EA043299B1 - NON-INVASIVE DIAGNOSIS OF NON-ALCOHOLIC FATTY LIVER, NON-ALCOHOLIC STEATOHEPATITIS AND/OR LIVER FIBROSIS - Google Patents

Description

Non-alcoholic fatty liver disease (NAFLD) is an asymptomatic disease defined as the accumulation of fat in the liver (steatosis) for reasons other than excessive alcohol consumption. NAFLD is the most common cause of elevated aminotransferases in patients presenting to hepatologists. NAFLD ranges from benign simple steatosis to the pathological condition in some patients, non-alcoholic steatohepatitis (NASH), where necrosis/inflammation leads to progressive accumulation of fibrosis in the liver, eventually leading to cirrhosis, liver failure, hepatocellular carcinoma (HCC), transplant liver and liver failure. Both epidemiologically and pathophysiologically, NAFLD and NASH are strongly associated with obesity, metabolic syndrome, and type 2 diabetes. Thus, in parallel with the epidemics of obesity and type 2 diabetes, the prevalence of NAFLD and NASH has increased dramatically in recent decades, and NASH is becoming the leading cause of liver transplantation in the United States. Consequently, NASH is considered a growing global public health problem given that there is no optimal solution for diagnosis and there is no approved treatment for NASH.

While NAFLD can be diagnosed by detecting fat accumulation in the liver using ultrasound techniques, NASH and NASH-associated liver fibrosis can only be diagnosed by histological examination of a liver biopsy. On microscopic examination of liver biopsies, NASH is determined by accumulation of fatty acids (lipid droplets) associated with damaged hepatocytes (ballooning or necrosis of hepatocytes) and signs of lobular inflammation. Although fibrosis is not a mandatory histological feature for diagnosing NASH, the presence and stage of liver fibrosis are critical in assessing the severity of the disease and the risk of developing cirrhosis, HCC (hepatocellular carcinoma), and liver failure, which is a liver-related death of the patient.

Histological scoring/staging systems have been developed to assess NAFLD activity level and fibrosis staging and assess the risk of liver clinical outcomes. The NALFD Activity Score (NAS) was developed to assess disease activity. NAS is the sum of individual unweighted biopsy scores for steatosis (0 to 3), lobular inflammation (0 to 3), hepatocellular ballooning (0 to 2). According to Kleiner et al. (Hepatology, 2005; 41:1313-21), NAS is the sum of three histological scores obtained from liver biopsy sections:

S: steatosis score: 0: <5%; 1: 5-33%; 2: 34-66% and 3: >66%,

LI: Lobular inflammation score (field focus 20x): 0: no; 1: <2; 2: 2-4 and 3: >4,

HB: ballooning dystrophy score: 0: none; 1: few; 2: many cells/pronounced ballooning.

Using this system, a patient with NASH has NAS>3 and at least 1 steatosis score, at least 1 lobular inflammation score, and at least 1 hepatocyte ballooning score. A patient is considered to have active NASH when NAS>4 and has at least 1 steatosis score, at least 1 inflammation score, and at least 1 hepatocyte ballooning score.

The location and extent of fibrosis on histological examination indicates the severity (progress) of the disease, and NASH-CRN has developed a specific fibrosis staging system (Kleiner et al., Hepatology, 2005; 41:1313-21):

Perisinusoidal or periportal fibrosis1

Mild perisinusoidal fibrosis (zone 3)1a

Moderate perisinusoidal fibrosis (zone 3)1b

Portal/periportal fibrosis1c

Perisinusoidal and portal/periportal fibrosis2

Bridge fibrosis3

Cirrhosis4

When using this fibrosis staging system, patients with no or minimal fibrosis (F=0-1) are generally not considered at risk of developing cirrhosis, HCC, or liver failure. Patients with significant (F=2) and moderate fibrosis (F=3) have an increased risk of developing cirrhosis, liver failure, HCC, and liver failure. Patients with compensated liver cirrhosis have severe fibrosis (F=4) and are at high risk for liver failure (decompensated cirrhosis), HCC, and liver-related death.

Recently, there has been a focus on the activity index (AI) derived from these two widely used scoring and staging systems, which can be defined as the sum of the scores for lobular inflammation and hepatocyte ballooning. In addition, Munteanu et al., Aliment Pharmacol Ther., 2016, 44(8):877-89 proposed the SAF feature to separately provide steatosis, disease activity and fibrosis scores.

Diagnosis of NAFLD and NASH, as well as evaluation of disease activity using the aforementioned NAS, AI, and liver fibrosis staging, require liver biopsy, which has a number of obvious disadvantages that preclude its routine use. Indeed, liver biopsy is an invasive procedure that can be burdensome, distressing, and painful for the patient, and liver biopsy is associated with a risk of hemorrhage and even death. Accordingly, due to the growing epidemic of NASH and liver fibrosis, and because biopsy cannot be considered as a sufficiently effective and safe procedure, there is an urgent need for new non-invasive methods for diagnosing NAFLD, NASH and/or liver fibrosis.

Ultrasound and imaging techniques (ultrasound echography, controlled attenuation parameter, magnetic resonance imaging (MRI), and proton density-weighted fat fraction measurement using magnetic resonance imaging (MRI-DPFF)) have been developed for the diagnosis of NAFLD. However, these techniques are limited by both inter-observer and intra-observer variability, cost, and/or are time consuming. In addition, MRI-DPFF is usually unavailable and too complex for clinical use. In addition, fibrosis stage is associated with all-cause mortality in a dose-dependent manner, with an increased risk in patients with F2 fibrosis. Ultrasound elastography, such as Fibroscan and shear wave elastography, has moderate to high accuracy in the diagnosis of advanced fibrosis or cirrhosis. However, F2 fibrosis is not an advanced stage of fibrosis and therefore cannot be accurately detected using these techniques.

In addition to ultrasound and imaging techniques, intensive efforts have been made to identify and validate new circulating biomarkers for reliable, simple, and cost-effective non-invasive detection of NAFLD, NASH, and/or liver fibrosis. The following table lists individual biomarkers that have been described as being modulated in NAFLD/NASH and/or liver fibrosis.__________________________________________________________________

Function of hepatocytes fatty textile Metabolism Oxidative stress/apopt 03 Fibrosis Inflammation ALT AST ALP GGT Gaptoglobi Η Albumin Bilirubin Platelet count in Adiponectin Leptin resistin Fasting Plasma Glucose Fasting Insulin HOMA Index Triglycerides DY Cholesterol L11VP VLCL-C Apolipoproteins (ApoAl, ApoB, ApoCSH) Malondialdehyde TBARS OxLDL CK18-M30 CK18-M65 Ferritin YKL-40 (CHI3L1) Fibronec tin Hyaluronic Acid Type IV Collagen PIIINP TIMP-1 TNFa ILlb, IL6, IL8, IFNg, TGFb hs-CRP MCP1 sCD14

Some studies have shown that some of these serum biomarkers had better diagnostic values than common serum markers of liver dysfunction, such as transaminases (Naveau S. et al., Clin Gastroenterol Hepatol., 2005; 3 (2): 167 -74 Castera L et al J Hepatol 2000 32: 412-8 Annoni G et Hepatology 1989 9 693-7 Nojgaard C et al J Hepatol 2003 39: 179-86; Chossegros P. 1995; 22 (2 Suppl): 96-9). However, none of these studies have identified and validated an effective biomarker for diagnosing NAFLD, NASH, and/or liver fibrosis. In attempts to improve diagnostic performance, multivariate scores combining multiple biomarkers and/or common variables have been generated, but their diagnostic performance for identifying patients with NAFLD, NASH, and/or liver fibrosis remains largely unreliable.

NASH is associated with faster progression of fibrosis than NAFLD and is currently the main target of pharmacological treatment. Patients with NASH are more likely to develop cirrhosis of the liver and die from cardiovascular and liver-related causes, with a worsening prognosis as the stage of fibrosis progresses (Ekstedt et al, 2015). Despite the large number of serum biomarkers, combination panels, and imaging biomarkers that have been proposed, there is still a need to identify effective, less invasive, and more affordable ways to diagnose and monitor NAFLD, NASH, and liver fibrosis, in particular, ways that have been validated by an independent panel. clinical check.

Identification of patients at risk of developing HCC, cirrhotic complications, and liver-related death is the main reason for assessing the state of the liver.

The essence of the invention

The inventors of the present invention conducted several very accurate and complete analyzes of various patient groups in order to provide new and highly sensitive non-invasive methods for diagnosing and monitoring non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH) and liver fibrosis. The data presented herein demonstrate that miR-193 is an effective circulating biomarker associated with NAFLD, NASH and/or liver fibrosis. This biomarker has been validated in three independent clinical cohorts. Thus, the methods of the present invention allow for the diagnosis, monitoring and classification of risk for a subject suffering from NAFLD, NASH and/or hepatic fibrosis. The authors of the present invention also provide a method for diagnosing, monitoring and classifying the risk of subjects potentially suffering from NAFLD, NASH and/or liver fibrosis. The methods of the present invention may also contribute to the development of new therapeutic treatments.

Accordingly, the invention provides a method for diagnosing NAFLD, NASH, or hepatic fibrosis in a subject, comprising determining the level of miR-193 in a body fluid sample of said subject.

These methods are based on determining the level of miR-193 in the biological fluid of the subject. In all of the methods and embodiments provided herein, miR-193 microRNA implemented in the present invention may be hsa-miR-193 miRNA, such as hsamiR-193, selected from the group consisting of hsa-miR-193a-3p, hsa-miR-193a-5p, hsa-miR-193b-5p and hsamiR-193b-3p. In a specific embodiment, determine the level of hsa-miR-193b-3p. In all of the methods and embodiments provided herein, the body fluid sample may be a blood sample, a fluid derived from blood (such as serum and plasma, in particular platelet-free plasma, such as platelet-free cell-free plasma obtained from using citrate), a saliva, cerebrospinal fluid or urine sample. In a specific embodiment, the biological fluid is plasma or serum without or with platelets.

In the methods of the present invention, the level of miR-193 in a subject's body fluid can be compared to a control level of miR-193. Control level refers to a predetermined standard or level determined experimentally in a similarly treated sample from a control subject. Depending on the purpose of the method of the present invention, the control subject may be a healthy subject, a subject with NAFLD but no NASH, a subject with NASH but no active NASH, or a subject with no or minimal hepatic fibrosis. The control subject can also be a patient receiving a placebo. The control level can also be the level of miR-193 determined in a similarly treated biological fluid sample obtained in the past from the same subject, which allows you to determine the evolution of NAFLD, NASH or liver fibrosis in the subject, in particular, allows you to determine the evolution of disease activity or fibrosis, or the effectiveness of the treatment of the disease, depending on the implemented method.

Accordingly, in a specific embodiment, the diagnosis and/or detection of NAFLD, or the diagnosis and/or detection of potential NAFLD in a subject, is based on the detection of an elevated level of miR-193 in a body fluid sample relative to a control level measured in healthy individuals without hepatic steatosis.

In a specific embodiment, diagnosing and/or detecting NASH, or diagnosing

- 3 043299 and/or detection of potential NASH in a subject is based on the detection of an elevated level of miR-193 in a biological fluid sample relative to a control level measured in a subject without NASH, such as a healthy subject, a subject with NAS<3, or a subject with at least one NAS component with a score of 0.

In another embodiment, the diagnosis and/or detection of active NASH, or the diagnosis and/or detection of potentially active NASH in a subject, is based on the detection of an elevated level of miR-193 in a body fluid sample relative to a control level measured in a healthy subject, a subject with NAS<4, or a subject with at least one NAS component having a score of 0. In a specific embodiment, for diagnosing and detecting active NASH or potentially active NASH, the reference level is the miR193 level measured in a subject with NAS=3, steatosis score 1, lobular inflammation and 1 point for hepatocyte ballooning.

In a further embodiment, the diagnosis and detection of liver fibrosis (F>1) or potential liver fibrosis (F>1) in a subject is based on the detection of elevated levels of miR-193 in a body fluid sample relative to a control level measured in a healthy subject without liver fibrosis (F =0).

In another embodiment, diagnosing and identifying significant (F=2), moderate (F=3), or severe (F=4; i.e., cirrhosis) hepatic fibrosis or potential significant hepatic fibrosis, potential moderate hepatic fibrosis, or potential severe hepatic fibrosis in a subject are based on the detection of elevated levels of miR-193 in a body fluid sample relative to a control level measured in a subject with no (F=0) or minimal (F=1) hepatic fibrosis.

In another embodiment, the diagnosis and detection of significant (F=2), moderate (F=3), or severe (F=4) liver fibrosis, or potential significant liver fibrosis, potential moderate liver fibrosis, or potential severe liver fibrosis in a subject is based on the detection of an elevated miR-193 level in a body fluid sample relative to a control level measured in a subject with minimal hepatic fibrosis (F=1). In another specific embodiment, the control level is measured in a subject with F=1a, 1b or 1c.

In another embodiment, the diagnosis and detection of significant liver fibrosis or potential significant liver fibrosis in a subject is based on the detection of an elevated level of miR-193 in a body fluid sample relative to a control level measured in a subject with minimal fibrosis.

In another embodiment, the diagnosis and detection of moderate hepatic fibrosis or potential moderate hepatic fibrosis in a subject is based on the detection of an elevated level of miR-193 in a body fluid sample relative to a control level measured in a subject with significant fibrosis.

In another embodiment, the diagnosis and detection of severe fibrosis or potential severe fibrosis in a subject is based on the detection of an elevated level of miR-193 in a body fluid sample relative to a control level measured in a subject with moderate fibrosis.

According to another object, the invention relates to a method for classifying a subject as potentially receiving (to be treated, or TBT) or not receiving (not to be treated, or NTBT) treatment for NAFLD, NASH, or liver fibrosis, based on the detection of elevated levels of miR-193 in a sample. biological fluid relative to miR-193 control level measured in NTBT patients, as defined below.

In a further embodiment, the invention also provides a method for determining the level of NAFLD activity, the level of NASH activity, and/or the stage of liver fibrosis in a subject based on determining the level of miR-193 in a subject's body fluid sample.

In another aspect, the invention also allows clinical prediction of fibrosis, namely, prediction of the risk factor for liver fibrosis to cirrhosis and other liver outcomes (such as HCC and liver-related death) of a patient with NAFLD or NASH, based on the miR-193 level determined in a sample of the subject's body fluid.

The invention also provides a method for monitoring the evolution of the level of NAFLD activity, the level of NASH activity, and/or the stage of liver fibrosis in a subject based on the evolution of the level of MIR-193 in a body fluid sample of the subject relative to a control level of miR-193 in one or more body fluid samples collected from the same subject in the past. In this method, an increase in miR-193 indicates that disease activity and fibrosis are increasing, while a decrease in miR193 indicates that disease activity and fibrosis are decreasing.

The invention further provides a method for determining the efficacy of treating NAFLD, NASH, or liver fibrosis in a subject based on the evolution of miR-193 level in a subject's body fluid sample relative to a miR-193 control level in one or more body fluid samples collected from the same subject. in past. In this method, an increase in miR-193 or a stable level of miR-193 indicates that the treatment is ineffective, then

- 4 043299 as a decrease in the level of miR-193 indicates that the treatment is effective. In another embodiment of this method, a stable miR-193 level may also indicate that the treatment is effective in stabilizing the subject's NASH, NAFLD, or liver fibrosis, thereby reducing the subject's risk of developing critical outcomes such as cirrhosis, HCC. or liver-related death.

The invention further provides a method for predicting a subject's response (e.g., predicting changes in NAFLD, NASH activity, and liver fibrosis stage) to a particular treatment (responder subject) based on the detection of a differential level of miR-193 in a body fluid sample relative to a control level measured in subject not responding to treatment.

In another aspect, the present invention provides a method for diagnosing NAFLD, NASH, or hepatic fibrosis, or potential NAFLD, NASH, or hepatic fibrosis, or identifying a subject at risk of progressing to clinical outcomes from NAFLD, NASH, or hepatic fibrosis (e.g., hepatic cirrhosis, cirrhotic complications, and/ or liver-related death), the method comprising determining the level of miR-193 and at least one marker selected from the group consisting of YKL-40 (CHI3L1), tissue inhibitor of metalloproteinase 1 (TIMP)-1 ), platelet count, hyaluronic acid (HYUA2) and glycated hemoglobin (HbA1c). In a specific embodiment, the method further includes determining the metabolic syndrome (ms) status of the patient. In a specific embodiment, the method includes determining the level of miR-193 and YKL-40. In a further specific embodiment of this aspect, the method includes:

(i) determining the level of miR-193, such as the amount of hsa-miR-193a-5p, hsa-miR193a-3p, hsa-miR193b-5p or hsa-miR-193b-3p in a body fluid sample from the subject;

(ii) analysis:

amounts of YKL-40 (CHI3L1), tissue inhibitor of metalloproteinase 1 (TIMP-1), platelets, hyaluronic acid (HYUA2), and glycated hemoglobin HbA1c; or analysis of the amount of YKL-40 (CHI3L1), tissue inhibitor of metalloproteinase 1 (TIMP-1), the number of platelets in a sample of biological fluid from the subject and determining whether the subject has metabolic syndrome (ms);

(iii) determining a score for the subject based on the results obtained in steps (i) and (ii); and (iv) comparing the score to a threshold value to determine the subject's risk of NASH progression. In an exemplary embodiment, the amount of each of miR-193b-3p, YKL-40, TIMP-1, and platelet counts, as well as the determination of ms, are analyzed in the method. In another exemplary embodiment, miR-193b-3p, YKL-40, TIMP-1, HYUA2, HbA1c, and platelet counts are each assayed in the method, and thresholds are determined using miRNA levels by Cq or log10 copies.µl-1 in blood sample.

In another embodiment, the method includes determining the level of miR-193, YKL-40, TIMP-1, platelet count, hyaluronic acid (HYUA2), and glycated hemoglobin HbA1c. In another embodiment, the method includes determining miR-193, YKL-40, TIMP-1, platelet and hyaluronic acid (HYUA2) levels and determining the metabolic syndrome status of the patient. In any of the embodiments of this aspect, the preferred option includes determining the level of hsa-miR-193a-3p, hsa-miR-193a-5p, hsa-miR-193b-5p or hsamiR-193b-3p, in particular, hsa-miR -193b-3p.

Description of drawings

Fig. 1. Serum level of hsa-miR-193b-3p in non-treatable patients (NTBT) and in patients eligible for treatment (TBT) GOLDEN-DIAG at inclusion according to three different definitions of TBT patients: TBT1, TBT2 and TBT7. and in healthy subjects (n=100). Results are expressed as Mean±SEM. Statistical significance was calculated using the Kruskal-Wallis ANOVA test followed by Dunn's multiple comparison test:***, p-value<0.001. NTBT1 n=83, TBT1 n=187; NTBT2 n=161, TBT2 n=109, NTBT7 n=119, TBT7 n=151

TBT1=score for steatosis, lobular inflammation, and hepatocyte ballooning >1, NAS>4, F>1,

TBT2=score for steatosis, lobular inflammation, and hepatocyte ballooning >1, NAS>4, F>2,

TBT7=score for steatosis, lobular inflammation, and hepatocyte ballooning >1, NAS>4, F=1b, 1c, 2, 3, or 4.

Fig. 2. Serum level of hsa-miR-193b-5p in NTBT and TBT GOLDEN-DIAG patients at inclusion according to three different definitions of TBT patients: TBT1, TBT2 and TBT7. Results are expressed as Mean±SEM. Statistical significance was calculated using the Mann-Whitney test: ***, p-value <0.001.

TBT1=scores for steatosis, lobular inflammation, and hepatocyte ballooning >1 each, NAS>4, F>1

TBT2=scores for steatosis, lobular inflammation, and hepatocyte ballooning >1 each,

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NAS>4, F>2

TBT7= scores for steatosis, lobular inflammation, and hepatocyte ballooning >1 each,

NAS>4, F=1b, 1c, 2, 3 or 4.

Fig. 3. Serum level of hsa-miR-19 3a-5p in NTBT and TBT GOLDEN-DIAG patients at inclusion according to three different definitions of TBT patients: TBT1, TBT2 and TBT7. Results are expressed as Mean±SEM. Statistical significance was calculated using the Mann-Whitney test: ***, p-value <0.001.

Fig. Fig. 4. Serum level of hsa-miR-193b-3p in healthy blood donors, in NTBT2 and TBT2 patients (left), in patients with NAS<4 and NAS>4 (in the middle) and in patients with F<2 and F>2 (right) GOLDENDIAG at inclusion (top) and OBESE cohort (bottom). Results are expressed as Mean±SEM. Statistical significance was calculated using the Kruskal-Wallis ANOVA test followed by Dunn's multiple comparison test (Golden Diag) and Mann-Whitney's test: ***, p-value <0.001.

(Obesity)

Fig. Fig. 5. Serum level of hsa-miR-193a-5p in NTBT2 and TBT2 patients (left), in patients with NAS<4 and NAS>4 (center) and in patients with F<2 and F>2 (right) in cohorts GOLDEN-DIAG when turned on (top) and OBESE (bottom). Results are expressed as Mean±SEM. Statistical significance was calculated using the Mann-Whitney test: ***, p-value <0.001.

Fig. Fig. 6. Serum level of hsa-miR-193b-5p in NTBT2 and TBT2 patients (left), in patients with NAS<4 and NAS>4 (center) and in patients with F<2 and F>2 (right) in cohorts GOLDEN-DIAG when turned on (top) and OBESE (bottom). Results are expressed as Mean±SEM. Statistical significance was calculated using the non-Mann-Whitney test: ***, p-value <0.001.

Fig. 7. Serum levels of hsa-miR-193b-3p, hsa-miR-193b-5p and hsa-miR-193a-5p in NTBT2 and TBT2 patients (left), in patients with NAS<4 and NAS>4 (center) and in patients with F<2 and F>2 (right) of the RESOLVE-IT study. Results are expressed as Mean±SEM. Statistical significance was calculated using the non-Mann-Whitney test: ** p-value <0.005; ***, p-value <0.001.

