Identification and Quantification of Fat in the Liver by MRI and its Correlation with Serum Metabolomics Jesús M. Banales, PhD

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1 Identification and Quantification of Fat in the Liver by MRI and its Correlation with Serum Metabolomics Jesús M. Banales, PhD Head, Liver Diseases Group Biodonostia Institute, San Sebastian (Spain)

2 Non Alcoholic Fatty Liver Disease Introduction Steatosis in > 5% hepatocytes Alcohol consumption < 20 g/day Absence of basal chronic liver disease Simple steatosis Non-alcoholic steatohepatitis (NASH) Fibrosis Hepatocellular carcinoma (HCC) Kanuri G, et al. Int J Mol Sci 2013

3 Epidemiology Introduction Normal liver Steatosis 25-30% general population 10-15% 10-15% Cirrhosis NASH

4 Risk factors Introduction Obesity Diabetes Hypercholesterolemia Hypertriglyceridemia Sedentarism Genetic predisposition Environmental factors Metabolic syndrome Obesity NAFLD General population NAFLD (25-30%) NASH (2-5%) Diabetes NAFLD NASH (15-60%) NASH (20-80%) Wahba I, et al. CJASN 2007

5 Overweight & Obesity Introduction Prevalence Epidemia (XXI Century)

Diagnosis: NAFLD Introduction Main aim: quantification of liver fat Semiquantitative Inter-observer variability Invasive Histology Sample variability

6 Diagnosis: NAFLD Introduction Main aim: quantification of liver fat Semiquantitative Inter-observer variability Invasive Histology Sample variability Diagnostic screening Gold standard Monitor NAFLD Brunt EM, et al. Am J Gastroenterol 1999 Tang A, et al. Radiology 2015 Lee SS, et al. World J Gastroenterol 2014

concentration) Destroys sample Diagnostic screening Gold standard

7 Diagnosis: NAFLD Introduction Quantitative Objective Sample variability Invasive Biochemistry: Folch value (triglyceride concentration) Destroys sample Diagnostic screening Gold standard Monitor NAFLD Folch J,et al. J Biol Chem 1957 Iverson SJ, et al. Lipids 2001

8 Diagnosis: NAFLD Introduction Non-invasive biomarkers Serological: - OWLiver care/owliver test (metabolomics) - Steatotest - FLI - LAP - NAFLD Liver Fat Score Image Techniques: - MRI (3D) - Ecography - Tomography

$steatosis (Folch value) Histological analisis Excellent correlation between the fat fraction calculated by multi-echo$

9 Diagnosis: NAFLD Introduction Experimental model of steatosis (high fat diet) 10 animals without steatosis (controls) 40 animals with different grades of steatosis Multiecho MRI Sacrifice (4 weeks): Biochemical quantification of steatosis (Folch value) Histological analisis Excellent correlation between the fat fraction calculated by multi-echo MRI and the biochemical determination of steatosis (triglyceride concentration: Folch value) Hijona E, et al. Eur J Radiol 2012

10 Treatment: NAFLD Introduction Main aim Prevention and regression of liver damage Healthy diet Healthy Lifestyle Weight loss Physical exercise

al. J Gastroenterol Hepatol 2007 Dixon JB, et al.

11 Treatment: NAFLD Introduction Morbid obesity Lose weight 7-10% Improves steatosis 10% Improves NASH and fibrosis Bariatric surgery Furuya CK, et al. J Gastroenterol Hepatol 2007 Dixon JB, et al. Obes Surg 2006 Vilar-Gómez E, et al. Gastroenterology 2015 Lassailly G, et al. Gastroenterology 2015

12 Hipothesis Multiecho MRI Obese/ Non obese Bariatric surgery (weight loss) 3D-quantification liver fat content Monitorization evolution of steatosis

13 Objectives I. Evaluate the capacity of multi-echo MRI to quantitate the liver fat content compared to both biochemical and histological methods on liver biopsies II. Test the ability of multi-echo MRI to monitor the evolution of steatosis in obese NAFLD patients undergoing bariatric surgery

14 Patient Selection Material & Methods Non-obese patients (BMI <35 Kg/m 2 ) - Non obese 1 (n=32) Obese patients (BMI 35 Kg/m 2 ) - Obese 1 (n=197) Whatever pathology without underlying liver disease ** Bypass o gastric tube Hepatic surgery Multi-echo MRI Histological analysis Biochemical analysis Bariatric sugery** Hepatic surgery* Multi-echo MRI Hepatic biopsy Histological analysis Biochemical measurement -2-1 Surgical intervention 1 Days Jiménez-Agüero R, et al. BMC Medicine 2014

