Surveillance of the liver in type 2 diabetes: important but unfeasible?

Fatty liver plays a pivotal role in the pathogenesis of the metabolic syndrome and type 2 diabetes. According to an updated classification, any individual with liver steatosis and one or more features of the metabolic syndrome, without excess alcohol consumption or other known causes of steatosis, has metabolic dysfunction-associated steatotic liver disease (MASLD). Up to 60-70% of all individuals with type 2 diabetes have MASLD. However, the prevalence of advanced liver fibrosis in type 2 diabetes remains uncertain, with reported estimates of 10-20% relying on imaging tests and likely overestimating the true prevalence. All stages of MASLD impact prognosis but fibrosis is the best predictor of all-cause and liver-related mortality risk. People with type 2 diabetes face a two- to threefold increase in the risk of liver-related death and hepatocellular carcinoma, with 1.3% progressing to severe liver disease over 7.7 years. Because reliable methods for detecting steatosis are lacking, MASLD mostly remains an incidental finding on imaging. Regardless, several medical societies advocate for universal screening of individuals with type 2 diabetes for advanced fibrosis. Proposed screening pathways involve annual calculation of the Fibrosis-4 (FIB-4) index, followed by a secondary test such as transient elastography (TE) for intermediate-to-high-risk individuals. However, owing to unsatisfactory biomarker specificity, these pathways are expected to channel approximately 40% of all individuals with type 2 diabetes to TE and 20% to tertiary care, with a false discovery rate of up to 80%, raising concerns about feasibility. There is thus an urgent need to develop more effective strategies for surveying the liver in type 2 diabetes. Nonetheless, weight loss through lifestyle changes, pharmacotherapy or bariatric surgery remains the cornerstone of management, proving highly effective not only for metabolic comorbidities but also for MASLD. Emerging evidence suggests that fibrosis biomarkers may serve as tools for risk-based targeting of weight-loss interventions and potentially for monitoring response to therapy.

Machine learning approaches to enhance diagnosis and staging of patients with MASLD using routinely available clinical information.

AIMS: Metabolic dysfunction Associated Steatotic Liver Disease (MASLD) outcomes such as MASH (metabolic dysfunction associated steatohepatitis), fibrosis and cirrhosis are ordinarily determined by resource-intensive and invasive biopsies. We aim to show that routine clinical tests offer sufficient information to predict these endpoints. METHODS: Using the LITMUS Metacohort derived from the European NAFLD Registry, the largest MASLD dataset in Europe, we create three combinations of features which vary in degree of procurement including a 19-variable feature set that are attained through a routine clinical appointment or blood test. This data was used to train predictive models using supervised machine learning (ML) algorithm XGBoost, alongside missing imputation technique MICE and class balancing algorithm SMOTE. Shapley Additive exPlanations (SHAP) were added to determine relative importance for each clinical variable. RESULTS: Analysing nine biopsy-derived MASLD outcomes of cohort size ranging between 5385 and 6673 subjects, we were able to predict individuals at training set AUCs ranging from 0.719-0.994, including classifying individuals who are At-Risk MASH at an AUC = 0.899. Using two further feature combinations of 26-variables and 35-variables, which included composite scores known to be good indicators for MASLD endpoints and advanced specialist tests, we found predictive performance did not sufficiently improve. We are also able to present local and global explanations for each ML model, offering clinicians interpretability without the expense of worsening predictive performance. CONCLUSIONS: This study developed a series of ML models of accuracy ranging from 71.9-99.4% using only easily extractable and readily available information in predicting MASLD outcomes which are usually determined through highly invasive means.

Development and Validation of the Nonalcoholic Fatty Liver Disease Familial Risk Score to Detect Advanced Fibrosis: A Prospective, Multicenter Study.

BACKGROUND & AIMS: Nonalcoholic fatty liver disease (NAFLD)-related fibrosis is heritable, but it is unclear how family history may be used to identify first-degree relatives with advanced fibrosis. We aimed to develop and validate a simple risk score to identify first-degree relatives of probands who have undergone assessment of liver fibrosis who are at higher risk of NAFLD with advanced fibrosis. METHODS: This prospective, cross-sectional, familial study consisted of a derivation cohort from San Diego, California, and a validation cohort from Helsinki, Finland. This study included consecutive adult probands (n = 242) with NAFLD and advanced fibrosis, NAFLD without advanced fibrosis, and non-NAFLD, with at least 1 of their first-degree relatives. All included probands and first-degree relatives underwent evaluation of liver fibrosis, the majority by magnetic resonance elastography. RESULTS: A total of 396 first-degree relatives (64% male) were included. The median age and body mass index were 47 years (interquartile range, 32-62 y) and 27.6 kg/m2 (interquartile range, 24.1-32.5 kg/m2), respectively. Age (1 point), type 2 diabetes (1 point), obesity (2 points), and proband with NAFLD and advanced fibrosis (2 points) were predictors of advanced fibrosis among first-degree relatives in the derivation cohort (n = 220) and formed the NAFLD Familial Risk Score. The area under the receiver operator characteristic curve of the NAFLD Familial Risk Score for detecting advanced fibrosis was 0.94 in the validation cohort (n = 176). The NAFLD Familial Risk Score outperformed the Fibrosis-4 index in the validation cohort (area under the receiver operator characteristic curve, 0.94 vs 0.70; P = .02). CONCLUSIONS: The NAFLD Familial Risk Score is a simple and accurate clinical tool to identify advanced fibrosis in first-degree relatives. These data may have implications for surveillance in NAFLD.