Fig. 8. Correlation between serum levels of hsa-miR-193b-3p with NAS, fibrosis stage, activity index, steatosis score, hepatocyte ballooning score, lobular inflammation score in GOLDEN-DIAG cohort patients (bottom). Results are expressed as Mean±SEM. Statistical significance was calculated using the Kruskal-Wallis ANOVA test followed by Dunn's multiple comparison test: *, p-value <0.05; ** p-value <0.005; ***, p-value <0.001.

Fig. 9. Correlation between serum levels of hsa-miR-193b-5p with NAS, fibrosis stage, activity index, steatosis score, hepatocyte ballooning score, lobular inflammation score in GOLDEN-DIAG cohort patients (bottom). Results are expressed as Mean±SEM. Statistical significance was calculated using the Kruskal-Wallis ANOVA test followed by Dunn's multiple comparison test: *, p-value <0.05; ** p-value <0.005; ***, p-value <0.001.

Fig. 10. Correlation between serum levels of hsa-miR-193a-5p with NAS, fibrosis stage, activity index, steatosis score, hepatocyte ballooning score, lobular inflammation score in GOLDEN-DIAG patients (bottom). Results are expressed as Mean±SEM. Statistical significance was calculated using the Kruskal-Wallis ANOVA test followed by Dunn's multiple comparison test: *, p-value <0.05; ** p-value <0.005; ***, p-value <0.001.

Fig. Fig. 11. True/false detection (ROC) curve analysis of Y1 algorithm with hsa-miR-193b-3p (log10 copies.µl-1), TIMP-1, YKL-40, platelet count, and metabolic syndrome. Comparison of area under the curve (AUC) between this algorithm (NIS) and individual variables in the GOLDEN-DIAG study at inclusion.

Fig. Fig. 12. True/false detection (ROC) curve analysis of Y2 algorithm with hsa-miR-193b-3p (log10 copies.µl-1), YKL-40, TIMP-1, HbA1c, HYUA2 and platelet count.

Fig. Fig. 13. True/false detection (ROC) curve analysis of Y3 algorithm with hsa-miR-193b-3p (Cq), YKL-40, TIMP-1, HbA1c, HYUA2 and platelet count.

Detailed description of the invention

The authors of the present invention provide a new method for diagnosing, monitoring and classifying the risk of subjects suffering from or potentially suffering from NAFLD, NASH and/or liver fibrosis.

The present invention is based on the very precise analysis of patient biopsies during a clinical trial in order to correlate the presence or level of circulating biological markers and classify patients as treatable or non-treatable. In particular, the invention also provides NAS estimation as described below. In particular, the present invention defines in a non-limiting manner three classes of NASH patients to be treated. These patients are classified in relation to the assessment of NASH characteristics.

Experimental data presented herein surprisingly identifies miR-193 as a circulating biomarker for NAFLD, NASH and/or liver fibrosis in two large independent patient cohorts, namely GOLDEN-DIAG (N=270 at inclusion; N=223 at 52 weeks) and the OBESE cohort (N=253) with assessed liver biopsies and corresponding blood, plasma and serum samples. The results were confirmed in the third independent RESOLVEIT cohort (N=263).

The invention will now be presented in more detail.

Definitions

According to the present invention, the terms NAFLD or non-alcoholic fatty liver refers to a condition in which fat is deposited in the liver (hepatic steatosis), with or without signs of inflammation and fibrosis, in the absence of excessive alcohol consumption.

According to the invention, the terms NAFLD activity level refer to the progression of NAFLD and are defined by an increase in steatosis score as defined herein. The level of NAFLD activity also refers to the progression of NAFLD towards NASH or fibrosis and severity of NASH.

According to the invention, the term steatosis refers to a process describing abnormal lipid retention or accumulation of fat in the liver.

According to the invention, the term NASH or non-alcoholic steatohepatitis refers to a NAFLD condition characterized by the concomitant presence of hepatic steatosis, hepatocyte ballooning, and liver inflammation on histological examination (i.e., NAS>3 with at least 1 steatosis score of at least 1 lobular inflammation score and at least 1 hepatocyte ballooning score) in the absence of excessive alcohol consumption and after exclusion of other liver diseases such as viral hepatitis (HCV, HBV).

According to the invention, the terms NASH activity level refer to the progression of NASH and are defined as an increase in the NAS score above the minimum parameters for determining NASH, which are S=1, LI=1 and HB=1. The level of NASH activity also refers to the progression of NASH towards irreversible NASH and/or fibrosis and the severity of NASH.

According to the invention, the term active NASH refers to a NASH characterized by a NAS>4, at least 1 on steatosis, at least 1 on lobular inflammation, and at least 1 on hepatocyte ballooning.

In accordance with the present invention, the term hepatocellular ballooning is usually defined at the level of a light microscope based on hematoxylin and eosin (H&E) staining as an increase in cells 1.5-2 times the normal diameter of hepatocytes, with sparse cytoplasm. In a more general sense, the term refers to the process of cell death of hepatocytes.

According to the present invention, the term lobular inflammation refers to the presence of foci of lobular inflammation (aggregated inflammatory cells) on microscopic examination of a hematoxylin and eosin (H&E) stained liver biopsy section.

According to the present invention, the NAFLD or NAS activity score refers to the sum of the steatosis, hepatocellular ballooning, lobular inflammation scores as follows:

S: steatosis score: 0: <5%; 1: 5-33%; 2: 34-66% and 3:>66%;

LI: score for lobular inflammation (lesions/field x20): 0: no; 1: <2; 2:2-4 and 3:>4;

HB: ballooning degeneration score: 0: none; 1: few; 2: a lot.

According to the present invention, the activity index refers to the sum of the scores of hepatocellular ballooning and lobular inflammation.

According to the present invention, the term fibrosis or fibrosis of the liver refers to the presence of fibrous connective tissue on microscopic examination of a stained (H&E, trichrome or picrosirius red stain) liver biopsy.

In the context of the present invention, the term fibrosis stage refers to the location and degree of fibrosis on histological examination as follows:

Perisinusoidal or periportal fibrosis,

Mild perisinusoidal fibrosis (zone 3),

Moderate perisinusoidal fibrosis (zone 3),

Portal / periportal fibrosis,

Perisinusoidal and portal/periportal fibrosis,

bridging fibrosis,

Cirrhosis.

Alternatively, the stage of fibrosis can be defined as follows in the context of the present invention:

F=0: no fibrosis,

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F=1: minimal fibrosis,

F=2: significant fibrosis,

F=3: moderate fibrosis,

F=4: severe fibrosis (ie, cirrhosis).

According to the present invention, a subject to be treated or a TBT subject is a subject whose disease activity score (e.g., NAS or Activity Index) and/or stage of liver fibrosis makes the subject eligible for the treatment of NAFLD, NASH, and/or liver fibrosis. In contrast, a non-treatable subject, or NTBT subject, is a subject whose disease activity score (e.g., NAS or activity index) and/or liver fibrosis stage is not high enough to make it suitable for the treatment of NAFLD, NASH, and / or liver fibrosis. Therefore, a TBT subject is also referred to as a recipient or potential recipient of treatment for NAFLD, NASH, and/or liver fibrosis. In the present invention, the preferred TBT subjects are:

i) subjects with NASH, ii) subjects with active NASH, iii) subjects with significant, moderate or severe liver fibrosis, iv) subjects with NASH and fibrosis.

The definition encompasses various NASH activity scores and fibrosis stages defining various embodiments of the invention.

Preferred embodiments of the invention are detailed as follows.

The first version of TBT (TBT2).

A TBT2 subject is defined as a subject having the following liver biopsy scores:

S>1,

HB>1,

LI>1,

NAS (NAFLD activity score) >4, fibrosis stage >2 (such as fibrosis stage of 2, 3 or 4, in particular 2 or 3).

Thus, a subject with NTBT2 differs from a subject with TBT2 by at least one lower score on steatosis, hepatocyte ballooning, lobular inflammation, NAS, and/or fibrosis stage. For clarity, an NTBT2 subject may be, for example, a subject with NASH having NAS=4, S>1, LI>1, HB>1 and fibrosis stage 1 (such as fibrosis stage 1a, 1b or 1c) or NAS equal to 3 , and fibrosis stage >2 (eg, fibrosis stage equal to 2, 3, or 4), or any other combination of scores as defined above.

The second variant of TBT (TBT1).

A TBT1 subject is defined as a subject having the following liver biopsy scores:

steatosis score >1, hepatocyte ballooning score >1, lobular inflammation score >1,

NAS (NAFLD Activity Score) >4, fibrosis stage >1 (eg, fibrosis stage 1, 2, 3, or 4).

Similarly, an NTBT1 subject differs from a TBT1 subject by having at least one lower score for steatosis, hepatocyte ballooning, lobular inflammation, NAS, and/or fibrosis stage. For clarity, an NTBT1 subject may be, for example, a subject with NASH having NAS=4, S>1, LI>1, HB>1, and fibrosis stage 0, or NAS equal to 3 and fibrosis stage >1 (e.g., stage fibrosis equal to 1a, 1b or 1c, 2, 3 or 4), or any other combination of scores as defined above.

The third variant of TBT (TBT7).

A TBT7 subject is defined as a subject demonstrating the following liver biopsy scores:

steatosis score >1, hepatocyte ballooning score >1, lobular inflammation score >1,

NAS (NAFLD activity score) >4, fibrosis stage=1b, 1c, 2, 3, or 4.

Thus, an NTBT7 subject differs from a TBT7 subject in having at least one lower score on steatosis, hepatocyte ballooning, lobular inflammation, NAS, and/or fibrosis stage. For clarity, an NTBT7 subject may be, for example, a subject with NASH having NAS=4, S>1, LI>1, HB>1 and a fibrosis stage of 0 or 1a, or a NAS of 3 and a fibrosis stage of 1b, 1c, 2, 3 or 4, or any other combination of scores as defined above.

- 8 043299

In a specific embodiment, the miR-193 microRNA used in the present invention is selected from the group consisting of hsa-miR-193a-3p, hsa-miR-193a-5p, hsa-miR-193b-5p and hsa-miR193b-3p, the sequences of which are available in the miRBase database (http://mirbase.org), respectively, under miRBase access codes MIMAT0000459, MIMAT0004614, MIMAT004767, and MIMAT0002819, respectively.

In another embodiment, miR-193 miRNA used in the present invention is a miR-193 hairpin form, such as miR-193 miRNA selected from the group consisting of hsa-miR-193a, also referred to as HGNC:MIR193A, and hsa- miR-193b, the sequences of which are available in the miRBase database (http://mirbase.org), respectively, under miRBase access codes miRBase=MI0000487 and MI0003137.

In a specific embodiment, the miR-193 miRNA used in the present invention is hsa-miR-193b-3p.

Samples and sample preparation

According to the present invention, the term body fluid sample means any body fluid sample obtained from a subject, such as blood and blood-derived fluids (such as plasma and serum), lymphatic fluid, cerebrospinal fluid, synovial fluid, urine, saliva, mucous membranes, mucus and phlegm. In a particular embodiment, the biological fluid is selected from blood and fluids derived from blood (such as plasma and serum), saliva, cerebrospinal fluid, and urine. In a particular embodiment, the body fluid sample is blood or a blood-derived fluid (such as plasma and serum), saliva, cerebrospinal fluid, or urine. In yet another specific embodiment, the biological fluid is blood, plasma or serum. The biological fluid sample may be taken by any suitable means. Suitable biological fluids may be cell-free fluids. Such cell-free biological fluids are typically obtained by treating the cell-containing biological fluid by, for example, centrifugation or filtration to remove cells. As a rule, a cell-free biological fluid does not contain intact cells, however, some fluids may contain cell fragments or cellular debris. The body fluid sample may be used immediately or may be stored for later use. Any suitable storage method known in the art can be used to store the biological fluid sample: for example, the sample can be frozen at -20 to -80°C.

Isolation and quantification of miRNAs

Total RNA, including miRNA, can be isolated from a sample by various extraction methods, which include: phenol:chloroform extraction followed by alcohol precipitation (TRIzol), phenol:chloroform extraction followed by solid phase extraction (on columns; e.g. miRVana and miRNeasy) and solid phase separation with/without magnetic affinity resin particles (Norgen total and Isolate II) or direct lysis methods. In the practice of the present invention, microRNAs were extracted using the miRVana Paris extraction kit for subsequent quantitative RT-PCR (RTqPCR) analysis or captured using special probes for further HTG Edge Sequence analysis.

The miRNAs are then detected in clinical samples using any technique available to those skilled in the art, such as sequencing-based, amplification-based, or hybridization-based methods. Common approaches to clinical testing of miRNAs include short RNA sequencing (Hafner et al, 2012; Vigneault et al, 2012), HTG Edge Whole Transcriptome, a next-generation sequencing-based miRNA profiling platform (Lizarraga et al, 2016; Satake et al, 2018 ), quantitative real-time miRNA reverse transcription PCR (qRT-PCR) (Chen et al., 2005), miRNA microarray (Castoldi et al., 2007), multiplex microRNA detection using color-coded probe pairs (NanoString expression system n Counter) (Geiss et al., 2008), spot digital PCR (ddPCR) after reverse transcription (Miotto et al., 2014), and in situ microRNA hybridization (Nelson et al., 2006). The level of miR193 can be determined using conventional methodologies well known in the art such as immunoassays (e.g. ELISA) or molecular biology assays (quantitative OT-PCR or next generation sequencing) or biochemical assays (colorimetric or other assays) . In a specific embodiment of the method of the present invention, miRNAs are detected using HTG Edge whole transcriptome assays or HTG Edge sequencing and quantitative OT-PCR.

In the practice of the present invention, any of the methods described above may further include normalizing the level of miR-193 in a body fluid sample from a subject to a level or microRNA level that does not change in subjects with NAFLD, NASH and/or liver fibrosis relative to healthy patients. In order to reduce a potential source of technical variability, an additional or exogenous synthetic microRNA of known sequence and quantity, such as miR-39C, can be added to the sample prior to RNA extraction.

- 9 043299 elegans. The additive or exogenous synthetic miRNA may be a miRNA that is not expressed in human samples, such as cel-miR-38 Caenorhabditis elegans or ath-miR159a Arabidopsis thaliana. These synthetic microRNAs can be added after the addition of lysis buffer to blood samples prior to RNA extraction and provide process control with respect to technical normalization. Thus, the efficiency of RNA extraction, complementary DNA synthesis and PCR amplification can be controlled using these exogenous synthetic miRNAs.

A microRNA normalizer or small non-coding RNA controls for normalizing quantitative PCR data, which are endogenous controls exposed to the same sources of variability as target genes at all stages of the experimental process, can be used to normalize the level of target miRNA, miR- 193.

A standard protocol for measuring miR-193 by quantitative OT-PCR is provided. Briefly, measurements are made on total RNA isolated from a biological fluid sample, such as a blood, plasma or serum sample, in particular a platelet-free cell-free plasma sample obtained using citrate. An appropriate internal control (such as miRNA of known sequence and quantity, eg C. elegans miR-39) can be added to the sample prior to RNA extraction. Cq values are determined using quantitative OT-PCR. Commercial kits are available for such assays. For example, the Taqman miRNA RT-qPCR assay: Taqman MicroRNA reverse transcription kit, TaqMan MicroRNA 20X assay, and TaqMan Universal Master Mix II (Applied Biosystems) can be used according to the manufacturer's instructions. Reverse transcription can be performed using readily available PCR systems such as the GeneAmp® PCR System 9700 thermal cycler (Applied Biosystems) with appropriate cycling settings such as 16°C for 30 minutes followed by 42°C for 30 minutes and 85° C for 5 minutes and subsequent holding at 4°C. Reverse transcription may be implemented in a multiplexed format. Quantitative PCR is then carried out using a quantitative PCR system such as the CFX96TM real-time system (C1000 TouchTM Thermal Cycler, BioRad). Preferably, quantitative PCR is carried out using Bio-Rad's CFX96-C1000 Certified In Vitro Diagnostic (IVD) Real Time PCR Detection System. Cycling conditions can be as follows: 95°C for 10 minutes, then 95°C for 15 s and 60°C for 60 s for a total of 50 cycles, followed by 30°C for 30 s. The Cq determination mode may be, for example, the regression mode in a quantitative PCR system. In a specific embodiment, the Cq value determined in accordance with the method of the invention is the Cq value that can be obtained using the above specific parameters and material. The Cq values of the samples may be excluded from the analysis if the values exceed the maximum Cq of the standard curve of each miRNA. The standard curve can be used to evaluate the performance of the PCR reaction. Serial dilutions can be made at eight points, starting with the most concentrated cDNA sample, to ensure that the standard curve covers all potential template concentrations that may be encountered during the assay. The standard curve can be constructed by plotting the logarithm of the initial amount of the matrix with respect to the obtained Cq values. For absolute quantitation, synthetic miRNAs (e.g. from Integrated DNA Technologies, 5'-phosphate, 3'OH, HPLC purified) diluted to e.g. 3.125 fmol/ml and 5 µl can be used for reverse transcription simultaneously with RNA extracted from serum samples. The product can then be serially diluted and PCR performed on all samples (standards and serum-derived RNA). The standard curve can be drawn once, twice, or three times and used to convert Cq data to copies/µl of fluid.

Alternatively, delta Ct (cycle threshold) or delta Cq (cycle quantification) can be used to assess miR-193 levels. Delta Ct or delta Cq corresponds to the difference between the Ct or Cq of the target in the patient test sample and the Ct or Cq of the target in the control sample (ie, healthy subjects, control sample).

Alternatively, miR-193 levels can be determined by quantitative RT-PCR using a hairpin reverse transcription (RT) reaction along with TaqMan qPCR or poly(A) tail RT along with detection of SYBR Green and closed nucleic acid (LNA) primers .

Methods of the invention

In all of the following aspects, embodiments, and embodiments, the preferred embodiment relates to determining the level of hsa-miR-193 in a blood, serum, or plasma sample. A preferred embodiment of this aspect relates to determining the level of hsa-miR-193b-3p.

The present invention relates to a method for diagnosing or detecting NAFLD in a subject, including determining the level of miR-193 in a sample of a biological fluid of the specified subject. The present invention relates to a method for diagnosing or detecting potential NAFLD in a subject, which includes determining the level of miR-193 in a sample of a biological fluid of the specified subject. In a specific embodiment, NAFLD or potential NAFLD is detected based on an elevated level of miR-193 in a body fluid sample from a subject relative to a control level measured in a sample from a subject without hepatic steatosis. In a further specific embodiment, the diagnosis or detection of NAFLD or potential NAFLD is based on the detection of elevated levels of miR-193 in a body fluid sample compared to levels normally measured in healthy individuals without hepatic steatosis. In a specific embodiment, the method further includes the step of confirming that the subject is suffering from NAFLD. Such confirmation can be carried out in accordance with any method known to those skilled in the art, such as taking a liver biopsy or ultrasound or imaging techniques (such as ultrasound, measurement of the controlled attenuation parameter using transient elastography (Fibroscan), magnetic resonance imaging ( MRI), Proton Density Weighted Fat Fraction Measurement by Magnetic Resonance Imaging (MRI-DPFF), and Proton Density Weighted Fat Fraction Measurement by Magnetic Resonance Spectroscopy (MRS-DPFF)). Alternatively, hepatic steatosis can be assessed by several indicators and scores, including, without limitation:

liver fat index (FLI), which includes BMI, waist circumference and serum triglyceride and gamma-glutaryltransferase (GGT) levels, liver steatosis index (HIS), which includes the ratio of aspartate aminotransferase (AST) to alanine aminotransferase (ALT) in serum, BMI, gender and presence of diabetes, NAFLD (metabolic syndrome, type 2 diabetes, fasting serum insulin and AST, AST:ALT ratio), steatotest (alpha 2 macroglobulin (A2M), haptoglobin, apolipoprotein A1, total bilirubin, GGT, fasting blood glucose and adjusted for age, sex, weight, and height), and NAFLD score (ALT, cholesterol, triglycerides, glycated hemoglobin A1c (HbA1 and WBC count) and data on comorbidities (hypertension)).

In a specific embodiment, genetic and genomic markers can assess the risk and severity of NAFLD (single nucleotide polymorphisms (SNPs): rs738409 (SNPs in PNPLA3), cell-free non-coding RNAs, miR-122, a composite panel of serum-derived omics data).

The present invention also relates to a method for diagnosing or detecting NASH in a subject, which includes determining the level of miR-193 in a sample of a biological fluid of the specified subject. The present invention also relates to a method for diagnosing or detecting potential NASH in a subject, which includes determining the level of miR-193 in a sample of a biological fluid of the specified subject. In a specific embodiment, the diagnosis or detection of NASH or potential NASH is based on the detection of an elevated level of miR-193 in a body fluid from a subject relative to a control level of miR-193 measured in a healthy subject, in a subject with NAS<3, or in a subject with at least one NAS component scored as 0. In a specific embodiment, a control sample is taken from a subject with NAS<3 with at least one NAS component scored as 0, such as a subject with the following scores: S=1, LI=1, and HB =0; S=1, LI=0 and HB=1; S=0, LI=1 and HB=1. In a specific embodiment, the diagnosis or detection of NASH or potential NASH is based on the detection of elevated levels of hsa-miR-193 expression, in particular hsa-miR-193a-3p, hsa-miR-193a-5p, hsa-miR-193b-3p and hsa-miR-193b-5p in blood, serum, or plasma relative to control levels measured in subjects without NASH, including healthy subjects, subjects with NAS<3, or subjects with at least one NAS component scored as 0. In a particular embodiment, carrying out the method further includes the step of confirming that the subject suffers from NASH. Such confirmation can be performed according to any method known to those skilled in the art, such as taking a liver biopsy or imaging biomarkers measured by imaging techniques such as MRI-based techniques, gadoxetic acid MRI, superparamagnetic iron oxide MRI. , intracellular ATP level using 32P-MRS and MRE. Alternatively, several indices and scores can evaluate potential NASH biomarkers, including, without limitation:

apoptosis markers (CK18 fragment, total cytokeratin, serum level of apoptosis-mediated FAS surface antigen), inflammatory markers (C-reactive protein (CRP), TNF, IL-8, chemokine ligand CXC 10 (CXCL10)), lipid oxidation products (11-hydroxyeicosatetraenoic acid (HETE), 9hydroxydecadienoic acid (HODE), 13-HODE, 13-oxooctadecadienoic acid (ODE), LA-13HODE (OxNASH score), 11,12-dihydroxy)-eicosatrienoic acid (diHETrE)), adipocytokines and hormones (adiponectin , leptin, resistin, visfatin, retinol binding protein (RBP) 4, fatty acid binding protein (FABP) 4, fibroblast growth factor (FGF21)), lysosomal enzymes (cathepsin D), and combination panels (NASH test, NASH diagnostic panel).

