Method for diagnosis of microbiota dysbiosis by detection of glycoprotein 2 (GP2) in stool

Abstract

The invention relates to an in vitro method for the diagnosis of a microbiota dysbiosis in a subject by detection of Glycoprotein 2 (GP2). In embodiments, in the invention relates to an in vitro method comprising providing a stool sample of a subject, providing a GP2 binding reagent, contacting said sample with said binding reagent, thereby forming a complex comprising GP2 from said sample with said GP2 binding reagent, and determining a level of GP2 in said sample, wherein the level of GP2 is indicative of microbiota dysbiosis of the subject. The present invention further relates to a kit and use thereof for the diagnosis of a microbiota dysbiosis in a subject by detection of Glycoprotein 2 (GP2) in stool.

Description

[0001] METHOD FOR DIAGNOSIS OF MICROBIOTA DYSBIOSIS BY DETECTION OF GLYCOPROTEIN 2 (GP2) IN STOOL

[0002] DESCRIPTION

[0003] The invention is in the field of molecular biology, diagnostics and microbiology, in particular using biomarkers to identify microbiota dysbiosis.

[0004] The invention relates to an in vitro method for the diagnosis of a microbiota dysbiosis in a subject by detection of Glycoprotein 2 (GP2). In particular, the in vitro method comprises providing a stool sample of the subject, providing a GP2 binding reagent, contacting said sample with said binding reagent, thereby forming a complex comprising GP2 from said sample with said GP2 binding reagent, and determining a level of GP2 in said sample, wherein the level of GP2 is indicative of microbiota dysbiosis of the subject.

[0005] The present invention further relates to use of a GP2 binding reagent for detecting Glycoprotein 2 (GP2) in stool, in an in vitro method for the diagnosis of a microbiota dysbiosis in a subject.

[0006] The present invention further relates to a kit for the diagnosis of a microbiota dysbiosis in a subject by detection of Glycoprotein 2 (GP2) in stool. In particular, the kit comprises a GP2 binding reagent, preferably with a solid surface for immobilization of said reagent, or preferably a GP2 binding reagent immobilized to a solid surface, a labelled secondary affinity reagent directed to GP2, and preferably means for detecting the signal emitted from said label, and reference data corresponding to GP2 levels indicative of a microbiota dysbiosis, preferably additionally reference data indicative of a subject having and / or developing systemic inflammation. Said reference data can be stored on a computer readable medium and / or employed in the form of computer executable code configured for comparing the determined levels of GP2 to the reference data, and optionally a sample collection device suitable for obtaining a stool sample.

[0007] BACKGROUND OF THE INVENTION

[0008] Gut bacteria are not passive bystanders but carry out important metabolic functions and their interplay with antimicrobial components of the host's immune system is crucial for the maintenance of health. Pathological alterations of the gut microbiome, so-called dysbiosis, have been implicated in the development and progression of various diseases [1], Several determining factors that shape or affect the gut microbiome composition have been described so far, but many more variables influencing the gut microbiota variation remain unknown [2, 3],

[0009] Recently the exocrine pancreas has been identified as one of the most important host factors which influence the gut microbiota composition in the general population [4, 5], A preserved exocrine pancreatic function not only supports a healthy gut microbiome composition but also predicts increased microbiome stability in the future [6], Still, the correlation of these observations has not been completely understood. On the one hand, loss of exocrine pancreatic function may change the nutritional substrate composition in the large intestines and select for specific bacteria according to their primary energy source [4, 7], On the other hand, secretory proteins from the pancreatic acinar cell, like microbiome-sensing pancreatic glycoprotein 2 (GP2), have been described to play an important role in the innate immune response against different commensal bacteria or opportunistic pathogens like Escherichia (E.) coli and the associated potential loss of tolerance [8-10],

[0010] In addition, expression of GP2 has also been detected at the apical plasma membrane of small intestinal M cells and presumably colonic enteroendocrine L cells [8, 11], In inflammatory bowel and autoimmune liver diseases, GP2 appears to be a potential autoantigenic target related to severity and tumourigenesis [12, 13], The loss of tolerance to GP2 in form of GP2 autoantibodies appears to be a stratification factor of Grohns’ disease and seems related to changes of the gut microbiota composition [14-16], Patients suffering from IBD show higher fecal GP2 levels, whereas GP2 deficient colitis mice exhibit a phenotype characterized by increased intestinal inflammation and epithelial attachment of E. coli

[0019] , Furthermore, in primary sclerosing cholangitis, an autoimmune liver disease associated with a specific change of the gut microbiota, the occurrence of GP2 IgA is a predictor of disease severity and cholangiocarcinogenesis [17, 18],

[0011] However, in the general population without manifest gastrointestinal disease, the role and importance of GP2 is less clear. Furthermore, clinicians are seeking novel means for determining the presence or absence of microbiota dysfunction or dysbiosis, without the complications of directly analyzing commensal or other bacteria of the human microbiome, which is often complex and requires time intensive laboratory techniques.

[0012] US2019 / 216861 A1 discloses a method for treating Clostridium difficile infections, which involves administering a composition containing at least three specific bacterial strains that are typically reduced in cases of intestinal microbiota dysbiosis. Additionally, US2019 / 216861 A1 describes using various biomarkers, including free amino acids and short-chain fatty acids, extracted from stool samples for diagnosing microbial dysbiosis.

[0013] Debyser Griet et al. disclose fecal metaproteomics to analyze the composition of host and microbial proteins in the gastrointestinal tract. Differences in microbial diversity and protein abundance were identified by examining stool samples from children with cystic fibrosis and their unaffected siblings. While GP2 is briefly mentioned, it is not considered a determining factor in the analysis. Furthermore, GP2 was not detectable in patients affected by microbial dysbiosis, and no accurate measurement of GP2 concentration levels was performed.

[0014] EP3299818A discloses an in vitro method for the diagnosis of acute pancreatitis (AP) by detection of the protein glycoprotein 2 isoform alpha (GP2a).

[0015] Kurashima Yosuke et al. investigate the biological function of GP2 in the intestine and demonstrates that luminal GP2, originating from pancreatic acinar cells and induced by TNF during colitis, binds to commensal E. coli, thereby preventing its adhesion to and penetration of the intestinal epithelium. Furthermore, Kurashima Yosuke et al. reveal that both the absence and presence of GP2 in the colon are associated with variations in the population of different bacterial species. However, while the role of GP2 in modulating bacterial interactions in the gut is explored, it does not suggest the use of GP2 as a biomarker for diagnosing or treating microbial dysbiosis.

[0016] Thus, none of the prior art suggests a solution for determining the presence or absence of microbiota dysfunction or dysbiosis without directly analyzing the human microbiota itself. The prior art disclosures, while addressing aspects of microbiota composition and function, do not propose a method or biomarker, such as GP2, that enables the assessment of microbial dysbiosis.

[0017] SUMMARY OF THE INVENTION

[0018] In light of the prior art the technical problem underlying the present invention is to provide alternative and / or improved means for the diagnosis and / or evaluation of microbiota dysbiosis. Another problem underlying the present invention is to provide alternative and / or improved means for diagnosis and / or evaluation of systemic inflammation. Other problems underlying the invention include providing means for determining the presence or absence of microbiota dysfunction or dysbiosis, without directly analyzing the human microbiota.

[0019] The problems are solved by the features of the independent claims. Preferred embodiments of the present invention are provided by dependent claims.

[0020] The invention therefore relates to an in vitro method for the diagnosis of a microbiota dysbiosis in a subject by detection of Glycoprotein 2 (GP2). In embodiments, the method comprises: providing a stool sample of the subject, providing a GP2 binding reagent, contacting said sample with said binding reagent, thereby forming a complex comprising GP2 from said sample with said GP2 binding reagent, and determining a level of GP2 in said sample, wherein the level of GP2 is indicative of microbiota dysbiosis of the subject.

[0021] The invention further relates to a kit for the diagnosis of a microbiota dysbiosis in a subject by detection of Glycoprotein 2 (GP2) in stool. In embodiments, the kit comprises: a GP2 binding reagent, preferably with a solid surface for immobilization of said reagent, or preferably a GP2 binding reagent immobilized to a solid surface, a labelled secondary affinity reagent directed to GP2, and preferably means for detecting the signal emitted from said label, and reference data corresponding to GP2 levels indicative of a microbiota dysbiosis. In embodiments, the reference data comprises additionally reference data indicative of a subject having and / or developing systemic inflammation, wherein said reference data is stored on a computer readable medium and / or employed in the form of computer executable code configured for comparing the determined levels of GP2 to the reference data, and optionally, the kit comprises a sample collection device suitable for obtaining or holding a stool sample.

[0022] The various aspects of the invention are unified by, benefit from, are based on and / or are linked by the common and surprising finding of the correlation between fecal glycoprotein 2 and gut microbiota dysbiosis. The relationship between GP2 and the human gut microbiota may represent an important factor in clinical practice regarding gut microbiota dysbiosis and gastrointestinal inflammation. To the best knowledge of the inventors, there has been no suggestion in the art regarding diagnosis of microbiota dysbiosis and systemic inflammation by detecting fecal GP2. In one aspect, the present invention relates to an in vitro method for the diagnosis of a microbiota dysbiosis in a subject by detection of Glycoprotein 2 (GP2), comprising:

[0023] Providing a stool sample of the subject,

[0024] Providing a GP2 binding reagent,

[0025] Contacting said sample with said binding reagent, thereby forming a complex comprising GP2 from said sample with said GP2 binding reagent, and

[0026] Determining a level of GP2 in said sample, wherein the level of GP2 is indicative of microbiota dysbiosis of the subject.

[0027] The main source of fecal GP2 is believed to be its secretion by zymogen granules in pancreatic acinar cells

[0031] , Another origin by expression in the follicle-associated epithelium of small intestinal Peyer's patches and colonic L cells has also been reported [8, 11], Elevated expression of GP2 has been found in both the exocrine pancreas and the intestinal mucosa in association with inflammatory processes in patients with Crohn’s disease or Crohn’s-like inflammation [9, 11 , 19], Without being bound by the theory, this may result from a tumour necrosis factor (TNF)- triggered GP2 synthesis and elevated secretion from the exocrine pancreas

[0019] , Alternatively, it could indicate GP2 secretion by intestinal sources into the gut lumen. Lower fecal GP2 levels were measured in individuals with a preserved exocrine pancreatic function. GP2 is therefore an established marker for inflammatory processes in the intestine, for example in various forms of IBD. However, it is a surprising finding that fecal GP2 levels correlate with changes in the gut microbiome composition, in particular, that higher fecal GP2 levels are associated with gut microbiome dysbiosis. As shown in more detail in the examples below, altered fecal GP2 levels associate with microbial variation. A total of 33 and 41 bacterial taxa were detected with significant associations with fecal GP2 in linear and binary regression models, respectively. The use of GP2 determination (detection, measurement, quantification) provides diagnostic and / or prognostic information on the status of an individuals’ microbiome composition and health. GP2 levels associate with microbiota dysbiosis, enabling the detection of GP2 to be employed in a reliable and straightforward molecular approach, based on the detection of one or a few protein molecules in a stool sample, to provide information on overall health and status of a human microbiome.

[0028] In embodiments, positive associations are found, for example, with Clostridium XlVa, Collinsella or the opportunistic pathogens Haemophilus and Streptococcus. In a recent publication, the presence of Clostridium XlVa in the gut microbiome of (still) healthy individuals associated with fatty liver disease or diabetes mellitus over 5 years with a possible causal involvement [6], Detection of Collinsella has been linked to diabetes mellitus, obesity and precedes the development of fatty liver disease [6, 33, 34], The assessment of microbiome enabled by GP2 therefore has follow-on relevance and thus prognostic potential in multiple diseases that associate with microbial dysbiosis.

[0029] In embodiments, a reduced presence of the opportunistic Gram-negative pathogens Escherichia / Shigella and Citrobacter, is found in individuals with elevated fecal GP2 levels. In embodiments, elevated GP2 levels inversely correlate with the presence of gut microbial pathways necessary for short-chain fatty acids (SOFA) biosynthesis, such as Ruminococcaceae, Butyrivibrio, Faecalibacterium, Lachnospiraceae, or Roseburia.

