledge can usually be obtained from, for example, a previous diagnosis of periodontitis (although it may not be possible to distinguish the degree of periodontitis), or, for example, assumed from the oral health status record of the subject.

[0076] The clinical definition as recognized in the art is based on the following:

[0077] Gingival Index (GI)

[0078] The full mouth gingival index will be recorded based on the Lobene modified gingival index (MGI) rated on a scale of 0-4, where:

[0079] ——0 = no inflammation,

[0080] - 1 = Mild inflammation; slight change in color of any part of the marginal or papillary gingival unit but not the entire marginal or papillary gingival unit, with little or no change in texture,

[0081] -2 = mild inflammation; but involving the entire marginal or papillary unit,

[0082] - 3 = moderate inflammation; pigmentation, redness, edema and / or hypertrophy of the margin or papillary units,

[0083] - 4 = severe inflammation; marked erythema, edema and / or hypertrophy of marginal or papillary gingival units, spontaneous bleeding, hyperaemia or ulceration.

[0084] Probing Depth (PD)

[0085] Using a manual UNC-15 periodontal probe, the probing depth was recorded to the nearest mm. The probing depth was the distance from the probe tip (assumed to be at the base of the pocket) to the free gingival margin.

[0086] Gingival recession (REC)

[0087] Gingival recession was recorded to the nearest mm using a manual UNC-15 periodontal probe. Gingival recession was the distance from the free gingival margin to the cemento-enamel junction. Gingival recession was indicated by positive numbers, and gingival overgrowth was indicated by negative numbers.

[0088] Clinical attachment loss (CAL)

[0089] Clinical attachment loss was calculated as the sum of probing depth + depression at each site.

[0090] Bleeding on probing (BOP)

[0091] After probing, each site was assessed for bleeding on probing and was assigned a score of 1 if bleeding occurred within 30 seconds of probing and 0 otherwise.

[0092] The resulting subject groups (patient groups) were defined as follows, whereby the moderate periodontitis and severe periodontitis groups are the "periodontitis" relevant to the present invention:

[0093] - Healthy group (H): PD ≤ 3 mm for all sites (but up to four 4 mm pockets distal to the last upright molar were allowed), no sites with interproximal attachment loss, GI ≥ 2.0 in ≤ 10% of sites, % BOP score ≤ 10%;

[0094] - Gingivitis group (G): GI ≥ 3.0 in >30% of sites, no sites with interproximal attachment loss, no sites with PD > 4 mm, % BOP score > 10%;

[0095] -- Moderate periodontitis group (MP): ≥8 teeth with 5mm-7mm interproximal PD (equivalent to approximately 2mm-4mm CAL), %BOP score >30%;

[0096] - Advanced periodontitis group (AP): ≥12 teeth with interproximal PD ≥7 mm (equivalent to approximately ≥5 mm of CAL), %BOP score >30%.

[0097] In one embodiment, the method of the present invention utilizes Figure 1 The system schematically shown in FIG. The system may be a single device with various equipment components (units) integrated therein. The system may also have various components as independent devices, or some of these components. Figure 1 The components shown are the measuring device (A), the graphical user interface (B) and the computer processing unit (C).

[0098] As mentioned above, the system of the invention comprises a data connection to the interface, whereby the interface itself may be part of the system or may be a remote interface. The latter refers to the possibility of using different devices to provide the actual interface, preferably handheld devices such as smartphones or tablets. In this case, the data connection will preferably involve wireless data transmission, such as by Wi-Fi or Bluetooth, or by other technologies or standards.

[0099] The measuring device (A) is configured to receive a saliva sample, for example by placing a drop of saliva on a cartridge (A1), which can be inserted into the device (A). The device can be an existing device capable of determining protein concentration from the same saliva sample.

