FibroGENE: A gene-based model for staging liver fibrosis

Artificial intelligence applied to 'omics data in liver disease: towards a personalised approach for diagnosis, prognosis and treatment

Advancements in omics technologies and artificial intelligence (AI) methodologies are fuelling our progress towards personalised diagnosis, prognosis and treatment strategies in hepatology. This review provides a comprehensive overview of the current landscape of AI methods used for analysis of omics data in liver diseases. We present an overview of the prevalence of different omics levels across various liver diseases, as well as categorise the AI methodology used across the studies. Specifically, we highlight the predominance of transcriptomic and genomic profiling and the relatively sparse exploration of other levels such as the proteome and methylome, which represent untapped potential for novel insights. Publicly available database initiatives such as The Cancer Genome Atlas and The International Cancer Genome Consortium have paved the way for advancements in the diagnosis and treatment of hepatocellular carcinoma. However, the same availability of large omics datasets remains limited for other liver diseases. Furthermore, the application of sophisticated AI methods to handle the complexities of multiomics datasets requires substantial data to train and validate the models and faces challenges in achieving bias-free results with clinical utility. Strategies to address the paucity of data and capitalise on opportunities are discussed. Given the substantial global burden of chronic liver diseases, it is imperative that multicentre collaborations be established to generate large-scale omics data for early disease recognition and intervention. Exploring advanced AI methods is also necessary to maximise the potential of these datasets and improve early detection and personalised treatment strategies.

MAFLD: an ideal framework for understanding disease phenotype in individuals of normal weight

The prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD) is significant, impacting almost one-third of the global population. MAFLD constitutes a primary cause of end-stage liver disease, liver cancer and the need for liver transplantation. Moreover, it has a strong association with increased mortality rates due to various extrahepatic complications, notably cardiometabolic diseases. While MAFLD is typically correlated with obesity, not all individuals with obesity develop the disease and a significant percentage of MAFLD occurs in patients without obesity, termed lean MAFLD. The clinical features, progression and underlying physiological mechanisms of patients with lean MAFLD remain inadequately characterized. The present review aims to provide a comprehensive summary of current knowledge on lean MAFLD and offer a perspective on defining MAFLD in individuals with normal weight. Key to this process is the concept of metabolic health and flexibility, which links states of dysmetabolism to the development of lean MAFLD. This perspective offers a more nuanced understanding of MAFLD and its underlying mechanisms and highlights the importance of considering the broader metabolic context in which the disease occurs. It also bridges the knowledge gap and offers insights that can inform clinical practice.

A machine learning-based model analysis for serum markers of liver fibrosis in chronic hepatitis B patients

Early assessment and accurate staging of liver fibrosis may be of great help for clinical diagnosis and treatment in patients with chronic hepatitis B (CHB). We aimed to identify serum markers and construct a machine learning (ML) model to reliably predict the stage of fibrosis in CHB patients. The clinical data of 618 CHB patients between February 2017 and September 2021 from Zhejiang Provincial People's Hospital were retrospectively analyzed, and these data as a training cohort to build the model. Six ML models were constructed based on logistic regression, support vector machine, Bayes, K-nearest neighbor, decision tree (DT) and random forest by using the maximum relevance minimum redundancy (mRMR) and gradient boosting decision tree (GBDT) dimensionality reduction selected features on the training cohort. Then, the resampling method was used to select the optimal ML model. In addition, a total of 571 patients from another hospital were used as an external validation cohort to verify the performance of the model. The DT model constructed based on five serological biomarkers included HBV-DNA, platelet, thrombin time, international normalized ratio and albumin, with the area under curve (AUC) values of the DT model for assessment of liver fibrosis stages (F0-1, F2, F3 and F4) in the training cohort were 0.898, 0.891, 0.907 and 0.944, respectively. The AUC values of the DT model for assessment of liver fibrosis stages (F0-1, F2, F3 and F4) in the external validation cohort were 0.906, 0.876, 0.931 and 0.933, respectively. The simulated risk classification based on the cutoff value showed that the classification performance of the DT model in distinguishing hepatic fibrosis stages can be accurately matched with pathological diagnosis results. ML model of five serum markers allows for accurate diagnosis of hepatic fibrosis stages, and beneficial for the clinical monitoring and treatment of CHB patients.

Prevalence and Crucial Parameters in Diabesity-Related Liver Fibrosis: A Preliminary Study

Diabetes and obesity have been recognized as confirmed risk factors for the occurrence of liver fibrosis. Despite the long-standing acknowledgment of "diabesity", the simultaneous existence of diabetes and obesity, scholarly literature has shown limited attention to this topic. The aim of this pilot study was to assess the prevalence of liver fibrosis among individuals with diabetes (specifically those who are obese) in order to identify the key factors associated with hepatofibrosis and determine the most important associations and differences between patients with and without liver fibrosis. The research included a total of 164 participants (48.17% had comorbid obesity). Liver elastography (Fibroscan) was performed on these individuals in addition to laboratory tests. Liver fibrosis was found in 34.76% of type 2 diabetes patients; male gender almost doubled the risk of hepatofibrosis (RR 1.81) and diabesity nearly tripled this risk (RR 2.81; however, in degree III of obesity, the risk was elevated to 3.65 times higher). Anisocytosis, thrombocytopenia, or elevated liver enzymes raised the incidence of liver fibrosis by 1.78 to 2.47 times. In these individuals, liver stiffness was negatively correlated with MCV, platelet count, and albumin concentration; GGTP activity and HbA1c percentage were positively correlated. The regression analysis results suggest that the concentration of albumin and the activity of GGTP are likely to have a substantial influence on the future management of liver fibrosis in patients with diabesity. The findings of this study can serve as the basis for subsequent investigations and actions focused on identifying potential therapeutic and diagnostic avenues.

Advances in Noninvasive Biomarkers for Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) currently represents one of the most common liver diseases worldwide. Early diagnosis and disease staging is crucial, since it is mainly asymptomatic, but can progress to nonalcoholic steatohepatitis (NASH) or cirrhosis or even lead to the development of hepatocellular carcinoma. Over time, efforts have been put into developing noninvasive diagnostic and staging methods in order to replace the use of a liver biopsy. The noninvasive methods used include imaging techniques that measure liver stiffness and biological markers, with a focus on serum biomarkers. Due to the impressive complexity of the NAFLD's pathophysiology, biomarkers are able to assay different processes involved, such as apoptosis, fibrogenesis, and inflammation, or even address the genetic background and "omics" technologies. This article reviews not only the currently validated noninvasive methods to investigate NAFLD but also the promising results regarding recently discovered biomarkers, including biomarker panels and the combination of the currently validated evaluation methods and serum markers.

Identification of Fast Progressors Among Patients With Nonalcoholic Steatohepatitis Using Machine Learning

Background and Aims

There is a high unmet need to develop noninvasive tools to identify nonalcoholic fatty liver disease/nonalcoholic steatohepatitis (NAFLD/NASH) patients at risk of fast progression to end-stage liver disease (ESLD). This study describes the development of a machine learning (ML) model using data around the first clinical evidence of NAFLD/NASH to identify patients at risk of future fast progression.

Methods

Adult patients with ESLD (cirrhosis or hepatocellular carcinoma) due to NAFLD/NASH were identified in Optum electronic health records (2007-2018 period). Patients were stratified into fast (0.5 and 3 years) and standard progressor (6-10 years) cohorts based on retrospectively established progression time between ESLD and the earliest observable disease, and characteristics were reported using descriptive statistics. Two ML models predicting fast progression were created, performance was compared, and top predictive features from the final model were compared between cohorts.

