Fibrosis biomarkers for non-alcoholic fatty liver disease

Abstract

Biomarkers and methods for accurate non-invasive diagnosis or prognosis of liver fibrosis in subjects with non-alcoholic fatty liver disease (NAFLD) are disclosed. The biomarkers include circulating levels of thrombospondin 2 (TSP2), which can be measured at any time during the course of the disease. The methods include non-invasive assessment of circulating levels of TSP2, either alone or in combination with other molecular, physiological or radiographic biomarkers. The methods are highly sensitive, detecting advanced liver fibrosis with a sensitivity of about 80% or greater. The methods can accurately predict the risk of developing advanced liver fibrosis in a subject using circulating levels of TSP2, either alone or in combination with other molecular, physiological or radiographic biomarkers.

Description

Technical Field

[0001] The present invention generally relates to biomarkers and methods for non-invasive diagnosis or prognosis of liver fibrotic diseases.

Background Art

[0002] Thrombospondin (TSP) is a type of matrix cell protein that interacts with a number of ligands including extracellular matrix (ECM) structural proteins, cell receptors, growth factors, and cytokines. TSP regulates cell-matrix interactions and has anti-angiogenic properties. Among the five thrombospondins (TSP1-5), TSP1 and TSP2 have similar structures. Nevertheless, previous studies have reported that TSP1 and TSP2 bind to different ligands, there are spatial and temporal differences in their expression, and their roles are not interchangeable (Agah et al., Am J Pathol; 161:831-839 (2002); Helkin et al., Biochem Biophys Res Commun; 464:1022-1027 (2015); Zhang et al., Int J Mol Med; 45:1275-1293 (2020)).

[0003] Hyperglycemia may induce the expression of both TSP1 and TSP2, and increased tissue expression of TSP1 and TSP2 was observed in patients with type 2 diabetes. Regarding non-alcoholic fatty liver disease (NAFLD), genetic inhibition of TSP1 was shown to prevent the development of non-alcoholic steatohepatitis (NASH) in mice, and serum levels of TSP1 were found to be positively correlated with the degree of hepatic steatosis in NAFLD patients (Min-DeBartolo et al., PLoS One;14:e0226854(2019); Bai et al., EBioMedicine;57:102849(2020)). One study revealed that liver expression of the THBS2 gene encoding TSP2 was significantly upregulated in patients with progressive fibrosis compared to those without (Lou et al., Sci Rep;7:4748(2017)), but the clinical relevance of circulating TSP2 remains unclear.

[0004] Type 2 diabetes is a significant risk factor for the progression of NAFLD (Younossi et al., Clin Gastroenterol Hepatol;2:262-265(2004); Kim et al., Clin Gastroenterol Hepatol;17:543-550 e542(2019); and Zoppini et al., Am J Gastroenterol;109:1020-1025(2014)). Among the various stages of NAFLD, hepatic fibrosis is a major determinant of all-cause mortality and liver-related adverse outcomes (Angulo et al., Gastroenterology;149:389-397 e310(2015); Ekstedt et al., Hepatology;61:1547-1554(2015)). Surprisingly, more than 70% of patients with type 2 diabetes also have NAFLD, or more specifically, metabolic dysfunction-associated fatty liver disease (MAFLD) using a recently proposed definition (Eslam et al., J Hepatol., 73:202-209 (2020)). NAFLD is the most prevalent chronic liver disease in the United States. NAFLD exists as two main histological subtypes: nonalcoholic fatty liver (NAFL) and nonalcoholic steatohepatitis (NASH) (Kleiner et al., Hepatology.; 41(6):1313-1321 (2005)). NAFL is associated with a relatively benign clinical course, while NASH is associated with an increased risk of progressive fibrosis and cirrhosis. NASH can be defined by the presence of fatty degeneration of the liver and inflammation accompanied by hepatocellular damage (ballooning), with or without fibrosis (Chalasani et al., Hepatology; 55: 2005-23 (2012)).

[0005] Non-alcoholic fatty liver disease (NAFLD) comprises a range of liver diseases, from isolated hepatic steatosis to non-alcoholic steatohepatitis (NASH), progressive fibrosis, cirrhosis, and hepatocellular carcinoma (HCC) (Chalasani et al., Diagnosis and Management of NAFLD: Practice Guidance from AASLD; Hepatology 2018). NAFLD can be diagnosed by the presence of hepatic steatosis on imaging or histological examination after excluding secondary causes of hepatic fat accumulation. However, NASH is a histological diagnosis that can only be diagnosed by liver biopsy and involves the presence of inflammation with hepatocyte damage (ballooning), with or without fibrosis. Hepatic fibrosis can be non-invasively assessed using clinical decision-making tools (e.g., NAFLD fibrosis score) and imaging studies (e.g., VTCE, MR elastography).

[0006] In NAFLD, liver biopsy remains the gold standard for histological diagnosis, assessment of activity, and classification of fibrosis staging. However, the routine use of liver biopsy is limited by its invasiveness, risk of complications, cost, sampling error, and poor patient acceptance. This highlights the urgent need for non-invasive and accurate methods for disease detection and staging. Currently, there is no reliable non-invasive method to distinguish NAFL from NASH (Siddiqui et al., Clin Gastroenterol Hepatol.; 17(1): 156–163 (2019)). Also, in some individuals with advanced fibrosis, NASH is relatively less common (Caldwell et al., Annals of Hepatology, 8, 346–352 (2009)).

[0007] Therefore, prognostic biomarkers are urgently needed to identify patients at high risk of disease progression, particularly the development of progressive fibrosis, who are at increased risk of long-term liver-related morbidity and mortality. (Lee et al., J Diabetes Investig;8:131-133(2017)).

[0008] Therefore, an object of the present invention is to provide biomarkers for non-invasive detection of fibrosis in NAFLD and for predicting the prognosis of fibrosis progression.

[0009] Another object of the present invention is to provide a method for non-invasive detection of fibrosis in NAFLD and for predicting the prognosis of fibrosis progression. [Prior art documents] [Non-patent literature]

[0010] [Non-Patent Document 1] Agah et al.,Am J Pathol;161:831-839(2002) [Non-Patent Document 2] Helkin et al.,Biochem Biophys Res Commun;464:1022-1027(2015) [Non-Patent Document 3] Zhang et al.,Int J Mol Med;45:1275-1293(2020) [Non-Patent Document 4] Min-DeBartolo et al.,PLoS One;14:e0226854(2019) [Non-Patent Document 5] Bai et al.,EBioMedicine;57:102849(2020)) [Non-Patent Document 6] Lou et al.,Sci Rep;7:4748(2017) [Non-Patent Document 7] Younossi et al., Clin Gastroenterol Hepatol;2:262-265(2004) [Non-Patent Document 8] Kim et al.,Clin Gastroenterol Hepatol;17:543-550 e542(2019) [Non-Patent Document 9] Zoppini et al.,Am J Gastroenterol;109:1020―1025(2014)

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[0011] Methods for non-invasively detecting advanced hepatic fibrosis in subjects are described. Methods for detecting the risk of developing advanced hepatic fibrosis in subjects are also described. These methods typically involve measuring the circulating level of the biomarker thrombospondin 2 (TSP2) in a sample from a subject. Measurement of the circulating level of TSP2 may be performed using a set of capture reagents containing one or more antibody-binding fragments having binding specificity to TSP2, preferably human TSP2. The set of capture reagents may contain binding fragments that have binding specificity to TSP2 but not to TSP1, TSP3, TSP4, and TSP5. Generally, this method detects the circulating level of TSP2 in a sample from a subject in the nanogram / ml range, for example, between 0.2 ng / ml and 10 ng / ml. The measurement method may be an immunoassay with a minimum detection limit of TSP2 of about 0.156 ng / ml to about 1 ng / ml, for example, about 0.2 ng / ml to about 0.5 ng / ml, or about 0.5 ng / ml.

[0012] Generally, this method detects advanced liver fibrosis when the circulating level of TSP2 in a sample from a subject exceeds approximately 3.6 ng / ml. Typically, the subject has non-alcoholic fatty liver disease (NAFLD). The subject may also have one or more other conditions or conditions, such as metabolic syndrome, type 2 diabetes, cardiovascular disease (CVD), and chronic kidney disease (CKD). The subject may have NAFLD and type 2 diabetes. The subject may or may not have non-alcoholic steatohepatitis (NASH).

[0013] This method typically involves using a blood or serum sample from the subject to measure the circulating level of TSP2.

