Lipid and Bile Acids as NAFLD-Related Biomarkers

Puneet Puri, MBBS, MDDivision of Gastroenterology, Hepatology and Nutrition

Virginia Commonwealth University, Richmond, VA

No Disclosures

1st International Workshop on NASH BiomarkersWashington DC, USAFriday 29th April 2016

Spectrum of Nonalcoholic Fatty Liver Disease (NAFLD)

BIOMARKERS

• Who is at risk?

• How can we diagnose?

• Can we differentiate disease phenotypes?

• Can we assess risk of progression?

• How does it change with change in disease condition?

• How can it guide prognosis?

• How do these relate to therapeutic intervention?

Overview of Lipid Metabolism in NAFLD

Cohen JC et al. Science 332, 1519 (2011)

Overview of Lipid Metabolism in NAFLD

1

3

2

1

3

2

Cohen JC et al. Science 332, 1519 (2011)

Hepatic Lipidome in NASHLow PCHigh LyPCHigh Free Cholesterol

Puri P et al. Hepatology. 2007 Dec;46(4):1081-90.

A Lipidomic Analysis of Nonalcoholic Fatty Liver Disease

The Plasma Lipidomic Signature of Nonalcoholic Steatohepatitis

Puri P et al. Hepatology. 2009 Dec;50(6):1827-38.

NAFLD is associated with increased de novo lipogenesisA 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. 2009 Dec;50(6):1827-38.

NAFLD is associated with increased de novo lipogenesisA 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. 2009 Dec;50(6):1827-38.

Docosahexaenoic acid (DHA, 22:6n3) to docosapentaenoic

acid (DPA, 22:5n3) ratio

Plasmalogen levels

NAFLD is associated with

peroxisomal dysfunction

Puri P et al. Hepatology. 2009 Dec;50(6):1827-38.

NAFLD is Associated with Increased Inflammatory and Oxidative Stress Related Eicosanoid Metabolites

Puri P et al. Hepatology. 2009 Dec;50(6):1827-38.

Puri P et al. Hepatology. 2009 Dec;50(6):1827-38.

INFLAMMATION

LIPOGENESIS

OXIDATIVE STRESS

Circulating Lipidome Model for NAFLD Pathophysiology

Circulating Oxidized Fatty Acids (OxFA) Levels Are Markedly Increased and Relate to Disease Severity in NASH Patients

J. Lipid Res. 2010. 51: 3046–3054

Circulating oxNASH Score Can Predict NASH

0.83 (95% CI: 0.73, 0.93)0.74 (95% CI: 0.6, 0.88)

oxNASH: 13-HODE/LA ratio, age, BMI, and AST J. Lipid Res. 2010. 51: 3046–3054

Higher oxNASH Levels Increase the Risk of NASH

Biomarkers of NAFLD progression

Common analytes between liver and plasma J. Lipid Res. 2015. 56: 722–736.

Plasma Lipidome Can Distinctly Identify NAFL and NASH

J. Lipid Res. 2015. 56: 722–736.

NAFL/ Steatosis

NASH

Plasma and Hepatic Lipidomic Biomarkers of NAFLD Progression

Disease Progression in NAFLD – Training Cohort

“The Lipidomic Signature of Disease Progression in Non-alcoholic Fatty Liver Disease (NAFLD)” AASLD 2015

Metabolites & NAFLD Progression

22 plasma metabolites associated with

NAFLD progression

“The Lipidomic Signature of Disease Progression in Non-alcoholic Fatty Liver Disease (NAFLD)”

AASLD 2015

Lipid Metabolites Associated WithNAFLD Progression

DECREASE WITH NAFLD PROGRESSIONINCREASE WITH NAFLD PROGRESSION

AASLD 2015

Lipid Metabolites & NAFLD progression

Previous metabolites associatedwith NAFLD progression wereevaluated in the new cohort.

The same trend was obtainedfor all of them.

EASL 2016

Linear regression modelsThree linear regression models have been built comparing:

• NAFLD (all samples) vs. controls

• NAFLD with and without fibrosis

• NAFLD F3-F4 vs. NAFLD F1-F2

All the models has been weighted due to the difference in sample size of thegroups.

Leave-one-out cross validation (LOOCV) of the models has been performed.

CONTROL NAFLD F1-F2 F3-F4

EASL 2016

NAFLD vs. ControlsN=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: 0.97Specificity: 0.61

Pos Pred Value: 0.95

Neg Pred Value: 0.74

Leave One Out Cross Validation (LOOCV): AUROC = 0.91, Accuracy = 0.92 EASL 2016

NAFLD with and without Fibrosis

Leave One Out Cross Validation (LOOCV): AUROC = 0.85, Accuracy = 0.78

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: 0.90Specificity: 0.77

Pos Pred Value: 0.86

Neg Pred Value: 0.83

NAFLD F3-F4 vs. NAFLD F1-F2

Leave One Out Cross Validation (LOOCV): AUROC = 0.86, accuracy = 0.81

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: 0.62Specificity: 0.93

Pos Pred Value: 0.78

Neg Pred Value: 0.85

Bile Acids in NAFLD

Rinella and Sanyal. Nature Reviews Gastroenterology & Hepatology 12, 65–66 (2015)

• Obeticholic acid: Bile acid (BA) derivative of 6-ethylchenodeoxycholic acid • Potent activator of the farnesoid X nuclear receptor (FXR)• Improved histological features of NASH• Its long-term benefits and safety need further assessment

Neuschwander-Tetri BA et al, Lancet 2015

Plasma Lipid MetabolitesNASH vs. NAFL vs. Control

Bile Acid

Long chain fatty acids

Sterol/Steroid

Essential fatty acid

NASH NAFL Control

Fatty acid, MonohydroxyFatty acid, Dicarboxylate

Fatty acid metabolism

Carnitine metabolismGlycerolipid metabolism

Lysolipid

Sphingolipid

Unpublished data

Plasma Lipid Metabolites NASH vs No NASH

Bile Acid

Long chain fatty acid

Sterol/Steroid

NASH No NASH

Fatty acid, Dicarboxylate

Fatty acid metabolismInositol metabolism

Glycerolipid metabolism

Lysolipid

Sphingolipid

Carnitine metabolism

Fatty acid, Monohydroxy

Endocannabanoid

Unpublished data

Training Cohort Validation Cohort

Fecal Bile Acid Metabolome in NAFLD

Random Forest Classification Features ranked by their respective contribution to classification accuracy

EASL 2015

Training CohortFeatures ranked by their contributions to classification accuracy

Fecal Glycodeoxycholate is Significantly Higher in NASH

EASL 2015

Fecal Glycodeoxycholate in Validation Cohort Significantly Higher in NASH

Validation Cohort EASL 2015

Conclusion

• Circulating lipidome and bile acids can differentiate controls from NAFLD, and can separate NAFL from NASH

• Circulating lipidome is associated with disease progression in NAFLD

• Three different lipidomic signatures can discriminate between:• NAFLD vs. controls

• NAFLD with and without fibrosis

• NAFLD F3-F4 vs. NAFLD F1-F2

• Fecal glycodeoxycholate is significantly higher in both training and validation cohorts in NASH

Future Directions

• Diagnosis: Pre-disease to disease

• Markers for fibrosis and disease progression

• Prognosis

• Predictors of response and failure to therapy