15 Results Morbid Obesity Increases the Prevalence of Steatosis P < 0.05 Grade 0 (0-5%) 53.12% 11.34% 1 (5-33%) 34.38% 31.96% 2 (33-66%) 9.38% 41.24% 3 (>66%) 3.12% 12.40% Jiménez-Agüero R, et al. BMC Medicine 2014

16 Obesity is an Independent Risk Factor of NAFLD Results Jiménez-Agüero R, et al. BMC Medicine 2014

17 Correlation Between MRI and Histology is Moderate Results Jiménez-Agüero R, et al. BMC Medicine 2014

18 Results Correlation Between [TG] (Folch) and Histology is Moderate Jiménez-Agüero R, et al. BMC Medicine 2014

19 Excellent Linear Correlation between MRI and [TG] (Folch) Results Jiménez-Agüero R, et al. BMC Medicine 2014

20 Multi-echo MRI Allows to Accurately Estimate the Hepatic Triglyceride Concentration (Folch value) Results Validation phase: 31 adult patients 7 (Non obese) / 24 (Obese). Jiménez-Agüero R, et al. BMC Medicine 2014

21 Objectives I. Evaluate the capacity of multi-echo MRI to quantitate the liver fat content compared to both biochemical and histological methods on liver biopsies II. Test the ability of multi-echo MRI to monitor the evolution of steatosis in obese NAFLD patients undergoing bariatric surgery

22 Weight Loss Secondary to Bariatric Surgery Improves Hepatic Steatosis Results Obese patients with bariatric surgery Jiménez-Agüero R, et al. BMC Medicine 2014

23 Weight Change Influences the Evolution of Hepatic Steatosis Results Obese patients without bariatric surgery n.s.: non significant Jiménez-Agüero R, et al. BMC Medicine 2014

24 Conclusion Multi-echo MRI is an accurate approach to estimate the hepatic lipid concentration, representing an economic non-invasive method to diagnose and monitor steatosis in humans.

25 CORRELATION BETWEEN METABOLIC SERUM PROFILE, MRI AND HEPATIC TRIGLYCERIDE CONTENT IN OBESE PATIENTS

Barr J et al. J Prot Res 2010;9:4501-12 Barr J et al.

Material & Methods OWL has developed unique process to perform

Untargeted & Targeted Analyses Data Mining Organic and Aqueous

26 Barr J et al. J Prot Res 2010;9: Barr J et al. J Prot Res 2012;11: Metabolomics Process Overview Material & Methods OWL has developed unique process to perform metabolomics Metabolite Extraction Reverse UHPLC - MS Untargeted & Targeted Analyses Data Mining Organic and Aqueous Phases Liquid Chromatography and Mass Spectrometry Chromatogram Peak Area Integration

Platform Versatility Material & Methods 1200 metabolites Lipids > 1000 Glycerophospholipids PC, PE, PI, PG, LPC, LPE, LPI, LPG Glycerolipids MAG DAG TAG Fatty acyls AC NEFA oxfa FAA NAE Sterols CE BA

27 Platform Versatility Material & Methods 1200 metabolites Lipids > 1000 Glycerophospholipids PC, PE, PI, PG, LPC, LPE, LPI, LPG Glycerolipids MAG DAG TAG Fatty acyls AC NEFA oxfa FAA NAE Sterols CE BA ST Sphingolipids Cer SM FSB CMH Others > 200 Nucleotides Nucleosides TCA Glycolysis Pentose-P Amino Acids Peptides Tissues Liver Adipose Sciatic Nerve Stratum Corneum/Skin Brain Pancreas Cells Hepatocytes Hepatomes Biological Materials Biofluids Serum/Plasma Urine Lymph Tear Ear Aqueous Humor Feces Cellular Components Lipid rafts Membranes LIPID Metabolites And Pathways Strategy; Human Metabolome Database;

28 Patient Selection Material & Methods

29 Results Excellent Correlation between the Lipidomic Signature and MRI NAFLD

30 The Lipidomic Signature/MRI Coefficient Shows Good Correlation with the NAS score Results NAFLD NASH

31 Good Correlation between the Lipidomic Signature and the [TG] Results NAFLD

32 The Lipidomic Signature/[TG] Coefficient Shows Good Correlation with the NAS score Results NAFLD NASH

33 Conclusion The lipidomic profiling of serum samples showed strong correlation with the grade of steatosis measured biochemically and by MRI in obese patients. We have obtained a new non-invasive lipidomic signature able to accurately estimate the grade of steatosis (i.e. hepatic triglyceride concentration and MRI fat fraction) in obese patients.

