Methods for predicting the risk of developing liver fibrosis

Abstract

This invention relates to a method for identifying NAFLD patients who may develop advanced liver fibrosis within 52 weeks.

Description

[Technical Field]

[0001] This invention relates to a method for identifying patients with non-alcoholic fatty liver disease (NAFLD) who may develop advanced liver fibrosis within 52 weeks. [Previous Technology]

[0002] Abnormal and excessive deposition of the extracellular matrix is ​​a hallmark of all fibrotic diseases, including liver, lung, kidney, or heart fibrosis. The extent of affected organs, the progressive nature of the fibrotic process, the large number of people affected, and the lack of symptoms before the disease becomes life-threatening all pose significant challenges.

[0003] When the liver is damaged, a fibrous layer forms, becoming scar tissue in the liver. This early stage of damage is called fibrosis.

[0004] Several types of liver diseases can lead to fibrosis. These liver diseases include: ● Autoimmune hepatitis ● Biliary duct obstruction ● Non-alcoholic fatty liver disease, including non-alcoholic fatty liver disease (NAFL) and non-alcoholic steatosis (NASH) ● Viral hepatitis B and C ● Alcoholic liver disease ● Hepatitis D: This type of hepatitis can also cause cirrhosis. It is common in people who already have hepatitis B. ● Bile duct damage, the function of which is to drain bile: One example of this is primary biliary cirrhosis. ● Diseases that affect the body's ability to process iron and copper: Two examples are hemochromatosis and Wilson's disease. ● Medications (acetaminophen, some antibiotics, and some antidepressants can cause cirrhosis).

[0005] The most common cause of liver fibrosis is non-alcoholic fatty liver disease (NAFLD), while the second leading cause is alcoholic liver disease caused by long-term excessive drinking.

[0006] The range of liver damage can be: *Minor to mild damage *Mild to moderate damage (fibrosis) *Moderate to severe damage (fibrosis to compensated cirrhosis) *Severe to liver failure (decompensated cirrhosis)

[0007] "Liver fibrosis" refers to the presence of fibrous connective tissue in the microscopic examination of stained sections of liver biopsy (H&E, trichrome, or picrosirius red staining). In the context of this invention, the term "fibrosis stage" indicates the location and extent of liver fibrosis in histological examination, as follows: Perisinusoidal or periportal fibrosis 1 Mild periisinusoidal fibrosis (3 zones) 1a Moderate periisinusoidal fibrosis (3 zones) 1b Perisinusoidal / perisinusoidal fibrosis 1c Perisinusoidal and periportal / perisinusoidal fibrosis 2 Bridging fibrosis 3 Cirrhosis 4 (Kleiner et al., Design and Validation of a Histological Scoring System for Nonalcoholic Fatty Liver Disease Hepatology, 2005; 41:1313-1321).

[0008] In many cases, liver fibrosis has almost no symptoms until the liver damage becomes severe enough (cirrhosis). In such cases, patients may experience severe fatigue, loss of appetite, difficulty thinking clearly, confusion, abdominal (ascites) and leg swelling, itchy skin, and gastrointestinal bleeding.

[0009] Mild liver damage caused by fibrosis is reversible if the cause is found and eliminated before too much damage occurs. However, if the scarring persists for a long time, the fibrosis becomes permanent. The damage continues to form bands throughout the liver, destroying the liver's internal structure, impairing its regenerative capacity, damaging liver function, and leading to cirrhosis.

[0010] Complications caused by liver damage (scar tissue) can interfere with liver function. Scar tissue replaces healthy liver cells needed to perform liver functions. Scar tissue can disrupt blood flow to the liver. If there is not enough blood in the liver, cells will die and more scar tissue will form.

[0011] The more scar tissue formed, the more serious the possible complications.

[0012] Ultimately, if a person’s fibrosis progresses to cirrhosis and liver failure, he or she may develop complications such as: ascites (severe abdominal fluid accumulation), hepatic encephalopathy (waste buildup leading to confusion), hepatorenal syndrome, portal hypertension, and varicose vein bleeding.

[0013] The most serious complication of liver fibrosis may be cirrhosis, or severe scarring, which severely damages the liver to the point that a person becomes ill. This usually takes a long time to occur, such as one to twenty years.