[0030] In embodiments, GP2 levels are positively correlated with one or more bacteria selected from Turicibacter, Erysipelotrichaceae, Phascolarctobacterium, Mitsuokella, Allisonella, Sutterella, Parasutterella, Haemophilus, Collinsella, Slackia, Prevotella, Streptococcus, Clostridium sensu stricto, Roseburia, Clostridium XlVa, Fusicatenibacter, Dorea, Lachnospiraceae, Romboutsia, Faecalibacterium and / or Ruminococcus.

[0031] As demonstrated in figure 2, the presence of these bacteria positively correlates with GP2 levels, albeit with different correlation coefficients indicating the strength of the relationship between said GP2 levels and said bacteria.

[0032] In embodiments, the correlation coefficient can be over 0, such as 0.1 , 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8 or 0.9. In one embodiment, GP2 levels are positively correlated with Mitsuokella with a correlation coefficient over 0.3. Therefore, an overrepresentation of Mitsuokella can be determined by elevated levels of fecal GP2, thereby indicating a microbiota dysbiosis.

[0033] In embodiments, the GP2 levels are positively correlated with one or more bacteria selected from Haemophilus, Collinsella, Streptococcus and / or Clostridium XlVa.

[0034] The presence of Clostridium XlVa in the gut microbiome of (still) healthy individuals associated with fatty liver disease or diabetes mellitus over 5 years with a possible causal involvement. Detection of Collinsella has been linked to diabetes mellitus, obesity and precedes the development of fatty liver disease. Advantageously, based on such correlations, GP2 can be used to predict the possibility or risk of acquiring a fatty liver disease or diabetes mellitus in a subject.

[0035] In embodiments, GP2 levels are inversely correlated with one or more bacteria selected from Clostridium IV, Oscillibacter, Anaerotruncus, Pseudoflavonifractor, Ruminococcaceae, Victivallis, Oxalobacter, Akkermansia, Odoribacter, Butyricimonas, Alistipes and / or Catabacter.

[0036] As demonstrated in Figure 2, these bacteria are inversely correlated with GP2 levels exhibiting different correlation coefficient indicating the strength of the relationship.

[0037] In embodiments, GP2 levels indicates an increased presence (above a threshold or an average population level) of one or more bacteria selected from Haemophilus, Actinomyces, Gordonibacter, Streptococcus, Clostridium sensu stricto, Dorea, Anaerostipes, Romboutsia, Turicibacter, Clostridium XVI II and / or Veillonella.

[0038] In embodiments, GP2 levels indicate a reduced presence (below a threshold or an average population level) of one or more bacteria selected from Victivallis, Oxalobacter, Sutterella, Desulfovibrio, Bilophila, Desulfovibrionaceae, Escherichia / Shigella, Citrobacter, Coraliomargarita, Akkermansia, Olsenella, Coriobacteriaceae, Barnesiella, Coprobacter, Butyricimonas, Porphyromonadaceae, Prevotella, Paraprevotella, Alloprevotella, Rikenellaceae, Catabacter, Anaerovorax, Mogibacterium, Butyrivibrio, Eisenbergiella, Peptococcus, Ethanoligenens, Sporobacter, Anaerofilum and / or Coprobacillus. In embodiments, GP2 levels are inversely correlated with the presence and / or amount of Escherichia / Shigella and / or Citrobacter.

[0039] Escherichia / Shigella and Citrobacter are opportunistic Gram-negative pathogens. Without being bound by the theory, one reason for the inverse correlation is that GP2 is an intestinal M-cells transcytotic receptor specific of type-l-piliated bacteria, which participates in the mucosal immune response towards these bacteria. This finding enables evaluation of whether a subject is susceptible to be infected by these opportunistic Gram-negative pathogens.

[0040] In embodiments, elevated GP2 levels indicate reduced amounts of bacteria involved in short chain fatty acid (SOFA) synthesis. In other embodiments, elevated GP2 levels indicate reduced SOFA synthesis. In embodiments, reduced SOFA synthesis can be detrimental to human health.

[0041] Advantageously, an elevated GP2 level (above a threshold or an average population level) enables indication of impaired and / or pathogenic biosynthesis of small chain fatty acids and / or lactic acid which are relevant to prevent systemic inflammation.

[0042] In one embodiment, an elevated GP2 level (above a threshold value or an average population level, such as above an average GP2 level of a healthy human population) enables indication of a microbial dysbiosis and systemic inflammation.

[0043] In embodiments, GP2 levels inversely correlate with the microbial pathway of pyruvate fermentation to acetone.

[0044] In embodiments, GP2 levels inversely correlate with the microbial pathway of heterolactic fermentation.

[0045] In embodiments, GP2 levels inversely correlate with the microbial pathway of Bifidobacterium shunt.

[0046] In embodiments, GP2 levels inversely correlate with the microbial pathway of succinate fermentation to butanoate.

[0047] In embodiments, GP2 levels inversely correlate with the microbial pathway of acetyl-CoA fermentation to butanoate II.

[0048] In embodiments, GP2 levels inversely correlate with the microbial pathway of pyruvate fermentation to acetate and lactate II.

[0049] In embodiments, GP2 levels inversely correlate with the microbial pathway of homolactic fermentation.

[0050] In embodiments, GP2 levels inversely correlate with the microbial pathway of 4-aminobutanoate degradation V.

[0051] In embodiments, GP2 levels inversely correlate with the microbial pathway of pyruvate fermentation to isobutanol.

[0052] In embodiments, GP2 levels inversely correlate with the microbial pathway of acetylene degradation. In embodiments, GP2 levels inversely correlate with the microbial pathway of L-1 ,2-propanediol degradation.

[0053] In embodiment, an elevated GP2 level (for example above healthy subjects or population averages) indicates the absence of one or more microbial taxa.

[0054] In embodiments, an elevated GP2 level (for example above healthy subjects or population averages) indicates a reduced gut microbial alpha diversity.

[0055] In embodiments, an elevated GP2 level (for example above healthy subjects or population averages) inversely correlates with micro diversity scores, such as Simpson diversity number (N2), Shannon diversity index (H), Chad estimator and species richness (NO).

[0056] In a further aspect, the present invention relates to an in vitro method for the risk stratification of systemic inflammation, wherein a GP2 level below a threshold level is indicative of the absence of or a low risk of having and / or developing systemic inflammation, or a GP2 level equal to or above a threshold level is indicative of a high risk of having and / or developing systemic inflammation.

[0057] Surprisingly, high fecal GP2 levels were associated with increased systemic inflammation as indicated by high hs-CRP (C-reactive protein) levels (Table. 1). Without being bound by the theory, inflammatory processes lead to raised TNF levels which could trigger an elevated pancreatic secretion of GP2. Further, high fecal GP2 levels correlate with a marked reduction in a broad range of SCFA-producing bacteria. Therefore, the present invention enables determination or diagnosis of an unhealthy metabolic phenotype with increased systemic inflammation.

[0058] In embodiments, if the level of GP2 is indicative of a microbiota dysbiosis, the method may additionally comprise indicating a suitable treatment and / or administering said treatment, said treatment selected from one or more of administration of probiotics, probiotics comprising fructooligosaccharides (FOS), galacto-oliogosaccharides (GOS) and trans-galacto-oligosacchrides (TOS), diet modification, fecal microbiota transplantation (FMT), or antibiotic therapy.

[0059] In embodiments, if the subject has or is suspected of having a microbiota dysbiosis, the method may additionally comprise indicating a suitable treatment and / or administering a treatment, said treatment selected from one or more of administration of probiotics, probiotics comprising fructooligosaccharides (FOS), galacto-oliogosaccharides (GOS) and trans-galacto-oligosacchrides (TOS), diet modification, fecal microbiota transplantation (FMT), or antibiotic therapy.

[0060] In embodiments, if the level of GP2 is indicative of a microbiota dysbiosis, the method additionally comprises indicating administration of and / or administering one or more bacteria selected from the group consisting of Clostridium IV, Oscillibcacter, Anaerotruncus, Pseudoflavonifractor, Ruminococcaceae, Victivallis, Oxalobacter, Akkermansia, Odoribacter, Butyricimonas, Alistipes and / or Catabacter, Victivallis, Oxalobacter, Sutterella, Desulfovibrio, Bilophila, Desulfovibrionaceae, Escherichia / Shigella, Citrobacter, Coraliomargarita, Akkermansia, Olsenella, Coriobacteriaceae, Bamesiella, Coprobacter, Butyricimonas, Porphyromonadaceae, Prevotella, Paraprevotella, Alloprevotella, Rikenellaceae, Catabacter, Anaerovorax, Mogibacterium, Butyrivibrio, Eisenbergiella, Peptococcus, Ethanoligenens, Sporobacter, Anaerofilum and / or Coprobacillus, Escherichia / Shigella and / or Citrobacter.

[0061] In embodiments, if the level of GP2 is indicative of a microbiota dysbiosis, the method additionally comprises indicating administration of and / or administering one or microbiota selected from the group consisting of Lactococcus, Lactobacillus, Bifidobacteria, Saccharomyces orapathogenic Escherichia coli or Enterococcus.

[0062] In embodiments, if the subject has or suspect of having a microbiota dysbiosis, the method additionally comprises indicating administration of and / or administering one or microbiota selected from the group consisting of Clostridium IV, Oscillibcacter, Anaerotruncus, Pseudoflavonifractor, Ruminococcaceae, Victivallis, Oxalobacter, Akkermansia, Odoribacter, Butyricimonas, Alistipes and / or Catabacter, Victivallis, Oxalobacter, Sutterella, De sulfovibrio, Bilophila, Desulfovibrionaceae, Escherichia / Shigella, Citrobacter, Coraliomargarita, Akkermansia, Olsenella, Coriobacteriaceae, Barnesiella, Coprobacter, Butyricimonas, Porphyromonadaceae, Prevotella, Paraprevotella, Alloprevotella, Rikenellaceae, Catabacter, Anaerovorax, Mogibacterium, Butyrivibrio, Eisenbergiella, Peptococcus, Ethanoligenens, Sporobacter, Anaerofilum and / or Coprobacillus, Escherichia / Shigella and / or Citrobacter.

[0063] In embodiments, if the subject has or suspect of having a microbiota dysbiosis, the method additionally comprises indicating administration of and / or administering one or microbiota selected from the group consisting of Lactococcus, Lactobacillus, Bifidobacteria, Saccharomyces orapathogenic Escherichia coli or Enterococcus.

[0064] With respect to the aspects and embodiments described herein, one or more cut-off or threshold levels may be employed in order to determine whether any given GP2 levels is indicative of any given indication and / or corresponding treatment.

[0065] In embodiments, the threshold level is 200 ± 20%, 300, 400, 500, 600, 700, 800, 900, 1000, 1200, 1400, 1600, 1800, 2000, 2200, 2400, 2600, 2800, 3000, 3200, 3400, 3600, 3800, or 4000 ± 20% ng / g. The threshold level may also fall within a range defined by any given two values of those provided above. In embodiments of the invention, deviations from these possible cut-off values are also claimed, such as deviations of ± 30%, 29%, 28%, 27%, 26%, 25%, 24%, 23%, 22%, 21 %, 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 1 1 %, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2% or ± 1 %, which apply to any given threshold disclosed herein.

[0066] The cut-off values disclosed herein refer preferably to measurements of the protein level of GP2 or fragments thereof in a stool sample, or sample prepared from a stool sample, by means of the detection methods described in the examples below. By way of example, for determination of GP2 levels in stool, native fecal samples are analyzed using the Pancreatitis GP2 ELISA (GA Generic Assays, Berlin, Germany) according to the manufacturer's protocol. The assay detects the larger isoform of GP2

[0022] , OD-Measurements are carried out using a spectrophotometer (for example a SpectraMax 190 from Molecular Devices) and GP2 values are calculated as ng GP2 / mg stool, or ng GP2 / g stool, from an internal GP2 standard curve. Accordingly, the values disclosed herein may vary to some extent depending on the detection / measurement method employed, and the specific values disclosed herein are intended to also read on the corresponding values determined by other methods. As shown in the examples below, the study population was randomly selected from the general population of North-East Germany, as the study aimed to investigate the prevalence and characteristics of common diseases and their risk factors in this area. Median GP2 levels were 1 ,118.7 ng / g stool, whereby 215.4 was the first quartile and 3,659.1 was the third quartile.

[0067] In embodiments, the threshold level is equal to or above 215 ± 20% ng / g. This threshold identifies subjects with GP2 levels on the second to fourth quartiles.

[0068] In embodiments, the threshold level is equal to or above 1118 ± 20% ng / g. This threshold identifies subjects with GP2 levels above the median level in a healthy population, and / or in a general population without preselection for particular medical conditions.

