This study was designed as a scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines (7), The protocol of this study was registered on Open Science Framework (OSF)(https://osf.io/u4nw7). The methodological framework proposed by Daudt et al. was adopted to comprehensively examine the current status and characteristics of research on inflammatory and metabolic biomarkers in the non-invasive diagnosis of NAFLD.

This review focuses on two core questions:

A comprehensive literature search was conducted across multiple databases, with tailored search terms for each platform: Chinese databases included CNKI, Wanfang, and VIP; English databases included PubMed, Web of Science, Cochrane Library, and Embase. The strategy combined subject headings and free-text terms using Boolean operators. Reference lists were also manually searched using snowballing techniques to identify additional systematic reviews. The search covered publications up to August 31, 2024. For example, the PubMed search strategy is detailed in Table 1 . The search strategies for other databases can be found in Supplementary Material 1 .

Based on the PCC framework for scoping reviews (8)—Participants, Concept, and Context—the inclusion criteria were:

Exclusion criteria were:

All retrieved records were imported into EndNote for deduplication. A two-stage screening process was then conducted. In the first round, two reviewers independently screened titles and abstracts. In the second round, full texts were reviewed. Disagreements were resolved through discussion or consultation with a third reviewer. Data extracted included author, publication year, country/region, study design, participant characteristics, sample size, type of biomarker, and its association with NAFLD.

Two reviewers independently assessed the methodological quality of included studies. The Cohen’s Kappa (κ) between the reviewers was 0.80, indicating almost perfect agreement (9).Cohort and case-control studies were evaluated using the Newcastle-Ottawa Scale (NOS) (10), which includes three domains: selection, comparability, and exposure assessment, with a maximum score of 9. Scores of 0–3, 4–6, and 7–9 were interpreted as indicative of low, moderate, and high methodological quality, respectively.

Cross-sectional studies were evaluated using the quality assessment tool developed by the Agency for Healthcare Research and Quality (AHRQ) (11), comprising 11 items. Total scores of 0-3, 4-7, and 8–11 indicated low, medium, and high quality, respectively (12). Any disagreements were resolved through discussion or by a third reviewer.

A total of 27,864 studies were retrieved from seven databases: CNKI (n=744), Wanfang (n=3,078), VIP (n=143), PubMed (n=5,565), Web of Science (n = 8,767), Cochrane Library (n=2,468), and Embase (n=7,099). After removing duplicates, 12,061 articles remained for screening. Based on pre-established inclusion and exclusion criteria, 15 studies were finally included (6 in Chinese and 9 in English). The study selection process is shown in the PRISMA flow diagram (13) ( Figure 1 ).

The 15 studies were published between 2009 and 2024 and conducted in China (n =10), Turkey (n=1), Germany (n=1), Iran (n=1), Egypt (n=1), and the United States (n= 1). Most were case-control studies (n=11), with additional cohort studies (n=2), one cross-sectional study, and one retrospective study. Sample sizes ranged from 42 to 11,883 participants, including both adults and children. All included studies scored ≥7 in methodological quality assessments, indicating generally high quality. To unify the analytical logic, biomarkers were categorized into five functional groups: Inflammatory markers: CRP, IL-6, TNF-α, IL-1β, IL-18;Immune cell-derived ratios: NLR, MHR, SII, AISI, Th17/Treg;Metabolic markers: TyG index, FGF21, adiponectin, visfatin;Liver injury/inflammatory markers: CK18, OPN, PTX3, LCN2;Oxidative stress markers: Serum uric acid, hemoglobin.Detailed information is presented in Table 2 .

Findings from the included studies suggest that inflammatory, metabolic, and liver injury biomarkers—as well as derived immune-inflammatory ratios—have potential clinical utility in identifying and stratifying different stages of NAFLD.

Inflammatory biomarkers such as IL-6, IL-1β, IL-18, TNF-α, and CRP were positively correlated with NAFLD severity, particularly IL-6 and TNF-α, which demonstrated value in disease stratification and phenotype identification.

Immune cell-derived inflammatory ratios (e.g., Th17/Treg, NLR, MHR) are accessible through routine blood tests, making them cost-effective and convenient indicators of systemic or cellular immune inflammation. Several studies found that combining these markers in predictive models enhanced diagnostic accuracy for NASH and fibrosis progression compared to traditional single biomarkers.

Metabolic biomarkers such as FGF21, TyG index, and adiponectin were closely linked to insulin resistance and hepatic steatosis, indicating their suitability for early diagnosis and high-risk population screening.