Results

Among a total of 4013 NAFLD patients with cirrhosis or hepatocellular carcinoma (mean age 58.6 ± 12.5; 65% female), 24% were fast (n = 951) and 25% standard (n = 992) progressors that were used for modeling. The cohorts were comparable for gender, body mass index, type 2 diabetes, and arterial hypertension, but differed significantly for obesity, hyperlipidemia, and age at index. The final model (NASH FASTmap) is a 44 feature light gradient boosting model which performed better (area under the curve [0.77], F1-score [0.74], accuracy [0.71], and precision [0.71]) than eXtreme gradient boosting model to predict fast progression.

Conclusion

Future fast progression to ESLD in NAFLD/NASH patients can be predicted from clinical data using ML. Electronic health record implementation of NASH FASTmap could support clinical assessment for risk stratification and potentially improve disease management.

Detangling the interrelations between MAFLD, insulin resistance, and key hormones

Metabolic dysfunction-associated fatty liver disease (MAFLD) has increasingly become a significant and highly prevalent cause of chronic liver disease, displaying a wide array of risk factors and pathophysiologic mechanisms of which only a few have so far been clearly elucidated. A bidirectional interaction between hormonal discrepancies and metabolic-related disorders, including obesity, type 2 diabetes mellitus (T2DM), and polycystic ovarian syndrome (PCOS) has been described. Since the change in nomenclature from non-alcoholic fatty liver disease (NAFLD) to MAFLD is based on the clear impact of metabolic elements on the disease, the reciprocal interactions of hormones such as insulin, adipokines (leptin and adiponectin), and estrogens have strongly pointed to the intrinsic links that lead to the heterogeneous epidemiology, clinical presentations, and risk factors involved in MAFLD in different populations. The objective of this work is twofold. Firstly, there is a brief discussion regarding the change in nomenclature as well as epidemiology, risk factors, and pathophysiologic mechanisms other than hormonal effects, which include nutrition and the gut microbiome, as well as genetic and epigenetic influences. Secondly, we review the basis of the most important hormonal factors involved in the development and progression of MAFLD that act both independently and in an interrelated manner.

Metabolic (dysfunction)-associated fatty liver disease in individuals of normal weight

Metabolic (dysfunction)-associated fatty liver disease (MAFLD) affects up to a third of the global population; its burden has grown in parallel with rising rates of type 2 diabetes mellitus and obesity. MAFLD increases the risk of end-stage liver disease, hepatocellular carcinoma, death and liver transplantation and has extrahepatic consequences, including cardiometabolic disease and cancers. Although typically associated with obesity, there is accumulating evidence that not all people with overweight or obesity develop fatty liver disease. On the other hand, a considerable proportion of patients with MAFLD are of normal weight, indicating the importance of metabolic health in the pathogenesis of the disease regardless of body mass index. The clinical profile, natural history and pathophysiology of patients with so-called lean MAFLD are not well characterized. In this Review, we provide epidemiological data on this group of patients and consider overall metabolic health and metabolic adaptation as a framework to best explain the pathogenesis of MAFLD and its heterogeneity in individuals of normal weight and in those who are above normal weight. This framework provides a conceptual schema for interrogating the MAFLD phenotype in individuals of normal weight that can translate to novel approaches for diagnosis and patient care.

Biomarkers of Metabolic (Dysfunction)-associated Fatty Liver Disease: An Update

The prevalence of metabolic (dysfunction)-associated fatty liver disease (MAFLD) is rapidly increasing and affects up to two billion individuals globally, and this has also resulted in increased risks for cirrhosis, hepatocellular carcinoma, and liver transplants. In addition, it has also been linked to extrahepatic consequences, such as cardiovascular disease, diabetes, and various types of cancers. However, only a small proportion of patients with MAFLD develop these complications. Therefore, the identification of high-risk patients is paramount. Liver fibrosis is the major determinant in developing these complications. Although, liver biopsy is still considered the gold standard for the assessment of patients with MAFLD. Because of its invasive nature, among many other limitations, the search for noninvasive biomarkers for MAFLD remains an area of intensive research. In this review, we provide an update on the current and future biomarkers of MAFLD, including a discussion of the associated genetics, epigenetics, microbiota, and metabolomics. We also touch on the next wave of multiomic-based biomarkers.

Advances in fibrosis biomarkers in nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) affects a quarter of the adult world population and the degree of liver fibrosis represents the best predictor of the development of liver-related outcomes. Easily applicable and well performing non-invasive fibrosis tests can overcome the limitations of liver biopsy and are of paramount importance to identify at-risk subjects in clinical practice. While tests with optimal performance and ease of use do not exist at this stage, available markers can be divided in three broad groups: simple serum tests, complex serum tests and elastographic methods. Simple scores (such as Fibrosis-4 and NAFLD Fibrosis Score) are based on readily available biochemical data and clinical features, while complex/proprietary tests (such as Fibrotest, Enhanced Liver Fibrosis and Hepascore) directly measure markers of fibrogenesis and fibrolysis, but have higher costs. Elastography techniques estimate the degree of fibrosis from liver stiffness and are based on either ultrasound or magnetic resonance (MR) imaging. MR elastography has better performance compared with sonographic techniques and is not affected by obesity and inflammation, but is highly costly and less available. In general, non-invasive tests are able to exclude the presence of fibrosis, but their positive predictive value is low to moderate and they lead to a high number of indeterminate results. In this context, a combination of different tests might increase accuracy while reducing gray-zone results. Their ability to predict future events and response to treatment is suboptimal and needs to be studied further. Finally, recent studies have tried different approaches, spanning from "omics" to the microbiome and micro-RNAs, with some promising results.

Stratifying individuals into non-alcoholic fatty liver disease risk levels using time series machine learning models

Non-alcoholic fatty liver disease (NAFLD) affects 25% of the population worldwide, and its prevalence is anticipated to increase globally. While most NAFLD patients are asymptomatic, NAFLD may progress to fibrosis, cirrhosis, cardiovascular disease, and diabetes. Research reports, with daunting results, show the challenge that NAFLD's burden causes to global population health. The current process for identifying fibrosis risk levels is inefficient, expensive, does not cover all potential populations, and does not identify the risk in time. Instead of invasive liver biopsies, we implemented a non-invasive fibrosis assessment process calculated from clinical data (accessed via EMRs/EHRs). We stratified patients' risks for fibrosis from 2007 to 2017 by modeling the risk in 5579 individuals. The process involved time-series machine learning models (Hidden Markov Models and Group-Based Trajectory Models) profiled fibrosis risk by modeling patients' latent medical status resulted in three groups. The high-risk group had abnormal lab test values and a higher prevalence of chronic conditions. This study can help overcome the inefficient, traditional process of detecting fibrosis via biopsies (that are also medically unfeasible due to their invasive nature, the medical resources involved, and costs) at early stages. Thus longitudinal risk assessment may be used to make population-specific medical recommendations targeting early detection of high risk patients, to avoid the development of fibrosis disease and its complications as well as decrease healthcare costs.

Update on genetics and epigenetics in metabolic associated fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) is becoming the most frequent chronic liver disease worldwide. Metabolic (dysfunction) associated fatty liver disease (MAFLD) is suggested to replace the nomenclature of NAFLD. For individuals with metabolic dysfunction, multiple NAFLD-related factors also contribute to the development and progression of MAFLD including genetics and epigenetics. The application of genome-wide association study (GWAS) and exome-wide association study (EWAS) uncovers single-nucleotide polymorphisms (SNPs) in MAFLD. In addition to the classic SNPs in PNPLA3, TM6SF2, and GCKR, some new SNPs have been found recently to contribute to the pathogenesis of liver steatosis. Epigenetic factors involving DNA methylation, histone modifications, non-coding RNAs regulations, and RNA methylation also play a critical role in MAFLD. DNA methylation is the most reported epigenetic modification. Developing a non-invasion biomarker to distinguish metabolic steatohepatitis (MASH) or liver fibrosis is ongoing. In this review, we summarized and discussed the latest progress in genetic and epigenetic factors of NAFLD/MAFLD, in order to provide potential clues for MAFLD treatment.