[0069] In embodiments, the threshold level is equal to or above 3659 ± 20% ng / g. This threshold identifies subjects with GP2 levels on the fourth quartiles, this group represents the quarter of the population with relatively high GP2 levels. In embodiments, similar but diverging threshold levels may be employed, such as 3500, 3550, 3600, 3650, 3700, 3750 or 3800 ng / g , or any value within a range formed between any two said values.

[0070] In other embodiments, fecal GP2 levels of the lowest 20% of the population are below 124.4 ng / g ± 20%.

[0071] In other embodiments, fecal GP2 levels of the second 20% of the population are between 124.4 ng / g ± 20% and 686.8 ng / g± 20%.

[0072] In other embodiments, fecal GP2 levels of the third 20% of the population are between 686.9 ng / g ± 20% and 1853.7 ng / g± 20%.

[0073] In other embodiments, fecal GP2 levels of the fourth 20% of the population are between 1853.8 ± 20% ng / g and 4605.6 ± 20% ng / g.

[0074] In other embodiments, fecal GP2 levels of the highest 20% of the population are above 4605.7 ± 20% ng / g.

[0075] In embodiments of the invention, the cut-off value of GP2 may define a transition from a low to a high risk, and may be any value disclosed herein, or any value in a range defined by values disclosed herein. Any value disclosed with ± 20% may also be defined by any other variation according to the disclosure herein, for example as above, such as between ± 30% to ± 1%.

[0076] In embodiments, the method as used herein comprises additionally the diagnosis, prognosis and / or risk stratification of a subject having and / or developing systemic inflammation, such as systemic inflammation associated with a gastrointestinal disorder, by detection of Glycoprotein 2 (GP2), wherein the level of GP2 is indicative of the subject having and / or developing systemic inflammation. Because the levels of GP2 correlates with certain bacterial strains or taxa, elevated or reduced GP2 levels in comparison to population averages may be used to indicate the presence or absence of a microbiota dysbiosis. Considering the study described in the Examples, using a random population, the GP2 values may be measured and an appropriate cut-off selected based on distribution of GP2 levels in the population. The correlations between GP2 and microbiota dysbiosis or other conditions such as systemic inflammation may therefore employed to identify said medical conditions, without having to fix exact cut-off levels. Nevertheless, a skilled person is capable for determining an appropriate cut-off using established means in the art.

[0077] By way of example, methods based on a ROC analysis can be used to determine statistically significant differences between two clinical patient groups. Receiver Operating Characteristic (ROC) curves measure the sorting efficiency of the model’s fitted probabilities to sort the response levels. ROC curves can also aid in setting criterion points in diagnostic tests. The higher the curve from the diagonal, the better the fit. If the logistic fit has more than two response levels, it produces a generalized ROC curve. In such a plot, there is a curve for each response level, which is the ROC curve of that level versus all other levels. Software capable of enabling this kind of analysis in order to establish suitable reference levels and cut-offs is available, for example JMP 12, JMP 13, 20 Statistical Discovery, from SAS.

[0078] In embodiments: a GP2 level below a threshold level is indicative of the absence of or a non-severe microbiota dysbiosis and / or the absence of or a low risk of having and / or developing systemic inflammation, or a GP2 level equal to or above a threshold level is indicative of the presence of or a severe microbiota dysbiosis and / or a high risk of having and / or developing systemic inflammation. wherein the threshold level is 3659.1 ng / g ± 20%.

[0079] According to the present invention, the term “indicate” in the context of “indicative of a microbiota dysbiosis”, or other medical condition or state, is intended as a measure of risk and / or likelihood. Preferably, the “indication” of the presence or absence of e.g., microbiota dysbiosis is intended as a risk assessment, and is typically not to be construed in a limiting fashion as to point definitively to the absolute presence or absence of said state. Keeping the above in mind, the determination of high and low levels of GP2 is however very reliable with respect to determining the presence or absence of a microbiota dysbiosis, such that the estimation of risk enables an appropriate action by a medical professional.

[0080] In embodiments, the GP2 detected is a Glycoprotein 2 isoform alpha (GP2a).

[0081] In embodiments, the GP2 detected is a Glycoprotein 2 isoform beta (GP2b).

[0082] In embodiments, detection of GP2 is via detecting isoform alpha (GP2a) protein, wherein Glycoprotein 2 isoform alpha (GP2a) comprises or consists of a protein: a) with an amino acid sequence according to SEQ ID NO 1 or 2, b) a truncated amino acid sequence according to SEQ ID NO 1 or 2, with no more than 50 amino acids lacking from the N and / or C terminus of the sequence, or c) an amino acid sequence of more than 80%, more than 85%, more than 90% or more preferably more than 95% sequence identity to a) or b). The isoforms of GP2 also relate to those of substantially the same amino acid sequence as those explicitly listed. This refers to one or more amino acid sequences that is similar, but not identical to, the amino acid sequence provided explicitly herein.

[0083] In a further embodiment of the invention as described herein, an affinity reagent specifically binds GP2a, wherein GP2a preferably comprises or consists of a protein a) with an amino acid sequence according to SEQ ID NO 1 or 2, b) a truncated amino acid sequence according to SEQ ID NO 1 or 2, with no more than 50 amino acids lacking from the N and / or C terminus of the sequence, or c) an amino acid sequence of more than 80%, more than 85%, more than 90% or more preferably more than 95% sequence identity to a) or b).

[0084] In embodiments, detection of GP2 is via detecting isoform beta (GP2b) protein, wherein Glycoprotein 2 isoform beta (GP2b) comprises or consists of a protein: a) with an amino acid sequence according to SEQ ID NO 3 or 4, b) a truncated amino acid sequence according to SEQ ID NO 3 or 4, with no more than 50 amino acids lacking from the N and / or C terminus of the sequence, or c) an amino acid sequence of more than 80%, more than 85%, more than 90% or more preferably more than 95% sequence identity to a) or b).

[0085] In other embodiments, an affinity reagent specifically binds Glycoprotein 2 isoform beta (GP2b), wherein GP2b preferably comprises or consists of a protein a) with an amino acid sequence according to SEQ ID NO 3 or 4, b) a truncated amino acid sequence according to SEQ ID NO 3 or 4, with no more than 50 amino acids lacking from the N and / or C terminus of the sequence, or c) an amino acid sequence of more than 80%, more than 85%, more than 90% or more preferably more than 95% sequence identity to a) or b).

[0086] In other embodiments, an affinity reagent binds GP2a and GP2b. In other embodiments, the affinity reagent specifically binds GP2a, with no binding or negligible binding to Glycoprotein 2 isoform beta (GP2b), preferably according to SEQ ID NO 3 or 4. In other embodiments, the affinity reagent specifically binds GP2b, with no binding or negligible binding to Glycoprotein 2 isoform alpha (GP2a), preferably according to SEQ ID NO 1 or 2.

[0087] Variation in length of the amino acid sequences and encoding nucleic acids as described herein is also encompassed by the present invention. A skilled person is capable of detecting amino acid sequence variants that are longer or shorter than the specific sequences of SEQ ID NO 1 to 4, which will still exhibit sufficient similarity to the natural forms in order to provide the diagnostic outcomes described herein. For example, shorter variants or fragments of the longer isoforms (SEQ ID NO 1 or 2) comprising 10, 20, 30, 40 or 50 amino acids less than the full-length form may also enable effective diagnostic outcomes, as described herein. For example, longer variants of the shorter isoforms (SEQ ID NO 3 or 4) comprising 10, 20, 30, 40 or 50 amino acids of GP2 sequence more than the natural length form may also enable effective diagnostic outcomes, as described herein.

[0088] In a further embodiment, the method as described herein is conducted as an Enzyme Linked Immunosorbent Assay (ELISA), wherein said affinity reagent is immobilized on a solid surface before contacting said sample. It is a great advantage of the method according to present invention that it can be carried out as an ELISA, which is a conventional and routine laboratory technique that can be carried out in almost every diagnostic laboratory. As the method can be conducted as an ELISA, complicated diagnostic procedures such as endoscopies or biopsy analysis can be avoided and thereby a greater target group of people is enabled to execute the method according to the present invention.

[0089] In one embodiment the method of the present invention is characterized in that the determination of GP2 concentration is carried out by a) capturing GP2 from the sample via a GP2 affinity reagent that is immobilized to a solid surface, b) treating said captured GP2 with a labeled secondary affinity reagent directed to GP2, c) detecting a signal emitted from said labeled secondary affinity reagent directed to GP2, and d) comparing the signal obtained from said labeled secondary affinity reagent with the signal from one or more control samples of pre-determined GP2 concentration.

[0090] In one embodiment the method of the present invention is characterized in that the determination of GP2a concentration is carried out by a) capturing GP2a from the sample via the GP2a affinity reagent that is immobilized to the solid surface, b) treating said captured GP2a with a labeled secondary affinity reagent directed to GP2, c) detecting a signal emitted from said labeled secondary affinity reagent directed to GP2, and d) comparing the signal obtained from said labeled secondary affinity reagent with the signal from one or more control samples of pre-determined GP2a concentration.

[0091] In one embodiment the method of the present invention is characterized in that the determination of GP2b concentration is carried out by a) capturing GP2b from the sample via the GP2b affinity reagent that is immobilized to the solid surface, b) treating said captured GP2b with a labeled secondary affinity reagent directed to GP2, c) detecting a signal emitted from said labeled secondary affinity reagent directed to GP2, and d) comparing the signal obtained from said labeled secondary affinity reagent with the signal from one or more control samples of pre-determined GP2b concentration.

[0092] It is a great advantage of the present invention that the concentration of GP2 in a sample can be carried out by comparing the signal emitted from the labeled secondary affinity reagent that has captured GP2 within the sample to the signal emitted from the said secondary affinity reagents from one or more control samples of pre-determined GP2 concentration. Such control samples can easily be generated at the time of performing the method by using recombinant GP2. This allows for determination of the GP2 concentration in a routine laboratory procedure that only requires standard laboratory equipment.

[0093] The fact that the affinity reagent that is specific to GP2 is immobilized allows the removal of all other sample components except GP2 from the surface coupled to the GP2 affinity reagent by washing the solid surface after capturing the GP2 molecules present in the sample. In the case of isoform specific detection, as there is no other GP2 than the isolated isoform present on the solid surface after washing away all other sample components, it is possible to use a secondary affinity reagent that is not specific to a GP2 isoform but just has to be able to recognize any labeled GP2 affinity reagent. Such affinity reagents are known in the art and are readily available, which is a great advantage for making the present invention widely available.

[0094] In a preferred embodiment of the present invention, said signal is preferably obtained from horseradish peroxidase conjugated to the secondary affinity reagent. Horseradish peroxidase (HRP) is used in biochemistry applications primarily for its ability to amplify a weak signal and increase detectability of a target molecule. Its presence is made visible by using a substrate that, when oxidized by HRP using hydrogen peroxide as the oxidizing agent, yields a characteristic change that is detectable by spectrophotometric methods. Numerous substrates for the horseradish peroxidase enzyme have been described and commercialized to exploit the desirable features of HRP. Horseradish peroxidase is also commonly used in techniques such as ELISA and Immunohistochemistry due to its monomeric nature and the ease with which it produces colored products. Horseradish peroxidase is ideal in many aspects for these applications because it is smaller, more stable, and less expensive than other popular alternatives. It also has a high turnover rate that allows generation of strong signals in a relatively short time span.

[0095] In one embodiment the invention additionally comprises informing the patient of the results of the diagnostic method described herein.

[0096] In a further aspect, the present invention relates to the use of a GP2 binding reagent for detecting Glycoprotein 2 (GP2) in stool, in an in vitro method for the diagnosis of a microbiota dysbiosis in a subject.

[0097] In a further aspect, the present invention relates to a kit for the diagnosis of a microbiota dysbiosis in a subject by detection of Glycoprotein 2 (GP2) in stool, comprising: an GP2 binding reagent, preferably with a solid surface for immobilization of said reagent, or preferably a GP2 binding reagent immobilized to a solid surface, a labelled secondary affinity reagent directed to GP2, and preferably means for detecting the signal emitted from said label, and reference data corresponding to GP2 levels indicative of a microbiota dysbiosis, preferably additionally reference data indicative of a subject having and / or developing systemic inflammation, wherein said reference data is stored on a computer readable medium and / or employed in the form of computer executable code configured for comparing the determined levels of GP2 to the reference data, and optionally a sample collection device suitable for obtaining a stool sample.

