non invasive biomarkers in nash (non-alcoholic steatohepatitis) webinar slides

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NON-INVASIVE BIOMARKERS IN NASH (NON-ALCOHOLIC STEATOHEPATITIS)

Latest Advances and Potential Clinical Applications

@Covance

Non-alcoholic #Steatohepatitis

#NASH

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Agenda

► The Urgent Need for Non-Invasive Biomarkers in NASH

Claudia Filozof, MD, PhD

► Non-invasive Diagnosis of NASH and Liver Fibrosis: Present and Future

Marge Connelly, PhD, MBA

► Leveraging Genomics in NASH Biomarker Development

Mark Parrish, BS

► Strategic Use of Non-Invasive Testing for NASH Drug Development


► Role of Non-Invasive Biomarkers in Clinical Practice

Arun Sanyal, MD

► Q&A

2 | Non-Alcoholic Steatohepatitis

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The Urgent Need for Non-Invasive Biomarkers in NASH



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Biomarker

► A characteristic that is objectively measured and evaluated as an indication of normal biologic processes, pathogenic processes or pharmacologic responses to a therapeutic intervention

► Surrogate biomarker or endpoint

A biomarker intended to substitute for a clinical endpoint


NIH Definitions Working Group. Biomarkers and Surrogate Endpoints. 2000

J K Aronson Br J Clin Pharmacol 2005

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Liver Biopsy

► Remains the gold standard test for NASH diagnosis, grading and staging


Several limitations

– Sampling error

Length: >15 mm long, 16 gauge needle are recommended

– Intra- and interobserver reading variability

Reduced when performed by a NASH expert pathologist

– Invasive, unpleasant for the patient

– Procedure-related morbidity and mortality

– Relatively high cost

Liver

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Non-Invasive Biomarkers in NASH: Methodological considerations

► Liver biopsy: imperfect reference standard

► Taking into account a range of accuracies of the biopsy, even in the best possible scenario, an AUROC* >0.90 might not be achieved for a perfect marker of liver disease

► Spectrum bias: The AUROC can vary based on the prevalence of each stage of fibrosis


*Area under the receiver operator characteristic curve

AUROC curve of ELF predicting stages 0,1 Vs 2-6 in NAFLD

cohort (none or mild fibrosis from significant fibrosis Ishak

classification)

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Non-Invasive Diagnosis of NASH and Liver Fibrosis: Present and Future


Marge Connelly, PhD

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| Non-Alcoholic Steatohepatitis 8

Fibronectin

Hyaluronic acid (HA)

Type IV collagen S

Procollagen type III N-terminal Peptide (PIIINP)

Tissue inhibitor of metalloproteinase 1 (TIMP-1)

Cytokines: TNF-α, IL-1β, IL-6, IL-8, IFNγ, TGFβ

Adipokines: Adiponectin, Leptin, Resistin

Acute phase reactants: hsCRP, GlycA

Chemoattractants: MCP-1

Ferritin, Soluble CD14

Present Biomarkers of NAFLD

Alanine aminotransferase (ALT)

Aspartate aminotransferase (AST)

Alkaline phosphatase (ALP)

Gamma-glutamyl-transpeptidase (GGT)

Acute phase reactants: α1-antitrypsin,

ceruloplasmin, haptoglobin, GlycA

Albumin, Lipid panel, Platelet count

Measures of insulin resistance

Malondialdehyde, TBARS, Oxidized LDL

Cytokeratin-18 (CK-18) fragments

Ferritin

1. Adapted from Fitzpatrick et al., Noninvasive biomarkers in NAFLD World, J Gastroenterol 2014;20(31):10851-10863.

2. Armutcu et al., Adv in Clin Chem 2013;61:67-125.

Oxidative Stress

and Apoptosis

Fibrosis

Inflammation

Hepatocyte Function

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Diagnosis of NASH

► Liver function tests: ALT, AST, GGT, albumin

► Measures of insulin resistance (HOMA-IR, adiponectin)

► NASH diagnostic: cleaved and intact CK-18, adiponectin, resistin (AUROC 0.70-0.85)