Marked difference in liver fat measured by histology vs. magnetic resonance-proton density fat fraction: A meta-analysis.

Background & Aims: Pathologists quantify liver steatosis as the fraction of lipid droplet-containing hepatocytes out of all hepatocytes, whereas the magnetic resonance-determined proton density fat fraction (PDFF) reflects the tissue triacylglycerol concentration. We investigated the linearity, agreement, and correspondence thresholds between histological steatosis and PDFF across the full clinical spectrum of liver fat content associated with non-alcoholic fatty liver disease. Methods: Using individual patient-level measurements, we conducted a systematic review and meta-analysis of studies comparing histological steatosis with PDFF determined by magnetic resonance spectroscopy or imaging in adults with suspected non-alcoholic fatty liver disease. Linearity was assessed by meta-analysis of correlation coefficients and by linear mixed modelling of pooled data, agreement by Bland-Altman analysis, and thresholds by receiver operating characteristic analysis. To explain observed differences between the methods, we used RNA-seq to determine the fraction of hepatocytes in human liver biopsies. Results: Eligible studies numbered 9 (N = 597). The relationship between PDFF and histology was predominantly linear (r = 0.85 [95% CI, 0.80-0.89]), and their values approximately coincided at 5% steatosis. Above 5% and towards higher levels of steatosis, absolute values of the methods diverged markedly, with histology exceeding PDFF by up to 3.4-fold. On average, 100% histological steatosis corresponded to a PDFF of 33.0% (29.5-36.7%). Targeting at a specificity of 90%, optimal PDFF thresholds to predict histological steatosis grades were ≥5.75% for ≥S1, ≥15.50% for ≥S2, and ≥21.35% for S3. Hepatocytes comprised 58 ± 5% of liver cells, which may partly explain the lower values of PDFF vs. histology. Conclusions: Histological steatosis and PDFF have non-perfect linearity and fundamentally different scales of measurement. Liver fat values obtained using these methods may be rendered comparable by conversion equations or threshold values. Impact and implications: Magnetic resonance-proton density fat fraction (PDFF) is increasingly being used to measure liver fat in place of the invasive liver biopsy. Understanding the relationship between PDFF and histological steatosis fraction is important for preventing misjudgement of clinical status or treatment effects in patient care. Our analysis revealed that histological steatosis fraction is often significantly higher than PDFF, and their association varies across the spectrum of fatty liver severity. These findings are particularly important for physicians and clinical researchers, who may use these data to interpret PDFF measurements in the context of histologically evaluated liver fat content.

Liver Investigation: Testing Marker Utility in Steatohepatitis (LITMUS): Assessment & validation of imaging modality performance across the NAFLD spectrum in a prospectively recruited cohort study (the LITMUS imaging study): Study protocol.

Non-alcoholic fatty liver disease (NAFLD) is the liver manifestation of the metabolic syndrome with global prevalence reaching epidemic levels. Despite the high disease burden in the population only a small proportion of those with NAFLD will develop progressive liver disease, for which there is currently no approved pharmacotherapy. Identifying those who are at risk of progressive NAFLD currently requires a liver biopsy which is problematic. Firstly, liver biopsy is invasive and therefore not appropriate for use in a condition like NAFLD that affects a large proportion of the population. Secondly, biopsy is limited by sampling and observer dependent variability which can lead to misclassification of disease severity. Non-invasive biomarkers are therefore needed to replace liver biopsy in the assessment of NAFLD. Our study addresses this unmet need. The LITMUS Imaging Study is a prospectively recruited multi-centre cohort study evaluating magnetic resonance imaging and elastography, and ultrasound elastography against liver histology as the reference standard. Imaging biomarkers and biopsy are acquired within a 100-day window. The study employs standardised processes for imaging data collection and analysis as well as a real time central monitoring and quality control process for all the data submitted for analysis. It is anticipated that the high-quality data generated from this study will underpin changes in clinical practice for the benefit of people with NAFLD. Study Registration: clinicaltrials.gov: NCT05479721.

Validation of the Blood Test MACK-3 for the Noninvasive Diagnosis of Fibrotic Nonalcoholic Steatohepatitis: An International Study With 1924 Patients.