Genetics Is of the Essence to Face NAFLD

Nonalcoholic fatty liver disease (NAFLD) is the commonest cause of chronic liver disease worldwide. It is closely related to obesity, insulin resistance (IR) and dyslipidemia so much so it is considered the hepatic manifestation of the Metabolic Syndrome. The NAFLD spectrum extends from simple steatosis to nonalcoholic steatohepatitis (NASH), a clinical condition which may progress up to fibrosis, cirrhosis and hepatocellular carcinoma (HCC). NAFLD is a complex disease whose pathogenesis is shaped by both environmental and genetic factors. In the last two decades, several heritable modifications in genes influencing hepatic lipid remodeling, and mitochondrial oxidative status have been emerged as predictors of progressive hepatic damage. Among them, the patatin-like phospholipase domain-containing 3 (PNPLA3) p.I148M, the Transmembrane 6 superfamily member 2 (TM6SF2) p.E167K and the rs641738 membrane bound-o-acyltransferase domain-containing 7 (MBOAT7) polymorphisms are considered the most robust modifiers of NAFLD. However, a forefront frontier in the study of NAFLD heritability is to postulate score-based strategy, building polygenic risk scores (PRS), which aggregate the most relevant genetic determinants of NAFLD and biochemical parameters, with the purpose to foresee patients with greater risk of severe NAFLD, guaranteeing the most highly predictive value, the best diagnostic accuracy and the more precise individualized therapy.

A Sequential Algorithm Combining ADAPT and Liver Stiffness Can Stage Metabolic-Associated Fatty Liver Disease in Hospital-Based and Primary Care Patients

INTRODUCTION

Metabolic-associated fatty liver disease is common, with fibrosis the major determinant of adverse outcomes. Population-based screening tools with high diagnostic accuracy for the staging of fibrosis are lacking.

METHODS

Three independent cohorts, 2 with both liver biopsy and liver stiffness measurements (LSMs, n = 254 and 65) and a population sample (n = 713), were studied. The performance of a recently developed noninvasive algorithm (ADAPT [age, diabetes, PRO-C3 and platelets panel]) as well as aspartate aminotransferase-to-platelet ratio index, fibrosis-4, nonalcoholic fatty liver disease fibrosis score, and LSM was used to stage patients for significant (≥F2) and advanced (≥F3) fibrosis.

RESULTS

In the hospital-based cohorts, the N-terminal propeptide of type 3 collagen (Pro-C3) increased with fibrosis stage (P < 0.0001) and independently associated with advanced fibrosis (odds ratio = 1.091, 95% confidence interval [CI]: 1.053-1.113, P = 0.0001). ADAPT showed areas under the receiver operating characteristics curve of 0.831 (95% CI: 0.779-0.875) in the derivation and 0.879 (95% CI: 0.774-0.946) in the validation cohort for advanced fibrosis. This was superior to the existing fibrosis scores, aspartate aminotransferase-to-platelet ratio index, fibrosis-4, BARD (BMI, aspartate aminotransferase to alanine aminotransferase ratio [AAR], diabetes), and nonalcoholic fatty liver disease fibrosis score in most comparisons and comparable with LSM. Serial use of ADAPT and LSM had diagnostic accuracy of 92.5%, with 98% and 100% negative predictive value in the derivation and validation cohorts, respectively. In the population cohort, PRO-C3 associated with advanced fibrosis (P = 0.04), while ADAPT had a negative predictive value of 98% for excluding advanced fibrosis.

DISCUSSION

PRO-C3 and ADAPT reliably exclude advanced fibrosis in low-risk populations. The serial combination of ADAPT with LSM has high diagnostic accuracy with a low requirement for liver biopsy. The proposed algorithm would help stratify those who need biopsies and narrow down those patients who would need to be referred to specialty clinics.

NAFLD: a multi-faceted morbid spectrum with uncertain diagnosis and complicated management. Where do we stand? Review of the literature

NASH can be considered the "contemporary era pandemic", because of its global widespread in parallel with obesity, diabetes and metabolic dysfunction. It is a disease that often poses many difficulties, since making a early diagnosis is often impossible since specific diagnostic tests and criteria are missing: so, it needs a high degree of suspicion. Most of the times the evolution to its more severe and terminal step, NASH cirrhosis, is unavoidable and so are the social pressure on health sistem and economic consequences it brings back. In this work we aim to review the literature about both NAFLD and NASH, thus structuring a wide, comprehensive, 360 degree work with a focus on all major aspects of NAFLD, spanning from diagnosis, physiopathology and its repercussions on liver transplantation. Moreover we also focused on patients related issues both in pre- and post-transplant management (when these patients are listed for liver transplant). NAFLD and NASH are a contemporary plague, and an exaustive knowledge of the problem throughout all its aspects is necessary in order to lower economic weight that metabolic issues bring back and to have a open view to possible solutions to all management issues that NASH patients have and that are oten prohibitive to a definitive cure (for example cardiovascular risk in patients otherwise eligible to liver transplantation). We aim to offer a complete view on the actual knowledge about NAFLD and NASH, by an extensive review of the literature.

Interferon-λ rs12979860 genotype association with liver fibrosis in chronic hepatitis C (CHC) patients in the Pakistani population

Risk and progression of liver fibrosis and cirrhosis in chronic hepatitis C (CHC) patients is significantly influenced by host genetic factors in a polygenic manner. The rs12979860 genetic polymorphism in the interferon-λ3-interferon-λ4 (IFNL3-IFNL4) region has been found to be a major determinant of hepatic inflammatory and fibrotic progression in CHC patients of mainly Caucasian origin; however, it is not known if this association applies to other ethnicities, including Pakistani CHC patients. Here, we genotyped IFNL3-IFNL4 rs12979860 genetic variants in a sample set of 502 Pakistani patients with CHC and used logistic regression analysis to determine its association with the risk and progression of HCV-related fibrosis and cirrhosis. We demonstrate that the rs12979860 major (CC) genotype, despite not determining the risk of stage-specific hepatic fibrosis independently, is associated with a marginally significant risk of liver cirrhosis (OR: 1.64, p = 0.049) after an adjustment for age, gender, body mass index, HCV viral load, and liver enzymes. In a subgroup of CHC patients with sustained ALT levels of <60 IU/L, a more pronounced impact of the IFNL3-IFNL4 rs12979860 major (CC) genotype on advanced liver fibrosis (OR: 4.99, p = 0.017) and cirrhosis (OR: 3.34, p = 0.005) was seen. The present study suggests that IFNL3-IFNL4 rs12979860 polymorphism may also be a significant predictor of hepatic fibrosis and cirrhosis in Pakistani CHC patients, especially in those with normal or near-normal liver enzyme levels.

Development of a gene signature for predicting cirrhosis risk score of chronic liver disease associated with HCV infection in Egyptians

BACKGROUND

Complex diseases such as fibrosis are likely polygenic. Lately, cirrhosis risk score (CRS) clearly discriminated Chronic HCV patients with high-risk versus those with low-risk for cirrhosis better than clinical factors.

METHODS

Herein, the CRS was assessed via genotyping by allelic discrimination assays in 243 HCV Egyptian patients categorized into 164 patients didn't develop HCC (93 mild, 71 advanced fibrosis); and 79 patients developed HCC. APRI and FIB-4 scores were calculated, compared with CRS and correlated with degree of fibrosis progression.