34 Acknowledgements Enara Arretxe David Balgoma Cristina Alonso Ibon Martínez-Arranz Azucena Castro Pablo Ortiz Marcin Krawczyk Frank Lammert

35 Thanks!!! Eskerrik asko!!! Donostia-San Sebastian (Spain)

36 Blind Validation of OWLiver, a Non-Invasive Lipidomic Test for the Diagnosis of NASH Cristina Alonso, PhD Owl Metabolomics

Developmental Milestones Test evolution from concept to validated liver assays 2002: OWL Founded Early-stage biomarker isolation Creation of initial liver assays, refinement of decision algorithm(s)

active liver biopsy 2015 and beyond: Fully commercialized assays (EU), (bio)pharma CDx development Pioneer translational work on selected model and human samples were performed by parallel analyses

37 Developmental Milestones Test evolution from concept to validated liver assays 2002: OWL Founded Early-stage biomarker isolation Creation of initial liver assays, refinement of decision algorithm(s) : Continued assay validation vs. active liver biopsy 2015 and beyond: Fully commercialized assays (EU), (bio)pharma CDx development Pioneer translational work on selected model and human samples were performed by parallel analyses among Gnmt-KO mice, NAFLD patients and healthy individuals Separating simple NAFLD from NASH with 540 metabolites BMI-dependent NASH diagnosis with ca. 40 metabolites Further refinement of metabolite selection Continued assay validation & refinement: OWLiver Care 1.0/ 2.0 for NAFLD discrimination OWLiver 1.0/2.0/3.0 for NASH diagnosis Non-invasive test for screening fatty liver disease from normal individuals The world s 1st non-invasive test for diagnosing NASH

38 NAFLD/NASH Animal Models Defective or excessive S-adenosylmethionine (SAMe) gives rise to NAFLD and hepatocellular carcinoma (HCC) Defective SAMe Methionine adenosyltransferase knockout mice (Mat1a-KO) At 3 months develops fatty-liver (methionine deficient diet) At 8 months steatohepatitis (NASH) appears spontaneously At 11 months HCC is detectable Cano, et al. Hepatology 2011;54(6): Excessive SAMe Glycine N-Methyltransferase knockout mice (Gnmt-KO) At 3 months develops fatty-liver and fibrosis At 8 months HCC appears Martínez-Chantar ML, et al. Hepatology 2008 Apr;47(4): Martínez-Uña, et al. Hepatology 2013;58(4):

Preclinical Study in Gnmt KO Mice Key markers found in humans follow the same

39 Parallel Metabolic Profiling: Human & Mouse Model Sera OWL examined the serum metabolic profile in a small cohort of obese liver-biopsied patients Preclinical Study in Gnmt KO Mice Key markers found in humans follow the same trend witnessed in the NAFLD mouse model ( next slide) Barr J, et al. J Prot Res 2010;9:

40 Parallel Metabolic Profiling: Human & Mouse Model Sera Barr J, et al. J Prot Res 2010;9:

41 Clinical Validation 467 biopsied patients 11 participating hospitals Biopsy classification: Normal Liver Steatosis NASH Each class grouped into 3 different BMI cohorts Barr J, et al. J Prot Res 2012;11:

42 Metabolic Profiling BMI-dependent NAFLD-associated serum lipidomic signature in humans St/Normal NASH/Normal NASH / St Log 2 Fold- Change 4 3 The metabolic profile is routinely dependent on BMI, suggesting that the NAFLD pathogenesis mechanism may be quite different depending on an individual s level of obesity Barr J, et al. J Prot Res 2012;11:

43 NAFLD Assay Evolution Version Metabolites (n) 540 (L+AA) 25 TAG 11 TAG BMI Stratified Stratified Continuum Lean/Pre-obese: 0.98 ± 0.02 AUROC ± se ± 0.02 Sensitivity 0.93 ± se Specificity (all BMI) Obese class I-II: 0.99 ± sp L= Lipids, AA= Amino Acids, TAG= Triglycerides

44 Version 3.0: Blind validation in a new cohort Patient cohort 181 additional biopsied patients (new cohort) 2 countries: Czech Republic and Spain 5 Hospitals: Hosp. Marqués de Valdecilla (Santander, Spain / n=67) Hosp. Virgen de Valme (Seville, Spain / n=33) Hosp. Clínico Universitario Valladolid (Valladolid, Spain / n=30) Hosp. Clinic Barcelona (Barcelona, Spain / n=17) Faculty of Medicine, Charles Univ. of Prague (Prague, Czech Republic / n=34) ILC2016 Poster FRI-289; Crespo, J. et al.