► NASH diagnostic panel: gender, BMI, diabetes, triglycerides, cleaved and intact CK-18 (AUROC 0.81)

► ION: Index of NASH >55 (AUROC 0.88)

Limitations

► Need more rigorous clinical validation (e.g. larger, more clearly defined study populations without spectrum bias)


1. Buzzetti et al., Int J Endocrinol 2015; 343828. 2. Otgonsuren et al., Hepatol 2014;29:2006-2013.

3. Armutcu et al., Adv in Clin Chem 2013;61:67-125. 4. Yilmaz et al., Curr Drug Targets 2013;14:1357-1366.

5. Pearce et al., Biomarker Res 2013:1:7-17. 6. Image adapted from Mayo Foundation for Medical Education

and Research, www.mayoclinic.org.

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NASH FibroSure Test

► Includes 10 biomarkers in combination with age, gender, BMI

SteatoTest: Marker of hepatic steatosis grade S0-S3 (0.00-1.00)

Steatosis score >0.5, sensitivity= 71%, specificity= 72% for identification of steatosis1

NASHTest: Diagnostic assessment of the presence of NASH

N0 = No NASH, N1 = Borderline NASH, N2 = NASH per the Kleiner classification2

Prediction of NASH, sensitivity = 88%, specificity = 50% (AUROC 0.69-0.83)3,4

FibroTest: Quantitative surrogate fibrosis marker (0.00-1.00)

Corresponds to Metavir F0-F4 fibrosis staging

Fibrosis score of >0.3, sensitivity = 83%, specificity = 78% for ≥F3 (AUROC 0.88)4,5


FibroSure Content

Alpha-2-macroglobulin Alanine transaminase (ALT)

Haptoglobin Aspartate aminotransferase (AST)

Apolipoprotein A1 Total cholesterol

γ-glutamyl transpeptidase (GGT) Triglycerides

Total bilirubin Fasting glucose

Widely used ~100,000 FibroSure Tests were conducted at LabCorp in 2014

1. Poynard et al., Comp Hepatol, 2005;4:10. 2. Kleiner et al., Hepatol, 2005;41(6):1313-1321. 3. Poynard et al.,

41st Annual EASLD Meeting 2006;Abstract 86. 4. Buzzetti et al., Int J Endocrinol 2015;343828. 5. Ratziu et al.,

BMC Gastroenterol, 2006;6:6.

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Diagnosis of Liver Fibrosis

► NFS: NAFLD Fibrosis Score - age, BMI, IFG/diabetes, AST/ALT ratio, platelet count, albumin (AUROC 0.82-0.88)

► Hepascore: Bilirubin, GGT, HA, α2-macroglobulin, age, gender (AUROC 0.81)

► APRI: AST to platelet ratio index (AUROC 0.62-0.94)

► FIB-4 Index: Age, AST, ALT, platelet count (AUROC 0.87, 0.88)

► BARDI: BMI, AST/ALT ratio, diabetes, INR (AUROC 0.88)

Limitations

► Performance may be affected by morbid obesity

► Well validated in patients with chronic viral hepatitis, less validated in NAFLD

► Assay performance better for detecting significant than moderate fibrosis

► May also reflect extra-hepatic fibrosis


1. EASL-ALEH Clinical Practice Guidelines: Non-invasive tests for evaluation of liver disease severity and prognosis.

J Hepatol 2015;63:237-264. 2. Shah et al., Clin Gastroenter Hepatol 2009;7:1104-1112. 3. Buzzetti et al.,

Int J Endocrinol 2015; 343828. 4. Image adapted from Mayo Foundation for Medical Education and Research,

www.mayoclinic.org.

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Enhanced Liver Fibrosis (ELF) Score

► 3 direct biomarkers of fibrosis combined into one score: Hyaluronic acid

Procollagen III N terminal peptide (PIIINP)

Tissue inhibitor of metalloproteinase 1 (TIMP1)

► Good at diagnosing severe fibrosis in patients with chronic hep B, C, HIV

► Not as much validation in subjects with NAFLD

► Significant overlap with normal ranges, which may confound interpretation of results in mild to moderate fibrosis range

► Used in NASH trials as a surrogate marker for fibrosis; preliminary results encouraging


1. ELF Test is trademarked by Siemens Healthcare Diagnostics, Inc. Licensed for use outside of US; not currently

available in the US. 2. Yoo et al, Liver Int. 2013;33:706-713.