[0100] The processing unit (C) receives the numerical value of the protein concentration from component (A). The unit (C) is provided with software (typically embedded software) to allow it to calculate a score (S) between 0-1. The software also includes the numerical value of a threshold value (T). If the calculated value (S) exceeds (T), the unit (C) will output an indication (I) of "periodontitis" to the GUI (B), otherwise it will output "no periodontitis". Another embodiment may use a specific value of (S) to indicate the certainty of making the indication (I). This may be a probability score, where 0.5 is a possible threshold, for example, a score S=0.8 indicates the possibility of periodontitis. Interesting options are:

[0101] Based on the score S, the certainty can be directly indicated, i.e. S = 0.8 means that the certainty of periodontitis is 80%; or

[0102] In order to make an indication by defining the range of R1-R2, when R1<S<R2, the indication (I) shows "uncertain".

[0103] For example, a particular calculation of the score may be achieved using a sigmoid function applying the following formula:

[0104]

[0105] Where N is the number of proteins / biomarkers. 0 、c 1 etc. are coefficients (values), B 1 , B 2 etc. are the concentrations of various proteins.

[0106] Coefficient C i This can be determined through a training procedure:

[0107] - N1 subjects with periodontitis (as determined by dentists using current criteria) and N2 patients without periodontitis (either with healthy gums or with gingivitis) were selected.

[0108] - Saliva samples were obtained from each subject and the protein concentrations of the biomarker panels as described above were determined.

[0109] - The score S for periodontitis was defined as 1, and the score S for no periodontitis (healthy gums or gingivitis) was defined as 0.

[0110] - Fit a sigmoid function to the score vs. protein concentration values.

[0111] Other regression or machine learning methods (linear regression, neural networks, support vector machines) may be used, where patients with periodontitis have a higher score S and non-periodontitis / healthy controls have a lower score S.

[0112] In particular, such procedures have been applied (in examples) using clinical studies on subjects with or without periodontitis (i.e., healthy gums or with gingivitis, as identified by clinical evaluation by a dental professional according to current standards, such as the American Academy of Periodontology standards). The performance of various biomarker combinations was evaluated by leave-one-out-cross validation, resulting in the preferred biomarker combinations of the present invention.

[0113] With reference to the above system, the present invention also provides, in another aspect, a system for assessing whether a human patient suffers from periodontitis, the system comprising:

[0114] - a detection device capable of and adapted to detect at least two proteins selected from the group consisting of matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8) in a saliva sample of a human patient;

[0115] As described above, such devices are known and can be easily obtained by a skilled person. Typically, a container is provided for receiving an oral sample of a subject therein, and the above-mentioned detection device is disposed in the container;

[0116] - A processor capable and adapted to determine, from the determined concentration of the protein, an indication that the patient suffers from periodontitis.

[0117] Optionally, the system includes a user interface (or a data connection to a remote interface) capable of presenting information, particularly a graphical user interface (GUI); a GUI is a user interface that allows a user to interact with an electronic device through graphical icons and visual indicators such as auxiliary symbols, rather than a text-based user interface, typed instruction labels or text navigation (any such interface is not excluded in the present invention); GUIs are generally well known and are typically used in handheld mobile devices such as MP3 players, portable media players, gaming devices, smart phones and smaller home, office and industrial control devices; as described above, optionally, the interface may also be selected to be capable of inputting information such as the subject's age, gender, BMI (body mass index).

[0118] Alone or as part of the above system, the present invention also provides a kit for detecting at least two periodontitis biomarkers in a saliva sample of a human patient, the kit comprising one or more detection agents for detecting at least two proteins selected from matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8).

[0119] Typically, the kit includes two or more, or three or more detection agents, each for a different biomarker of the invention. In one embodiment, the first detection agent is used to detect MMP8, and the second detection agent is used to detect MMP-9, PK or S100A8. A third detection agent may be included to detect another of MMP-9, PK or S100A8. A fourth detection agent may be included to detect the last of MMP-9, PK and S100A8.

