ANGPTL3 Downregulation Increases Intracellular Lipids by Reducing Energy Utilization.

BACKGROUND: ANGPTL3 (angiopoietin-like protein 3) is a circulating protein with a key role in maintaining lipoprotein homeostasis. A monoclonal antibody against ANGPTL3 is an approved and well-tolerated treatment to reduce lipoproteins in familial hypercholesterolemia homozygotes. However, the reduction of hepatic ANGPTL3 synthesis using an antisense oligonucleotide unexpectedly resulted in a dose-dependent increase in liver lipid content and circulating transaminases, resulting in the termination of the clinical trial. Meanwhile, the use of silencing RNAs remains an area of active investigation. Our study sought to investigate whether intracellular downregulation of ANGPTL3 may lead to a primary increase in neutral lipids within the hepatocyte. METHODS: We downregulated ANGPTL3 by silencing RNA in primary human hepatocytes 3-dimensional spheroids, HepG2/LX-2 3-dimensional spheroids, and in HepG2, Hep3B2, and Huh7 cultured in 2 dimensions. RESULTS: ANGPTL3 downregulation increased neutral lipids in all models investigated. Interestingly, ANGPTL3 induced lower intracellular deiodinase type 1 protein levels resulting in a reduction in beta-oxidation and causing an increase in triglycerides stored in lipid droplets. CONCLUSIONS: In conclusion, intracellular ANGPTL3 downregulation by silencing RNA led to an increase in triglycerides content due to a reduction in energy substrate utilization resembling a primary intracellular hepatocyte hypothyroidism.

Partitioned polygenic risk scores identify distinct types of metabolic dysfunction-associated steatotic liver disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses an excess of triglycerides in the liver, which can lead to cirrhosis and liver cancer. While there is solid epidemiological evidence of MASLD coexisting with cardiometabolic disease, several leading genetic risk factors for MASLD do not increase the risk of cardiovascular disease, suggesting no causal relationship between MASLD and cardiometabolic derangement. In this work, we leveraged measurements of visceral adiposity and identified 27 novel genetic loci associated with MASLD. Among these loci, we replicated 6 in several independent cohorts. Next, we generated two partitioned polygenic risk scores (PRS) based on the mechanism of genetic association with MASLD encompassing intra-hepatic lipoprotein retention. The two PRS suggest the presence of at least two distinct types of MASLD, one confined to the liver resulting in a more aggressive liver disease and one that is systemic and results in a higher risk of cardiometabolic disease.

Interaction between estrogen receptor-α and PNPLA3 p.I148M variant drives fatty liver disease susceptibility in women.

Fatty liver disease (FLD) caused by metabolic dysfunction is the leading cause of liver disease and the prevalence is rising, especially in women. Although during reproductive age women are protected against FLD, for still unknown and understudied reasons some develop rapidly progressive disease at the menopause. The patatin-like phospholipase domain-containing 3 (PNPLA3) p.I148M variant accounts for the largest fraction of inherited FLD variability. In the present study, we show that there is a specific multiplicative interaction between female sex and PNPLA3 p.I148M in determining FLD in at-risk individuals (steatosis and fibrosis, P < 10-10; advanced fibrosis/hepatocellular carcinoma, P = 0.034) and in the general population (P < 10-7 for alanine transaminase levels). In individuals with obesity, hepatic PNPLA3 expression was higher in women than in men (P = 0.007) and in mice correlated with estrogen levels. In human hepatocytes and liver organoids, PNPLA3 was induced by estrogen receptor-α (ER-α) agonists. By chromatin immunoprecipitation and luciferase assays, we identified and characterized an ER-α-binding site within a PNPLA3 enhancer and demonstrated via CRISPR-Cas9 genome editing that this sequence drives PNPLA3 p.I148M upregulation, leading to lipid droplet accumulation and fibrogenesis in three-dimensional multilineage spheroids with stellate cells. These data suggest that a functional interaction between ER-α and PNPLA3 p.I148M variant contributes to FLD in women.

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.

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.

Cellular Genome-Scale Metabolic Modeling Identifies New Potential Drug Targets Against Hepatocellular Carcinoma.