RESULTS

Median of the three CRS, APRI and FIB-4 scores were significantly elevated in late fibrotic and HCC patients (p < 0.001); however CRS displayed proper discrimination (mild fibrosis (0.59; 0.4-0.75), advanced fibrosis (0.75; 0.7-0.86) and HCC (0.73; 0.57-0.77); (p < 0.001)). The ROC analysis of CRS score displayed modest accuracy to discriminate between mild and advanced fibrotic patient; AUC was 0.73; p < 0.0001), while AUC was only 0.57 (p = 0.05) for the discrimination between HCC and no HCC. Moreover, the combination of CRS, APRI and FIB4 lessened the power of correlation (AUC, 0.63 (p < 0.0001)) in fibrosis prognosis. In HCC prognosis, the combination of CRS, APRI and FIB4 in HCC patients showed modest accuracy with AUC, 0.59 (p = 0.0001).

CONCLUSION

The diagnostic accuracy of FIB-4 for predicting liver fibrosis was nearly identical to that of CRS, however the strength of CRS score stemmed from that it is built on 7 SNPs host genetic factor. Our study validates non invasive algorithms for fibrosis prognosis purposes which may aid in decision making for therapeutic intervention.

The NAFLD-MAFLD debate: Eminence vs evidence

Debates are inevitable in science and could be a powerful tool for addressing controversial topics as it promotes critical thinking and inspires individuals to consider alternate viewpoints. However, debates can help only to identify the issues that need to be clarified to address this question, but it can never help resolve the controversy itself. In the era of evidence-based medicine, the need for an evidence-based debate is mandatory. Polarising opinions and major debate have recently arisen in hepatology on the nomenclature and diagnostic criteria for fatty liver disease associated with metabolic dysfunction (non alcoholic fatty liver disease [NAFLD]-metabolic (dysfunction) associated fatty liver disease [MAFLD] debate). The aim of this viewpoint is to suggest a way to settle the debate through evidence. Descriptive review using PubMed to identify literature on the evidence and eminence-based medicine and studies comparing MAFLD and NAFLD criteria. The emerging studies comparing the performance of diagnostic criteria of NAFLD and MAFLD represent the dawn of a new era for reframing the ongoing debate by acquisition of the mandatory evidence that will both resolve the debate and lead to novel avenues of research. In conclusion, the time has come to hold debate and focus on gathering and building the evidence to settle it. It does not matter who wins the debate and once there is robust evidence, we should all follow it wherever it leads.

Non-alcoholic Fatty Liver and Liver Fibrosis Predictive Analytics: Risk Prediction and Machine Learning Techniques for Improved Preventive Medicine

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease worldwide, with a prevalence of 20%-30% in the general population. NAFLD is associated with increased risk of cardiovascular disease and may progress to cirrhosis with time. The purpose of this study was to predict the risks associated with NAFLD and advanced fibrosis on the Fatty Liver Index (FLI) and the 'NAFLD fibrosis 4' calculator (FIB-4), to enable physicians to make more optimal preventive medical decisions. A prospective cohort of apparently healthy volunteers from the Tel Aviv Medical Center Inflammation Survey (TAMCIS), admitted for their routine annual health check-up. Data from the TAMCIS database were subjected to machine learning classification models to predict individual risk after extensive data preparation that included the computation of independent variables over several time points. After incorporating the time covariates and other key variables, this technique outperformed the predictive power of current popular methods (an improvement in AUC above 0.82). New powerful factors were identified during the predictive process. The findings can be used for risk stratification and in planning future preventive strategies based on lifestyle modifications and medical treatment to reduce the disease burden. Interventions to prevent chronic disease can substantially reduce medical complications and the costs of the disease. The findings highlight the value of predictive analytic tools in health care environments. NAFLD constitutes a growing burden on the health system; thus, identification of the factors related to its incidence can make a strong contribution to preventive medicine.

MAFLD identifies patients with significant hepatic fibrosis better than NAFLD

BACKGROUND & AIMS

Diagnostic criteria for metabolic associated fatty liver disease (MAFLD) have been proposed, but not validated. We aimed to compare the diagnostic accuracy of the MAFLD definition vs the existing NAFLD criteria to identify patients with significant fibrosis and to characterize the impact of mild alcohol intake.

METHODS

We enrolled 765 Japanese patients with fatty liver (median age 54 years). MAFLD and NAFLD were diagnosed in 79.6% and 70.7% of patients respectively. Significant fibrosis was defined by FIB-4 index ≥1.3 and liver stiffness ≥6.6 kPa using shear wave elastography. Mild alcohol intake was defined as <20 g/day. Factors associated with significant fibrosis were analysed by logistic regression and decision-tree analyses.

RESULTS

Liver stiffness was higher in MAFLD compared to NAFLD (7.7 vs 6.8 kPa, P = .0010). In logistic regression, MAFLD (OR 4.401; 95% CI 2.144-10.629; P < .0001), alcohol intake (OR 1.761; 95% CI 1.081-2.853; P = .0234), and NAFLD (OR 1.721; 95%CI 1.009-2.951; P = .0463) were independently associated with significant fibrosis. By decision-tree analysis, MAFLD, but not NAFLD or alcohol consumption was the initial classifier for significant fibrosis. The sensitivity for detecting significant fibrosis was higher for MAFLD than NAFLD (93.9% vs 73.0%). In patients with MAFLD, even mild alcohol intake was associated with an increase in the prevalence of significant fibrosis (25.0% vs 15.5%; P = .0181).

CONCLUSIONS

The MAFLD definition better identifies a group with fatty liver and significant fibrosis evaluated by non-invasive tests. Moreover, in patients with MAFLD, even mild alcohol consumption is associated with worsening of hepatic fibrosis measures.

The diagnostic conundrum in non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) has become the most common liver alteration worldwide. It encompasses a spectrum of disorders that range from simple steatosis to a progressive form, defined non-alcoholic steatohepatitis (NASH), that can lead to advanced fibrosis and eventually cirrhosis and hepatocellular carcinoma. On liver histology, NASH is characterized by the concomitant presence of significant fat accumulation and inflammatory reaction with hepatocellular injury. Until now, liver biopsy is still required to differentiate simple steatosis from NASH and evaluate the degree of liver fibrosis. Unfortunately, this technique has well-known limitations, including invasiveness and expensiveness. Moreover, it may be biased by sampling error and intra- or inter-observed variability. Furthermore, due to the increasing prevalence of NAFLD worldwide, to program a systematic screening with liver biopsy is not imaginable. In recent years, different techniques were developed and validated with the aim of non-invasively identifying NASH and assess liver fibrosis degrees. The non-invasive tests range from simple blood-tests analyses to composite scores and complex imaging techniques. Nevertheless, even if they could represent cost-effective strategies for diagnosing NASH, advanced fibrosis and cirrhosis, their accuracy and consequent usefulness are to be discussed. With this aim, in this review the authors summarize the current state of non-invasive assessment of NAFLD. In particular, in addition to the well-established tests, the authors describe the future perspectives in this field, reporting the latest tests based on OMICS, gut-miocrobioma and micro-RNAs. Finally, the authors provide an accurate assessment of how these non-invasive tools perform in clinical practice depending on the clinical context, with the aim of giving the clinicians a useful tool to try to resolve the diagnostic conundrum of NAFLD.

