Screening strategy for non-alcoholic fatty liver disease

Article information

Clin Mol Hepatol. 2023;29(Suppl):S103-S122
Publication date (electronic) : 2022 November 30
doi :
1Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong
2State Key Laboratory of Liver Research, The University of Hong Kong, Hong Kong
3Department of Medicine, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
Corresponding author : Wai-Kay Seto Department of Medicine, The University of Hong Kong-Shenzhen Hospital, No.1, Haiyuan 1st Road, Futian District, Shenzhen, Guangdong 518009, China Tel: +86 75586913333, Fax: +86 75586913108, E-mail:

Editor: Sung Won Lee, The Catholic University of Korea, Korea

Received 2022 October 25; Revised 2022 November 13; Accepted 2022 November 16.


Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, affecting approximately 25% of the general population worldwide, and is forecasted to increase global health burden in the 21st century. With the advancement of non-invasive tests for assessing and monitoring of steatosis and fibrosis, NAFLD screening is now feasible, and is increasingly highlighted in international guidelines related to hepatology, endocrinology, and pediatrics. Identifying high-risk populations (e.g., diabetes mellitus, obesity, metabolic syndrome) based on risk factors and metabolic characteristics for non-invasive screening is crucial and may aid in designing screening strategies to be more precise and effective. Many screening modalities are currently available, from serum-based methods to ultrasonography, transient elastography, and magnetic resonance imaging, although the diagnostic performance, cost, and accessibility of different methods may impact the actual implementation. A two-step assessment with serum-based fibrosis-4 index followed by imaging test vibration-controlled transient elastography can be an option to stratify the risk of liverrelated complications in NAFLD. There is a need for fibrosis surveillance, as well as investigating the cost-effectiveness of different screening algorithms and engaging primary care for first-stage triage screening.


Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease that places an increasing burden on global health in the 21st century, and is known to affect approximately 25% of the general population worldwide [1]. NAFLD includes two pathologically distinct conditions: non-alcoholic fatty liver and non-alcoholic steatohepatitis (NASH); the latter covers a wide spectrum of disease severity, including inflammation, hepatocyte injury (hepatocellular ballooning), and fibrosis at different stages [2,3]. Without appropriate management, it can progress to cirrhosis and liver-related complications, including hepatocellular carcinoma (HCC) and liver failure [4]. Compared to the general population, individuals with NAFLD have an increased risk of overall mortality, with common causes of death, besides liver-related ones, being cardiovascular disease and malignancy [5-8]. A modelling study forecasted the total NAFLD population of eight major countries to increase by 18.3% from 2016 onward, reaching a prevalence of 28.4% by 2030 [9]. Most individuals with NAFLD remain undiagnosed and, worryingly, the prevalence of advanced fibrosis and cirrhosis is projected to double by 2030 [9]. Despite the high population prevalence of NAFLD, recognition and management of the condition varies, with improvements still required in investigations at the primary care level and in the staging of fibrosis [10].

The need for NAFLD screening in the community has been questioned given the high associated direct and indirect costs, the low predictive value of non-invasive tests, the risks of liver biopsy, and the lack of effective treatment for NAFLD [11]. However, the progressive form of NAFLD (i.e., NASH), particularly when associated with advanced fibrosis, should be identified in patients at risk (age >50 years, type 2 diabetes mellitus or metabolic syndrome) [12], due to its prognostic implications. Although familial clustering occurs, based on current evidence, family screening is not generally advisable [12]. There is also a lack of validated cost-utility studies on the effectiveness of screening.

Currently, there is no consensus on the recommended population requiring screening for NAFLD. The American Association for the Study of Liver Diseases (AASLD) recommends against routine screening in any population, regardless of body mass index (BMI) [13], but also endorses “vigilance” in patients with type 2 diabetes mellitus (T2DM). The guidelines issued by the European Association for the Study of Liver (EASL), European Association for the Study of Diabetes (EASD), and European Association for the Study of Obesity (EASO) recommend screening in individuals with obesity or metabolic syndrome [12]; the recommendations from the Asian Pacific Association for the Study of the Liver (APASL) [14] and the Korean Association for the Study of the Liver (KASL) [15] are similar. There are also variations in the recommendations from British [16], diabetic and pediatric professional associations (Table 1) [17-20].

Current guidance on screening for NAFLD

In this review, we aimed to highlight the high-risk populations in which NAFLD screening may prove beneficial, summarize recent non-invasive tests for the screening for NAFLD, and discuss the importance of fibrosis surveillance.


Screening should ideally be performed via an organized program that has the capacity to identify target populations, and perform thorough evaluation, monitoring, and treatment [21]. Screening should preferably be the main purpose of the program; if risk factors of NAFLD require management, patients should be referred to appropriate healthcare providers (Table 2).

Differences among international guidelines in screening recommendations for NAFLD in high-risk populations


NAFLD is found in 50–60% of T2DM patients and up to 45% of type 1 diabetes mellitus (T1DM) patients [22], which raises an important question: Should we screen for NAFLD in the diabetic population?

Disease progression is more aggressive in T2DM patients with underlying hepatic necroinflammation and fibrosis. Mechanistically, lipotoxicity-induced mitochondrial dysfunction and activation of inflammatory pathways, rather than steatosis, cause progressive liver damage [23]. Among patients with T2DM, NASH is a leading cause of end-stage liver disease and a risk factor for cardiovascular disease [24]. Similar to diabetic retinopathy and nephropathy, NASH is increasingly being recognized as a complication of T2DM [25], which may imply the condition should be considered for incorporation into diabetic complication screening programs. Since T2DM patients are at high risk of developing NASH, concomitant NAFLD can be present even when liver transaminases are normal [26].

Several studies have reported the results of screening for liver fibrosis in the general population or individuals with T2DM using non-invasive methods (mainly by transient elastography). A population-based study from Hong Kong [27] investigated liver fat and fibrosis using proton-magnetic resonance spectroscopy (1H-MRS) and transient elastography in 922 healthy individuals recruited by random selection. The prevalence of NAFLD (defined by an intrahepatic triglyceride content >5%) was 27.3%, and the prevalence of advanced fibrosis (liver stiffness >9.6 kPa) was 3.7%. In another study involving 1,918 T2DM patients [28], the prevalence of increased liver stiffness (>9.6 kPa, suggestive of stage ≥F3) was 18%. Among approximately one-third of patients who underwent a liver biopsy, 56% had steatohepatitis, 21% had advanced fibrosis, and 29% had cirrhosis. A prospective study demonstrated the feasibility of using two accurate, precise, and validated non-invasive image-based biomarkers: magnetic resonance imaging-estimated proton density fat fraction (MRI-PDFF) to quantify liver fat, and magnetic resonance elastography (MRE) to detect advanced fibrosis in T2DM patients in a primary care setting [29], with a 65% prevalence of NAFLD and a 7.1% prevalence of advanced fibrosis found in the study population.

Altogether, these results confirmed the increased prevalence of advanced fibrosis among individuals with T2DM, thereby justifying the potential benefits of screening for NAFLD among T2DM patients, although the use of magnetic resonance (MR)-based technologies would raise issues related to cost and accessibility.


It has been well-documented that obesity is associated with an increased risk of NAFLD. Increased BMI and waist circumference, a measure of visceral adiposity, are positively related to the presence of NAFLD [30] and predict advanced disease, particularly in the elderly [31]. Common obesity comorbidities, such as sleep apnea [32], also contribute to the disease burden of NAFLD. The majority (>95%) of patients with morbid obesity undergoing bariatric surgery would have underlying NAFLD [33,34], of which the prevalence of advanced fibrosis is estimated at 10% [35]. Since obesity can limit successful liver stiffness measurements, the XL probe (lower ultrasound frequency of 2.5 MHz; can reach deeper liver tissue 35–75 mm from the skin surface) has been shown to be effective in liver stiffness measurement in obese patients with increased success rates of measurements, compared to the standard M probe [36,37].

In addition, patients with BMI <25 kg/m2 but with visceral fat accumulation or dysfunctional adipose tissue can exhibit NAFLD with or without elevation in liver aminotransferases [38,39]; these individuals are usually described as “lean NAFLD.” The populations of lean NAFLD vary worldwide, comprising 17.3% of the NAFLD cohort in the United States [40], but with higher proportions of 50% and 75% in Japan [41] and India, respectively [42]. However, the concept of lean NAFLD is somewhat misleading and simplistic, as it draws a line at 25 kg/m2 (or 23 kg/m2 for Asian people). The definition of “lean” is based on BMI, but it does not consider how the weight is distributed in the body (fat vs. muscle, intra-abdominal fat vs. subcutaneous fat). Thus, lean NAFLD refers to the presence of NAFLD in lean people who often have some abdominal fat accumulation or other subtle metabolic abnormalities [43]. Caucasian lean subjects with NAFLD represent a wide spectrum of NAFLD, which can develop into advanced liver disease, metabolic comorbidities, cardiovascular disease, as well as liver-related mortality [43]. These findings illustrate the oversimplified concept of lean NAFLD.

The indications for screening of NAFLD in lean individuals are not well-defined; NAFLD may be easily missed since such patients do not fit the classic phenotype of obesity [44]. The fibrosis-4 (FIB-4) index and NAFLD fibrosis score (NFS), while well-validated, are generally more useful in excluding fibrosis than identifying it. A recent study found NFS and FIB-4 to be less accurate in discriminating the severity of disease in lean NAFLD patients [45]. Meanwhile, both non-obese and lean groups had substantial long-term liver and non-liver comorbidities. A retrospective study from 1999–2016 indicated that non-obese NAFLD individuals had higher 15-year cumulative all-cause mortality (51.7%) compared to obese NAFLD (27.2%) and non-NAFLD (20.7%) individuals in the United States [46]. These findings suggest that obesity should not be the sole criterion for NAFLD screening [47].


A third condition in which screening may be considered is metabolic syndrome, which comprises multiple metabolic and cardiovascular risk factors, primarily increased waist circumference, and a mixed combination of dyslipidemia, hypertension, and diabetes/prediabetes [48]. NAFLD parallels the prevalence of metabolic syndrome and its components, which also increases the risk of advanced disease. The link between metabolic syndrome and NAFLD is complex and bidirectional. Evidence indicated that NAFLD diagnosed via ultrasonography was associated with an increased risk of incident metabolic syndrome with a pooled relative risk of 3.22 [49]. suggesting that a vicious cycle of worsening disease states is likely to exist.

