Recent developments in non-invasive methods for assessing metabolic dysfunction-associated fatty liver disease

Abstract

The prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD) is increasing, affecting over one-third of the global population and contributing to significant morbidity and mortality. Diagnosing MAFLD, especially with advanced fibrosis, remains challenging due to the limitations of liver biopsy, the current gold standard. Non-invasive tests are crucial for early detection and management. Among these, the fibrosis-4 index (Fib-4) is widely recommended as a first-line test for screening for liver fibrosis. Advanced imaging techniques, including ultrasound-based elastography and magnetic resonance elastography, offer high accuracy but are limited by cost and availability. Combining biomarkers, such as in the enhanced liver fibrosis score and FibroScan-AST score, enhances diagnostic precision and is recommended to further stratify patients who are considered to be intermediate or high risk from the Fib-4 score. We believe that the future lies in the combined use of biomarkers to improve diagnostic accuracy.

Key Words: Non-invasive tests; Metabolic-associated fatty liver disease; Fibrosis-4 index; Magnetic resonance elastography; Enhanced liver fibrosis

Core Tip: Fibrosis-4 index, enhanced liver fibrosis, and magnetic resonance elastography are among the non-invasive tests (NITs) recommended by the American Association for the Study of Liver Disease for evaluation of patients at risk for or with established metabolic dysfunction-associated fatty liver disease (MAFLD). The recent non-invasive biomarkers of metabolic liver disease and liver investigation: Testing marker utility in steatohepatitis projects, have helped validate NITs for the detection of liver fibrosis and have significantly improved the reliability of NIT panels. While omics-based biomarkers present exciting possibilities, they are still in the early stages of clinical validation. The integration and combined use of various NITs appear to be the future direction for a more effective and precise assessment of MAFLD.

TO THE EDITOR

We read with great interest the article by Qu and Li[1] and Trinks et al[2] on the non-invasive diagnostic for metabolic dysfunction-associated fatty liver disease (MAFLD)[1,2]. The prevalence of MAFLD is increasing with recent estimates showing that it affects over one-third of the global population[3]. It contributes significantly to the incidence of end-stage liver disease and hepatocellular carcinoma, leading to poorer patient outcomes and increased mortality. Further, MAFLD is closely linked to adverse impact on the cardiovascular and excess death attributable to it[4,5]. Hence, early identification of MAFLD especially with high-risk features is critical to improve overall outcomes. We agree with the authors that identifying MAFLD patients with advanced fibrosis, who are at higher risk of complications, is challenging. Currently, liver biopsy is regarded as the gold standard for MAFLD diagnosis. However, it is typically utilized only when a patient is suspected of having another liver disease or for enrollment in clinical trials. One of the primary impediments to liver biopsy is its invasive nature, which carries a risk of complications. Additionally, ineligible histology (with rates up to 60%-80% seen in clinical trials) and limitations such as observer variability and sampling bias further restrict its use. Given the relatively asymptomatic nature of MAFLD, especially during the early years of its progression, there is a pressing need for safe, effective, and non-invasive tests (NITs). These tests would facilitate the early detection and management of the disease, ultimately improving patient outcomes.

Fibrosis scores

The American Association for the Study of Liver Disease (AASLD) recommends the fibrosis-4 index (Fib-4) for primary risk assessment in patients[6]. These include those with incidental findings of steatosis noted on imaging, a family history of cirrhosis, or clinical suspicion of MAFLD (those with metabolic risk factors or unexplained elevation in liver chemistries). The Fib-4 score is calculated using a person’s age, aspartate aminotransferase (AST) level, alanine transaminase (ALT) level, and platelet count. Originally, the Fib-4 index was utilized to predict significant fibrosis in patients with human immunodeficiency virus and hepatitis C virus (HCV) co-infection[7]. It has since become the most validated NIT for MAFLD, demonstrating a high negative predictive value for fibrosis progression[8,9].