[0014] Liver cirrhosis is one of the leading causes of death worldwide. Cirrhosis can lead to cancerous liver tumors, liver failure, and the need for a liver transplant. Therefore, it is important to diagnose and treat people as early as possible, before liver fibrosis progresses to cirrhosis. It is estimated that 6% to 7% of the world's population has liver fibrosis, but they are unaware of it because they are asymptomatic.

[0015] Because such diseases can be reversed or at least have limited consequences if diagnosed early enough, it seems crucial to provide the medical field with suitable tools to achieve such early, rapid and accurate diagnosis.

[0016] Despite numerous attempts to develop non-invasive methods for diagnosing and determining the severity of liver fibrosis, histological analysis of liver biopsies remains the best method for assessing the stage of fibrosis. However, liver biopsies have several significant drawbacks. First, the material collected in a liver biopsy represents only a small portion of the liver of the individual being diagnosed, raising doubts about whether the collected sample is representative of the overall condition of the organ. Furthermore, liver biopsies are a highly invasive procedure that can cause inconvenience, anxiety, and pain for patients, and raises concerns about morbidity and mortality. Finally, given these considerations, it is not reasonable to recommend liver biopsies as a routine procedure for determining whether an individual has fibrosis.

[0017] These drawbacks of biopsy-based diagnosis have led to active development of non-invasive methods for detecting NASH (non-alcoholic steatosis hepatitis). For example, WO2017046181 and WO2017167934 provide non-invasive diagnostic methods based on the measurement of circulating biomarker levels.

[0018] Another option is an imaging test called transient elastography. This is a test that measures the degree of liver stiffness. When a person has liver fibrosis, scar cells cause the liver to harden. This test uses low-frequency sound waves to measure the degree of stiffness of liver tissue. However, false positives may occur in cases where liver tissue may appear stiff. [Summary of the Invention]

[0019] This invention relates to a method for identifying a subgroup of individuals with NAFLD who are at risk of progressing to late-stage fibrosis (F≥3) within 52 weeks. Individuals thus identified are referred to as "fast progressors".

[0020] The experimental section below shows that the method of the present invention has better prognostic value for identifying rapidly progressing patients compared with other tests available in this technique, such as FIB-4 (fibrosis 4), ELF (enhanced liver fibrosis) and NFS (NAFLD fibrosis score).

[0021] In one specific embodiment, the method of the present invention further includes the step of measuring the liver fibrosis of the individual using physical methods. Specifically, the method may include the step of measuring the liver stiffness of the individual. In another specific embodiment, liver stiffness is measured by measuring the difference in the propagation velocity of elastic shear waves in the liver.

Implementation Method

[0023] According to the present invention, the terms "fibrosis," "fibrotic disease," "fibrotic syndrome," and their tendencies refer to a pathological condition of excessive deposition of fibrous connective tissue in the liver. More specifically, fibrosis is a pathological process including persistent fibrotic scar formation and excessive production of extracellular matrix by connective tissue as a response to tissue damage. Physiologically, the deposition of connective tissue can degrade the structure and function of underlying organs or tissues.

[0024] According to the present invention, the term "non-alcoholic steatotic hepatitis" or NASH refers to a condition of NAFLD characterized by the simultaneous presence of hepatic steatosis, hepatocyte ballooning, and hepatitis on histological examination in the absence of excessive alcohol consumption and after ruling out other liver diseases such as viral hepatitis (HCV, HBV). According to the present invention, the term "steatosis" refers to the process describing abnormal lipid retention or fat accumulation in the liver. According to the present invention, the term "hepatocyte ballooning" is generally defined as, on an optical microscopic level, based on hematoxylin and eosin (H&E) staining, cells enlarged to 1.5-2 times the diameter of normal hepatocytes with thin cytoplasm. It more generally refers to the process of hepatocyte death. According to the present invention, the term "lobular inflammation" refers to the presence of lobular inflammatory foci (clusters of inflammatory cells) on microscopic examination of hematoxylin and eosin (H&E) stained sections of liver biological specimens.

[0025] According to the present invention, "NAFLD activity score" or "NAS" refers to the sum of scores for steatosis, hepatocellular ballooning degeneration, and lobular inflammation, as follows: S: steatosis score: 0: <5%; 1: 5-33%; 2: 34-66% and 3: >66%; L1: lobular inflammation score (lesion / ×20 field): 0: none; 1: <2; 2: 2-4 and 3: >4; HB: ballooning degeneration score: 0: none; 1: very few; 2: many cells / protruding ballooning degeneration.

