This document discusses non-invasive biomarkers for non-alcoholic steatohepatitis (NASH). It provides an agenda for a meeting on this topic, including discussions of the need for non-invasive biomarkers in NASH, current and future methods for non-invasive diagnosis of NASH and liver fibrosis, leveraging genomics in biomarker development, and the strategic use of non-invasive testing in NASH drug development and clinical practice. Specific non-invasive tests are discussed, such as blood-based biomarkers, imaging techniques, and genomic and proteomic profiling methods for assessing liver fat, inflammation, fibrosis and other aspects of NASH.
NAFLD is a vast topic and recently gaining a lot of importance. Fatty liver, NASH, are other topics discussed here. sleissenger, sheila sherlock and Harrisons are used for reference
Slides From Hot Topics in NASH:New Strategies for the Diagnosis of NASH.2019hivlifeinfo
Slides From Hot Topics in NASH: New Strategies for the Diagnosis of NASH
xpert faculty present key data on current and emerging NASH treatment options for your patients.
Rita Basu, MD
Wing-Kin Syn, MBChB, PhD, FACP, FRCP
Format: Microsoft PowerPoint (.ppt)
File Size: 3.84 MB
Released: February 11, 2019
Nonalcoholic Steatohepatitis (NASH) is a type of NAFLD (Nonalcoholic Fatty Liver Disease) which is characterized by inflammation and buildup of excess of fat in the liver. NASH is considered to be strongly associated with insulin resistance, central obesity, reduced glucose tolerance, type II diabetes mellitus (T2DM), arterial hypertension, and hypertriglyceridemia.The exact cause of the NASH has not been illuminated because generally it not same for every patient.
Emergence of noninvasive diagnostic methods for identifying patients (and stratify the NAFLD and NASH populations based on severity and risk of progression) would be a key driver, with significant impact on evolving the market for NASH therapies.
Differences in method of assessment of NASH (Ultrasound, MRI, Liver biopsy, non-invasive tests leads to profound variation in prevalence rates. We estimated that diagnosed NASH prevalence will reach 18 Million by 2027at a compound growth rate of 2.82% for seven major markets i.e. US, EU5 and Japan.
In the United States, we found that NASH Fibrosis (F0) and NASH Fibrosis-1 (F1) accounts for approximately 67% and 13% cases of total NASH respectively.
NAFLD is a vast topic and recently gaining a lot of importance. Fatty liver, NASH, are other topics discussed here. sleissenger, sheila sherlock and Harrisons are used for reference
Slides From Hot Topics in NASH:New Strategies for the Diagnosis of NASH.2019hivlifeinfo
Slides From Hot Topics in NASH: New Strategies for the Diagnosis of NASH
xpert faculty present key data on current and emerging NASH treatment options for your patients.
Rita Basu, MD
Wing-Kin Syn, MBChB, PhD, FACP, FRCP
Format: Microsoft PowerPoint (.ppt)
File Size: 3.84 MB
Released: February 11, 2019
Nonalcoholic Steatohepatitis (NASH) is a type of NAFLD (Nonalcoholic Fatty Liver Disease) which is characterized by inflammation and buildup of excess of fat in the liver. NASH is considered to be strongly associated with insulin resistance, central obesity, reduced glucose tolerance, type II diabetes mellitus (T2DM), arterial hypertension, and hypertriglyceridemia.The exact cause of the NASH has not been illuminated because generally it not same for every patient.
Emergence of noninvasive diagnostic methods for identifying patients (and stratify the NAFLD and NASH populations based on severity and risk of progression) would be a key driver, with significant impact on evolving the market for NASH therapies.
Differences in method of assessment of NASH (Ultrasound, MRI, Liver biopsy, non-invasive tests leads to profound variation in prevalence rates. We estimated that diagnosed NASH prevalence will reach 18 Million by 2027at a compound growth rate of 2.82% for seven major markets i.e. US, EU5 and Japan.
In the United States, we found that NASH Fibrosis (F0) and NASH Fibrosis-1 (F1) accounts for approximately 67% and 13% cases of total NASH respectively.
Nonalcoholic Steatohepatitis (NASH) also known as “silent disease” is a type of fatty liver disease, which mainly affects people with diabetes and obesity. Symptoms of NASH are found among all demographics (from children to adults); however, they are more prevalent in younger people. Corner stage of cirrhosis is a form of NASH that can be reversed with proper medication. Moreover, most of the NASH specific pharmaceutical solution are in clinical trial phase
Nonalcoholic steatohepatitis (NASH) is liver inflammation and damage caused by a buildup of fat in the liver. The report includes detailed competitive landscape of the global nonalcoholic steatohepatitis market and an analysis of Porter’s five forces model for the NASH market has also been included.
Validation of an Off-the-Shelf, Diet-Induced NASH Mouse Model using Digital Whole Slide Scanning of Liver Tissue and Artificial Intelligence-Enabled, Quantitative Histopathological Analysis
Clinical Impact of New NAFLD/NASH Data From San Francisco 2018hivlifeinfo
Expert faculty summarize key NAFLD/NASH studies from this important annual conference. Use these slides to review data on noninvasive screening, clinical outcomes, emerging treatments.
Ira M. Jacobson, MD
Philip N. Newsome, PhD, FRCPE
Format: Microsoft PowerPoint (.ppt)
File Size: 421 KB
Released: December 3, 2018
Genomics Solutions - Single Target to Whole Genome AnalysisCovance
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Covance, in partnership with Oracle, offers a full-service, validated, private cloud, single-tenancy solution based on Argus technology, which enables faster and better safety decisions. This automated and integrated solution allows for easy scientific querying and analytics, which improves the quality and efficiency of safety operations. It also enhances compliance with E2B exchange for expedited and periodic reporting, allowing the organization to conduct global case processing, which can scale to tens of thousands of annual cases.
