Polyunsaturated fatty acid metabolites as novel lipidomic biomarkers for noninvasive diagnosis of nonalcoholic steatohepatitis
2014; Elsevier BV; Volume: 56; Issue: 1 Linguagem: Inglês
10.1194/jlr.p055640
ISSN1539-7262
AutoresRohit Loomba, Oswald Quehenberger, Aaron M. Armando, Edward A. Dennis,
Tópico(s)Metabolomics and Mass Spectrometry Studies
ResumoLipotoxicity is a key mechanism thought to be responsible for the progression of nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH). Noninvasive diagnosis of NASH is a major unmet clinical need, and we hypothesized that PUFA metabolites, in particular arachidonic acid (AA)-derived eicosanoids, in plasma would differentiate patients with NAFL from those with NASH. Therefore, we aimed to assess the differences in the plasma eicosanoid lipidomic profile between patients with biopsy-proven NAFL versus NASH versus normal controls without nonalcoholic fatty liver disease (NAFLD; based on MRI fat fraction <5%). We carried out a cross-sectional analysis of a prospective nested case-control study including 10 patients with biopsy-proven NAFL, 9 patients with biopsy-proven NASH, and 10 non-NAFLD MRI-phenotyped normal controls. We quantitatively compared plasma eicosanoid and other PUFA metabolite levels between NAFL versus NASH versus normal controls. Utilizing a uniquely well-characterized cohort, we demonstrated that plasma eicosanoid and other PUFA metabolite profiling can differentiate between NAFL and NASH. The top candidate as a single biomarker for differentiating NAFL from NASH was 11,12-dihydroxy-eicosatrienoic acid (11,12-diHETrE) with an area under the receiver operating characteristic curve (AUROC) of 1. In addition, we also found a panel including 13,14-dihydro-15-keto prostaglandin D2 (dhk PGD2) and 20-carboxy arachidonic acid (20-COOH AA) that demonstrated an AUROC of 1. This proof-of-concept study provides early evidence that 11,12-diHETrE, dhk PGD2, and 20-COOH AA are the leading eicosanoid candidate biomarkers for the noninvasive diagnosis of NASH. Lipotoxicity is a key mechanism thought to be responsible for the progression of nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH). Noninvasive diagnosis of NASH is a major unmet clinical need, and we hypothesized that PUFA metabolites, in particular arachidonic acid (AA)-derived eicosanoids, in plasma would differentiate patients with NAFL from those with NASH. Therefore, we aimed to assess the differences in the plasma eicosanoid lipidomic profile between patients with biopsy-proven NAFL versus NASH versus normal controls without nonalcoholic fatty liver disease (NAFLD; based on MRI fat fraction 150 such metabolites and have used this approach to profile AA and other PUFAs as well as their metabolites in human plasma (15Dumlao D.S. Buczynski M.W. Norris P.C. Harkewicz R. Dennis E.A. High- throughput lipidomic analysis of fatty acid derived eicosanoids and N-acylethanolamines.Biochim. Biophys. Acta. 2011; 1811: 724-736Crossref PubMed Scopus (116) Google Scholar, 16Quehenberger O. Dennis E.A. The human plasma lipidome.N. Engl. J. Med. 2011; 365: 1812-1823Crossref PubMed Scopus (302) Google Scholar, 17Quehenberger O. Armando A.M. Brown A.H. Milne S.B. Myers D.S. Merrill A.H. Bandyopadhyay S. Jones K.N. Kelly S. Shaner R.L. et al.Lipidomics reveals a remarkable diversity of lipids in human plasma.J. Lipid Res. 2010; 51: 3299-3305Abstract Full Text Full Text PDF PubMed Scopus (905) Google Scholar). We have now applied this approach to analyze the plasma of NAFLD patients. The aim of this proof-of-concept study was to detect if plasma eicosanoid profiling can differentiate well-characterized patients with biopsy-proven NASH versus NAFL versus uniquely phenotyped normal controls by documenting liver fat content of 14 drinks per week in a man or >7 drinks per week in a woman. Approximately 10 g of alcohol equals one "drink" unit. One unit equals 1 ounce of distilled spirits, one 12 ounce beer, or one 4 ounce glass of wine. Secondary causes of hepatic steatosis included previous surgeries, bariatric surgery, total parenteral nutrition, short bowel syndrome, steatogenic medications, evidence of chronic hepatitis B as marked by the presence of Hepatitis B surface antigen in serum, evidence of chronic hepatitis C as marked by the presence of anti-Hepatitis C virus antibody (HCV) or HCV RNA in serum, evidence of other causes of liver disease (such as