The present invention also relates to a method for diagnosing or detecting active NASH

- 11 043299 in a subject, which includes determining the level of miR-193 in a sample of biological fluid of the specified subject. The present invention also relates to a method for diagnosing or detecting potential active NASH in a subject, which includes determining the level of miR-193 in a sample of a biological fluid of the specified subject. In a specific embodiment, the diagnosis or detection of active NASH or potential active NASH is based on the detection of an elevated level of miR-193 in a body fluid from a subject compared to a control level of miR-193 measured in a healthy subject, in a subject with NAS<4, or in a subject with at least one NAS component scored as 0. In a specific embodiment, the control sample is taken from a subject with NAS=3, S=1, LI=1, and HB=1. In a specific embodiment, the diagnosis or detection of active NASH or potential active NASH is based on the detection of elevated levels of hsa-miR-193 expression, in particular hsa-miR-193a-3p, hsa-miR-193a-5p, hsa-miR-193b3p and hsa-miR-193b-5p in blood, serum, or plasma samples of a subject compared to control levels measured in healthy subjects, subjects with NAS<4, or subjects with at least one NAS component scored as 0. In a particular embodiment, the method further includes the step of confirming that the subject is suffering from active NASH. Such confirmation can be performed according to any method known to those skilled in the art, such as liver biopsy or imaging techniques such as MRI-based, superparamagnetic iron oxide MRI, multiparametric MRI, MRS, and MRE. Alternatively, several indices and scores can evaluate potential NASH biomarkers, including, without limitation:

apoptosis markers (CK18 fragment, total cytokeratin, serum level of apoptosis-mediated FAS surface antigen), inflammatory markers (C-reactive protein (CRP), TNF, IL-8, chemokine ligand CXC 10 (CXCL10)), lipid oxidation products (11-hydroxyeicosatetraenoic acid (HETE), 9hydroxydecadienoic acid (HODE), 13-HODE, 13-oxooctadecadienoic acid (ODE), LA-13HODE (OxNASH score), 11,12-dihydroxy)-eicosatrienoic acid (diHETrE)), adipocytokines and hormones (adiponectin , leptin, resistin, visfatin, retinol binding protein (RBP) 4, fatty acid binding protein (FABP) 4, fibroblast growth factor (FGF21)), lysosomal enzymes (cathepsin D), and combination panels (NASH test, NASH diagnostic panel).

Such confirmation can be done by measuring the risk of NAFLD (progression to NASH or fibrosis) and severity markers such as genetic and genomic markers such as SNPs (rs738409 in PNPLA3), cell free non-coding RNAs (miR-122, miR-1290, miR- 192 and miR-7b), a composite panel of serum-derived omics data such as rs738409 and proteomic data including ACY1, SHBG, CTSZ, MET, GNS, LGALS3BP, CHL1 and SERPINC1, SNPs at multiple loci (PNPLA3, SOD2, KLF6 and LPIN1), miR-122, a composite panel including miR-122, miR-192, miR-21, ALT, CK18 Asp396, cell-free DNA such as circulating methylated PPARG.

The present invention also relates to a method for characterizing the occurrence or extent of lobular inflammation of the liver in a subject, including determining the level of miR-193 in a sample of a biological fluid of the specified subject.

The present invention also relates to a method for characterizing the occurrence or degree of ballooning of hepatocytes in a subject, which includes determining the level of miR-193 in a sample of a biological fluid of the specified subject.

The present invention also relates to a method for characterizing the occurrence or degree of hepatic steatosis in a subject, including determining the level of hsa-miR-193 in a sample of a biological fluid of the specified subject.

The present invention also relates to a method for diagnosing or detecting hepatic fibrosis in a subject, including determining the level of miR-193 (such as hsa-miR-193) in a sample of the biological fluid of the specified subject. The present invention also relates to a method for diagnosing or detecting potential liver fibrosis in a subject, which includes determining the level of miR-193 in a sample of a biological fluid of the specified subject. In a specific embodiment, the fibrosis is at least significant fibrosis (ie, F>2). In a variant of this embodiment, the diagnosis or detection of liver fibrosis or potential liver fibrosis is based on the detection of an elevated level of miR-193 in the body fluid from the subject relative to a control level of miR-193 measured in a subject with no fibrosis or minimal fibrosis, in particular with minimal fibrosis . In a further specific embodiment, the fibrosis is at least moderate fibrosis or cirrhosis of the liver (ie, F>3). In a variant of this embodiment, the diagnosis or detection of liver fibrosis or potential liver fibrosis is based on the detection of an elevated level of miR-193 in the body fluid from a subject compared to a control level of miR-193 measured in a subject without fibrosis, with

- 12 043299 minimal fibrosis or with severe fibrosis, in particular with severe fibrosis. In a specific embodiment, the method further includes the step of confirming that the subject is suffering from liver fibrosis or confirming the stage of liver fibrosis. Such confirmation may be performed in accordance with any method known to those skilled in the art, such as by taking a liver biopsy or by means of imaging biomarkers, including, without limitation:

FibroScan (transient elastography), point transverse wave elastography pSWE, acoustic radiation force impulse (ARFI), 2D 3D shear wave elastography 2D-3D SWE, magnetic resonance elastography MRE, multiparametric MRI.

Alternatively, several non-invasive tests for fibrosis and cirrhosis of the liver:

AST:ALT ratio and AST:platelet ratio index (APRI), fibrosis index-4 (FIB-4) which includes age, AST, ALT and platelet count, NAFLD fibrosis score (age, BMI, impaired fasting glucose and/or diabetes, AST, ALT, platelet count and albumin), BARD core (AST, ALT, BMI and diabetes).

In another embodiment, specific liver fibrosis markers and a panel can assess liver fibrosis:

specific markers of fibrosis: hyaluronic acid, type III collagen N-terminal propeptide (PIIINP), specific competitive neo-epitope immunoassay for PIIINP (Pro-C3), tissue inhibitor of metalloproteinases (TIMP-1), laminin.

Fibrosis-specific panels: improved panel for liver fibrosis (ELF), which includes PIIINP, hyaluronic acid and TIMP-1; Fibrotest (gamma-glutamyltransferase (GGT), total bilirubin, alpha-2 macroglobulin (A2M), apolipoprotein A1 and haptoglobin; FibroMeter NAFLD (body weight, prothrombin index, ALT, AST, ferritin and fasting glucose).

The present invention also relates to a method for determining the stage of liver fibrosis in a subject, including determining the level of miR-193 (such as hsa-miR-193) in a sample of the body fluid of the specified subject.

In a specific embodiment, stage F=4 can be determined if the level of miR-193 in the body fluid sample of the specified subject is higher than the level of miR-193 in the control sample from the subject with stage F<4 fibrosis, for example, when F=0, F =1, F=2 or F=3. In a specific embodiment, the control sample is taken from a subject with F=3.

In a specific embodiment, stage F=3 can be determined if the level of miR-193 in the body fluid sample of the specified subject is higher than the level of miR-193 in the control sample from the subject with stage F<3 fibrosis, for example, with F=0, F =1 or F=2. In a specific embodiment, the control sample is taken from a subject with F=2.

In a specific embodiment, stage F=2 can be determined if the level of miR-193 in the body fluid sample of the specified subject is higher than the level of miR-193 in the control sample from the subject with stage F<2 fibrosis, for example, with F=0 or F =1. In a specific embodiment, the control sample is taken from a subject with F=1.

In a specific embodiment, stage F=1 can be determined if the level of miR-193 in the body fluid sample of the specified subject is higher than the level of miR-193 in the control sample from the subject with stage F<1 fibrosis, for example, with F=0.

In a specific embodiment, the method is for diagnosing and detecting significant or severe fibrosis (F>2) and progressive liver fibrosis (F>3) in a subject with NAFLD or NASH based on the detection of elevated levels of hsa-miR-193 expression, in particular hsa -miR193a-3p, hsa-miR-193a-5p, hsa-miR-193b-3p, and hsa-miR-193b-5p, in blood, serum, or plasma samples from the subject compared to control levels measured in patients without fibrosis and /or with minimal fibrosis (F=0-1).

In a specific embodiment, the method for determining the stage of liver fibrosis further includes the step of confirming the stage of liver fibrosis in the subject. Such confirmation may be carried out in accordance with any method known to those skilled in the art, for example by taking a liver biopsy or by other means such as the imaging biomarkers listed above for diagnosing fibrosis.

Since liver fibrosis is a common consequence of most chronic liver diseases, the present invention also relates to the diagnosis and detection of significant or progressive liver fibrosis caused by other fibrotic liver diseases such as viral hepatitis (HBV, HCV, ...), alcoholic steatohepatitis, biliary tract diseases. pathways (primary biliary cholangitis, primary sclerosing cholangitis, autoimmune hepatitis, Wilson's disease, alpha-1 antitrypsin deficiency).

- 13 043299

The present invention also relates to a method for classifying a subject as potentially receiving or not receiving treatment for NAFLD, NASH and/or liver fibrosis, which includes determining the level of miR-193 in a sample of said subject's body fluid. In a specific embodiment, the method is for classifying a subject as potentially receiving or not receiving NAFLD treatment. In another specific embodiment, the method is for classifying a subject as potentially receiving or not receiving NASH treatment. In a further embodiment, the method is for classifying a subject as a potential potentially treated or untreated liver fibrosis.

More specifically, the present invention relates to a method for classifying a subject as potentially receiving (TBT) or not receiving (NTBT) NASH and/or fibrosis treatment, comprising determining the level of miR-193 (such as hsa-miR-193) in a biological sample. fluids of said subject.

In a specific embodiment, a subject is classified as a TBT2 subject if the miR-193 level in said subject's body fluid sample is higher than the miR-193 level in the subject's control NTBT2 sample. In a specific embodiment, an NTBT2 subject is a subject with NAS=4, S>1, LI>1, HB>1, and F=1 (eg, fibrosis stage 1a, 1b, or 1c).

In a specific embodiment, a subject is classified as a TBT1 subject if the miR-193 level in the subject's body fluid sample is higher than the miR-193 level in the subject's control NTBT1 sample. In a particular embodiment, an NTBT1 subject is a subject with NAS=4, S>1, LI>1, HB>1, and F=0.

In a specific embodiment, a subject is classified as a TBT7 subject if the miR-193 level in the subject's body fluid sample is higher than the miR-193 level in the subject's control NTBT7 sample. In a specific embodiment, an NTBT7 subject is a subject with NAS=4, S>1, LI>1, HB>1, and F=1a.

In a specific embodiment, the method of the invention is for classifying a subject as a TBT2 subject.

Other embodiments of the invention relate to a method for classifying patients as potentially receiving (TBT) or not receiving (NTBT) treatment for NASH and/or fibrosis based on the detection of increased expression of hsa-miR-193, in particular hsa-miR-193a-5p, hsa -miR-193b-3p and hsa-miR193b-5p, in blood, serum, or plasma compared to hsa-miR-193 control levels measured in NTBT patients.

Such a classification may also serve as a basis for determining whether a subject should undergo further liver tests, such as modern liver tests such as ultrasound, elastography, imaging techniques, including MRI, or a liver biopsy, before a treatment decision is made.

The definition of TBT, or treated patient, as opposed to NTBT, or untreated patient, may vary depending on the balance of drug efficacy and drug safety at different values of disease activity (NAS or activity index) and different values of fibrosis stage, as above.

The present invention also relates to a method for determining NAFLD or NASH activity in a subject, including determining the level of miR-193 (such as hsa-miR-193) in a sample of a biological fluid of the specified subject.

The invention also relates to a method for predicting the risk of developing NAFLD or NASH activity in a subject, which includes determining the level of miR-193 (such as hsa-miR-193) in a sample of the body fluid of the specified subject. In a specific embodiment, the method is designed to predict the risk of developing NAFLD or NASH activity in the absence of treatment.

The invention also relates to a method for predicting the risk of developing fibrosis to cirrhosis of the liver and clinical outcomes in a patient, including determining the level of miR-193 (such as hsamiR-193) in a sample of the biological fluid of the specified patient. In a specific embodiment, the method is designed to predict the risk of developing fibrosis to cirrhosis and clinical outcomes for the liver in the absence of treatment.

The invention also relates to a method for monitoring the development (ie, progression or regression) of NAFLD or NASH activity in a subject, which includes determining the level of hsamiR-193 in a sample of said subject's body fluid.

The invention also relates to a method for monitoring the development (ie, progression or regression) of liver fibrosis in a subject, which includes determining the level of hsa-miR-193 in a sample of the biological fluid of the specified subject.

The invention also relates to a method for predicting a patient's response to a particular treatment for NAFLD, NASH and/or liver fibrosis, which includes determining the level of hsa-miR-193 in a sample of a biological fluid of the specified subject.

- 14 043299

According to another embodiment, the invention relates to a method for determining the stage of steatosis in a subject based on determining the level of miR-193 in a sample of a subject's body fluid.

According to another embodiment, the invention relates to a method for determining the degree of hepatocellular ballooning in a subject based on determining the level of miR-193 in a sample of a subject's body fluid.

According to another embodiment, the invention relates to a method for determining the degree of lobular inflammation in a subject based on determining the level of miR-193 in a sample of a subject's body fluid.

In the practice of the present invention, miR-193 threshold concentrations can be calculated to facilitate decision making by the person implementing the methods of the present invention. As used herein, the expression threshold concentration refers to the concentration of miR-193 above which a symptom or disease is statistically predicted and below which a disease or symptom is not statistically predicted. Such threshold concentrations can be determined as follows for various scenarios.

The threshold concentration for classifying a subject as a subject with NAFLD (or potential NAFLD) or as a healthy subject without NAFLD can be determined by:

i) measuring the concentration of miR-193 in body fluid samples from control cohorts of subjects, including subjects with NAFLD and healthy subjects without NAFLD, ii) applying a specific statistical analysis to the control data set to determine the optimal concentration threshold.

In particular, the current statistical ROC (Correct/False Detection Ratio) method can be applied to calculate the optimal concentration threshold to distinguish between NAFLD and healthy subjects in control cohorts.

The cutoff for classifying a subject as a subject with NASH (or potential NASH) or as a subject without NASH can be determined by:

i) measuring miR-193 concentrations in body fluid samples of control cohorts of subjects, including both NASH and non-NASH subjects, ii) applying a specific statistical analysis to the control data set to determine the optimal concentration threshold. In particular, the current statistical ROC (correct/false detection ratios) method can be applied to calculate the optimal cut-off concentration to distinguish between subjects with NASH (or potential NASH) and subjects without NASH in control cohorts.

The threshold concentration for classifying a subject as a subject with active NASH (or potential active NASH) or as a subject without active NASH can be determined by:

i) measuring miR-193 concentrations in body fluid samples of control cohorts of subjects, including subjects with active NASH and subjects without active NASH, ii) applying a specific statistical analysis to the control data set to determine the optimal concentration threshold. In particular, the modern statistical method of ROC (correct/false detection ratios) can be applied to calculate the optimal threshold concentration to distinguish between patients with active NASH (or potential active NASH) and subjects without active NASH in control cohorts.

The threshold concentration for classifying a subject as having significant hepatic fibrosis (F>2) (or potentially significant hepatic fibrosis) or as having no fibrosis or minimal fibrosis can be determined by:

i) measurements of miR-193 concentrations in body fluid samples of control cohorts of patients, including both patients with significant or severe liver fibrosis (F>2) or advanced liver fibrosis (F>3), and subjects without fibrosis or with minimal fibrosis (F =0-1), ii) applying a special statistical analysis to the control data set to determine the optimal threshold concentration. In particular, the modern statistical method of ROC (correct/false detection ratios) can be used to calculate the optimal threshold concentration to distinguish between subjects with significant liver fibrosis (F>2) or severe liver fibrosis (F>3) and subjects with no fibrosis or minimal fibrosis (F=0-1) in control cohorts.

The threshold concentration for classifying a subject as a TBT subject or an NTBT subject can be determined by:

i) measuring concentrations of miR-193 in body fluid samples of control cohorts of subjects, including both TBT and NTBT subjects, ii) applying a specific statistical analysis to the control data set to determine the optimal concentration threshold. In particular, the modern statistical method of ROC (correct and false detection ratios) can be applied to calculate the optimal concentration threshold for distinguishing between TBT and NTBT subjects in control cohorts.

- 15 043299

The data presented herein show that miR-193 is a circulating diagnostic biomarker for non-invasive classification of histological lesions (steatosis, lobular inflammation, hepatocyte ballooning), assessment of NAFLD activity level, activity level

NASH and assessment of the severity of liver fibrosis in the subject.

According to another embodiment of the present invention, a method is provided for predicting the risk of developing NAFLD or NASH activity in a subject in the absence of treatment based on the level of miR-193 in a subject's body fluid sample.

Another embodiment of the invention relates to a method for predicting the risk of fibrosis to cirrhosis and liver outcomes in a patient with NAFLD or NASH based on miR-193 levels measured in a subject's body fluid sample. The present invention is also intended to predict the risk of developing fibrosis in patients suffering from other fibrotic liver diseases such as: viral hepatitis (HBV, HCV, ...), alcoholic steatohepatitis, diseases of the biliary tract (primary biliary cholangitis, primary sclerosing cholangitis, autoimmune hepatitis , Wilson's disease, alpha-1 antitrypsin deficiency).

The present inventors have also shown a correlation between changes in circulating miR-193 levels and an increase in histological parameters, in particular an increase in activity index, NAS and fibrosis stage. These assays support the use of miR-193 in a method for monitoring histological progression in a subject, whether or not they are being treated with an anti-NAFLD drug, an anti-NASH drug, or an anti-fibrotic drug. In addition, the method of the invention can be used to evaluate the activity of a drug against NAFLD, against NASH and/or against fibrosis in intervention trials involving changes in serum miR-193 levels as surrogates for histological evolution.

Thus, another embodiment of the present invention relates to a method for monitoring the evolution (i.e., progression or regression) of NAFLD or NASH activity based on the evolution of the level of MIR-193 in body fluid samples collected at two or more different time points from the same same subject.

Thus, another embodiment of the invention relates to a method for monitoring the evolution (i.e., progression or regression) of the stage of liver fibrosis, based on the evolution of miR193 levels in body fluid samples taken two or more times separately from the same subject.

The present invention also relates to the staging of fibrosis in other fibrotic liver diseases such as: viral hepatitis (HBV, HCV, ...), alcoholic steatohepatitis, diseases of the biliary tract (primary biliary cholangitis, primary sclerosing cholangitis, autoimmune hepatitis, Wilson's disease , alpha-1 antitrypsin deficiency).

Another aspect of the invention relates to a method for predicting a subject's response (predicting changes in NAFLD activity, NASH activity, and liver fibrosis stage) to a particular treatment (responder subject) based on detecting the level of miR-193 differential expression in a subject's body fluid sample compared to control levels measured in subjects not responding to therapy.

Thus, the present invention provides methods for:

characterizing the presence of NAFLD in a subject, characterizing the presence of NASH in a subject, characterizing the presence of hepatic fibrosis in a subject, characterizing the presence of hepatocellular ballooning in a subject, characterizing the presence of lobular inflammation in a subject, or characterizing the presence of hepatic steatosis in a subject.

In addition, the present invention provides methods for: diagnosing a subject for NAFLD and/or more severe NAFLD, diagnosing a subject for NASH and/or more severe NASH, diagnosing a subject as having liver fibrosis and/or advanced liver fibrosis, diagnosing the subject having hepatocellular ballooning and/or a higher hepatocellular ballooning score, diagnosing the subject with lobular inflammation and/or a higher score for lobular inflammation, or diagnosing the subject as having hepatic steatosis and/or a higher hepatic steatosis score.

In addition, the methods according to the present invention allow:

determine NAFLD or NASH activity in a subject, determine the stage of fibrosis in a subject, determine the severity of NASH in a subject, or determine the progression or regression of pathology in a patient with NASH.

In addition, the methods according to the present invention allow:

classify the subject as receiving or not receiving NAFLD treatment,

classify the subject as treated or untreated for NASH, classify the subject as treated or untreated for hepatic fibrosis, classify the subject as treated or untreated for hepatocellular ballooning, classify the subject as treated or untreated for lobular inflammation, or classify the subject as treated or untreated for hepatic steatosis.

In addition, the methods according to the present invention allow:

evaluate the effectiveness of drug treatment based on the administration of a drug for the treatment of NAFLD disease, evaluate the effectiveness of drug treatment based on the administration of a drug for the treatment of NASH disease, evaluate the effectiveness of drug treatment based on the administration of a drug for the treatment of fibrosis disease, evaluate the effectiveness of drug treatment, based on the administration of a drug for the treatment of a hepatocellular ballooning disease, or to evaluate the effectiveness of a drug treatment based on the administration of a drug for the treatment of a lobular inflammation disease.

In addition, the methods according to the present invention allow:

determine the progression or regression of pathology in a patient with NAFLD after administration of drug treatment, determine the progression or regression of pathology in a patient with NASH after administration of drug treatment, determine the progression or regression of pathology in a patient suffering from fibrosis after administration of drug treatment, determine the progression or regression of pathology in of a patient suffering from hepatocellular ballooning disease after administration of drug treatment, or to determine the progression or regression of pathology in a patient suffering from lobular inflammation disease after administration of drug treatment.