Plant Metabolism Studies: Options for Plant CultivationCovance
Regulators across the world are concerned with ensuring that any residues left in or on a crop after application of a plant protection product (PPP), present minimal risk to the health of humans and animals. To achieve this, regulators need information on the identity of the residues and the levels of residues remaining in or on a crop, in order to assess dietary risk and set maximum residue levels (MRLs). The testing approaches used are harmonized across most countries worldwide, focusing on the Organization for Economic Co-operation and Development (OECD) Test Guidelines (TGs) for pesticide residue chemistry. This e-book paper focuses on the laboratory-based plant cultivation methods that underlie the success of OECD crop metabolism studies, namely TG 501 and 502.
Basavarajeeyam is a Sreshta Sangraha grantha (Compiled book ), written by Neelkanta kotturu Basavaraja Virachita. It contains 25 Prakaranas, First 24 Chapters related to Rogas& 25th to Rasadravyas.
Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
Muktapishti is a traditional Ayurvedic preparation made from Shoditha Mukta (Purified Pearl), is believed to help regulate thyroid function and reduce symptoms of hyperthyroidism due to its cooling and balancing properties. Clinical evidence on its efficacy remains limited, necessitating further research to validate its therapeutic benefits.
Local Advanced Lung Cancer: Artificial Intelligence, Synergetics, Complex Sys...Oleg Kshivets
Overall life span (LS) was 1671.7±1721.6 days and cumulative 5YS reached 62.4%, 10 years – 50.4%, 20 years – 44.6%. 94 LCP lived more than 5 years without cancer (LS=2958.6±1723.6 days), 22 – more than 10 years (LS=5571±1841.8 days). 67 LCP died because of LC (LS=471.9±344 days). AT significantly improved 5YS (68% vs. 53.7%) (P=0.028 by log-rank test). Cox modeling displayed that 5YS of LCP significantly depended on: N0-N12, T3-4, blood cell circuit, cell ratio factors (ratio between cancer cells-CC and blood cells subpopulations), LC cell dynamics, recalcification time, heparin tolerance, prothrombin index, protein, AT, procedure type (P=0.000-0.031). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and N0-12 (rank=1), thrombocytes/CC (rank=2), segmented neutrophils/CC (3), eosinophils/CC (4), erythrocytes/CC (5), healthy cells/CC (6), lymphocytes/CC (7), stick neutrophils/CC (8), leucocytes/CC (9), monocytes/CC (10). Correct prediction of 5YS was 100% by neural networks computing (error=0.000; area under ROC curve=1.0).
Knee anatomy and clinical tests 2024.pdfvimalpl1234
This includes all relevant anatomy and clinical tests compiled from standard textbooks, Campbell,netter etc..It is comprehensive and best suited for orthopaedicians and orthopaedic residents.
Basavarajeeyam is an important text for ayurvedic physician belonging to andhra pradehs. It is a popular compendium in various parts of our country as well as in andhra pradesh. The content of the text was presented in sanskrit and telugu language (Bilingual). One of the most famous book in ayurvedic pharmaceutics and therapeutics. This book contains 25 chapters called as prakaranas. Many rasaoushadis were explained, pioneer of dhatu druti, nadi pareeksha, mutra pareeksha etc. Belongs to the period of 15-16 century. New diseases like upadamsha, phiranga rogas are explained.
Adv. biopharm. APPLICATION OF PHARMACOKINETICS : TARGETED DRUG DELIVERY SYSTEMSAkankshaAshtankar
MIP 201T & MPH 202T
ADVANCED BIOPHARMACEUTICS & PHARMACOKINETICS : UNIT 5
APPLICATION OF PHARMACOKINETICS : TARGETED DRUG DELIVERY SYSTEMS By - AKANKSHA ASHTANKAR
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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
Claudia Filozof, MD, PhD
► 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
3 | Non-Alcoholic Steatohepatitis
Claudia Filozof, MD, PhD
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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
4 | Non-Alcoholic Steatohepatitis
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
5 | Non-Alcoholic Steatohepatitis
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
6 | Non-Alcoholic Steatohepatitis
*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
7 | Non-Alcoholic Steatohepatitis
Marge Connelly, PhD
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| Non-Alcoholic Steatohepatitis8
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)
9 | Non-Alcoholic Steatohepatitis
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
10 | Non-Alcoholic Steatohepatitis
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
11 | Non-Alcoholic Steatohepatitis
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
12 | Non-Alcoholic Steatohepatitis
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
13 | Non-Alcoholic Steatohepatitis
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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NASH in a Genomic Context
15 | Non-Alcoholic Steatohepatitis
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
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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
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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
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18
Gut. 2015 May ; 64(5): 800–812
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Considerations for Genomic Profiling
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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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Strategic Use of Non-Invasive Testing
for NASH Drug Development
Claudia Filozof, MD, PhD
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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
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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
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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
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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
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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
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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
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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
• Non-invasive fibrosis estimation:**
- FIB4 >2.67
- APRI >1.5
- NFS >0.675
• Fibroscan® >11 kPa *
Intermediate-risk profile
• BMI >29.9
• Age >40
• Multiple features metabolic syndrome
• Non-invasive fibrosis estimation:**
- 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
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Claudia Filozof, MD, PhD
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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Thank you for attending!
37 | Non-Alcoholic Steatohepatitis
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