[0014] Typically, this method provides non-invasive detection of advanced liver fibrosis or non-invasive detection of the risk of progression to liver fibrosis of grade F3 or higher. Typically, advanced liver fibrosis of grade F3 or higher is measured by vibration-controlled transient elastography (VCTE). Advanced liver fibrosis of grade F3 or higher is fibrosis graded by liver stiffness (LS) measurement in VCTE with cutoff values ​​of approximately 9.6 kilopascals (kPa) with an M probe or 9.3 kPa with an XL probe and above.

[0015] This method typically detects advanced liver fibrosis with a sensitivity of over 80% and a specificity of over 60% when the circulating level of TSP2 in the sample from the subject exceeds approximately 3.6 ng / ml. This method typically detects advanced liver fibrosis with a negative predictive value of over 90%.

[0016] The report also describes a method for detecting the risk of developing progressive liver fibrosis over time in subjects. Typically, this method involves measuring the circulating level of the biomarker TSP2 in a sample from the subject. This method detects that the risk of developing progressive liver fibrosis over time is 2.82 times greater per unit increase in logarithmically transformed serum TSP2 levels, measured in ng / ml. Typically, this period is approximately 0.1 to 3 years from sample acquisition, measurement of circulating TSP2 levels, or both.

[0017] Also described are kits and immunoassays using a set of capture reagents containing one or more antibody-binding fragments having binding specificity to TSP2, preferably human TSP2.

[0018] Using circulating TSP2 levels as a novel fibrosis biomarker for grade F3 or higher fibrosis in NAFLD enables early liver risk stratification of a large number of NAFLD patients, regardless of the presence or absence of concomitant type 2 diabetes. Patients with advanced fibrosis and high circulating TSP2 levels indicating a high risk of fibrosis progression can be identified for referral to a hepatologist for further evaluation and more close monitoring for the development of adverse hepatic outcomes (such as cirrhosis, varices, and liver cancer). Furthermore, these patients can be given priority in receiving antidiabetic drugs that may improve hepatic fibrosis, liver dysfunction, and / or fat content, and, especially in places with limited medical resources, novel NAFLD treatments where clinically available. [Brief explanation of the drawing]

[0019] [Figure 1] This graph shows receiver operating characteristic curves for identifying fibrosis of F3 or higher in study participants, with and without including circulating TSP2 levels as a clinical risk factor. The data shown are AUROC, with their 95% CI shown in parentheses. AUROC is the lower region of the receiver operating characteristic curve; TSP2 is thrombospondin 2; BMI is the body mass index; and AST is aspartate aminotransferase. [Modes for carrying out the invention]

[0020] I. Definition As used herein, the term “progressive fibrosis” refers to hepatic fibrosis characterized by non-invasive detection using vibration-controlled transient elastography, having grade F3 or higher, graded by LS cutoffs: F3 at 9.6–11.4 kPa and F4 at ≥11.5 kPa (M probe); F3 at 9.3–10.9 kPa and F4 at ≥11.0 kPa (XL probe) (Kwok et al., Gut;65:1359-1368(2016)).

[0021] As used herein, the term “biomarker” refers to molecular, histological, radiographic, and / or physiological characteristics measured as indicators of normal biological processes, pathogenic processes, or responses to interventions or exposures, including procedural interventions. Biomarkers may be diagnostic and / or prognostic biomarkers used for detecting tissue conditions or diseases, monitoring tissue conditions or diseases, and / or predicting tissue conditions or diseases. For example, a measurement of a biomolecule that is a biomarker may not only provide information about a tissue condition as a diagnostic biomarker, but also provide information about future changes in the tissue condition as a prognostic biomarker. Other examples of biomarkers include body mass index (BMI) as a physiological biomarker, or tissue elasticity as a radiographic biomarker, both of which can be diagnostic and prognostic biomarkers.

[0022] As used herein, the terms “non-invasive” or “by means of detection” refer to a method of obtaining information about an organ of interest without physically taking a sample from it, for example, without performing a biopsy of the organ of interest. For example, non-invasive detection of advanced hepatic fibrosis means detecting advanced hepatic fibrosis without performing a liver biopsy.

[0023] As used herein, the term “antibody” refers to antibodies such as polyclonal or monoclonal immunoglobulin molecules. In addition to intact immunoglobulin molecules, this also includes fragments or polymers of these immunoglobulin molecules, and human or humanized versions of immunoglobulin molecules or fragments thereof, as long as the molecules maintain their ability to bind to epitopes such as the TSP2 epitope. Antibodies can be tested for desired activity using in vitro assays or similar methods, and their in vivo treatment activity and / or diagnostic activity can then be confirmed and quantified according to known clinical trial methods.

[0024] In some embodiments, the antibody is a monoclonal antibody or a conjugated fragment thereof. A monoclonal antibody is an antibody in which individual antibodies within a population are identical.

[0025] As used herein, the term “isolated antibody” refers to an antibody that substantially contains no other antibodies with different antigen specificities (for example, an isolated antibody that specifically binds to TSP2 substantially contains no antibodies that specifically bind to antigens other than TSP2). The isolated antibody specifically binds to an epitope, isoform, or variant of TSP2. Furthermore, the isolated antibody may not substantially contain other cellular material and / or chemical substances.

[0026] As used herein, terms such as “binding fragment,” “antigen-binding fragment,” and “antibody-binding fragment” refer to one or more portions of an antibody that include the CDR of the antibody and, optionally, framework residues constituting the antigen-recognition site of the “variable region” of the antibody, and that exhibit the ability to bind immunospecifically to an antigen. Such fragments include Fab', F(ab')2, Fv, single-chain Fv(ScFv), and their mutants and variants, as well as naturally occurring variants.

[0027] As used herein, the term “fragment” refers to a peptide or polypeptide comprising an amino acid sequence of at least 5 consecutive amino acid residues, at least 10 consecutive amino acid residues, at least 15 consecutive amino acid residues, at least 20 consecutive amino acid residues, at least 25 consecutive amino acid residues, at least 40 consecutive amino acid residues, at least 50 consecutive amino acid residues, at least 60 consecutive amino acid residues, at least 70 consecutive amino acid residues, at least 80 consecutive amino acid residues, at least 90 consecutive amino acid residues, at least 100 consecutive amino acid residues, at least 125 consecutive amino acid residues, at least 150 consecutive amino acid residues, at least 175 consecutive amino acid residues, at least 200 consecutive amino acid residues, or at least 250 consecutive amino acid residues.

[0028] The variable region may also be substituted and modified in a manner that does not exclude the binding and binding specificity of the variable region or CDR. For disclosed antibodies and polypeptides having substitutions, modifications, or removals of parts of the antibody other than the variable region (or CDR), it is preferable that the sequence of the variable region and the CDR sequence are the variable region or CDR of the disclosed monoclonal antibody, or modeled after them.

[0029] As used herein, the terms “binding specificity,” “specificity,” “specifically reacts,” “specifically interacts,” or “specific to” refer to the ability of an antibody or other drug to detectably bind to an epitope presented on an antigen, such as the TSP2 epitope, but to have relatively little detectable reactivity with other structures. Specificity can be determined relatively by binding assays or competitive assays, for example, using a Biacore instrument. Specificity is indicated by the affinity / affinity ratio of binding to a specific antigen and nonspecific binding to other unrelated molecules, for example, about 5:1, about 10:1, about 20:1, about 50:1, about 100:1, or about 10000:1 or higher. For the disclosed antibodies and polypeptides, “bispecificity” and similar terms refer to an antibody or polypeptide containing at least two different specific binding elements, each specifically binding to a different epitope or ligand.

[0030] As used herein, the terms “detect,” “determine,” or “decide” typically refer to obtaining information. Detection or determination may involve any of the various techniques available to those skilled in the art, including, for example, certain techniques expressly mentioned herein. Detection or determination may include the manipulation of physical samples, the consideration and / or manipulation of data or information, the use of a computer or other processing device adapted to perform relevant analysis, and / or the receipt of relevant information and / or material from a source. Detection or determination may also mean comparing an obtained value to a known value, such as a known test value, a known control value, or a threshold. Detection or determination may also mean forming a conclusion based on the difference between the obtained value and a known value.

[0031] As used herein, the term “sensitivity” refers to the ability of a test to accurately identify true positives, i.e., subjects having hepatic fibrosis. For example, sensitivity can be expressed as a percentage, i.e., the proportion of actual positives that are correctly identified (e.g., the proportion of subjects with hepatic fibrosis that are accurately identified by the test as having hepatic fibrosis). Highly sensitive tests have a low false-negative rate, i.e., the rate at which cases with hepatic fibrosis are not identified as hepatic fibrosis. Generally, the disclosed assays and methods have a sensitivity of at least about 80%, at least about 85%, at least about 90%, at least 92%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or at least 100%.