In addition, the methods according to the present invention allow:

predict whether a patient will respond or not, i.e., whether they are a potential responder or not a responder to a particular NAFLD drug treatment, predict whether a patient will respond or not, i.e., whether they are (potentially) a responder or ( potentially) is not a Responder to drug treatment for NASH, predict whether the patient will respond or not, i.e. whether he is (potentially) a Responder or (potentially) not a Responder to drug treatment for liver fibrosis, predict whether whether the patient responds or not, i.e. whether he is (potentially) a responder or (potentially) not a responder to medication for the treatment of hepatocellular disease, or to predict whether the patient will respond or not, i.e. whether he is (potentially) a responder or (potentially) is not a responder to medical treatment of lobular inflammation disease.

In some embodiments, methods for determining whether a subject has NAFLD or NASH, or active NASH, or hepatic fibrosis (such as significant liver fibrosis), or lobular inflammation, or hepatocyte ballooning, or determining whether a subject is a drug recipient (TBT) or a potential responder for a particular drug, includes taking a body fluid sample from a subject suspected of having the condition being assessed and determining miR-193 levels; wherein a level higher than the control level of miR-193 indicates the presence of the condition being assessed, or the diagnosis of the subject as having NAFLD or NASH, or active NASH, or hepatic fibrosis (such as significant fibrosis), or lobular inflammation, or ballooning of hepatocytes , or that the subject is a potential drug recipient (TBT) or responder.

In specific embodiments, the subject is a subject at risk of developing NALFD, NASH, active NASH, or hepatic fibrosis, or a subject at risk of developing NAFLD, NASH, active NASH, or hepatic fibrosis in the future, such as a subject that is obese, diabetic, suffering from metabolic syndrome, and /or having elevated levels of liver enzymes and/or having other signs of liver dysfunction. The subject may also be a subject with previously identified NAFLD, NASH, or active NASH, or hepatic fibrosis, whereby the method of the invention allows disease activity and fibrosis staging to be determined and the risks of disease progression towards cirrhosis, cirrhotic complications, hepatocarcinoma, liver transplantation, cardiovascular disease, or death associated with the liver.

- 17 043299

In specific embodiments, the subject suffers from NASH, wherein the method of the invention determines the efficacy of a drug in the treatment of NASH, classifies the subject as a NASH responder/non-responder, or monitors the evolution of the subject's NASH condition.

According to a specific aspect of the invention, for each type of patient to be treated, a NASH score can be obtained.

In specific embodiments of the present invention, to diagnose NAFLD, NASH, or liver fibrosis and/or to determine disease activity, stage of fibrosis in a subject, and/or to assess the effectiveness of drug treatment, and/or to determine the evolution (progression or regression) of pathology in a subject with NAFLD, with NASH or liver fibrosis, and/or to classify a subject as a potential non-responder to drug treatment, and/or to predict disease outcome for a subject, miR-193 measurement can be introduced into mathematical models (algorithms) to be combined with other variables such as sex, age, body mass index, weight, health status, blood pressure, or other body fluid markers such as circulating blood, serum, or plasma markers, such as those listed in the table below.

Function of hepatocytes fatty textile Metabolism Oxidative stress/apopto 3 Fibrosis Inflammation ALT AST ALP GGT Haptoglobin Albumin Bilirubin n Platelet count Adiponec tin Leptin resistin Fasting plasma glucose Fasting insulin HOMA index Triglycerides Cholesterol livp VLCL-C Apolipoproteins (ApoAl, ApoB, ApoCSH) Malondialdehyde TBARS OxLDL CK18-M30 CK18-M65 ferritin YKL-40 (CHI3L1) Fibronectin Hyaluronic acid Collagen type IV PIIINP TIMP-1 TNFa ILlb, IL6, IL8, IFNg, TGFb hs-CRP MCP1 sCD14

According to another embodiment, the methods of the present invention include the determination of the level of other biomarkers in addition to miR-193.

In a specific embodiment, such biomarkers are selected from the group consisting of alpha-2 macroglobulin (A2M), glycated hemoglobin (HbA1c), fasting glucose or fructosamine levels, N-terminal type III collagen propeptide (PIIINP), and YKL-40.

In a further specific embodiment, such biomarkers are selected from the group consisting of TIMP-1, YKL-40, platelet count, metabolic syndrome, hyaluronic acid, and HbA1c.

In another additional specific embodiment, such biomarkers are selected from the group consisting of TIMP-1, YKL-40, platelet count, and metabolic syndrome.

In another specific embodiment, such biomarkers are selected from the group consisting of TIMP-1, YKL-40, platelet count, hyaluronic acid, and HbA1c.

In a more specific embodiment, such a biomarker is YKL-40, TIMP-1, PIIINP, HbA1c, platelet count, or A2M.

In another embodiment, such biomarkers are markers of NAFLD, NASH, or liver fibrosis, such as the degree of steatosis, non-inflammation, and fibrosis, as assessed by magnetic resonance imaging (MRI), magnetic resonance elastography (MRE), magnetic resonance spectroscopy (MRS), measurements of controlled attenuation parameter (CAP) and liver stiffness by transient elastography (TE), ultrasound (USG), FibroScan, point transverse wave elastography (pSWE), 2D shear wave elastography (2D-SWE), single nucleotide polymorphisms (SNP) , cell-free DNA, cell-free non-coding RNA, and polymorphisms of genes (such as PNPLA3 and TM6SF2).

In a specific embodiment, such biomarkers are NAFLD markers, such as markers associated with liver fat index, markers associated with liver steatosis index, markers associated with NAFLD liver fat score, SteatoTest parameters, NAFLD score parameters, circulating triglycerides, body mass index (BMI); imaging biomarkers such as degree of beam scatter on tissue (USG), degree of ultrasound attenuation by liver fat (CAP), proportion of fat weighted by proton density (MRI-PDFF), content of triglycerides in the liver, proportion of fat estimated by signal (MRS) .

In a specific embodiment, such biomarkers are NASH blood biochemical markers, such as markers of apoptosis (CK18 fragment, total cytokeratin, serum level of apoptosis-mediated surface antigen FAS), markers of inflammation (C-reactive protein (CRP), TNF, IL-8 , chemokine ligand CXC 10 (CXCL10)), lipid oxidation products (11hydroxyeicosatetraenoic acid (HETE), 9-hydroxydecadienoic acid (HODE), 13-HODE, 13oxooctadecadienoic acid (ODE), LA-13-HODE (oxNASH score), 11, 12-dihydroxy-eicosatrienoic acid (diHETrE)), adipocytokines and hormones (adiponectin, leptin, resistin, visfatin, retinol binding protein (RBP) 4, fatty acid binding protein (FABP) 4, fibroblast growth factor (F21), lysosomal enzymes ( cathepsin D) and/or combination panels (NASH test, NASH diagnostic panel); imaging biomarkers such as Kupffer cell uptake function (MRI), enhancement of liver function with gadoxetic acid (MRI), hepatocyte membrane metabolism and intracellular ATP (MRS) , liver stiffness (MRE).

In a specific embodiment, such biomarkers are liver fibrosis markers: imaging biomarkers such as mechanically induced pulse, quantitative measurement of shear wave velocity (FibroScan-transient elastography, pSWE-ARFI, 2D-3DSWE), ultrasonic beam pulsed death imaging (pSWE -ARFI), the use of a modified phase-contrast method to visualize the propagation of a transverse wave in the liver parenchyma (MRE); blood biochemical markers such as AST:ALT ratio, AST:platelet ratio index (APRI), FIB4 index parameters, NAFLD fibrosis score parameters, BARD score parameters, specific fibrosis markers such as HA, PIIINP, Pro-C3, TIMP-1 , laminin, ELF-bonded panels, fiber test parameters, NAFLD fibrometer parameters.

In another additional embodiment, such markers are NAFLD risk and severity markers such as genetic and genomic markers such as SNPs (rs738409 in PNPLA3), cell free non-coding RNAs (miR-122, miR-1290, miR-192 and miR-7b) , a composite panel of serum derived omics data such as rs738409 and proteomic data including ACY1, SHBG, CTSZ, MET, GNS, LGALS3BP, CHL1 and SERPINC1, SNPs at multiple loci (PNPLA3, SOD2, KLF6 and LPIN1), miR- 122, composite panel including miR-122, miR-192, miR-21, ALT, CK18 Asp396, cell-free DNA such as circulating methylated PPARG.

According to a further embodiment, the other biomarkers are other circulating miRNAs in addition to miR-193. In particular, illustrative additional microRNAs that may be useful in the practice of the present invention include: miR-34a, miR-122, and miR-200.

According to these embodiments, the methods may include the steps of:

i) measuring the level of miR-193 and at least one other circulating marker of liver injury (such as a circulating marker of liver injury in blood, serum, or plasma), and ii) combining these measurements to generate mathematical models (algorithms) using bioinformatics approaches ( for example, linear logistic regression or random forest) to obtain a score of NAFLD, NASH, and/or liver fibrosis with high diagnostic/monitoring/prognostic/predictive scores for assessing NALFD, NASH, active NASH, or liver fibrosis in a subject.

In a particular embodiment, the method of the invention includes the steps of:

hsa-miR-193 level measurements, in particular hsa-miR-193b, more specifically hsa-miR-193b-3p or hsa-miR-193b-5p, or hsa-miR-193a, more specifically hsa-miR- 193a-5p or hsa-miR-193a-3p; and measuring the level of at least one other marker, preferably all, selected from the group consisting of:

tissue inhibitor of metalloproteinase 1 (TIMP-1);

YKL-40;

platelet count;

metabolic syndrome (ms).

In a particular embodiment, the method of the invention includes the steps of:

hsa-miR-193 level measurements, in particular hsa-miR-193b, more specifically hsa-miR-193b-3p or hsa-miR-193b-5p, or hsa-miR-193a, more specifically hsa-miR- 193a-5p or hsa-miR-193a-3p; and measuring the level of at least one other marker, preferably all selected from the group consisting of:

- 19 043299 tissue inhibitor of metalloproteinase 1 (TIMP-1);

YKL-40;

platelet count;

and determining whether the subject has metabolic syndrome.

The diagnosis of the metabolic syndrome can be made according to the criteria set out in Kotronen et al., Gastroenterology 2009, 137: 865-872.

In a specific embodiment, the method of the invention includes measuring the levels of the following markers:

miR-193b level (in particular, miR-193b-3p); and TIMP-1 level; and YKL-40 level; and platelet count and metabolic syndrome.

In a specific embodiment, the method of the invention can be used to calculate a score, or NASH score, from levels of biomarkers that have been measured.

In a particular embodiment, the S1 NASH score is defined as a logistic function:

Where

Y=k+a*A+b*B+c*C+d*D+f*F, while

S1 is the NASH score according to the present invention;

A is the level of hsa-miR-193b-3p in log10 copies.µl ^-1 ;

B is the level of TIMP-1 in ng/ml;

C is the level of YKL-40 in pg/ml;

D is the number of platelets: 10 ⁹ /l;

F is metabolic syndrome;

k is a logistic function constant;

a is the coefficient associated with the level of hsa-miR-193b-3p;

b is the coefficient associated with the level of TIMP-1;

c is the coefficient associated with the level of YKL-40;

d is a coefficient related to platelet count;

f is a coefficient associated with metabolic syndrome.

In a specific embodiment, the metabolic syndrome is defined as having a value of 1 if the subject has the metabolic syndrome, or 0 if the subject does not have the metabolic syndrome. In this particular embodiment, the factor f is applied to a value of 1 when the patient has a metabolic syndrome.

Thus, the NASH score represents the probability of having moderate to high NASH activity, or severe NASH.

If S1 is greater than or equal to the threshold, the subject is classified as having NASH, or as having or potentially having a steatosis score > 1, a hepatocyte ballooning score > 1, a lobular inflammation score > 1, a NAS > 4, and a fibrosis stage > 2, and/or classified as being treated for NASH or potentially being treated for NASH, or being classified as being treated for NASH and/or receiving dietary and/or lifestyle advice. In a specific embodiment, if S1 is below a threshold value, the subject may be classified as treatable or not treatable, in particular not treatable, and/or the subject is classified as a recipient or potential recipient of dietary and/or lifestyle advice for control his/her NASH with low activity or moderate NASH.

In another specific embodiment, derived from the bootstrap model as described in the experimental part of the present invention:

k is a number from -8.39 to -2.67, a is a number from 0.58 to 2.50 b is a number from 2.29E-03 to 1.87E-02, c is a number in the range 2.14E-06 to 1.65E-05, d is a number in the range of -1.56E-02 to -1.05E-03, f is a number in the range of 0.03 to 1.63, and wherein the threshold value is from 0.3050 to 0.6518, and more specifically, it is 0.3993±10%, in particular, it is 0.3993.

In accordance with a particular embodiment, the subject is classified as having NASH or as having, or potentially having, a steatosis score >1, a hepatocyte ballooning score >1, a lobular inflammation score >1, a NAS >4, and a fibrosis stage >2, and/ or classified as a recipient or potential recipient of treatment if the S1 score for NASH is greater than or equal to a threshold value between 0.3050 and 0.6518, and in particular equal to 0.3993±10%, in particular, equal to 0.3993.

In a specific embodiment, also derived from the bootstrapping model:

k is -5.53;

a is 1.54;

b is equal to 0.0105;

c is 0.00000934;

d is -0.00832;

f is 0.83; and wherein the threshold value is from 0.3050 to 0.6518, and more specifically, is 0.3993±10%, in particular, is 0.3993.

In accordance with a specific embodiment, the subject is classified as having NASH or having, or potentially having, a steatosis score > 1, a hepatocyte ballooning score > 1, a lobular inflammation score > 1, a NAS > 4, and a fibrosis stage >2, and/or be classified as a recipient or potential recipient of treatment if the S1 NASH score is greater than or equal to a threshold value between 0.3050 and 0.6518, and in particular equal to 0.3993±10%, in particular equal to 0.3993.

According to this particular embodiment, the AUC is at least 0.80.

In a particular embodiment, the method of the invention includes the steps of:

hsa-miR-193 level measurements, in particular hsa-miR-193b, more specifically hsa-miR-193b-3p or hsa-miR-193b-5p, or hsa-miR-193a, more specifically hsa-miR- 193a-5p or hsa-miR-193a-3p; and measuring the level of at least one other marker, preferably all, selected from the group consisting of:

YKL-40;

tissue inhibitor of metalloproteinase 1 (TIMP-1);

hyaluronic acid (HYUA2);

HbA1c; and platelet count.

In a specific embodiment, the method of the invention includes measuring the levels of the following markers:

miR-193b level (in particular, miR-193b-3p); and YKL-40 level; and TIMP-1 level; and hyaluronic acid (HYUA2);

HbA1c; and platelet count.

In a specific embodiment, the S2 score on the NASH scale is defined as a logistic function:

Where

Y2=l+a2*A+c2*C+b2*B+e*E+g*G+d2*D, while

S2 is the NASH score according to the present invention;

A is the level of hsa-miR-193b-3p in log10 copies.µl ^-1 ;

C is the level of YKL-40 in pg/ml;

B is the level of TIMP-1 in ng/ml;

E is the HbA1c level in percent;

G is the level of hyaluronic acid in ng/ml;

D is the number of platelets: 10 ⁹ /l;

l is a constant of the logistic function;

a2 is the coefficient associated with the level of hsa-miR-193b-3p;

c2 is the coefficient associated with the level of YKL-40;

b2 is the coefficient associated with the level of TIMP-1;

e is the coefficient associated with the level of HbA1c;

g is a coefficient related to the level of hyaluronic acid;

d2 is a coefficient related to platelet count.

Thus, the S2 NASH score represents the probability of having moderate to high NASH activity, or severe NASH.

If S2 is greater than or equal to the threshold, the subject is classified as having NASH,

- 21 043299 or having or potentially having steatosis score > 1, hepatocyte ballooning score > 1, lobular inflammation score > 1, NAS > 4, and fibrosis stage > 2, and/or classified as treatable NASH, or potentially treatable NASH or is classified as being treated for NASH and/or receiving dietary and/or lifestyle advice. In a specific embodiment, if S2 is below a threshold value, the subject may be classified as treatable or not treatable, in particular not treatable, and/or the subject is classified as a recipient or potential recipient of dietary and/or lifestyle advice for monitoring. his/her NASH with low activity or moderate NASH.

In another specific embodiment, derived from the bootstrap model as described in the experimental part of the present invention:

l is a number in the range of -10.92 to -3.89, a2 is a number in the range of 0.44 to 2.17, c2 is a number in the range of 0.0035 to 0.02, b2 is a number in the range of 0.0016 to 0.018, e is a number in the range of -0.0053 to 0.0057, g is a number in the range of 0.13 to 1.08, d2 is a number in the range of -0.017 to -0.0027, wherein the threshold value is from 0.2461 to 0.6252, and in particular is 0.4216±10%, in particular is 0.4216.

In accordance with a specific embodiment, the subject is classified as having NASH, or having or potentially having a steatosis score >1, a hepatocyte ballooning score >1, a lobular inflammation score >1, a NAS >4, and a fibrosis stage >2, and/or is classified as a recipient or potential recipient of treatment if the S2 NASH score is greater than or equal to the cut-off value between 0.2461 and 0.6252, and in particular equal to 0.4216±10%, in particular equal to 0.4216.

In a specific embodiment, also derived from the bootstrapping model:

l is -7.52;

a2 is 1.29;

c2 is 0.01;

b2 is 0.0092;

e is -0.0024;

g is 0.59;

d2 is -0.009; and while the threshold value is from 0.2461 to 0.6252 and, in particular, is equal to 0.4216±10%, in particular, is equal to 0.4216.

In accordance with a specific embodiment, the subject is classified as having NASH, or having or potentially having a steatosis score >1, hepatocyte ballooning score >1, lobular inflammation score >1, NAS >4, and fibrosis stage >2, and/or classified as a recipient or potential recipient of treatment if the NASH S2 score is greater than or equal to the cut-off value between 0.2461 and 0.6252, and in particular 0.4216±10%, in particular 0.4216.

According to this particular embodiment, the AUC is at least 0.80.

In a particular embodiment, the S3 NASH score is defined as a logistic function:

S3 - ——rm l + e ^V3 where

Y3=m+a3*A+c3*C+b3*B+e2*E+g2*G+d3*D, while

S3 is the NASH score according to the present invention;

A' represents the level of hsa-miR-193b-3p in Cq;

C is the level of YKL-40 in pg/ml;

B is the level of TIMP-1 in ng/ml;

E is the HbA1c level in percent;

G is the level of hyaluronic acid in ng/ml;

D is the number of platelets: 10 ⁹ /l;

m is a constant of the logistic function;

a3 is the coefficient associated with the level of hsa-miR-193b-3p;

c3 is the coefficient associated with the level of YKL-40;

b3 is the coefficient associated with the level of TIMP-1;

e2 is the coefficient associated with the level of HbA1c;

g2 is the coefficient associated with the level of hyaluronic acid;

- 22 043299 d3 is the coefficient associated with the number of platelets.

Thus, the S3 NASH score represents the probability of having moderate or high NASH activity, or severe NASH.

If S3 is greater than or equal to the threshold, the subject is classified as having NASH, or having or potentially having a steatosis score >1, hepatocyte ballooning score >1, lobular inflammation score >1, NAS >4, and fibrosis stage >2, and/ or classified as being treated for NASH, or potentially being treated for NASH, or being classified as being treated for NASH and/or receiving dietary and/or lifestyle advice. In a specific embodiment, if S3 is below a threshold value, the subject may be classified as treatable or not treatable, in particular not treatable, and/or the subject is classified as a recipient or potential recipient of dietary and/or lifestyle advice for monitoring. his/her NASH with low activity or moderate NASH.

In another specific embodiment, derived from the bootstrapping model as described in the experimental part of the present invention:

m is a number in the range of -1.27 to 17.54, a3 is a number in the range of -0.64 to -0.09, c3 is a number in the range of 0.005 to 0.019, b3 is a number in the range 0.001 to 0.016, e2 is a number in the range -0.0054 to 0.0045, g2 is a number in the range 0.12 to 1.08, d3 is a number in the range -0.0164 to -0 .0016, wherein the threshold value is between 0.2270 and 0.6364, and in particular is 0.3741±10%, in particular is 0.3741.

In accordance with a specific embodiment, the subject is classified as having NASH, or having or potentially having a steatosis score >1, hepatocyte ballooning score >1, lobular inflammation score >1, NAS >4, and fibrosis stage >2, and/or classified as a recipient or potential recipient of treatment if the S3 NASH score is greater than or equal to the cut-off value between 0.2270 and 0.6364, and in particular equal to 0.3741±10%, in particular equal to 0.3741.

In a specific embodiment, also derived from the bootstrapping model:

m is 8.08;

a3 is -0.38;

c3 is 0.01;

b3 is 0.01;

e2 is -0.0024;

g2 is 0.57;

d3 is -0.0090; and while the threshold value is from 0.2270 to 0.6364 and, in particular, is equal to 0.3741±10%, in particular, is equal to 0.3741.

In accordance with a specific embodiment, the subject is classified as having NASH or having, or potentially having, a steatosis score >1, a hepatocyte ballooning score >1, a lobular inflammation score >1, a NAS >4, and a fibrosis stage >2, and/or classify as a recipient or potential recipient of treatment if the S3 NASH score is greater than or equal to a threshold value of 0.2270 to 0.6364, and in particular equal to 0.3741±10%, in particular equal to 0.3741.

According to this particular embodiment, the AUC is at least 0.80.

In a further specific embodiment, the above methods described for calculating a NASH score are implemented on a blood, serum or plasma sample, in particular a plasma sample.

In another embodiment, diagnosing, detecting, monitoring, risk assessing, or evaluating the efficacy of treating NAFLD, NASH, or liver fibrosis is performed by determining the level of miR193 in a subject's body fluid sample and referring the subject for diagnosis through non-invasive physical techniques such as ultrasound, elastography, or imaging techniques. such as MRI.