[0098] In embodiments, the reference data can be a list of overrepresented and / or underrepresented bacteria correlated with fecal GP2 levels. In embodiments, the reference data can be a dysbiosis index with respect to the correlation between fecal GP2 level and the bacteria population. In embodiments, the reference data can be a threshold level of fecal GP2 indicative of systemic inflammation.

[0099] The combination of a kit according to the present invention with a computer system appropriate for carrying out automated analysis of one or more samples has been motivated only by the novel and surprising finding of the present invention. The combination of the components of the kit and the computer system therefore is to be considered an unexpected development of the art. There exists no suggestion in the relevant literature that the provision of a system comprising said components should have been developed.

[0100] It is a great advantage of the computer system for automated analysis of one or more samples that it comprises components that are available in most laboratories carrying out in vitro methods of diagnosis. The one skilled in the art knows different embodiments of computer processing devices, plate readers and camera devices for detecting the signal of the labeled secondary affinity reagent directed to GP2.

[0101] Embodiments and features of the invention described with respect to the method for diagnosis of microbiota dysbiosis by detecting GP2 in a stool sample of a subject are considered to be disclosed with respect to each and every other aspect of the disclosure, such that features characterizing the method as used herein may be employed to characterized the use of fecal GP2 for diagnosis of microbiota dysbiosis and a kit as described therein, and vice-versa.

[0102] The various aspects of the invention are unified by, benefit from, are based on and / or are linked by the common and surprising finding of the correlation between fecal glycoprotein 2 and gut microbiota dysbiosis.

[0103] DETAILED DESCRIPTION OF THE INVENTION

[0104] All cited documents of the patent and non-patent literature are hereby incorporated by reference in their entirety.

[0105] The term “microbiota dysbiosis” shall mean alternations in gut microbiota composition and function. In preferred embodiments, dysbiosis is an alternation in gut microbiota that is detrimental to the health of a subject. The most typical features of dysbiosis are a decrease in the diversity of the microbiota, a loss of beneficial microbiota, or an overgrowth of harmful microbiota. The term “gut microbiota” includes all microorganisms, i.e., not only bacteria, but also fungi, protists, archaea, and viruses that reside in the gastrointestinal tract. All of them can be possible triggers of gut microbiota dysbiosis.

[0106] Dysbiosis of the gut microbiota has been associated with numerous adverse conditions, such as Clostridioides difficile (formerly designated Clostridium difficile') infection (GDI), metabolic syndrome, inflammatory bowel disease (IBD), colorectal cancer, chronic hepatitis, common variable immunodeficiency, and even schizophrenia. Dysbiosis has also been observed in nonintestinal microbial communities, such as those of the gums, oral mucosa and saliva, and scalp and forehead. The application of the term dysbiosis may include a change of a single species to the perturbation of entire microbial communities.

[0107] In embodiments, dysbiosis can be caused by host-specific factors such as genetic background, health status (infections, inflammation), lifestyle habits or environmental factors, such as diet (high sugar, low fibre), xenobiotics (antibiotics, drugs, food additives), and hygiene.

[0108] As used herein, the term “microbiota” includes bacteria, archaea, protists, fungi and viruses present in an ecological community of commensal, symbiotic and pathogenic microorganisms, as found in and on all multicellular organisms from plants to animals. Microbiota are crucial for immunologic, hormonal and metabolic homeostasis of their host. Different microbiota live on different parts of the body, prefer different foods, and perform different functions. There is an oral microbiota of the mouth, a microbiota of the skin that has many subcategories (the armpits, nose, feet, etc.), and a gut microbiota, among many others.

[0109] The term “microbiome” describes either the collective genomes of the microorganisms that reside in an environmental niche or the microorganisms themselves, including microbial structural elements, such as proteins / peptides, lipids, polysaccharides, nucleic acids, mobile genetic elements, or microbial metabolites such as, signaling molecules, toxins, and (an)organic molecules. The term “microbiota” and the term “microbiome” can be used herein interchangeably.

[0110] A “Dysbiosis index” is a measure to characterize diseases and adverse conditions, or predict treatment outcomes. Most dysbiosis indexes are based on comparison to a set of individuals or samples used as references. In embodiments, dysbiosis indexes may comprise, multiple, for example comprise five, categories based on one or more methodologies for assessing the microbiota, including large-scale bacterial marker profiling, relevant taxon-based methods, neighborhood classification, random forest prediction, and combined alpha-beta diversity (as indicated in Shangdong Wei et al. 2021 Determining Gut Microbial Dysbiosis: a Review of Applied Indexes for Assessment of Intestinal Microbiota Imbalances). The dysbiosis index can be applied for example as a reference data for the diagnosis. The skilled person can create his own dysbiosis indexes according to the correlation of the fecal GP2 level and bacteria.

[0111] The term “stool sample” is any sample comprising fecal matter, for example used for a stool test which is a medical diagnostic technique that involves the collection and analysis of fecal matter. Microbial analysis (culturing), microscopy and chemical tests are among the tests performed on stool samples. In the context of the present invention, fecal GP2 level refers to GP2 level detected from a stool sample.

[0112] In embodiments, the stool sample may be processed prior to analysis. In embodiments, the stool sample contacted with said GP2 binding reagent has been processed and made suitable for an immunoassay. Standard procedures may be employed, known to a skilled person. In embodiments, the sample is derived from a stool sample. In embodiments, the stool sample was obtained prior to the present method, and employed in the present method, which is exclusively an ex vivo or in vitro method. Sample collection can therefore in embodiments be carried out prior to the present method.

[0113] By way of non-limiting example, participants are provided a fecal collection tube. Fecal samples are collected by the study participants at home and brought to the study center individually or shipped by mail. For determination of GP2 levels in stool, native fecal samples are analyzed using the Pancreatitis GP2 ELISA (GA Generic Assays, Berlin, Germany) according to the manufacturer's protocol. The assay detects the larger isoform of GP2

[0022] , Briefly, 25mg of stool are homogenized in 1.25ml extraction buffer and centrifuged for 10min at 3.000g. 20pl of supernatant are subsequently analyzed in 96-well plates, which included GP2 standards as well as positive and negative controls. Final OD-Measurements are carried out in a spectrophotometer (for example a SpectraMax 190 from Molecular Devices) and GP2 values are calculated as [ng GP2 / mg stool] or [ng GP2 / g stool] from an internal GP2 standard curve.

[0114] The term “probiotics” shall mean live microorganisms that provide health benefits when consumed, generally by improving or restoring the gut microbiota. Non limiting examples are Lactococcus, Lactobacillus, Bifidobacteria, Saccharomyces or apathogenic Escherichia coli or Enterococcus.

[0115] The term “probiotics” shall mean compounds in food that foster growth or activity of beneficial microorganisms such as bacteria and fungi. The most common environment considered is the gastrointestinal tract, where probiotics can alter the composition of organisms in the gut microbiome.

[0116] The term “taxa” (singular taxon) shall mean is a group of one or more populations of an organism or organisms seen by taxonomists to form a unit.

[0117] The term "diagnosis" in the context of the present invention relates to the recognition and (early) detection of a clinical condition of a subject linked to microbiota dysbiosis and / or systemic inflammation. Also the assessment of the severity of the condition may be encompassed by the term.

[0118] The term "prognosis" relates to the prediction of an outcome or a specific risk for a subject based on microbiota dysbiosis. This may also include an estimation of the chance of recovery or the chance of an adverse outcome for said subject.

[0119] In the present invention, the terms "risk assessment" and "risk stratification" relate to the grouping of subjects into different risk groups according to their further prognosis. Risk assessment also relates to stratification for applying preventive and / or therapeutic measures. Examples of the risk stratification are the low, intermediate and high-risk levels disclosed herein. The term “correlation” shall mean a relationship between two or more variables. The relationship does not necessarily imply cause and effect. When two variables are correlated, it shall mean that as one variable changes, so does the other. By way of example, a correlation can be measured by calculating a statistic known as a correlation coefficient. A correlation coefficient can be a number from -1 to +1 that indicates the strength and direction of the relationship between variables (for example as indicated in figures 2 and 3), usually represented by the letter r. The present invention is based on the unexpected finding of the correlation between fecal GP2 and the diversity of the microbiota, in particular, microbiota dysbiosis. Such correlations reveal the relationship between fecal GP2 and microbiota diversity and enables a novel diagnostic method for microbiota dysbiosis by detecting fecal GP2.

[0120] The term “correlation coefficient” refers to a measure of the strength of the relationship. The number portion of the correlation coefficient indicates the strength of the relationship. The closer the number is to 1 (be it negative or positive), the more strongly related the variables are, and the more predictable changes in one variable will be as the other variable changes. The closer the number is to zero, the weaker the relationship, and the less predictable the relationships between the variables becomes. For instance, a correlation coefficient of 0.9 indicates a far stronger relationship than a correlation coefficient of 0.3. If the variables are not related to one another at all, the correlation coefficient is 0. In the present invention, a correlation coefficient above 0 indicates a relationship between fecal GP2 level and the bacteria. The closer the number to 1 , the stronger the relationship, and the more predictable the relationships between fecal GP2 and the bacteria.

[0121] The term “positive correlation” shall mean the variables move in the same direction. Put another way, it means that as one variable increases so does the other, and conversely, when one variable decreases so does the other.

[0122] In embodiments, the fecal GP2 level is positively correlated with one or more bacteria selected from Turicibacter, Erysipeloetrichaceae, Phascolarctobacterium, Mitsuokella, Allisonella, Sutterella, Parasutterella, Haemophilus, Collinsella, Slackia, Prevotella, Streptococcus, Clostridium sensu stricto, Roseburia, Clostridium XlVa, Fusicatenibacter, Dorea, Lachnospiraceae, Romboutsia, Faecalibacterium and / or Ruminococcus, Haemophilus, Collinsella, Streptococcus and / or Clostridium XlVa, Haemophilus, Actinomyces, Gordonibacter, Streptococcus, Clostridium .sensu .stricto, Dorea, Anaerostipes, Romboutsia, Turicibacter, Clostridium XVIII and / or Veillonelila. The correlation coefficient of each positive correlation are different which indicates not only the existing relationship between the fecal GP2 but also the strength of the relationship.

[0123] The term “inverse correlation”, also called “negative correlation” shall mean the variables move in opposite directions. If two variables are negatively correlated, a decrease in one variable is associated with an increase in the other and vice versa.

[0124] In embodiments, the fecal GP2 level is inversely correlated with one or more bacteria selected from Clostridium IV, Oscillibcacter, Anaerotruncus, Pseudoflavonifractor, Ruminococcaceae, Victivallis, Oxalobacter, Akkermansia, Odoribacter, Butyricimonas, Alistipes and / or Catabacter, Victivallis, Oxalobacter, Sutterella, Desulfovibrio, Bilophila, Desulfovibrionaceae, Escherichia / Sshigella, Citrobacter, Coraliomargarita, Akkermansia, Olsenella, Coriobacteriaceae, Barnesiella, Coprobacter, Butyricimonas, Porphyromonadaceae, Prevotella, Paraprevotella, Alloprevotella, Rikenellaceae, Catabacter, Anaerovorax, Mogibacterium, Butyrivibrio, Eisenbergiella, Peptococcus, Ethanoligenens, Sporobacter, Anaerofilum and / or Coprobacillus, Escherichia / Shigella and / or Citrobacter. The correlation coefficients of each inverse correlation are different which indicates not only the existing relationship between the fecal GP2 but also the strength of the relationship.

[0125] The term “reduced presence” shall mean decrease of the bacteria in the microbiota diversity, compared to a healthy subject, or population average of healthy subjects.

[0126] The term “gut microbial alpha diversity” refers to a measure of microbiome diversity applicable to a single sample. Many indices exist, each reflecting different aspects of community heterogeneity. In embodiments, alpha diversity measures can be seen as a summary statistic of a single population (within sample diversity). The term “gut microbial beta diversity” refers to a measure of the similarity or dissimilarity of two communities. It is an essential measure for many popular statistical methods in ecology, such as ordination-based methods, and is used for studying the association between environmental variables and microbial composition.

[0127] As used herein, the term "therapy" refers to application of certain therapies or medical interventions based on the value of one or more biomarkers and / or clinical parameter and / or clinical scores.