[0032] As used herein, the term “specificity” refers to the ability of a test to accurately identify true negatives, i.e., subjects who do not have hepatic fibrosis. For example, specificity can be expressed as a percentage, which is the proportion of actual negatives that are correctly identified (e.g., the proportion of subjects who do not have hepatic fibrosis that are correctly identified as not having hepatic fibrosis by the test). Highly specific tests have a low proportion of false positives, i.e., patients who do not have hepatic fibrosis but are suggested by the test to have it. Generally, the disclosed methods have a specificity of at least about 60%, at least about 70%, at least about 80%, at least about 90%, at least 92%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or at least 100%.

[0033] As used herein, the term “accurate” refers to the ability of a test to produce highly sensitive and highly specific results, such as sensitivity above approximately 80% and specificity above approximately 60%, sensitivity above approximately 85% and specificity above approximately 65%, or sensitivity above approximately 90% and specificity above approximately 80%.

[0034] As used herein, the term “sample” means a bodily fluid, body smear, cell, tissue, organ, or part thereof isolated from a subject. A sample may be a single cell or multiple cells. A sample may be a specimen obtained by biopsy (e.g., surgical biopsy). A sample may be cells from a subject placed in or adapted for tissue culture. A sample may be one or more of cells, tissue, serum, plasma, urine, saliva, sputum, and feces. A sample may be one or more of saliva, sputum, tears, sweat, urine, exudate, blood, serum, plasma, or vaginal secretions.

[0035] As used herein, the terms “subject,” “individual,” or “patient” refer to human or non-human mammals. A subject may be a non-human primate, livestock, farm animal, or laboratory animal. For example, a subject may be a dog, cat, goat, horse, pig, mouse, or rabbit. A subject may also be human. A subject may be healthy, but may also suffer from or be susceptible to disease, disability, or condition. A patient refers to a subject suffering from disease or disability. The term “patient” includes human and veterinary subjects.

[0036] A "control" sample or value refers to a sample that serves as a reference for comparison with a test sample, usually a known reference. For example, a test sample may be taken from a test subject, while a control sample may be taken from a control subject, such as a known normal (non-disease) individual. A control can also represent a mean value collected from a group of similar individuals, e.g., disease patients or healthy individuals with similar medical backgrounds, the same age, weight, etc. A person skilled in the art will recognize that controls can be designed to evaluate any number of parameters.

[0037] As used herein, the terms “treatment” or “to treat” mean administering a composition to a subject or system in order to treat one or more symptoms of a disease. The effect of administering a composition to a subject may be, but is not limited to, cessation of a particular symptom of a condition, reduction or prevention of a condition, reduction of the severity of a condition, complete elimination of a condition, stabilization or delay of the onset or progression of a particular event or characteristic, or minimization of the likelihood of a particular event or characteristic occurring.

[0038] As used herein, the terms “effective dose” and “therapeutic effective dose” are interchangeable when applied to the nanoparticles, treatment agents, and pharmaceutical compositions described herein, and refer to the amount necessary to produce the desired therapeutic effect. For example, an effective dose is the level at which the composition and / or treatment agent, or pharmaceutical composition, is effective in treating, curing, or alleviating the symptoms of the disease to which it is administered. Depending on the specific therapeutic objective sought, the effective dose depends on a variety of factors, including the disease being treated and its severity and / or stage of onset / progression, the bioavailability and activity of the specific compound and / or anti-cancer agent, or pharmaceutical composition used, the route or method of administration, and the site of introduction in the target.

[0039] The descriptions of value ranges in this specification are merely intended to serve as a simplified method for individually referring to each individual value within that range, unless otherwise stated herein, and each individual value is incorporated into the specification as if it were individually stated herein.

[0040] The use of the term "approximately" is intended to represent values ​​that are above or below the stated values ​​within a range of approximately + / - 10%, in other embodiments the values ​​may be above or below the stated values ​​within a range of approximately + / - 5%, in other embodiments the values ​​may be above or below the stated values ​​within a range of approximately + / - 2%, and in other embodiments the values ​​may be above or below the stated values ​​within a range of approximately + / - 1%.

[0041] II. Biomarkers for advanced liver fibrosis Biomarkers for non-invasively detecting advanced liver fibrosis in a subject, or for determining the risk of developing advanced liver fibrosis, include molecular biomarkers, radiographic biomarkers, and / or physiological biomarkers. Biomarkers may be used individually or in any combination. For example, any one or more molecular biomarkers may be used with any one or more radiographic biomarkers and / or any one or more physiological biomarkers. In some embodiments, one or more molecular biomarkers are used with one or more physiological biomarkers and / or one or more radiographic biomarkers to detect or predict the risk of developing advanced liver fibrosis.

[0042] Typically, molecular biomarkers include TSP2 and aspartate transaminase (AST). Typically, physiological biomarkers include body mass index (BMI, kg / m²). 2 Typically, biomarkers for radiography include liver stiffness (LS, kPa) and controlled attenuation parameter (CAP, dB / m) readings from vibration-controlled transient elastography.

[0043] A. Thrombospongin-2 in liver fibrosis The TSP family includes Ca 2+The TSP family comprises five members (TSP1-5) representing multimeric glycoproteins that bind to and interact with other ECM proteins, contributing to intercellular and cell-ECM binding. The TSP family is divided into two subgroups: trimer subgroup A (TSP1 and TSP2) and pentamer subgroup B (TSP3, TSP4, and TSP5). TSPs have a complex multi-domain structure. The C-terminal domain, type III repeat, and epidermal growth factor (EGF)-like repeat are present in all TSPs, highlighting the TSP family. Oligomerization domains are also found in all family members, but are more diverse compared to other shared structures. Subgroup A contains three EGF-like repeats, a type I repeat (thrombospongin repeat, also called TSR), a von Willebrand factor type C (vWC) domain, and an N-terminal domain. Subgroup B contains four EGF-like repeats, but lacks a vWC domain and TSR (Chistiakov et al., Int.J.Mol.Sci., 18, 1540:1-29 (2017)).

[0044] The TSP2 protein exists in both cell-bound and circulating forms. TSP2 is a member of a functionally related group of extracellular matrix (ECM) glycoproteins and can mediate the construction of the extracellular matrix, cell-matrix interactions, the degradation of matrix metalloproteinases (MMP)-2 and MMP-9, and the inhibition of angiogenesis. In addition to angiogenesis, TSP2 has been reported to interact with multiple cell receptors, growth factors, and ECM proteins, regulating apoptosis, cell proliferation, and cell adhesion. TSP2 expression and its prognostic implications have been studied in several cancers (Tian et al., JBUON;23(5):1331-1336(2018)).

[0045] TSP2 is a 150 kDa calcium-binding protein secreted by various types of cells. The amino acid sequence of human TSP2 is as follows:

[0046] TIFF0007837065000001.tif148168TIFF0007837065000002.tif222168TIFF0007837065000003.tif220168TIFF0007837065000004.tif19168

[0047] The mRNA sequence of human TSP2 is located under accession number NM_001381939.1.

[0048] In humans, TSP2 is encoded by the gene THBS2 (gene ID: 7058).

[0049] B. Progressive liver fibrosis Generally, advanced hepatic fibrosis refers to liver fibrosis characterized by F3 grade or higher fibrosis, as determined by non-invasive detection using oscillatory-controlled transient elastography. Grade F3 or higher fibrosis is graded according to the LS cutoff: F3 is 9.6-11.4 kPa and F4 is ≥11.5 kPa (M probe); F3 is 9.3-10.9 kPa and F4 is ≥11.0 kPa (XL probe) (Kwok et al., Gut;65:1359-1368 (2016)).

[0050] Progressive liver fibrosis can occur as a pathological condition within NAFLD. NAFLD is associated with metabolic disorders and other systemic diseases. NAFLD is recognized as an independent risk factor for metabolic syndrome, type 2 diabetes, cardiovascular disease (CVD), and chronic kidney disease (CKD). The severity of NAFLD is associated with the development of disease.

[0051] NAFLD encompasses a wide range of liver conditions, from simple fatty degeneration to non-alcoholic steatohepatitis (NASH) and advanced liver fibrosis. Therefore, NASH may or may not be accompanied by advanced liver fibrosis.

[0052] Fatty degeneration, also known as steatosis, is the abnormal accumulation of fat (lipids) within cells or organs. Fatty degeneration can occur in the liver, the major organ for lipid metabolism, and this condition is commonly referred to as fatty liver disease.

[0053] Vibration-controlled transient elastography (VCTE®), offered by Fibroscan® (Echosens, Paris, France), is a non-invasive test for detecting fatty degeneration and fibrosis of the liver using controlled damping parameters (CAP®) and liver stiffness (LS), respectively.