In other embodiments, the implementation of the methods of the present invention can be combined with the method disclosed in WO 2017046181, belonging to the same applicant.

In some embodiments, through the methods of the invention, a decision may be made to provide lifestyle advice to the patient (e.g., dietary or physical activity advice), to provide medical care to the subject (e.g., by scheduling regular doctor visits or regular check-ups, e.g., for routine monitoring of markers of liver damage) or to administer to the subject at least one NAFLD therapy,

- 23 043299

NASH or liver fibrosis. This classification of a subject as a recipient, or TBT, is based on elevated levels of miR-193 compared to control levels of miR-193 measured in non-recipients (NTBTs) as described above.

Thus, the invention further provides an anti-NAFLD, anti-NASH, or anti-fibrosis compound for use in a method for treating NAFLD, NASH, or liver fibrosis in a subject in need thereof, the subject having been identified by the method of the invention.

In particular, the invention relates to an anti-NAFLD compound for use in a method of treating NAFLD in a subject in need thereof, the subject having been classified as a recipient of said treatment by means of the method of the invention.

In particular, the invention relates to an anti-NASH compound for use in a method of treating NASH in a subject in need thereof, the subject having been classified as a recipient of said treatment by the method of the invention.

In particular, the invention relates to an anti-fibrosis compound for use in a method for treating liver fibrosis in a subject in need thereof, the subject having been classified as a recipient of said treatment by means of the method of the invention.

Exemplary anti-NAFLD, anti-NASH, and anti-fibrosis compounds are listed below. Compound of formula (I):

Rs in which

X1 is halo, R1 or G1-R1;

A represents CH=CH or a CH2-CH2 group;

X2 represents the G2-R2 group;

G1 and G2, identical or different, represent an oxygen or sulfur atom;

R1 represents a hydrogen atom, an unsubstituted alkyl group, an aryl group, or an alkyl group which is substituted by one or more halogen atoms, an alkoxy or alkylthio group, cycloalkyl groups, cycloalkylthio groups, or heterocyclic groups;

R2 is an alkyl group substituted with at least a -COOR3 group, where R3 is a hydrogen atom or an alkyl group which is substituted or unsubstituted by one or more halogen atoms, cycloalkyl groups or heterocyclic groups.

R4 and R5, the same or different, represent an alkyl group which is substituted or unsubstituted by one or more halogen atoms, cycloalkyl groups, heterocyclic groups;

or a pharmaceutically acceptable salt thereof;

acetyl-CoA carboxylase inhibitors such as GS-0976, ND-654, AC-8632, PF05175157, CP640186, Gemcabene, MK-4074 and PF05175157;

adenosine A3 receptor agonists such as 2-(1-hexynyl)-N-methyladenosine, piclidenosone CF101 (IB-MECA), namodenosone CF-102, 2-Cl-IB-MECA, CP-532,903, inosine, LUF-6000 and MRS-3558;

aldosterone antagonists and mineralocorticoid receptor antagonists such as apararenone (MT 3995), amiloride, spironolactone, eplerenone, canrenone and potassium canrenoate, progesterone, drospirenone, gestodene and benidipine;

AMP-activated protein kinase stimulants such as PXL-770, MB-11055 Debio-0930B metformin, CNX-012, O-304, mangiferin calcium, eltrombopag, carotuximab, and imeglimine;

amylin receptor agonists and calcitonin receptor agonists include, but are not limited to, KBP-042 and KBP-089;

angiopoietin-related protein-3 inhibitors such as ARO-ANG3, IONIS-ANGGPTL3-LRx or AKCEA-ANGPTL3LRx, evinacumab and ALN-ANG;

anti-LPS antibodies such as IMM-124-E;

an antisense oligonucleotide targeting transforming growth factor beta 2 includes, but is not limited to, ASPH-0047, IMC-TR1, and ISTH-0047;

apical sodium codependent bile acid transporter inhibitors such as A-4250, volixibate, maralixibate formerly SHP-625, GSK-2330672, elobixibate and CJ-14199;

betaine anhydrous or PM-003.

Bile acids include obeticholic acid (OCA) and UDCA, norursodeoxycholic acid, and ursodiol.

Bioactive lipids such as 5-hydroxyeicosapentaenoic acid (15-HEPE, DS-102), unsaturated fatty acids such as 25-arachidonic acid, icosapentetyl ester, eicosapentanoic acid and docosahexaenoic acid.

- 24 043299

Cannabinoid CB1 receptor antagonists such as GRC-10801, MRI-1569, MRI-1867, DBPR211, AM-6527, AM-6545, NESS-11-SM, CXB-029, GCC-2680, TM-38837, Org-50189 , PF-514273, BMS812204, ZYO-1, AZD-2207, AZD-1175, otenabant, ibipinabant, surinabant; rimonabant, drinabant,

SLV-326, V-24343 and O-2093.

Cannabinoid CB2 receptor mimetics such as anabasum (Resunab, JKT-101).

Dual cannabinoid CB1 receptor/iNOS inhibitor.

Caspase inhibitors such as emricasan, belnakasan, nivokasan, IDN-7314, F-573, VX-166, YJP60107, MX-1122, IDN-6734, TLC-144, SB-234470, IDN-1965, VX-799, SDZ -220-976 and L-709049.

Cathepsin inhibitors such as VBY-376, VBY-825, VBY-036, VBY-129, VBY-285, Org-219517, LY3000328, RG-7236 and BF/PC-18.

CCR antagonists such as cenicriviroc (CCR2/5 antagonist), PG-092, RAP-310, INCB-10820, RAP-103, PF-04634817 and CCX-872.

CCR3 chemokine modulators and eotaxin 2 ligand inhibitors

Diαcylglycerol-O-αcyltransferase (DGAT) inhibitors such as IONIS-DGAT2Rx formerly ISIS-DGAT2Rx, ISIS 703802, LY-3202328, BH-03004, KR-69530, OT-13540, AZD-7687, PF039064646 and A BT-046.

Dipeptidyl peptidase IV (DPP4) inhibitors, evogliptin, vildagliptin, fotagliptin, alogliptin, sahagliptin, tylogliptin, anagliptin, sitagliptin, retagliptin, melogliptin, gosogliptin, trelagliptin, teneligliptin, utogliptin, linagliptin, gemigliptin, yogliptin, betagliptin , imigliptin, omarigliptin, vildagliptin and denagliptin .

Insulin ligand and insulin receptor agonists.

Insulin mensibilizer and MCH-1 receptor antagonist.

NOX (NADPH oxidase) inhibitors such as Dual NOX (NADPH oxidase) inhibitors 1 and 4; GKT-831 (2-(2-chlorophenyl)-4-[3-(dimethylamino)phenyl]-5-methyl-1H-pyrαzolo[4,3-c]pyridine-3,6(2H,5H)dione), formerly called GKT137831 and GKT-901.

Extracellular matrix protein modulators such as CNX-024, CNX-025 and SB-030.

Fatty acid synthesis inhibitors (FAS) such as TVB-2640; TVB-3664; TVB-3166, TVB-3150, TVB-3199, TVB-3693BZL-101, 2-octadecic acid, MDX-2, Fasnall, MT-061, G28UCM, MG-28, HS160, GSK-2194069, KD-023 and Cilostazol .

In a specific embodiment, the FAS inhibitor is a compound selected from the following list of compounds:

- 25 043299

- 26 043299

and TVB-2640. In another specific embodiment, the FAS inhibitor is selected from:

In a specific embodiment, the FAS inhibitor is TVB-2640.

fatty acids such as omega-3 fatty acids, omacor or MF4637, fish oil, polyunsaturated fatty acids (efamax, optiEPA);

stearoyl-CoA desaturase-1/fatty acid bile acid conjugates (FABAC);

farnesoid X receptor (FXR) agonists; obeticholic acid, (OCA), GS-9674, LJN-452, EDP-305; AKN-083, INT-767, GNF-5120, LY2562175, INV-33, NTX-023-1, EP-024297, Px-103, SR-45023;

fibroblast growth factor 19 receptor ligand (FGF-19) or an operably engineered variant of FGF-19;

recombinant variants of fibroblast growth factor 19 (FGF-19) such as NGM-282;

Fibroblast growth factor 21 (FGF-21) agonists such as PEG-FGF21, formerly

- 27 043299

BMS-986036, YH-25348, BMS-986171, YH-25723, LY-3025876 and NNC-0194-0499;

galectin 3 inhibitors such as GR-MD-02, TD-139, ANG-4021, galectin-3C, LJPC-201, TFD100, GR-MD-03, GR-MD-04, GM-MD-01, GM- CT-01, GM-CT-02, Gal-100 and Gal-200;

glucagon-like peptide-1 (GLP-1) analogs such as semaglutide, liraglutide, exenatide, albiglutide, dulaglutide, lixisenatide, loxenatide, efpeglenatide, taspoglutide, MKC-253, DLP-205 and 0RM;

glucagon-like peptide-1 (GLP-1) receptor agonists such as LY-3305677 and long acting oxyntomodulin;

G protein-coupled receptor (GPCR) modulators such as CNX-023;

a G protein-coupled receptor 84 antagonist (GPR84 antagonist), a connective tissue growth factor ligand inhibitor, and a free fatty acid receptor 1 agonist (FFAR1 agonist) such as PBI-4050, PBI-4265, PBI-4283 and PBI-4299;

a growth hormone;

Hedgehog cell signaling inhibitors such as vismodegib, TAK-441, IPI-926, saridegib, sonidegib/erismodegib, BMS-833923/XL139, PF-04449913, taladegib/LY2940680, ETS-2400, sHr1514 and CUR-1514, CUR- 1514, CUR-1514, CUR-1514, and CUR-1514, CUR-1514 inhibitors of the sodium dependent ileal bile acid cotransporter such as A-4250, GSK-2330672, volixibat, CJ-14199 and elobixibate;

immunomodulators such as PBI-4050, PBI-4265, PBI-4283, PBI-4299 and AIC-649;

an insulin sensitizer and an MCH receptor antagonist such as MSDC-0602k, MSDC-0602, CSTI100 and AMRI;

integrin inhibitors; Pliant Therapeutics Integrin Inhibitors, Indalo Therapeutics Integrin Inhibitors, Saint Louis University Integrin Inhibitors, ProAgio and GSK-3008348;

ketohexokinase inhibitors such as JNJ-28165722; JNJ-42065426; JNJ-42152981; JNJ-42740815; JNJ-42740828 and PF-06835919;

leukotriene (LT)/phosphodiesterase (PDE)/lipoxygenase (LO) inhibitors such as tipelukast (formerly called MN-001), tomelukast, sulukast, masilukast, zafirlukast, pranlukast, montelukast, hemilukast, verlukast, aclukast, pobilikast, cinalukast, and iralukast ;

lysyl oxidase homologue 2 inhibitors such as Rappaport, InterMune, Pharmaxis, AB-0023, simtuzumab, PXS-5382A and PXS-5338;

macrolides like lysolithromycin, azithromycin and erythromycin;

macrophage mannose receptor modulators such as AB-0023, MT-1001, [18F]FB18mHSA, Xemys, technetium Tc 99m tilmanocept and CDX-1307;

methyl CpG binding protein 2 modulator and transglutaminase inhibitors include, but are not limited to, cysteamine, EC cysteamine, enteric cysteamine bitartrate, cysteamine bitartrate (enteric coated), Bennu, cysteamine bitartrate (enteric coated), Raptor, cysteamine bitartrate, DR cysteamine, sustained-release enteric-coated cysteamine bitartrate, mercaptamine, mercaptamine (enteric-coated), Bennu, mercaptamine (enteric-coated), Raptor, RP-103, RP-104, PROCYSBI, and mercaptamine (enteric-coated);

miRNA antagonists such as RG-125 formerly AZD4076, RGLS-5040, RG-101, MGN-5804 and MRG-201;

a metalloproteinase-9 (MMP9) stimulator such as the MMP9 stimulator Elastomic Ab;

a mitochondrial carrier family inhibitor and a mitochondrial phosphate carrier protein inhibitor include, but are not limited to, TRO-19622, Trophos, olesoxime, RG-6083, or RO-7090919;

myeloperoxidase inhibitors include, but are not limited to, PF-06667272;

monoclonal antibodies such as bertilimumam, NGM-313, IL-20 targeting monocolonal antibodies, frezolimumab (anti-TGFe), formerly GC1008, thymolumab, formerly BTT-1023, namacizumab, omalizumab, ranibizumab, bevacizumab, lebrikizumab, epratuzumab, felvizumab, matuzumab, monalizumab, reslizumab, foralumab (NI-0401, anti-CD3), simbezumab (GS6624), anti-LOXL2 monoclonal antibody, ustekinumab, anti-TNF antibody, and inebilizumab;

monoclonal antibodies such as anti-IL20 monoclonal antibodies, anti-TGFe antibodies, antu-CD3 antibodies, anti-LOXL2 antibodies and anti-TNF antibodies;

NAD-dependent deacetylase sirtuin stimulator; a PDE 5 inhibitor such as NS-0200;

NF-kappa B inhibitors such as LC-280126;

nicotinic acid such as niacin or vitamin B3;

nicotinic acid agonists (GPR109) such as ARI-3037MO, MMF, LUF 6283, acifran, IBC 293, MK-1903, GSK256073, MK-6892, MK-0354, SLx-4090, lomitapide, lexibulin, apabetalone, acifran, laropiprant , daporinad, anacetrapib, INCB-19602, ST-07-02, lomefloxacin, niacin and controlled release laropiprant;

- 28 043299 non-steroidal anti-inflammatory drugs (NSAIDs) include, but are not limited to, F-351, salicylates (aspirin), acetaminophen, propionic acid derivatives (ibuprofen, naproxen), acetic acid derivatives (indomethacin, diclofenac), enolic acid derivatives (piroxicam , phenylbutazone), anthranilic acid derivatives (meclofenalmic acid, flufenamic acid), selective COX-2 inhibitors (celecoxib, parecoxib) and sulfonanilides (nimesulide);

mTOR modulators such as MSDC-0602 and AAV gene therapy co-administered with SVPsirolimus;

nuclear receptor ligands such as DUR-928, formerly DV 928;

P2Y13 protein agonists such as CER-209;

PDGFR modulators such as BOT-501 and BOT-191;

phenylalanine hydroxylase stimulants such as pegvalase, sapropterin, AAV-PAH, CDX6114, sepiapterin, RMN-168, ALTU-236, ETX-101, HepaStem, rolipram, and alprostadil;

protease-activated receptor (PAR)-2 antagonists such as PZ-235 and NP-003;

protein kinase modulators such as CNX-014, MB-11055, ALF-1, mangiferin, amlexanox, GS444217, REG-101 and valine;

PPAR-alpha agonists such as fenofibrate, ciprofibrate, pemafibrate, gemfibrozil, clofibrate, binifibrate, clinofibrate, clofibric acid, nicofibrate, pyrifibrate, plafibride, ronifibrate, theofibrate, tocofibrate and SR10171;

PPAR-gamma agonists such as pioglitazone, deuterated pioglitazone, rosiglitazone, efatutazone, ATx08-001, OMS-405, CHS-131, THR-0921, SER-150-DN, KDT-501, GED-0507-34-Levo, CLC-3001 and ALL-4;

PPAR delta agonists such as GW501516 (endurabol or ({4-[({4-methyl-2-[4(trifluoromethyl)phenyl]-1,3-thiazol-5-yl}methyl)sulfanyl]-2-methylphenoxy }acetic acid)),

MBX8025 (celadelpar or {2-methyl-4-[5-methyl-2-(4-trifluoromethylphenyl)-2H-[1,2,3]triazol-4ylmethylsilfanyl]phenoxy}-acetic acid), GW0742 ([4-[ [[2-[3-fluoro-4-(trifluoromethyl)phenyl]-4methyl-5-thiazolyl]methyl]thio]-2-methylphenoxy]acetic acid), L165041, HPP-593 and NCP-1046;

PPAR alpha/gamma agonists (also called glitazars) such as saroglitazar, aleglitazar, muraglitazar, tesaglitazar, DSP-8658;

PPAR alpha/delta agonists such as elafibranor and T913659;

PPAR gamma/delta-like conjugated linoleic acid (CLA), T3D-959;

PPAR alpha/gamma/delta agonists or PPAR panagonists such as IVA337 (lanifibranor), TTA (tetradecylthioacetic acid), bavaquinine, GW4148, GW9135, bezafibrate, lobeglitazone and CS038;

prebiotic fibers, probiotics;

pregnane X receptors such as rifampicin;

Rho-associated protein kinase 2 (ROCK2) inhibitors such as KD-025, TRX-101, BA1049, LYC-53976, INS-117548 and RKI-1447;

signal regulating kinase 1 (ASK1) inhibitors such as GS-4997;

sodium glucose transport inhibitors (SGLT) 1 such as LX-4212/LX-4211/sotagliflozin, SAR-439954, LIK-066 (lycoglyfosin), LX-2761, GSK-161235, LP-925219, KGA-2727, SAR - 7226, SAR474832, SY-008 and AVX-3030;

sodium glucose transport (SGLT) 2 inhibitors such as remogliflozin, dapagliflozin, empagliflozin, ertugliflozin, sotagliflozin, ipragliflozin, tianagliflozin, canagliflozin, tofogliflozin, janagliflozin, bexagliflozliflozin, bexagliflozliflozin, HEC-44616, AST-1935 and PLD -101;

statins such as atorvastatin or simvastatin;

stearoyl-CoA desaturase-1/fatty acid conjugates such as aramchol, GRC-9332, steamchol, TSN-2998, GSK-1940029 and XEN-801;

thyroid receptor β (THR β) agonists such as VK-2809, MGL-3196, MGL-3745, SKL-14763, sobetirome, BCT-304, ZYT-1, MB-07811 and eprotirom;

Toll-like receptor 2 and 4 (TLR-2) antagonists such as CI-201, also known as VB201;

Toll-like receptor 4 (TLR-4) antagonists such as naltrexone, JKB-121, M-62812, rezatorvid, dendrofilin, CS-4771, AyuV-1, AyuV-25, NI-0101, EDA-HPVE7, and eritoran;

type I natural killer cell inhibitors such as GRI-0621;

tyrosine kinase receptor (RTK) modulators such as CNX-025, KBP-7018, nintedanib and sorafenib;

urate anion exchanger 1 inhibitors and xanthine oxidase inhibitors such as lesinurad, RLBN-1001, verinurad, KUX-1151 and lesinurad + allopurinol;

vascular adhesion protein-1 (VAP-1) inhibitors, also called containing copper amine oxidase 2 (AOC3), such as BI-1467335, formerly PXS-4728A, CP-664511, PRX-167700, ASP8232, RTU-1096, RTU- 007 and BTT-1023;

- 29 043299 Vitamin D receptor (VDR) agonists such as calciferol, alfacalcidol, 1,25 dihydroxy vitamin D3, vitamin D2, vitamin D3, calcitriol, vitamin D4, vitamin D5, dihydrotachysterol, calcipotriol, tacalcitol, 1,24 dihydroxy vitamin D3 and paricalcitol ;

vitamin E and isoforms, vitamin E in combination with vitamin C and atorvastatin.

Other anti-NASH agents include KB-GE-001 and NGM-386 and NGM-395 and NC-10 and TCM-606F. Other anti-NASH agents include icosabutate, NC-101, NAIA-101, colesevelam, and PRC-4016. Other antifibrotic agents include HEC-585, INV-240, therapeutic RNAi (Silence Therapeutics) and the SAMiRNA program (Bioneer Corp).

Other exemplary antifibrotic agents include pirfenidone or receptor tyrosine kinase (RTKI) inhibitors such as nintedanib, sorafenib, and other RTKIs, or angiotensin II receptor blockers (ATIs), or a CTGF inhibitor, or any antifibrotic compound susceptible to interference with TGFe- and BMP- activated pathways including TGFe latent complex activators such as MMP2, MMP9, THBS1 or cell surface integrins, type I (TGFBRI) or type II (TGFBRII) TGFe receptors and their ligands such as TGFe, activin, inhibin, Nodal, anti- Mueller hormone, GDF or BMP, accessory co-receptors (also known as type III receptors) or components of an SMAD-dependent canonical pathway, including regulatory or inhibitory SMAD proteins, or members of SMAD-1-independent or non-canonical pathways, including various branches of MAPK signaling, TAK1, Rho-like GTPase signaling pathways, phosphatidylinositol-3 kinase/AKT pathways, TGFe-induced EMT, or canonical and non-canonical Hedgehog signaling pathways, including Hh ligands or target genes, or any members of WNT, or Notch pathways, which are sensitive to the influence of TGFe.

In a specific embodiment, the treatment of NASH or liver fibrosis comprises administering a compound of formula (I) selected from the group consisting of the following: 1-[4-methylthiophenyl]-3-[3,5dimethyl-4-carboxydimethylmethyloxyphenyl]prop-2- en-1-one, 1-[4-methylthiophenyl]-3-[3,5-dimethyl-4isopropyloxycarbonyldimethylmethyloxyphenyl]prop-2-en-1-one, 1-[4-methylthiophenyl]-3-[3,5- dimethyl-4tert-butyloxycarbonyldimethylmethyloxyphenyl]prop-2-en-1-one, 1-[4-trifluoromethylphenyl]-3-[3,5dimethyl-4-tert-butyloxycarbonyl dimethylmethyloxyphenyl]prop-2-en-1-one, 1 - [4-trifluoromethylphenyl]-3[3,5-dimethyl-4-carboxydimethylmethyloxyphenyl]prop-2-en-1-one, 1-[4-trifluoromethyloxyphenyl]-3-[3,5dimethyl-4-tert-butyloxycarbonyldimethylmethyloxyphenyl]prop -2-en-1-one, 1-[4-trifluoromethyloxyphenyl]3-[3,5-dimethyl-4-carboxydimethylmethyloxyphenyl]prop-2-en-1-one 2-[2,6-dimethyl-4-[ 3-[4(methylthio)phenyl]-3-oxopropyl]phenoxy]-2-methylpropanoic acid and 2-[2,6-dimethyl-4-[3-[4(methylthio)phenyl]-3-oxopropyl]phenoxy] -2-methylpropanoic acid isopropyl ether; or a pharmaceutically acceptable salt thereof. In a further specific embodiment, the compound of formula (I) is 1-[4-methylthiophenyl]-3-[3,5-dimethyl-4carboxydimethylmethyloxyphenyl]prop-2-en-1-one, or a pharmaceutically acceptable salt thereof.