History of Nonalcoholic Fatty Liver Disease

Based on the assumption that characterizing the history of a disease will help in improving practice while offering a clue to research, this article aims at reviewing the history of nonalcoholic fatty liver disease (NAFLD) in adults and children. To this end, we address the history of NAFLD histopathology, which begins in 1980 with Ludwig's seminal studies, although previous studies date back to the 19th century. Moreover, the principal milestones in the definition of genetic NAFLD are summarized. Next, a specific account is given of the evolution, over time, of our understanding of the association of NAFLD with metabolic syndrome, spanning from the outdated concept of "NAFLD as a manifestation of the Metabolic Syndrome", to the more appropriate consideration that NAFLD has, with metabolic syndrome, a mutual and bi-directional relationship. In addition, we also report on the evolution from first intuitions to more recent studies, supporting NAFLD as an independent risk factor for cardiovascular disease. This association probably has deep roots, going back to ancient Middle Eastern cultures, wherein the liver had a significance similar to that which the heart holds in contemporary society. Conversely, the notions that NAFLD is a forerunner of hepatocellular carcinoma and extra-hepatic cancers is definitely more modern. Interestingly, guidelines issued by hepatological societies have lagged behind the identification of NAFLD by decades. A comparative analysis of these documents defines both shared attitudes (e.g., ultrasonography and lifestyle changes as the first approaches) and diverging key points (e.g., the threshold of alcohol consumption, screening methods, optimal non-invasive assessment of liver fibrosis and drug treatment options). Finally, the principal historical steps in the general, cellular and molecular pathogenesis of NAFLD are reviewed. We conclude that an in-depth understanding of the history of the disease permits us to better comprehend the disease itself, as well as to anticipate the lines of development of future NAFLD research.

Genetic and metabolic factors: the perfect combination to treat metabolic associated fatty liver disease

The prevalence of nonalcoholic or more recently re-defined metabolic associated fatty liver disease (MAFLD) is rapidly growing worldwide. It is characterized by hepatic fat accumulation exceeding 5% of liver weight not attributable to alcohol consumption. MAFLD refers to an umbrella of conditions ranging from simple steatosis to nonalcoholic steatohepatitis which may finally progress to cirrhosis and hepatocellular carcinoma. MAFLD is closely related to components of the metabolic syndrome and to environmental factors. In addition to the latter, genetic predisposition plays a key role in MAFLD pathogenesis and strictly contributes to its progressive forms. The candidate genes which have been related to MAFLD hereditability are mainly involved in lipids remodeling, lipid droplets assembly, lipoprotein packaging and secretion, de novo lipogenesis, and mitochondrial redox status. In the recent years, it has emerged the opportunity to translate the genetics into clinics by aggregating the genetic variants mostly associated with MAFLD in polygenic risk scores. These scores might be used in combination with metabolic factors to identify those patients at higher risk to develop more severe liver disease and to schedule an individual therapeutic approach.

Advances in non-invasive assessment of hepatic fibrosis

Liver fibrosis should be assessed in all individuals with chronic liver disease as it predicts the risk of future liver-related morbidity and thus need for treatment, monitoring and surveillance. Non-invasive fibrosis tests (NITs) overcome many limitations of liver biopsy and are now routinely incorporated into specialist clinical practice. Simple serum-based tests (eg, Fibrosis Score 4, non-alcoholic fatty liver disease Fibrosis Score) consist of readily available biochemical surrogates and clinical risk factors for liver fibrosis (eg, age and sex). These have been extensively validated across a spectrum of chronic liver diseases, however, tend to be less accurate than more 'complex' serum tests, which incorporate direct measures of fibrogenesis or fibrolysis (eg, hyaluronic acid, N-terminal propeptide of type three collagen). Elastography methods quantify liver stiffness as a marker of fibrosis and are more accurate than simple serum NITs, however, suffer increasing rates of unreliability with increasing obesity. MR elastography appears more accurate than sonographic elastography and is not significantly impacted by obesity but is costly with limited availability. NITs are valuable for excluding advanced fibrosis or cirrhosis, however, are not sufficiently predictive when used in isolation. Combining serum and elastography techniques increases diagnostic accuracy and can be used as screening and confirmatory tests, respectively. Unfortunately, NITs have not yet been demonstrated to accurately reflect fibrosis change in response to treatment, limiting their role in disease monitoring. However, recent studies have demonstrated lipidomic, proteomic and gut microbiome profiles as well as microRNA signatures to be promising techniques for fibrosis assessment in the future.

Serum Marker Panels for Predicting Liver Fibrosis - An Update

Fibrosis prediction is an essential part of the assessment and management of patients with chronic liver disease. Traditionally the gold standard for assessment of fibrosis is liver biopsy, but it suffers from various limitations including risk of patient injury and sampling error. As a result, noninvasive tests of hepatic fibrosis have been used in patients with chronic liver disease due to conditions such as hepatitis B and C, and alcoholic and non-alcoholic fatty liver disease. With the advent of new direct-acting antivirals, hepatic fibrosis staging is an important component of treatment decisions in the care of patients with chronic hepatitis C virus infection. Current limitations of the noninvasive biomarker models include a significant indeterminate range, and a predictive ability that is limited to only a few stages of fibrosis. However newer technologies and novel proteins identified by proteomics and genomics offer the possibility for further refinement and individualisation of biomarker fibrosis models in the future.

Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning.

METHODS AND FINDINGS

We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (<5% or ≥5%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86; p < 0.001), which compared with a ROCAUC of 0.82 (95% CI 0.81, 0.83; p < 0.001) for a model including 9 clinically accessible variables. The IMI DIRECT prediction models outperformed existing noninvasive NAFLD prediction tools. One limitation is that these analyses were performed in adults of European ancestry residing in northern Europe, and it is unknown how well these findings will translate to people of other ancestries and exposed to environmental risk factors that differ from those of the present cohort. Another key limitation of this study is that the prediction was done on a binary outcome of liver fat quantity (<5% or ≥5%) rather than a continuous one.

CONCLUSIONS

In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03814915.

The influence of gene-chronic hepatitis C virus infection on hepatic fibrosis and steatosis

Host single nucleotide polymorphisms (SNPs) in different genes can play a role in chronic hepatitis C virus (HCV) infection and influence the presence of hepatic fibrosis and comorbidities such as hepatic steatosis. We assessed the combined effect of SNPs in the PNPLA3, MTTP, TM6SF2, and IFNL3/IFNL4 genes in 288 Brazilian patients who were chronically infected with HCV. Hepatic fibrosis was observed in 246 (85.4%) patients and hepatic steatosis in 141 (49.0%) patients. PNPLA3 rs738409 (CG/GG) (P = 0.044) and TM6SF2 rs58542926 (CT) (P = 0.004) were alone associated with fibrosis, and PNPLA3 rs738409 (P < 0.05, in distinct genetic models) was associated with steatosis. Multiple logistic regression of each SNP combined with HCV genotype 3 infection showed that MTTP rs1800591 (GT/TT) combined with HCV genotype 3 was associated with a 6.72-fold increased chance of hepatic steatosis (P = 0.013). In the analysis of SNPs combined 2 by 2, no influence on hepatic fibrosis or steatosis was observed.

The STAT4 and not the IFNL3 variant is associated with hepatitis B virus clearance in a population from the Khyber Pakhtunkhwa region of Pakistan

BACKGROUND AND STUDY AIMS

Host genetic modifiers of the risk and persistence of hepatitis B virus (HBV) infection in the Pakistani population have not been clearly elucidated. Recently, two genome-wide association studies described that STAT4 and IFNL3 variants are associated with different aspects of the course of HBV infection. However, the roles of these variants in the persistence of HBV infection have not been investigated in the HBV-infected population of Pakistan. Therefore, we examined the roles of the STAT4 and IFNL3 variants in a chronic HBV-infected population from the Khyber Pakhtunkhwa (KPK) region of Pakistan.

PATIENTS AND METHODS

STAT4 rs7574865 and IFNL3 rs12979860 genotyping were performed in 297 subjects (240 infected with HBV and 57 controls). Statistical analyses were performed using the chi-squared test, Student's t-test, Hardy-Weinberg equilibrium tests and logistic regression models.

RESULTS

Among the 297 subjects, compared with the IFNL3 rs12979860 genotype [odds ratio (OR) = 0.7, 95% confidence interval (CI) = 0.39-1.29, p = 0.2), the STAT4 rs7574865 genotype was independently associated with the risk of developing chronic HBV infection [OR = 1.9, 95% CI = 1.09-3.50, p = 0.02].