[0128] The term “reference data” shall not be limited to a threshold level of fecal GP2 and can be an overrepresentation and / or underrepresentation of the bacteria correlated with fecal GP2 levels. In embodiments, the reference data can be the threshold level of fecal GP2 indicative of systemic inflammation. In embodiments, the reference data can be dysbiosis index with respect to the correlation between fecal GP2 level and the bacteria population.

[0129] The term “short-chain fatty acids” (SCFAs) and / or “lactic acid” refer to primary metabolites that can impact the composition and function of human microbiota. Many SCFA- and lactate- producing bacteria have been identified in the gut microbiota.

[0130] The term “systemic inflammation” refers to the result of release of pro-inflammatory cytokines from immune-related cells and the activation of the innate immune system. In embodiments, the systemic inflammation is chronic inflammation. It can contribute to the development or progression of certain conditions such as cardiovascular disease, cancer, diabetes mellitus, chronic kidney disease, non-alcoholic fatty liver disease, autoimmune and neurodegenerative disorders, and coronary heart disease. Certain species of microbes produce specific enzymes that enable fermentation of nutrients into absorbable forms, including that of indigestible carbohydrates into short-chain fatty acids (SCFAs). These SCFAs may have anti-inflammatory and immunomodulatory effects. In the present invention, fecal GP2 levels are inversely correlated with the gut microbial pathways needed for SCFA-biosynthesis indicative of a systemic inflammation.

[0131] Gut bacteria possess the capability of metabolising complex carbohydrates, otherwise undigested by the host, into SCFAs. SCFAs play a critical role in the interplay between diet, the gut microbiota and downstream activation or inhibition of inflammatory cascades. Additionally, they contribute to the homeostatic control of energy and appetite regulation through their effects on metabolic pathways. Depending on the type and concentration of SCFA, their effects on inflammation differ, and SCFA levels may vary in obese and lean phenotypes. In many animal studies, SCFA butyrate has been associated with a variety of roles that oppose the onset of metabolic disorders. Through epigenetic interactions, butyrate promotes lipolysis and mitochondrial functioning in adipocytes, thus enabling a greater energy expenditure and preventing the onset or maintenance of obesity. Butyrate is an anti-inflammatory metabolite that is known to inhibit the pathways that lead to the production of pro-inflammatory cytokines. In a clinical study of 13 patients with Crohn’s disease, oral administration of butyrate was found to alleviate inflammation in nine patients. Additionally, butyrate minimises the risk of development of insulin resistance as it improves insulin signalling. Butyrate has also been shown to minimise LPS translocation in the intestines, thus reducing LPS-associated effects. Faecalibacterium prausnitzii has been identified as a butyrate-producing bacterium with an inverse relationship with different pro-inflammatory markers. In obese individuals, F. prausnitzii abundance is reduced compared to individuals with healthy body weight.

[0132] Acetate, another SCFA, is an important molecule for the processes of lipogenesis and gluconeogenesis. Acetate can serve as a substrate for cholesterol synthesis, thus contributing to elevated serum cholesterol levels. In a study of rats, contrasting with butyrate, acetate was found to correlate with greater insulin resistance and an increase in ghrelin secretion as a result of its activation of the parasympathetic nervous system. As ghrelin is an appetite-stimulating hormone associated with greater food intake, acetate may consequently be linked with weight gain.

[0133] The present invention therefore also relates to methods for diagnosing, prognosing or determining a risk or likelihood of a subject suffering form altered SCFA metabolism and associated medical conditions using the methods of GP2 detection and determination of microbial dysbiosis described herein.

[0134] As used herein, the "patient" or "subject" may be a vertebrate. In the context of the present invention, the term "subject" includes both humans and animals, particularly mammals, and other organisms. The term "individual,” “subject,” or “patient” typically refers to humans, but also to other animals including, e.g., other primates, rodents, canines, felines, equines, ovines, porcines, and the like.

[0135] The term “in vitro method” relates to a method that is performed on a sample, for example, without limitation, a stool sample, a tissue or a bodily fluid, outside of the outside their normal biological context.

[0136] As used herein, the term “substantially the same amino acid sequence” includes an amino acid sequence that is similar, but not identical to, the naturally-occurring amino acid sequence. For example, an amino acid sequence, i.e., polypeptide, that has substantially the same amino acid sequence as the GP2 isoforms in SEQ ID NO 1 to 4 and can have one or more modifications such as amino acid additions, deletions, or substitutions relative to the amino acid sequence of the GP2 isoforms, provided that the modified polypeptide retains substantially at least one biological activity of GP2 such as immunoreactivity.

[0137] As used herein, the term “GP2 isoform” includes a protein that has at least about 70% amino acid identity with one or more SEQ ID No 1 to 4. As a non-limiting example, an GP2 isoform of the invention can have at least about 70%, 75%, 80%, 85%, 90%, 91 %, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% amino acid sequence identity with one or more SEQ ID No 1 to 4.

[0138] Affinity reagents, such as antibodies, directed against GP2 isoforms or GP2 proteins with substantially the same amino acid sequence may therefore be employed in the present invention in order to detect GP2.

[0139] The analysis described herein of determining GP2 concentration via antibody binding to one or more GP2 isoforms is a preferred method of the present invention. Alternatively, or in combination, control values or standards may be used that provide samples with GP2 isoforms or represent control amounts thereof, as have already been obtained from previous analytical tests. It is possible to use control values having been generated by the testing of cohorts or other large numbers of subjects suffering from any given disease or control group. Appropriate statistical means are known to those skilled in the art for analysis and comparison of such data sets. Control samples for positive controls (such as disease sufferers) or negative controls (from healthy subjects) may be used for reference values in either simultaneous of non-simultaneous comparison.

[0140] The term “affinity reagent” in the context of the present invention relates to an antibody, peptide, nucleic acid, small molecule, or any other molecule that specifically binds to a target molecule in order to identify, track, capture, or influence its activity. The term “capturing” refers to binding of a target molecule by an affinity reagent.

[0141] The term “secondary affinity reagent” refers to any affinity reagent according to the above definition, which is used to bind to an antigen that is already bound by another affinity reagent.

[0142] As used herein, the term “antibody” includes a population of immunoglobulin molecules, which can be polyclonal or monoclonal and of any isotype, or an immunologically active fragment of an immunoglobulin molecule. Such an immunologically active fragment contains the heavy and light chain variable regions, which make up the portion of the antibody molecule that specifically binds an antigen. For example, an immunologically active fragment of an immunoglobulin molecule known in the art as Fab, Fab' or F(ab )2 is included within the meaning of the term antibody.

[0143] The term “monoclonal antibody” refers to antibodies that are made by identical immune cells that are all clones of a unique parent cell, in contrast to polyclonal antibodies, which are made from several different immune cells. Monoclonal antibodies can have monovalent affinity, in that they bind to the same epitope (the part of an antigen that is recognized by the antibody). Engineered bispecific monoclonal antibodies also exist, where each "arm" of the antibody is specific for a different epitope. Given almost any substance, it is possible to produce mono-clonal antibodies that specifically bind to that substance; they can then serve to detect or purify that substance.

[0144] In another advantageous embodiment an immunoassay is used in the detection of GP2 to which end binding of the GP2 specific antibody to a solid phase is envisaged. Following addition of sample solution, the patient's GP2 included therein binds to the GP2 antibody. GP2, which is obtained e.g. from the stool of a patient and bound to the GP2 antibody, is subsequently detected using a label, or labelled reagent and optionally quantified. Thus, according to the invention, detection of GP2 in this method is effected using labelled reagents according to the well-known ELISA (Enzyme-Linked Immunosorbent Assay) technology. Labels according to the invention therefore comprise enzymes catalysing a chemical reaction which can be determined by optical means, especially by means of chromogenic substrates, chemiluminescent methods or fluorescent dyes. In another preferred embodiment GP2 is detected by labelling with weakly radioactive substances in radioimmunoassays (RIA) wherein the resulting radioactivity is measured.

[0145] As examples of means for detecting the label in the method of the present invention, a variety of immunoassay techniques, including competitive and non-competitive immunoassays, can be used to determine the presence or level of one or more markers in a sample (see, e.g., Self et al., Curr. Opin. Biotechnol., 7:60-65 (1996)). The term immunoassay encompasses techniques including, without limitation, enzyme immunoassays (EIA) such as enzyme multiplied immunoassay technique (EMIT), enzyme-linked immunosorbent assay (ELISA), antigen capture ELISA, sandwich ELISA, IgM antibody capture ELISA (MAC ELISA), and microparticle enzyme immunoassay (MEIA); capillary electrophoresis immunoassays (CEIA); radioimmunoassays (RIA); immunoradiometric assays (IRMA); fluorescence polarization immunoassays (FPIA); lateral flow tests; and chemiluminescence assays (CL).

[0146] In another preferred embodiment of the method according to the invention GP2 is detected in a lateral flow test, which can also be referred to as immunochromatographic test or lateral flow immunochromatographic test. Lateral flow tests are preferably based on a series of capillary beds, such as, for example, pieces of porous paper, microstructured polymer, or sintered polymer. Each of these elements has the capacity to transport fluid spontaneously. The first element (the sample pad) acts as a sponge and holds an excess of sample fluid. Once soaked, the fluid migrates to the second element (conjugate pad) in which the manufacturer has stored the so-called conjugate, a dried format of bio-active particles (see below) in a salt-sugar matrix that contains everything to guarantee an optimized chemical reaction between the target molecule (e.g., an antigen) and its chemical partner (e.g., antibody) that has been immobilized on the particle's surface. While the sample fluid dissolves the salt-sugar matrix, it also dissolves the particles and in one combined transport action the sample and conjugate mix while flowing through the porous structure. In this way, the analyte binds to the particles while migrating further through the third capillary bed. This material has one or more areas (often called stripes) where a third molecule has been immobilized by the manufacturer. By the time the sample-conjugate mix reaches these strips, analyte has been bound on the particle and the third 'capture' molecule binds the complex. After a while, when more and more fluid has passed the stripes, particles accumulate and the stripe-area changes colour. Typically there are at least two stripes: one (the control) that captures any particle and thereby shows that reaction conditions and technology worked fine, the second contains a specific capture mole-cule and only captures those particles onto which an analyte molecule has been immobilized. After passing these reaction zones the fluid enters the final porous material, the wick that simply acts as a waste container. Lateral Flow Tests can operate as either competitive or sandwich assays and can in principle be performed by using any coloured particle. However latex (blue colour) or nanometer sized particles of gold (red colour) are commonly used. The gold particles are red in colour due to localised surface plasmon resonance. Fluorescent or magnetic labelled particles can also be used, however these require the use of an electronic reader to assess the test result.

[0147] If desired, such immunoassays can be automated. Immunoassays can also be used in conjunction with laser induced fluorescence (see, e.g., Schmalzing et al., Electrophoresis, 18:2184-2193 (1997); Bao, J. Chromatogr. B. Biomed. Sci., 699:463-480 (1997)). Liposome immunoas-says, such as flow-injection liposome immunoassays and liposome immunosensors, are also suitable for use in the present invention (see, e.g., Rongen et al., J. Immunol. Methods, 204:105-133 (1997)). In addition, nephelometry assays, in which the formation of pro-tein / antibody complexes results in increased light scatter that is converted to a peak rate signal as a function of the marker concentration, are suitable for use in the present invention. Nephe-lometry assays are commercially available from Beckman Coulter (Brea, Calif.; Kit #449430) and can be performed using a Behring Nephelometer Analyzer (Fink et al., J. Clin. Chem. Clin. Biol. Chem., 27:261-276 (1989)).

[0148] In another preferred embodiment of the method according to the invention GP2 is detected in an immunoassay, preferably with direct or indirect coupling of one reactant to a labelling substance. This enables flexible adaptation of the method to the potentials and requirements of different laboratories and their laboratory diagnostic equipment. In one advantageous embodiment GP2 is detected in an immunoassay wherein GP2 is present dissolved in a liquid phase, preferably diluted in a conventional buffer solution well-known to those skilled in the art or in an undiluted body fluid. According to the invention, detection can also be effected using stool samples.

[0149] In another preferred embodiment of the invention, soluble or solid phase-bound antibodies are used to bind specific isoforms of GP2. In a second reaction step, secondary anti-GP2 affinity reagents are employed, preferably secondary anti-GP2 antibodies, which are detectably la-belled conjugates of two components which can be conjugated with any conventional labelling enzymes, especially chromogenic and / or chemiluminescent substrates, preferably with horse-radish peroxidase, alkaline phosphatase. The advantage of this embodiment lies in the use of ELISA technology usually available in laboratory facilities so that detection according to the invention can be established in a cost-effective manner. In another preferred embodiment of the invention secondary anti-GP2 affinity reagents is detectably coupled to fluorescein isothio-cyanate (FITC). Much like the above-mentioned ELISA, the FITC technology represents a system that is available in many places and therefore allows smooth and low-cost establishment of the inventive detection in laboratory routine.

