| 1. |
- Teo, Kevin, et al.
(author)
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rs641738C>T near MBOAT7 is associated with liver fat, ALT, and fibrosis in NAFLD: a meta-analysis.
- 2021
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In: Journal of hepatology. - : Elsevier BV. - 1600-0641 .- 0168-8278. ; 74:1, s. 20-30
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Journal article (peer-reviewed)abstract
- A common genetic variant near MBOAT7 (rs641738C>T) has been previously associated with hepatic fat and advanced histology in non-alcoholic fatty liver disease (NAFLD), however, these findings have not been consistently replicated in the literature. We aimed to establish whether rs641738C>T is a risk factor across the spectrum of NAFLD and characterize its role in the regulation of related metabolic phenotypes through meta-analysis.We performed meta-analysis of studies with data on the association between rs641738C>T genotype and: liver fat, NAFLD histology, and serum ALT, lipids, or insulin. These included directly genotyped studies and population-level data from genome-wide association studies (GWAS). We performed random effects meta-analysis using recessive, additive, and dominant genetic models.Data from 1,066,175 participants (9,688 with liver biopsies) across 42 studies were included in the meta-analysis. rs641738C>T was associated with higher liver fat on CT/MRI (+0.03 standard deviations [95% CI: 0.02 - 0.05], pz=4.8x10-5) and diagnosis of NAFLD (OR 1.17 [95% CI 1.05 - 1.3], pz=0.003) in Caucasian adults. The variant was also positively associated with presence of advanced fibrosis (OR 1.22 [95% CI: 1.03 - 1.45], pz=0.021) in Caucasian adults using a recessive model of inheritance (CC+CT vs. TT). Meta-analysis of data from previous GWAS found the variant to be associated with higher ALT (pz=0.002) and lower serum triglycerides (pz=1.5x10-4). rs641738C>T was not associated with fasting insulin and no effect was observed in children with NAFLD.Our study validates rs641738C>T near MBOAT7 as a risk factor for the presence and severity of NAFLD in individuals of European descent.
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| 2. |
- Selvaraj, Emmanuel Anandraj, et al.
(author)
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Diagnostic accuracy of elastography and magnetic resonance imaging in patients with NAFLD : a systematic review and meta-analysis
- 2021
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In: Journal of Hepatology. - : Elsevier. - 0168-8278 .- 1600-0641. ; 75:4, s. 770-785
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Research review (peer-reviewed)abstract
- BACKGROUND AND AIMS: Vibration-controlled transient elastography (VCTE), point shear wave elastography (pSWE), two-dimensional shear wave elastography (2DSWE), magnetic resonance elastography (MRE), and magnetic resonance imaging (MRI) are proposed as non-invasive tests for patients with non-alcoholic fatty liver disease (NAFLD). This study evaluated their diagnostic accuracy for liver fibrosis and non-alcoholic steatohepatitis (NASH).METHODS: PubMED/MEDLINE, EMBASE and the Cochrane Library were searched for studies examining the diagnostic accuracy of these index tests against histology as the reference standard, in adult patients with NAFLD. Two authors independently screened and assessed methodological quality of studies and extracted data. Summary estimates of sensitivity, specificity and area under the curve (sAUC) were calculated for fibrosis stages and NASH, using a random effects bivariate logit-normal model.RESULTS: We included 82 studies (14,609 patients). Meta-analysis for diagnosing fibrosis stages was possible in 53 VCTE, 11 MRE, 12 pSWE and four 2DSWE studies, and for diagnosing NASH in four MRE studies. sAUC for diagnosis of significant fibrosis were: 0.83 for VCTE, 0.91 for MRE, 0.86 for pSWE and 0.75 for 2DSWE. sAUC for diagnosis of advanced fibrosis were: 0.85 for VCTE, 0.92 for MRE, 0.89 for pSWE and 0.72 for 2DSWE. sAUC for diagnosis of cirrhosis were: 0.89 for VCTE, 0.90 for MRE, 0.90 for pSWE and 0.88 for 2DSWE. MRE had sAUC of 0.83 for diagnosis of NASH. Three (4%) studies reported intention-to-diagnose analyses and 15 (18%) studies reported diagnostic accuracy against pre-specified cut-offs.CONCLUSIONS: When elastography index tests are acquired successfully, they have acceptable diagnostic accuracy for advanced fibrosis and cirrhosis. The potential clinical impact of these index tests cannot be assessed fully as intention-to-diagnose analyses and validation of pre-specified thresholds are lacking.LAY SUMMARY: Non-invasive tests that measure liver stiffness or use magnetic resonance imaging (MRI) have been suggested as alternatives to liver biopsy in assessing the severity of liver scarring (fibrosis) and fatty inflammation (steatohepatitis) in patients with non-alcoholic fatty liver disease (NAFLD). In this study, we summarise the results of previously published studies on how accurately these non-invasive tests can diagnose liver fibrosis and inflammation, using liver biopsy as the reference. We found that some techniques that measure liver stiffness had a good performance for the diagnosis of severe liver scarring.