BACKGROUND & AIMS: Drug development in nonalcoholic steatohepatitis (NASH) is hampered by a high screening failure rate that reaches 60% to 80% in therapeutic trials, mainly because of the absence of fibrotic NASH on baseline liver histology. MACK-3, a blood test including 3 biomarkers (aspartate aminotransferase, homeostasis model assessment, and cytokeratin 18), recently was developed for the noninvasive diagnosis of fibrotic NASH. We aimed to validate the diagnostic accuracy of this noninvasive test in an international multicenter study. METHODS: A total of 1924 patients with biopsy-proven nonalcoholic fatty liver disease from 10 centers in Asia, Australia, and Europe were included. The blood test MACK-3 was calculated for all patients. FibroScan-aspartate aminotransferase score (FAST), an elastography-based test for fibrotic NASH, also was available in a subset of 655 patients. Fibrotic NASH was defined as the presence of NASH on liver biopsy with a Nonalcoholic Fatty Liver Disease Activity Score of 4 or higher and fibrosis stage of F2 or higher according to the NASH Clinical Research Network scoring system. RESULTS: The area under the receiver operating characteristic of MACK-3 for fibrotic NASH was 0.791 (95% CI 0.768-0.814). Sensitivity at the previously published MACK-3 threshold of less than 0.135 was 91% and specificity at a greater than 0.549 threshold was 85%. The MACK-3 area under the receiver operating characteristic was not affected by age, sex, diabetes, or body mass index. MACK-3 and FAST results were well correlated (Spearman correlation coefficient, 0.781; P < .001). Except for an 8% higher rate of patients included in the grey zone, MACK-3 provided similar accuracy to that of FAST. Both tests included 27% of patients in their rule-in zone, with 85% specificity and 35% false positives (screen failure rate). CONCLUSIONS: The blood test MACK-3 is an accurate tool to improve patient selection in NASH therapeutic trials.

Programmed cell death 1 genetic variant and liver damage in nonalcoholic fatty liver disease.

BACKGROUND AND AIMS: Programmed cell death 1/programmed cell death-ligand 1 (PD-1/PDL-1) axis has been reported to modulate liver inflammation and progression to hepatocellular carcinoma (HCC) in patients with nonalcoholic fatty liver disease (NAFLD). Here, we examined whether the PDCD1 variation is associated with NAFLD severity in individuals with liver biopsy. METHODS: We examined the impact of PDCD1 gene variants on HCC, as robust severe liver disease phenotype in UK Biobank participants. The strongest genetic association with the rs13023138 G>C variation was subsequently tested for association with liver damage in 2889 individuals who underwent liver biopsy for suspected nonalcoholic steatohepatitis (NASH). Hepatic transcriptome was examined by RNA-Seq in a subset of NAFLD individuals (n = 121). Transcriptomic and deconvolution analyses were performed to identify biological pathways modulated by the risk allele. RESULTS: The rs13023138 C>G showed the most robust association with HCC in UK Biobank (p = 5.28E-4, OR = 1.32, 95% CI [1.1, 1.5]). In the liver biopsy cohort, rs13023138 G allele was independently associated with severe steatosis (OR 1.17, 95% CI 1.02-1.34; p = .01), NASH (OR 1.22, 95% CI 1.09-1.37; p < .001) and advanced fibrosis (OR 1.26, 95% CI 1.06-1.50; p = .007). At deconvolution analysis, rs13023138 G>C allele was linked to higher hepatic representation of M1 macrophages, paralleled by upregulation of pathways related to inflammation and higher expression of CXCR6. CONCLUSIONS: The PDCD1 rs13023138 G allele was associated with HCC development in the general population and with liver disease severity in patients at high risk of NASH.

Machine learning algorithm improves the detection of NASH (NAS-based) and at-risk NASH: A development and validation study.

BACKGROUND AND AIMS: Detecting NASH remains challenging, while at-risk NASH (steatohepatitis and F≥ 2) tends to progress and is of interest for drug development and clinical application. We developed prediction models by supervised machine learning techniques, with clinical data and biomarkers to stage and grade patients with NAFLD. APPROACH AND RESULTS: Learning data were collected in the Liver Investigation: Testing Marker Utility in Steatohepatitis metacohort (966 biopsy-proven NAFLD adults), staged and graded according to NASH CRN. Conditions of interest were the clinical trial definition of NASH (NAS ≥ 4;53%), at-risk NASH (NASH with F ≥ 2;35%), significant (F ≥ 2;47%), and advanced fibrosis (F ≥ 3;28%). Thirty-five predictors were included. Missing data were handled by multiple imputations. Data were randomly split into training/validation (75/25) sets. A gradient boosting machine was applied to develop 2 models for each condition: clinical versus extended (clinical and biomarkers). Two variants of the NASH and at-risk NASH models were constructed: direct and composite models.Clinical gradient boosting machine models for steatosis/inflammation/ballooning had AUCs of 0.94/0.79/0.72. There were no improvements when biomarkers were included. The direct NASH model produced AUCs (clinical/extended) of 0.61/0.65. The composite NASH model performed significantly better (0.71) for both variants. The composite at-risk NASH model had an AUC of 0.83 (clinical and extended), an improvement over the direct model. Significant fibrosis models had AUCs (clinical/extended) of 0.76/0.78. The extended advanced fibrosis model (0.86) performed significantly better than the clinical version (0.82). CONCLUSIONS: Detection of NASH and at-risk NASH can be improved by constructing independent machine learning models for each component, using only clinical predictors. Adding biomarkers only improved the accuracy of fibrosis.