[0054] Fibroscan® measurements typically include a variety of probes to ensure measurement accuracy and consistency. The probe model range usually matches the measurement area of ​​most patient morphologies. By adjusting the measurement area according to the distance from the skin surface to the liver, a consistent exploration volume of 3 cubic cm can be maintained. This is achieved by the following three probes:

[0055] S+ probe, pediatric: Designed for pediatric patients with a chest circumference of less than 75 cm; M+ probe, medium size: Designed for adults with a skin-to-liver capsule distance of 25 mm or less; and XL+ probe, extra large: Designed for heavier adults with a skin-to-liver capsule distance exceeding 35mm.

[0056] Typically, non-invasive liver fibrosis (stiffness) can be measured by VCTE®, and non-invasive fatty liver degeneration can be measured by CAP®. FibroScan® allows for simultaneous measurement of stiffness (kPa) and CAP (dB / m). The scan's S, M, and XL probes are suitable for all patient morphologies. CAP is a tool for non-invasive assessment and quantification of fatty degeneration. CAP is a measure of ultrasound attenuation, corresponding to the decrease in ultrasound amplitude as ultrasound propagates through the liver. CAP is defined as follows: CAP and liver stiffness are measured simultaneously in the same liver volume; CAP is expressed in decibels per meter (dB / m); This is enhanced by an advanced guidance process based on VCTE that ensures this.

[0057] Hepatic steatosis is graded according to the published CAP cutoffs: mild steatosis 248–267 dB / m, moderate steatosis 268–279 dB / m, and severe steatosis ≥280 dB / m (Karlas et al., J Hepatol;66:1022-1030) (2017).

[0058] Progressive hepatic fibrosis may be detected regardless of the presence of mild, moderate, or severe hepatic steatosis. Table 1 shows the detection of progressive hepatic fibrosis in subjects with mild, moderate, or severe hepatic steatosis.

[0059] C. Circulating TSP2 as a biomarker for advanced liver fibrosis The circulating level of TSP2 in a subject may be used to detect the presence of advanced hepatic fibrosis in the subject or to detect the risk of developing advanced hepatic fibrosis in the subject.

[0060] 1. TSP2 for detecting advanced liver fibrosis The circulating level of TSP2 is significantly associated with the presence of advanced liver fibrosis (F3 fibrosis or higher) at the initial assessment.

[0061] When the circulating level of TSP2 is approximately 2 ng / ml or higher, it usually provides information about the presence or risk of developing advanced liver fibrosis. Typically, the circulating level of TSP2 is measured using assays that detect TSP2 on a nanogram / ml scale. The circulating level of TSP2 in samples taken from subjects may range from approximately 0.2 ng / ml to approximately 10 ng / ml.

[0062] Circulating levels of TSP2 are typically a biomarker for pre-existing advanced liver fibrosis, and advanced liver fibrosis is detected when the circulating level of TSP2 in a sample from a subject is above approximately 3.6 ng / ml, such as between approximately 3.6 ng / ml and 10 ng / ml. Typically, when the circulating level of TSP2 in a sample from a subject is above approximately 3.6 ng / ml, circulating levels of TSP2 can detect advanced liver fibrosis with a sensitivity of approximately 80% or higher, a specificity of approximately 60% or higher, and a negative predictive value of approximately 90% or higher.

[0063] When combined with other physiological and / or radiographic biomarkers, detection sensitivity can be over 80%, and specificity can be over 80%. When circulating levels of TSP2 are combined with body mass index (BMI) and serum aspartate aminotransferase (AST), circulating levels of TSP2 can detect advanced liver fibrosis with sensitivity over 80% and specificity over 80%.

[0064] In patients with type 2 diabetes, a circulating TSP2 level of approximately 3.6 ng / ml may be a cutoff value for detecting advanced liver fibrosis. In patients with type 2 diabetes, a circulating TSP2 level of approximately 3.6 ng / ml or higher may indicate advanced liver fibrosis.

[0065] 2. TSP2 for the risk of developing advanced liver fibrosis The circulating level of TSP2 in the initial assessment also showed a significant association with the progression of liver fibrosis and can be used to detect the risk of developing progressive liver fibrosis (F3 fibrosis or higher) over time.

[0066] Circulating levels of TSP2 are typically advantageous in predicting the risk of developing advanced liver fibrosis. Typically, circulating levels of TSP2 are measured using methods that detect TSP2 on a nanogram / ml scale.

[0067] Typically, detecting the risk of developing progressive liver fibrosis over time involves measuring the circulating levels of the TSP2 biomarker and detecting the risk of developing progressive liver fibrosis. Typically, subjects have a 2.82-fold increased risk of developing progressive liver fibrosis over time for every unit increase in logarithmically transformed serum TSP2 levels measured in ng / ml. Typically, this period is approximately 0.1 to 3 years from the time sample is obtained from the subject, from the time circulating levels of TSP2 in the sample are measured, or both.

[0068] Combining TSP2 levels with other physiological and / or radiographic biomarkers can more accurately detect the risk of developing advanced liver fibrosis. For example, combining circulating TSP2 levels with body mass index (BMI), platelet count, and CAP values ​​allows for the detection of the risk of developing advanced liver fibrosis with higher NRI and IDI levels based on circulating TSP2 levels.

[0069] In subjects who may have one or more of the following conditions: metabolic syndrome, type 2 diabetes, cardiovascular disease (CVD), or chronic kidney disease (CKD), the present method can detect the risk of developing progressive liver fibrosis over time in these patients.

[0070] 3. Target The beneficiaries of the disclosed methods are human beings. These beneficiaries may be healthy, or they may be suffering from or susceptible to disease, disability, or condition.

[0071] The subjects may not have any disease. The subjects may have one or more of the following conditions: metabolic syndrome, type 2 diabetes, CVD, and CKD. The subjects may have metabolic syndrome with one or more of the following conditions: obesity, insulin resistance, diabetes, dyslipidemia, and hypertension. The subjects may have diabetes, liver disease, or a combination of diabetes and liver disease. The subjects may have type 2 diabetes. The subjects may have NAFLD. The subjects may have both type 2 diabetes and NAFLD. The subjects may or may not have NASH.

[0072] III. Measurement Method of TSP2 A. Assay for measurement 1. Affinity chromatography The circulating level of TSP2 can be detected by affinity chromatography using a resin or column immobilized with a TSP2 ligand or anti-TSP2 antibody. The target protein TSP2 is typically adsorbed as the sample or diluted sample passes through the column, while other substances are washed away. The target substance is then eluted and becomes available for analysis by reversing the conventional experimental conditions.

[0073] TSP2 binds to extracellular matrix ligands such as TGF-β-1, histidine-rich glycoprotein, TSG6, heparin, MMP-2, and heparan sulfate proteoglycans. TSP2 also binds to cell surface receptors including CD36, CD47, LDL receptor-associated protein-1 (via calreticulin), integrins α-V / β-3, α-4 / β-1, and α-6 / β-1. Chromatographic columns may also contain antibodies or antibody-conjugated fragments for capturing TSP2. One or more of these ligands may be capture reagents or sets of capture reagents used in affinity chromatography for the capture and purification of TSP2.

[0074] Once separated from the column and eluted, the concentration of TSP2 can be detected using a standard protein quantification assay.

[0075] 2. Immunoassay This method for measuring the circulating level of TSP2 includes an immunoassay in which the polypeptide of the biomarker is evaluated or detected by interaction with a biomarker-specific antibody, an antibody-conjugated fragment, a combination of different antibodies, or a combination of different antibody-conjugated fragments. The biomarker can be detected qualitatively or quantitatively. Exemplary immunoassays that can be used for the detection of the polypeptide and protein of the biomarker include, but are not limited to, radioimmunoassays, ELISA, immunoprecipitation assays, Western blotting, fluorescence immunoassays, and immunohistochemistry, flow cytometry, protein arrays, multiplex bead arrays, magnetic trapping, in vivo imaging, fluorescence resonance energy transfer (FRET), and fluorescence recovery / localization after photobleaching (FRAP / FLAP).

[0076] Some immunoassays, such as ELISA, may require antibodies or ligands specific to two different biomarkers (e.g., a capture ligand or antibody, and a detection ligand or antibody). In certain embodiments, the protein biomarker is captured by a surface ligand or antibody, and the protein biomarker is labeled with an enzyme. In one example, a detection antibody conjugated to biotin or streptavidin can be used to create a biotin-streptavidin conjugate to an enzyme containing biotin or streptavidin. A signal is generated when the enzyme substrate is converted into a colored molecule, and the intensity of the color in the solution is quantified by measuring the absorbance with a light sensor. Assays may utilize chromogenic reporters and substrates that produce an observable color change to indicate the presence of a protein biomarker. Fluorescence, electrochemiluminescence, and real-time PCR reporters have also been investigated to generate quantifiable signals.