CONCLUSION

The STAT4 rs7574865 and not the IFNL3 rs12979860 variant is associated with persistence of HBV infection in a Pakistani population from the KPK region.

Macrophages in metabolic associated fatty liver disease

Metabolic associated fatty liver disease (MAFLD), formerly named non-alcoholic fatty liver disease is the most common liver disorder in many countries. The inflammatory subtype termed steatohepatitis is a driver of disease progression to cirrhosis, hepatocellular carcinoma, liver transplantation, and death, but also to extrahepatic complications including cardiovascular disease, diabetes and chronic kidney disease. The plasticity of macrophages in response to various environmental cues and the fact that they can orchestrate cross talk between different cellular players during disease development and progression render them an ideal target for drug development. This report reviews recent advances in our understanding of macrophage biology during the entire spectrum of MAFLD including steatosis, inflammation, fibrosis, and hepatocellular carcinoma, as well as for the extra-hepatic manifestations of MAFLD. We discuss the underlying molecular mechanisms of macrophage activation and polarization as well as cross talk with other cell types such as hepatocytes, hepatic stellate cells, and adipose tissue. We conclude with a discussion on the potential translational implications and challenges for macrophage based therapeutics for MAFLD.

Noninvasive Diagnosis of NAFLD and NASH

The aim of this review is to outline emerging biomarkers that can serve as early diagnostic tools to identify patients with nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) and, among them, the subgroup of best candidates for clinical trials on emerging compounds. Regarding possible predictors of NAFLD, a number of studies evaluated a combination of serum biomarkers either available in routine practice (or investigational) or proprietary and expensive. So far, magnetic resonance imaging-derived proton density fat fraction (MRI-PDFF) appears to be the most accurate for fatty liver diagnosis. In clinical practice, the main question is how to diagnose NASH early. There are new promising biomarkers that can help in diagnosing early stages of NASH, yet they include variables not routinely tested. In the setting of NASH, most studies confirm that, in spite of several well-known limitations, transient elastography or point shear wave elastography can help in enriching the pool of patients that should be screened for investigational treatments. Newer multiomics biomarkers including those focusing on microbiota can be useful but require methods to be standardized and implemented. To date, one biomarker alone is not able to non- or minimally invasively identify patients with NASH and mild to moderate fibrosis.

The Epigenetic Drug Discovery Landscape for Metabolic-associated Fatty Liver Disease

Despite decades of research, effective therapies for metabolic (dysfunction)-associated fatty liver disease (MAFLD) are lacking. An increasing body of evidence suggests that epigenetic dysregulation is frequent in MAFLD, and orchestrates many aspects of its development and progression. Furthermore, the high plasticity of epigenetic modifications in response to environmental cues renders epigenetics a novel area for therapeutic drug discovery. Over recent years, several epigenetics-based drugs and diagnostic biomarkers have entered clinical development and/or obtained regulatory approval. Here, we review recent advances in our understanding of epigenetic regulation and programming during MAFLD, including DNA methylation, histone modifications, chromatin remodelling, transcriptional control, and noncoding (nc)RNAs. We also discuss the potential translational implications and challenges of epigenetics in the context of MAFLD.

Genetic contributions to NAFLD: leveraging shared genetics to uncover systems biology

Nonalcoholic fatty liver disease (NAFLD) affects around a quarter of the global population, paralleling worldwide increases in obesity and metabolic syndrome. NAFLD arises in the context of systemic metabolic dysfunction that concomitantly amplifies the risk of cardiovascular disease and diabetes. These interrelated conditions have long been recognized to have a heritable component, and advances using unbiased association studies followed by functional characterization have created a paradigm for unravelling the genetic architecture of these conditions. A novel perspective is to characterize the shared genetic basis of NAFLD and other related disorders. This information on shared genetic risks and their biological overlap should in future enable the development of precision medicine approaches through better patient stratification, and enable the identification of preventive and therapeutic strategies. In this Review, we discuss current knowledge of the genetic basis of NAFLD and of possible pleiotropy between NAFLD and other liver diseases as well as other related metabolic disorders. We also discuss evidence of causality in NAFLD and other related diseases and the translational significance of such evidence, and future challenges from the study of genetic pleiotropy.

IFNL3 genotype is associated with pulmonary fibrosis in patients with systemic sclerosis

Fibrosis across different organs and tissues is likely to share common pathophysiological mechanisms and pathways. Recently, a polymorphism (rs12979860) near the interferon lambda gene (IFNL3) was shown to be associated with fibrosis in liver across multiple disease etiologies. We determined whether this variant is a risk factor for pulmonary fibrosis (PF) and worsening cutaneous fibrosis in systemic sclerosis (SSc). Caucasian patients with SSc (n = 733) were genotyped to test for association with the presence of PF and worsening of skin fibrosis. Serum IFN-λ3 levels from 200 SSc cases were evaluated. An association of the IFNL3 polymorphism with PF was demonstrated (OR: 1.66 (95% CI: 1.142-2.416, p = 0.008). The IFNL3 variant was not a risk factor for worsening of skin fibrosis. Functionally, IFN-λ3 serum levels were higher among subjects with PF compared to those unaffected (P < 0.0001). In conclusion, IFNL3 serum levels and the genetic variant known to be associated with liver fibrosis are similarly linked to PF, but not to worsening of skin fibrosis in SSc. These data highlight both common fibrosis pathways operating between organs, as well as differential effects within the same disease.

Interferon Lambda and Liver Fibrosis

Fibrosis is a highly conserved and coordinated wound healing response to injury. In the liver, injury is promoted by immune effector mechanisms that are common across various disease etiologies and even between organs such as lungs, kidneys, heart, and other organs. Thus, the liver represents a useful model to study inflammation and repair, particularly as it is frequently biopsied in clinical contexts. Currently, strong evidence implicates IFNL3/4 polymorphisms and interferon (IFN)-λ3 levels as determinants of the extent of hepatic inflammation and fibrosis in viral and nonviral liver diseases, as well as in governing the severity of nonhepatotropic viral diseases. Interestingly, IFNL3/4 polymorphisms and IFN-λ3 levels correlate with fibrosis extent in other organs such as the lung and kidney. In this review, we discuss the association between IFN-λ and tissue inflammation and fibrosis in human disease and the potential clinical utility of the findings.

What Have We Learned from Studies of IFN-λ Variants and Hepatitis C Virus Infection?

Chronic infection with the hepatitis C virus (HCV) is a major cause of cirrhosis and hepatocellular carcinoma. In 2009, genome-wide association studies (GWAS) strongly linked genetic variants in the interferon lambda (IFN-λ) chromosomal region to HCV clearance. In 2013, discovery of the IFNL4 gene provided a functional explanation for those GWAS findings. The IFNL4-ΔG/TT (rs368234815) variant controls generation of the IFN-λ4 protein. Paradoxically, the IFNL4-TT allele, which abrogates IFN-λ4, associates with higher rates of spontaneous HCV clearance and better response to treatments for HCV infection. The finding that a "knock-out" allele for IFN-λ4 enhances HCV clearance challenges the paradigm of IFNs as antiviral cytokines. Genetic variants in the IFN-λ region have also been associated with hepatic inflammation and fibrosis from various etiologies, however, alleles that are linked with improved HCV clearance associates with worse inflammation and fibrosis. These studies demonstrate that GWAS of infectious diseases may yield important and unexpected biological insights.

Genetic Insights for Drug Development in NAFLD

Drug development is a costly, time-consuming, and challenging endeavour, with only a few agents reaching the threshold of approval for clinical use. Therefore, approaches to more efficiently identify targets that are likely to translate to clinical benefit are required. Interrogation of the human genome in large patient cohorts has rapidly advanced our knowledge of the genetic architecture and underlying mechanisms of many diseases, including nonalcoholic fatty liver disease (NAFLD). There are no approved pharmacotherapies for NAFLD currently. Genetic insights provide a powerful and new approach to infer and prioritise candidate drugs, with such selection avoiding myriad pitfalls, while defining likely benefits. In this review, we discuss the prospects and challenges for the optimal utilisation of genetic findings for improving and accelerating the NAFLD drug discovery pipeline.