[0026] Therefore, NASH refers to NAFLD characterized by the following liver biopsy scores: NAS ≥ 3, steatosis score of at least 1, lobular inflammation score of at least 1, and hepatocyte ballooning degeneration score of at least 1.

[0027] More severe forms of NASH are characterized by a higher grade of one of the above-mentioned S, LI and HB scores, and / or the presence of liver fibrosis.

[0028] As described above, the fibrosis stage ranges from F=0 (or F0), i.e., no fibrosis, to F4, i.e., cirrhosis. In the context of this invention, the fibrosis stage of F≥3 (i.e., F3 or F4) is referred to herein as "late fibrosis".

[0029] Individuals identified as rapidly progressing according to the method of the present invention may be individuals with fibrosis stage 0, 1, or 2 and a condition selected from the group consisting of: NAFLD; non-alcoholic steatosis hepatitis (NASH); proliferative fibrosis; biliary obstruction; alcohol- or drug-induced liver fibrosis; cirrhosis; infection-induced liver fibrosis, specifically viral infections such as hepatitis A, B, or C; radiation- or chemotherapy-induced fibrosis; chronic fibrotic biliary lesions such as primary sclerosing cholangitis (PSC), primary biliary cholangitis (PBC), biliary atresia, hemochromatosis, Wilson's disease, and drug-induced liver fibrosis. In a particular embodiment, an individual identified as rapidly progressing according to the method of the present invention may be an individual with NASH and fibrosis stage 0, 1, or 2. The present invention more specifically provides a method for determining the likelihood that such an individual will progress to advanced fibrosis within 52 weeks from the determination.

[0030] In the method of the present invention, the levels of at least four circulating markers are measured from blood samples of an individual. The at least four circulating markers are: hsa-miR34a, α2 macroglobulin (A2M), YKL40, and glycated hemoglobin (HbA1c).

[0031] The measurement of these marker levels is performed in a blood-derived sample of the individual, such as blood, serum, or plasma, specifically platelet-free plasma, such as cell-free, citrate-derived platelet-free plasma samples. In one particular embodiment, the levels of hsa-miR34a, A2M, and YKL40 are measured from one or more serum samples of the individual. In another particular embodiment, the level of HbA1c is measured from a blood sample of the individual.

[0032] In a specific embodiment, the contents of hsa-miR34a, A2M, YKL40 and HbA1c are measured as described in WO2017167934.

[0033] It should be understood that in all embodiments and variations disclosed herein, hsa-miR34a may be more specifically hsa-miR34a-5p. In this application, the combination of hsa-miR34a-5p, α2 macroglobulin (A2M), YKL40, and glycated hemoglobin (HbA1c) is also referred to as NIS4™.

[0034] In one particular embodiment, the score is calculated in the logistic function using the content of cyclic markers as measured herein, for example, as provided in application WO2017167934. In short, the logistic function can be determined from data obtained from NASH reference individuals who progressed from stage F0, F1, or F2 to advanced fibrosis at inclusion. Such data may have been obtained in the same reference individuals: a first set of measurements of cyclic marker content determined by liver biopsy when the reference individuals were in stage F0, F1, or F2, and measurements of cyclic marker content in the same reference individuals 52 weeks after the first set of measurements when the reference individuals were determined to be in stage F≥3 by another liver biopsy.

[0035] Those familiar with this technique can use the information provided in the experimental section of this document and the teachings of WO2017167934 to determine the logic functions and cutoff values ​​related to the required test sensitivity, specificity, positive predictive value and / or negative predictive value.

[0036] According to a specific embodiment, the fraction is defined as a logical function derived from a bootstrap model: where: Y = k + a*A + b*B + c*C + d*D Where: S is the fraction; A is the serum concentration of hsa-miR-34a (specifically hsa-miR-34a-5p) in Cq; B is the serum concentration of α2 macroglobulin, in g / L; C is the serum concentration of YKL-40, in pg / ml; D is the concentration of HbA1c, in percentage (e.g., if the measured HbA1c percentage is 10%, then D equals 10); k is the constant of the logical function; a is the coefficient related to the serum concentration of hsa-miR-34a (specifically hsa-miR-34a-5p); b is the coefficient related to the serum concentration of α2 macroglobulin; c is the coefficient related to the serum concentration of YKL-40. The coefficient of d-coefficient related to HbA1c content.