Liver injury/inflammatory biomarkers such as CK18, LCN2, PTX3, and OPN showed good performance in disease classification and fibrosis risk prediction. CK18 and LCN2 reflect hepatocellular apoptosis and tissue damage, while OPN and PTX3 are involved in inflammation-mediated fibrogenesis, aiding in the identification of NASH and advanced high-risk patients.

Oxidative stress-related biomarkers, including elevated serum uric acid and hemoglobin levels, were independently associated with NAFLD, possibly reflecting oxidative stress and metabolic burden. These may serve as useful tools for early detection in high-risk individuals.

Inflammatory responses play a pivotal role in the pathogenesis of non-alcoholic fatty liver disease (NAFLD), exacerbating lipid metabolic disturbances and insulin resistance while directly promoting hepatic fat accumulation and chronic disease progression. Current evidence highlights the diagnostic significance of classical acute-phase proteins, pro-inflammatory cytokines, and immune cell-derived inflammatory ratios in disease stratification, staging assessment, and fibrosis risk prediction in NAFLD.

An imbalance between Th17 and Treg cells is a hallmark of immune dysregulation in NAFLD. Th17 cells secrete pro-inflammatory cytokines such as IL-17, contributing to hepatic inflammation and lipid accumulation, whereas Treg cells release IL-10 and exert immunosuppressive and anti-inflammatory effects (68, 69). Studies have shown that the Th17/Treg ratio is significantly elevated in patients with NAFLD and is closely associated with insulin resistance and liver injury, indicating its potential as an early warning signal for NASH risk (18).

Peripheral counts of neutrophils, monocytes, and lymphocytes, as well as their derived ratios, serve as accessible indicators of systemic inflammation and have demonstrated potential in early NAFLD screening (68, 70). Neutrophil infiltration is a characteristic feature of NASH, and elevated neutrophil counts have been identified as an independent risk factor for NAFLD (71). As key components of innate immunity, intermediate monocyte subsets (CD14++CD16+) are significantly increased in NAFLD and may serve as potential predictive markers (72).

CD4+ T lymphocytes play a central role in adaptive immune regulation and can differentiate into Th1, Th2, Th17, and Treg subsets, coordinating both pro- and anti-inflammatory responses in liver tissue (73). Impaired proliferation and activation of CD4+ and CD8+ T cells may compromise immune surveillance, thereby facilitating NAFLD progression (74). Lymphocyte aggregation correlates positively with lobular inflammation and fibrosis staging, suggesting a potential bridging role in the transition from NAFL to NASH (75).

Composite inflammatory indices derived from routine hematological and biochemical parameters have gained attention for their simplicity, low cost, and applicability in large-scale non-invasive screening of NAFLD. These indices reflect subclinical systemic inflammation and include the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-HDL ratio (MHR), systemic immune-inflammation index (SII), and aggregate index of systemic inflammation (AISI). NLR is markedly elevated in patients with moderate-to-severe NAFLD and NASH (76); MHR reflects the balance between immune activation and anti-inflammatory capacity (77); and SII and AISI, as integrative markers, have demonstrated strong discriminatory power in disease stratification and fibrosis prediction (78). These scoring systems help reduce the bias of single biomarkers and support early risk stratification and individualized therapeutic decision-making.

The liver plays a central role in lipid metabolism, encompassing fatty acid synthesis, transport, and oxidation. Disruptions in lipid metabolic homeostasis constitute a foundational mechanism in the pathogenesis of NAFLD and interact bidirectionally with insulin resistance and oxidative stress, leading to lipotoxicity and chronic inflammation (79). Accordingly, lipid metabolism–related biomarkers hold potential clinical value in early screening and identification of high-risk individuals.

Fibroblast growth factor 21 (FGF21), primarily secreted by hepatocytes, regulates lipogenesis, energy metabolism, and insulin sensitivity (80). In patients with NAFLD, elevated FGF21 levels are thought to represent a compensatory response to metabolic stress, particularly endoplasmic reticulum stress (81). A recent study demonstrated promising diagnostic performance of FGF21 for NAFLD, with an AUC of 0.832 (95% CI: 0.77–0.886, P < 0.001), suggesting its potential utility as an adjunctive biomarker (82).

Adiponectin, an adipokine with anti-inflammatory, antioxidant, and anti-fibrotic properties, is markedly reduced during the progression from NAFLD to NASH (83). Hypoadiponectinemia is closely linked to insulin resistance and increased cardiovascular risk (84). In a comparative analysis, adiponectin outperformed several metabolic markers in differentiating NAFLD subtypes, with an AUC of 0.643–0.644 (95% CI: 0.089–0.345, P < 0.001) (85).