Association of serum interferon-λ3 levels with hepatocarcinogenesis in chronic hepatitis C patients treated with direct-acting antiviral agents

AIM

Although the efficacy of hepatitis C virus (HCV) treatment is improved dramatically by direct-acting antiviral agents (DAAs), the assessment of hepatocellular carcinoma (HCC) remains important. Interferon lambda 3 (IFN-λ3) is associated with liver fibrosis and inflammation in chronic hepatitis C (CHC) patients, but its impact on carcinogenesis remains controversial and little is known about its effects after viral clearance. To determine the contribution of IFN-λ3 to hepatocarcinogenesis after HCV clearance, we analyzed IFNL3 genotypes and serial serum IFN-λ3 levels in CHC patients who achieved sustained virologic responses (SVR).

METHODS

This study comprised 201 CHC patients treated with DAAs. Serum samples were collected sequentially and IFN-λ3 levels were quantified by chemiluminescence enzyme immunoassay. The IFNL3 polymorphism (rs8099917) was genotyped in 195 patients.

RESULTS

One hundred and twenty-five patients were rs8099917 T/T and 70 were non-T/T. Serum IFN-λ3 levels did not differ significantly with IFNL3 genotype, dropped markedly by 1 week and remained low up to 24 weeks after the end of treatment. Interferon-λ3 levels were significantly higher after viral clearance in patients who developed HCC and were associated with a higher potential for hepatocarcinogenesis, such as a higher frequency of non-hypervascular hypointensive nodules (P = 0.046), higher stages of liver fibrosis (P < 0.001), and higher post-treatment levels of Wisteria floribunda agglutinin positive Mac-2 binding protein (P < 0.001) and alanine aminotransferase (P < 0.001).

CONCLUSIONS

Serum IFN-λ3 levels after HCV clearance are associated with the potential for HCC development. Interferon-λ3 could be helpful for elucidating the relationships among immunologic status, liver fibrosis, liver inflammation, and hepatocarcinogenesis, after achieving SVR.

ADAPT: An Algorithm Incorporating PRO-C3 Accurately Identifies Patients With NAFLD and Advanced Fibrosis

Given the high global prevalence of nonalcoholic fatty liver disease (NAFLD), the need for relevant noninvasive biomarkers and algorithms to accurately stage disease severity is a critical unmet medical need. Identifying those with advanced fibrosis (≥ F3) is the most crucial, as these individuals have the greatest risk of adverse, long-term, liver-related outcomes. We aimed to investigate the role of PRO-C3 (a marker of type III collagen formation) as a biomarker for advanced fibrosis in NAFLD. We measured PRO-C3 by enzyme-linked immunosorbent assay in two large independent cohorts with extensive clinical phenotyping and liver biopsy: 150 in the derivation and 281 in the validation cohort. A PRO-C3-based fibrosis algorithm that included age, presence of diabetes, PRO-C3, and platelet count (ADAPT) was developed. PRO-C3 increased with fibrosis stage (Rho 0.50; P < 0.0001) and was independently associated with advanced fibrosis (odds ratio = 1.05; 95% confidence interval [CI] 1.02-1.08; P = 0.003). ADAPT showed areas under the receiver operating characteristics curve of 0.86 (95% CI 0.79-0.91) in the derivation and 0.87 in the validation cohort (95% CI 0.83-0.91) for advanced fibrosis. This was superior to the existing fibrosis scores, aspartate aminotransferase to platelet ratio index (APRI), FIB-4, and NAFLD fibrosis score (NFS) in most comparisons. Conclusion: PRO-C3 is an independent predictor of fibrosis stage in NAFLD. A PRO-C3-based score (ADAPT) accurately identifies patients with NAFLD and advanced fibrosis and is superior to APRI, FIB-4, and NFS.

A variant in the MICA gene is associated with liver fibrosis progression in chronic hepatitis C through TGF-β1 dependent mechanisms

Hepatocarcinogenesis is tightly linked to liver fibrosis. Recently, two GWAS variants, MICA rs2596542 and DEPDC5 rs1012068 were identified as being associated with the development of HCV-induced hepatocellular carcinoma (HCC) in Japanese patients. The role of these variants on hepatic inflammation and fibrosis that are closely associated with HCC development is not known, nor are the biological mechanisms underlying their impact on the liver. Here, we demonstrate in 1689 patients with chronic hepatitis C (CHC) (1,501 with CHC and 188 with HCV-related HCC), that the MICA (T) allele, despite not being associated with HCC susceptibility, is associated with increased fibrosis stage (OR: 1.47, 95% CI: 1.05–2.06, p = 0.02) and fibrosis progression rate (hazards ratio: 1.41, 95% CI: 1.04–1.90, p = 0.02). The DEPDC5 variant was not associated with any of these phenotypes. MICA expression was down-regulated in advanced fibrosis stages. Further, (T) allele carriage was associated with lower MICA expression in liver and serum. Transforming growth factor-β1 (TGF-β1) expression suppresses MICA expression in hepatic stellate cells. Our findings suggest a novel mechanism linking susceptibility to advanced fibrosis and subsequently indirectly to HCC, to the level of MICA expression through TGF-β1-dependent mechanisms.

Current status, problems, and perspectives of non-alcoholic fatty liver disease research

Non-alcoholic fatty liver disease (NAFLD) is a major chronic liver disease that can lead to liver cirrhosis, liver cancer, and ultimately death. NAFLD is pathologically classified as non-alcoholic fatty liver (NAFL) or non-alcoholic steatohepatitis (NASH) based on the existence of ballooned hepatocytes, although the states have been known to transform into each other. Moreover, since the detection of ballooned hepatocytes may be difficult with limited biopsied specimens, its clinical significance needs reconsideration. Repeated liver biopsy to assess histological NAFLD activity for therapeutic response is also impractical, creating the need for body fluid biomarkers and less invasive imaging modalities. Recent longitudinal observational studies have emphasized the importance of advanced fibrosis as a determinant of NAFLD outcome. Thus, identifying predictors of fibrosis progression and developing better screening methods will enable clinicians to isolate high-risk NAFLD patients requiring early intensive intervention. Despite the considerable heterogeneity of NAFLD with regard to underlying disease, patient age, and fibrosis stage, several clinical trials are underway to develop a first-in-class drug. In this review, we summarize the present status and future direction of NAFLD/NASH research towards solving unmet medical needs.

Genetic Factors That Affect Spontaneous Clearance of Hepatitis C or B Virus, Response to Treatment, and Disease Progression

Hepatitis C virus (HCV) and hepatitis B virus (HBV) infections can lead to cirrhosis, end-stage liver disease, and hepatocellular carcinoma. Over the past decade, studies of individuals infected with these viruses have established genetic associations with the probability of developing a chronic infection, risk of disease progression, and likelihood of treatment response. We review genetic and genomic methods that have been used to study risk of HBV and HCV infection and patient outcomes. For example, genome-wide association studies have linked a region containing the interferon lambda genes to spontaneous and treatment-induced clearance of HCV. We review the genetic variants associated with HCV and HBV infection, and how these variants affect specific expression or activities of their products. Further studies of these variants could provide insights into risk factors for and mechanisms of chronic infection and disease progression, as well as new strategies for treatment.