Genome-scale metabolic modeling (GEM) is one of the key approaches to unpack cancer metabolism and for discovery of new drug targets. In this study, we report the Transcriptional Regulated Flux Balance Analysis-CORE (TRFBA-), an algorithm for GEM using key growth-correlated reactions using hepatocellular carcinoma (HCC), an important global health burden, as a case study. We generated a HepG2 cell-specific GEM by integrating this cell line transcriptomic data with a generic human metabolic model to forecast potential drug targets for HCC. A total of 108 essential genes for growth were predicted by the TRFBA-CORE. These genes were enriched for metabolic pathways involved in cholesterol, sterol, and steroid biosynthesis. Furthermore, we silenced a predicted essential gene, 11-beta dehydrogenase hydroxysteroid type 2 (HSD11B2), in HepG2 cells resulting in a reduction in cell viability. To further identify novel potential drug targets in HCC, we examined the effect of nine drugs targeting the essential genes, and observed that most drugs inhibited the growth of HepG2 cells. Some of these drugs in this model performed better than Sorafenib, the first-line therapeutic against HCC. A HepG2 cell-specific GEM highlights sterol metabolism to be essential for cell growth. HSD11B2 downregulation results in lower cell growth. Most of the compounds, selected by drug repurposing approach, show a significant inhibitory effect on cell growth in a wide range of concentrations. These findings offer new molecular leads for drug discovery for hepatic cancer while also illustrating the importance of GEM and drug repurposing in cancer therapeutics innovation.

Rare ATG7 genetic variants predispose patients to severe fatty liver disease.

BACKGROUND & AIMS: Non-alcoholic fatty liver disease (NAFLD) is the leading cause of liver disorders and has a strong heritable component. The aim of this study was to identify new loci that contribute to severe NAFLD by examining rare variants. METHODS: We performed whole-exome sequencing in individuals with NAFLD and advanced fibrosis or hepatocellular carcinoma (n = 301) and examined the enrichment of likely pathogenic rare variants vs. the general population. This was followed by validation at the gene level. RESULTS: In patients with severe NAFLD, we observed an enrichment of the p.P426L variant (rs143545741 C>T; odds ratio [OR] 5.26, 95% CI 2.1-12.6; p = 0.003) of autophagy-related 7 (ATG7), which we characterized as a loss-of-function, vs. the general population, and an enrichment in rare variants affecting the catalytic domain (OR 13.9; 95% CI 1.9-612; p = 0.002). In the UK Biobank cohort, loss-of-function ATG7 variants increased the risk of cirrhosis and hepatocellular carcinoma (OR 3.30; 95% CI 1.1-7.5 and OR 12.30, 95% CI 2.6-36, respectively; p <0.001 for both). The low-frequency loss-of-function p.V471A variant (rs36117895 T>C) was also associated with severe NAFLD in the clinical cohort (OR 1.7; 95% CI 1.2-2.5; p = 0.003), predisposed to hepatocellular ballooning (p = 0.007) evolving to fibrosis in the Liver biopsy cohort (n = 2,268), and was associated with liver injury in the UK Biobank (aspartate aminotransferase levels, p <0.001), with a larger effect in severely obese individuals in whom it was linked to hepatocellular carcinoma (p = 0.009). ATG7 protein localized to periportal hepatocytes, particularly in the presence of ballooning. In the Liver Transcriptomic cohort (n = 125), ATG7 expression correlated with suppression of the TNFα pathway, which was conversely upregulated in p.V471A carriers. CONCLUSIONS: We identified rare and low-frequency ATG7 loss-of-function variants that promote NAFLD progression by impairing autophagy and facilitating ballooning and inflammation. LAY SUMMARY: We found that rare mutations in a gene called autophagy-related 7 (ATG7) increase the risk of developing severe liver disease in individuals with dysmetabolism. These mutations cause an alteration in protein function and impairment of self-renewal of cellular content, leading to liver damage and inflammation.

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.

Accuracy of controlled attenuation parameter for assessing liver steatosis in individuals with morbid obesity before bariatric surgery.

BACKGROUND & AIMS: The ultrasound-based controlled attenuation parameter (CAP) is a non-invasive tool widely validated for assessing liver steatosis across different etiologies. However, few studies, with liver biopsy available, have investigated its performance in individuals with morbid obesity. Herein, we aimed to evaluate the diagnostic accuracy of CAP in participants with morbid obesity from the MAFALDA study before bariatric surgery. METHODS: A total of 120 individuals with valid examinations within three months from bariatric surgery were included. Clinical, laboratory, FibroScan® (XL probe), and liver biopsy data were collected using standardized procedures. The overall accuracy of CAP for detecting liver steatosis was estimated by the area under the receiver-operating characteristics curve (AUROC). Optimal cut-offs were chosen at points with the highest Youden index. RESULTS: The AUROCs of CAP for detecting S ≥ S1, S ≥ S2, and S = S3 were 0.91 (95% CI 0.86-0.97), 0.83 (95% CI 0.76-0.90), and 0.86 (95% CI 0.79-0.94), respectively. The best CAP cut-offs for S ≥ S1, S ≥ S2, and S = S3 were 300 dB/m (95% CI 275-316), 328 dB/m (95% CI 296-345), and 344 dB/m (95% CI 343-352), respectively. CAP values were independently influenced by steatosis grade (estimate 20.60, 95% CI 12.70-28.40, P = 1.05 × 10-6 ). The AUROC of FibroScan-AST (FAST) score for detecting progressive non-alcoholic steatohepatitis was 0.76 (95% CI 0.66-0.86). CONCLUSIONS: In individuals with morbid obesity, CAP measured by XL probe is an accurate non-invasive tool for grading liver steatosis. Measurement of liver fat content by CAP may help identify those eligible for bariatric procedures and estimate the effect of bariatric surgery on hepatic steatosis. LAY SUMMARY: The ultrasound-based controlled attenuation parameter (CAP) by using the XL probe has an excellent performance for grading liver steatosis among individuals with morbid obesity. CAP may represent an accurate tool for the non-invasive assessment of liver steatosis among individuals with morbid obesity before and after bariatric surgery.