A cohort study over a 6-year follow-up period has observed 3,913 new cases of NAFLD in 15,791 Han Chinese individuals, and the risk of incident NAFLD was markedly higher in those with metabolic syndrome [50]. The hazard ratios for incident NAFLD increased when three features of metabolic syndrome were present as compared to individuals who exhibited no metabolic syndrome components. Advanced fibrosis was observed in 10.4% of health checkup examinees by FIB-4 index and shear wave elastography in health checkup examinations [51]. Furthermore, metabolic syndrome with mild-to-moderate alcohol consumption was associated with advanced fibrosis [51].

The EASL-EASD-EASO Clinical Practice Guidelines 2016 indicated that all individuals with steatosis should be screened for features of metabolic syndrome, independent of liver enzymes [12]. For patients with newly-presenting metabolic syndrome, screening for NAFLD by liver enzymes and/or ultrasound should be routine [12]. Since all components of metabolic syndrome correlate with liver fat level, regardless of BMI, the presence of metabolic syndrome in any particular patient should prompt an assessment of the risk of NAFLD, and vice versa, the presence of NAFLD should prompt an examination of all components of metabolic syndrome. A thorough evaluation of each element of the metabolic syndrome is required as part of the metabolic workup.


The diagnosis of NAFLD conventionally requires the exclusion of other chronic liver diseases, including excess alcohol use and viral hepatitis [13]. Steatosis of metabolic origin can occur in chronic hepatitis B, chronic hepatitis C, and alcoholic liver disease. In fact, the distinction between “alcoholic” and “non-alcoholic” may not be clear-cut, with overlap and heterogeneity between the two conditions. One example would be a high-alcohol-producing bacteria-Klebsiella pneumoniae, which resides in the gut microbiota of >60% Chinese NAFLD patients, and produces high levels of ethanol which accelerates the development of steatosis regardless of alcoholic intake [52].

In order to establish defined “positive” clinical criteria, an international panel of experts have detailed the rationale for an update of the nomenclature describing the liver disease associated with metabolic dysfunction, known as metabolic dysfunction-associated fatty liver disease (MAFLD) [53]. According to the recent international consensus statement, the diagnosis of MAFLD is based on the detection of liver steatosis combined with the coexistence of at least one of three positive criteria, which include overweight or obesity, T2DM, or clinical evidence of metabolic dysfunction, such as an increased waist circumference and an abnormal lipid or glycemic profile [54]. The diagnosis can be established irrespective of any presence of concomitant chronic liver disease. Concomitant MAFLD has been shown to be associated with adverse outcomes in both chronic hepatitis B virus (HBV) infection [55] and alcoholic liver disease [56]. Concomitant presence of diabetes, obesity, and metabolic screening should prompt screening, although it remains uncertain if screening may be beneficial for additional sub-groups.


An important risk factor for NAFLD development is increasing age, demonstrated by a NAFLD prevalence of over 50% in elderly Taiwanese (mean age: 70.3 years) [57], as well as over 60% of middle-aged (age >45 years) Southeast Asians [58]. Another important factor is sex, with NAFLD more common in men than in women, although NAFLD risk increases in women after menopause, suggesting that estrogen has a protective role [59]. Moreover, the impact of ethnicity cannot be ignored. As evidenced by a population‐based cohort in the United States, NAFLD prevalence differs significantly between ethnicities, being more common in non-Hispanic whites (28.4%) compared to Asian Americans (18.3%) [60]. Consistently, in another population study of 4,538 people, NAFLD prevalence was the lowest in non-Hispanic Blacks (18.0%) and Asians (18.1%), and the highest amongst Mexican Americans (48.4%). Within the NAFLD group, advanced fibrosis was the highest in non-Hispanic Blacks (28.5%) and the lowest amongst non-Hispanic Asians (2.7%) [61].

NAFLD is underdiagnosed in children due to a lack of recognition, screening, or appreciation of associated complications by healthcare providers. One study showed that less than one-third of children with obesity were screened for NAFLD through laboratory testing at clinic visits [62]. Children may not be recognized as being obese at clinic visits, and age-appropriate norms for BMI may go unacknowledged. Similar to adults, children with features of metabolic syndrome, such as obesity, hypertension, insulin resistance, and dyslipidemia, are at higher risk for NAFLD [63]. NAFLD may also be incidentally discovered in children while undergoing imaging. The 2017 North American Society of Pediatric Gastroenterology, Hepatology and Nutrition (NASPGHAN) guideline [16] recommends that screening for NAFLD should be considered for all obese youths starting at the age of 9–11 years with additional risk factors (central adiposity, insulin resistance, pre-diabetes or diabetes, dyslipidemia, sleep apnea, or family history of NAFLD/NASH) by alanine aminotransferase (ALT) levels, but recommends against using routine ultrasonography owing to low sensitivity. However, the 2018 AASLD guidance [13] has no recommendation regarding screening in children who are overweight and obese, due to a paucity of evidence.


Knowledge of the genetic component of NAFLD has grown exponentially, in part owing to genome-wide association studies and the advent of high-throughput omics technologies. Currently, at least five variants in different genes have been robustly associated with NAFLD [64], such as patatin-like phospholipase domain-containing protein 3 (PNPLA3), transmembrane 6 superfamily member 2 (TM6SF2), membrane bound O-acyltransferase domain-containing 7 (MBOAT7), glucokinase regulator (GCKR), and Hydroxysteroid 17-Beta Dehydrogenase 13 (HSD17B13). Carriers of the PNPLA3 I148M [65-67] and the TM6SF2 E167K variants [68,69] have a higher liver fat content and increased risk of NASH. Nevertheless, the incorporation of NAFLD genetic markers into routine clinical testing for the dynamic assessment of disease status and response to therapy has been protracted. While PNPLA3 I148M is the best-characterized genetic variant associated with NAFLD, its contribution to NAFLD heritability remains modest [70,71]. Accordingly, the EASL-EASD-EASO Clinical Practice Guidelines 2016 [12] do not recommend the testing of these genetic variants in routine clinical practice, although genotyping may be considered in selected patients and clinical studies.


The risk of undiagnosed liver disease in first-degree relatives of NAFLD patients has been of concern, particularly in those who have more advanced fibrosis. By using magnetic resonance elastography to quantify hepatic fibrosis in siblings, parents, and offspring of patients with NAFLD-cirrhosis [72], first-degree relatives of patients with NAFLD-cirrhosis have a 12 times higher risk of advanced fibrosis than healthy controls, even after adjustment for age, sex, ethnicity, BMI, and diabetes status, signifying that screening for advanced fibrosis in first-degree relatives of patients with NAFLD-cirrhosis can be beneficial. With that being said, both the 2016 EASL-EASD-EASO [12] and 2018 AASLD guidelines [13] stated that, until further evidence emerges, systematic screening of family members for NAFLD is not advisable currently.


Primary care would be taking up the main bulk of identifying patients with diabetes, dyslipidemia, hypertension, and components of metabolic syndrome; and are the optimal providers to identify patients with NAFLD, make appropriate referrals to specialists, and arrange appropriate surveillance. Once patients develop advanced fibrosis, the risk of liver-related mortality is exponentially increased [73]. Therefore, the challenge for primary care providers is the early identification of high-risk patients for specialist referral.

A prospective cohort study was designed to assess 1,118 patients with incidental abnormal liver function tests in the primary care setting and found the incidence rate of NAFLD to be 26.4% [74]. However, the number of primary care patients with abnormal liver enzymes may underestimate the true underlying prevalence, given the poor association between liver enzyme derangement and the presence of NAFLD. In terms of identifying patients with advanced fibrosis using the Enhanced Liver Fibrosis (ELF) test, with the low population prevalence of advanced fibrosis in the primary care setting, the positive predictive value of non-invasive testing was similarly low [75]. The use of non-invasive blood tests (a two-step algorithm combining FIB-4 score and ELF) for liver fibrosis improves the detection of advanced fibrosis and cirrhosis while reducing unnecessary referrals in patients with NAFLD [76]. With that being said, in order to implement primary care as a first-stage triage screening, primary care physicians need to be aware of the asymptomatic presentation of most NAFLD patients and understand the differences between NAFLD and NASH [77].


Liver biopsy is essential for the diagnosis of NASH, and is the only procedure that reliably differentiates NAFL from NASH [78]. A histologically-based scoring system, NAFLD activity score (NAS) [79,80], was developed and validated to fulfill the diagnostic criteria for NASH and include the full spectrum of NAFLD. Recent accurate quantitative assessments of liver fibrosis based on liver biopsy, such as second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy imaging [81], can improve the efficacy endpoint for fibrosis in NASH clinical trials and give a more precise method for NASH staging. According to the 2018 AASLD guideline [13], liver biopsy should be considered in patients with NAFLD who are at increased risk of steatohepatitis and advanced fibrosis. However, the risks of percutaneous liver biopsy, including bleeding, organ perforation, sepsis, and death, are also critical [82].

With the vast majority of NAFLD patients being stable and asymptomatic, performing liver biopsies on all patients is unfeasible and unethical for disease screening, diagnosis, or progression assessment. Non-invasive diagnostic methods using plasma samples, ultrasonography, liver elastography (including both transient and magnetic resonance) have been developed with good diagnostic performance for liver steatosis and fibrosis [83,84]. These methods have been widely used for early steatosis detection, disease severity assessment, identification of patients needing a liver biopsy for confirmatory diagnosis (e.g., after discrepant results) and for the assessment of fibrosis progression. While avoiding the risks associated with a liver biopsy, these non-invasive tools, with the possible exception of transient elastography, are also hampered by several limitations, including suboptimal sensitivity to evaluate the complete spectrum of NAFLD histological lesions and the lack of validity to be used for routine diagnosis (Table 3).

Current non-invasive methods for NAFLD screening

Several scoring systems have been established for further elucidation of the presence of NAFLD [85-93]. The FIB-4 index (calculated by four clinical variables: age, aspartate aminotransferase [AST], ALT, and platelet count) [94] and NFS (age, BMI, impaired fasting glucose and/or diabetes, AST, ALT, platelet count, and albumin) [95-97] have been recommended by the EASL-EASD-EASO guidelines [12] as part of the diagnostic algorithm for ruling out advanced fibrosis. Importantly, the NFS has been shown to predict liver decompensation and mortality in patients with NAFLD [95].