A Pathophysiologic Approach Combining Genetics and Insulin Resistance to Predict the Severity of Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) is a complex disease dictated by both genetic and environmental factors. While insulin resistance (IR) is a key pathogenic driver, two common genetic variants in patatin‐like phospholipase domain containing 3 (PNPLA3) and transmembrane 6 superfamily member 2 (TM6SF2) also impart significant risk for disease progression. Traditional approaches to NAFLD risk stratification rely on biomarkers of fibrosis, an end result of disease progression. We hypothesized that by combining genetics and a novel measurement for IR we could predict disease progression by the NAFLD activity score (NAS) and histologic presence of significant fibrosis. A total of 177 patients with biopsy‐proven NAFLD were enrolled in this cross‐sectional study. PNPLA3 I148M and TM6SF2 E167K genotypes were determined by TaqMan assays. The enhanced lipoprotein IR index (eLP‐IR) was calculated from serum biomarkers using nuclear magnetic resonance (NMR) spectroscopy. Multivariate regression models were used to study the relationships between genetics, IR, and histologic features of NAFLD. In the multivariate analysis, the eLP‐IR was strongly associated with histologic features of NAFLD activity and hepatic fibrosis (P < 0.001 to 0.02) after adjustment for potential confounders. PNPLA3 148M and TM6SF2 E167K genotypes were significantly associated with steatosis (P = 0.003 and P = 0.02, respectively). A combination of the eLP‐IR and genetic score was able to predict the presence of NAS ≥3 with an area under the receiver operating characteristic curve (AUROC) of 0.74. Adding age to this model predicted stages 3‐4 liver fibrosis with an AUROC of 0.82. Conclusion: This proof‐of‐concept study supports the hypothesis that genetics and IR are major determinants of NAFLD severity and demonstrates the feasibility of a new risk stratification paradigm using exclusively pathogenic factors.

When to Initiate Weight Loss Medications in the NAFLD Population

Nonalcoholic fatty liver disease (NAFLD) is characterized by histological evidence of hepatic steatosis, lobular inflammation, ballooning degeneration and hepatic fibrosis in the absence of significant alcohol use and other known causes of chronic liver diseases. NAFLD is subdivided into nonalcoholic fatty liver (NAFL) and nonalcoholic steatohepatitis (NASH). NAFL is generally benign but can progress to NASH, which carries a higher risk of adverse outcomes including cirrhosis, end-stage liver disease, hepatocellular carcinoma and death if liver transplantation is not pursued in a timely fashion. Currently, lifestyle modifications including healthy diet and increased physical activity/exercise culminating in weight loss of 5% to >10% is the cornerstone of treatment intervention for patients with NAFLD. Patients with NAFLD who fail to obtain this goal despite the help of dietitians and regimented exercise programs are left in a purgatory state and remain at risk of developing NASH-related advance fibrosis. For such patients with NAFLD who are overweight and obese, healthcare providers should consider a trial of FDA-approved anti-obesity medications as adjunct therapy to provide further preventative and therapeutic options as an effort to reduce the risk of NAFLD-related disease progression.

Clinical prediction of HBV and HCV related hepatic fibrosis using machine learning

Clinical prediction of advanced hepatic fibrosis (HF) and cirrhosis has long been challenging due to the gold standard, liver biopsy, being an invasive approach with certain limitations. Less invasive blood test tandem with a cutting-edge machine learning algorithm shows promising diagnostic potential.

In this study, we constructed and compared machine learning methods with the FIB-4 score in a discovery dataset (n = 490) of hepatitis B virus (HBV) patients. Models were validated in an independent HBV dataset (n = 86). We further employed these models on two independent hepatitis C virus (HCV) datasets (n = 254 and 230) to examine their applicability.

In the discovery data, gradient boosting (GB) stably outperformed other methods as well as FIB-4 scores (p < .001) in the prediction of advanced HF and cirrhosis. In the HBV validation dataset, for classification between early and advanced HF, the area under receiver operating characteristic curves (AUROC) of GB model was 0.918, while FIB-4 was 0.841; for classification between non-cirrhosis and cirrhosis, GB showed AUROC of 0.871, while FIB-4 was 0.830. Additionally, GB-based prediction demonstrated good classification capacity on two HCV datasets while higher cutoffs for both GB and FIB-4 scores were required to achieve comparable specificity and sensitivity.

Using the same parameters as FIB-4, the GB-based prediction system demonstrated steady improvements relative to FIB-4 in HBV and HCV cohorts with different cutoff values required in different etiological groups. A user-friendly web tool, LiveBoost, makes our prediction models freely accessible for further clinical studies and applications.

Non-alcoholic fatty liver disease: a narrative review of genetics

Non-alcoholic fatty liver disease (NAFLD) is now the most common cause of chronic liver diseases worldwide. It encompasses a spectrum of disorders ranging from isolated hepatic steatosis to nonalcoholic steatohepatitis (NASH), fibrosis, cirrhosis, and hepatocellular carcinoma. One of the key challenges in NAFLD is identifying which patients will progress. Epidemiological and genetic studies indicate a strong pattern of heritability that may explain some of the variability in NAFLD phenotype and risk of progression. To date, at least three common genetic variants in the PNPLA3, TM6SF2, and GCKR genes have been robustly linked to NAFLD in the population. The function of these genes revealed novel pathways implicated in both the development and progression of NAFLD. In addition, candidate genes previously implicated in NAFLD pathogenesis have also been identified as determinants or modulators of NAFLD phenotype including genes involved in hepatocellular lipid handling, insulin resistance, inflammation, and fibrogenesis. This article will review the current understanding of the genetics underpinning the development of hepatic steatosis and the progression of NASH. These newly acquired insights may transform our strategy to risk-stratify patients with NAFLD and to identify new potential therapeutic targets.

Genetics and epigenetics of NAFLD and NASH: Clinical impact

Non-alcoholic fatty liver disease (NAFLD) is now recognised as the most common liver disease worldwide. It encompasses a broad spectrum of conditions, from simple steatosis, through non-alcoholic steatohepatitis, to fibrosis and ultimately cirrhosis and hepatocellular carcinoma. A hallmark of NAFLD is the substantial inter-patient variation in disease progression. NAFLD is considered a complex disease trait such that interactions between the environment and a susceptible polygenic host background determine disease phenotype and influence progression. Recent years have witnessed multiple genome-wide association and large candidate gene studies, which have enriched our understanding of the genetic basis of NAFLD. Notably, the I148M PNPLA3 variant has been identified as the major common genetic determinant of NAFLD. Variants with moderate effect size in TM6SF2, MBOAT7 and GCKR have also been shown to have a significant contribution. The premise for this review is to discuss the status of research into important genetic and epigenetic modifiers of NAFLD progression. The potential to translate the accumulating wealth of genetic data into the design of novel therapeutics and the clinical implementation of diagnostic/prognostic biomarkers will be explored. Finally, personalised medicine and the opportunities for future research and challenges in the immediate post genetics era will be illustrated and discussed.

Prospects in non-invasive assessment of liver fibrosis: Liquid biopsy as the future gold standard?

Liver fibrosis is the result of persistent liver injury, and is characterized by sustained scar formation and disruption of the normal liver architecture. The extent of fibrosis is considered as an important prognostic factor for the patient outcome, as an absence of (early) treatment can lead to the development of liver cirrhosis and hepatocellular carcinoma. Till date, the most sensitive and specific way for the diagnosis and staging of liver fibrosis remains liver biopsy, an invasive diagnostic tool, which is associated with high costs and discomfort for the patient. Over time, non-invasive scoring systems have been developed, of which the measurements of serum markers and liver stiffness are validated for use in the clinic. These tools lack however the sensitivity and specificity to detect small changes in the progression or regression of both early and late stages of fibrosis. Novel non-invasive diagnostic markers with the potential to overcome these limitations have been developed, but often lack validation in large patient cohorts. In this review, we will summarize novel trends in non-invasive markers of liver fibrosis development and will discuss their (dis-)advantages for use in the clinic.