[0077] Some assays optionally include immobilizing one or more antibodies on a solid support before contacting the antibody with the sample to facilitate washing and subsequent isolation of the complex. Examples of solid supports include, for example, glass or plastic in the form of microtiter plates, sticks, beads, or microbeads. Antibodies can also be conjugated to probes, substrates, or PROTEINCHIP® arrays.

[0078] Flow cytometry is a laser-based technique that can be used to count, classify, and detect protein biomarkers by suspending particles in a flow of liquid and passing them through an electronic detector. Flow cytometers have the ability to distinguish different particles based on color. Differential staining of particles with different dyes that emit light at two or more different wavelengths allows for differentiation of particles. Multiplex analysis, such as FLOWMETRIX™, is described in Fulton, et al., Clinical Chemistry, 43(9):1749-1756 (1997), and allows multiple individual assays to be performed simultaneously in a single tube using the same sample.

[0079] In some specific embodiments, biomarker levels are measured using LUMINEX XMAP® technology. LUMINEX XMAP® is often compared to conventional ELISA technology, which has the limitation of being able to measure only a single analyte. The difference between ELISA and LUMINEX XMAP® technology lies primarily in the support structure of the capture antibody. Unlike conventional ELISA, the capture antibody in LUMINEX XMAP® is covalently bound to the bead surface, allowing for a larger surface area and effectively enabling the matrix or free solution / liquid environment to react with the analyte. The suspended beads allow for the flexibility of assays in singleplex or multiplex formats.

[0080] Commercial formats incorporating LUMINEX XMAP® technology include, for example, the BIO-PLEX® multiplex immunoassay system, which allows for the multiplexing of up to 100 different assays within a single sample. This technology involves a set of 100 distinctly color-coded beads created using two fluorescent dyes in different ratios. These beads can be further conjugated with reagents specific to particular bioassays. These reagents may include antigens, antibodies, oligonucleotides, enzyme substrates, or receptors. This technology enables multiplex immunoassays where one antibody against a specific analyte is conjugated to a set of beads of the same color, and a second antibody against the analyte is conjugated to a fluorescent reporter dye label. Using beads of different colors allows for simultaneous multiplex detection of many other analytes within the same sample. Dual-detection flow cytometers can be used to classify different assays by bead color in one channel and determine the concentration of the analyte by measuring the fluorescence of the reporter dye in the other channel.

[0081] In some specific embodiments, biomarker levels are measured using Quanterix's SIMOA® technology. SIMOA® technology (named after single molecule array) is based on the isolation of individual immunocomplexes on paramagnetic beads using standard ELISA reagents. The key difference between Simoa and conventional immunoassays lies in its ability to capture single molecules in femtoliter-sized wells, enabling "digital" readings of individual beads and determining whether or not they are bound to the target analyte. The digital nature of this technology allows for an average sensitivity improvement of 1000-fold compared to conventional assays with a CV of less than 10%. The commercially available SIMOA® technology platform offers multiplexing options of up to 10 plexes with various analyte panels, enabling the automation of assays.

[0082] Multiplexing experiments can generate large amounts of data. Therefore, in some embodiments, computer systems are used to automate and control data acquisition setup, organization, and interpretation.

[0083] Typically, assays for detecting TSP2 include immunoassays with detection limits between approximately 0.01 ng / ml and approximately 0.18 ng / ml, for example between approximately 0.01 ng / ml and approximately 0.16 ng / ml, or at the lowest detection limit such as approximately 0.156 ng / ml. In some embodiments, assays for detecting TSP2 have intra-assay and inter-assay accuracies of less than 4.6% and 7.2%, respectively.

[0084] 3. Comparison Methods involving the analysis of one or more biomarkers typically involve comparison with a control. For example, the level of a biomarker detected in a sample collected from a subject can be compared to a control. Appropriate controls will be known to those skilled in the art. Controls may include, for example, healthy subjects such as subjects without disease or disability, or standards obtained from unaffected tissue from the same subjects. Controls may be single values, pooled values, or mean values ​​from similar individuals using the same assay. Reference indices can be established by using subjects diagnosed with different diseases or disabilities with varying degrees of disease severity or prognosis.

[0085] B. Sensitivity and specificity of liver fibrosis detection Sensitivity can be expressed as a percentage, which is the proportion of actual positive cases that are correctly identified (e.g., the proportion of subjects with advanced hepatic fibrosis that are accurately identified by the test as having advanced hepatic fibrosis). Highly sensitive tests have a low rate of false negatives, i.e., cases where individuals have advanced hepatic fibrosis but are not identified by the test. Generally, disclosed assays and methods have a sensitivity of at least 80%, at least 90%, at least 92%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or at least 100%.

[0086] Specificity can be expressed as a percentage, which is the proportion of actual negatives that are correctly identified (e.g., the proportion of subjects without progressive hepatic fibrosis that are accurately identified by the test as not having progressive hepatic fibrosis). Highly specific tests have a low proportion of false positives, i.e., patients who do not have progressive hepatic fibrosis but are suggested by the test. Generally, the disclosed method has a specificity of at least 60%, at least 70%, at least 80%, at least 90%, at least 92%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or at least 100%.

[0087] The positive and negative predictive values ​​are influenced by the prevalence of the disease in the population being tested. In environments with high prevalence, a person who tests positive is more likely to actually have the disease than when testing is conducted in a population with low prevalence.

[0088] Typically, when the circulating level of TSP2 in a sample from a subject is greater than approximately 3.6 ng / ml, this method detects advanced liver fibrosis with a sensitivity of over 80%, a specificity of over 60%, and a negative predictive value of over 90%.

[0089] IV. Kit for TSP2 measurement A set of capture reagents having binding specificity to TSP2 can be packaged together in any suitable combination as a kit useful for performing or assisting in the disclosed method. It is useful if the kit components within a given kit are designed and adapted to be used together in the disclosed method.

[0090] For example, a kit comprising one or more sets of capture reagents is disclosed. The kit may include a dilution buffer, a sample buffer, a control reagent, an elution reagent, and a detection reagent. The kit may include substrates for the capture, elution, and detection of TSP2. The kit may include substrates for the capture and detection of TSP2. Instructions for use may be included. [Examples]

[0091] Example 1. Serum TSP2 levels as a diagnostic and prognostic marker for progressive fibrosis in non-alcoholic fatty liver disease with type 2 diabetes. Research design and methods research participants All participants were recruited from the Hong Kong West Diabetes NAFLD Cohort, comprised of patients regularly followed up at the Diabetes Clinic of Queen Mary Hospital in Hong Kong. Treatment-continuing patients, Chinese aged 21 to 80 years, who had participated in diabetes complication screening since January 2017, were invited to a prospective study aimed at identifying risk factors for NAFLD fibrosis progression in type 2 diabetes. VCTE was used to assess hepatic steatosis and fibrosis at regular intervals. Patients with a history of active malignancy, associated chronic hepatitis B or C, or other liver diseases including alpha-1 antitrypsin deficiency, Wilson's disease, autoimmune hepatitis, drug-induced liver injury, and primary biliary cholangitis, or those on prolonged use of lipogenic drugs such as amiodarone, methotrexate, or tamoxifen were excluded. Furthermore, patients with daily alcohol consumption exceeding 30g for men and 20g for women were excluded (Chalasani et al., Hepatology; 67:328-357 (2018)). This study protocol was approved by the Institutional Review Board of the Hospital Authority Hong Kong West Cluster. Written informed consent was obtained from all recruited participants prior to any surgery related to the study.

[0092] This study, which evaluated the relationship between circulating TSP2 levels and NAFLD in type 2 diabetes, included only participants who had hepatic steatosis at baseline and were recruited between January 2017 and June 2020. Furthermore, analyses examining the expected association between circulating TSP2 levels and progression of hepatic fibrosis included only participants who did not have advanced fibrosis or cirrhosis at baseline. The levels of hepatic steatosis and fibrosis were defined by measuring the control attenuation parameter (CAP) and liver stiffness (LS), respectively, using oscillatory controlled transient elastography (VCTE).