A Polygenic Risk Score to Refine Risk Stratification and Prediction for Severe Liver Disease by Clinical Fibrosis Scores.

BACKGROUND & AIMS: A polygenic risk score based on well-known genetic variants in PNPLA3, TM6SF2, MBOAT7, and GCKR predicts hepatic fat content (polygenic risk score-hepatic fat content [PRS-HFC]). Here, we hypothesized that the addition of PRS-HFC to clinical fibrosis scores may improve risk stratification and prediction of severe liver disease (SLD). METHODS: We used data from 266,687 individuals in the UK Biobank, evaluating the incidence of cirrhosis, decompensated liver disease, hepatocellular carcinoma, and/or liver transplantation during a median follow-up period of 9 years. Nonalcoholic fatty liver disease fibrosis score, Fibrosis-4, aspartate aminotransferase-to-platelet ratio, BARD, and Forns scores, and PRS-HFC, were computed. All analyses were stratified according to the presence of diabetes, obesity, and a positive fatty liver index (≥60). RESULTS: Unfavorable genetics (PRS-HFC, ≥0.396) further stratified the risk of SLD in subjects in intermediate-/high-risk classes of fibrosis scores, with a higher effect in those with metabolic risk factors, and the prediction was improved by integrating PRS-HFC (areas under the receiver operating characteristic increased for all scores with a P value of approximately 10-2 to 10-4, except for the aspartate aminotransferase-to-platelet ratio in the overall population and in subjects with obesity). PRS-HFC improved diagnostic accuracies and positive predictive values for SLD in intermediate-high clinical score risk classes. Risk stratification and prediction were not affected or were poorly affected by unfavorable genetics in subjects without metabolic risk factors. CONCLUSIONS: Integration of genetics with clinical fibrosis scores refines individual risk and prediction for SLD, mainly in individuals at risk for nonalcoholic fatty liver disease. These data provide evidence from a prospective cohort that common genetic variants capture additional prognostic insights not conveyed by validated clinical/biochemical parameters.

Inborn and acquired risk factors for severe liver disease in Europeans with type 2 diabetes from the UK Biobank.

BACKGROUND & AIMS: Type 2 diabetes is a major driver of fatty liver disease and its long-term complications. The aim of this study was to investigate the individual contribution of inborn and acquired risk factors for severe liver disease in individuals with type 2 diabetes from the UK Biobank study. METHODS: A total of 22,812 UK Biobank participants of European descent without clinical history of liver disease and liver cancer were prospectively followed for the development of severe liver disease, defined as a composite diagnosis of cirrhosis, decompensated liver disease, hepatocellular carcinoma, and/or liver transplantation from the National Health Service records. The contribution of inborn and acquired risk factors to the risk of incident severe liver disease was assessed by Cox proportional hazards models. RESULTS: During a median follow-up of 8.9 years (IQR 8.1-9.6), there were 279 individuals with severe liver disease, including 255 with cirrhosis and/or decompensated liver disease, 47 with hepatocellular carcinoma, and 5 with liver transplantation; death from severe liver disease occurred in 83 individuals. Risk factors independently associated with increased risk of incident severe liver disease included abnormal aspartate aminotransferase (adjusted hazard ratio [aHR] 4.85, 95% CI 2.76-8.54), decrease in serum albumin (aHR 2.39, 95% CI 1.76-3.24) and platelet count (aHR 1.12, 95% CI 1.09-1.16), cardiovascular disease (aHR 1.86, 95% CI 1.23-2.79), microalbuminuria (aHR 1.55, 95% CI 1.04-2.30), PNPLA3 rs738409 (aHR 1.67, 95% CI 1.27-2.18) and TM6SF2 rs58542926 (aHR 1.63, 95% CI 1.12-2.39), while the net effect of male sex was protective (aHR 0.49, 95% CI 0.26-0.94). CONCLUSIONS: These findings may help in clinical care to identify individuals with type 2 diabetes at risk of severe liver disease, in turn leading to personalised risk prediction and prevention strategies. LAY SUMMARY: Type 2 diabetes is a key driver of severe liver disease, namely cirrhosis, hepatocellular carcinoma, and liver-related mortality. In Europeans with type 2 diabetes from the prospective UK Biobank study, abnormal liver function, cardiovascular disease, microalbuminuria, and genetic variants in PNPLA3 and TM6SF2 genes are the major independent risk factors for severe liver disease. These findings may contribute in clinical care to identify and closely monitor individuals with type 2 diabetes at risk of developing severe liver disease, requiring more intensive follow-up strategies.