[0120] As discussed above with respect to the methods of the invention, the kit may include more detection agents, such as detection agents for other proteins. In a preferred embodiment, as mentioned, the detection agents available in the kit consist of detection agents for detecting two, three or four proteins constituting the biomarker panel of the invention. In other embodiments, a separate detection agent for one or more of IL-1β, HGF, FLCκ, FLCλ, A1AGP, Hb-β, Hb-δ, keratin 4, inhibitor protein and S100A9 may also be included. In other embodiments, a separate detection agent is provided for each biomarker protein present in the combination exemplified in Table 1 in the examples below.

[0121] Preferably, the kit comprises a solid support, such as a chip, microtiter plate or beads or resin containing the detection agent. In some embodiments, the kit comprises a mass spectrometry probe, such as ProteinChip TM .

[0122] The kit may also provide a specific wash solution and / or a detection agent (sandwich type assay) for unbound detection agent or biomarker.

[0123] In an interesting aspect, the identification of a biomarker panel of the present invention is applied to monitoring the periodontitis status of a human patient over time. 1 At the second time point t 2 An in vitro method for determining changes in the periodontitis status of a human patient suffering from periodontitis at a time interval of t 1 At least one saliva sample obtained from the patient at t 2 The concentration of at least two proteins selected from matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8) is detected in at least one saliva sample obtained from the patient at the time of the test, and the concentrations are compared, whereby the difference in at least two concentrations preferably reflects a change in state. Such a difference may be referred to as a concentration difference, thereby allowing a direct comparison without first generating a number between 0 and 1, or any other classification. It should be understood that the measurements received at the two time points may also be processed in the same manner as when determining the periodontitis state as above.

[0124] The present invention also provides a method for diagnosing whether a human patient suffers from periodontitis, comprising detecting at least two proteins selected from matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8) in a saliva sample of the human patient.

[0125] Typically, the concentration of the protein in the sample is used to assess whether the patient suffers from periodontitis. Optionally, the method of this aspect includes a further step of treating the patient's periodontitis. The optional treatment step may include applying a known therapeutic agent or a dental procedure, or a combination of a therapeutic agent and a dental procedure. Known therapeutic agents include applying an antimicrobial agent-containing agent, such as a mouthwash, a chip, a gel or a microsphere. A typical antimicrobial agent for treating periodontitis is chlorhexidine. Other therapeutic agents include antibiotics, typically oral antibiotics, and enzyme inhibitors, such as doxycycline. Known non-surgical treatment procedures include scaling and root planing (SRP). Known surgical treatments include surgical pocket repositioning, flap surgery, gum grafts or bone grafts, which are typically specifically used for severe periodontitis and are not typically used for treating gingivitis.

[0126] The present invention also provides a method for detecting at least two proteins selected from matrix metalloproteinase-8 (MMP-8), matrix metalloproteinase-9 (MMP-9), pyruvate kinase (PK) and S100 calcium binding protein A8 (S100A8) in a human patient, comprising:

[0127] (a) obtaining a saliva sample from a human patient; and

[0128] (b) detecting the presence or absence of the protein in the sample by contacting the sample with one or more detection agents for binding to the protein, and detecting binding between each protein and the one or more detection agents.

[0129] The invention will be further illustrated with reference to the following non-limiting examples.

[0130] Example

[0131] A clinical study was conducted on 153 subjects, including:

[0132] 39 people have healthy gums (H)

[0133] 35 people were diagnosed with gingivitis (G)

[0134] 41 people were diagnosed with mild periodontitis (MP)

[0135] Thirty-eight subjects were diagnosed with advanced periodontitis (AP).

[0136] Receiver-Operator-Characteristic Area-Under-the-Curve values ​​of >0.9 were obtained using the biomarker panel of the invention containing up to 4 protein biomarkers.

[0137] Area under the ROC (Receiver-Operator-Characteristic) curve (AUC) values ​​were obtained.The performance of various biomarker combinations was evaluated by logistic regression using leave-one-out cross validation (LOOCV), resulting in preferred biomarker combinations as described herein.