[0037] In another specific embodiment, as described in the experimental section of application WO2017167934, the following values ​​are derived from the bootstrap model: k is a number between 9.51 and 34.37; a is a number between -1.17 and -0.47; b is a number between 0.02 and 0.84; c is a number between 6.10E-06 and 2.09E-05; and d is a number between 0.07 and 0.89.

[0038] As described above, those skilled in the art can use the information provided herein and the teachings of WO2017167934 to determine the logic functions and cutoff values ​​associated with the desired test sensitivity, specificity, positive predictive value, and / or negative predictive value. In one particular embodiment, the low cutoff value is 0.36 and the high cutoff value is 0.63. As shown in the experimental section, due to this particular embodiment, individuals with scores below 0.36 can be identified as having a very low probability of progressing to advanced fibrosis (exclusion), with a progression probability of only 2%, while individuals with scores of 0.63 or higher can be identified as having a very high probability of progressing to advanced fibrosis (inclusion), with a probability of 38% (positive predictive value 38% (23-56)) and a specificity of 88% (81-92), and a sensitivity of 69% (44-86).

[0039] In a particular embodiment, the method further includes measuring the individual's liver fibrosis using a physical method. This measurement can be performed using a variety of methods well-known in the art. Illustrative methods include, but are not limited to, medical imaging and / or clinical measurements. In a particular embodiment, the physical method is elastography. Elastography methods can be further specifically selected from the group consisting of: acoustic radiation force, pulse imaging (ARFI imaging), transient elastography (TE), and MRI stiffness. In a particular embodiment of the invention, the physical method is transient elastography, which measures the difference in the velocity of elastic shear waves propagating in the liver. According to a preferred method, transient elastography (such as FIBROSCAN®) is used, a technique for assessing liver stiffness or rigidity, measured in kilopascals (kPa) and correlated with fibrosis, without invasive studies. TE results (such as FIBROSCAN® results) can range from 2.5 kPa to 75 kPa. 90-95% of healthy individuals without liver disease have liver stiffness measurements <7.0 kPa. In one particular embodiment, the method may include a step of measuring the individual's liver stiffness. In another particular embodiment, liver stiffness is measured by measuring the difference in the propagation velocity of elastic shear waves within the liver.

[0040] The invention is further described with reference to the following non-limiting examples. Examples

[0041] Example 1: Histological progress of late-stage fibrosis and cirrhosis in NASH.

[0042] This analysis was conducted on a subgroup of the phase 2 clinical trial GOLDEN-505 (NCT01694849), which included 161 patients histologically diagnosed with NASH, NAFLD activity score (NAS) ≥3 and fibrosis stage 0-2, who underwent biopsies at baseline and at the end of the study (week 52). GOLDEN-505 was a multicenter, randomized, double-blind, placebo-controlled study evaluating the efficacy and safety of once-daily Elafibranor (1-[4-methylthiophenyl]-3-[3,5-dimethyl-4-carboxydimethylmethoxyphenyl]prop-2-en-1-one) in patients with non-alcoholic steatotic hepatitis (NASH).

[0043] To monitor the histological progression of the disease, biological samples taken at the time of inclusion and at the end of one year of treatment were used to examine and score the histological lesions. Histological scoring based on the NASH-CRN system (NASH Clinical Research Network) was performed centrally by pathologists.

[0044] Patient characteristics were compared between “rapid progression” patients (n=16) who progressed from NASH (NAS≥3) with fibrosis F0 to F2 to advanced (F≥3) fibrosis within 52 weeks and patients who did not progress to F≥3 (n=145).

[0045] Hsa-miR-34a-5p, α-2-macroglobulin, YKL-40 and hemoglobin A1c are quantified before the algorithm calculation to determine the NIS4™ score.

[0046] In short, the patient's blood was collected in serum separation tubes (SST) for measuring YKL-40, hsa-miR-34a-5p levels, and α2-macroglobulin A2M. Blood was also collected in EDTA collection tubes for HbA1c measurement. YKL40 (also known as CHI3L1) was quantitatively determined by ELISA (Quantikine® ELISA catalog number DC3L10). Values ​​are expressed as ng / mL. α2-macroglobulin levels were measured by turbidity assay on the BN II system (Siemens Healthcare). Values ​​are expressed as g / L. HbA1c was measured by ion-exchange high-performance liquid chromatography (HPLC) (Menarini HA-8160 HbA1c automated analyzer) and reported as a percentage of total hemoglobin.