Conventional ultrasonography is the most common method for the qualitative assessment of hepatic steatosis due to its accessibility and low cost [98]. However, the ability to detect steatosis in patients with NASH is limited by the presence of advanced fibrosis [99]. Ultrasonography is useful at detecting moderate-to-severe steatosis with high diagnostic accuracy, with an area under the receiver operating characteristic curve (AUROC) of 0.93 [100], but is unable to discriminate between steatosis, fibrosis, inflammation, or NASH [101]. Furthermore, ultrasonography is also limited by both inter- and intra-observer reliability [102].

Vibration-controlled transient elastography (VCTE) is the most validated and commonly used elastography method worldwide [103]. VCTE measures the tissue elasticity, which is directly related to liver stiffness, and in turn, is related to the degree of fibrosis [104]. Besides liver stiffness assessment, controlled attenuation parameter (CAP) is obtained by VCTE to quantify the liver fat [105]. A CAP value ≥248 dB/m is the commonly used cut-off to define hepatic steatosis [106,107]. Mild (equivalent to number of affected hepatocytes: 5–33%), moderate (34–66%), and severe (>66%) steatosis are defined as CAP 248–267 dB/m, CAP 268–279 dB/m, and CAP ≥280 dB/m, respectively [106]. According to recently published cut-offs in a large multicenter study [108] and a meta-analysis [109], low risk of advanced fibrosis was defined as liver stiffness measurements <8.0 kPa, intermediate risk (8.0–12.0 kPa), and high risk >12.0 kPa.

MRI provides high specificity and sensitivity in detecting liver steatosis, especially MRI-PDFF. MRI-PDFF enables fat mapping of the entire liver, which is more accurate than CAP in detecting all grades of steatosis in NAFLD patients (AUROC 0.99) [110]. MRI-PDFF is usually used as a research tool and is not easily accessible in clinical practice due to the logistical complexities, lengthy scan time, and lack of required expertise at the majority of medical imaging centers [111]. Additionally, H-magnetic resonance spectroscopy (H-MRS) is a well-established and validated method of non-invasive liver fat quantification by directly measuring chemical composition of tissue [88]. H-MRS is highly accurate for even minimal amounts of steatosis [112], but its widespread application is also hampered by its cost and availability.

MRE enables non-invasive assessment of hepatic fibrosis, and is currently considered the most accurate non-invasive modality. MRE uses a modified phase-contrast method to image the propagation of the shear wave in the liver parenchyma for quantitatively assessing tissue stiffness [113,114]. A meta-analysis found that MRE detected fibrosis in NAFLD with a high level of accuracy (AUROC 0.86–0.91) for all stages [115]. This technique is more accurate than VCTE in detecting F2 fibrosis (AUROC 0.86–0.89 vs. AUROC 0.84) and F4 fibrosis (AUROC 0.88–0.97 vs. AUROC 0.95) [110,116]. However, its wider application is limited by cost, expertise, and availability. Currently, MRI-related techniques are unlikely to be applied as a first-line screening method in clinical practice.

Shear wave elastography (SWE) was developed based on the technological foundation of conventional ultrasonography. A potential advantage of SWE is the ability to perform measurements over a wider region of interest, thereby reducing sampling error [117]. Point shear wave elastography (pSWE) has similar advantages to VCTE in that the performance is better for severe fibrosis and cirrhosis than for the lower stages of fibrosis [88,117]. Unfortunately, pSWE does not allow for the assessment or quantification of steatosis. Values obtained with pSWE have a narrow range (0.5–4.4 m/s), which limits the definitions of cut-off values for discriminating different fibrosis stages, reducing its impact on management decisions [118]. There are no well-established cutoffs for pSWE in NAFLD patients.

In addition to the currently used screening modalities mentioned above, there are also various serum, metabolomic, stool, and device-based approaches (Table 4) that have potential for screening. Measuring the mean fluorescence intensity of perilipin-2 (PLIN2) or ras-related protein 14 (RAB14) in peripheral blood monocytes has been demonstrated to be an accurate liquid biopsy for NASH [119]; however, since it is detected by flow cytometry, its practicality for screening remains uncertain. Other promising markers, including serum thrombospondin-2 (TSP2) [120] and lipocalin-2 (LCN2) [121], lack validation and well-established cut-off values. Multi-spectral electrical impedance tomography (EIT) [122] is a self-administrative medical device for liver steatosis, but it is still in very early phases of development. Other methods with potential include metabolomic-based markers for fibrosis, ballooning and NASH [123-125], fecal-based bacterial signatures [126], and the 13C-methacetin breath test [127-129].

Potential future modalities for NAFLD screening


Most of the screening algorithms proposed to use these non-invasive assessments in a sequential algorithm [130,131]. A stepwise ultrasonography-FIB-4/NFS-VCTE strategy to screen for NAFLD is shown in Figure 1. First, ultrasonography is the preferred first-line diagnostic procedure for imaging of NAFLD. Fatty liver index (FLI), SteatoTest, and NAFLD liver fat score are acceptable alternatives for the diagnosis of steatosis if imaging tools are not available or feasible [12]. For fibrosis assessment, a non-invasive test with a single cut-off is performed in primary care or endocrinology units to exclude patients with a low risk of advanced fibrosis. FIB-4 or NFS are inexpensive, easy-to-perform tests for the exclusion of advanced fibrosis using a single cut-off (NFS <-1.455 and FIB-4 <1.30), and can be used as a first screening option for intermediate-to-high–risk patients. Both these tests may be influenced by age and should use a different cut-off for patients aged >65 years (NFS <0.12 and FIB-4 <2.0).

Once FIB-4 yields intermediate or high results, second-line VCTE can be used to improve the identification of advanced fibrosis, which has been shown to reduce the need for liver biopsy [131,132]. Patients can then undergo VCTE when advanced fibrosis cannot be excluded [133]. The cut-off for advanced fibrosis with VCTE is 8.0 kPa (M probe) or 6.2 kPa (XL probe) for the exclusion of advanced fibrosis. The XL probe is highly recommended in obese patients. Patients above the recommended thresholds should be referred to a hepatologist for subsequent management.

The optimal surveillance strategy for patients with NAFLD is undetermined. The variable risk of progression of both the hepatic disease and the underlying metabolic conditions, as well as the cost and workload for healthcare providers, need to be considered. According to the EASL-EASD-EASO algorithm [12], monitoring should include routine biochemistry, assessment of comorbidities, and non-invasive monitoring of fibrosis. NAFLD patients without worsening of metabolic risk factors, should be monitored at 2- to 3-year intervals. Patients with NASH and/or fibrosis should be monitored annually, and those with NASH cirrhosis at 6-month intervals. If indicated on a case-by-case basis, liver biopsy could be repeated after 5 years.


The question of whether NAFLD screening should be undertaken is deeply influenced by cost-effectiveness. High direct and indirect costs could be a barrier to screening. The AASLD guidelines do not recommend population screening for NAFLD [13]. Screening for liver fibrosis by VCTE at primary care centers is a highly cost-effective intervention and leads to earlier identification of patients in European and Asian populations, better than by standard of care alongside or using serum biomarkers [134]. Whether a two-step screening program using serum biomarkers followed by VCTE is more cost-effective and cost-saving in population screening should be tested in future studies. Moreover, the use of non-invasive liver fibrosis tests (FIB-4, ELF, or VCTE) in primary care increases early detection of advanced liver fibrosis, reduces unnecessary referral of patients with mild disease, and is cost-efficient [135]. Adopting a two-tier approach improves resource utilization [135].

For high-risk populations, one study found screening for NASH in T2DM (age >50 years) by ultrasonography to lack cost-effectiveness; however, that may in part be related to the study’s design, with the outcome measures of HCC and liver transplantation not being considered [136]. More recent data have supported the cost-effectiveness of screening. A comprehensive cost-utility analysis indicated that screening for NAFLD in patients with T2DM in the United States using an algorithm-based approach, starting with ultrasound and liver biochemistry and followed by VCTE for fibrosis to detect those most likely to have advanced fibrosis, was more cost-effective than the status quo of no screening [137]. Moreover, screening at a younger age will increase cost-effectiveness. However, comparisons of the cost-effectiveness of screening for NAFLD in general populations versus high-risk populations are still required.

FIB-4 followed by either VCTE, MRE, or liver biopsy can be cost-effective strategies for identifying cirrhosis in populations in whom the prevalence of cirrhosis varies between 0.27% and 4% [138]. Based on the U.S. health system, the combination of FIB-4 and VCTE, was the most cost-effective and the least costly, followed by the combination of FIB-4 and MRE. FIB-4 and VCTE remained the most cost-effective strategy if the aim were to avoid liver biopsy. Again, these findings require validation in other healthcare jurisdictions.


To this end, identifying high-risk populations based on the risk factors and metabolic characteristics for non-invasive screening is crucial. Screening all populations is generally not advisable and is not cost-effective [136]. Despite variations in international guidelines regarding how and who to screen, patients with T2DM, metabolic syndrome or persistently elevated liver enzymes may benefit the most from screening (Fig. 1). Screening for NAFLD in these high-risk patients, starting with ultrasound and liver biochemistry, and followed by non-invasive testing for fibrosis to detect advanced liver fibrosis, is more cost-effective than not screening this population [137]. The increasing availability of novel non-invasive tools, including transient elastography and MRI-based methods, will accurately quantify the severity of NAFLD and may help in screening and monitoring disease outcomes. The stepwise FIB-4/NFS-VCTE algorithm has been developed to rule out patients with a low risk of advanced fibrosis.

Figure 1.

Diagnostic flow-chart to assess and monitor disease severity in the presence of suspected NAFLD. NFS threshold: -1.455 in patients aged <65 years, 0.12 in patients aged ≥65 years. FIB-4 threshold: 1.30 in patients aged <65 years, 2.0 in patients aged ≥65 years. CAP, controlled attenuation parameter; FIB-4, fibrosis-4 index; FLI, fatty liver index; HCC, hepatocellular carcinoma; NAFLD, nonalcoholic fatty liver disease; NFS, NAFLD fibrosis score; VCTE, vibration controlled transient elastography; T2DM, type 2 diabetes mellitus; LSM, liver stiffness measurement.