ELF Score Severity of Liver Fibrosis Fibrosis Stage AUROC

< 7.7 None to mild ≥F2 0.82

≥ 7.7 - < 9.8 Moderate ≥F3 0.90

≥ 9.8 Severe ≥F4 0.87

≥ 11.3 Cirrhosis

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Future Assays May Include NMR Biomarkers of Insulin Resistance, NASH and Liver Fibrosis

► LP-IR, lipoprotein insulin resistance index1,2

Multivariable algorithm, 6 lipoprotein parameters related to insulin resistance

Validated in hyperinsulinemic-euglycemic clamp studies and multiple clinical cohorts

Simple, inexpensive way to assess insulin resistance in large clinical studies

► NASH specific analytes3

VLDL size and small LDL particle number

► Liver fibrosis specific analytes3,4

Small VLDL particle number

Branched chain amino acid (BCAA) concentrations associated with reduced liver function

► GlycA, glycoprotein marker of inflammation5-8

Reduced with later stage liver fibrosis and cirrhosis


1. Shalaurova et al. Met Syn Rel Dis 2014;12(8):422-429. 2. Mackey et al. Diab Care 2015;38(4):628-636. 3. Jiang et al. Liver Int 2016; doi: 10.1111/liv.13076.

4. Cheng et al., PLoS One 2015;10(10);e0138889. 5. Otvos et al., Clin Chem 2015;61(5):714-23. 6. Akinkuolie, et al., JAHA 2014;3(5):e001221. 7. Akinkuolie et

al., ATVB 2015;35(6):1544-50. 8. Sands et al, Amer J Gastroenterology 2015;110:159-169.

BCAA

VLDL

particle

number

(VLDL-P)

Large VLDL

Medium VLDL

Small VLDL

IDL

Medium LDL

Small LDL

Large HDL

Medium HDL

Small HDL

LIPOPROTEIN SUBCLASS PARTICLE NUMBERS

Positive Association Negative Association

LDL

particle

number

(LDL-P)

HDL

particle

number

(HDL-P)

VLDL Size

LDL Size

HDL Size

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Leveraging Genomics in NASH Biomarker Development

Mark Parrish, BS


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NASH in a Genomic Context


Underlying every protein or phenotype is a

genetic component

Genes influence proteins and each other

The genomics toolbox is expanding and

highly flexible

Genomics has influence at every level of the

progression of NASH

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PNPLA3 Gene with the strongest association with NASH

Genotype increases odds for NASH and HCC

Associated with all aspects of progression

Higher prevalence of disease-causing genotype in some populations

TM6SF2

Increased risk for NASH

Associated with ALT/AST levels

Involved in hepatic triglyceride secretion

Other genes of metabolism

ADIPOQ, LEPR, INS-1, NCAN, FDFT1

Increase likelihood of other liver diseases and comorbidities

Strength of association varies, highly dependent on the

phenotype studied and population

Genes Associated with NASH


Biochimica et Biophysica Acta 1812 (2011) 1557–1566

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cfDNA High levels of cfDNA are correlated to various liver indications

cfDNA is nonspecific to NASH

May indicate later stages of liver disease, HCC

Microbiome Profiling

The composition of gut/stool bacteria correlates with

NASH status

NASH patients tend to have higher levels of alcohol-producing

bacteria

Emerging/Exploratory DNA Biomarkers


Adv Anthro (2012) Vol.2, No.4, 214-220

Hepatology (2013) Vol. 57, No. 2

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miRNAs are signaling molecules

miRNAs regulate intracellular gene expression

mRNAs are also packaged and released as signaling molecules

Sensitive markers of liver health

miR-122 is highly indicative to liver injury • Viral, alcohol or chemical

Regulates lipid metabolism genes

Localized to the lipid droplets and cell membranes

Surrogate markers of NAFLD and NASH

miR-122 is not sufficient to distinguish NASH

miR-192 and miR-375 are also increased in NASH serum

miroRNA Profiling


Gut. 2015 May ; 64(5): 800–812

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Considerations for Genomic Profiling