[0093] Clinical and biochemical evaluation All patients at the diabetes clinic underwent regular assessments for complications as part of routine clinical management. This was to confirm blood glucose control, cardiovascular risk factors, and the presence of diabetic complications. Anthropometric parameters such as body weight (BW), height (BH), body mass index (BMI), waist circumference (WC), and blood pressure (BP) were measured. Fasting blood was collected for testing of plasma glucose, lipids, glycated hemoglobin (HbA1c), complete blood count, liver function, and kidney function. Albuminuria status was assessed in random urine samples and classified by the ratio of albumin to creatinine in the urine (<30 mg / g [A1], ≥30 to <300 mg / g [A2], and ≥300 mg / g [A3]). In addition, all patients underwent regular retinal photography and / or evaluation by an ophthalmologist. For individuals who consented to participate in the NAFLD cohort study, smoking status, alcohol consumption, detailed medical history, medication history, and family history were obtained using a standardized questionnaire, and prothrombin time was also confirmed. Furthermore, fasting blood was aliquoted and stored at -70°C for assays of novel NAFLD biomarkers.

[0094] Conventional fibrosis scores, including the NAFLD fibrosis score (NFS) and the Fibrosis-4 index (FIB-4), were determined using published formulas and classified based on recommended cutoffs (Vilar-Gomez and Chalasani, J Hepatol; 68: 305-315 (2018)).

[0095] Measurement of TSP2 level Serum TSP2 levels were measured using an enzyme-linked immunosorbent assay (ELISA) kit for human TSP-2, employing a pair of monoclonal antibodies that recognize specific sites of human TSP2 (Antibody and Immunoassay Services, University of Hong Kong). The antibodies used were IgG. Serum samples were diluted 2-fold in this assay. The secondary antibody was biotin-labeled.

[0096] The assay was highly specific to human TSP2 and showed no cross-reactivity to human TSP1, TSP3, TSP4, and TSP5. The lowest detection limit was 0.156 ng / ml, and intra-assay and inter-assay precisions were <4.6% and <7.2%, respectively.

[0097] Vibration-controlled transient elastography All participants underwent VCTE at baseline and thereafter every 12–18 months for reassessment. VCTE was performed after at least 8 hours of fasting. CAP and LS were measured using Fibroscan® (Echosens, Paris, France) by two operators with experience of over 500 measurements. Inter-rater reliability was satisfactory, as reflected in the intraclass correlations of 0.98 for CAP and 0.97 for LS. Both CAP and LS were expressed as the median of 10 reliable measurements, defined as having an interquartile range of less than 30% and a success rate greater than 60%. To ensure the validity of the results, only CAP values ​​with an interquartile range of 40 dB / m or greater were used (Wong et al., J Hepatol;67:577-584 (2017)). In the initial trial, all tests were performed using the M probe, and BMI was 30 kg / m². 2 If the value exceeded a certain limit, an XL probe was used.

[0098] Hepatic steatosis was graded according to the published CAP cutoffs: mild steatosis 248-267 dB / m, moderate steatosis 268-279 dB / m, and severe steatosis ≥280 dB / m (Karlas et al., J Hepatol; 66:1022-1030 (2017)). Progressive fibrosis (F3) and cirrhosis (F4) were graded according to the LS cutoffs: F3 9.6-11.4 kPa and F4 ≥11.5 kPa (M probe); F3 9.3-10.9 kPa and F4 ≥11.0 kPa (XL probe) (Kwok et al., Gut; 65:1359-1368 (2016)). Progression of fibrosis was defined as the development of fibrosis of F3 or higher (i.e., advanced fibrosis or cirrhosis) as of December 31, 2020, based on a reassessment of VCTE.

[0099] Definition of clinical variables Central obesity was defined as a waist circumference (WC) of ≥80 cm for women and ≥90 cm for men. Hypertension was defined as a blood pressure of ≥140 / 90 mmHg or the presence of antihypertensive medication. Dyslipidemia was defined as fasting triglycerides (TG) ≥150 mg / dL, high-density lipoprotein cholesterol (HDL-C) less than 40 mg / dL for men and <50 mg / dL for women, and low-density lipoprotein cholesterol (LDL-C) ≥100 mg / dL, or the presence of lipid-lowering medication. Diagnoses of coronary heart disease (CHD) and stroke were based on the diagnostic codes of the International Classification of Diseases (ICD-9) 9th edition (CHD: 410, 36.01-10; stroke: 430-438).

[0100] statistical analysis All data were analyzed using R version 3.6.0 (MatchIt Package, DeLong test of two correlated receiver operating characteristic curves) and IBM SPSS Statistics version 26.0 (IBM Corp., Armonk, New York). Data determined to be non-normally distributed by the Kolmogorov-Smirnov test, such as plasma TG, ALT, AST, FIB4, and TSP2 levels, were logarithmically transformed to achieve near-normality before analysis. Values ​​were reported as mean ± standard deviation (SD), median of the 25th and 75th percentiles (for variables with skewed data), or percentages, as needed. Chi-square tests and ANOVA were used to compare categorical and continuous variables, respectively. Multivariate logistic regression analysis was performed to assess independent determinants of the presence and onset of fibrosis ≥ F3, based on the lowest Akaike Information Criterion (AIC) model. Variables that were statistically significant in univariate analysis were included in the multivariate logistic regression analysis. The area under the receiver operating characteristic curve (AUROC) for serum TSP2 was determined with and without clinical risk factors, and the AUROCs of various clinical models were compared using the DeLong method. The optimal cutoff for serum TSP2 levels to identify the presence of fibrosis ≥ F3 was derived based on the point on the ROC curve y=[sensitivity-(1-specificity)] where the Youdenj index (y) was maximized. The predictive performance of various models was further evaluated using category-free net reclassification improvement (NRI) and integrated discrimination improvement (IDI). In all statistical tests, a two-sided p-value < 0.05 was considered significant.

[0101] result Serum TSP2 levels were significantly associated with the presence of fibrosis of F3 or higher in type 2 diabetes. Of the 820 participants with type 2 diabetes and NAFLD included in this study, 138 (16.8%) had baseline fibrosis of F3 or higher. Table 1 summarizes the baseline characteristics of the study participants. Participants with F3 or higher fibrosis were significantly younger, had higher BMI, WC, serum TG, ALT, and AST, and lower HDL-C levels and platelet counts compared to participants without F3 or higher fibrosis. Furthermore, the duration of diabetes was significantly shorter and the prevalence of albuminuria was higher compared to patients without F3 or higher fibrosis. In addition, participants with F3 or higher fibrosis had significantly higher CAP, NFS, and FIB4 values ​​than participants without F3 or higher fibrosis (CAP: 339 dB / m vs. 299 dB / m, p<0.001; NFS: -0.75 vs. -1.13, p=0.001; FIB4: 1.26 vs. 1.05, p<0.001 for all). Notably, median serum TSP2 levels were significantly higher in participants with fibrosis of F3 or higher than in participants without (4.17 ng / ml vs. 2.33 ng / ml, respectively; p<0.001).

[0102] [Table 1]

[0103] Data were expressed as mean ± standard deviation or median (25th to 75th percentile).

[0104] TSP2 is thrombospondin 2; BMI is body mass index; WC is waist circumference; BP is blood pressure; NAFLD is non-alcoholic fatty liver disease; GLP1rA is glucagon-like peptide 1 receptor agonist; SGLT2i is sodium-glucose cotransporter 2 inhibitor; HbA1c is glycated hemoglobin; HDL-C is high-density lipoprotein cholesterol; LDL-C is low-density lipoprotein cholesterol; TG is triglycerides; ALT is alanine aminotransferase; AST is aspartate transaminase; eGFR is estimated glomerular filtration rate; CAP is controlled decay parameter; NFS is fibrosis score for non-alcoholic fatty liver disease; FIB4 is fibrosis-4 index.

[0105] Albuminuria is defined as a urinary albumin-to-creatinine ratio of ≥30 mg / g; the conversion factor from mmol / l to mg / dL for HDL / LDL-C is ×38.9; and the conversion coefficient from mmol / l to mg / dL for TG is ×88.2.

[0106] Table 2 summarizes the associations between baseline clinical variables and increased quartiles of serum TSP2 levels in study participants. Higher quartiles of baseline TSP2 levels were significantly associated with higher baseline BMI (p<0.001), WC (p<0.001), systolic blood pressure (p=0.01), serum HbA1c (p=0.005), TG (p=0.001), ALT (p<0.001), AST levels (p<0.001), and prevalence of albuminuria (p<0.001), but were significantly associated with lower baseline HDL-C (p=0.02), eGFR (p=0.001), albumin levels (p<0.001), and platelet count (p=0.023). Furthermore, higher quartiles of baseline TSP2 levels were also significantly associated with higher stages of hepatic steatosis (p<0.001 for CAP) and fibrosis (NFS, FIB4, and LS; all p<0.001).