Regardless of screening strategies, patient participation will always be a key determinant of success. This is a social and behavioral challenge, as screening is a personal choice that is ideally based on informed decision-making. Increased patient participation [139] and physician awareness of the importance of screening will be crucial in reducing the morbidity and mortality related to NAFLD.


Authors’ contribution

S Zhang: Conceptualization, Literature Review, Writing and Original Draft Preparation; LY Mak: Review, Critical Revision; MF Yuen: Review, Critical revision, final approval of published version; WK Seto: Review, Critical revision, final approval of published version.

Conflicts of Interest

MF Yuen is an advisory board member and/or received research funding from AbbVie, Arbutus Biopharma, Assembly Biosciences, Bristol Myer Squibb, Dicerna Pharmaceuticals, GlaxoSmithKline, Gilead Sciences, Janssen, Merck Sharp and Dohme, Clear B Therapeutics, Springbank Pharmaceuticals; and received research funding from Arrowhead Pharmaceuticals, Fujirebio Incorporation and Sysmex Corporation. WK Seto received speaker’s fees from AstraZeneca and Mylan, is an advisory board member of CSL Behring, is an advisory board member and received speaker’s fees from AbbVie, and is an advisory board member, received speaker’s fees and researching funding from Gilead Sciences. No other authors have any conflict of interest to disclose.