You can’t analyze what you don’t collect

New techniques are always evolving

Cost of collection and storage is cheaper than repeating a study

Consider IRB requirements for genetic testing

Clear use of samples needs to be identified up front

Don’t assume broad use, especially across geographies

Consider appropriate collection matrix

Certain collection agents limit future use

Timing and storage is critical

RNA/miRNA expression is dynamic

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Sp

ecif

ic

Pre

dic

tive

No

n-S

pecif

ic

Microbiome

cfDNA

PNPLA3

TM6SF2

miR-122

miR-192, miR-375

Healthy

liver

15-30% NAFLD 12-40% NASH 15-25% Cirrhosis ~7%

50%

Liver transplant/death

Hepato-cellular

carcinoma

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Strategic Use of Non-Invasive Testing for NASH Drug Development



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Imaging

Liver Fat

► Ultrasound low sensitivity ( <20%-30% of liver fat)

► Magnetic resonance-based

MRI-PDFF / MRS

Multiscan

Liver Stiffness

► Vibration-controlled transient elastography (VCTE)

► US elastography (pSWE or ARFI and 2D-SWD)

► Magnetic resonance elastography


MRI-PDFF: Magnetic resonance imagins-protocol density fat fraction

MRS: Magnetic resonance spectroscopy

pSWE: point shear wave elastography-ARFI: acoustic radiation force impulse imaging

2D-SWD 2D-shear wave elastography

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Non-Invasive Biomarkers: Utility in Clinical Development

► Enrich target population: In a POC study when a population of biopsy-confirmed NASH patients may not be feasible

► Potential endpoints in proof of concept trials/facilitate decision making during interim analysis

► Identification of potential progression to cirrhosis

In Phase III/IV trials: Fibroscan, MRE or other markers of fibrosis can help identify patients with cirrhosis prior to a liver biopsy confirmation


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1-Enrich Target Population 2-Endpoints in POC Trials


1-Target Population:

Adult (≥18 years) with fatty liver AND ► T2DM

► Metabolic syndrome

► High ALT levels

► Other serum biomarkers > predefined threshold

► Multiscan with LIF > 3

2-Endpoints: Changes in liver

fat by MRI, changes in ALT

and other biomarkers

(metabolic/ inflammation/

fibrosis)

weeks

Placebo=XX

R

N XX

N=XX dose 3

-4 -2 0 12/16/24

Screening

period Run-in

N=XX dose 2

N=XX dose 1

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Non-Invasive Biomarkers Can Help in Decision Making During Interim Analysis in Protocols Using an Adaptive Design

Population:

• Adult (≥18 years) with biopsy-confirmed NASH (within 90 to 180 days)

• NAS ≥ 4

• Enrich the population with a minimum number of patients with F2/F3

N=XX dose 2

N=XX placebo

weeks

N=XX dose 3

-4 -2 0 48/52

Screening

period Run-in

IA when X% of the population completes week 12/16-24:

futility/efficacy criteria based on changes in liver fat by MRI,

changes in ALT and other non-invasive biomarkers facilitate

decision making and potential adaptations

N=XX dose 1

Placebo=XX


R

N XX

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Non-Invasive Biomarkers Can Help Identify Patients with Compensated Cirrhosis in a Long-Term Outcome Trial

R N XX

N=XX placebo

N=XX dose 3

-4 -2 0 72 months

N=XX Dose X

12 24 36 48 60

Fibroscan, MRE, biomarkers of fibrosis for early identification of progression to F4


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Limitations Of Non-Invasive Biomarkers

► Limited data for prediction of treatment response

Resolution of or improvement in NASH (inflammation/ballooning)

Improvement in one stage of fibrosis


Transient elastography

Requires a dedicated device

Affected by obesity, ascites, operator experience

False positive in case of acute hepatitis, extra hepatic cholestasis, liver congestion, food intake

and excessive alcohol intake

Unable to discriminate between intermediate stages of fibrosis

MRE

Requires MRI facility

Not applicable in case of iron overload

Time-consuming and high cost

Further validation warranted

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Role of Non-Invasive Biomarkers in Clinical Practice

