المؤلفون: Gill, Ryan M., Allende, Daniela, Belt, Patricia H., Behling, Cynthia A., Cummings, Oscar W., Guy, Cynthia D., Carpenter, Daniela, Neuschwander-Tetri, Brent A., Sanyal, Arun J., Tonascia, James, Van Natta, Mark L., Wilson, Laura A., Yamada, Goro, Yeh, Matthew, Kleiner, David E.

المصدر: Hepatology Communications; Feb2023, Vol. 7 Issue 2, p1-14, 14p

مصطلحات موضوعية: NON-alcoholic fatty liver disease, FATTY liver, BODY mass index, MEDICAL research, METABOLIC syndrome, LIVER biopsy

مستخلص: Background and Aims: The NAFLD activity score was developed to measure histologic changes in NAFLD during therapeutic trials. Hepatocyte ballooning (HB) is the most specific feature in steatohepatitis diagnosis, yet the impact of variations in HB has not been incorporated. Approach and Results: Liver biopsies from patients enrolled in the NASH Clinical Research Network with an initial diagnosis of NASH or NAFL (n =1688) were evaluated to distinguish classic hepatocyte ballooning (cHB) from smaller, nonclassic hepatocyte ballooning (nHB), and also to designate severe ballooning and assign an extended hepatocyte ballooning (eB) score [0 points, no ballooning (NB); 1 point, few or many nHB; 2 points, few cHB; 3 points, many cHB; 4 points, severe cHB] to the biopsy assessment. The eB score was reproducible among NASH CRN liver pathologists (weighted kappa 0.76) and was significantly associated with older age (mean 52.1 y, cHB; 48.5 y, nHB, p< 0.001), gender (72.3% female, cHB; 54.5% female, nHB, p < 0.001), diabetes (49.8% diabetes, cHB; 28.2% diabetes, nHB, p <0.001), metabolic syndrome (68.5% metabolic syndrome, nHB; 50.2% metabolic syndrome, NB, p <0.001), and body mass index [33.2, 34.2, 35 mean body mass index (kg/m2); NB, nHB, and cHB, respectively, p <0.05]. Finally, fibrosis stage, as a marker of disease severity, was significantly correlated with the eB score (p< 0.001). Conclusions: The eB score allows for a reproducible and more precise delineation of the range of ballooned hepatocyte morphology and corresponds with both clinical features of NASH and fibrosis stage. [ABSTRACT FROM AUTHOR]

: Copyright of Hepatology Communications is the property of Lippincott Williams & Wilkins and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

المؤلفون: Brandman, Danielle, Boyle, Marie, McPherson, Stuart, Van Natta, Mark L., Sanyal, Arun J., Kowdley, Kris, Neuschwander‐Tetri, Brent, Chalasani, Naga, Abdelmalek, Manal F., Terrault, Norah A., McCullough, Art, Bettencourt, Ricki, Caussy, Cyrielle, Kleiner, David E., Behling, Cynthia, Tonascia, James, Anstee, Quentin M., Loomba, Rohit

المصدر: Alimentary Pharmacology & Therapeutics; Jun2022, Vol. 55 Issue 11, p1441-1451, 11p, 4 Charts, 1 Graph

مصطلحات موضوعية: NON-alcoholic fatty liver disease, CLINICAL prediction rules, CIRRHOSIS of the liver, GLEASON grading system

مصطلحات جغرافية: UNITED Kingdom, NEWCASTLE upon Tyne (England)

مستخلص: Summary: Background and Aims: Patients with nonalcoholic fatty liver disease (NAFLD) cirrhosis benefit from referral to subspecialty care. While several clinical prediction rules exist to identify advanced fibrosis, the cutoff for excluding cirrhosis due to NAFLD is unclear. This analysis compared clinical prediction rules for excluding biopsy‐proven cirrhosis in NAFLD. Methods: Adult patients were enrolled in the NASH Clinical Research Network (US) and the Newcastle Cohort (UK). Clinical and laboratory data were collected at enrolment, and a liver biopsy was taken within 1 year of enrolment. Optimal cutoffs for each score (eg, FIB‐4) to exclude cirrhosis were derived from the US cohort, and sensitivity, specificity, positive predictive value, negative predictive value and AUROC were calculated. The cutoffs were evaluated in the UK cohort. Results: 147/1483 (10%) patients in the US cohort had cirrhosis. All prediction rules had similarly high NPV (0.95–0.97). FIB‐4 and NAFLD fibrosis scores were the most accurate in characterising patients as having cirrhosis (AUROC 0.84–0.86). 59/494 (12%) patients in the UK cohort had cirrhosis. Prediction rules had high NPV (0.92–0.96), and FIB‐4 and NAFLD fibrosis score the most accurate in the prediction of cirrhosis in the UK cohort (AUROC 0.87–0.89). Conclusions: This cross‐sectional analysis of large, multicentre international datasets shows that current clinical prediction rules perform well in excluding cirrhosis with appropriately chosen cutoffs. These clinical prediction rules can be used in primary care to identify patients, particularly those who are white, female, and <65, unlikely to have cirrhosis so higher‐risk patients maintain access to specialty care. [ABSTRACT FROM AUTHOR]

: Copyright of Alimentary Pharmacology & Therapeutics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