non-alcoholic fatty liver disease


nonalcoholic steatohepatitis


hepatocellular carcinoma


American Association for the Study of Liver Diseases


body mass index


European Association for the Study of Liver


European Association for the Study of Diabetes


European Association for the Study of Obesity


Asian Pacific Association for the Study of the Liver


Korean Association for the Study of the Liver


type 2 diabetes mellitus


type 1 diabetes mellitus


proton-magnetic resonance spectroscopy


magnetic resonance imaging-estimated proton density fat fraction


magnetic resonance elastography


NAFLD fibrosis score


metabolic dysfunction-associated fatty liver disease


North American Society of Pediatric Gastroenterology


aspartate aminotransferase


alanine aminotransferase


enhanced liver fibrosis


NAFLD activity score


second harmonic generation/two-photon excitation fluorescence


vibration-controlled transient elastography


controlled attenuation parameter


shear wave elastography


point shear wave elastography




ras-related protein 14






electrical impedance tomography


fatty liver index


1. Younossi ZM, Koenig AB, Abdelatif D, Fazel Y, Henry L, Wymer M. Global epidemiology of nonalcoholic fatty liver diseaseMeta-analytic assessment of prevalence, incidence, and outcomes. Hepatology 2016;64:73–84.
2. Singh S, Allen AM, Wang Z, Prokop LJ, Murad MH, Loomba R. Fibrosis progression in nonalcoholic fatty liver vs nonalcoholic steatohepatitis: a systematic review and meta-analysis of paired-biopsy studies. Clin Gastroenterol Hepatol 2015;13:643–654. e1-9.
3. Brunt EM. Pathology of nonalcoholic fatty liver disease. Nat Rev Gastroenterol Hepatol 2010;7:195–203.
4. Goldberg D, Ditah IC, Saeian K, Lalehzari M, Aronsohn A, Gorospe EC, et al. Changes in the prevalence of hepatitis C virus infection, nonalcoholic steatohepatitis, and alcoholic liver disease among patients with cirrhosis or liver failure on the waitlist for liver transplantation. Gastroenterology 2017;152:1090–1099. e1.
5. Simon TG, Roelstraete B, Khalili H, Hagström H, Ludvigsson JF. Mortality in biopsy-confirmed nonalcoholic fatty liver disease: results from a nationwide cohort. Gut 2021;70:1375–1382.
6. Taylor RS, Taylor RJ, Bayliss S, Hagström H, Nasr P, Schattenberg JM, et al. Association between fibrosis stage and outcomes of patients with nonalcoholic fatty liver disease: a systematic review and meta-analysis. Gastroenterology 2020;158:1611–1625. e12.
7. Hagström H, Nasr P, Ekstedt M, Hammar U, Stål P, Hultcrantz R, et al. Fibrosis stage but not NASH predicts mortality and time to development of severe liver disease in biopsy-proven NAFLD. J Hepatol 2017;67:1265–1273.
8. Wijarnpreecha K, Aby ES, Ahmed A, Kim D. Evaluation and management of extrahepatic manifestations of nonalcoholic fatty liver disease. Clin Mol Hepatol 2021;27:221–235.
9. Estes C, Anstee QM, Arias-Loste MT, Bantel H, Bellentani S, Caballeria J, et al. Modeling NAFLD disease burden in China, France, Germany, Italy, Japan, Spain, United Kingdom, and United States for the period 2016-2030. J Hepatol 2018;69:896–904.
10. Neilson LJ, Macdougall L, Lee PS, Hardy T, Beaton D, Chandrapalan S, et al. Implementation of a care bundle improves the management of patients with non-alcoholic fatty liver disease. Frontline Gastroenterol 2021;12:578–585.
11. Chalasani N, Younossi Z, Lavine JE, Diehl AM, Brunt EM, Cusi K, et al. The diagnosis and management of non-alcoholic fatty liver disease: practice Guideline by the American Association for the Study of Liver Diseases, American College of Gastroenterology, and the American Gastroenterological Association. Hepatology 2012;55:2005–2023.
12. European Association for the Study of the Liver (EASL), ; European Association for the Study of Diabetes (EASD), ; European Association for the Study of Obesity (EASO). EASL-EASDEASO clinical practice guidelines for the management of nonalcoholic fatty liver disease. J Hepatol 2016;64:1388–1402.
13. Chalasani N, Younossi Z, Lavine JE, Charlton M, Cusi K, Rinella M, et al. The diagnosis and management of nonalcoholic fatty liver disease: practice guidance from the American Association for the Study of Liver Diseases. Hepatology 2018;67:328–357.
14. Eslam M, Sarin SK, Wong VW, Fan JG, Kawaguchi T, Ahn SH, et al. The Asian Pacific Association for the Study of the Liver clinical practice guidelines for the diagnosis and management of metabolic associated fatty liver disease. Hepatol Int 2020;14:889–919.
15. Kang SH, Lee HW, Yoo JJ, Cho Y, Kim SU, Lee TH, et al, ; Korean Association for the Study of the Liver (KASL). KASL clinical practice guidelines: Management of nonalcoholic fatty liver disease. Clin Mol Hepatol 2021;27:363–401.
16. McPherson S, Armstrong MJ, Cobbold JF, Corless L, Anstee QM, Aspinall RJ, et al. Quality standards for the management of non-alcoholic fatty liver disease (NAFLD): consensus recommendations from the British Association for the Study of the Liver and British Society of Gastroenterology NAFLD Special Interest Group. Lancet Gastroenterol Hepatol 2022;7:755–769.
17. Vos MB, Abrams SH, Barlow SE, Caprio S, Daniels SR, Kohli R, et al. NASPGHAN clinical practice guideline for the diagnosis and treatment of nonalcoholic fatty liver disease in children: recommendations from the Expert Committee on NAFLD (ECON) and the North American Society of Pediatric Gastroenterology, Hepatology and Nutrition (NASPGHAN). J Pediatr Gastroenterol Nutr 2017;64:319–334.
18. Estrada E, Eneli I, Hampl S, Mietus-Snyder M, Mirza N, Rhodes E, et al, ; Children’s Hospital Association. Children’s Hospital Association consensus statements for comorbidities of childhood obesity. Child Obes 2014;10:304–317.
19. Barlow SE, ; Expert Committee. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics 2007;120 Suppl 4:S164–192.
20. American Diabetes Association. 4. Comprehensive medical evaluation and assessment of comorbidities: standards of medical care in diabetes-2019. Diabetes Care 2019;42(Suppl 1):S34–S45.
21. Sagan A, McDaid D, Rajan S, Farrington J, McKee M. Screening: when is it appropriate and how can we get it right? Copenhagen: European Observatory on Health Systems and Policies; 2020.
22. Smith BW, Adams LA. Nonalcoholic fatty liver disease and diabetes mellitus: pathogenesis and treatment. Nat Rev Endocrinol 2011;7:456–465.
23. Buzzetti E, Pinzani M, Tsochatzis EA. The multiple-hit pathogenesis of non-alcoholic fatty liver disease (NAFLD). Metabolism 2016;65:1038–1048.
24. Targher G, Byrne CD. Clinical review: nonalcoholic fatty liver disease: a novel cardiometabolic risk factor for type 2 diabetes and its complications. J Clin Endocrinol Metab 2013;98:483–495.
25. Tomah S, Alkhouri N, Hamdy O. Nonalcoholic fatty liver disease and type 2 diabetes: where do diabetologists stand? Clin Diabetes Endocrinol 2020;6:9.
26. Kotronen A, Juurinen L, Hakkarainen A, Westerbacka J, Cornér A, Bergholm R, et al. Liver fat is increased in type 2 diabetic patients and underestimated by serum alanine aminotransferase compared with equally obese nondiabetic subjects. Diabetes Care 2008;31:165–169.
27. Wong VW, Chu WC, Wong GL, Chan RS, Chim AM, Ong A, et al. Prevalence of non-alcoholic fatty liver disease and advanced fibrosis in Hong Kong Chinese: a population study using proton-magnetic resonance spectroscopy and transient elastography. Gut 2012;61:409–415.
28. Kwok R, Choi KC, Wong GL, Zhang Y, Chan HL, Luk AO, et al. Screening diabetic patients for non-alcoholic fatty liver disease with controlled attenuation parameter and liver stiffness measurements: a prospective cohort study. Gut 2016;65:1359–1368.
29. Doycheva I, Cui J, Nguyen P, Costa EA, Hooker J, Hofflich H, et al. Non-invasive screening of diabetics in primary care for NAFLD and advanced fibrosis by MRI and MRE. Aliment Pharmacol Ther 2016;43:83–95.
30. Bedogni G, Miglioli L, Masutti F, Tiribelli C, Marchesini G, Bellentani S. Prevalence of and risk factors for nonalcoholic fatty liver disease: the Dionysos nutrition and liver study. Hepatology 2005;42:44–52.
31. Frith J, Day CP, Robinson L, Elliott C, Jones DE, Newton JL. Potential strategies to improve uptake of exercise interventions in non-alcoholic fatty liver disease. J Hepatol 2010;52:112–116.
32. Aron-Wisnewsky J, Minville C, Tordjman J, Lévy P, Bouillot JL, Basdevant A, et al. Chronic intermittent hypoxia is a major trigger for non-alcoholic fatty liver disease in morbid obese. J Hepatol 2012;56:225–233.
33. Sasaki A, Nitta H, Otsuka K, Umemura A, Baba S, Obuchi T, et al. Bariatric surgery and non-alcoholic Fatty liver disease: current and potential future treatments. Front Endocrinol (Lausanne) 2014;5:164.
34. Subichin M, Clanton J, Makuszewski M, Bohon A, Zografakis JG, Dan A. Liver disease in the morbidly obese: a review of 1000 consecutive patients undergoing weight loss surgery. Surg Obes Relat Dis 2015;11:137–141.
35. Machado M, Marques-Vidal P, Cortez-Pinto H. Hepatic histology in obese patients undergoing bariatric surgery. J Hepatol 2006;45:600–606.
36. Naveau S, Lamouri K, Pourcher G, Njiké-Nakseu M, Ferretti S, Courie R, et al. The diagnostic accuracy of transient elastography for the diagnosis of liver fibrosis in bariatric surgery candidates with suspected NAFLD. Obes Surg 2014;24:1693–1701.
37. Wong VW, Vergniol J, Wong GL, Foucher J, Chan AW, Chermak F, et al. Liver stiffness measurement using XL probe in patients with nonalcoholic fatty liver disease. Am J Gastroenterol 2012;107:1862–1871.
38. Gaggini M, Morelli M, Buzzigoli E, DeFronzo RA, Bugianesi E, Gastaldelli A. Non-alcoholic fatty liver disease (NAFLD) and its connection with insulin resistance, dyslipidemia, atherosclerosis and coronary heart disease. Nutrients 2013;5:1544–1560.
39. Gómez-Ambrosi J, Silva C, Galofré JC, Escalada J, Santos S, Millán D, et al. Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity. Int J Obes (Lond) 2012;36:286–294.
40. Younossi ZM, Stepanova M, Negro F, Hallaji S, Younossi Y, Lam B, et al. Nonalcoholic fatty liver disease in lean individuals in the United States. Medicine (Baltimore) 2012;91:319–327.
41. Kojima S, Watanabe N, Numata M, Ogawa T, Matsuzaki S. Increase in the prevalence of fatty liver in Japan over the past 12 years: analysis of clinical background. J Gastroenterol 2003;38:954–961.
42. Das K, Das K, Mukherjee PS, Ghosh A, Ghosh S, Mridha AR, et al. Nonobese population in a developing country has a high prevalence of nonalcoholic fatty liver and significant liver disease. Hepatology 2010;51:1593–1602.
43. Younes R, Govaere O, Petta S, Miele L, Tiniakos D, Burt A, et al. Caucasian lean subjects with non-alcoholic fatty liver disease share long-term prognosis of non-lean: time for reappraisal of BMI-driven approach? Gut 2022;71:382–390.
44. Lonardo A, Nascimbeni F, Maurantonio M, Marrazzo A, Rinaldi L, Adinolfi LE. Nonalcoholic fatty liver disease: evolving paradigms. World J Gastroenterol 2017;23:6571–6592.
45. Eren F, Kaya E, Yilmaz Y. Accuracy of Fibrosis-4 index and nonalcoholic fatty liver disease fibrosis scores in metabolic (dysfunction) associated fatty liver disease according to body mass index: failure in the prediction of advanced fibrosis in lean and morbidly obese individuals. Eur J Gastroenterol Hepatol 2022;34:98–103.
46. Zou B, Yeo YH, Nguyen VH, Cheung R, Ingelsson E, Nguyen MH. Prevalence, characteristics and mortality outcomes of obese, nonobese and lean NAFLD in the United States, 1999-2016. J Intern Med 2020;288:139–151.
47. Ye Q, Zou B, Yeo YH, Li J, Huang DQ, Wu Y, et al. Global prevalence, incidence, and outcomes of non-obese or lean nonalcoholic fatty liver disease: a systematic review and metaanalysis. Lancet Gastroenterol Hepatol 2020;5:739–752.
48. Cornier MA, Dabelea D, Hernandez TL, Lindstrom RC, Steig AJ, Stob NR, et al. The metabolic syndrome. Endocr Rev 2008;29:777–822.
49. Ballestri S, Zona S, Targher G, Romagnoli D, Baldelli E, Nascimbeni F, et al. Nonalcoholic fatty liver disease is associated with an almost twofold increased risk of incident type 2 diabetes and metabolic syndrome. Evidence from a systematic review and meta-analysis. J Gastroenterol Hepatol 2016;31:936–944.
50. Zhang T, Zhang C, Zhang Y, Tang F, Li H, Zhang Q, et al. Metabolic syndrome and its components as predictors of nonalcoholic fatty liver disease in a northern urban Han Chinese population: a prospective cohort study. Atherosclerosis 2015;240:144–148.
51. Yamamura S, Kawaguchi T, Nakano D, Tomiyasu Y, Yoshinaga S, Doi Y, et al. Profiles of advanced hepatic fibrosis evaluated by FIB-4 index and shear wave elastography in health checkup examinees. Hepatol Res 2020;50:199–213.
52. Yuan J, Chen C, Cui J, Lu J, Yan C, Wei X, et al. Fatty liver disease caused by high-alcohol-producing Klebsiella pneumoniae. Cell Metab 2019;30:675-688.e7. Erratum in: Cell Metab 2019;30:1172.
53. Eslam M, Sanyal AJ, George J, ; International Consensus Panel. MAFLD: a consensus-driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology 2020;158:1999–2014. e1.
54. Eslam M, Newsome PN, Sarin SK, Anstee QM, Targher G, Romero-Gomez M, et al. A new definition for metabolic dysfunction-associated fatty liver disease: an international expert consensus statement. J Hepatol 2020;73:202–209.
55. Mak LY, Yuen MF, Seto WK. Letter regarding “A new definition for metabolic dysfunction-associated fatty liver disease: An international expert consensus statement”. J Hepatol 2020;73:1573–1574.
56. Boyle M, Masson S, Anstee QM. The bidirectional impacts of alcohol consumption and the metabolic syndrome: cofactors for progressive fatty liver disease. J Hepatol 2018;68:251–267.
57. Hung SC, Lai SW, Chen MC, Li PC, Lin KC. Prevalence and related factors of non-alcoholic fatty liver disease among the elderly in Taiwan. Eur Geriatr Med 2013;4:78–81.
58. Goh SC, Ho EL, Goh KL. Prevalence and risk factors of non-alcoholic fatty liver disease in a multiracial suburban Asian population in Malaysia. Hepatol Int 2013;7:548–554.
59. DiStefano JK. NAFLD and NASH in postmenopausal women: implications for diagnosis and treatment. Endocrinology 2020;161:bqaa134.
60. Golabi P, Paik J, Hwang JP, Wang S, Lee HM, Younossi ZM. Prevalence and outcomes of non-alcoholic fatty liver disease (NAFLD) among Asian American adults in the United States. Liver Int 2019;39:748–757.
61. Le MH, Yeo YH, Cheung R, Wong VW, Nguyen MH. Ethnic influence on nonalcoholic fatty liver disease prevalence and lack of disease awareness in the United States, 2011-2016. J Intern Med 2020;287:711–722.
62. Riley MR, Bass NM, Rosenthal P, Merriman RB. Underdiagnosis of pediatric obesity and underscreening for fatty liver disease and metabolic syndrome by pediatricians and pediatric subspecialists. J Pediatr 2005;147:839–842.
63. Patton HM, Lavine JE, Van Natta ML, Schwimmer JB, Kleiner D, Molleston J, ; Nonalcoholic Steatohepatitis Clinical Research Network. Clinical correlates of histopathology in pediatric nonalcoholic steatohepatitis. Gastroenterology 2008;135:1961–1971. e2.
64. Eslam M, Valenti L, Romeo S. Genetics and epigenetics of NAFLD and NASH: clinical impact. J Hepatol 2018;68:268–279.
65. Dongiovanni P, Donati B, Fares R, Lombardi R, Mancina RM, Romeo S, et al. PNPLA3 I148M polymorphism and progressive liver disease. World J Gastroenterol 2013;19:6969–6978.
66. Sookoian S, Pirola CJ. Meta-analysis of the influence of I148M variant of patatin-like phospholipase domain containing 3 gene (PNPLA3) on the susceptibility and histological severity of nonalcoholic fatty liver disease. Hepatology 2011;53:1883–1894.
67. Valenti L, Al-Serri A, Daly AK, Galmozzi E, Rametta R, Dongiovanni P, et al. Homozygosity for the patatin-like phospholipase-3/adiponutrin I148M polymorphism influences liver fibrosis in patients with nonalcoholic fatty liver disease. Hepatology 2010;51:1209–1217.
68. Liu YL, Reeves HL, Burt AD, Tiniakos D, McPherson S, Leathart JB, et al. TM6SF2 rs58542926 influences hepatic fibrosis progression in patients with non-alcoholic fatty liver disease. Nat Commun 2014;5:4309.