Arun Sanyal, MD


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The Clinician’s Perspective

Population at risk

Symptoms or

accidental finding

Progression to HCC

End-stage liver disease

Ignored Triaged for care

Lifestyle

Vit E/TZD

clinical trials

DEATH OR OLT

LARGELY IN

REALM OF

PRIMARY CARE


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Barriers to Better NASH-Related Clinical Care

► Awareness

► Lack of point-of-care diagnostics

► Lack of easy ways to risk stratify and triage subjects

► Lack of approved therapies

► Need for a liver biopsy to determine whether treatments are effective


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The Clinical Questions Involved in the Area of NASH

Clinical question Target population Provider population

Is NAFLD present? General population Primary care providers

Will it lead to

outcomes?

Those where NAFLD

present

Primary care providers

Diabetologists

Cardiovascular clinics

Is disease progressing,

stable or regressing?

Those with NAFLD Primary care, diabetologists,

GI-Hep, cardiovascular clinics

Is drug therapy

warranted?

Those with NAFLD and

at risk for outcomes

Primary care, diabetologists,

GI-Hep, cardiovascular clinics

What drug to choose? NASH with some fibrosis Hepatology, primary care,

diabetologists

How is the subject

responding?

NASH and fibrosis Hepatologists, GI, primary care,

diabetes


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Biomarker Qualification

► Define the clinical question and use

► Identify the population to be studied

► Validation:

biological plausibility

face validity

scale of measure

sensitivity to change

methodological quality controls

► Ability to predict the outcome of interest in rigorously designed trials


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What Will Make a Biomarker Useful for a Clinician?

► Validated to outcomes

► Biological plausibility

► Ease of use:

point of care trumps need to make a separate appointment

balance between ease of use versus accuracy

► Ability to guide actionable next step in clinical care

► Ability to reduce unnecessary testing, exposure to potentially harmful drugs

► Contribution of improving overall cost of clinical care


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CONCLUSION: What We Would Like the Care Flow to Look Like in the Future


If risk profile improves

and drugs can be stopped Worsening risk profile

outcomes

outcomes

Low-risk profile for outcomes High-risk profile

Population at risk

Intermediate

risk profile

Immediate intervention

Escalation of intervention

Low-risk interventions

Healthy living

Periodic monitoring

of risk vs Intervention

outcomes

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Rinella and Sanyal, Nature Reviews Gastroenterology and Hepatology In press 2016


Suspected NAFLD (Hepatic steatosis on imaging ± elevated serum ALT)

Exclude alternate causes of ↑ ALT

Evaluate alcohol consumption

Low-risk profile • BMI <29.9

• Age <40 years

• No T2DM or metabolic syndrome features

• Non-invasive fibrosis estimation:**

- FIB4 <1.3

- APRI < 0.5

- NFS < -1.455

• Fibroscan® <5 kPa *

High-risk profile • AST>ALT

• Platelets <150k


- FIB4 >2.67

- APRI >1.5

- NFS >0.675

• Fibroscan® >11 kPa *

Intermediate-risk profile • BMI >29.9

• Age >40

• Multiple features metabolic syndrome


- FIB4 :1.3-2.67

- APRI: 0.5-1.5

- NFS: - 1.455-0.675

• Fibroscan® 6–11 kPa *

Consider liver biopsy Follow patient and reassess

as risk factors evolve

Risk stratification for liver-related outcomes

Consider liver biopsy or

confirmatory testing for cirrhosis

such as MR elastography

Confirmation of NAFLD

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Panel Q&A



Senior Medical Director,

Cardiovascular/Metabolic

Covance

Margery A. Connelly, PhD, MBA Vice President,

Translational Research

LabCorp (LipoScience)

Mark L. Parrish, BS Associate Scientific

Director of Genomic

Solutions

Covance

Arun Sanyal, MD Executive Director,

Education Core

Center for Clinical and

Translational Research

Virginia Commonwealth

University, USA

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non invasive biomarkers in nash (non-alcoholic steatohepatitis) webinar slides

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