α-1-antitrypsin deficiency, Wilson disease, glycogen storage disease, dysbetalipoproteinemia, known phenotypic hemochromatosis, autoimmune liver disease, or drug-induced liver injury), or concomitant severe underlying systemic illness that in the opinion of the investigator would interfere with the study. A novel aspect of this study was the inclusion of a uniquely well-characterized non-NAFLD normal control group. Participants were classified as normal non-NAFLD by accurate hepatic fat quantification by MRI-PDFF-derived fat fraction of <5% (18Noureddin M. Lam J. Peterson M.R. Middleton M. Hamilton G. Le T.A. Bettencourt R. Changchien C. Brenner D.A. Sirlin C. et al.Utility of magnetic resonance imaging versus histology for quantifying changes in liver fat in nonalcoholic fatty liver disease trials.Hepatology. 2013; 58: 1930-1940Crossref PubMed Scopus (353) Google Scholar, 20Le T.A. Chen J. Changchien C. Peterson M.R. Kono Y. Patton H. Cohen B.L. Brenner D. Sirlin C. Loomba R. et al.Effect of colesevelam on liver fat quantified by magnetic resonance in nonalcoholic steatohepatitis: a randomized controlled trial.Hepatology. 2012; 56: 922-932Crossref PubMed Scopus (190) Google Scholar). Liver biopsy is unethical in normal individuals. Other noninvasive measures such as ultrasound and computed tomography are inaccurate and lack sensitivity especially at liver fat fraction between 1% and 10%. Therefore, MRI-PDFF was utilized in this study for accurate diagnosis of absence of hepatic steatosis. MRI-PDFF is highly accurate, sensitive, reproducible, and precise. The detailed description of MRI-PDFF protocol has been published previously (18Noureddin M. Lam J. Peterson M.R. Middleton M. Hamilton G. Le T.A. Bettencourt R. Changchien C. Brenner D.A. Sirlin C. et al.Utility of magnetic resonance imaging versus histology for quantifying changes in liver fat in nonalcoholic fatty liver disease trials.Hepatology. 2013; 58: 1930-1940Crossref PubMed Scopus (353) Google Scholar, 19Permutt Z. Le T.A. Peterson M.R. Seki E. Brenner D.A. Sirlin C. Loomba R. Correlation between liver histology and novel magnetic resonance imaging in adult patients with non-alcoholic fatty liver disease - MRI accurately quantifies hepatic steatosis in NAFLD.Aliment. Pharmacol. Ther. 2012; 36: 22-29Crossref PubMed Scopus (252) Google Scholar, 20Le T.A. Chen J. Changchien C. Peterson M.R. Kono Y. Patton H. Cohen B.L. Brenner D. Sirlin C. Loomba R. et al.Effect of colesevelam on liver fat quantified by magnetic resonance in nonalcoholic steatohepatitis: a randomized controlled trial.Hepatology. 2012; 56: 922-932Crossref PubMed Scopus (190) Google Scholar, 22Tang A. Tan J. Sun M. Hamilton G. Bydder M. Wolfson T. Gamst A.C. Middleton M. Brunt E.M. Loomba R. et al.Nonalcoholic fatty liver disease: MR imaging of liver proton density fat fraction to assess hepatic steatosis.Radiology. 2013; 267: 422-431Crossref PubMed Scopus (329) Google Scholar, 23Patel N.S. Peterson M.R. Brenner D.A. Heba E. Sirlin C. Loomba R. Association between novel MRI-estimated pancreatic fat and liver histology-determined steatosis and fibrosis in non-alcoholic fatty liver disease.Aliment. Pharmacol. Ther. 2013; 37: 630-639Crossref PubMed Scopus (90) Google Scholar, 24Loomba, R., Wolfson, T., Ang, B., Booker, J., Behling, C., Peterson, M., Valasek, M., Lin, G., Brenner, D., Gamst, A. 2014. Magnetic resonance elastography predicts advanced fibrosis in patients with nonalcoholic fatty liver disease: a prospective study. Hepatology. (Epub ahead of print). October 29, 2014; doi:10.1002/hep.27362.Google Scholar, 25Patel, N. S., Doycheva, I., Peterson, M. R., Hooker, J., Kisselva, T., Schnabl, B., Seki, E., Sirlin, C. B., Loomba, R. 2014. Effect of weight loss on MRI estimation of liver fat and volume in patients with nonalcoholic steatohepatitis. Clin. Gastroenterol. Hepatol. (Epub ahead of print). September 13, 2014; doi:10.1016/j.cgh.2014.08.039.Google Scholar). Inclusion criteria in the healthy (non-NAFLD) control group included 1) age greater than 18 years, 2) liver MRI-PDFF <5%, and 3) no history of known liver disease. Exclusion criteria included 1) age less than 18 years; 2) significant systemic illness; 3) inability to undergo MRI; and 4) evidence of possible liver disease, including any previous liver biopsy, positive hepatitis B surface antigen, hepatitis C viral RNA, or autoimmune serologies, α-1 antitrypsin