Biomarkers for staging fibrosis and non-alcoholic steatohepatitis in non-alcoholic fatty liver disease (the LITMUS project): a comparative diagnostic accuracy study.

BACKGROUND: The reference standard for detecting non-alcoholic steatohepatitis (NASH) and staging fibrosis-liver biopsy-is invasive and resource intensive. Non-invasive biomarkers are urgently needed, but few studies have compared these biomarkers in a single cohort. As part of the Liver Investigation: Testing Marker Utility in Steatohepatitis (LITMUS) project, we aimed to evaluate the diagnostic accuracy of 17 biomarkers and multimarker scores in detecting NASH and clinically significant fibrosis in patients with non-alcoholic fatty liver disease (NAFLD) and identify their optimal cutoffs as screening tests in clinical trial recruitment. METHODS: This was a comparative diagnostic accuracy study in people with biopsy-confirmed NAFLD from 13 countries across Europe, recruited between Jan 6, 2010, and Dec 29, 2017, from the LITMUS metacohort of the prospective European NAFLD Registry. Adults (aged ≥18 years) with paired liver biopsy and serum samples were eligible; those with excessive alcohol consumption or evidence of other chronic liver diseases were excluded. The diagnostic accuracy of the biomarkers was expressed as the area under the receiver operating characteristic curve (AUC) with liver histology as the reference standard and compared with the Fibrosis-4 index for liver fibrosis (FIB-4) in the same subgroup. Target conditions were the presence of NASH with clinically significant fibrosis (ie, at-risk NASH; NAFLD Activity Score ≥4 and F≥2) or the presence of advanced fibrosis (F≥3), analysed in all participants with complete data. We identified thres holds for each biomarker for reducing the number of biopsy-based screen failures when recruiting people with both NASH and clinically significant fibrosis for future trials. FINDINGS: Of 1430 participants with NAFLD in the LITMUS metacohort with serum samples, 966 (403 women and 563 men) were included after all exclusion criteria had been applied. 335 (35%) of 966 participants had biopsy-confirmed NASH and clinically significant fibrosis and 271 (28%) had advanced fibrosis. For people with NASH and clinically significant fibrosis, no single biomarker or multimarker score significantly reached the predefined AUC 0·80 acceptability threshold (AUCs ranging from 0·61 [95% CI 0·54-0·67] for FibroScan controlled attenuation parameter to 0·81 [0·75-0·86] for SomaSignal), with accuracy mostly similar to FIB-4. Regarding detection of advanced fibrosis, SomaSignal (AUC 0·90 [95% CI 0·86-0·94]), ADAPT (0·85 [0·81-0·89]), and FibroScan liver stiffness measurement (0·83 [0·80-0·86]) reached acceptable accuracy. With 11 of 17 markers, histological screen failure rates could be reduced to 33% in trials if only people who were marker positive had a biopsy for evaluating eligibility. The best screening performance for NASH and clinically significant fibrosis was observed for SomaSignal (number needed to test [NNT] to find one true positive was four [95% CI 4-5]), then ADAPT (six [5-7]), MACK-3 (seven [6-8]), and PRO-C3 (nine [7-11]). INTERPRETATION: None of the single markers or multimarker scores achieved the predefined acceptable AUC for replacing biopsy in detecting people with both NASH and clinically significant fibrosis. However, several biomarkers could be applied in a prescreening strategy in clinical trial recruitment. The performance of promising markers will be further evaluated in the ongoing prospective LITMUS study cohort. FUNDING: The Innovative Medicines Initiative 2 Joint Undertaking.

Mapping transcriptional heterogeneity and metabolic networks in fatty livers at single-cell resolution.

Non-alcoholic fatty liver disease is a heterogeneous disease with unclear underlying molecular mechanisms. Here, we perform single-cell RNA sequencing of hepatocytes and hepatic non-parenchymal cells to map the lipid signatures in mice with non-alcoholic fatty liver disease (NAFLD). We uncover previously unidentified clusters of hepatocytes characterized by either high or low srebp1 expression. Surprisingly, the canonical lipid synthesis driver Srebp1 is not predictive of hepatic lipid accumulation, suggestive of other drivers of lipid metabolism. By combining transcriptional data at single-cell resolution with computational network analyses, we find that NAFLD is associated with high constitutive androstane receptor (CAR) expression. Mechanistically, CAR interacts with four functional modules: cholesterol homeostasis, bile acid metabolism, fatty acid metabolism, and estrogen response. Nuclear expression of CAR positively correlates with steatohepatitis in human livers. These findings demonstrate significant cellular differences in lipid signatures and identify functional networks linked to hepatic steatosis in mice and humans.