[0150] The term “denaturated” sample conditions” refers to conditions, which induce denaturation of the molecules contained in a sample. Denaturation is a process in which proteins or nucleic acids lose the quaternary structure, tertiary structure and secondary structure, which is pre-sent in their native state, by application of some external stress or compound such as a strong acid or base, a concentrated inorganic salt, an organic solvent (e.g., alcohol or chloroform), radiation or heat.

[0151] A “kit for diagnosis” includes all necessary analyte specific reagents required for carrying out a diagnostic test. It may also contain instructions on how to conduct the test using the provided reagents. Specific immunological binding of an affinity reagent such as an antibody to the marker of interest can be detected directly or indirectly via a label that is emitting a signal. Any given means for detecting these labels may be considered means for detecting the label according to the method of the invention. Direct labels include fluorescent or luminescent tags, metals, dyes, radionuclides, and the like, attached to the antibody. An antibody labelled with iodine-125 (1251) can be used for determining the levels of one or more markers in a sample. A chemiluminescence assay using a chemiluminescent antibody specific for the marker is suitable for sensitive, non-radioactive detection of marker levels. An antibody labelled with fluorochrome is also suitable for determining the levels of one or more markers in a sample. Examples of fluorochromes include, without limitation, DAPI, fluorescein, Hoechst 33258, R-phycocyanin, B- phycoerythrin, R-phycoerythrin, rhodamine, Texas red, and lissamine. Secondary antibodies linked to fluorochromes can be obtained commercially, e.g., goat F(ab')2 anti-human IgG-FITC is available from Tago Immunologicals (Burlingame, Calif.).

[0152] Indirect labels include various enzymes well-known in the art, such as horseradish peroxidase (HRP), alkaline phosphatase (AP), p-galactosidase, urease, and the like. A horseradish- peroxidase detection system can be used, for example, with the chromogenic substrate tetramethyl benzidine (TMB), which yields a soluble product in the presence of hydrogen peroxide that is detectable at 450 nm. An alkaline phosphatase detection system can be used with the chromogenic substrate p-nitrophenyl phosphate, for example, which yields a soluble product readily detectable at 405 nm. Similarly, a P-galactosidase detection system can be used with the chromogenic substrate o-nitrophenyl-p-D-galactopyranoside (ON PG), which yields a solu-ble product detectable at 410 nm.

[0153] Methods for determining the concentration of specific molecules of interest in a sample a known to the person skilled in the art. For example, the concentration of the molecule of interest, for example a specific isoform of GP2, in a sample is determined by comparing the signal generated by a secondary affinity reagent according to the present invention that has captured the molecule of interest in said sample to the signal generated by a secondary affinity reagent that has captured the molecule of interest in a control sample, wherein the concentration of the molecule of interest in said control sample is known.

[0154] The method as described herein may also be described in terms of determining the amount of GP2, as an alternative or supplementary description to determining the concentration of GP2.

[0155] “Plate readers”, also known as microplate readers or microplate photometers, are instruments which are used to detect biological, chemical or physical events of samples in microtiter plates. They are widely used in research, drug discovery, bioassay validation, quality control and manufacturing processes in the pharmaceutical and biotechnological industry and academic organizations. Sample reactions can be assayed, for example, without limitation, in 6-1536 well format microtiter plates. Common detection modes for microplate assays are, for example, without limitation, absorbance, fluorescence intensity, luminescence, time-resolved fluorescence, and fluorescence polarization.

[0156] A “camera device” in the context of the present invention is a device suitable for detection of the signal of the labelled secondary affinity reagent directed against GP2. The camera device can provided as being comprised in the plate reader or individually. The person skilled in the art is familiar with such devices, which are selected based on the label of the secondary affinity reagent.

[0157] A signal from the direct or indirect label can be analysed, for example, using a spectrophotometer to detect colour from a chromogenic substrate; a radiation counter to detect radiation such as a gamma counter for detection of 1251; or a fluorometer to detect fluorescence in the presence of light of a certain wavelength. For detection of enzyme-linked antibodies, a quantitative analysis of the amount of marker levels can be made using a spectrophotometer such as an EMAX Microplate Reader (Molecular Devices; Menlo Park, Calif.) in accordance with the manufacturer’s instructions. If desired, the assays of the present invention can be automated or performed robotically, and the signal from multiple samples can be detected simultaneously.

[0158] The invention also relates to protein and nucleic acid molecules corresponding to the sequences described herein, for example proteins or nucleic acid molecules comprising or consisting of said sequences.

[0159] As used herein, the term “GP2 isoform”, “GP2”, “GP2-antigen”, “GP2-molecule”, “GP2-protein”, “GP2-peptide” or “GP2-autoantigen”, or other GP2-referencing phrase relates to the GP2- isoforms of the sequences as disclosed herein, or functionally analogous sequences thereof, preferably to those isoforms 1 , 2, 3 and 4. In a preferred embodiment of the method according to the invention the GP2-isoform is of human, animal, recombinant or synthetic origin. GP2 represents a highly conserved peptide so that GP2 of any origin can advantageously be used for detection as long as the sequence is functionally analog to the sequence according to the invention.

[0160] In another preferred embodiment of the invention the anti-GP2 antibody directed to GP2 in accordance with one or more of the sequences disclosed herein is bound to a solid phase. Binding of the anti-GP2 antibody in accordance with one or more of the sequences disclosed herein to the solid phase can be effected via a spacer. All those chemical compounds having suitable structural and functional preconditions for spacer function can be used as spacers as long as they do not modify the binding behaviour in such a way that binding of the anti-GP2 antibody to GP2 in accordance with one or more of the sequences disclosed herein is adversely affected.

[0161] In another preferred embodiment of the invention the affinity reagents according to the present application are immobilized. More specifically, the solid phase-bound anti-GP2, preferably anti- GP2, antibody directed to a GP2 molecule in accordance with one or more of the sequences as disclosed herein is bound to organic, inorganic, synthetic and / or mixed polymers, preferably agarose, cellulose, silica gel, polyamides and / or polyvinyl alcohols. In the meaning of the invention, immobilization is understood to involve various methods and techniques to fix the peptides on specific carriers, e.g. according to WO 99 / 56126 or WO 02 / 26292. For exam-pie, immobilization can serve to stabilize the peptides so that their activity would not be re-duced or adversely modified by biological, chemical or physical exposure, especially during storage or in single-batch use. Immobilization of the peptides allows repeated use under technical or clinical routine conditions; furthermore, a sample - preferably blood components - can be reacted with at least one of the peptides according to the invention in a continuous fashion. In particular, this can be achieved by means of various immobilization techniques, with binding of the peptides to other peptides or molecules or to a carrier proceeding in such a way that the three-dimensional structure - particularly in the active center mediating the interaction with the binding partner - of the corresponding molecules, especially of said peptides, would not be changed.

[0162] Advantageously, there is no loss in specificity to the GP2a antibodies as a result of such immobilization. In the meaning of the invention, three basic methods can be used for immobilization:

[0163] (i) Crosslinking: in crosslinking, the peptides are fixed to one another without adversely affect-ing their activity. Advantageously, they are no longer soluble as a result of such crosslinking.

[0164] (ii) Binding to a carrier: binding to a carrier proceeds via adsorption, ionic binding or covalent binding, for example. Such binding may also take place inside microbial cells or liposomes or other membranous, closed or open structures. Advantageously, the peptides are not adversely affected by such fixing. For example, multiple or continuous use of carrier-bound peptides is possible with advantage in clinical diagnosis or therapy.

[0165] (iii) Inclusion: inclusion in the meaning of the invention especially proceeds in a semipermeable membrane in the form of gels, fibrils or fibers. Advantageously, encapsulated peptides are separated from the surrounding sample solution by a semipermeable membrane in such a way that interaction with the binding partner or fragments thereof still is possible. Various methods are available for immobilization, such as adsorption on an inert or electrically charged inorganic or organic carrier. For example, such carriers can be porous gels, aluminum oxide, bentonite, agarose, starch, nylon or polyacrylamide. Immobilization proceeds via physical binding forces, frequently involving hydrophobic interactions and ionic binding. Advantageously, such meth-ods are easy to handle and have little influence on the conformation of the peptides. Advantageously, binding can be improved as a result of electrostatic binding forces between the charged groups of the peptides and the carrier, e.g. by using ion exchangers, particularly Sephadex.

[0166] Another method is covalent binding to carrier materials. In addition, the carriers may have reactive groups forming homopolar bonds with amino acid side chains. Suitable groups in peptides are carboxy, hydroxy and sulfide groups and especially the terminal amino groups of lysines. Aromatic groups offer the possibility of diazo coupling. The surface of microscopic porous glass particles can be activated by treatment with silanes and subsequently reacted with peptides. For example, hydroxy groups of natural polymers can be activated with bromocyanogen and subsequently coupled with peptides. Advantageously, a large number of peptides can undergo direct covalent binding with polyacrylamide resins. Inclusion in three-dimensional networks involves inclusion of the peptides in ionotropic gels or other structures well-known to those skilled in the art. More specifically, the pores of the matrix are such in nature that the peptides are retained, allowing interaction with the target molecules. In crosslinking, the peptides are converted into polymer aggregates by crosslinking with bifunctional agents. Such structures are gelatinous, easily deformable and, in particular, suitable for use in various reactors. By adding other inactive components such as gelatin in crosslinking, advantageous improvement of mechanical and binding properties is possible. In microencapsulation, the reaction volume of the peptides is restricted by means of membranes. For example, microencapsulation can be carried out in the form of an interfacial polymerization. Owing to the immobilization during microencapsulation, the peptides are made insoluble and thus reusable. In the meaning of the invention, immobilized peptides are all those peptides being in a condition that allows reuse thereof. Restricting the mobility and solubility of the antibodies by chemical, biological or physical means advantageously results in lower process cost.

[0167] The invention also relates to a diagnostic kit. The diagnostic kit optionally includes instructions concerning combining the contents of the kit for the detection of AP and differentiation from other diseases. For example, the instruction can be in the form of an instruction leaflet or other medium providing the user with information as to the type of method wherein the substances mentioned are to be used. Obviously, the information need not necessarily be in the form of an instruction leaflet, and the information may also be imparted via the Internet, for example. As used herein, the terms “comprising” and “including” or grammatical variants thereof are to be taken as specifying the stated features, integers, steps or components but do not preclude the addition of one or more additional features, integers, steps, components or groups thereof. This term encompasses the terms “consisting of and “consisting essentially of. Thus, the terms “comprising” / “including7”having” mean that any further component (or likewise features, integers, steps and the like) can / may be present. The term “consisting of means that no further component (or likewise features, integers, steps and the like) is present.

[0168] Sequence listing according to the present invention:

[0169] FIGURES

[0170] The following figures are presented to describe particular embodiments of the invention, without being limiting in scope. Brief description of the figures:

[0171] Figure 1 : Contribution of GP2 levels and other important host factors to gut microbiota diversity. Figure 2: Association of GP2 levels with gut microbiota.

[0172] Figure 3: Association of GP2 levels with gut microbial presence-absence patterns.

[0173] Figure 4: Association of GP2 levels with microbial alpha diversity reduction.

[0174] Figure 5: Association of GP2 levels with reduced SOFA and lactic acid biosynthesis capability.

[0175] Detailed description of the figures:

[0176] Figure 1 : Contribution of GP2 levels and other important host factors to gut microbiota diversity. Shown are the two major PCo1 and PCo2 with each dot representing one individual gut microbiome sample, colored according to the quantities of fecal GP2. The length of the blue arrows indicates the effect size of specific variable contributions to gut microbiota beta diversity. Variation in fecal GP2 and pancreatic elastase levels have the highest impact on microbial variation. BMI: Body mass index. FFS: Food frequency score (healthy diet).

[0177] Figure 2: Association of GP2 levels with gut microbiota. Shown is a cladogram depicting microbial genera or families (continuous data) and their association with fecal GP2 levels. Significant results (q<0.05) are depicted by a red (positive association) or blue dot (inverse association). The dot diameter corresponds to the magnitude of the regression effect estimate. Different phyla are color coded. The analyses revealed marked gut microbiota changes in association to variation in fecal GP2 levels. G: Genus. F: Family.