In particular, the invention relates to a combination product containing at least an anti-NAFLD and/or anti-NASH and/or an anti-fibrotic agent for use in a method of treating NAFLD, NASH, active NASH and/or liver fibrosis in a subject in need thereof, wherein the subject has been classified as a recipient of said treatment by means of the method of the invention.

In a more specific embodiment, the invention relates to the treatment of NAFLD, NASH, active NASH and/or liver fibrosis with a combined product comprising at least one agent selected from the group of anti-NAFLD, anti-NASH and/or anti-fibrosis compounds, or pharmaceutically acceptable salts thereof. .

In a more specific embodiment, the invention relates to the treatment of NAFLD, NASH, active NASH and/or liver fibrosis with elafibranor.

In a further embodiment, treatment for NASH or liver fibrosis comprises administering vitamin E or pioglitazone, obeticholic acid, elafibranor, seloncertib, saroglitazar and/or cenicrivoc.

Considering the role of miRNAs in modulating gene expression, the results obtained by the inventors also confirm the pathophysiological role of miR-193 in the development and evolution of NAFLD, NASH and/or liver fibrosis.

Thus, the methods of the invention can be used to identify specific subsets of subjects with NAFLD, NASH, and/or liver fibrosis based on circulating miR-193 levels. These subpopulations may have miR-193 dependent disease that causes these patients to respond to specific drugs acting directly (miR-193 or anti-miR-193 mimetics) or indirectly on miR-193 dependent pathways.

Furthermore, based on this observation, in a further aspect, the invention provides a miR-193 inhibitory compound for use in the treatment of NAFLD, NASH, or liver fibrosis in a subject in need thereof.

As used herein, the term miR-193 inhibitor compound and its declensions refer to any compound, such as a nucleic acid compound, capable of preventing the action of miR-193 and in particular hsa-miR-193a-5p, hsa- miR-193b-3p or hsa-miR-193b-5p. In a specific embodiment, the miR-193 inhibitory compound of the present invention is a compound that inhibits or reduces the activity of miR-193, for example, by binding to miR-193, or that inhibits the expression of miR-193. The term inhibition of miR-193 expression means that miR-193 production in the liver or hepatocytes after treatment with said inhibitory compound is less than the amount produced before treatment. One of skill in the art can readily determine whether miR-193 expression has been inhibited in the liver or hepatocytes using, for example, microRNA transcript level techniques.

Suitable miR-193 inhibitory compounds include double-stranded RNA (such as short or small interfering RNA or siRNA), antagonists, antisense nucleic acids, and RNA enzymatic molecules such as ribozymes. Each of these compounds can be targeted to a given microRNA and can destroy or induce destruction of the target microRNA. For example, expression of a given microRNA can be inhibited by inducing RNA interference of the microRNA with an isolated double-stranded RNA (dsRNA) molecule that has at least 90%, e.g., 95%, 98%, 99%, or 100% sequence homology of at least at least with a part or, preferably, with all miRNA. In a preferred embodiment, the dsRNA molecule is an siRNA. siRNAs suitable for the present methods include a short double-stranded RNA of about 17 nucleotides to about 29 nucleotides in length, preferably about 19 to about 25 nucleotides. The siRNA contains a strand of sense RNA and a strand of complementary antisense RNA annealed together using standard Watson-Crick base-pairing interactions (hereinafter base-paired). The sense strand contains a nucleic acid sequence that is substantially identical to the nucleic acid sequence contained in the target siRNA.

Sets

According to a further aspect, the present invention relates to a kit containing a means for determining the level:

(i) miR-193 in the body fluid sample, and optionally (ii) at least one other circulating marker of liver injury.

According to another aspect, the present invention also relates to a kit containing a means for determining the level:

(i) miR-193 in the body fluid sample, and optionally (ii) at least one other marker for NAFLD, NASH, or liver fibrosis.

The kit of the invention is useful for implementing the methods described above. In addition, it may further contain instructions for implementing these methods. The kit may contain reagents and buffers suitable for measuring levels of miR-193 and any other circulating marker of liver injury as described above. In particular, the kit may contain antibodies specific for the protein to be quantified and/or the necessary primers. In a more specific embodiment, the kit may contain primers and/or probes for quantifying microRNA levels, as is well known in the art.

The kit may contain reagents and buffers suitable for measuring levels of miR193 and any other NAFLD and/or NASH marker.

The present invention also relates to a kit containing means for determining the level:

at least one marker selected from the group consisting of hsa-miR-193 (particularly hsa-miR-193b, more specifically miR-193b-3p); and at least one other, in particular all, markers selected from a group selected from:

TIMP-1;

YKL-40;

platelet count; and metabolic syndrome score.

The present invention also relates to a kit containing means for determining the level:

at least one marker selected from the group consisting of hsa-miR-193 (particularly hsa-miR-193b, more specifically miR-193b-3p); and at least one other, in particular all, markers selected from a group selected from:

YKL-40;

TIMP-1;

HbA1c;

hyaluronic acid and platelet count.

The present invention also relates to a kit containing means for determining the level:

at least one marker selected from the group consisting of hsa-miR-193 (particularly hsa-miR-193b, more specifically miR-193b-3p); and at least one other, in particular all,

- 31 043299 markers selected from a group selected from:

YKL-40;

TIMP-1;

HbA1c;

hyaluronic acid and platelet count.

In a preferred embodiment, the kit contains means for determining the level of miR-193b-3p.

The kit according to the invention is useful for implementing the methods described above, and may additionally contain instructions for implementing these methods. The kit may contain reagents and buffers suitable for measuring the levels of the markers mentioned above. In particular, the kit may contain antibodies specific for the protein to be quantified and/or primers useful for quantifying miRNA levels, as is well known in the art.

It should be understood that the above description, as well as the examples below, are intended to illustrate and not to limit the scope of the invention. Other aspects, advantages and modifications within the scope of the invention will be apparent to those skilled in the art to which the invention pertains.

Examples

Materials and methods.

A. Clinical samples.

The clinical trial (Phase 2 GOLDEN-505 at NASH (GFT505-212-7 -NCT01694849) is a multicenter, randomized, double-blind, placebo-controlled trial to evaluate the efficacy and safety of elafibranor (1-[4-methylthiophenyl]-3-[3.5 -dimethyl-4carboxydimethylmethyloxyphenyl]prop-2-en-1-one) once daily for steatohepatitis in patients with non-alcoholic steatohepatitis (NASH). Liver biopsy was taken to confirm the diagnosis of NASH after appropriate exclusion of other liver disease. NASH was diagnosed as steatohepatitis assessed by liver biopsy within 6 months prior to randomization Confirmation of steatohepatitis was based on centralized reading of liver biopsies Patients with NASH were defined as having NAS>3, including steatosis score >1, and hepatocyte ballooning score >1, and lobular inflammation>1.

The study was approved by the relevant regulatory authorities at each participating center and all patients consented to participate in the medical study.

The blood samples used in this biomarker study were from patients in the GOLDEN-DIAG study at entry (270 samples) and one year later (223 samples).

The present inventors also had access to human blood samples from liver biopsy subjects and associated clinical and biological data from the UZA biobank, OBESE cohort. This morbidly obese cohort also includes NAFLD/non-NASH patients, NASH patients, cirrhotic patients, and healthy controls. Sera from 253 patients were processed to test the candidate circulating miRNA identified in the GOLDEN-DIAG study using next-generation sequencing (NGS) technology and quantitative OT-PCR, respectively.

For both the GOLDEN and OBESE cohorts, written informed consent for the collection, storage, and use of additional samples was obtained from each patient.

The present inventors also had access to human blood samples from liver biopsy subjects and associated clinical and biological data from the RESOLVE-IT study. RESOLVE-IT is a phase III, multicenter, randomized, double-blind, placebo-controlled trial (NCT02704403) to evaluate the efficacy and safety of elafibranor in patients with non-alcoholic steatohepatitis (NASH) and fibrosis. The study was approved by the relevant regulatory authorities, and all patients gave informed consent to participate. Liver biopsy at study entry was used to study and evaluate histological lesions. Blood samples were taken at screening. Additional blood samples were taken from patients who signed a special informed consent for the study of new diagnostic biomarkers of NASH.

Sera from 370 patients in the RESOLVE-IT study at screening with 263 matching liver biopsies were processed to identify circulating miRNAs using HTG Edge sequence analysis.

Serum from 370 patients in the RESOLVE-IT study at screening with 263 matching liver biopsies was processed to validate the candidate circulating miRNA identified in the GOLDEN-DIAG study by HTG Edge sequence analysis and quantitative OT-PCR.

- 32 043299

Sera from 100 subjects from EFS (Etablissement Français u Sang) were processed to assess levels of candidate circulating miRNAs in healthy subjects using HTG sequence analysis.

Edge and quantitative OT-PCR.

Serum samples were used for analysis by NGS and quantitative PCR.

Blood sampling and laboratory tests

Blood samples were collected in accordance with the central laboratory protocol and Genfit guidelines - GFT505-212-7.

According to the study protocol, the following analyzes were carried out.

Hematology includes hemoglobin, hematocrit, red blood cell count, white blood cell count, differential white blood cell count (neutrophils, lymphocytes, eosinophils, monocytes, basophils - values and %), platelet count and reticulocytes.

Biochemistry,

Panel I, includes plasma glucose, triglycerides (TG), creatinine, creatinine clearance, gamma-glutamyl transferase (GGT), aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatine phosphokinase (CPK), alkaline phosphatase, thyroid stimulating hormone (TSH), and HbA1c.

Biochemistry,

Panel II, includes plasma glucose, creatinine, creatinine clearance, total protein, albumin, sodium, potassium, chloride, calcium, uric acid, urea expressed as blood urea nitrogen (BUN), aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT), alkaline phosphatase, creatine phosphokinase (CPK), total bilirubin, conjugated bilirubin, C-reactive protein (hsCRP), AST/ALT ratio and HbA1c.

Urinalysis includes test strip analysis (specific gravity, pH, RBC, leukocytes, glucose, protein, ketones, bilirubin, urobilinogen, and nitrite).

Microscopic analysis includes RBCs, WBCs, casts, crystals, bacteria, epithelial cells, and yeasts.

Chemical analysis (albumin and creatinine).

Serology includes HIV I/II antibodies, HCV antibodies, HCV RNA (tested only after receiving HCV RNA samples at the visit and in case of reactive or indeterminate result for HCV antibodies) and HbsAg.

Lipid panel includes triglycerides (TG), total cholesterol, non-HDL-C (estimated), high density lipoprotein cholesterol (HDL-C), low density lipoprotein (LDL-C) (estimated), very low density lipoprotein cholesterol (VLDL) calculated -C) (calculation), apolipoprotein AI (ApoAI) and apolipoprotein B (ApoB).

Urine chemistry includes alpha-1-microglobulin, beta-N-acetylglucosaminidase (beta-NAG), and neutrophil-gelatinase-associated lipocalin (N-Gal).

Safety markers include homocysteine, NT-ProBNP, troponin T, cystatin C, and beta2-microglobulin.

Glycemic and other lipid parameters include leptin, insulin, homeostatic model assessment (HOMA-IR), serum glucose (for HOMA-IR calculation), fructosamine, C-peptide, and free fatty acids (FFA).

Inflammatory markers include haptoglobin, fibrinogen, tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6), and plasminogen activator inhibitor 1 (PAI-1) Ag (citrate).

Liver markers include cytokeratin-18 (CK18) (M65 and M30), adiopectin, ferritin, alpha2 macroglobulin, FGF19 and FGF21, hyaluronic acid (Advia centaur, reagents procured by Siemens Belgium and paid for by Genfit at cost transfer), N-terminal collagen propeptide type III (PIIINP) (Advia centaur, reagents purchased from Siemens Belgium) and tissue inhibitor of matrix metalloprotease-1 (TIMP-1) (Advia centaur, reagents purchased from Siemens).

The list of methods, instruments and manufacturers for each biochemical analysis is presented in this table.

parameter method tool manufacturer leptin ELISA manually R&D Systems

- 33 043299

insulin CLIA Immulite 2000 Siemens HOMA-IR Calculation with glucose and insulin fructosamine colorimetric Modular P800 Roche Diagnostics C-peptide CLIA Immulitis 2000 Siemens haptoglobin immunoturbidimetry Modular P800 Roche Diagnostics fibrinogen Clauss method STAR- evolution Stago TNF alpha fluorokine multi profiling analyte Luminex Millipore IL-6 fluorokine multi profiling analyte Luminex Millipore PAI-1Ag ELISA manually Stago FFA ACS-ACOD Modular P800 Roche Diagnostics SK18M30 ELISA manually Peviva SK18M65 ELISA manually Peviva adiponectin ELISA manually Millipore ferritin ECLIA Modular E170 Roche Diagnostics alpha2 macro oglobulin nephelometry BN II Siemens hyaluronic acid immunological analysis advia centaur Siemens PIIINP immunological analysis advia centaur Siemens TIMP-1 immunological analysis advia centaur Siemens FGF-19 ELISA manually R&D Systems FGF-21 ELISA manually R&D Systems visfatin ELISA manually Alpco immunoassays resistin ELISA manually R&D Systems YKL-40, CHI3L1 Immunological assay for human chitinase-3-like protein 1 Quantikine® ELISA Part number DC3L10 For the quantitative determination of human chitinase-3-like protein 1 (CHI3L1) concentrations in cell culture supernatants, serum, plasma and urine.

Collection and storage of samples.

The blood samples used in this biomarker study were taken from patients in study 505.212.7 prior to treatment. Written informed consent for the collection, storage and use of additional samples was obtained from each patient.

Blood collected in tubes containing citrate with a volume of 2.7 ml was processed by separating cell-free plasma from blood cells within 15 minutes after collection by centrifugation at 1500

- 34 043299 rpm for 15 minutes. The supernatant plasma was transferred to a new tube. The tubes were stored at -70°C.

In order to proceed with the RNA extraction, the plasma tubes were then centrifuged on

13,000 rpm for 2 minutes to sediment and remove platelets. The platelet-free supernatant plasma was transferred to a new tube, frozen in liquid nitrogen, and stored at -80°C.

Blood collected in an 8.5 ml Serum Separation Tube (SST) was processed one hour after sampling by separating cell-free serum from blood cells by centrifugation at 1300 to 2000 rpm for 10 minutes. The serum was then transferred to a new tube. The tubes were stored at -70°C. RNA extraction was performed without additional centrifugation.

B. Next generation sequencing.

The HTG Edge sequencing system was used to sequence miRNAs contained in serum samples.

A complete microRNA transcriptome (WTA) HTG kit was used. Library preparation and sequencing were performed according to the manufacturer's recommendations. For each sample, an average of 931,000 reads per sample was obtained. The data were normalized at the manufacturer's recommendation to enable direct comparison between different samples by adjusting the number of reads.

Limma, an R/Bioconductor software suite, included differential analysis for HTG Edge sequencing.

C. Quantitative RT-PCR of miRNAs in serum.

Total serum RNA with preserved miRNAs was extracted from 100 µl of serum using the miRVanaParis extraction kit (AMI556, Ambion) according to the manufacturer's instructions. Synthetic added miR-39 C. elegans was added to the samples [3125 mmol] (MSY0000010, Qiagen) before RNA extraction as an internal control of the RNA extraction process. Elution was carried out in 100 μl of elution buffer.

Mature miRNA expression was determined according to the manufacturer's instructions using the Taqman MicroRNA OT-PCR assay: TaqMan MicroRNA Reverse Transcription Kit (Ref: 4366596, Applied Biosystems, Carlsbad, CA), TaqMan MicroRNA 20X Assay (Ref: 4440887, Applied Biosystems) and TaqMan Universal Master Mix II (Ref: 4440040, Applied Biosystems).

Reverse transcription was performed using a GeneAmp® PCR System 9700 thermal cycler (Ref: 200005, Applied Biosystems). Reverse transcription was multiplexed with 4 reverse RNA specific primers.

Quantitative PCR was performed using the CFX96™ real time system (C 1000 Touch™ Thermal Cycler, BioRad).

MicroRNA sequences of interest and Taq Man assay identifiers are shown in the following table.

miRNA ID Subsequence miRbase number Test ID hsa-miR-193a-3p AACUGGCCUACAAAGUCCCAGU (sequence ID:1) MIMAT0000459 002250 hsa-miR-193a-5p UGGGUCUUUGCGGGCGAGAUGA (Sequence ID: 2) MIMAT0004614 002281 hsa-miR-193b-5p CGGGGUUUUGAGGGCGAGAUGA (Sequence ID: 3) MIMAT004767 002366 hsa-miR-193b-3p AACUGGCCCUCAAAGUCCCGCU (Sequence ID: 4) MIMAT0002819 002367

Synthetic hsa miRNAs (Integrated DNA Technologies) were diluted to 3.125 fmol/ml and 5 μl were used for reverse transcription simultaneously with RNA isolated from serum samples. The product was serially diluted and PCR was performed on all samples (standards and RNA obtained from serum). A standard curve was built and used to convert Cq data to copies/µl. Cq determination mode - regression. Quantification is expressed in copies/µl serum format.

All synthetic hsa miRNAs were supplied by IDT.

D. Statistical analysis.

Purpose and definition.

The aim of these analyzes was to identify biomarkers that may be associated with the identification of NASH patients eligible for treatment. Patients to be treated (TBT) are defined differently depending on the different parts of the study.

According to the first classification, TBT is defined as:

- 35 043299 steatosis score >1, hepatocyte ballooning score >1, lobular inflammation score >1,

NAS (NAFLD activity score) >4 (NAS is defined as the sum of the steatosis score, the hepatocyte ballooning score, and the lobular inflammation score), fibrosis stage >2 (such as a fibrosis stage of 2, 3, or 4, such as 2 or 3).

According to the second classification, TBT is defined as:

steatosis score >1, hepatocyte ballooning score >1, lobular inflammation score >1,

NAS (NAFLD activity score) >4 (NAS is defined as the sum of the steatosis score, the hepatocyte ballooning score, and the lobular inflammation score), fibrosis stage >1 (eg, fibrosis stage equal to 1, 2, 3, or 4).

According to the third classification, TBT is defined as:

steatosis score >1, hepatocyte ballooning score >1, lobular inflammation score >1,

NAS (NAFLD activity score) >4 (NAS defined as the sum of the steatosis score, the hepatocyte ballooning score, and the lobular inflammation score), fibrosis stage=1b, 1c, 2, 3, or 4.

Other patients were designated as non-treatable (NTBT). For analysis, TBT patients were classified as 1 and NTBT as 0 in the dependent variable. As shown above, the explanatory variables cover a wide range of biomarkers measured in blood samples (hematology, biochemistry, coagulation, liver markers, circulating miRNA) or urine (dipstick, sediment), to demographic (age, sex, race), region (research center, country, continent) or medical records (diabetes).

Bootstrap model.

In bootstrap modeling, a logistic generalized linear model of the dependent variable (defining TBT/NTBT patients) in relation to explanatory variables (biomarkers) is calculated for all patients from a common data set. Variable selection is reversed and the optimal algorithm is selected using AIC. The significance of the variable coefficients from this optimal algorithm is then tested by running the algorithm using 1000 bootstrap samples. Coefficients that show a 95% confidence interval, excluding zero, are considered significant. The algorithm is then tested by calculating ROC, AUC, optimal threshold, overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value.

results

First, circulating levels of 2083 microRNA species were simultaneously measured in 517 serum samples from GOLDEN-DIAG and OBESE using next-generation sequencing at Edge Sequencing to unbiasedly select miRNAs whose circulating levels could distinguish between TBT2 patients (definition TBT2=NAS >4 and F > 2, and at least one score for steatosis, lobular inflammation, and hepatocyte ballooning) and NTBT2 subjects (an NTBT2 subject differs from a TBT2 subject by at least one point in scores for steatosis, hepatocyte ballooning, lobular inflammation, NAS and/or fibrosis stages). TBT2 patients should be treated due to an increased risk of developing serious liver diseases such as cirrhosis, HCC, liver failure, liver transplant, and liver failure.

From this analysis, the inventors identified mir193, which generally had increased expression in serum samples from TBT2 patients compared to NTBT2 patients in the GOLDEN-DIAG and OBESE cohort at inclusion.

As shown in Table. 1, and is significant and unexpected, in the GOLDEN-DIAG and OBESE cohorts, the RPM for hsa-miR193a-5p, hsa-miR193a-3p, and hsa-miR193b-3p was significantly higher in TBT2 patients than in NTBT2 patients.

For example, 778, 592 and 632 RPM (reads per million) were obtained in TBT2 patients compared to 516, 439 and 392 RPM for NTBT2 patients for hsa-miR-193a-3p, hsa-miR-193a-5p and hsa-miR193b -3p, respectively.

The inventors also used liver biopsy and serum samples collected at the end of the one year treatment period in the GOLDEN trial as a third independent dataset and further confirmed that the RPMs for hsa-miR193a-5p and hsa-miR193b-3p were significant higher in TBT2 patients than in NTBT2 patients. The hsa-miR-193b-5p level was also significantly higher in TBT2 patients than in NTBT2 patients.

These results were confirmed in an independent OBESE cohort between TBT2 patients and

- 36 043299

NTBT2.

In addition, biopsy and serum samples collected from the independent RESOLVE-IT clinical cohort were also processed through the HTG Edge Sequencing assay. Upregulation of hsa-miR-193a-5p, hsa-miR-193b-5p and hsa-miR-193b-3p was confirmed in this additional data set and clinical cohort.