Development and Validation of a Score for Fibrotic Nonalcoholic Steatohepatitis.

BACKGROUND & AIMS: Noninvasive assessment of histological features of nonalcoholic fatty liver disease (NAFLD) has been an intensive research area over the last decade. Herein, we aimed to develop a simple noninvasive score using routine laboratory tests to identify, among individuals at high risk for NAFLD, those with fibrotic nonalcoholic steatohepatitis (NASH) defined as NASH, NAFLD activity score ≥4, and fibrosis stage ≥2. METHODS: The derivation cohort included 264 morbidly obese individuals undergoing intraoperative liver biopsy in Rome, Italy. The best predictive model was developed and internally validated using a bootstrapping stepwise logistic regression analysis (2000 bootstrap samples). Performance was estimated by the area under the receiver operating characteristic curve (AUROC). External validation was assessed in 3 independent European cohorts (Finland, n = 370; Italy, n = 947; England, n = 5368) of individuals at high risk for NAFLD. RESULTS: The final predictive model, designated as Fibrotic NASH Index (FNI), combined aspartate aminotransferase, high-density lipoprotein cholesterol, and hemoglobin A1c. The performance of FNI for fibrotic NASH was satisfactory in both derivation and external validation cohorts (AUROC = 0.78 and AUROC = 0.80-0.95, respectively). In the derivation cohort, rule-out and rule-in cutoffs were 0.10 for sensitivity ≥0.89 (negative predictive value, 0.93) and 0.33 for specificity ≥0.90 (positive predictive value, 0.57), respectively. In the external validation cohorts, sensitivity ranged from 0.87 to 1 (negative predictive value, 0.99-1) and specificity from 0.73 to 0.94 (positive predictive value, 0.12-0.49) for rule-out and rule-in cutoff, respectively. CONCLUSION: FNI is an accurate, simple, and affordable noninvasive score which can be used to screen for fibrotic NASH in individuals with dysmetabolism in primary health care.

Risk of advanced fibrosis in first-degree relatives of patients with nonalcoholic fatty liver disease.

BACKGROUNDA pilot, single-center study showed that first-degree relatives of probands with nonalcoholic fatty liver disease (NAFLD) cirrhosis have a high risk of advanced fibrosis. We aimed to validate these findings using 2 independent cohorts from the US and Europe.METHODSThis prospective study included probands with NAFLD with advanced fibrosis, NAFLD without advanced fibrosis, and non-NAFLD, with at least 1 first-degree relative. A total of 396 first-degree relatives - 220 in a derivation cohort and 176 in a validation cohort - were enrolled in the study, and liver fibrosis was evaluated using magnetic resonance elastography and other noninvasive imaging modalities. The primary outcome was prevalence of advanced fibrosis in first-degree relatives.RESULTSPrevalence of advanced fibrosis in first-degree relatives of probands with NAFLD with advanced fibrosis, NAFLD without advanced fibrosis, and non-NAFLD was 15.6%, 5.9%, and 1.3%, respectively (P = 0.002), in the derivation cohort, and 14.0%, 2.6%, and 1.3%, respectively (P = 0.004), in the validation cohort. In multivariable-adjusted logistic regression models, age of ≥50 years (adjusted OR [aOR]: 2.63, 95% CI 1.0-6.7), male sex (aOR: 3.79, 95% CI 1.6-9.2), diabetes mellitus (aOR: 3.37, 95% CI 1.3-9), and a first-degree relative with NAFLD with advanced fibrosis (aOR: 11.8, 95% CI 2.5-57) were significant predictors of presence of advanced fibrosis (all P < 0.05).CONCLUSIONFirst-degree relatives of probands with NAFLD with advanced fibrosis have significantly increased risk of advanced fibrosis. Routine screening should be done in the first-degree relatives of patients with advanced fibrosis.FUNDINGSupported by NCATS (5UL1TR001442), NIDDK (U01DK061734, U01DK130190, R01DK106419, R01DK121378, R01DK124318, P30DK120515, K23DK119460), NHLBI (P01HL147835), and NIAAA (U01AA029019); Academy of Finland grant 309263; the Novo Nordisk, EVO, and Sigrid Jusélius Foundations; and the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement 777377. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and the EFPIA.

PSD3 downregulation confers protection against fatty liver disease.

Fatty liver disease (FLD) is a growing health issue with burdening unmet clinical needs. FLD has a genetic component but, despite the common variants already identified, there is still a missing heritability component. Using a candidate gene approach, we identify a locus (rs71519934) at the Pleckstrin and Sec7 domain-containing 3 (PSD3) gene resulting in a leucine to threonine substitution at position 186 of the protein (L186T) that reduces susceptibility to the entire spectrum of FLD in individuals at risk. PSD3 downregulation by short interfering RNA reduces intracellular lipid content in primary human hepatocytes cultured in two and three dimensions, and in human and rodent hepatoma cells. Consistent with this, Psd3 downregulation by antisense oligonucleotides in vivo protects against FLD in mice fed a non-alcoholic steatohepatitis-inducing diet. Thus, translating these results to humans, PSD3 downregulation might be a future therapeutic option for treating FLD.