[0107] [Table 2] TIFF0007837065000007.tif55168

[0108] TSP2 is thrombospondin 2; BMI is body mass index; WC is waist circumference; BP is blood pressure; HbA1c is glycated hemoglobin; HDL-C is high-density lipoprotein cholesterol; LDL-C is low-density lipoprotein cholesterol; TG is triglycerides; ALT is alanine aminotransferase; AST is aspartate transaminase; eGFR is estimated glomerular filtration rate; CAP is controlled attenuation parameter; LS is hepatic rigidity; NFS is fibrosis score for non-alcoholic fatty liver disease; FIB4 is fibrosis-4 index. Albuminuria is defined as urinary albumin to creatinine ratio ≥ 30 mg / g; the conversion factor from mmol / l to mg / dL for HDL / LDL-C is ×38.9; the conversion factor from mmol / l to mg / dL for TG is ×88.2. Multivariate logistic regression analysis was performed including age, BMI, duration of diabetes, platelet count, serum HDL-C, TG, ALT, AST, CAP, TSP2 levels, and albuminuria. Serum TSP2 levels were independently associated with the presence of fibrosis of F3 or higher at baseline, along with BMI (OR 1.14, 95% CI 1.08-1.20, p<0.001), as well as serum AST (OR 8.01, 95% CI 4.10-15.60, p<0.001) and CAP levels (OR 1.008, 95% CI 1.002-1.014, p=0.01) (odds ratio OR 5.13, 95% CI 3.16-8.32, p<0.001) (Table 3).

[0109] [Table 3]

[0110] The variables included in the analysis were age, BMI, duration of diabetes, albuminuria, HDL-C, TG, ALT, AST, platelet count, CAP, and TSP2 levels. Model selection was based on the Akaike Information Criterion. TSP2 is thrombospondin 2; BMI is the body mass index; HDL-C is high-density lipoprotein cholesterol; TG is triglycerides; ALT is alanine aminotransferase; AST is aspartate aminotransferase; CAP is the controlled decay parameter; OR is the odds ratio; and 95% CI is the 95% confidence interval. Albuminuria was defined as a urinary albumin to creatinine ratio ≥ 30 mg / g.

[0111] The results were similar when BMI was replaced with WC (OR 5.67, 95% CI 3.49-9.22, p<0.001 for TSP2; OR 1.06, 95% CI 1.04-1.08, p<0.001 for WC). Furthermore, in subgroup analysis, the association between serum TSP2 levels and fibrosis of F3 or higher remained significant regardless of NFS or FIB4 levels, but the association was clearly stronger in individuals with higher conventional non-invasive fibrosis scores (Table 4).

[0112] [Table 4]

[0113] The model includes BMI, AST, and CAP.

[0114] TSP2 is thrombospondin-2; OR is odds ratio; 95% CI is 95% confidence interval; FIB4 is fibrosis-4 index; NFS is fibrosis score for non-alcoholic fatty liver disease; BMI is body mass index; AST is aspartate aminotransferase; CAP is controlled decay parameter.

[0115] Performance of serum TSP2 to identify the presence of fibrosis of F3 or higher in VCTE Next, we investigated whether serum TSP2 levels are clinically useful in identifying individuals with F3 or higher fibrosis in VCTE who may require referral to a hepatologist for further evaluation. The AUROC for serum TSP2 alone indicating F3 or higher fibrosis in VCTE was 0.80 (95% CI 0.76-0.84). Notably, when serum TSP2 levels were added to a clinical model consisting of BMI and serum AST, two other independent determinants of F3 or higher fibrosis, the AUROC significantly increased from 0.86 (95% CI, 0.83-0.89) to 0.89 (95% CI 0.86-0.92, p=0.01) (Figure 1). This was accompanied by substantial improvements in both NRI (60.7, 95% CI 53.1-78.3, p<0.001) and IDI (8.1, 95% CI 5.0-11.0, p<0.001). Using an optimal serum TSP2 cutoff of 3.6 ng / ml to identify the presence of fibrosis of F3 or higher, we obtained a sensitivity of 83.6%, specificity of 64.5%, positive predictive value (PPV) of 44.3%, and negative predictive value (NPV) of 92.1%.

[0116] Baseline serum TSP2 levels were independently associated with the development of fibrosis of F3 or higher in patients with type 2 diabetes. Of the 682 participants who did not have F3 or higher fibrosis at baseline, 491 underwent reassessment VCTE during the study period, excluding 90 participants who refused to return due to COVID-19, 17 who refused further TE, 19 who were unable to be followed up, 6 who died, and 59 who were not scheduled for reassessment TE. At a median follow-up of 1.5 years, 43 of the 491 participants (8.8%) developed F3 or higher fibrosis.

[0117] Participants with fibrosis of stage F3 or higher were significantly younger, had higher baseline BMI, WC, ALT, AST, CAP, and NFS levels, and lower serum HDL-C and platelet counts than participants without stage F3. Importantly, participants with stage F3 or higher fibrosis had significantly higher baseline serum TSP2 levels than participants without stage F3 (3.21 ng / ml vs. 2.29 ng / ml, p<0.001) (Table 5).

[0118] [Table 5]

[0119] Data were expressed as mean ± standard deviation or median (25th–75th percentile). TSP2 is thrombospondin 2; BMI is body mass index; WC is waist circumference; BP is blood pressure; NAFLD is non-alcoholic fatty liver disease; GLP1rA is glucagon-like peptide 1 receptor agonist; SGLT2i is sodium-glucose cotransporter 2 inhibitor; HbA1c is glycated hemoglobin; HDL-C is high-density lipoprotein cholesterol; LDL-C is low-density lipoprotein cholesterol; TG is triglyceride; ALT is alanine aminotransferase; AST is aspartate transaminase; eGFR is estimated glomerular filtration rate; CAP is controlled attenuation parameter; NFS is fibrosis score for non-alcoholic fatty liver disease; FIB4 is fibrosis-4 index. Albuminuria is defined as a urinary albumin-to-creatinine ratio of ≥30 mg / g; the conversion factor from mmol / l to mg / dL for HDL / LDL-C is ×38.9; and the conversion factor from mmol / l to mg / dL for TG is ×88.2.

[0120] Multivariate logistic regression analysis of baseline age, BMI, serum HDL-C, ALT, AST, platelet count, CAP, and TSP2 levels revealed that baseline serum TSP2 levels were independently associated with the development of fibrosis of F3 or higher (OR 2.82, 95% CI 1.37-5.78, p=0.005), along with baseline BMI (OR 1.12, 95% CI 1.03-1.21, p=0.007), platelet count (OR 0.992, 95% CI 0.987-0.998, p=0.01), and CAP levels (OR 1.02, 95% CI 1.01-1.03, p<0.001) (Table 6).

[0121] [Table 6]

[0122] The variables included in the analysis were age, BMI, HDL-C, ALT, AST, platelet count, CAP, and TSP2 level. Model selection was based on the Akaike Information Criterion.

[0123] TSP2 is thrombospondin 2; BMI is the body mass index; HDL-C is high-density lipoprotein cholesterol; ALT is alanine aminotransferase; AST is aspartate aminotransferase; CAP is controlled decay parameter; OR is odds ratio; 95% CI is 95% confidence interval.

[0124] AUROC, which predicts the onset of fibrosis of F3 or higher, did not change significantly even when baseline circulating TSP2 levels were included (0.837 vs. 0.816 in the model with and without TSP2, p=0.19). However, significant improvements were observed in both the NRI (37.3, 95%CI 6.4-68.1, p=0.02) and IDI (2.2, 95%CI 0.1-4.4, p=0.045) models after adding baseline circulating TSP2 levels to the clinical model consisting of baseline BMI, platelet count, and CAP values.

[0125] This study demonstrated the clinical relevance of circulating TSP2 levels as a fibrosis biomarker in NAFLD, based on both cross-sectional and prospective approaches. Serum TSP2 levels were observed to be associated with the presence of fibrosis of F3 or higher and were also an independent predictor of the development of advanced fibrosis in patients with NAFLD and type 2 diabetes.

[0126] The TSP2 gene, THBS2, was identified among five priority genes specifically associated with hepatic fibrosis, independent of the etiology, and its expression showed a positive correlation with the stage of hepatic fibrosis. Increased hepatic TSP2 protein expression was found in rodent hepatic fibrosis models (mice treated with carbon tetrachloride (CCl4) and rats with bile duct ligation) (Chen et al., Am J Physiol Gastrointest Liver Physiol;316:G744-G754 (2019)). Similarly, in another study using apolipoprotein E knockout (ApoEKO) mice fed a high-fat, high-cholesterol diet, hepatic THBS2 gene expression was higher in mice with severe fibrosis than in mice with mild fibrosis. A study evaluating eight NAFLD patients for whom liver biopsy tissue was available showed significant upregulation of THBS2 gene expression in the liver in patients with F3 or higher fibrosis compared to patients with F0 / 1 fibrosis (Lou et al., Sci Rep;7:4748(2017)).