69. Dongiovanni P, Petta S, Maglio C, Fracanzani AL, Pipitone R, Mozzi E, et al. Transmembrane 6 superfamily member 2 gene variant disentangles nonalcoholic steatohepatitis from cardiovascular disease. Hepatology 2015;61:506–514.
70. Loomba R, Schork N, Chen CH, Bettencourt R, Bhatt A, Ang B, et al, ; Genetics of NAFLD in Twins Consortium. Heritability of hepatic fibrosis and steatosis based on a prospective twin study. Gastroenterology 2015;149:1784–1793.
71. Stender S, Kozlitina J, Nordestgaard BG, Tybjærg-Hansen A, Hobbs HH, Cohen JC. Adiposity amplifies the genetic risk of fatty liver disease conferred by multiple loci. Nat Genet 2017;49:842–847.
72. Caussy C, Soni M, Cui J, Bettencourt PRS, Schork N, Chen CH, et al, ; Familial NAFLD Cirrhosis Research Consortium. Nonalcoholic fatty liver disease with cirrhosis increases familial risk for advanced fibrosis. J Clin Invest 2017;127:2697–2704.
73. Dulai PS, Singh S, Patel J, Soni M, Prokop LJ, Younossi Z, et al. Increased risk of mortality by fibrosis stage in nonalcoholic fatty liver disease: Systematic review and meta-analysis. Hepatology 2017;65:1557–1565.
74. Armstrong MJ, Houlihan DD, Bentham L, Shaw JC, Cramb R, Olliff S, et al. Presence and severity of non-alcoholic fatty liver disease in a large prospective primary care cohort. J Hepatol 2012;56:234–240.
75. Vali Y, Lee J, Boursier J, Spijker R, Löffler J, Verheij J, et al, ; LITMUS systematic review team. Enhanced liver fibrosis test for the non-invasive diagnosis of fibrosis in patients with NAFLD: A systematic review and meta-analysis. J Hepatol 2020;73:252–262.
76. Srivastava A, Gailer R, Tanwar S, Trembling P, Parkes J, Rodger A, et al. Prospective evaluation of a primary care referral pathway for patients with non-alcoholic fatty liver disease. J Hepatol 2019;71:371–378.
77. Tokushige K, Ikejima K, Ono M, Eguchi Y, Kamada Y, Itoh Y, et al. Evidence-based clinical practice guidelines for nonalcoholic fatty liver disease/nonalcoholic steatohepatitis 2020. J Gastroenterol 2021;56:951–963.
78. Gunn NT, Shiffman ML. The use of liver biopsy in nonalcoholic fatty liver disease: when to biopsy and in whom. Clin Liver Dis 2018;22:109–119.
79. Kleiner DE, Brunt EM, Van Natta M, Behling C, Contos MJ, Cummings OW, et al, ; Nonalcoholic Steatohepatitis Clinical Research Network. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 2005;41:1313–1321.
80. Brunt EM, Kleiner DE, Wilson LA, Belt P, Neuschwander-Tetri BA, ; NASH Clinical Research Network (CRN). Nonalcoholic fatty liver disease (NAFLD) activity score and the histopathologic diagnosis in NAFLD: distinct clinicopathologic meanings. Hepatology 2011;53:810–820.
81. Soon G, Wee A. Updates in the quantitative assessment of liver fibrosis for nonalcoholic fatty liver disease: histological perspective. Clin Mol Hepatol 2021;27:44–57.
82. Neuberger J, Patel J, Caldwell H, Davies S, Hebditch V, Hollywood C, et al. Guidelines on the use of liver biopsy in clinical practice from the British Society of Gastroenterology, the Royal College of Radiologists and the Royal College of Pathology. Gut 2020;69:1382–1403.
83. Poynard T, Ratziu V, Benhamou Y, Thabut D, Moussalli J. Biomarkers as a first-line estimate of injury in chronic liver diseases: time for a moratorium on liver biopsy? Gastroenterology 2005;128:1146–1148. author reply 1148.
84. Sebastiani G, Alberti A. Non invasive fibrosis biomarkers reduce but not substitute the need for liver biopsy. World J Gastroenterol 2006;12:3682–3694.
85. Bedogni G, Bellentani S, Miglioli L, Masutti F, Passalacqua M, Castiglione A, et al. The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population. BMC Gastroenterol 2006;6:33.
86. Lee JH, Kim D, Kim HJ, Lee CH, Yang JI, Kim W, et al. Hepatic steatosis index: a simple screening tool reflecting nonalcoholic fatty liver disease. Dig Liver Dis 2010;42:503–508.
87. Munteanu M, Tiniakos D, Anstee Q, Charlotte F, Marchesini G, Bugianesi E, et al, ; FLIP Consortium and the FibroFrance Group. Diagnostic performance of FibroTest, SteatoTest and ActiTest in patients with NAFLD using the SAF score as histological reference. Aliment Pharmacol Ther 2016;44:877–889.
88. Wong VW, Adams LA, de Lédinghen V, Wong GL, Sookoian S. Noninvasive biomarkers in NAFLD and NASH - current progress and future promise. Nat Rev Gastroenterol Hepatol 2018;15:461–478.
89. Wong GL, Chan HL, Choi PC, Chan AW, Yu Z, Lai JW, et al. Noninvasive algorithm of enhanced liver fibrosis and liver stiffness measurement with transient elastography for advanced liver fibrosis in chronic hepatitis B. Aliment Pharmacol Ther 2014;39:197–208.
90. Guha IN, Parkes J, Roderick P, Chattopadhyay D, Cross R, Harris S, et al. Noninvasive markers of fibrosis in nonalcoholic fatty liver disease: validating the European Liver Fibrosis Panel and exploring simple markers. Hepatology 2008;47:455–460.
91. Nobili V, Parkes J, Bottazzo G, Marcellini M, Cross R, Newman D, et al. Performance of ELF serum markers in predicting fibrosis stage in pediatric non-alcoholic fatty liver disease. Gastroenterology 2009;136:160–167.
92. Imbert-Bismut F, Ratziu V, Pieroni L, Charlotte F, Benhamou Y, Poynard T, ; MULTIVIRC Group. Biochemical markers of liver fibrosis in patients with hepatitis C virus infection: a prospective study. Lancet 2001;357:1069–1075.
93. Munteanu M, Pais R, Peta V, Deckmyn O, Moussalli J, RaNgotziu Y, et al, ; FibroFrance Group. Long-term prognostic value of the FibroTest in patients with non-alcoholic fatty liver disease, compared to chronic hepatitis C, B, and alcoholic liver disease. Aliment Pharmacol Ther 2018;48:1117–1127.
94. Shaheen AA, Myers RP. Diagnostic accuracy of the aspartate aminotransferase-to-platelet ratio index for the prediction of hepatitis C-related fibrosis: a systematic review. Hepatology 2007;46:912–921.
95. Angulo P, Bugianesi E, Bjornsson ES, Charatcharoenwitthaya P, Mills PR, Barrera F, et al. Simple noninvasive systems predict long-term outcomes of patients with nonalcoholic fatty liver disease. Gastroenterology 2013;145:782–789. e4.
96. Angulo P, Hui JM, Marchesini G, Bugianesi E, George J, Farrell GC, et al. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology 2007;45:846–854.
97. Wong VW, Wong GL, Chim AM, Tse AM, Tsang SW, Hui AY, et al. Validation of the NAFLD fibrosis score in a Chinese population with low prevalence of advanced fibrosis. Am J Gastroenterol 2008;103:1682–1688.
98. Wong VW, Chan WK, Chitturi S, Chawla Y, Dan YY, Duseja A, et al. Asia-Pacific Working Party on Non-alcoholic Fatty Liver Disease guidelines 2017-Part 1: definition, risk factors and assessment. J Gastroenterol Hepatol 2018;33:70–85.
99. Hannah WN Jr, Harrison SA. Noninvasive imaging methods to determine severity of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Hepatology 2016;64:2234–2243.
100. Hernaez R, Lazo M, Bonekamp S, Kamel I, Brancati FL, Guallar E, et al. Diagnostic accuracy and reliability of ultrasonography for the detection of fatty liver: a meta-analysis. Hepatology 2011;54:1082–1090.
101. Dasarathy S, Dasarathy J, Khiyami A, Joseph R, Lopez R, McCullough AJ. Validity of real time ultrasound in the diagnosis of hepatic steatosis: a prospective study. J Hepatol 2009;51:1061–1067.
102. Cengiz M, Sentürk S, Cetin B, Bayrak AH, Bilek SU. Sonographic assessment of fatty liver: intraobserver and interobserver variability. Int J Clin Exp Med 2014;7:5453–5460.
103. Afdhal NH, Bacon BR, Patel K, Lawitz EJ, Gordon SC, Nelson DR, et al. Accuracy of fibroscan, compared with histology, in analysis of liver fibrosis in patients with hepatitis B or C: a United States multicenter study. Clin Gastroenterol Hepatol 2015;13:772–779. e1-3.
104. Asrani SK. Incorporation of noninvasive measures of liver fibrosis into clinical practice: diagnosis and prognosis. Clin Gastroenterol Hepatol 2015;13:2190–2204.
105. Sasso M, Beaugrand M, de Ledinghen V, Douvin C, Marcellin P, Poupon R, et al. Controlled attenuation parameter (CAP): a novel VCTE™ guided ultrasonic attenuation measurement for the evaluation of hepatic steatosis: preliminary study and validation in a cohort of patients with chronic liver disease from various causes. Ultrasound Med Biol 2010;36:1825–1835.
106. Karlas T, Petroff D, Sasso M, Fan JG, Mi YQ, de Lédinghen V, et al. Individual patient data meta-analysis of controlled attenuation parameter (CAP) technology for assessing steatosis. J Hepatol 2017;66:1022–1030.
107. Seto WK, Hui RWH, Mak LY, Fung J, Cheung KS, Liu KSH, et al. Association between hepatic steatosis, measured by controlled attenuation parameter, and fibrosis burden in chronic hepatitis B. Clin Gastroenterol Hepatol 2018;16:575–583. e2.
108. Papatheodoridi M, Hiriart JB, Lupsor-Platon M, Bronte F, Boursier J, Elshaarawy O, et al. Refining the Baveno VI elastography criteria for the definition of compensated advanced chronic liver disease. J Hepatol 2021;74:1109–1116.
109. Mózes FE, Lee JA, Selvaraj EA, Jayaswal ANA, Trauner M, Boursier J, et al, ; LITMUS Investigators. Diagnostic accuracy of noninvasive tests for advanced fibrosis in patients with NAFLD: an individual patient data meta-analysis. Gut 2022;71:1006–1019.
110. Park CC, Nguyen P, Hernandez C, Bettencourt R, Ramirez K, Fortney L, et al. Magnetic resonance elastography vs transient elastography in detection of fibrosis and noninvasive measurement of steatosis in patients with biopsy-proven nonalcoholic fatty liver disease. Gastroenterology 2017;152:598–607. e2.
111. European Association for Study of Liver, ; Asociacion Latinoamericana para el Estudio del Higado. EASL-ALEH Clinical Practice Guidelines: Non-invasive tests for evaluation of liver disease severity and prognosis. J Hepatol 2015;63:237–264.
112. Bohte AE, van Werven JR, Bipat S, Stoker J. The diagnostic accuracy of US, CT, MRI and 1H-MRS for the evaluation of hepatic steatosis compared with liver biopsy: a meta-analysis. Eur Radiol 2011;21:87–97.
113. Venkatesh SK, Yin M, Ehman RL. Magnetic resonance elastography of liver: technique, analysis, and clinical applications. J Magn Reson Imaging 2013;37:544–555.
114. Dulai PS, Sirlin CB, Loomba R. MRI and MRE for non-invasive quantitative assessment of hepatic steatosis and fibrosis in NAFLD and NASH: Clinical trials to clinical practice. J Hepatol 2016;65:1006–1016.
115. Singh S, Venkatesh SK, Wang Z, Miller FH, Motosugi U, Low RN, et al. Diagnostic performance of magnetic resonance elastography in staging liver fibrosis: a systematic review and metaanalysis of individual participant data. Clin Gastroenterol Hepatol 2015;13:440–451. e6.
116. Imajo K, Kessoku T, Honda Y, Tomeno W, Ogawa Y, Mawatari H, et al. Magnetic Resonance imaging more accurately classifies steatosis and fibrosis in patients with nonalcoholic fatty liver disease than transient elastography. Gastroenterology 2016;150:626–637. e7.
117. Cassinotto C, Boursier J, de Lédinghen V, Lebigot J, Lapuyade B, Cales P, et al. Liver stiffness in nonalcoholic fatty liver disease: A comparison of supersonic shear imaging, FibroScan, and ARFI with liver biopsy. Hepatology 2016;63:1817–1827.
118. Cassinotto C, Lapuyade B, Mouries A, Hiriart JB, Vergniol J, Gaye D, et al. Non-invasive assessment of liver fibrosis with impulse elastography: comparison of Supersonic Shear Imaging with ARFI and FibroScan®. J Hepatol 2014;61:550–557.
119. Angelini G, Panunzi S, Castagneto-Gissey L, Pellicanò F, De Gaetano CAH, Pompili M, et al. Accurate liquid biopsy for the diagnosis of non-alcoholic steatohepatitis and liver fibrosis. Gut 2022;doi: 10.1136/gutjnl-2022-327498 [Epub ahead of print].
120. Lee CH, Seto WK, Lui DT, Fong CH, Wan HY, Cheung CY, et al. Circulating thrombospondin-2 as a novel fibrosis biomarker of nonalcoholic fatty liver disease in type 2 diabetes. Diabetes Care 2021;44:2089–2097.
121. Xu G, Wang YM, Ying MM, Chen SD, Li ZR, Ma HL, et al. Serum lipocalin-2 is a potential biomarker for the clinical diagnosis of nonalcoholic steatohepatitis. Clin Mol Hepatol 2021;27:329–345.
122. Touboul A, Zouari F, Minciullo L, Modak D, Lee RMV, Wong EC, et al. Unmixing multi-spectral electrical impedance tomography (EIT) predicts clinical-standard controlled attenuation parameter (CAP) for nonalcoholic fatty liver disease classification: a feasibility study. Annu Int Conf IEEE Eng Med Biol Soc 2022;2022:576–579.
123. Gaggini M, Carli F, Rosso C, Buzzigoli E, Marietti M, Della Latta V, et al. Altered amino acid concentrations in NAFLD: Impact of obesity and insulin resistance. Hepatology 2018;67:145–158.
124. Kim HY. Recent advances in nonalcoholic fatty liver disease metabolomics. Clin Mol Hepatol 2021;27:553–559.
125. Nimer N, Choucair I, Wang Z, Nemet I, Li L, Gukasyan J, et al. Bile acids profile, histopathological indices and genetic variants for non-alcoholic fatty liver disease progression. Metabolism 2021;116:154457.
126. Loomba R, Seguritan V, Li W, Long T, Klitgord N, Bhatt A, et al. Gut microbiome-based metagenomic signature for noninvasive detection of advanced fibrosis in human nonalcoholic fatty liver disease. Cell Metab 2017;25:1054–1062. e5. Erratum in: Cell Metab 2019;30:607.
127. Molina-Molina E, Shanmugam H, Di Ciaula A, Grattagliano I, Di Palo DM, Palmieri VO, et al. (13C)-Methacetin breath test provides evidence of subclinical liver dysfunction linked to fat storage but not lifestyle. JHEP Rep 2020;3:100203.
128. Fierbinteanu-Braticevici C, Plesca DA, Tribus L, Panaitescu E, Braticevici B. The role of 13C-methacetin breath test for the non-invasive evaluation of nonalcoholic fatty liver disease. J Gastrointestin Liver Dis 2013;22:149–156.
129. Braden B, Faust D, Sarrazin U, Zeuzem S, Dietrich CF, Caspary WF, et al. 13C-methacetin breath test as liver function test in patients with chronic hepatitis C virus infection. Aliment Pharmacol Ther 2005;21:179–185.
130. Vilar-Gomez E, Chalasani N. Non-invasive assessment of nonalcoholic fatty liver disease: Clinical prediction rules and blood-based biomarkers. J Hepatol 2018;68:305–315.
131. Boursier J, Guillaume M, Leroy V, Irlès M, Roux M, Lannes A, et al. New sequential combinations of non-invasive fibrosis tests provide an accurate diagnosis of advanced fibrosis in NAFLD. J Hepatol 2019;71:389–396.
132. Petta S, Wong VW, Cammà C, Hiriart JB, Wong GL, Vergniol J, et al. Serial combination of non-invasive tools improves the diagnostic accuracy of severe liver fibrosis in patients with NAFLD. Aliment Pharmacol Ther 2017;46:617–627.
133. Maya-Miles D, Ampuero J, Gallego-Durán R, Dingianna P, Romero-Gómez M. Management of NAFLD patients with advanced fibrosis. Liver Int 2021;41 Suppl 1:95–104.
134. Serra-Burriel M, Graupera I, Torán P, Thiele M, Roulot D, Wai- Sun Wong V, et al, ; investigators of the LiverScreen Consortium. Transient elastography for screening of liver fibrosis: cost-effectiveness analysis from six prospective cohorts in Europe and Asia. J Hepatol 2019;71:1141–1151.
135. Srivastava A, Jong S, Gola A, Gailer R, Morgan S, Sennett K, et al. Cost-comparison analysis of FIB-4, ELF and fibroscan in community pathways for non-alcoholic fatty liver disease. BMC Gastroenterol 2019;19:122.
136. Corey KE, Klebanoff MJ, Tramontano AC, Chung RT, Hur C. Screening for nonalcoholic steatohepatitis in individuals with type 2 diabetes: a cost-effectiveness analysis. Dig Dis Sci 2016;61:2108–2117.
137. Noureddin M, Jones C, Alkhouri N, Gomez EV, Dieterich DT, Rinella ME, ; NASHNET. Screening for nonalcoholic fatty liver disease in persons with type 2 diabetes in the United States is cost-effective: a comprehensive cost-utility analysis. Gastroenterology 2020;159:1985–1987. e4. Erratum in: Gastroenterology 2021;160:2226.
138. Vilar-Gomez E, Lou Z, Kong N, Vuppalanchi R, Imperiale TF, Chalasani N. Cost effectiveness of different strategies for detecting cirrhosis in patients with nonalcoholic fatty liver disease based on United States health care system. Clin Gastroenterol Hepatol 2020;18:2305–2314. e12.
139. Ng CH, Lim WH, Chin YH, Yong JN, Zeng RW, Chan KE, et al. Living in the non-alcoholic fatty liver disease silent epidemic: a qualitative systematic review of patients’ perspectives. Aliment Pharmacol Ther 2022;56:570–579.