المؤلفون: Brandman, Danielle, Boyle, Marie, McPherson, Stuart, Van Natta, Mark L., Sanyal, Arun J., Kowdley, Kris, Neuschwander‐Tetri, Brent, Chalasani, Naga, Abdelmalek, Manal F., Terrault, Norah A., McCullough, Art, Bettencourt, Ricki, Caussy, Cyrielle, Kleiner, David E., Behling, Cynthia, Tonascia, James, Anstee, Quentin M., Loomba, Rohit

المصدر: Alimentary Pharmacology & Therapeutics; Jul2022, Vol. 56 Issue 1, p182-183, 2p

مصطلحات موضوعية: PREDICTION models, NON-alcoholic fatty liver disease, CIRRHOSIS of the liver, AUTHORS

مستخلص: LINKED CONTENT: This article is linked to Brandman et al papers. To view these articles, visit https://doi.org/10.1111/apt.16874Test and https://doi.org/10.1111/apt.16931Test [ABSTRACT FROM AUTHOR]

: Copyright of Alimentary Pharmacology & Therapeutics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

المؤلفون: Sanyal, Arun J.¹ (AUTHOR) arun.sanyal@vcuhealth.org, Williams, Stephen A.² (AUTHOR), Lavine, Joel E.³ (AUTHOR), Neuschwander-Tetri, Brent A.⁴ (AUTHOR), Alexander, Leigh⁵ (AUTHOR), Ostroff, Rachel² (AUTHOR), Biegel, Hannah⁵ (AUTHOR), Kowdley, Kris V.⁶ (AUTHOR), Chalasani, Naga⁷ (AUTHOR), Dasarathy, Srinivasan⁸ (AUTHOR), Diehl, Anna Mae⁹ (AUTHOR), Loomba, Rohit¹⁰ (AUTHOR), Hameed, Bilal¹¹ (AUTHOR), Behling, Cynthia¹⁰ (AUTHOR), Kleiner, David E.¹² (AUTHOR), Karpen, Saul J.¹³ (AUTHOR), Williams, Jessica¹⁴ (AUTHOR), Jia, Yi² (AUTHOR), Yates, Katherine P.¹⁵ (AUTHOR), Tonascia, James¹⁵ (AUTHOR)

المصدر: Journal of Hepatology. Apr2023, Vol. 78 Issue 4, p693-703. 11p.

مصطلحات موضوعية: *FATTY liver, *NON-alcoholic fatty liver disease, *NONINVASIVE diagnostic tests, *INFLAMMATION, *BLOOD proteins, *FIBROSIS

مستخلص: Despite recent progress, non-invasive tests for the diagnostic assessment and monitoring of non-alcoholic fatty liver disease (NAFLD) remain an unmet need. Herein, we aimed to identify diagnostic signatures of the key histological features of NAFLD. Using modified-aptamer proteomics, we assayed 5,220 proteins in each of 2,852 single serum samples from 636 individuals with histologically confirmed NAFLD. We developed and validated dichotomized protein-phenotype models to identify clinically relevant severities of steatosis (grade 0 vs. 1-3), hepatocellular ballooning (0 vs. 1 or 2), lobular inflammation (0-1 vs. 2-3) and fibrosis (stages 0-1 vs. 2-4). The AUCs of the four protein models, based on 37 analytes (18 not previously linked to NAFLD), for the diagnosis of their respective components (at a clinically relevant severity) in training/paired validation sets were: fibrosis (AUC 0.92/0.85); steatosis (AUC 0.95/0.79), inflammation (AUC 0.83/0.72), and ballooning (AUC 0.87/0.83). An additional outcome, at-risk NASH, defined as steatohepatitis with NAFLD activity score ≥4 (with a score of at least 1 for each of its components) and fibrosis stage ≥2, was predicted by multiplying the outputs of each individual component model (AUC 0.93/0.85). We further evaluated their ability to detect change in histology following treatment with placebo, pioglitazone, vitamin E or obeticholic acid. Component model scores significantly improved in the active therapies vs. placebo, and differential effects of vitamin E, pioglitazone, and obeticholic acid were identified. Serum protein scanning identified signatures corresponding to the key components of liver biopsy in NAFLD. The models developed were sufficiently sensitive to characterize the longitudinal change for three different drug interventions. These data support continued validation of these proteomic models to enable a "liquid biopsy"-based assessment of NAFLD. Not applicable. An aptamer-based protein scan of serum proteins was performed to identify diagnostic signatures of the key histological features of non-alcoholic fatty liver disease (NAFLD), for which no approved non-invasive diagnostic tools are currently available. We also identified specific protein signatures related to the presence and severity of NAFLD and its histological components that were also sensitive to change over time. These are fundamental initial steps in establishing a serum proteome-based diagnostic signature of NASH and provide the rationale for using these signatures to test treatment response and to identify several novel targets for evaluation in the pathogenesis of NAFLD. [Display omitted] • Aptamer proteomics and machine learning generated blood-based NASH models. • Serum models of liver steatosis, inflammation, ballooning and fibrosis were validated. • Models accurately reflect liver biopsy results and NASH severity. • Models allow for non-invasive longitudinal monitoring of treatment response. [ABSTRACT FROM AUTHOR]