Distinct contributions of metabolic dysfunction and genetic risk factors in the pathogenesis of non-alcoholic fatty liver disease.

BACKGROUND & AIMS: There is substantial inter-individual variability in the risk of non-alcoholic fatty liver disease (NAFLD). Part of which is explained by insulin resistance (IR) ('MetComp') and part by common modifiers of genetic risk ('GenComp'). We examined how IR on the one hand and genetic risk on the other contribute to the pathogenesis of NAFLD. METHODS: We studied 846 individuals: 492 were obese patients with liver histology and 354 were individuals who underwent intrahepatic triglyceride measurement by proton magnetic resonance spectroscopy. A genetic risk score was calculated using the number of risk alleles in PNPLA3, TM6SF2, MBOAT7, HSD17B13 and MARC1. Substrate concentrations were assessed by serum NMR metabolomics. In subsets of participants, non-esterified fatty acids (NEFAs) and their flux were assessed by D5-glycerol and hyperinsulinemic-euglycemic clamp (n = 41), and hepatic de novo lipogenesis (DNL) was measured by D2O (n = 61). RESULTS: We found that substrate surplus (increased concentrations of 28 serum metabolites including glucose, glycolytic intermediates, and amino acids; increased NEFAs and their flux; increased DNL) characterized the 'MetComp'. In contrast, the 'GenComp' was not accompanied by any substrate excess but was characterized by an increased hepatic mitochondrial redox state, as determined by serum ß-hydroxybutyrate/acetoacetate ratio, and inhibition of hepatic pathways dependent on tricarboxylic acid cycle activity, such as DNL. Serum ß-hydroxybutyrate/acetoacetate ratio correlated strongly with all histological features of NAFLD. IR and hepatic mitochondrial redox state conferred additive increases in histological features of NAFLD. CONCLUSIONS: These data show that the mechanisms underlying 'Metabolic' and 'Genetic' components of NAFLD are fundamentally different. These findings may have implications with respect to the diagnosis and treatment of NAFLD. LAY SUMMARY: The pathogenesis of non-alcoholic fatty liver disease can be explained in part by a metabolic component, including obesity, and in part by a genetic component. Herein, we demonstrate that the mechanisms underlying these components are fundamentally different: the metabolic component is characterized by hepatic oversupply of substrates, such as sugars, lipids and amino acids. In contrast, the genetic component is characterized by impaired hepatic mitochondrial function, making the liver less able to metabolize these substrates.

Exposure to environmental contaminants is associated with altered hepatic lipid metabolism in non-alcoholic fatty liver disease.

BACKGROUND & AIMS: Recent experimental models and epidemiological studies suggest that specific environmental contaminants (ECs) contribute to the initiation and pathology of non-alcoholic fatty liver disease (NAFLD). However, the underlying mechanisms linking EC exposure with NAFLD remain poorly understood and there is no data on their impact on the human liver metabolome. Herein, we hypothesized that exposure to ECs, particularly perfluorinated alkyl substances (PFAS), impacts liver metabolism, specifically bile acid metabolism. METHODS: In a well-characterized human NAFLD cohort of 105 individuals, we investigated the effects of EC exposure on liver metabolism. We characterized the liver (via biopsy) and circulating metabolomes using 4 mass spectrometry-based analytical platforms, and measured PFAS and other ECs in serum. We subsequently compared these results with an exposure study in a PPARa-humanized mouse model. RESULTS: PFAS exposure appears associated with perturbation of key hepatic metabolic pathways previously found altered in NAFLD, particularly those related to bile acid and lipid metabolism. We identified stronger associations between the liver metabolome, chemical exposure and NAFLD-associated clinical variables (liver fat content, HOMA-IR), in females than males. Specifically, we observed PFAS-associated upregulation of bile acids, triacylglycerols and ceramides, and association between chemical exposure and dysregulated glucose metabolism in females. The murine exposure study further corroborated our findings, vis-à-vis a sex-specific association between PFAS exposure and NAFLD-associated lipid changes. CONCLUSIONS: Females may be more sensitive to the harmful impacts of PFAS. Lipid-related changes subsequent to PFAS exposure may be secondary to the interplay between PFAS and bile acid metabolism. LAY SUMMARY: There is increasing evidence that specific environmental contaminants, such as perfluorinated alkyl substances (PFAS), contribute to the progression of non-alcoholic fatty liver disease (NAFLD). However, it is poorly understood how these chemicals impact human liver metabolism. Here we show that human exposure to PFAS impacts metabolic processes associated with NAFLD, and that the effect is different in females and males.