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Figure 1.

Diagnostic flow-chart to assess and monitor disease severity in the presence of suspected NAFLD. NFS threshold: -1.455 in patients aged <65 years, 0.12 in patients aged ≥65 years. FIB-4 threshold: 1.30 in patients aged <65 years, 2.0 in patients aged ≥65 years. CAP, controlled attenuation parameter; FIB-4, fibrosis-4 index; FLI, fatty liver index; HCC, hepatocellular carcinoma; NAFLD, nonalcoholic fatty liver disease; NFS, NAFLD fibrosis score; VCTE, vibration controlled transient elastography; T2DM, type 2 diabetes mellitus; LSM, liver stiffness measurement.

Table 1.

Current guidance on screening for NAFLD

Professional organizations Year Guidance statements
European Association for the Study of Liver (EASL), European Association for the Study of Diabetes (EASD), and European Association for the Study of Obesity (EASO) [12] 2016 Screening for NAFLD in people with obesity, metabolic syndrome, and in particular, T2DM
American Association for the Study of Liver Diseases (AASLD) [13] 2018 1. Routine screening for NAFLD in high-risk populations (obesity, T2DM) is not advised due to uncertainties in diagnostic testing, long-term management, and cost-effectiveness
2. Endorses “vigilance” in patients with T2DM
3. Systematic screening of family members for NAFLD is not currently recommended
Asian Pacific Association for the Study of the Liver (APASL) [14] 2020 Screening in those with T2DM or metabolic syndrome, or those who are overweight/obese according to ethnic-specific cut-offs
The American Academy of Pediatrics [17-19] 2007; 2014; 2017 1. Currently, the best screening test for NAFLD in children is ALT; however, it has substantial limitations.
2. Screening should be considered for obese youth with additional risk factors (central adiposity, insulin resistance, pre-diabetes or diabetes, dyslipidemia, sleep apnea, or family history of NAFLD/ NASH)
3. Follow-up screening for NAFLD is recommended. When the initial screening test is normal, consider repeating ALT every 2–3 years if risk factors remain unchanged
The American Diabetes Association (ADA) [20] 2019 Patients with type 2 diabetes or prediabetes and elevated liver enzymes (ALT) or fatty liver on ultrasound should be evaluated for the presence of non-alcoholic steatohepatitis and liver fibrosis
Korean Association for the Study of the Liver (KASL) [15] 2021 1. Subjects who have persistent liver enzyme elevation, metabolic syndrome, or diabetes should be screened for NAFLD
2. Abdominal ultrasonography is the primary screening modality
British Association for the Study of the Liver (BASL) and British Society of Gastroenterology (BSG) NAFLD Special Interest Group [16] 2022 1. Services should have an agreed local clinical pathway for the investigation of suspected liver disease
2. Consider the possibility of liver fibrosis due to NAFLD in people with T2DM or metabolic syndrome

NAFLD, non-alcoholic fatty liver disease; T2DM, type 2 diabetes mellitus; ALT, alanine aminotransferase; NASH, nonalcoholic steatohepatitis.