[0127] However, the mechanism explaining the elevated circulating TSP2 levels in patients with progressive fibrosis appears to be complex. Both TSP1 and TSP2 are matrix cell proteins involved in wound healing and remodeling processes, but their tissue expression differs both spatially and temporally. For example, in wound healing, TSP1 functions as an acute-phase reactant, while TSP2, mainly produced by fibroblasts, is suggested to be more involved in subsequent remodeling processes. Hepatic fibrosis is also a wound healing and remodeling process that follows chronic liver injury such as NAFLD. However, unlike TSP1, which activates the classical fibrogenic cytokine latent transforming growth factor beta (TGF-β), TSP2 has minimal effect on TGF-β activity (Daniel et al., J Am Soc Nephrol; 18: 788-798 (2007)). In an experimental model of glomerulonephritis, genetic removal of TSP2 in mice promoted endothelial cell proliferation and capillary repair after renal injury, but also led to increased inflammation, matrix accumulation, and increased glomerulosclerosis compared to wild-type mice. Similarly, another rodent study on experimental brain injury showed that TSP2 deficiency impaired blood-brain barrier recovery, prolonged neuroinflammation, and increased local production of matrix metalloproteinase (MMP)-2 and MMP-9 levels after xenobiotic transplantation in mice (Tian et al., Am J Pathol;179:860-868(2011)), both of which were also involved in the pathogenesis of hepatic fibrosis. Furthermore, in rheumatoid arthritis, high TSP2 expression was found in synovial fibroblasts, endothelial cells, and macrophages in patients with diffuse arthritis.However, in an in vivo model of human rheumatoid arthritis, it has been demonstrated that overexpression of TSP2 actually induces angiogenesis in lesions, a significant decrease in tissue-infiltrating T cell density, and the production of pro-inflammatory mediators including tumor necrosis factor alpha (TNFα) and interferon-gamma (IFN-γ) (Park et al., Am J Pathol;165:2087-2098 (2004)). On the other hand, recent in vitro studies have shown that THBS2 mRNA is highly expressed in hepatic stellate cells, and that overexpression of THBS2 significantly promotes the activation of hepatic stellate cells. In diabetes, previous studies have shown that vitreous fluid TSP2 levels are significantly upregulated in patients with proliferative diabetic retinopathy (PDR) and active angiogenesis, suggesting that TSP2 may be a biomarker for proliferative diabetic retinopathy (Abu El-Asrar. Acta Ophthalmol;91:e169-177(2013)). The authors proposed that myofibroblasts may enhance TSP2 secretion to protect tissue from excessive angiogenesis in PDR. Recently, it has been found that TSP2 expression in the skin is significantly increased in patients with type 2 diabetes, reaching nearly three times that of non-diabetic individuals. In vitro analysis has revealed that hyperglycemia may activate the hexosamine pathway and nuclear factor kappa B (NFκB) signaling, thereby increasing TSP2 expression in fibroblasts. However, it has also been previously shown that hyperglycemia may upregulate TSP2 expression through increased oxidative stress (Bae et al., Arterioscler Thromb Vasc Biol;33:1920-1927(2013)). In summary, further mechanistic studies are needed to determine whether the effect of TSP2 on fibrosis is tissue-specific, or whether the upregulation of hepatic and circulating TSP2 levels in patients with progressive fibrosis represents a compensatory response to the inflammation and oxidative stress underlying NASH.

[0128] This study had several limitations. First, the observational study design prevented the inference of a causal relationship between high circulating TSP2 levels and the development of fibrosis of F3 or higher in patients with type 2 diabetes. Second, liver biopsies were not performed. However, VCTE is increasingly being used as an accurate alternative tool for assessing liver fibrosis in NAFLD, with an AUROC of up to 0.93 for detecting biopsy-proven fibrosis (Castera et al., Gastroenterology; 156:1264-1281e1264 (2019)). This is particularly relevant to the assessment of a large number of stable and asymptomatic patients with type 2 diabetes and concomitant NAFLD or MAFLD (Eslam et al., J Hepatol; 73:202-209 (2020)). Finally, the median observation period was only 1.5 years, which may contribute to the relatively low incidence of fibrosis progression compared to previous studies.

[0129] This study provides evidence for adopting circulating TSP2 levels as a biomarker for progressive fibrosis, which would be useful for stratifying liver risk in a large number of patients with concomitant type 2 diabetes and NAFLD. In particular, circulating TSP2 levels as a biomarker are especially useful in diabetes clinics where VCTE is not readily available, due to their high NPV (Non-Progressive Value) of over 90% and significant improvements in AUROC (Autonomous Circulation of Fibrocytology) for identifying fibrosis of F3 or higher on VTCE (Vascular Threshold Examination). Patients with high circulating TSP2 levels have shown a higher risk of fibrosis of F3 or higher and fibrosis progression on VCTE, and can be identified for referral to a hepatologist for further evaluation. Furthermore, these patients can be given priority in receiving antidiabetic drugs that may improve hepatic fibrosis, liver dysfunction, and / or steatosis, and new NAFLD treatments where clinically available.

[0130] Importantly, current detection and diagnosis of NAFLD typically require biopsy and histological analysis. For example, histological changes and NAFLD activity scores can only be determined using liver biopsy. The invention of biopsy and histological analysis was based on cross-sectional and prospective studies. This study, involving patients with type 2 diabetes, used both cross-sectional histology and a prospective approach to demonstrate that serum TSP2 levels are a valid marker for fibrosis of F3 or higher in oscillation-controlled transient elastography (VCTE). As described herein, this enables the detection and diagnosis of fibrosis of F3 or higher in NAFLD without the need for liver biopsy or histological analysis.

Claims

1. A method for non-invasively detecting advanced liver fibrosis in subjects with non-alcoholic fatty liver disease (NAFLD), (a) A step of measuring the circulating level of the biomarker thrombospondin 2 (TSP2) in a blood sample from the subject, and (b) A step of detecting advanced liver fibrosis when the circulating level of TSP2 in the blood sample from the subject exceeds 3.6 ng / ml, A method comprising the step of detecting the advanced liver fibrosis with a sensitivity of 80% or more and a specificity of 60% or more when the circulating level of TSP2 in the blood sample from the subject is greater than 3.6 ng / ml.

2. The method according to claim 1, wherein the measurement step includes a step of contacting the blood sample from the target with a set of capture reagents, the set of capture reagents comprising one or more antibody-binding fragments having binding specificity to TSP2.

3. The method according to claim 1 or 2, wherein the measurement includes the step of contacting the blood sample from the subject with a set of capture reagents, the set of capture reagents comprising one or more antibody-binding fragments having binding specificity to TSP2 but not binding specificity to TSP1, TSP3, TSP4, and TSP5.

4. The method according to any one of claims 1 to 3, wherein the measurement step includes contacting the blood sample from the subject with a set of capture reagents comprising two antibody-binding fragments, each having binding specificity to different sites of TSP2.

5. The method according to any one of claims 1 to 4, wherein the TSP2 is human TSP2.

6. The method according to any one of claims 1 to 5, wherein the blood sample is diluted or undiluted blood or serum.

7. The method according to any one of claims 1 to 6, wherein the blood sample is a diluted blood sample obtained by diluting the blood sample with a blood sample dilution buffer in a ratio of 1:5 to 1:500 (v / v).

8. The method according to any one of claims 1 to 7, wherein the advanced liver fibrosis includes fibrosis of F3 or higher as measured by vibration-controlled transient elastography (VCTE).

9. The method according to any one of claims 1 to 8, wherein the advanced liver fibrosis includes fibrosis of F3 or higher, which is graded by a measurement cutoff value of liver stiffness (LS) of 9.6 kilopascals (kPa) or 9.3 kPa or higher with an M probe.

10. The method according to any one of claims 1 to 9, wherein the advanced liver fibrosis is detected with a negative predictive value of 90% or more.

11. The method according to any one of claims 1 to 10, wherein the measurement step is performed by an immunoassay having a minimum detection limit of 0.01 ng / ml to 0.18 ng / ml for TSP2.

12. The method according to any one of claims 1 to 11, wherein the subject is one or more diseases selected from the group consisting of NAFLD, metabolic syndrome, type 2 diabetes, cardiovascular disease (CVD), and chronic kidney disease (CKD).

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