In a crosssectional study done by Siddiqui et al[10], Fib-4 outperformed other non-invasive models for detecting both moderate [C-statistic = 0.76 (0.74 to 0.78)] and advanced fibrosis [C-statistic = 0.80 (0.78 to 0.82)]. In their longitudinal follow-up of 256 patients with non-advanced fibrosis, changes in the Fib-4 score were significantly associated with changes in fibrosis stage, with a one-unit increase in Fib-4 corresponding to a fibrosis stage change of 0.26 [95% confidence interval (CI): 0.15-0.37; P < 0.001]. A retrospective study found no significant differences in the sensitivity (81.8% vs 83.5%; P = 0.85) or specificity (52.2% vs 52.0%; P = 0.97) of the Fib-4 score between lean and non-lean patients[11]. This suggests that Fib-4 can be effectively used for fibrosis screening in lean patients with MAFLD, a group typically associated with poorer outcomes. Additionally, the Fib-4 score has been recognized as a cost-effective tool for screening fibrosis in patients with type 2 diabetes mellitus and suspected MAFLD-related fibrosis[12].

AASLD recommends that patients with a Fib-4 score of less than 1.3 can be reassessed periodically, with the frequency depending on patient risk factors: Every 1-2 years for those with type 2 diabetes mellitus or pre-diabetic status or ≥ 2 metabolic risk factors, and every 2-3 years for those without Type 2 diabetes mellitus and fewer than 2 metabolic risk factors[6]. However, the Fib-4 score was developed in a cohort of patients with an average age of around 40 years. Recent studies have highlighted its overall low accuracy in patients younger than 35 years and noted that the specificity for detecting advanced fibrosis decreases with age, falling below 30% for individuals over 65[13]. Moreover, conditions or exposures affecting platelet counts or AST levels, such as immune thrombocytopenia or alcohol use, can lead to an overestimation of the Fib-4 score. Therefore, while useful, the Fib-4 index has limitations that must be considered in clinical practice.

Other NITs included the AST to platelet ratio index (APRI score), fatty liver index, composed of only three variables: AST/ALT ratio, presence of diabetes, and body mass index (BARD), non-alcoholic fatty liver disease fibrosis score, and Forns index. Among these, APRI scores are the most well-studied, inexpensive, and easily available. The APRI score was developed in a study on chronic HCV infection where it was shown to have a positive predictive value of 51% for significant fibrosis[14]. The fatty liver index calculates fibrosis risk based on body mass index (BMI), waist circumference, triglycerides, and gamma-glutamyl transferase (GGT). The BARD score considers the ALT/AST ratio, presence of diabetes, and BMI, while the Forns index uses patient age, total cholesterol, GGT, and platelet count. While these NITs are useful for detecting fibrosis, their accuracy can also be influenced by conditions affecting the levels of their constituent variables. Additionally, despite their demonstrated efficacy in identifying fibrosis, there is limited data on their utility for long-term monitoring of fibrosis in patients with MAFLD.

Imaging biomarkers

Elastography is an advanced imaging technique used to evaluate liver fibrosis by quantifying shear wave velocity, or the tissue displacement generated by an ultrasonic impulse. It can be categorized into ultrasound-based elastography and magnetic resonance imaging-based elastography (MRE). Vibration-controlled transient elastography (VCTE) utilizes one-dimensional ultrasound waves to determine liver stiffness. However, VCTE readings can be confounded by factors such as acute hepatitis, congestive heart failure, amyloidosis, biliary obstruction, or recent food intake[15]. Additionally, VCTE is less reliable in obese patients. Other ultrasound-based techniques include point shear-wave elastography and 2-dimensional shear-wave elastography, but their clinical use is limited due to insufficient long-term monitoring data.

MRE offers excellent accuracy for diagnosing and stratifying liver fibrosis, with an area under the received operator curve (AUROC) of > 0.90 for predicting significant or advanced liver fibrosis[16]. MRE is advantageous because it is not significantly affected by hepatic steatosis, inflammation, or obesity. However, its use is limited by high costs and limited availability. AASLD recommends VCTE for secondary risk assessment in patients with an indeterminate Fib-4 score. Patients who are low risk (liver stiffness < 8 kPa) can be reassessed periodically using the Fib-4 score, while patients with intermediate risk (8-12 kPa) or high risk (> 12 kPa) should follow up with a specialist[6]. MRE is recommended for additional risk assessment when NITs are indeterminate or when there is clinical suspicion of more advanced disease.

Combination biomarkers

Efforts have been made to combine various biomarkers to enhance the sensitivity and specificity for detecting liver fibrosis in patients with MAFLD. The enhanced liver fibrosis (ELF) score represents a notable marker derived from measuring three serum biomarkers: Hyaluronic acid, procollagen III N-terminal peptide, and tissue inhibitor of matrix metalloproteinase-1. Recent studies have shown the ELF score’s efficacy in detecting advanced liver fibrosis in patients with MAFLD (AUROC: 0.63-0.99)[17]. It is recommended by the National Institue for Health and Care Excellence and European Association for the study of the liver as a screening tool for liver fibrosis[18,19].