[0178] Figure 3: Association of GP2 levels with gut microbial presence-absence patterns. Shown is a cladogram depicting microbial genera or families (presence-absence data) and their association with fecal glycoprotein 2 (GP2) levels. Significant results (q<0.05) are depicted by a red (positive association) or blue dot (inverse association). The dot diameter corresponds to the magnitude of the regression effect estimate. Different phyla are color coded. The analyses revealed a loss of distinct microbial taxa in individuals with higher fecal GP2 levels. G: Genus. F: Family.

[0179] Figure 4: Association of GP2 levels with microbial alpha diversity reduction. The barplot shows inverse associations between fecal GP2 levels and the microbial diversity scores Simpson diversity number (N2), Shannon diversity index (H), Chad estimator and species richness (NO). *: indicates significant results (p<0.05).

[0180] Figure 5: Association of GP2 levels with reduced SCFA and lactic acid biosynthesis capability. The barplot shows inverse (blue) or positive (red) associations between fecal GP2 levels and predicted microbial pathways for SCFA or lactic acid biosynthesis. The analysis revealed a distinct reduction in the microbial capacity for SCFA or lactic acid biosynthesis in individuals with higher fecal GP2 levels. *: indicates significant results (q<0.05).

[0181] EXAMPLES

[0182] Example 1: GP2 Association Analyses with Phenotypic Factors The complete cohort comprised of 2,812 individuals with available fecal GP2 levels. Median GP2 levels were 1 ,1 18.7 ng / g stool (215.4 - 3,659.1 , first - third quartile). The phenotypic characteristics of the cohort are given in Table 1. Simple linear regression analyses revealed significant positive associations of fecal GP2 levels with smoking (p<0.001 ), BMI (p<0.001 ), alcohol consumption (p=0.001), hs-CRP (p=0.002), and fatty liver disease (p<0.005) whereas inverse associations were found with higher FFS values (p<0.001), female sex (p<0.001), fecal elastase (p<0.001), age (p<0.001), and chronic kidney disease (p=0.047). No associations were found for hypothyroidism, or other cardiometabolic disorders such as diabetes mellitus, dyslipidemia, hypertension, or manifest atherosclerotic disease. After including all of the aforementioned significantly associated variables into one multiple regression model inverse associations with fecal GP2 levels remained for fecal elastase (p<0.001 ), age (p=0.001 ), female sex (p=0.019), and FFS (p=0.023), whereas positive associations were confirmed for BMI (p<0.001 ), smoking (p=0.007) and hs-CRP (p=0.042).

[0183] Table 1. Phenotype characteristics and regression analysis

[0184] Example 2: Contribution of GP2 to Gut Microbial Beta Diversity

[0185] The beta diversity metric 'Bray-Curtis' dissimilarity was calculated and a subsequent PCoA was performed to identify the microbial variation that can be attributed to different phenotype factors. We analysed only those factors that exhibited significant associations with GP2 levels in the multiple regression model. Figure 1 shows that the highest effect on microbial variation in this dataset could be attributed to changes in fecal GP2 (r2= 13.5%, p<0.001) or pancreatic elastase (r2=9.4%, p<0.001). Significant influences also come from age (r2=5.8%, p<0.001), BMI (r2=4.4%, p<0.001), sex ([ =3.4%, p<0.001), smoking (r2=1 .8%, p<0.001), or FFS (r2=1 .4%, p<0.001 ).

[0186] Microbiome changes attributable to higher GP2 levels were positively correlated with smoking or high BMI whereas an inverse association pattern was seen (along PCo2) for high pancreatic elastase levels, female sex, FFS (healthy diet), or age.

[0187] Example 3: Association Patterns of GP2 with Gut Microbiota

[0188] A linear regression model was employed to analyse the association of fecal GP2 levels with individual gut microbial taxa. Significant association with increased GP2 levels were found for 21 taxa in this model whereas 12 taxa exhibited an inverse association (Figure 2). A logistic regression model was used to analyse how fecal GP levels affect presence-absence patterns of gut microbiota and revealed 1 1 positive and 30 inverse associations (Figure 3).

[0189] Example 4: Association Patterns of GP2 with Microbial Alpha Diversity

[0190] Higher GP2 levels were largely associated with the absence, but not the presence of different microbial taxa. To investigate the consequences of this finding on “in sample” microbial diversity (alpha diversity), the association of GP2 levels with the four different microbial diversity scores Simpson diversity number (N2), Shannon diversity index (H), Chaol estimator and species richness (NO) were calculated using a linear regression model. This analysis revealed a strong inverse association of higher GP2 levels to N2 (p=0.002), H (p<0.001), Chaol (p<0.001), and NO (p<0.001 ), (Figure 4). Example 5: Intestinal SCFA and Lactic Acid Biosynthesis Capability and its Relation to GP2

[0191] Diversity changes that were found to correlate with high or low fecal GP2 levels included microbial taxa known to be involved in the biosynthesis of SCFA such as Ruminococcaceae, Faecalibacterium, Lachnospiraceae, or Roseburia. To investigate whether fecal GP2 levels are related with lower or higher SCFA or lactic acid biosynthesis capability, we analysed the predicted metagenomic pathways (PICRUSt) for the respective metabolites (details see methods). Figure 5 shows, that in individuals with higher fecal GP2 levels, 12 out of 15 analysed predicted microbial pathways for SCFA or lactic acid biosynthesis were depleted.

[0192] Discussion of examples 1-5:

[0193] In the present study, a cohort of 2,812 individuals were analyzed for how fecal GP2 levels are related to a range of different host factors, disease phenotypes and the composition of the gut microbiome. The main source of fecal GP2 is believed to be its secretion by zymogen granules in pancreatic acinar cells

[0031] , Another origin by expression in the follicle-associated epithelium of small intestinal Peyer's patches and colonic L cells has also been reported [8, 1 1], Elevated expression of GP2 has been found in both the exocrine pancreas and the intestinal mucosa in association with inflammatory processes in patients with Crohn’s disease or Crohn’s-like inflammation [9, 11 , 19],

[0194] Alternatively, it could indicate GP2 secretion by intestinal sources into the gut lumen. We measured lower fecal GP2 levels in individuals with a preserved exocrine pancreatic function, and also found an inverse correlation of fecal GP2 with a balanced diet (FFS) and female sex. On the other hand, high fecal GP2 levels were associated with smoking, higher BMI and increased systemic inflammation as indicated by high hs-CRP levels. The latter would support the assumption that inflammatory processes leading to raised TNF levels could trigger an elevated pancreatic secretion of GP2. No significant association was found with cardiovascular disease or diabetes mellitus. Regression analysis revealed a significant association with fatty liver disease, which was, however, lost after the inclusion of BMI as a stronger independent variable into the multiple regression analysis. Given the predictive power of mucosal loss of tolerance to particularly the larger GP2 isoform with disease severity in primary sclerosing cholangitis

[0013] , an autoimmune liver disease with male preponderance and dysbiosis

[0018] , and the link of the male gender with higher fecal GP2 levels in this study, this may indicate a putative predisposition for the development of liver autoimmunity in males with high fecal GP2. Moreover, in another study PSC patients showed a marked reduction in a broad range of SCFA-producing bacteria similar to our observation of reduced predicted SCFA producing microbial pathways in association with higher GP2 levels

[0032] , Altogether, high fecal GP2 levels apparently indicate an unhealthy metabolic phenotype with increased systemic inflammation.

[0195] The underlying mechanisms leading to this observation revealed that higher fecal GP2 levels were associated with gut microbiome changes, and that altered fecal GP2 levels explained a large part of the microbial variation in a PCoA. In linear and binary regression models, we detected 33 and 41 taxa, respectively, with significant associations with fecal GP2. Positive associations were found with Clostridium XlVa, Collinsella or the opportunistic pathogens Haemophilus and Streptococcus. A recent publication has shown that the presence of Clostridium XlVa in the gut microbiome of (still) healthy individuals associates with the development of fatty liver disease or diabetes mellitus over 5 years with a possible causal involvement [6], Detection of Collinsella has been linked to diabetes mellitus, obesity and precedes the development of fatty liver disease [6, 33, 34], Interestingly, we observed a reduced presence of the opportunistic Gram-negative pathogens Escherichia / Shigella and Citrobacter, in individuals with higher fecal GP2 levels. This observation may be explained by the fact that GP2 is an intestinal M-cells transcytotic receptor specific of type-l-piliated bacteria which participates in the mucosal immune response towards these bacteria [8],

[0196] In individuals with higher GP2 levels also some taxa which are known to be involved in SCFA biosynthesis, such as Ruminococcaceae, Butyrivibrio, Faecalibacterium, Lachnospiraceae, or Roseburia, showed altered abundance or presence. Analyses of predicted metagenomic microbial pathways revealed, that the vast majority of these SCFA pathways, including those necessary for lactic acid biosynthesis, were depleted. SCFA such as acetate, propionate, or butyrate play important roles in the physiology of the intestinal tract. They represent an important energy source for colonic epithelia, have anti-inflammatory properties and promote the gut barrier function [35, 36], Likewise, lactic acid producing bacteria have a beneficial effect on the gut barrier function

[0037] , and the depletion of these microbial pathways may result in increased intestinal permeability, bacterial translocation, and increased (subclinical) systemic inflammation as indicated by higher serum hs-CRP levels. Even though our cross-sectional study did not detect associations of cardiovascular or manifest metabolic disease with higher fecal GP2 levels, elevated systemic inflammation may still increase the risk for cardiovascular disease or negatively affect metabolic conditions such as fatty liver disease or diabetes mellitus in the long-term [38, 39],

[0197] A further detrimental aspect of the gut microbiome in individuals with higher GP2 levels was a marked reduction of microbial alpha diversity. Low microbial diversity generally accompanies obesity

[0040] , gastrointestinal disorders such as pancreatitis

[0041] , or develops after cholecystectomy

[0024] , The consequence of low microbiota diversity is an increased instability of the gut microbiome which may facilitate the loss of potentially beneficial and the accumulation of pathogenic bacteria over time [6],

[0198] To summarize, the data indicate that the intestinal mucosa may be a more important source of fecal GP2 than pancreatic acinar cells provided that the fecal GP2 is not increased in a TNF- dependent manner in the latter. GP2 is a biomarker of gut microbiota dysbiosis associated with increased systemic inflammation. The potential clinical value of GP2 as a biomarker of gut microbial dysbiosis and intestinal inflammation needs to be clarified in future studies which include disease specific patient cohorts.

[0199] Material and methods:

[0200] Study Population

[0201] All individuals were participants of the Study of Health in Pomerania (SHIP) which is a longitudinal population-based cohort study encompassing the two independent cohorts SHIPTREND and SHIP-START

[0020] , Participants of both cohorts were randomly selected from the general population of North-east Germany, as SHIP aims to investigate the prevalence and characteristics of common diseases and their risk factors in this area

[0021] , Fecal samples were collected during the initial recruitment of SHIP-TREND (n = 4,420, 2008 - 2012) and during the second follow-up of the SHIP-START cohort (n = 2,333, 2008 - 2012, initial recruitment 1997 - 2001). GP2 measurements were available for a total of 2,919 individuals. Of these we removed 107 participants with GP2 levels outside the mean + / - 3 standard deviations (SD) or a history of pancreatic disease, leaving 2,812 datasets for analysis. Corresponding intestinal microbiome data based on 16S rRNA gene sequencing was available for 2,671 individuals. All participants provided written informed consent and the study was approved by the local ethics committee of the University Medicine Greifswald (BB 39 / 08 and BB 122 / 13).

[0202] Collection of Fecal Samples

[0203] The participants were provided two fecal collection tubes with and without DNA-stabilizing EDTA- buffer (0.5 M T ris, 10 mM NaCI, 100 mM EDTA, pH 7.0). Fecal samples were collected by the study participants as described before [4] at home and brought to the study center individually or shipped by mail.

[0204] Determination of Fecal Glycoprotein 2 (GP2) Levels

[0205] For determination of GP2 levels in stool, native fecal samples were analysed using the Pancreatitis GP2 ELISA (GA Generic Assays, Berlin, Germany) according to the manufacturer's protocol. The assays detects the larger isoform of GP2

[0022] , Briefly, 25mg of stool were homogenized in 1.25ml extraction buffer and centrifuged for 10min at 3.000g. 20pl of supernatant were subsequently analysed in 96-well plates, which included GP2 standards as well as positive and negative controls. Final OD-Measurements were done in a spectrophotometer (SpectraMax 190) from Molecular Devices and GP2 values were calculated as [ng GP2 / mg stool] from an internal GP2 standard curve.