45 Version 3.0: Blind validation in a new cohort Patient cohort (all biopsy-proven) ILC2016 Poster FRI-289; Crespo, J. et al.

46 Study group: 467 biopsied subjects Normal Liver (n=90) or NAFLD (377): Steatosis (246), NASH (131) 3.0 Validation Validation group: 181 biopsied subjects Normal Liver (n=30) or NAFLD (n=151): Steatosis (70), NASH (81)

47 NASH Assay Evolution Version Metabolites N 540 (L+AA) 25 TAG 20 TAG BMI Stratified Stratified Continuum Lean/Pre-obese: 0.99 ± ± 0.02 Obese class I-II: (all BMI) 0.90 ± Obese class III: 0.91 ± AUROC ± se Sensitivity Specificity L= Lipids, AA= Amino Acids, TAG= Triglycerides 0.95 ± sen 0.94 spec

48 Study group: 467 biopsied subjects Normal Liver (n=90) or NAFLD (377): Steatosis (246), NASH (131) 3.0 Validation Validation group: 181 biopsied subjects Normal Liver (n=30) or NAFLD (n=151): Steatosis (70), NASH (81)

49 Summary Establishes an easy, inexpensive, robust screening assay for NAFLD epidemiological studies Simplifies primary care patient triage to liver specialists Is a non-invasive assay for NASH diagnosis based on serum Is able to track evolution (progression/regression) of NASH patients Both tests are being commercialized in Spain and with new commercial partners starting operations in Portugal, Israel and Mexico

50 OWL Research plan Clinical Research Plan Summary Patients Samples Status Country 1 National Healthcare Hospitals in Spain Immuron NASH Phase II Trial US/Australia 3 Galmed Trial (ARREST) US/Israel/SA 4 International Blind Validation of OWLiver Follow Up Study in Type II Diabetes in Spain NASH Incidence in Morbid Obesity Bariatric Surgery Bariatric Surgery on NASH in Diabetics (Sheba Hospital) Trial on the Incidence in NASH in Blood Donors Historical Samples from Virginia Commonwealth University (VCU) US 10 VCU + Switzerland + Spain (OWLiver) Plasma US/Switzerland 11 Validation of Signature for NASH Staging (Screening Failures) US 12 Echosens Trial Phase II Pharma Trial US Total

51 Blind Validation of OWLiver, a Non-Invasive Lipidomic Test for the Diagnosis of NASH Questions / Comments? Cristina Alonso, PhD Owl Metabolomics

52 The Lipidomic Signature of Disease Progression in NAFLD Puneet Puri, MD Virginia Commonwealth University

53 NAFLD Most Common Liver Disorder NAFLD is the hepatic manifestation of metabolic syndrome

54 Spectrum of Nonalcoholic Fatty Liver Disease (NAFLD)

55 Cohen JC et al. Science 332, 1519 (2011) Overview of Lipid Metabolism in NAFLD

56 A lipidomic analysis of nonalcoholic fatty liver disease Hepatic Lipidome in NASH Puri P et al. Hepatology Dec;46(4):

57 A lipidomic analysis of nonalcoholic fatty liver disease Hepatic Lipidome in NASH Low PC High LyPC High Free Cholesterol Puri P et al. Hepatology Dec;46(4):

58 The Plasma Lipidomic Signature of Nonalcoholic Steatohepatitis Puri P et al. Hepatology Dec;50(6):

59 NAFLD is associated with increased de novo lipogenesis A composite fatty acid methyl ester data from all lipid classes reflective of monounsaturated fatty acids metabolism is displayed as pathway maps Puri P et al. Hepatology Dec;50(6):

60 NAFLD is associated with peroxisomal dysfunction The docosahexaenoic acid (DHA, 22:6n3) to docosapentaenoic acid (DPA, 22:5n3) ratio among different lipid classes and changes in plasmalogen levels are represented graphically Puri P et al. Hepatology Dec;50(6):