[0138] In statistics, the receiver operating characteristic curve or ROC curve is a performance curve graph of a binary classifier system when its discrimination threshold is changed. The curve is created by plotting the true positive rate (TPR) against the false positive rate (FPR) at various threshold settings. The true positive rate is also called detection sensitivity, recall or probability in machine learning. The false positive rate is also called the probability of false detection or false alarm, and can be calculated as (1-specificity). Therefore, the ROC curve is the sensitivity as a function of false detection. Generally, if both the probability distributions for detection and false alarm are known, the ROC curve can be generated by plotting the value of the cumulative distribution function of the probability of detection (the area under the probability distribution from negative infinity to the discrimination threshold) on the y-axis for each value of the threshold, and the value of the cumulative distribution function of the probability of false alarm on the x-axis. The accuracy of the test depends on the degree to which the test divides the group being tested into groups with or without the disease in question. The accuracy is measured by the area under the ROC curve. An area of ​​1 represents a perfect test; an area of ​​0.5 represents a worthless test. The guidance for classifying the accuracy of diagnostic tests is the traditional academic point system:

[0139] ——0.90-1=Excellent (A)

[0140] ——0.80-0.90=Good (B)

[0141] ——0.70-0.80=Normal (C)

[0142] ——0.60-0.70=difference (D)

[0143] ——0.50-0.60=Failure (F)

[0144] Based on the above, in the results of the above clinical studies, it is believed that a ROC AUC value greater than 0.75 represents an ideal accuracy for providing a diagnostic test.

[0145] The protein biomarkers explored in this study were:

[0146] MMP8

[0147] MMP9

[0148] IL-1β

[0149] ·HGF

[0150] Free light chain (FLC) κ

[0151] Free light chain (FLC) λ

[0152] ·A1AGP

[0153] Hb-β

[0154] Hb-δ

[0155] Keratin 4

[0156] ·Inhibitory proteins

[0157] Pyruvate kinase

[0158] ·S100A8

[0159] ·S100A9

[0160] Furthermore, we considered them as additional predictors κ+λ, κ-λ, κ / λ in the adopted logistic regression.

[0161] Additionally, we included age as a predictor.

[0162] This yields a total of 4204 possible non-redundant groups with up to 4 protein biomarkers (groups with only age are not considered). Non-redundant here means that groups including, for example, κ+λ and κ-λ as predictors are not considered, as in logistic regression, non-redundant gives the same results as the corresponding group including κ and λ as predictors.

[0163] Note that, given the above predictors, not restricting the number of protein markers in the groups yields 98,302 possible non-redundant groups (not considering groups with only age).

[0164] In the study, 1972 groups with a maximum of 4 protein markers were found, yielding AUC LOOCV > 0.9.

[0165] In these groups:

[0166] 4 groups had one protein marker (MMP8 or MMP9, both optionally plus age)

[0167] 59 groups had two protein markers

[0168] 368 groups had three protein markers

[0169] 1541 groups with four protein markers

[0170] As can be seen, only MMP-8 and MMP-9 (plus possible age) alone yielded an AUC > 0.9, otherwise at least two marker panels were required to obtain an AUC > 0.9.

[0171] Figure 2 The relationship between the number of groups and the required performance, expressed as minimum AUC LOOCV, is shown.

[0172] The highest performing ~150 panels with up to four protein biomarkers with AUC > ~0.97 had at least two markers from MMP8, MMP9, pyruvate kinase and S100A8. Thus, according to the present invention, biomarker combinations comprising two, three or four of MMP8, MMP9, pyruvate kinase and S100A8 are preferred.

[0173] Note that the AUC LOOCV obtained using the single marker panels MMP8 or MMP9 (optionally plus age) ranged from 0.94 to 0.97. In this regard, only the highest performing panels with AUC>0.97 may be preferred.

[0174] Of these best performing groups (AUC > 0.97), 4 groups had 2 markers, 29 groups had 3 markers, and the remainder had 4 markers. The 4 groups with only 2 markers were:

[0175] MMP8+MMP9

[0176] MMP8+pyruvate kinase

[0177] MMP8+S100A8

[0178] MMP9+pyruvate kinase.