[0047] According to the manufacturer's instructions, total RNA containing preserved miRNAs was extracted from 100 µl of individual serum using the miR-VanaParis extraction kit (AM1556, Ambion, Life Technologies, Carlsbad, CA). To monitor extraction efficiency and minimize inter-sample variability, i) synthetic Caenorhabditis elegans miR-39 [3,125 femoles] (MSY0000010, Qiagen, Venlo, The Netherlands) was added to each sample prior to RNA extraction, and ii) standard serum with known miR-34a Cq values ​​was processed simultaneously with the test samples. The samples were then washed with miR-VanaParis washing solutions (8680G and 8543G14 Ambion) and centrifuged to avoid ethanol residue. The total RNA, including miRNAs, was centrifuged and dissolved in deoxyribonuclease / ribonuclease-free water and immediately stored at -80°C until use. A fixed volume of 5 μl of total RNA from serum samples or synthetic hsa-miRNA-34a (single-stranded sequence = 5'Phos-UGGCAGUGUCUUAGCUGGUUGU-3' (SEQ ID NO:1); Integrated DNA Technologies) was diluted to 3.125 fmol / mL (for standard curve construction and miR-34a duplication count calculation) and reverse transcribed using a TaqMan MicroRNA reverse transcription kit (4366597, Applied Biosystems). Reverse transcription was performed in a 15 µL final mixture containing 10 µL of TaqMan MicroRNA Assay 5X and incubated in a GeneAmp® PCR System 9400 thermal cycler from Applied Biosystems. The cDNA was stored in low-binding tubes at -20°C until further use.

[0048] According to the manufacturer's instructions, the expression of mature miRNAs was quantified using Taqman miRNA RT-qPCR Assay 20X and TaqMan Universal Master Mix II, uracil-N-glycosidase (UNG)-free 2X (Applied Biosystems). A fixed volume of 5 μL of total RNA was used as the template for qPCR analysis using a CFX96™ instantaneous system. hsa-miR-34a-5p TaqMan analysis was performed. The RT products of the synthesized miRNAs were serially diluted, and PCR was performed on all samples (standard and serum-derived RNA). Standard curves were performed in duplicate and used to convert Cq data to duplicates / µL. Cq was used to determine pattern line regression. Transcript abundance is expressed as Cq.

[0049] The sequences and TaqMan analysis IDs of mature miRNAs are reported in the table below: miRNA ID sequence miRbase ID Analysis ID cel-miR-39-3p UCACCGGGUGUAAAUCAGCUUG (SEQ ID NO: 2) MIMAT0000010 000200 hsa-miR-34a-5p UGGCAGUGUCUUAGCUGGUUGU (SEQ ID NO:1) MIMAT0000255 000426 The data used to build the algorithm is in Cq format.

[0050] Next, as provided in application WO2017167934, the NIS4™ score is calculated as a logical function of the has-miR-34a-5p serum content expressed in Cq units.

[0051] In order to compare NIS4™ with other non-invasive scores, the following non-invasive scores stratified by established clinical cutoff values ​​were evaluated and used as predictive models: • Fibrosis-4 [FIB-4; age, AST, ALT, platelets] • NAFLD fibrosis score [NFS; age, BMI, IGF / diabetes status, AST, ALT, platelets, albumin] • Enhanced liver fibrosis [ELF™; hyaluronic acid (HA), collagenogen III aminoterminal peptide (PIIINP) and tissue inhibitor of matrix metalloproteinases (TIMP-1)].