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| 3. |
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| 4. |
- Masoodi, Mojgan, et al.
(author)
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Metabolomics and lipidomics in NAFLD : biomarkers and non-invasive diagnostic tests
- 2021
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In: Nature Reviews. Gastroenterology & Hepatology. - : Nature Publishing Group. - 1759-5045 .- 1759-5053. ; 18:12, s. 835-856
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Research review (peer-reviewed)abstract
- Nonalcoholic fatty liver disease (NAFLD) is one of the most common liver diseases worldwide and is often associated with aspects of metabolic syndrome. Despite its prevalence and the importance of early diagnosis, there is a lack of robustly validated biomarkers for diagnosis, prognosis and monitoring of disease progression in response to a given treatment. In this Review, we provide an overview of the contribution of metabolomics and lipidomics in clinical studies to identify biomarkers associated with NAFLD and nonalcoholic steatohepatitis (NASH). In addition, we highlight the key metabolic pathways in NAFLD and NASH that have been identified by metabolomics and lipidomics approaches and could potentially be used as biomarkers for non-invasive diagnostic tests. Overall, the studies demonstrated alterations in amino acid metabolism and several aspects of lipid metabolism including circulating fatty acids, triglycerides, phospholipids and bile acids. Although we report several studies that identified potential biomarkers, few have been validated.
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| 5. |
- Bianco, Cristina, et al.
(author)
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Non-invasive stratification of hepatocellular carcinoma risk in non-alcoholic fatty liver using polygenic risk scores.
- 2021
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In: Journal of hepatology. - : Elsevier BV. - 1600-0641 .- 0168-8278. ; 74:4, s. 775-782
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Journal article (peer-reviewed)abstract
- Hepatocellular carcinoma (HCC) risk stratification in individuals with dysmetabolism is a major unmet need. Genetic predisposition contributes to non-alcoholic fatty liver disease (NAFLD). We aimed to exploit robust polygenic risk scores (PRS) that can be evaluated in the clinic to gain insight into the causal relationship between NAFLD and HCC, and to improve HCC risk stratification.We examined at-risk individuals (NAFLD cohort, n=2,566; 226 with HCC; and a replication cohort of 427 German patients with NAFLD) and the general population (UK Biobank [UKBB] cohort, n=364,048; 202 with HCC). Variants in PNPLA3-TM6SF2-GCKR-MBOAT7 were combined in a hepatic fat PRS (PRS-HFC), and then adjusted for HSD17B13 (PRS-5).In the NAFLD cohort, the adjusted impact of genetic risk variants on HCC was proportional to the predisposition to fatty liver (p=0.002) with some heterogeneity in the effect. PRS predicted HCC more robustly than single variants (p<10-13). The association between PRS and HCC was mainly mediated through severe fibrosis, but was independent of fibrosis in clinically relevant subgroups, and was also observed in those without severe fibrosis (p<0.05). In the UKBB cohort, PRS predicted HCC independently of classical risk factors and cirrhosis (p<10-7). In the NAFLD cohort, we identified high PRS cut-offs (≥0.532/0.495 for PRS-HFC/PRS-5) that in the UKBB cohort detected HCC with ∼90% specificity but limited sensitivity; PRS predicted HCC both in individuals with (p<10-5) and without cirrhosis (p<0.05).Our results are consistent with a causal relationship between hepatic fat and HCC. PRS improved the accuracy to detect HCC and may help stratify HCC risk in individuals with dysmetabolism, including those without severe liver fibrosis. Further studies are needed to validate our findings.
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| 6. |
- Lazarus, Jeffrey V, et al.
(author)
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European NAFLD Preparedness Index - Is Europe ready to meet the challenge of fatty liver disease?