Obesity Modifies the Performance of Fibrosis Biomarkers in Nonalcoholic Fatty Liver Disease.

CONTEXT: Guidelines recommend blood-based fibrosis biomarkers to identify advanced nonalcoholic fatty liver disease (NAFLD), which is particularly prevalent in patients with obesity. OBJECTIVE: To study whether the degree of obesity affects the performance of liver fibrosis biomarkers in NAFLD. DESIGN: Cross-sectional cohort study comparing simple fibrosis scores [Fibrosis-4 Index (FIB-4); NAFLD Fibrosis Score (NFS); aspartate aminotransferase to platelet ratio index; BARD (body mass index, aspartate-to-alanine aminotransferase ratio, diabetes); Hepamet Fibrosis Score (HFS)] and newer scores incorporating neo-epitope biomarkers PRO-C3 (ADAPT, FIBC3) or cytokeratin 18 (MACK-3). SETTING: Tertiary referral center. PATIENTS: We recruited overweight/obese patients from endocrinology (n = 307) and hepatology (n = 71) clinics undergoing a liver biopsy [median body mass index (BMI) 40.3 (interquartile range 36.0-44.7) kg/m2]. Additionally, we studied 859 less obese patients with biopsy-proven NAFLD to derive BMI-adjusted cutoffs for NFS. MAIN OUTCOME MEASURES: Biomarker area under the receiver operating characteristic (AUROC), sensitivity, specificity, and predictive values to identify histological stage ≥F3 fibrosis or nonalcoholic steatohepatitis with ≥F2 fibrosis [fibrotic nonalcoholic steatohepatitis (NASH)]. RESULTS: The scores with an AUROC ≥0.85 to identify ≥F3 fibrosis were ADAPT, FIB-4, FIBC3, and HFS. For fibrotic NASH, the best predictors were MACK-3 and ADAPT. The specificities of NFS, BARD, and FIBC3 deteriorated as a function of BMI. We derived and validated new cutoffs for NFS to rule in/out ≥F3 fibrosis in groups with BMIs <30.0, 30.0 to 39.9, and ≥40.0 kg/m2. This optimized its performance at all levels of BMI. Sequentially combining FIB-4 with ADAPT or FIBC3 increased specificity to diagnose ≥F3 fibrosis. CONCLUSIONS: In obese patients, the best-performing fibrosis biomarkers are ADAPT and the inexpensive FIB-4, which are unaffected by BMI. The widely used NFS loses specificity in obese individuals, which may be corrected with BMI-adjusted cutoffs.

Assessment of Lifestyle Factors Helps to Identify Liver Fibrosis Due to Non-Alcoholic Fatty Liver Disease in Obesity.

Only some individuals with obesity develop liver fibrosis due to non-alcoholic fatty liver disease (NAFLD-fibrosis). We determined whether detailed assessment of lifestyle factors in addition to physical, biochemical and genetic factors helps in identification of these patients. A total of 100 patients with obesity (mean BMI 40.0 ± 0.6 kg/m2) referred for bariatric surgery at the Helsinki University Hospital underwent a liver biopsy to evaluate liver histology. Physical activity was determined by accelerometer recordings and by the Modifiable Activity Questionnaire, diet by the FINRISK Food Frequency Questionnaire, and other lifestyle factors, such as sleep patterns and smoking, by face-to-face interviews. Physical and biochemical parameters and genetic risk score (GRS based on variants in PNPLA3, TM6SF2, MBOAT7 and HSD17B13) were measured. Of all participants 49% had NAFLD-fibrosis. Independent predictors of NAFLD-fibrosis were low moderate-to-vigorous physical activity, high red meat intake, low carbohydrate intake, smoking, HbA1c, triglycerides and GRS. A model including these factors (areas under the receiver operating characteristics curve (AUROC) 0.90 (95% CI 0.84-0.96)) identified NAFLD-fibrosis significantly more accurately than a model including all but lifestyle factors (AUROC 0.82 (95% CI 0.73-0.91)) or models including lifestyle, physical and biochemical, or genetic factors alone. Assessment of lifestyle parameters in addition to physical, biochemical and genetic factors helps to identify obese patients with NAFLD-fibrosis.

Exome-Wide Association Study on Alanine Aminotransferase Identifies Sequence Variants in the GPAM and APOE Associated With Fatty Liver Disease.