61 NAFLD is Associated with Increased Inflammatory and Oxidative Stress Related Eicosanoid Metabolites Puri P et al. Hepatology Dec;50(6):

62 Circulating Lipidome Model for NAFLD Pathophysiology INFLAMMATION OXIDATIVE STRESS LIPOGENESIS Puri P et al. Hepatology Dec;50(6):

Disease Progression in NAFLD - Initial results Poster presentation @ 2015 AASLD titled, The Lipidomic Signature of

63 Disease Progression in NAFLD - Initial results Poster 2015 AASLD titled, The Lipidomic Signature of Disease Progression in Non-alcoholic Fatty Liver Disease (NAFLD), Arun Sanyal & Puneet Puri, Virginia Commonwealth University.

64 Metabolites & NAFLD Progression 22 plasma metabolites were associated with NAFLD progression

65 Metabolites Associated With NAFLD Progression INCREASE WITH NAFLD PROGRESSION DECREASE WITH NAFLD PROGRESSION

66 Cohort 208 samples from five participating hospitals CONTROL NAFLD F1-F2 F3-F4 USA: VCU (Dr. Sanyal) Switzerland: Inselspital - Bern University Hospital (Dr. Dufour) Spain: Hospital Universitario de Valme (Dr. Romero) Hospital Universitario Santa Cristina (Dr. García- Monzón) Hospital Universitario Príncipe de Asturias (Dr. Martín-Duce)

67 Metabolites & NAFLD progression Previous metabolites associated with NAFLD progression were evaluated in the new cohort. The same trend was obtained for all of them.

68 Linear regression models Three linear regression models have been built comparing: NAFLD (all samples) vs. controls NAFLD with fibrosis vs. NAFLD without fibrosis NAFLD F3-F4 vs. NAFLD F1-F2 CONTROL NAFLD F1-F2 F3-F4 All the models has been weighted due to the difference in sample size of the groups. Leave-one-out cross validation (LOOCV) of the models has been performed.

69 NAFLD vs. Controls N=208; Control (N=23) & NAFLD (N=185) 7 variables were included: phospholipids, sphingolipids & acyl carnitines AUROC (se) 0.95 (0.03) Accuracy 0.93 Sensitivity: 0.97 Specificity: 0.61 Pos Pred Value: 0.95 Neg Pred Value: 0.74 Leave One Out Cross Validation (LOOCV): AUROC = 0.91, Accuracy = 0.92

70 NAFLD without vs. NAFLD with fibrosis N=185; NAFLD without (N=71) & NAFLD with fibrosis (N=114) 16 variables were included: phospholipids, triacylglycerols & non-esterified fatty acids AUROC (se) 0.92 (0.02) Accuracy 0.85 Sensitivity: 0.90 Specificity: 0.77 Pos Pred Value: 0.86 Neg Pred Value: 0.83 Leave One Out Cross Validation (LOOCV): AUROC = 0.85, Accuracy = 0.78

71 NAFLD F3-F4 vs. NAFLD F1-F2 N=114; NAFLD F1-F2 (N=80) & NAFLD F3-F4 (N=34) 5 variables were included: phospholipids, triacylglycerols, acyl carnitines, sphingolipids & sterols AUROC (se) 0.89 (0.03) Accuracy 0.83 Sensitivity: 0.62 Specificity: 0.93 Pos Pred Value: 0.78 Neg Pred Value: 0.85 Leave One Out Cross Validation (LOOCV): AUROC = 0.86, accuracy = 0.81

72 Conclusions It is feasible to detect changes in the circulating lipidome that are associated with disease progression in NAFLD. Three different metabolomic signatures have been found that discriminate between: NAFLD vs. controls NAFLD with fibrosis vs. NAFLD without fibrosis NAFLD F3-F4 vs. NAFLD F1-F2

73 The Lipidomic Signature of Disease Progression in NAFLD Questions / Comments? Puneet Puri, MD Virginia Commonwealth University

A precision medicine approach to comprehensive NAFLD diagnosis via metabolomics-based liquid biopsy

A precision medicine approach to comprehensive NAFLD diagnosis via metabolomics-based liquid biopsy International Workshop on NASH Biomarkers May 5-6 2017, Washington D.C. Pablo Ortiz, MD, PhD (OWL CEO)