[0179] Note that these highest performing groups actually have at least one of MMP8 and MMP9. These four dual marker groups are preferred embodiments of the present invention. The top 25 performing groups with biomarkers with at most 4 proteins having AUC>0.97 are provided in Table 1 below:

[0180]

[0181] Table 1

[0182] Each of the protein biomarker combinations in the table is highlighted as a preferred combination of the present invention. Age may or may not be included as an additional biomarker.

[0183] While the invention has been illustrated and described in detail in the drawings and foregoing description, such illustration and description are to be considered illustrative or exemplary and not restrictive; the invention is not limited to the disclosed embodiments.

[0184] For example, different units may contain detection agents for different biomarkers. Alternatively, conveniently, the kit of the invention may include a fixed detection agent set for the protein biomarkers used in most embodiments, such as MMP-8, MMP-9, PK or S100-A8, and optionally a flexible module, including detection agents for other biomarkers, such as IL-1β, HGF, FLCκ, FLCλ, A1AGP, Hb-β, Hb-δ, keratin 4, inhibitor protein and / or S100A9.

[0185] In the process of practicing the claimed invention, other variations of the disclosed embodiments can be understood and implemented by those skilled in the art by studying the drawings, the disclosure and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality. The fact that certain features of the invention are recited in mutually different dependent claims does not indicate that a combination of these features cannot be used to advantage. Any reference signs in the claims should not be construed as limiting their scope.

[0186] In summary, we disclose here an in vitro method for assessing whether a human patient suffers from periodontitis. The method is based on the insight of determining biomarker proteins. Therefore, in a saliva sample from a patient, the concentration of the protein described herein is measured. Based on the measured concentration, a value reflecting the combined concentration of the protein is determined. The above value is compared with a threshold value, which reflects the combined concentration associated with periodontitis in the same manner. This comparison allows an assessment of whether the test value indicates that the patient suffers from periodontitis. Therefore, in general, a combined concentration reflected by the test value is lower than the combined concentration reflected by the threshold value, indicating that the patient does not suffer from periodontitis, and a combined concentration reflected by the test value is equal to or higher than the combined concentration reflected by the threshold value, indicating that the patient suffers from periodontitis.

Claims

1. A system for assessing whether a human patient suffers from periodontitis, the system comprising: - a detection device capable of and suitable for detecting the proteins of matrix metalloproteinase-8 (MMP-8), pyruvate kinase and S100 calcium binding protein A8 (S100A8) in a saliva sample of said human patient; - a processor capable and adapted to determine, from the determined concentration of the protein, an indication that the patient suffers from periodontitis.

2. The system of claim 1, further comprising a container for receiving an oral fluid sample, the container comprising the detection device.

3. The system according to claim 1 or 2, further comprising: - a user interface for presenting the indication to a user; and - a data connection between the processor and the user interface for transmitting the indication from the processor to the user interface.

4. The system according to claim 1 or 2, wherein: The processor is activated via an Internet-based application.

5. The system according to claim 3, wherein: The user interface is capable of inputting information regarding the age of the human patient, and the processor is capable of and adapted to determine an indication that the patient suffers from periodontitis based on the determined concentration.

6. A kit for detecting at least three biomarkers for periodontitis in a saliva sample of a human patient, the kit comprising detection agents for detecting proteins of matrix metalloproteinase-8 (MMP-8), pyruvate kinase, and S100 calcium binding protein A8 (S100A8).

7. The kit according to claim 6, wherein The detection reagents include a first detection reagent for detecting MMP-8, a second detection reagent for detecting pyruvate kinase, and a third detection reagent for detecting S100A8.

8. The kit according to claim 6, wherein The detection agent is contained on a solid support.

9. The kit according to claim 6 or 7, wherein The detection reagents consist of a first detection reagent for detecting MMP-8, a second detection reagent for detecting pyruvate kinase, and a third detection reagent for detecting S100A8.

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