deficiency, hemochromatosis genetic testing, or low ceruloplasmin. Plasma samples for lipidomic profiling were obtained within 90 days of the liver biopsy and MRI-PDFF for cases and controls, respectively. All plasma samples were stored at −80°C, thawed once, and immediately used for free fatty acid and eicosanoid isolation as described previously (15Dumlao D.S. Buczynski M.W. Norris P.C. Harkewicz R. Dennis E.A. High- throughput lipidomic analysis of fatty acid derived eicosanoids and N-acylethanolamines.Biochim. Biophys. Acta. 2011; 1811: 724-736Crossref PubMed Scopus (116) Google Scholar, 17Quehenberger O. Armando A.M. Brown A.H. Milne S.B. Myers D.S. Merrill A.H. Bandyopadhyay S. Jones K.N. Kelly S. Shaner R.L. et al.Lipidomics reveals a remarkable diversity of lipids in human plasma.J. Lipid Res. 2010; 51: 3299-3305Abstract Full Text Full Text PDF PubMed Scopus (905) Google Scholar). Briefly, 50 µl plasma was spiked with a cocktail of 26 deuterated internal standards (individually purchased from Cayman Chemicals, Ann Arbor, MI) and brought to a volume of 1 ml with 10% methanol. The samples were then purified by solid phase extraction on Strata-X columns (Phenomenex, Torrance, CA), using an activation procedure consisting of consecutive washes with 3 ml of 100% methanol followed by 3 ml of water. The eicosanoids were then eluted with 1 ml of 100% methanol, and the eluent was dried under vacuum, dissolved in 50 µl of buffer A [consisting of water-acetonitril-acetic acid, 60:40:0.02 (v/v/v)], and immediately used for analysis as follows: For free fatty acids analysis, 50 μl of plasma was spiked with deuterated fatty acid standards, and the free fatty acids were isolated by selective extraction with methanol and isooctane. The extracted fatty acids were derivatized and analyzed by gas chromatography and MS, as described (15Dumlao D.S. Buczynski M.W. Norris P.C. Harkewicz R. Dennis E.A. High- throughput lipidomic analysis of fatty acid derived eicosanoids and N-acylethanolamines.Biochim. Biophys. Acta. 2011; 1811: 724-736Crossref PubMed Scopus (116) Google Scholar). Eicosanoids in plasma were analyzed and quantified by LC/MS/MS as previously described (17Quehenberger O. Armando A.M. Brown A.H. Milne S.B. Myers D.S. Merrill A.H. Bandyopadhyay S. Jones K.N. Kelly S. Shaner R.L. et al.Lipidomics reveals a remarkable diversity of lipids in human plasma.J. Lipid Res. 2010; 51: 3299-3305Abstract Full Text Full Text PDF PubMed Scopus (905) Google Scholar, 26Quehenberger O. Yamashita T. Armando A.M. Dennis E.A. Palinski W. Effect of gestational hypercholesterolemia and maternal immunization on offspring plasma eicosanoids.Am. J. Obstet. Gynecol. 2011; 205: 156.e15-156.e25Abstract Full Text Full Text PDF Scopus (16) Google Scholar). Briefly, eicosanoids were separated by reverse-phase chromatography using a 1.7 μM 2.1 × 100 mm BEH Shield Column (Waters, Milford, MA) and an Acquity UPLC system (Waters). The column was equilibrated with buffer A, and 5 µl of sample was injected via the autosampler. Samples were eluted with a step gradient starting with 100% buffer A for 1 min, then to 50% buffer B (consisting of 50% acetonitril, 50% isopropanol, and 0.02% acetic acid) over a period of 3 min, and then to 100% buffer B over a period of 1 min. The LC was interfaced with an IonDrive Turbo V ion source, and mass spectral analysis was performed on a triple quadrupole AB SCIEX 6500 QTrap mass spectrometer (AB SCIEX, Framingham, MA). Eicosanoids were measured using electrospray ionization in negative ion mode and multiple reaction monitoring (MRM) using the most abundant and specific precursor ion/product ion transitions to build an acquisition method capable of detecting 158 analytes and 26 internal standards. The ionspray voltage was set at −4,500 V at a temperature of 550°C. Collisional activation of the eicosanoid precursor ions was achieved with nitrogen as the collision gas with the declustering potential, entrance potential, and collision energy optimized for each metabolite. Eicosanoids were identified by matching their MRM signal and chromatographic retention time with those of pure identical standards. Eicosanoids and free fatty acids were quantitated by the stable isotope dilution method. Briefly, identical amounts of deuterated internal standards were added to each sample and to all the primary standards used to generate standard curves. To calculate the amount of eicosanoids