Disease-specific eQTL screening reveals an anti-fibrotic effect of AGXT2 in non-alcoholic fatty liver disease.

BACKGROUND & AIMS: Non-alcoholic fatty liver disease (NAFLD) poses an increasing clinical burden. Genome-wide association studies have revealed a limited contribution of genomic variants to the disease, requiring alternative but robust approaches to identify disease-associated variants and genes. We carried out a disease-specific expression quantitative trait loci (eQTL) screen to identify novel genetic factors that specifically act on NAFLD progression on the basis of genotype. METHODS: We recruited 125 Korean patients (83 with biopsy-proven NAFLD and 42 without NAFLD) and performed eQTL analyses using 21,272 transcripts and 3,234,941 genotyped and imputed single nucleotide polymorphisms. We then selected eQTLs that were detected only in the NAFLD group, but not in the control group (i.e., NAFLD-eQTLs). An additional cohort of 162 Korean individuals with NAFLD was used for replication. The function of the selected eQTL toward NAFLD development was validated using HepG2, primary hepatocytes and NAFLD mouse models. RESULTS: The NAFLD-specific eQTL screening yielded 242 loci. Among them, AGXT2, encoding alanine-glyoxylate aminotransferase 2, displayed decreased expression in patients with NAFLD homozygous for the non-reference allele of rs2291702, compared to no-NAFLD individuals with the same genotype (p = 4.79 × 10-6). This change was replicated in an additional 162 individuals, yielding a combined p value of 8.05 × 10-8 from a total of 245 patients with NAFLD and 42 controls. Knockdown of AGXT2 induced palmitate-overloaded hepatocyte death by increasing endoplasmic reticulum stress, and exacerbated NAFLD diet-induced liver fibrosis in mice, while overexpression of AGXT2 attenuated liver fibrosis and steatosis. CONCLUSIONS: We identified a new molecular role for AGXT2 in NAFLD. Our overall approach will serve as an efficient tool for uncovering novel genetic factors that contribute to liver steatosis and fibrosis in patients with NAFLD. LAY SUMMARY: Elucidating causal genes for non-alcoholic fatty liver disease (NAFLD) has been challenging due to limited tissue availability and the polygenic nature of the disease. Using liver and blood samples from 125 Korean individuals (83 with NAFLD and 42 without NAFLD), we devised a new analytic method to identify causal genes. Among the candidates, we found that AGXT2-rs2291702 protects against liver fibrosis in a genotype-dependent manner with the potential for therapeutic interventions. Our approach enables the discovery of causal genes that act on the basis of genotype.

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.

Non-invasive stratification of hepatocellular carcinoma risk in non-alcoholic fatty liver using polygenic risk scores.

BACKGROUND & AIMS: 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. METHODS: 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). RESULTS: 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). CONCLUSIONS: Our results are consistent with a causal relationship between hepatic fat and HCC. PRS improved the accuracy of HCC detection and may help stratify HCC risk in individuals with dysmetabolism, including those without severe liver fibrosis. Further studies are needed to validate our findings. LAY SUMMARY: By analyzing variations in genes that contribute to fatty liver disease, we developed two risk scores to help predict liver cancer in individuals with obesity-related metabolic complications. These risk scores can be easily tested in the clinic. We showed that the risk scores helped to identify the risk of liver cancer both in high-risk individuals and in the general population.

A benchmark-driven approach to reconstruct metabolic networks for studying cancer metabolism.

Genome-scale metabolic modeling has emerged as a promising way to study the metabolic alterations underlying cancer by identifying novel drug targets and biomarkers. To date, several computational methods have been developed to integrate high-throughput data with existing human metabolic reconstructions to generate context-specific cancer metabolic models. Despite a number of studies focusing on benchmarking the context-specific algorithms, no quantitative assessment has been made to compare the predictive performance of these methods. Here, we integrated various and different datasets used in previous works to design a quantitative platform to examine functional and consistency performance of several existing genome-scale cancer modeling approaches. Next, we used the results obtained here to develop a method for the reconstruction of context-specific metabolic models. We then compared the predictive power and consistency of networks generated by our method to other computational approaches investigated here. Our results showed a satisfactory performance of the developed method in most of the benchmarks. This benchmarking platform is of particular use in algorithm selection and assessing the performance of newly developed algorithms. More importantly, it can serve as guidelines for designing and developing new methods focusing on weaknesses and strengths of existing algorithms.