[0052] Data and scores of patients who progressed to F≥3 were compared with those of patients who did not progress to F≥3 using Chi2 or Wilcoxon p-values. All patients Patients who progress to F≥3 Patients who have not progressed to F≥3 Chi2 or Wilcoxon p-values ​​for comparison between two groups n 161 16 145 Gender, male, % (n) 53% (85) 62% (10) 52% (75) 0.5785 Age (years), mean ± SD 51.48 ± 11.59 61.31 ± 9.41 50.4 ± 11.32 0.0002 BMI (kg / m 2 ), average ± SD 31.06 ± 4.83 33.01 ± 4.64 30.84 ± 4.82 0.0565 Obesity*, % (n) 51% (82) 69% (11) 49% (71) 0.2154 Prediabetes†, % (n) 15% (24) 12% (2) 15% (22) 1 Type 2 diabetes, % (n) 32% (51) 50% (8) 30% (43) 0.1685 Dyslipidemia‡, % (n) 49% (78) 50% (8) 49% (70) 1 Arterial hypertension, % (n) 49% (78) 81% (13) 45% (65) 0.0142 No metabolic risk factors §, % (n) 13% (21) 6% (1) 14% (20) 0.6396 ALT (IU / L), mean ± SD 61.19 ± 38.42 72.5 ± 31.19 59.94 ± 39.03 0.0258 AST (IU / L), mean ± SD 38.81 ± 23.3 57.94 ± 41.19 36.7 ± 19.52 0.0007 Glucose (mmol / L), mean ± SD 5.84 ± 1.66 6.36 ± 1.73 5.78 ± 1.65 0.1464 HbA1c (%), mean ± SD 5.94 ± 0.8 6.49 ± 0.94 5.88 ± 0.76 0.0038 TG (mmol / L), mean ± SD 1.84 ± 1.05 2.04 ± 1.19 1.82 ± 1.04 0.4977 HDL-C (mmol / L), mean ± SD 1.26 ± 0.33 1.34 ± 0.4 1.25 ± 0.32 0.3919 LDL-C (mmol / L), mean ± SD 2.89 ± 0.94 2.78 ± 0.77 2.91 ± 0.95 0.6694 Fibrosis stage, mean ± SD 1.14 ± 0.71 1.88 ± 0.34 1.06 ± 0.7 <0.0001 NAS, mean ± SD 4.88 ± 1.22 5.56 ± 1.21 4.81 ± 1.2 0.0187 Non-invasive diagnosis FIB-4, mean ± SD 1.22 ± 0.64 2.05 ± 1.03 1.13 ± 0.51 0.0001 NFS, mean ± SD -1.81 ± 1.33 -0.74 ± 1.14 -1.93 ± 1.3 0.0005 ELF TM Mean ± SD 9.13 ± 0.80 9.87 ± 0.67 9.04 ± 0.77 0.0001 NIS4 TMMean ± SD 0.38 ± 0.23 0.67 ± 0.25 0.35 ± 0.21 <0.0001 miR-34a-5p(cq), mean ± SD 31.87 ± 0.89 30.83 ± 1.47 31.98 ± 0.73 <0.0001 YKL-40 (ng / mL), mean ± SD 59.29 ± 48.02 99.56 ± 79.96 54.85 ± 41.38 0.0077 A2M (g / L), mean ± SD 2.12 ± 0.74 2.82 ± 0.99 2.05 ± 0.67 0.0032 Table 1: Patient Characteristics. A2M: α-2-macroglobulin. ALT: Alanine aminotransferase. AST: Aspartate aminotransferase. BMI: Body Mass Index. HbA1c: Glycated hemoglobin. NAS: Nonalcoholic fatty liver activity score. NASH: Nonalcoholic steatosis. *BMI ≥ 30 kg / m². †Fasting blood glucose concentration between 5.6 mmol / L and 7.0 mmol / L, and not classified as type 2 diabetes. ‡Determined by use of dyslipidemia medications. §No of the following metabolic risk factors: obesity, prediabetes, type 2 diabetes, dyslipidemia, or arterial hypertension.

[0053] Compared to non-rapid-progression patients, “rapid-progression” patients often have poorer clinical and biochemical characteristics (Table 1), including: • Older age • Higher metabolic comorbidities, including obesity, type 2 diabetes mellitus (T2DM), and hypertension • Higher ALT and AST levels • Higher mean noninvasive scores (FIB-4, NFS, NIS4™, and ELF™)

[0054] Next, patients with advanced fibrosis scores will be classified by score region.

[0055] The high-score region was defined as scores above the inclusion cutoff value, the uncertain region was defined as scores between the high and low cutoff values, and the low-score region was defined as scores below the exclusion cutoff value. To enable real-world clinical application, a low cutoff value below 0.36 was established to provide exclusion decisions, with a sensitivity of 81.5%, a specificity of 63%, and an NPV of 77.9%. In addition, a high cutoff value of 0.63 or higher was established to enable inclusion decisions, with a specificity of 87.1%, a sensitivity of 50.7%, and a PPV of 79.2% (Harrison et al. (The Lancet Gastroenterology & Hepatology, Vol. 5, No. 11, pp. 970-985, November 1, 2020; published online August 3, 2020).