All hsa-miR-193, hsa-miR-193a-5p, hsa-miR-193a-3p, hsa-miR-193b-5p and hsa-miR-193b-3p candidates tested were upregulated in NAFLD patients with minimal histologic foci (NTBT2) compared with serum from healthy subjects (Table 1).

Table 1

HGT-Edge next generation sequencing experiments and reads per million (RPM) obtained for hsa-miR-193a-3p and hsa-miR-193a-5p, hsa-miR-193b-3p and hsa-miR-193b- 5p in patients eligible for treatment (TBT2) compared with patients not eligible for treatment (NTBT2)

Golden Diag - when turned on hsa_MHKpoPHK RPM in RPM for TBT2 multiplicity p-value NTBT2 changes hsa-miR-193a-3p 516 778 1.33 3,ZZE-04 hsa-miR-193a-5p 439 592 1.38 4D6E-06 hsa-miR-193b-3p 392 632 1.76 8.08Е-09 hsa-miR-193b-5p 18 31 1.72 4.22E-06 Golden Diag - for 52 weeks e hsa miRNA RPM for NTBT2 RPM for TBT2 multiplicity p-value changes hsa-miR-193a-3p 512 598 1.11 3,O8E-O1 hsa-miR-193a-5p 382 636 1.61 1D4E-06 hsa-miR-193b-3p 354 720 1.83 1.71E-06 hsa-miR-193b-5p 16 35 1.91 6.41Е-06 OBESE - when turned on hsa miRNA RPM for NTBT2 RPM for TBT2 multiplicity p-value changes hsa-miR-193a-3p 811 1075 1.19 1D2E-01 hsa-miR-193a-5p 300 465 1.45 6.99E-06 hsa-miR-193b-3p 95 244 1.96 1.21E-11 hsa-miR-193b-5p 4 13 1.78 1, OZE-OZ RESOLVE-IT - when turned on cheniya hsa miRNA RPM for NTBT2 RPM for TBT2 multiplicity p-value changes hsa-miR-193a-3p 658 796 1.15 1D6E-01 hsa-miR-193a-5p 442 653 1.44 2.38E-06 hsa-miR-193b-3p 387 607 1.69 8.22E-08 hsa-miR-193b-5p 17 27 1.81 4.82E-06

Subjects of EFS

vamiRNA RPM y healthy hsa-miR-193a-3p 198.05 hsa-miR-193a-5p 212.04 hsa-miR-193b-3p 69.93 hsa-miR-193b-5p 3.44

- 37 043299

Reads per million (RPM) are expressed as the mean of the NTBT2 and TBT2 patient groups (Golden Diag study - at inclusion (109 TBT2 and 161 NTBT2 patients) and Golden Diag - one year later (76 TBT2 and 147 NTBT2); OBESE (50 TBT2 and 202 NTBT2 patients, RESOLVE-IT (137 TBT2 and 117 NTBT2)), respectively; TBT2 refers to patients with NAS >4 with at least 1 score for steatosis, hepatocyte ballooning, and lobular inflammation and fibrosis stage >2 on biopsy histology liver.An NTBT2 subject differs from a TBT2 subject by at least one point in terms of steatosis, hepatocyte ballooning, lobular inflammation, NAS, and/or stage of fibrosis.EFS (Etablissement Francais du Sang) subjects are healthy subjects not taking medicines.

For confirmation, hsa-miR193a-5p, hsa-miR193b-3p, and hsa-miR-193b-5p levels were then measured using the gold standard method for oligonucleotide quantification in body fluids, quantitative OT-PCR, using dedicated TaqMan miRNA assays . The results can be summarized as follows:

As shown in Table. 2 and in FIG. 2, in both cohorts at inclusion and in the GOLDEN-DIAG at week 52, serum concentrations of hsa-miR193a-5p, hsa-miR193b-3p, and hsa-miR-193b-5p were significantly higher in TBT2 patients than in NTBT2 patients. In GOLDEN-DIAG, serum concentrations of hsa-miR193b-3p were significantly higher in NAFLD patients with minimal histological changes (NTBT2) than in serum from healthy subjects (Fig. 1 and Fig. 4).

Table 2 Quantitative RT-PCR experiments to confirm/validate hsa-miR-193a-5p, hsa-miR-193b-3p, and hsa-miR-193b-5p overexpression in treated patients (TBT2) versus untreated patients ( NTBT2) in three _______________cohorts (GOLDE, OBESE and RESOLVE-IT)_______________

Golden Diag Copies/µl NTBT2 Copies/µl for TBT2 TBT2/NTBT2 Patients (N=161) (N=109) Copies, mk l-1 in serum Average SD SE M Average SD SE M ratio meaning R AU WITH hsa-miR193а-5р 400 285 22 609 412 39 1.52 <0.0001 0.68

- 38 043299

hsa-miR193b-3p 161 196 15 290 350 34 1.80 <0.0001 0.68 hsa-miR193b-5p 20 37 3 40 49 5 1.98 <0.0001 0.67 Golden Diag One year later at week 52 Copies/µl NTBT2 Copies/µl for TBT2 TBT2/NTBT2 Patients (N=147) (N=76) Copies, mk l-1 in serum Average SD SE M Average SD SE M attitude R - meaning AU WITH hsa-miR193а-5р 412 260 21 613 401 33 1.49 <0.0001 0.65 hsa-miR193b-3p 155 179 15 286 281 23 1.84 <0.0001 0.69 hsa-miR193b-5p 22 40 3 50 69 8 2.32 <0.0001 0.69 Obesity - at turn on And Copies/µl NTBT2 Copies/µl for TBT2 TBT2/NTBT2 Patient s (N=202) (N=50) Copies.mk l-1 in serum Average SD SE M Average SD SE M attitude R - meaning AU WITH hsa-miR193а-5р 452 269 19 637 412 58 1.41 <0.0001 0.65

- 39 043299

hsa-miR193b-3p 67 53 4 190 218 31 2.85 <0.0001 0.74 hsa-miR193b-5p 27 20 1 48 39 6 1.78 <0.0001 0.69 RESOLV E-IT - when turned on and Copies/µl NTBT2 Copies/µl for TBT2 TBT2/NTBT2 Patients (N=112) (N=136) Copies, mk l-1 in serum Average SD SEM Average SD SE M attitude R - meaning AU WITH hsa-miR193а-5р 334 254 27 503 332 33 1.51 <0.0001 0.70 hsa-miR193b-3p 56 73 8 105 112 eleven 1.88 <0.0001 0.73 hsa-miR193b-5p eleven 18 2 19 24 2 1.71 0.0010 „65

The statistical significance of TBT2 versus NTBT2 was calculated using the non-parametric Mann-Whitney test. TBT2 refers to patients with NAS >4, steatosis, hepatocyte ballooning, and lobular inflammation scores >1, and fibrosis stage >2 on liver biopsy histology. AUROC=Area under the curve of true/false detection ratios was derived to identify TBT2 versus NTBT2.

As shown in FIG. 1, 2, and 3, using the second definition of TBT patients and NTBT patients (TBT1 vs. NTNT) in the two cohorts, at inclusion, analyzes showed that for hsa-miR193b-3p (Fig. 1), hsa-miR193b-5p (Fig. 2 ) and hsa-miR193a-5p (Fig. 3), serum concentrations were significantly higher in TBT1 patients than in NTBT1 patients. In GOLDEN-DIAG, serum hsa-miR193b3p concentrations were significantly higher in NAFLD patients with minimal histological lesions (NTBT1) than in serum from healthy subjects (Figure 1). In these analyzes, TBT1 refers to patients with NAS >4 with at least 1 score for steatosis, hepatocyte ballooning, and lobular inflammation and fibrosis stage >1 on liver biopsy histology. The NTBT1 subject differs from the TBT1 subject by at least one point in terms of steatosis, hepatocyte ballooning, lobular inflammation, NAS, and/or fibrosis stage scores.

As shown in FIG. 1, 2 and 3, using the third definition of TBT patients and NTBT patients (TBT7 vs. NTBT7) in the two groups, at inclusion analyzes showed that serum concentrations of hsa-miR193b-3p (Fig. 1), hsa-miR193b-5p (Fig. 2) and hsa-miR193a-5p (FIG. 3) were significantly higher in TBT7 patients than in NTBT7 patients. In GOLDEN-DIAG, hsa-miR193b-3p serum concentrations were significantly higher in patients with minimal histological lesions (NTBT7) than in serum from healthy subjects (Fig. 1). In these analyzes, TBT7 refers to patients with NAS >4 with at least a score of 1 for steatosis, hepatocyte ballooning, and lobular inflammation and fibrosis stage >1 on liver biopsy histology. An NTBT1 subject differs from a TBT1 subject by at least one point in steatosis, hepatocyte ballooning, lobular inflammation, NAS, and/or fibrosis scores.

As shown in FIG. 4, 5 and 6, in two groups, hsa-miR193b-3p (Fig. 4), hsa-miR193a-5p (Fig. 5) and hsa-miR-193b-5p (Fig. 6), serum concentrations were significantly higher in patients with active NASH (NAS >4 with at least 1 score for steatosis, hepatocyte ballooning, and lobular inflammation) than in patients without NASH and with mild NASH (NAS<4). In GOLDEN-DIAG, hsa-miR-193b-3p serum concentrations were significantly higher in patients with minimal disease activity (NAS<4) than in serum from healthy subjects.

As shown in FIG. 4, 5 and 6, in two groups: hsa-miR-193b-3p (Fig. 4), hsa-miR-193a-5p (Fig. 5) and hsa-miR-193b-5p (Fig. 6), concentrations in serum were significantly higher in patients with significant

- 40 043299 fibrosis or a higher stage of fibrosis (F>2) than in patients without fibrosis or with minimal fibrosis (F<2). In GOLDEN-DIAG, serum concentrations of hsa-miR-193b-3p were significantly higher in NAFLD patients with no or minimal fibrosis (F<2) than in healthy controls.

These results were confirmed in the RESOLVE-IT study for hsa-miR-193b-3p, hsa-miR193a-5p and hsa-miR-193b-5p (FIG. 7).

Further analysis of quantitative OT-PCR experiments performed on serum samples from GOLDEN-DIAG at inclusion shows a strong correlation between levels of circulating miR-193 species and histological scores and fibrosis stage (similar results were obtained using OBESE and RESOLVE-IT samples).

As shown in FIG. 8, circulating hsa-miR193b-3p levels are positively correlated with steatosis score, lobular inflammation score, and hepatocyte ballooning score. Therefore, the level of circulating miR193b-3p significantly and positively correlates with NAS and activity index. Finally, there was a strong correlation between circulating 193b-5p levels and fibrosis stage in the GOLDEN DIAG at inclusion.

As shown in FIG. 9, circulating hsa-miR193b-5p levels are positively correlated with steatosis score, lobular inflammation score, and hepatocyte ballooning score. Therefore, the level of circulating miR193b-3p significantly and positively correlates with NAS and activity index. Finally, there was a strong correlation between circulating miR193b-5p levels and fibrosis stage in the GOLDEN DIAG at inclusion.

As shown in FIG. 10, circulating miR193a-5p levels are positively correlated with steatosis score, lobular inflammation score, and hepatocyte ballooning score. Therefore, the level of circulating miR193b-3p significantly and positively correlates with NAS and activity index. Finally, there was a strong correlation between circulating miR193a-5p levels and fibrosis stage in the GOLDEN DIAG at inclusion.

The results presented in the following table. 3 illustrate significant correlations between changes in circulating hsa-miR-193a-5p levels and the evolution of NAFLD and NASH activity at 52 weeks in GOLDEN patients. Similarly, the results presented in the following table. 3 illustrate significant correlations between changes in circulating hsa-miR-193b-3p levels and the evolution of NAFLD and NASH activity at 52 weeks in GOLDEN patients.

Table 3

Relationship between changes in serum levels of hsa-miR193a-5p and hsa-miR193b-3p and evolution of activity index (AI) and NAS during the one-year GOLDEN study

GOLDEN-DIAG (Week 52-Power On) Change in serum miR concentration (L miR) compared to the activity evolution index (AA1) Improvement (A AI<0) stable (A A1=0) Aggravation (A A1> 0) P-value (Kruskal Wallis test) AmiR-193a-5p (copies/µl) -72±33 -7±41 +202±91 0.02 AmiR-193b-3p (copies/µl) -41±26 -7±29 +49±36 0.17 GOLDEN-DIAG (Week 52-Power On) Change in serum miR concentration (AmiR) versus evolution of NAS (A NAS) Improvement (A stable Deterioration (A p-value

- 41 043299

NAS<0) (A NAS=0) NAS > 0) (Kruskal Wallis test) AmiR-193a-5p (copies/µl) -87±33 +23±50 +107±62 0.02 AmiR-193b-3p (copies/µl) -62±26 +8±38 +48±22 0.008

Modeling using the bootstrap approach allowed the selection of four significant variables with miR-193b-3p to differentiate between TBT2 patients and NTBT2 patients (Table 4). This model combines miR-193b-3p, tissue inhibitor of metalloproteinase 1 (TIMP-1), YKL-40, also called chitinase-3-like protein 1 (CHI3L1), platelet count, and metabolic syndrome (MS) to diagnose eligible patients with NASH or patients at risk of developing NASH.

Patients at risk for treatment fit the following liver biopsy grades: steatosis score >1, hepatocyte ballooning score >1, lobular inflammation score >1, NAS (NAFLD activity score) >4, and fibrosis stage >2 (for example, fibrosis stage is 2, 3 or 4, in particular 2 or 3).

Table 4

Selected variables in the optimal bootstrap model for identifying TBT2 patients in Golden. Confidence Ingerval—CI, SE: standard error

SE ratio 95% CI

Constant -5.53 1.46 -8.39 -2.67 miR-193b-3p (LoglO copies.mcl1) 1.54 0.49 0.58 2.50 tissue inhibitor metalloproteinase 1 (TIMP-1) 1.05Е-02 4D7E-03 2.29E-03 1.87E-02 YKL-40 or CHI3L1 9.34Е-06 3.67E-06 2D4E-06 1.65Е-05 Platelet count -8.32E-03 3.71E-03 -1.56E-02 -1.05Е-03 metabolic syndrome 0.83 0.41 0.03 1.63

The score is defined as a logistic function:

Where

Y=k+a*A+b*B+c*C+d*D+f*F, where

S is the NASH score;

A is the level of hsa-miR-193b-3p in log10 copies.µl-1;

B is the level of TIMP-1 in ng/ml;

C is the level of YKL-40 in pg/ml;

D is the number of platelets in 10 ⁹ /l;

F is the metabolic syndrome score;

k is a number in the range -8.39 to -2.67.

The AUC estimate for the bootstrapping model corresponding to the patient at risk, as described earlier, and the pooling of several variables is better than the AUC estimate obtained for individual variables. Thus, the combination of multiple variables with a logistic function in accordance with the present invention is better and more accurate than studying a single variable (Table 5 and FIG. 11).

- 42 043299

Table 5

Comparison of the estimates of the bootstrapping model of the present invention with individual variables in the GOLDEN-DIAG. Comparison of diagnostic characteristics.

Non-invasive profile=NIS=algorithm with miR-193b-3p AU WITH Optimal threshold accuracy b sensitivity specific be PPV NPV Genfit NIS 0.80 0.3993 72.62% 81.25% 64.77% 67.71 % 79.17 % hsa-miR193b-3p 0.68 2.1829 67.26% 65.00% 69.32% 65.82 % 68.54 % TIP-1 0.68 248.50 64.88% 65.00% 64.77% 62.65 % 67.06% CHI3L1 0.68 56512.88 65.48% 65.00% 65.91% 63.42 % 67.44 % Number of platelets OB 0.62 212.50 61.91% 65.00% 59.09% 59.09% 65.00%

The optimal model is tested by calculating the AUC in 1000 bootstrap samples. AUC was 0.80 (95% CI: 0.73-0.86). Using the AUC of the optimal model, 3 thresholds were determined to predict patients as TBT or NTBT.

1. The threshold closest to the point with 1-specificity=0% and sensitivity=100% was 0.3993. The corresponding factor table gave the following figures.

Overall accuracy: 72.62%.

Sensitivity: 81.25%.

Specificity: 64.77%.

PPV: 67.71%.

NPV (Negative Predictive Value): 79.17%.

2. The threshold giving 90% sensitivity was 0.3050. The corresponding factor table gave the following figures.

Overall accuracy: 70.24%.

Sensitivity: 90.00%.

Specificity: 52.27%.

PPV (Positive Predictive Value): 63.16%.

NPV (Negative Predictive Value): 85.19%.

3. The threshold giving a specificity greater than 90% was 0.6518. The corresponding factor table gave the following figures.

Overall accuracy: 70.24%.

Sensitivity: 47.50%.

Specificity: 90.91%.

PPV (Positive Predictive Value): 82.61%.

NPV (Negative Predictive Value): 65.57%.

A second modeling using a bootstrap approach with miRNA levels in log10 (copy.μl-1) and biochemical data allowed the selection of six significant variables with miR-193b-3p to differentiate between TBT2 patients and NTBT2 patients (Table 6). This model combines miR193b-3p, YKL-40, also called chitinase-3 like protein 1 (CHI3L1), tissue inhibitor of metalloproteinase 1 (TIMP-1), glycated hemoglobin (HbA1c), hyaluronic acid (HYUA2), and platelet count to diagnosing eligible patients with NASH or those at risk of developing NASH.

Patients at risk for treatment fit the following liver biopsy grades: steatosis score > 1, hepatocyte ballooning score > 1, lobular inflammation score > 1, NAS (NAFLD activity score) > 4, and fibrosis stage > 2 (for example, fibrosis stage is 2, 3 or 4, in particular 2 or 3).

- 43 043299

Table 6

Selected Variables in the Optimal Bootstrap Model for TBT2 Patient Identification in Golden_______________

Constant I miR-193b-3p (loglO copies.µl-1) YKL-40 or CHI3L1 TIMP-1 Coefficient -7.52 1.29 0.01 0.0092 p-value 3.72E-06 0.0028 0.0028 0.0097 95%CI -10.92 0.44 0.0035 0.0016 -3.89 2.17 0.020 0.0018 HYUA2 -0.0024 0.0131 -0.0053 0.0057 HbAlc 0.59 0.0042 0.13 1.08 Platelet count -0.009 0.0043 -0.017 -0.0027 Confidence interval=CI. The score is defined as a logistic function: ⁵² '1 + e™

Where

Y2=I+a2 *A+c2 *C+b2 *B+e*E+g*G+d2 *D, where

S2 is the NASH score;

A is the level of hsa-miR-193b-3p in log10 copies.µl-1;

C is the level of YKL-40 in pg/ml;

B is the level of TIMP-1 in ng/ml;

E is the level of HYUA2 in ng/ml;

G is the HbA1c level in %;

D is the number of platelets;

I is a number in the range -10.92 to -3.89.

The optimal model is tested by calculating the AUC in 1000 bootstrap samples. AUC was 0.80 (95% CI: 0.74-0.86). Using the AUC of the optimal model, the optimal threshold for predicting patients as TBT or NTBT was determined.

1. The threshold closest to the point with 1-specificity=0% and sensitivity=100% was 0.4216. The corresponding factor table gave the following figures.

Overall accuracy: 74.31%.

Sensitivity: 73.68%.

Specificity: 74.80% PPV: 69.31%.

NPV: 78.63%.

2. The threshold giving a sensitivity above 90% was 0.2461. The corresponding factor table gave the following figures.

Overall accuracy: 66.51%.

Sensitivity: 90.53%.

Specificity: 45.97%.

PPV: 57.33%.

NPV: 86.76%.

3. The threshold giving a specificity greater than 90% was 0.6252. The corresponding factor table gave the following figures.

Overall accuracy: 72.02%.

Sensitivity: 48.42%.

Specificity: 90.24%.

PPV: 79.31%.

NPV: 69.38%.

A third modeling using a bootstrap approach with miRNA levels in Cq and biochemical data allowed selection of the same six significant variables with miR-193b-3p to differentiate between TBT2 patients and NTBT2 patients (Table 6). This model combines miR-193b-3p, YKL-40, chitinase-3 like protein 1 (CHI3L1), tissue inhibitor of metalloproteinase 1 (TIMP-1), glycated hemoglobin (HbA1c), hyaluronic acid (HYUA2), and platelet count to diagnosing eligible patients with NASH or those at risk of developing NASH.

Patients at risk for treatment fit into the following liver biopsy grades: steatosis score > 1, hepatocyte ballooning score > 1, lobular inflammation score > 1, NAS (NAFLD activity score) > 4, and fibrosis stage > 2 (for example, fibrosis stage is 2, 3 or 4, in particular 2 or 3).

Table 6

Selected variables in the optimal bootstrap model for identifying TBT2 patients in Golden ___________________

Coefficient P-value 95% CI

constant w 8.08 0.0828 -1.27 17.54 miR193b-3p (Cq) -0.38 0.0030 -0.64 -0.09 YKL-40 or CHI3L1 0.01 0.0031 0.005 0.019 TIMP-1 0.01 0.0095 0.001 0.016 HYUA2 -0.0024 0.0138 -0.0054 0.0045 HbAlc 0.57 0.00460 0.12 1.08 Platelet count -0.009 0.0042 -0.0164 -0.0016

Confidence interval=C1.

The score is defined as a logistic function:

S3 where

Y3=m+a3 *A+c3 *C+b3 *B+e2*E+g2*G+d3 *D, where

S3 is the NASH score;

A is the level of hsa-miR-193b-3p in log10 copies.µl-1;

C is the level of YKL-40 in pg/ml;

B is the level of TIMP-1 in ng/ml;

E is the level of HYUA2 in ng/ml;

G is the HbA1c level in %;

D is the number of platelets;

m is a number in the range -1.27 to 17.54.

The optimal model is tested by calculating the AUC in 1000 bootstrap samples. AUC was 0.80 (95% CI: 0.74-0.86). Using the AUC of the optimal model, the optimal threshold for predicting patients as TBT or NTBT was determined.