and free fatty acids in a sample, ratios of peak areas between endogenous metabolite and matching deuterated internal standards were calculated. Ratios were converted to absolute amounts by linear regression analysis of standard curves generated under identical conditions. The Chi-square (χ2) test was used for comparisons between categorical variables, and the t-test was used for comparisons between continuous variables. We examined differences in the plasma eicosanoid profiles between normal controls, patients with biopsy-proven mild NAFL, and patients with biopsy-proven NASH. Finally, we examined the diagnostic accuracy of nine biomarkers that yielded significant differences as biomarkers to differentiate NAFL from NASH. A two-tailed P value ≤0.05 was considered statistically significant. Statistical analyses were performed using the SAS statistical software package version 9.4 (SAS Inc., Cary, NC). This study included 19 patients with NAFLD (10 NAFL cases and 9 cases of NASH) and 10 non-NAFLD normal controls. The detailed baseline characteristics including demographics, BMI, biochemical tests, lipid profile, MRI-PDFF for controls, and liver biopsy data on patients with NAFLD are described in Table 1. Non-NAFLD controls were younger, had lower BMI, and had lower serum ALT, AST, GGT, and glucose and insulin levels as expected. Routine liver-related and metabolic tests did not significantly differ between NAFL versus NASH (Table 1), except that plasma triglycerides were marginally higher in patients with NASH. Compared with patients with NAFL, patients with NASH had more severe liver histology with a higher degree of steatosis, ballooning degeneration, lobular inflammation, and fibrosis.TABLE 1Baseline demographic, clinical, biochemical, and histologic characteristics of the patients in the study populationControls (n = 10)NAFL (n = 10)NASH (n = 9)Control versus NAFL PNAFL versus NASH PAge31.8 ± 15.6648.90 ± 14.0345.89 ± 12.940.0190.633Sex40% male44% male40% maleBMI24.73 ± 4.1729.49 ± 5.3929.59 ± 5.010.0410.966Laboratory dataPlatelet240,500 ± 48,808.58264,900 ± 53,371.76244,888.89 ± 52,312.630.3000.400WBC7.05 ± 1.907.18 ± 2.285.96 ± 0.870.8920.101Alk P71.9 ± 23.6585.70 ± 40.4278.78 ± 18.190.3670.638ALT16.7 ± 8.5161.10 ± 39.73104.33 ± 61.790.0060.053AST23.1 ± 8.7135.00 ± 12.5366.33 ± 32.690.0250.013D Bili0.12 ± 0.040.12 ± 0.040.12 ± 0.041.0000.628T Bili0.49 ± 0.300.53 ± 0.210.56 ± 0.250.7320.763GGT18.8 ± 19.5246.20 ± 24.0372.89 ± 38.470.0120.067Glucose88.7 ± 5.9399.00 ± 13.4197.11 ± 8.680.0460.612Hba1c5.6 ± 0.305.79 ± 0.825.84 ± 0.450.5050.947Insulin8.7 ± 4.3513.64 ± 6.2314.78 ± 10.310.0030.608PT10.98 ± 0.5810.59 ± 1.3310.77 ± 0.800.4110.657Chol172.9 ± 21.46196.60 ± 33.20229.67 ± 28.970.0770.050TG87.5 ± 41.70124.80 ± 52.37221.22 ± 108.430.0960.034HDL58.1 ± 12.3855.00 ± 18.3455.44 ± 24.780.6640.847LDL97.6 ± 18.40116.50 ± 129.00129.00 ± 26.880.0830.284Liver histologySteatosis0.75 ± 0.52.33 ± 0.820.005Fibrosis0 ± 01.60 ± 0890.016NAS1.75 ± 0.56.33 ± 1.030.0001Hepatocellular ballooning0 ± 01.50 ± 0.840.007Lobular inflammation1 ± 02.17 ± 0.410.001Portal inflammation0.5 ± 0.550.17 ± 0.410.262The P values in bold are statistically significant (P ≤ 0.05). Differences between groups evaluated with t-test. Alk P, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; Chol, cholesterol; D Bili, direct bilirubin; GGT, gammaglutamyl transferase; Hba1c, hemoglobin a1c; PT, protime; T Bili, total bilirubin; WBC, white blood count. Open table in a new tab The P values in bold are statistically significant (P ≤ 0.05). Differences between groups evaluated with t-test. Alk P, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; Chol, cholesterol; D Bili, direct bilirubin; GGT, gammaglutamyl transferase; Hba1c, hemoglobin a1c; PT, protime; T Bili, total bilirubin; WBC, white blood count. At present, there are no noninvasive biomarkers with sufficient specificity to distinguish NASH from other fatty liver states. Liver biopsy remains the benchmark to reliably identify NAFL and NASH, but the procedure is invasive and carries certain risks. Thus, there is great demand from the clinical community for the development of noninvasive procedures capable of accurately characterizing and staging NAFLD, as that furnishes valuable information on treatment options and prognosis. Inflammation and oxidative stress contribute to disease
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