[0056] The NIS4™ score was calculated according to the method provided in WO2017167934 and Harrison et al. (The Lancet Gastroenterology & Hepatology, Vol. 5, No. 11, pp. 970-985, November 1, 2020; published online August 3, 2020). In short, the logistic function derived from the bootstrap model is defined as having the following characteristics, applicable to the sought specificity, sensitivity, PPV, and NPV at both low and high cutoff values ​​defined above: where: Y = k + a*A + b*B + c*C + d*D where: S is the NIS4™ score; A is the serum concentration of hsa-miR-34a (specifically hsa-miR-34a-5p) in Cq; B is the serum concentration of α2 macroglobulin, in g / L; C is the serum concentration of YKL-40, in pg / ml; D is the concentration of HbA1c, in percentage (e.g., if the measured percentage of HbA1c is 10%, then D equals 10); k is a number between 9.51 and 34.37; a is a number between -1.17 and -0.47; b is a number between 0.02 and 0.84; The c series numbers are between 6.10E-06 and 2.09E-05; and the d series numbers are between 0.07 and 0.89.

[0057] For each test / score region of NIS4™, FIB-4, NFS and ELF, the absolute number and relative percentage of «rapidly progressing» patients who transitioned from NASH (NAS≥3) and F0 to F2 fibrosis to advanced (F≥3) fibrosis were quantified, as shown in Table 2. Score or technique Fractional range Fraction range Number of rapid progressers (reaching F≥3) % of those who progressed rapidly (reaching F≥3) NIS4 TM high ≥ 0.63 11 69% (11 / 16) NIS4 TM uncertain 0.36 ≤ NIS4 < 0.63 3 19% (3 / 16) NIS4 TM Low < 0.36 2 13% (2 / 16) FIB-4 high ≥ 2.67 4 25% (4 / 16) FIB-4 uncertain 1.3 ≤ FIB-4 < 2.67 9 56% (9 / 16) FIB-4 Low < 1.3 3 19% (3 / 16) NFS high ≥ 0.676 2 13% (2 / 16) NFS uncertain -1.455 ≤ NFS < 0.676 9 56% (9 / 16) NFS Low < -1.455 5 31% (5 / 16) ELF TM high ≥ 9.8 9 56% (9 / 16) ELF TM uncertain 7.7 ≤ ELF < 9.8 7 44% (7 / 16) ELF TM Low < 7.7 0 0% (0 / 16) Table 2: Patients who progressed to advanced fibrosis were categorized by score region.

[0058] For NIS4™ and ELF™, the proportion of «rapidly progressing» patients categorized into low to medium to high score zones increases progressively. Compared to ELF™ (56%), NIS4™ categorizes more «rapidly progressing» patients into the high score zone (69%). In contrast, FIB-4 and NFS categorize most «rapidly progressing» patients into low or medium score zones.

[0059] The probability of progression to advanced fibrosis within 52 weeks was calculated based on the baseline score range (Table 3). Score or technique Fractional range Fraction range Patients in each region % of the total The probability of progressing to F≥3 within 52 weeks NIS4 TM high ≥ 0.63 29 18% (29 / 161) 38% (11 / 29) NIS4 TM uncertain 0.36 ≤ NIS4 < 0.63 45 28% (45 / 161) 7% (3 / 45) NIS4 TM Low < 0.36 87 54% (87 / 161) 2% (2 / 87) FIB-4 high ≥ 2.67 5 3% (5 / 161) 80% (4 / 5) FIB-4 uncertain 1.3 ≤ FIB-4 < 2.67 50 31% (50 / 161) 18% (9 / 50) FIB-4 Low < 1.3 106 66% (106 / 161) 3% (3 / 106) NFS high ≥ 0.676 5 3% (5 / 161) 40% (2 / 5) NFS uncertain -1.455 ≤ NFS < 0.676 57 35% (57 / 161) 14% (8 / 57) NFS Low < -1.455 99 61% (99 / 161) 6% (6 / 99) ELF TM high ≥ 9.8 28 17% (28 / 161) 32% (9 / 28) ELF TM uncertain 7.7 ≤ ELF < 9.8 128 80% (128 / 161) 5% (7 / 128) ELF TM Low < 7.7 5 3% (5 / 161) 0% (0 / 5) Table 3: Probability of fibrosis progression within 52 weeks by score.