1. The threshold closest to the point with 1-specificity=0% and sensitivity=100% was 0.3741. The corresponding factor table gave the following figures.

Overall accuracy: 73.39%.

Sensitivity: 78.95%.

Specificity: 69.11%.

PPV: 66.37% NPV: 80.95%.

2. The threshold giving a sensitivity above 90% was 0.2270. The corresponding factorial table gave the following figures.

Overall accuracy: 63.76%.

Sensitivity: 90.53%.

Specificity: 43.09%.

PPV: 55.13%.

NPV: 85.48%.

3. The threshold giving a specificity greater than 90% was 0.6364. The corresponding factor table gave the following figures.

Overall accuracy: 71.56%.

Sensitivity: 47.37%.

Specificity: 90.24%.

PPV: 78.95%.

NPV: 68.94%.

- 45 043299

As shown in FIG. 12 and 13, validation of Y2 algorithms (hsa-miR-193b-3p (log10 copies.µl-1),

YKL-40 or CHI3L1, TIMP-1, hyaluronic acid, HbA1c and platelet count) and Y3 (hsa-miR193b-3p (Cq), YKL-40 or CHI3L1, TIMP-1, hyaluronic acid, HbA1c and platelet count) in independent RESOLVE-IT cohort resulted in a comparable and even greater AUC of 0.81.

As shown in Table. 7, the identification of patients at increased risk even improved in the independent cohort, as evidenced by the positive predictive value.

Table 7 Diagnostic characteristics of models Y2 and Y3 in GOLDEN-DIAG and RESOLVE-IT

Manufacturer ness Overall Accuracy Sensitivity specificity PPV (%) NPV (%) Y2 GOLDEN DIAG 74.31% 73.68 74.80 69.31 78.63 Y2 RESOLVE- IT 70.61% 55.73 87.72 83.91 63.29 Y3 GOLDEN DIAG 73.58% 72.34 74.58 69.39 77.19 Y3 RESOLVE- IT 74.79% 77.69 71.43 75.94 73.39

PPV=Positive Predictive Value, NPV=Negative Predictive Value.

Finally:

i) These results, based on measuring miRNA levels in serum and plasma samples using two different methodologies (HTG Edge-Seq NGS and quantitative OT-PCR), confirm the use of hsa-mir193a-5p, hsa-miR193b-3p and hsa -193b-5p and, more generally, hsa-miR193, oligonucleotides as circulating diagnostic biomarkers to identify patients with NAFLD (NAS>1), NASH (NAS>3, at least 1 steatosis score, at least 1 lobular inflammation score and at least 1 hepatocyte ballooning score), active NASH (NAS>4, at least steatosis score 1, lobular inflammation score at least 1, and hepatocyte ballooning score of at least 1), significant fibrosis (F>2) and/or active NASH and fibrosis (TBT1, TBT2, TBT7);

ii) these results, based on the measurement of microRNA levels in serum and plasma samples, support the use of hsa-miR193 species as circulating diagnostic biomarkers for non-invasive classification of histological lesions (steatosis, lobular inflammation, hepatocyte ballooning), assessment of NASH activity (NAS or activity index ) and assessment of disease severity (fibrosis stage) in the subject;

iii) these results, based on the measurement of microRNA levels in serum and plasma samples, confirm the use of hsa-miR193 species as circulating diagnostic biomarkers for non-invasive classification of histological lesions (steatosis, lobular inflammation, hepatocyte ballooning), assessment of NASH activity (NAS or activity index ) and assessment of disease severity (fibrosis stage) in the subject;

iv) These results, based on measurements of miRNA levels in serum and plasma samples, support the use of hsa-miR193 species as circulating biomarkers to monitor the evolution of NAFLD activity, NASH activity, or fibrosis stage in the same drug-treated or untreated patient. an anti-NAFLD drug, an anti-NASH drug, or an anti-fibrosis drug;

v) Finally, the state of the art linking the level of NASH activity to the risk of developing fibrosis and linking the stage of fibrosis to the risk of long-term liver outcomes (liver cirrhosis, liver transplantation, HCC or liver failure) supports miR193 species as predictive biomarkers for assessing the risk of developing fibrosis before cirrhosis and assess the risk of long-term serious complications.

vi) The AUC estimate for the bootstrapping model corresponding to the patient at risk as described previously and the pooling of several variables is statistically better than the AUC estimate obtained for the individual variables. Thus, the combination of several variables using the logistic function according to the present invention is better and more accurate than the study of one variable.

vii) Modeling with hsa-miR-193b-3p in Cq and modeling with hsa-miR-193b-3p in log10 copies.µl-1 results in the same choice of variables: YKL-40 or CHI3L1, TIMP-1, hyaluronic acid , HbA1c and platelet count.

viii) AUC similarity between GOLDEN-DIAG and RESOLVE-IT and testing the diagnostic value of the Y2 and Y3 algorithms in an independent cohort cross-checks the power of these composite panels of biomarkers.

Claims (30)

1. A method for diagnosing non-alcoholic fatty liver disease (NAFLD), which includes determining the level of hsa-miR-193b-3p in a sample of a biological fluid of a subject, where the level of hsa-miR193b-3p is compared with control levels of hsa-miR-193b-3p, where an hsa-miR-193b-3p level that is higher than control levels obtained from samples from healthy subjects without fatty liver indicates the presence of NAFLD. 2. A method for diagnosing non-alcoholic steatohepatitis (NASH), which includes determining the level of hsa-miR-193b-3p in a sample of a biological fluid of a subject, where the level of hsa-miR-193b-3p is compared with control levels of hsa-miR-193b-3p, where an hsa-miR-193b-3p level that is higher than control range levels obtained from samples from a non-NASH subject indicates the presence of NASH, defined as 1 for steatosis, lobular inflammation, and hepatocyte ballooning; where an hsa-miR-193b-3p level that is higher than the control range level obtained from samples from subjects without active NASH indicates the presence of active NASH. 3. A method for diagnosing liver fibrosis, including determining the level of hsa-miR-193b-3p in a sample of biological fluid, where the level of hsa-miR-193b-3p is compared with the control levels of hsamiR-193b-3p, where the level of hsa-miR-193b-3p , which is higher than control levels obtained from samples with no or minimal liver fibrosis (F=0 or 1), indicating the presence of significant (F=2), moderate (F=3), or severe (F=4) fibrosis liver. 4. The method according to any one of claims 1 to 3, wherein the biological fluid sample is a blood, plasma or serum sample. 5. A method according to any one of the preceding claims, comprising classifying a subject as potentially receiving (TBT) or not receiving (NTBT) treatment for NASH and/or liver fibrosis, based on detection of an elevated level of hsa-miR-193b-3p relative to a control level of hsa -miR-193b-3p measured in NTBT subjects. 6. The method of claim 5, wherein the eligible (TBT) and non-treatable (NTBT) subjects have the following liver biopsy scores: a) TBT1: steatosis score >1, hepatocyte ballooning score >1, lobular inflammation score >1, NAS (NAFLD activity score) >4, fibrosis stage >1 (e.g., fibrosis stage of 1, 2, 3, or 4), NTBT1: differs from TBT1 by at least one point less in terms of steatosis, hepatocyte ballooning, lobular inflammation, NAS, or fibrosis stage; or b) TBT2: steatosis score >1, hepatocyte ballooning score >1, lobular inflammation score >1, NAS (NAFLD activity score) >4, fibrosis stage >2 (e.g., fibrosis stage of 2, 3 or 4, in particular 2 or 3), NTBT2: differs from TBT by at least one point less in terms of steatosis, hepatocyte ballooning, lobular inflammation, NAS, or fibrosis stage; or c) TBT7: steatosis score >1, hepatocyte ballooning score >1, lobular inflammation score >1, NAS (NAFLD activity score) >4, fibrosis stage=1b, 1c, 2, 3 or 4, NTBT7: differs from TBT by at least one point less in terms of steatosis, hepatocyte ballooning, lobular inflammation, NAS, or fibrosis stage. 7. A method for monitoring NAFLD, NASH and/or liver fibrosis, comprising determining the level of hsa-miR-193b-3p in a sample of a biological fluid of a subject, where the level of hsa-miR-193b-3p is compared with control levels of hsa-miR-193b-3p from one or more body fluid samples obtained from the same subject in the past. 8. The method of claim 7, comprising monitoring the evolution of NAFLD activity, NASH activity, or liver fibrosis in a subject based on the evolution of hsa-miR-193b-3p levels in samples collected at two or more different time points from the same subject. 9. A method for determining the effectiveness of the treatment of NAFLD, NASH and/or fibrosis, including determining the level of hsa-miR-193b-3p in a sample of a biological fluid of a subject, where the level of hsa-miR-193b3p is compared with control levels of hsa-miR-193b-3p from one or more body fluid samples obtained from the same subject in the past. 10. The method of claim 9 for evaluating the efficacy of treatment for NAFLD, NASH, or liver fibrosis based on the evolution of hsa-miR-193b-3p levels in samples collected at two or more different time points from the same treated subject. 11. Use of an anti-NAFLD compound in a method of treating a subject having NAFLD, wherein the subject is diagnosed or classified as a treatable patient due to NAFLD according to any one of claims 1, 4-6, and administering said compound to said diagnosed patient. - 48 043299 to the subject, where the specified molecule is represented by formula (I) Where X1 is halo, R1 or G1-R1; A represents CH=CH or a CH2-CH2 group; X2 is a G2-R2 group; G1 represents an oxygen atom; G2 represents an oxygen or sulfur atom; R1 represents a hydrogen atom, an unsubstituted alkyl group, an aryl group, or an alkyl group which is substituted by one or more halogen atoms, an alkoxy or alkylthio group, cycloalkyl groups, cycloalkylthio groups, or heterocyclic groups; R2 is an alkyl group substituted with at least a -COOR3 group, where R3 is a hydrogen atom or an alkyl group which is substituted or unsubstituted by one or more halogen atoms, cycloalkyl groups or heterocyclic groups, R4 and R5, the same or different, represent an alkyl group which is substituted or unsubstituted by one or more halogen atoms, cycloalkyl groups, heterocyclic groups; or a pharmaceutically acceptable salt thereof. 12. Use of an anti-NASH compound in a method of treating a subject having NASH, wherein the subject is diagnosed or classified as a treatable patient due to NASH according to any one of claims 2, 4-6, and administering said compound to said diagnosed subject, wherein said molecule is represented by the formula (I) Where X1 is halo, R1 or G1-R1; A represents CH=CH or a CH2-CH2 group; X2 is a G2-R2 group; G1 represents an oxygen atom; G2 represents an oxygen or sulfur atom; R1 represents a hydrogen atom, an unsubstituted alkyl group, an aryl group, or an alkyl group which is substituted by one or more halogen atoms, an alkoxy or alkylthio group, cycloalkyl groups, cycloalkylthio groups, or heterocyclic groups; R2 is an alkyl group substituted with at least a -COOR3 group, where R3 is a hydrogen atom or an alkyl group which is substituted or unsubstituted by one or more halogen atoms, cycloalkyl groups or heterocyclic groups, R4 and R5, the same or different, represent an alkyl group which is substituted or unsubstituted by one or more halogen atoms, cycloalkyl groups, heterocyclic groups; or a pharmaceutically acceptable salt thereof. 13. Use of an anti-fibrosis compound in a method of treating a subject having liver fibrosis, respectively, wherein the subject is diagnosed or classified as a patient to be treated due to liver fibrosis according to any one of claims 3 to 6, and administering said compound to said diagnosed subject, wherein said molecule represented by formula (I) Where X1 is halo, R1 or G1-R1; A represents CH=CH or a CH2-CH2 group; - 49 043299 X2 is a G2-R2 group; G1 represents an oxygen atom; G2 represents an oxygen or sulfur atom; R1 represents a hydrogen atom, an unsubstituted alkyl group, an aryl group, or an alkyl group which is substituted by one or more halogen atoms, an alkoxy or alkylthio group, cycloalkyl groups, cycloalkylthio groups, or heterocyclic groups; R2 is an alkyl group substituted with at least a -COOR3 group, where R3 is a hydrogen atom or an alkyl group which is substituted or unsubstituted by one or more halogen atoms, cycloalkyl groups or heterocyclic groups, R4 and R5, the same or different, represent an alkyl group which is substituted or unsubstituted by one or more halogen atoms, cycloalkyl groups, heterocyclic groups; or a pharmaceutically acceptable salt thereof. 14. Use of an hsa-miR-193b-3p inhibitory compound in a method of treating a subject having NAFLD, wherein the hsa-miR-193b-3p inhibitory compound is selected from double-stranded RNAs, antagonists, antisense nucleic acids, and RNA enzymatic molecules. 15. Use of an hsa-miR-193b-3p inhibitory compound in a method of treating a subject having NASH, wherein the hsa-miR-193b-3p inhibitory compound is selected from double-stranded RNAs, antagonists, antisense nucleic acids, and RNA enzymatic molecules. 16. Use of an hsa-miR-193b-3p inhibitory compound in a method of treating a subject having hepatic fibrosis, wherein the hsa-miR-193b-3p inhibitory compound is selected from double-stranded RNAs, antagonists, antisense nucleic acids, and RNA enzymatic molecules. 17. Use of an hsa-miR-193b-3p inhibitory compound according to any one of claims 14-16, wherein the subject has been diagnosed or classified for treatment according to any one of claims 1-6. 18. A method for diagnosing non-alcoholic steatohepatitis (NASH) and/or determining the activity, stage or severity of NASH in a subject, comprising measuring the level of circulating hsa-miR193b-3p in blood, serum or blood plasma and at least one other circulating in blood, serum or plasma marker of liver damage, where the level of hsa-miR-193b-3p is compared with the control level of hsa-miR-193b-3p. 19. A method for classifying a subject as receiving or not receiving NASH treatment and/or for classifying a patient as a potential responder or non-responder to drug treatment, comprising measuring the level of circulating hsa-miR-193b-3 in blood, serum or plasma and at least one other circulating blood, serum, or plasma marker of liver injury, wherein the hsa-miR-193b-3p level is compared to a control hsa-miR193b-3p level. 20. A method for determining the progression or repression of pathology in patients with NASH and/or for predicting the outcome of the disease in a patient, including measuring the level of circulating hsa-miR-193b-3p in blood, serum or blood plasma and at least one other circulating in blood, serum or plasma marker of liver damage, where the level of hsa-miR-193b-3p is compared with the control level of hsa-miR-193b-3p. 21. A method for determining surrogate markers of clinically significant results, including measuring the level of circulating hsa-miR-193b-3p in blood, serum or plasma and at least one other circulating blood, serum or plasma marker of liver damage, where the level of hsa -miR-193b-3p is compared with the control level hsa-miR-193b-3p. 22. The method of any one of claims 18 or 21, wherein said at least one other circulating liver injury marker is selected from the group consisting of TIMP-1, YKL-40, platelet count, HbA1c, and hyaluronic acid. 23. The method of claim 22, further comprising determining a metabolic syndrome score in the subject. 24. The method according to any one of claims 18-23, including the steps: measuring the level of hsa-miR-193b-3p and at least one marker of liver damage circulating in the blood, serum or plasma, and combining the results using a mathematical algorithm to obtain a NASH score. 25. The method of claim 23, wherein the NASH score is calculated according to the following logistic function: r ¹ where Y1=k+a*A+b*B+c*C+d*D+f*F, while S1 is the NASH score; - 50 043299 A is the level of miR-193b-3p in log10 copies.µl ^-1 ; B is the level of TIMP-1 in ng/ml; C is the level of YKL-40 in pg/ml; D is the number of platelets: 10 ⁹ /l; F represents the metabolic syndrome in the category; k is a logistic function constant; a is the coefficient associated with the level of hsa-miR-193b-3p; b is the coefficient associated with the level of TIMP-1; c is the coefficient associated with the level of YKL-40; d is a coefficient related to platelet count; and f is a coefficient associated with the metabolic syndrome, wherein the method is derived from a bootstrapping model where k is a number in the range -8.39 to -2.67, in particular -5.53, a is a number in in the range from 0.58 to 2.50, in particular 1.54, b is a number in the range from 2.29E-03 to 1.87E-02, in particular 1.05E-02, c is a number in the range from 2.14E-06 to 1.65E-05, in particular 9.34E-06, d is a number in the range -1.56E-02 to -1.05E-03, in particular -8.32E-03, f is a number in the range of 0.03 to 1.63, such as 0.83, with a threshold value of 0.3050 to 0.6518, such as 0.3993, with a NASH score greater than the threshold 0.2017 to 0.4645, in particular 0.2302, indicates severe NASH or moderate or high NASH activity; and therefore is an indication that the patient has a steatosis score >1, a hepatocyte ballooning score >1, a lobular inflammation score >1, a NAS >4, and a fibrosis stage >2. 26. The method of claim 23, wherein the NASH score is calculated according to the following logistic function: Where Y2=l+a2*A+c2*C+b2*B+e*E+g*G+d2*D, while S2 is the NASH score; A is the level of hsa-miR-193b-3p in log10 copies.µl ^-1 ; C is the level of YKL-40 in pg/ml; B is the level of TIMP-1 in ng/ml; E is the HbA1c level in percent; G is the level of hyaluronic acid in ng/ml; D is the number of platelets: 10 ⁹ /l; l is a constant of the logistic function; a2 is the coefficient associated with the level of hsa-miR-193b-3p; c2 is the coefficient associated with the level of YKL-40; b2 is the coefficient associated with the level of TIMP-1; e is the coefficient associated with the level of HbA1c; g is a coefficient related to the level of hyaluronic acid; d2 is a factor related to platelet count, the method being derived from a bootstrapping model where l is a number in the range -10.92 to -3.89, in particular -7.52, a2 is a number in the range from 0.44 to 2.17, in particular 1.29, c2 is a number in the range from 0.0035 to 0.02, in particular 0.01, b2 is a number in the range from 0.0016 to 0.018, in in particular 0.0092, e is a number in the range -0.0053 to 0.0057, in particular -0.0024, g is a number in the range 0.13 to 1.08, in particular 0.59, d2 is a number in the range -0.017 to -0.0027, such as -0.009, and wherein the threshold is from 0.2461 to 0.6252, such as 0.4216, with a NASH score greater than the threshold of from 0.2461 to 0.6252, in particular, equal to 0.4216, indicates severe NASH or moderate or high NASH activity; and therefore is an indication that the patient has a steatosis score >1, a hepatocyte ballooning score >1, a lobular inflammation score >1, a NAS >4, and a fibrosis stage >2. 27. The method of claim 23, wherein the NASH score is calculated according to the following logistic function: - 51 043299 "L ³ S3 - ——γ7 1 + e ^V3 where Y3=m+a3 *A'+c3 *C+b3 *B+e2*E+g2*G+d3 *D, while S3 is the NASH score according to the present invention; A' represents the level of hsa-miR-193b-3p in Cq; C is the level of YKL-40 in pg/ml; B is the level of TIMP-1 in ng/ml; E is the HbA1c level in percent; G is the level of hyaluronic acid in ng/ml; D is the number of platelets: 10 ⁹ /l; m is a logistic function constant; a3 is the coefficient associated with the level of hsa-miR-193b-3p; c3 is the coefficient associated with the level of YKL-40; b3 is the coefficient associated with the level of TIMP-1; e2 is the coefficient associated with the level of HbA1c; g2 is the coefficient associated with the level of hyaluronic acid; d3 is a factor related to platelet count, the method being derived from a bootstrapping model where m is a number in the range -1.27 to 17.54, in particular 8.08, a3 is a number in the range - 0.64 to -0.09, in particular -0.38, c3 is a number in the range of 0.005 to 0.019, in particular 0.01, b3 is a number in the range of 0.001 to 0.016, in particular 0.01, e2 is a number in the range of -0.0054 to 0.0045, in particular 0.0024, g2 is a number in the range of 0.12 to 1.08, in particular 0.57, d3 is a number in the range of -0.0164 to -0.0016, in particular -0.0090, and wherein the threshold is between 0.2270 and 0.6364, in particular 0.3741, with a NASH score above a threshold of 0, 2270 to 0.6364, in particular equal to 0.3741, indicates severe NASH or moderate to high NASH activity; and therefore is an indication that the patient has a steatosis score >1, a hepatocyte ballooning score >1, a lobular inflammation score >1, a NAS >4, and a fibrosis stage >2. 28. A kit for determining the level of (i) hsa-miR-193b-3p, (ii) at least one marker of liver damage circulating in blood, plasma or serum, where the kit contains means for determining the levels of hsa-miR-193b-3p and circulating marker(s) of liver injury. 29. Set according to item 28, containing a tool for determining the level of (i) hsa-miR-193b-3p; (ii) at least one liver injury marker circulating in blood, plasma or serum, corresponding to that used in the method according to any one of claims 1-27. 30. The use of an anti-NASH molecule in a method of treating NASH, wherein said anti-NASH molecule is administered to a patient in need thereof, diagnosed as having NASH or classified by the method of any one of claims 2, 4-6, in particular classified as a recipient of NASH treatment , wherein said molecule has the formula (I) wherein X1 is halo, R1 or G1-R1; A represents CH=CH or a CH2-CH2 group; X2 represents the G2-R2 group; G1 represents an oxygen atom; G2 represents an oxygen or sulfur atom; R1 represents a hydrogen atom, an unsubstituted alkyl group, an aryl group, or an alkyl group which is substituted by one or more halogen atoms, an alkoxy or alkylthio group, cycloalkyl groups, cycloalkylthio groups, or heterocyclic groups; - 52 043299 R2 is an alkyl group substituted with at least a -COOR3 group, where R3 is a hydrogen atom or an alkyl group which is substituted or unsubstituted by one or more halogen atoms, cycloalkyl groups or heterocyclic groups, R4 and R5, the same or different, represent an alkyl group which is substituted or unsubstituted by one or more halogen atoms, cycloalkyl groups, heterocyclic groups; or a pharmaceutically acceptable salt thereof.