In a prospective study of 457 patients, a one-unit increase in the ELF score was noted to correspond with doubling of the risk of liver-related outcomes. They also noted that over 6 years of follow-up, the ELF score was at least as accurate as liver biopsy in predicting liver-related outcomes[20]. In addition to being validated for MAFLD, ELF score has also been validated for use in patients with Hepatitis B, Hepatitis C, and mixed picture of liver disease[20-22]. In a recent study involving 1327 patients by Pearson et al[23], ELF was noted to outperform Fib-4 score assessment of liver related mortality (area under the curve: 94.3% vs 82.8% at 6 months)[23]. AASLD guidelines recommend that in patients with confirmed or suspected advanced fibrosis, an ELF ≥ 11.3 is a predictor of future liver-related events[6]. However, the ELF score is not particularly effective for evaluating early fibrosis, and its high cost limits widespread application.

The FibroScan-AST score which combines FibroScan results with AST levels, has shown impressive AUROC values ranging from 0.74 to 0.95 for detecting patients with metabolic dysfunction-associated steatohepatitis (MASH) and significant fibrosis on liver biopsy[24]. Recently proposed Agile 3 + and Agile 4 scores integrate liver stiffness measurements by VCTE with variables such as (age, sex, and presence of type II diabetes) and serum biomarkers (AST, ALT, and platelet counts). Studies indicate that Agile 3 + and Agile 4 scores have comparable diagnostic accuracy to VCTE, but with fewer indeterminate results[25]. These combination strategies hold promise as effective tools for accurately identifying patients with advanced stages of liver disease.

In recent years, the non-invasive biomarkers of metabolic liver disease (NIMBLE) and the liver investigation: Testing marker utility in steatohepatitis (LITMUS) projects have made significant strides in defining the sensitivity and specificity of various NIT panels[26,27]. The NIMBLE project evaluated the performance metrics of five biomarkers-NIS4, OWLiver, Pro-C3, ELF, and FibroMeter VCTE-for diagnosing MASH, at-risk MASH, and fibrosis severity in biopsy-proven individuals with MAFLD. The NIS4 score proved to be an excellent metric for identifying at-risk MASH, while the ELF and FibroMeter VCTE demonstrated good accuracy in detecting advanced fibrosis in MAFLD patients. The LITMUS project assessed 17 biomarker and multi-marker scores for detecting MASH and clinically significant fibrosis in MAFLD patients. Although none of the biomarkers achieved the predefined AUROC threshold required to replace liver biopsy, the study found that the SomaSignal test, the ADAPT (A Pro-C3-based score), and the liver stiffness measurement VCTE could be effectively used in a pre-screening strategy for clinical trial recruitment. These findings underscore the potential of these biomarkers in improving the efficiency of patient selection for clinical studies.

Omics-based biomarkers

In recent years, significant breakthroughs in omics methodologies have provided opportunities to leverage technological advances to discover MAFLD biomarkers across diverse biological specimens. These advances can aid in identifying and stratifying the risk of patients with MAFLD. However, as Trinks et al[2] have pointed out, omics-based research in MAFLD is currently limited by a lack of clinical validation and utility. Additionally, concerns persist regarding these methods’ reproducibility, accuracy, and reliability. Although no omics-based biomarkers have yet matured to clinical implementation, the advent of artificial intelligence and machine learning models has enabled the testing of thousands or even millions of analytes. Consequently, omics can help uncover the complex interplay between genes, proteins, metabolites, and the microbiome, facilitating more targeted hypothesis-driven approaches.

CONCLUSION

Significant progress has been made in the development and validation of NITs for identifying and risk-stratifying patients with MAFLD and advanced liver fibrosis. While omics-based markers show promise and considerable research and resources are being devoted to them, it is unlikely that they will become the sole diagnostic tool. Instead, the future lies in combination biomarkers and their inter-correlation to enhance diagnostic accuracy. The NIMBLE and LITMUS projects have been pivotal in advancing these efforts, highlighting the potential of integrated biomarker strategies to improve the precision of liver disease diagnosis and risk assessment.