[0060] In this group, low-score regions of the assessed tests generally indicate a lower risk of progression to late fibrosis (F≥3) (0-6% within 52 weeks). On the other hand, high-score regions typically represent the highest risk of progression within 52 weeks.

[0061] Finally, the clinical efficacy of each test in identifying «rapidly progressing individuals» with a high cutoff value was calculated (Table 4). Diagnostic measures (sensitivity, specificity, positive predictive value / PPV, negative predictive value / NPV) are provided together with the 95% CI calculated using an asymptotic formula based on the normal approximation of the binomial distribution (Fleiss, 2003).

[0062] All statistical analyses were performed using R version 3.4.1 (R Core Team, 2017). Score or technique Fractional range Fraction range Se Sp PPV NPV NIS4 TM high ≥0.63 69% (44 - 86) 88% (81 - 92) 38% (23 - 56) 96% (91 - 98) FIB-4 high ≥2.67 25% (10 - 49) 99% (86 - 100) 80% (38 - 96) 92% (87 - 96) NFS high ≥0.676 13% (3 - 36) 98% (94 - 99) 40% (12 - 77) 91% (86 - 95) ELF TM high ≥9.8 56% (33 - 77) 87% (80 - 91) 32% (18 - 51) 95% (90 - 97) Table 4: Sensitivity and specificity of each test evaluated for identifying "rapid progressors" at the high cutoff value. Se: Sensitivity; Sp: Specificity; PPV: Positive predictive value; NPV: Negative predictive value.

[0063] Overall, NIS4™ has the most balanced characteristics, with the highest sensitivity (Se=69-83%) in the evaluated tests (Se=0%-67%), and similarly high specificity (Sp=88-89%).

[0064] Compared to FIB-4≥2.67 (25%), NFS≥0.676 (13%) and ELF≥9.8 (56%), NIS4≥0.63 correctly identified the majority (69%) of the «Fast Progressive» group.

[0065] In summary, NIS4™ can identify a clinical subgroup of «rapidly progressing patients», who are highly likely to progress to advanced fibrosis within one year. Furthermore, NIS4™ has better prognostic efficacy in identifying rapidly progressing patients compared to FIB-4, ELF, and NAFLD fibrosis scores. [Simplified Explanation of the Diagram]

[0022] None [Sequence List]

Claims

1. A method for identifying an individual with NAFLD who is highly likely to progress to advanced liver fibrosis within 52 weeks, wherein the method comprises in vitro measurement of the levels of hsa-miR34a, α2 macroglobulin (A2M), YKL-40, and glycated hemoglobin (HbA1c) in a blood-derived sample of the individual, the measured levels being used in a logic function to calculate a fraction S, wherein the fraction S is calculated according to the following logic function: Wherein: Y = k + a*A + b*B + c*C + d*D where this method is derived from a bootstrap model, and where: S represents the fraction; A represents the serum hsa-miR-34a content in Cq; B represents the serum α2 macroglobulin content, in g / L; C represents the serum YKL-40 content, in pg / ml; D represents the HbA1c content, in percentage (e.g., if the measured HbA1c percentage is 10%, then D equals 10); k represents the constant of the logistic function; a represents the coefficient related to the serum hsa-miR-34a content; b represents the coefficient related to the serum α2 macroglobulin content; c represents the coefficient related to the serum YKL-40 content; d represents the coefficient related to the HbA1c content, where: k is a number between 9.51 and 34.37; a is a number between -1.17 and -0.47; b is a number between 0.02 and 0.84; The c series numbers are between 6.10E-06 and 2.09E-05; and the d series numbers are between 0.07 and 0.89, where a score S greater than or equal to a cutoff value of 0.63 indicates a high probability of progression to late fibrosis within 52 weeks.

2. The method as described in claim 1, comprising measuring the levels of hsa-miR34a-5p, HbA1c, YKL-40 and A2M, where A is the serum level of hsa-miR34a-5p and a is a coefficient relating the serum level of hsa-miR34a-5p.

3. The method as described in claim 1 or 2, wherein the individual has NAFLD and the fibrosis stage is 0, 1 or 2.

4. The method as described in either claim 1 or 2, further comprising measuring the individual’s liver fibrosis by physical methods.

5. The method as described in claim 4, wherein the physical measurement of liver fibrosis is performed by measuring the stiffness of the individual's liver.

6. The method as described in claim 5, wherein liver stiffness is measured by measuring the difference in the propagation velocity of elastic shear waves in the liver.