[0206] 16S rRNA Gene Sequencing of Fecal Samples

[0207] Determination of gut microbiota profiles using 16S rRNA gene sequencing was performed as described before in detail [4], In brief, DNA was extracted from fecal samples stored in a DNA- stabilizing EDTA-buffer using the PSP Spin Stool DNA Kit (Stratec Biomedical AG, Birkenfeld, Germany) following the manufacturer's instructions and isolates stored at -20 °C degrees until sequencing of the V1A / 2 region of the bacterial 16S rRNA gene using the 27F and the 338R primers on a MiSeq platform (Illumina, San Diego, USA).

[0208] Taxonomy Assignment and Predicted Metagenomics

[0209] CASAVA 1 .8.2 (https: / / support.illumina.com / sequencing / sequencing_software / casava) was employed to create MiSeq FastQ files. Data amplicon processing was then performed using the open-source software DADA2

[0023] according the recommendedt procedure for large datasets (https: / / benjjneb.github.io / dada2 / bigdata.html) adapted to the V1 / V2 16S rRNA gene region as described before

[0024] , For assignment of taxonomy, a Bayesian classifier and the Ribosomal Database Project (RDP) training set version 16 were used. All data were rarefied to 10,000 reads per sample before analysis. Metagenomic microbial functions were predicted based on the amplicon sequence variants (ASVs) derived from the DADA2 pipeline using the PICRUSt2 package

[0025] with the standardized workflow as described at https : / / g ith u b . co m / pi cru st / pi cru st2 / wi ki / Wo rkflo w.

[0210] Other Laboratory and Phenotypic Data

[0211] Fecal pancreatic elastase levels were determined using a monospecific pancreatic elastase ELISA assay (BIOSERV Diagnostics GmbH, Germany) according to the manufacturer's protocol as described before in detail [4], Laboratory parameters (alanine aminotransferase (ALT), creatinine, high-density lipoprotein (HDL), high-sensitivity CRP (hs-CRP), low-density lipoporotein (LDL), and thyroid-stimulating hormone (TSH)) were measured on a Dimension VISTA platform (Siemens Healthcare Diagnostics, Eschborn Germany). To determine glycated haemoglobin concentrations (HbA1 c) high-performance liquid chromatography (Bio-Rad Diamat, Munich, Germany) was performed. The CKD-EPI equation was employed for estimation of glomerular filtration rate (eGFR)

[0026] , Chronic kidney disease was assigned in case of eGFR values below 60 ml / min. Body mass index (BMI) was calculated as kilograms per square meter of the body height. Presence of diabetes mellitus was assigned in case of a positive patient history of diabetes in combination with current treatment (dietetically, orally, and / or insulin injections) or in case of HbA1c measurements s 6.5% or random blood gluocose levels =s 11.1 mmol / l. Hypothyroidism was assigned in case of thyroid hormone replacement therapy or an TSH s 4 mU / L. Dyslipidemia was considered in case of LDL / HDL ratios > 3.5 or > 3 for males or females, respectively, or current anti-lipid medication. For estimation of the daily alcohol intake in grams alcohol per day all alcoholic beverages that had been consumed over the last 30 days were counted and its average alcoholic contend calculated. Smoking was assigned if the participant was a present smoker. Fatty liver disease was diagnosed in case of hyperechogenic liver tissue using high resolution ultrasound (Vivid i, GE Healthcare, Chicago, Illinois, USA) in B mode in combination with serum alanine aminotransferase (ALT) levels belonging to the upper 25% of the investigated population. To assess the quality of diet, a food frequency score (FFS) based on consumption data from 15 food categories (meat, sausage, fish, boiled potatoes, pasta, rice, raw vegetables, boiled vegetables, fruits, whole grain / black / crisp bread, oats / cornflakes, eggs, cake / cookies, sweets and savoury snacks) was calculated as described elsewhere [24, 27, 28], where higher values indicated a healthier diet. Arterial hypertension was assigned in case of antihypertensive medication intake or a systolic or diastolic blood pressure =s 140 or 2s 90 mmHg, respectively. Manifest atherosclerotic disease was assigned in case of a history of myocardial infarction or stroke.

[0212] Data Analysis

[0213] All statistical analyses were implemented in 'R' (v. 3.6.3, https: / / www.R-project.org / )

[0029] , All figures were created using the packages 'ggplot2' or 'ggraph'

[0030] , Square root transformation of continuous phenotype variables was performed prior to all association analyses. To analyse the association patterns of fecal GP2-levels with other phenotypic variables a two-step apparoach was performed: i) Simple linear regression analyses (function 'Im', 'stats' package) were performed with GP2-levels as outcome and the respective phenotypic variable as explanatory variables, ii) All variables that were significantly associated with GP2-levels in simple linear regression were combined as predictors in a multiple linear regression model to validate the robustness of the associations. Microbial beta diversity was calculated using a Bray-Curtis dissimilarity (function 'vegdist', 'vegan' package) based on gut microbiota counts. Principal coordinate analysis (PCoA) was then performed (function 'cmdscale', 'vegan' package) and the contribution to the ordination result of different phenotypic variables analysed using the 'envfit' function ('vegan' package) assessing the statistical significance by 1 ,000 permutations.

[0214] To analyse the association of individual gut microbial taxa (outcome) with fecal GP2-levels (explanatory variable), two different models were calculated including the potential confounding factors pancreatic elastase, age, sex, BMI, FFS, smoking, cohort, and sequencing batch: i) Linear regression model with log-transformed continuous gut microbiota abundance data. Only taxa with presence in at least 10% of all samples were considered. Zeroes were treated as NA to avoid spurious results due to zero-inflation. Outliers ± 3 SD away from the mean were removed in each taxon. All taxa were normalized to enable comparable effect estimates, ii) Logistic regression model with binary gut microbiota data (absent vs. present). Only taxa with presence in at least 10% but not more than 80% of samples were considered. The alpha diversity scores 'Chaol estimator' or 'Shannon diversity index' (H), and 'Simpson diversity number' (N2) were computed using the 'vegan' package (Chaol estimator: function 'estimateR'; H and N2: function 'diversity'). To analyse the association of microbial alpha diversity (outcome) with fecal GP2 levels (explanatory variable) a linear regression model was used including the same possible confounding factors as for the taxon - trait associations analyses.

[0215] To analyse the association of predicted microbial pathways for short-chain fatty acid (SCFA) or lactic acid biosynthesis (outcome) with fecal GP2 levels (explanatory variable), the pathway gene abundance data were removed from outliers (± 3 SD), square root transformed and normalized. Again, the the same possible confounding factors as for the taxon - trait association analyses were used. All p-values derived from taxon-trait or pathway-trait associations were corrected for multiple testing using the method of 'Benjamini & Hochberg' and thereafter called q-values. P- or q-values < 0.05 were considered significant.

[0216] References

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Claims

CLAIMS1. An in vitro method for the diagnosis of a microbiota dysbiosis in a subject by detection of Glycoprotein 2 (GP2), comprising:Providing a stool sample of the subject,Providing a GP2 binding reagent,Contacting said sample with said binding reagent, thereby forming a complex comprising GP2 from said sample with said GP2 binding reagent, andDetermining a level of GP2 in said sample, wherein the level of GP2 is indicative of microbiota dysbiosis of the subject.

2. The method according to the preceding claim, wherein the GP2 level is positively correlated with one or more bacteria selected from Turicibacter, Erysipelotrichaceae, Phascolarctobacterium, Mitsuokella, Allisonella, Sutterella, Parasutterella, Haemophilus, Collinsella, Slackia, Prevotella, Streptococcus, Clostridium sensu stricto, Roseburia, Clostridium XlVa, Fusicatenibacter, Dorea, Lachnospiraceae, Romboutsia, Faecalibacterium and / or Ruminococcus.

3. The method according to any one of the preceding claims, wherein the GP2 level is positively correlated with one or more bacteria selected from Haemophilus, Collinsella, Streptococcus and / or Clostridium XlVa.

4. The method according to any one of the preceding claims, wherein the GP2 level is inversely correlated with one or more bacteria selected from Clostridium IV, Osillibacter, Anaerotruncus, Pseudoflavonifractor, Ruminococcaceae, Victivallis, Oxalobacter, Akkermansia, Odoribacter, Butyricimonas, Alistipes and / or Catabacter.

5. The method according to any one of the preceding claims, wherein the GP2 level indicates an increased amount and / or presence (above a threshold or an average population level) of one or more bacteria selected from Haemophilus, Actinomyces, Gordonibacter, Streptococcus, Clostridium sensu stricto, Dorea, Anaerostipes, Romboutsia, Turicibacter, Clostridium XVIII and / or Veillonella.

6. The method according to any one of the preceding claims, wherein the GP2 level indicates a reduced amount and / or presence (below a threshold or an average population level) of one or more bacteria selected from Victivallis, Oxalobacter, Sutterella, Desulfovibrio, Bilophila, Desulfovibrionaceae, Escherichia / Shigella, Citrobacter, Coraliomargarita, Akkermansia, Olsenella, Coriobacteriaceae, Barnesiella, Coprobacter, Butyricimonas, Porphyromonadaceae, Prevotella, Paraprevotella, Alloprevotella, Rikenellaceae, Catabacter, Anaerovorax, Mogibacterium, Butyrivibrio, Eisenbergiella, Peptococcus, Ethanoligenens, Sporobacter, Anaerofilum and / or Coprobacillus. (30)7. The method according to any one of the preceding claims, wherein the GP2 level is inversely correlated with the presence and / or amount of Escherichia / Shigella and / or Citrobacter.

8. The method according to any one of the preceding claims, wherein an elevated GP2 level (above a threshold or an average population level) indicates impaired and / or pathogenic biosynthesis of small chain fatty acids and / or lactic acid.

9. The method according to any one of the preceding claims, wherein an elevated GP2 level (above a threshold or an average population level) indicates a reduced gut microbial alpha diversity.

10. The method according to any one of the preceding claims, wherein the method comprises additionally the diagnosis, prognosis and / or risk stratification of a subject having and / or developing systemic inflammation, such as systemic inflammation associated with a gastrointestinal disorder, by detection of Glycoprotein 2 (GP2), wherein the level of GP2 is indicative of the subject having and / or developing systemic inflammation.11 . The method according to any one of the preceding claims, wherein a GP2 level below a threshold level is indicative of the absence of or a non-severe microbiota dysbiosis and / or the absence of or a low risk of having and / or developing systemic inflammation, or a GP2 level equal to or above a threshold level is indicative of the presence of or a severe microbiota dysbiosis and / or a high risk of having and / or developing systemic inflammation. wherein the threshold level is 3659.1 ± 20% ng / g.

12. The method according to any one of the preceding claims, wherein if the level of GP2 is indicative of a microbiota dysbiosis, the method additionally comprises indicating a suitable treatment, said treatment selected from one or more of administration of probiotics, prebiotics comprising fructo-oligosaccharides (FOS), galacto-oliogosaccharides (GOS) and trans- galacto-oligosacchrides (TOS), diet modification, fecal microbiota transplantation (FMT), antibiotic therapy.

13. The method according to any one of the preceding claims, wherein if the level of GP2 is indicative of a microbiota dysbiosis, the method additionally comprises indicating administration of one or microbiota according to any one of claims 4, 6 and 7 to the subject.

14. Use of a GP2 binding reagent for detecting Glycoprotein 2 (GP2) in stool, in an in vitro method for the diagnosis of a microbiota dysbiosis in a subject.

15. A Kit for the diagnosis of a microbiota dysbiosis in a subject by detection of Glycoprotein 2 (GP2) in stool, comprising: an GP2 binding reagent, preferably with a solid surface for immobilization of said reagent, or preferably a GP2 binding reagent immobilized to a solid surface, a labelled secondary affinity reagent directed to GP2, and preferably means for detecting the signal emitted from said label, andreference data corresponding to GP2 levels indicative of a microbiota dysbiosis, preferably additionally reference data indicative of a subject having and / or developing systemic inflammation, wherein said reference data is stored on a computer readable medium and / or employed in the form of computer executable code configured for comparing the determined levels of GP2 to the reference data, and optionally a sample collection device suitable for obtaining a stool sample.

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