- 2021
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In: JHEP Reports. - : Elsevier. - 2589-5559. ; 3:2
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Journal article (peer-reviewed)abstract
- Background & Aims: Non-alcoholic fatty liver disease (NAFLD), which is closely associated with obesity, metabolic syndrome, and diabetes, is a highly prevalent emerging condition that can be optimally managed through a multidisciplinary patientcentred approach. National preparedness to address NAFLD is essential to ensure that health systems can deliver effective care. We present a NAFLD Preparedness Index for Europe. Methods: In June 2019, data were extracted by expert groups from 29 countries to complete a 41-item questionnaire about NAFLD. Questions were classified into 4 categories: policies/civil society (9 questions), guidelines (16 questions), epidemiology (4 questions), and care management (12 questions). Based on the responses, national preparedness for each indicator was classified into low, middle, or high-levels. We then applied a multiple correspondence analysis to obtain a standardised preparedness score for each country ranging from 0 to 100. Results: The analysis estimated a summary factor that explained 71.3% of the variation in the dataset. No countries were found to have yet attained a high-level of preparedness. Currently, the UK (75.5) scored best, although falling within the midlevel preparedness band, followed by Spain (56.2), and Denmark (43.4), whereas Luxembourg and Ireland were the lowest scoring countries with a score of 4.9. Only Spain scored highly in the epidemiology indicator category, whereas the UK was the only country that scored highly for care management. Conclusions: The NAFLD Preparedness Index indicates substantial variation between countries readiness to address NAFLD. Notably, even those countries that score relatively highly exhibit deficiencies in key domains, suggesting that structural changes are needed to optimise NAFLD management and ensure effective public health approaches are in place. Lay summary: Non-alcoholic fatty liver disease (NAFLD), which is closely associated with obesity, metabolic syndrome, and diabetes, is a highly prevalent condition that can be optimally managed through a multidisciplinary patient-centred approach. National preparedness to address NAFLD is essential to allow for effective public health measures aimed at preventing disease while also ensuring that health systems can deliver effective care to affected populations. This study defined preparedness as having adequate policies and civil society engagement, guidelines, epidemiology, and care management. NAFLD preparedness was found to be deficient in all 29 countries studied, with great variation among the countries and the 4 categories studied. (C) 2021 The Authors. Published by Elsevier B.V. on behalf of European Association for the Study of the Liver (EASL).
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| 7. |
- McGlinchey, Aidan J, 1984-, et al.
(author)
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The Metabolomics of Non-Alcoholic Fatty Liver Disease : Of Networks and Biomarkers
- 2021
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In: Journal of Hepatology. - : Elsevier. - 0168-8278 .- 1600-0641. ; 75:Suppl. 2, s. S579-S580
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Journal article (other academic/artistic)abstract
- Background and aims: Non-alcoholic fatty liver disease (NAFLD), the leading cause of chronic liver disease, affects 25%+ of people worldwide. Detailed understanding of the metabolomics of NAFLD, and non-invasive diagnostic techniques for the stages of NAFLD are unavailable. We identify specific serum molecular lipid signatures to these ends.First, we leverage lipidomic and polar metabolomic data (n = 643) subjects, to produce a clear, meaningful interaction map, linking lipids, metabolites, clinical factors and disease outcomes. We find non-spurious associations therein, as features of interest, and for downstream analysis.Third, NAFLD fibrosis biomarker identification was performed using machine learning, with our candidate lipids/metabolites to be forwarded to a successor project; the LITMUS project, towards clinically-applicable, non-invasive, sensitive and specific classification of NAFLD patients.Method: Serum lipids and polar metabolites were measured by mass spectrometry in the EPoS cohort of patients (n = 176 lipids and n = 36 polar metabolites), combined with clinical data from (n = 643 subjects), followed by model-based clustering, giving 10 lipid clusters (LCs).Correlations were calculated pairwise between (1) all LCs, (2) “input” clinical data (height, weight, BMI, blood platelet count) and (3) outcomes (fibrosis, steatosis, NAS score, etc.). Non-rejection rates (NRRs) were calculated for relationships, remove spurious associations (NRR > 0.4). We project the remaining associations as a network; a novel metabolomic overview NAFLD.ANOVA and Tukey’s Honest Significant Differences (Tukey HSDs) revealed detailed metabolic signatures across NAFLD, fibrosis and steatosis stages.Random forest machine learning was used to classify NAFLD patients: LOW (0-1 fibrosis grade) or HIGH (2–4 fibrosis grade), using individual lipids and metabolites, identifying putative biomarkers.Results: In linewith our previous findings, many lipids associate with steatosis and fibrosis in NAFLD. Our novel overview network revealsas sociations between specific LCs and clinical variables, such as TGs (LC3), and a subgroup of TGs of lowest and highest carbon numbers (LC9) along with PC (O)s (LC7) positively associating with NAFLD score and fibrosis. Conversely, LPCs (LC4), particularly sphingomyelins (SMs, LC6), negatively associated with these variables. Many other metabolites changing across NAFLD stages beg further discussion.Conclusion: In addition to generation of a novel metabolomic network of NAFLD, we demonstrate feasibility of lipidomic and metabolomic data to classify NAFLD patients’fibrosis grades (median AUC: 0.765), competitive with gold-standard clinical variables (age, BMI, sex, diabetes, liver AST/ALT, platelet count) (median AUC: 0.778). These biomarkers are being taken forward (LITMUS project) to develop clinical testing.
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