Table 2.

Differences among international guidelines in screening recommendations for NAFLD in high-risk populations

Populations Supporting screening Guidelines Against screening Guidelines
Age >50 years 2016 EASL-EASD-EASO
Obesity √√ 2016 EASL-EASD-EASO X 2018 AASLD
2019 APASL
Type 2 diabetes √√√ 2016 EASL-EASD-EASO X 2018 AASLD
2019 APASL
2021 KASL
Metabolic syndrome √√√ 2016 EASL-EASD-EASO
2019 APASL
2021 KASL
Persistently abnormal liver enzymes √√√ 2016 EASL-EASD-EASO
2019 APASL
2021 KASL
Obese youth with additional risk factors* The American Academy of ediatrics
First-degree relatives of NAFLD XX 2016 EASL-EASD-EASO
2018 AASLD
Genetic variants XX 2016 EASL-EASD-EASO
2018 AASLD

NAFLD, non-alcoholic fatty liver disease; EASL, European Association for the Study of Liver; EASD, European Association for the Study of Diabetes; EASO, European Association for the Study of Obesity; APASL, Asian Pacific Association for the Study of the Liver; KASL, Korean Association for the Study of the Liver; AASLD, American Association for the Study of Liver Diseases; NASH, nonalcoholic steatohepatitis.

√ indicated the number of guidelines that support screening for NAFLD in this population. X indicated the number of guidelines against screening for NAFLD in this population. The number of markers indicate the strength of recommendation.


Such as central adiposity, insulin resistance, pre-diabetes or diabetes, dyslipidemia, sleep apnea, and family history of NAFLD/NASH.

Table 3.

Current non-invasive methods for NAFLD screening

Diagnostic panel Cost Features Detection abilities
Steatosis Advanced fibrosis Cirrhosis
Serological markers
Fatty liver index [85] $ Common parameters involved (BMI, WC, triglycerides, and GGT) X X
Cannot distinguish between steatosis grades
Hepatic steatosis index [86] $ Common parameters involved (AST: ALT ratio, BMI, female sex, and DM) X X
Inadequate distinction of the severity of steatosis
SteatoTest [87,88] $$ Involves biomarkers that are not routinely done (α2M, haptoglobin, ApoA-1, total bilirubin, GGT, fasting glucose, triglycerides, cholesterol, and ALT, adjusted for patient's age, sex, weight, and height) X X
FIB-4 [94] $ A formula comprising age, platelet, AST, and ALT X
One of the best non-invasive tests for diagnosing advanced fibrosis in NAFLD
Rules out advanced fibrosis
NFS [95-97] $ A formula comprising age, hyperglycemia, BMI, platelet count, albumin, and AST/ALT ratio X
Identifies advanced fibrosis well
Needs independent adjustment of BMI across ethnic groups
BARD score [95] $ A formula comprising BMI, AST/ALT ratio, and diabetes X
Does not predict fibrosis well in patients with mild NAFLD (specifically in patients with obesity or T2DM), which limits its clinical use
ELF [89-91] $$ Consists of an algorithm of three fibrosis markers (HA, PIIINP, and TIMP-1) that are not routinely measured X
Rules out advanced fibrosis
FibroTest [87,92,93] $$ Involves biomarkers that are not routinely done (α2M, haptoglobin, ApoA-1, total bilirubin, GGT) X X
Affected by other causes of hyperbilirubinemia and elevated GGT
Imaging modalities
Ultrasonography [99-101] $ AUROC 0.97 good predictive tool for steatosis but does not provide information regarding fibrosis, unless cirrhosis is established X
VCTE [105-107,111] $ AUROC 0.84 for F2 fibrosis with the M probe √ √ √ √ √ √
AUROC 0.93 for F3 fibrosis with the M probe
AUROC 0.95 for F4 fibrosis with the M probe
AUROC 0.80–0.85 for F2 fibrosis with the XL probe
AUROC 0.84–0.90 for F3 fibrosis with the XL probe
AUROC 0.91–0.95 for F4 fibrosis with the XL probe
Not accurate in patients with cholestasis, ascites, and congestive heart failure
MRI-PDFF [110-112] $$$ Good specificity and sensitivity in detecting steatosis √ √ X X
Less reliable for grading steatosis in patients with advanced fibrosis or cirrhosis
Cannot be performed in patients with claustrophobia, and the measurements are affected by hepatic iron deposition
Not widely available
MRS [112] $$$ Results of this tool might be affected by respiration movements, claustrophobia, and implanted devices √ √ √ X X
Only available in specialized centers
MRE [110,113-116] $$$ AUROC 0.86–0.89 for F2 fibrosis X √ √ √ √ √ √
AUROC 0.89–0.96 for F3 fibrosis
AUROC 0.88–0.97 for F4 fibrosis
Accessibility is limited by requirement of specific scanner hardware
SWE [88,117,118] $ No well-established cutoffs for NAFLD X √ √ √ √
Results may differ from liver biopsy; accurate if >30% of hepatocytes are steatotic
Reduced sampling errors

NAFLD, non-alcoholic fatty liver disease; BMI, body mass index; WC, waist circumference; GGT, gamma‐glutamyltransferase; DM, diabetes mellitus; ALT, alanine aminotransferase; AST, aspartate aminotransferase; FIB-4, fibrosis-4; NFS, NAFLD fibrosis score; T2DM, type 2 diabetes mellitus; ELF, enhanced liver fibrosis; AUROC, area under the receiver operating characteristic curve; VCTE, vibration-controlled transient elastography; MRI-PDFF, magnetic resonance imaging-estimated proton density fat fraction; MRS, magnetic resonance spectroscopy; MRE, magnetic resonance elastography; SWE, shear wave elastography; α2M, α2-macroglobulin; ApoA-1, Apolipoprotein AI; BARD, body mass index, AST/ALT ratio, and diabetes; HA, hyaluronic acid; PIIINP, type III procollagen peptide; TIMP-1, tissue inhibitor of metalloproteinases-1.

$ indicated the relative cost of using this method for NAFLD screening. $, relatively low; $$, relatively medium; $$$, relatively high. √ indicated the relative detection abilities of this method. $, relatively low; √, relatively medium; √, relatively high. X indicated that this screening method could not detect steatosis, advanced fibrosis, or cirrhosis.

Table 4.

Potential future modalities for NAFLD screening

Developing modalities Components AUROC Comments
Serum-based Perilipin-2 (PLIN2) [119] mean fluorescence intensity Combined with waist circumference, triglyceride, ALT and presence/absence of diabetes as covariates as a biomarker for NASH An accuracy of 93% in the discovery cohort and 92% in the validation cohort Using flow cytometry to measure PLIN2 in peripheral blood monocytes
Current form not feasible for screening
Ras-related protein (RAB14) [119] mean fluorescence intensity Combined with age, waist circumference, high-density lipoprotein cholesterol, plasma glucose, and ALT levels as covariates as a biomarker for NASH 99.3%, significantly higher than NFS (85.2%), FIB-4 (62.2%), APRI (61.8%) Using flow cytometry to measure RAB14 in peripheral blood monocytes
Current form not feasible for screening
Thrombospondin-2 (TSP2) [120] A novel fibrosis biomarker of NAFLD in T2DM 0.80, indicating fibrosis ≥F3 on VCTE, superior to both FIB-4 and NFS Existing commercial enzyme- linked Immuno-sorbent Assay
Cutoff: 3.6 ng/mL to identify ≥F3 fibrosis
Lipocalin-2 (LCN2) [121] A valuable NAFLD biomarker, especially for the transition from NAFL to NASH AUC: 0.987 for NASH diagnosis, and AUC: 0.977 for steatosis Unable to establish an optimal cut-off value for distinguishing NASH from NAFL
Using a rapid, portable, point-of- care, and user-friendly point-of- care assay
Metabolomics Amino acids [123,124] The ratio of glutamate/(serine+glycine) F0–F2 vs. F3–F4, highest odds ratio (OR) for liver fibrosis (F3–4) Using gas chromatography-mass spectrometry
Current form not feasible for screening
Bile acids [124,125] 7-ketodeoxycholic acid (7-Keto-DCA) Advanced fibrosis (OR, 4.2), NASH (OR, 24.5), and hepatocellular ballooning (OR, 18.7) Biomarkers for NAFLD progression
Independent validation is required
Using a stable isotope-dilution LC- MS/MS method
Current form not feasible for screening
7-ketolithocholic acid (7-Keto-LCA) NASH (OR, 9.4) and ballooning (OR, 5.9)
Stool-based Fecal-microbiome derived metagenomic signature [126] 37 bacterial species are used to construct a Random Forest classifier model to detect advanced fibrosis in NAFLD A robust diagnostic accuracy (AUC 0.936) Need to utilize metagenomics sequencing
Current form not feasible for screening
Device-based Multi-spectral EIT [122] Using waist-over-height biometric as complementary information Predict clinicalstandard CAP in patients with or without NAFLD Portable
Potentially cost-effective and with a short acquisition time (3 minutes)
Only with pilot results, need validation in large cohorts
13C-methacetin breath test [127,128] Quantitative evaluation of the cytochrome P450-dependent liver function A good tool for identifying patients with histologically proven NASH (AUROC: 0.824); Separate patients with normal/NAFL from patients with NASH
Fail to detect early stages of fibrosis
Predicts F3 or F4 fibrosis (AUROC: 0.936 and 0.973) Mainly investigated in patients with chronic hepatitis C

NAFLD, non-alcoholic fatty liver disease; AUROC, area under the receiver operating characteristic curve; ALT, alanine aminotransferase; NASH, nonalcoholic steatohepatitis; NFS, NAFLD fibrosis score; FIB-4, fibrosis-4; AST, aspartate aminotransferase; APRI, AST to platelet ratio index; T2DM, type 2 diabetes mellitus; VCTE, vibration-controlled transient elastography; AUROC, the area under a receiver operating characteristic curve; AUC, area under the curve; EIT, electrical impedance tomography; CAP, controlled attenuation parameter; LC-MS/MS, liquid chromatography-mass spectrometry/mass spectrometry.