BACKGROUND & AIMS: Fatty liver disease (FLD) is a growing epidemic that is expected to be the leading cause of end-stage liver disease within the next decade. Both environmental and genetic factors contribute to the susceptibility of FLD. Several genetic variants contributing to FLD have been identified in exome-wide association studies. However, there is still a missing hereditability indicating that other genetic variants are yet to be discovered. METHODS: To find genes involved in FLD, we first examined the association of missense and nonsense variants with alanine aminotransferase at an exome-wide level in 425,671 participants from the UK Biobank. We then validated genetic variants with liver fat content in 8930 participants in whom liver fat measurement was available, and replicated 2 genetic variants in 3 independent cohorts comprising 2621 individuals with available liver biopsy. RESULTS: We identified 190 genetic variants independently associated with alanine aminotransferase after correcting for multiple testing with Bonferroni method. The majority of these variants were not previously associated with this trait. Among those associated, there was a striking enrichment of genetic variants influencing lipid metabolism. We identified the variants rs2792751 in GPAM/GPAT1, the gene encoding glycerol-3-phosphate acyltransferase, mitochondrial, and rs429358 in APOE, the gene encoding apolipoprotein E, as robustly associated with liver fat content and liver disease after adjusting for multiple testing. Both genes affect lipid metabolism in the liver. CONCLUSIONS: We identified 2 novel genetic variants in GPAM and APOE that are robustly associated with steatosis and liver damage. These findings may help to better elucidate the genetic susceptibility to FLD onset and progression.

LPIAT1/MBOAT7 depletion increases triglyceride synthesis fueled by high phosphatidylinositol turnover.

OBJECTIVE: Non-alcoholic fatty liver disease (NAFLD) is a common prelude to cirrhosis and hepatocellular carcinoma. The genetic rs641738 C>T variant in the lysophosphatidylinositol acyltransferase 1 (LPIAT1)/membrane bound O-acyltransferase domain-containing 7, which incorporates arachidonic acid into phosphatidylinositol (PI), is associated with the entire spectrum of NAFLD. In this study, we investigated the mechanism underlying this association in mice and cultured human hepatocytes. DESIGN: We generated the hepatocyte-specific Lpiat1 knockout mice to investigate the function of Lpiat1 in vivo. We also depleted LPIAT1 in cultured human hepatic cells using CRISPR-Cas9 systems or siRNA. The effect of LPIAT1-depletion on liver fibrosis was examined in mice fed high fat diet and in liver spheroids. Lipid species were measured using liquid chromatography-electrospray ionisation mass spectrometry. Lipid metabolism was analysed using radiolabeled glycerol or fatty acids. RESULTS: The hepatocyte-specific Lpiat1 knockout mice developed hepatic steatosis spontaneously, and hepatic fibrosis on high fat diet feeding. Depletion of LPIAT1 in cultured hepatic cells and in spheroids caused triglyceride accumulation and collagen deposition. The increase in hepatocyte fat content was due to a higher triglyceride synthesis fueled by a non-canonical pathway. Indeed, reduction in the PI acyl chain remodelling caused a high PI turnover, by stimulating at the same time PI synthesis and breakdown. The degradation of PI was mediated by a phospholipase C, which produces diacylglycerol, a precursor of triglyceride. CONCLUSION: We found a novel pathway fueling triglyceride synthesis in hepatocytes, by a direct metabolic flow of PI into triglycerides. Our findings provide an insight into the pathogenesis and therapeutics of NAFLD.

The PNPLA3-I148M Variant Confers an Antiatherogenic Lipid Profile in Insulin-resistant Patients.

CONTEXT: The I148M (rs738409-G) variant in PNPLA3 increases liver fat content but may be protective against cardiovascular disease. Insulin resistance (IR) amplifies the effect of PNPLA3-I148M on liver fat. OBJECTIVE: To study whether PNPLA3-I148M confers an antihyperlipidemic effect in insulin-resistant patients. DESIGN: Cross-sectional study comparing the impact of PNPLA3-I148M on plasma lipids and lipoproteins in 2 cohorts, both divided into groups based on rs738409-G allele carrier status and median HOMA-IR. SETTING: Tertiary referral center. PATIENTS: A total of 298 obese patients who underwent a liver biopsy during bariatric surgery (bariatric cohort: age 49 ±â€…9 years, body mass index [BMI] 43.2 ±â€…6.8 kg/m2), and 345 less obese volunteers in whom liver fat was measured by proton magnetic resonance spectroscopy (nonbariatric cohort: age 45 ±â€…14 years, BMI 29.7 ±â€…5.7 kg/m2). MAIN OUTCOME MEASURES: Nuclear magnetic resonance profiling of plasma lipids, lipoprotein particle subclasses and their composition. RESULTS: In both cohorts, individuals carrying the PNPLA3-I148M variant had significantly higher liver fat content than noncarriers. In insulin-resistant and homozygous carriers, PNPLA3-I148M exerted a distinct antihyperlipidemic effect with decreased very-low-density lipoprotein (VLDL) and low-density lipoprotein (LDL) particles and their constituents, and increased high-density lipoprotein particles and their constituents, compared with noncarriers. VLDL particles were smaller and LDL particles larger in PNPLA3-I148M carriers. These changes were geometrically opposite to those due to IR. PNPLA3-I148M did not have a measurable effect in patients with lower IR, and its effect was smaller albeit still significant in the less obese than in the obese cohort. CONCLUSIONS: PNPLA3-I148M confers an antiatherogenic plasma lipid profile particularly in insulin-resistant individuals.