Visfatin, secreted primarily by visceral adipose tissue, exhibits insulin-mimetic properties by modulating glucose metabolism and insulin signaling pathways (86). Reduced visfatin levels may exacerbate insulin resistance and contribute to NAFLD progression, underscoring its potential as an indicator of metabolic dysregulation (87).

The triglyceride-glucose (TyG) index, derived from fasting plasma glucose and triglyceride levels, was initially developed to evaluate insulin resistance (88, 89). Multiple studies have demonstrated its superior diagnostic accuracy for NAFLD compared with traditional predictors (90, 91). The TyG index reflects underlying mechanisms of glucotoxicity and lipotoxicity that drive insulin resistance and hepatic fat accumulation (92). It has shown robust predictive capability for NAFLD, with an AUC of 0.782 (95% CI: 0.773–0.790), sensitivity of 72.2%, and specificity of 70.5% (93).

The progression of NAFLD involves hepatocellular apoptosis, tissue remodeling, and persistent inflammation. Certain serum biomarkers reflect both hepatic injury and systemic inflammation, thereby offering dual diagnostic value for disease classification and fibrosis risk prediction.

Cytokeratin-18 (CK-18) is a specific marker of hepatocyte apoptosis, released into circulation upon membrane disruption (94). Elevated serum CK-18 levels help distinguish NAFL from NASH, with the M30 fragment showing good diagnostic performance (AUC = 0.750, 95% CI: 0.714-0.787). When the CK-18 concentration exceeds 375 U/L, the diagnostic performance improves (AUC = 0.79), with a sensitivity of 81.5%, specificity of 65.0%, positive predictive value (PPV) of 80.8%, and negative predictive value (NPV) of 43.1% (P < 0.0001) (95).

Lipocalin-2 (LCN2), a glycoprotein secreted primarily by neutrophils, is upregulated in hepatic injury and inflammatory states. Induced by endotoxins, IL-6, and IL-1β, LCN2 contributes to neutrophil infiltration and upregulation of chemokine receptor CXCR2 (96–98). Its serum levels are significantly elevated in NASH and exhibit high diagnostic accuracy: for NAFLD, a cutoff of >57.57 ng/mL yields 76.47% sensitivity and 100% specificity; for NASH, a cutoff of >84.485 ng/mL yields 84.62% sensitivity and 80.95% specificity. The corresponding AUC values are 0.882 (95% CI: 0.745–0.961) and 0.868 (95% CI: 0.708–0.959), respectively (22).

Pentraxin 3 (PTX3), an acute-phase protein with immunomodulatory properties, is structurally similar to C-reactive protein (CRP) but exhibits higher specificity. Elevated PTX3 levels in NAFLD are associated with steatosis severity and hepatic enzyme abnormalities (99) (100). In pediatric NAFLD, PTX3 has a diagnostic cutoff of 3.03 U/L for NASH (sensitivity: 89%, specificity: 86%) (100). In adults, plasma PTX3 levels correlate significantly with NAFLD activity score, fibrosis stage, and steatosis grade (r = 0.659, P < 0.001; r = 0.354, P < 0.01; r = 0.455, P < 0.001). A cutoff of 2.45 ng/mL yields 91.1% sensitivity and 71.4% specificity for diagnosing NASH in adults (101).

Osteopontin (OPN), a glycoprotein secreted by adipose tissue macrophages, is closely associated with advanced hepatic fibrosis. OPN expression increases with fibrosis severity and is significantly elevated in patients with stage ≥F3 NAFLD (P < 0.001), supporting its potential use as a biomarker for progressive disease (102, 103).

Plasminogen activator inhibitor-1 (PAI-1), synthesized by hepatocytes and visceral adipose tissue, contributes to extracellular matrix accumulation and hepatic stellate cell activation. Elevated PAI-1 levels are associated with obesity, dyslipidemia, and inflammation, and promote fibrogenic progression in NAFLD (104, 105). Notably, PAI-1 demonstrates high diagnostic accuracy for NASH (106); a serum level >11.60 ng/mL yields an AUC of 0.954 (95% CI: 0.884–0.988), with 100% sensitivity and 90% specificity (107).

Oxidative stress is one of the key mechanisms driving the progression of non-alcoholic fatty liver disease (NAFLD) from metabolic dysfunction to tissue damage and liver fibrosis. The excessive production of reactive oxygen species (ROS), induced by metabolic toxicity, fatty acid peroxidation, and mitochondrial dysfunction, activates Kupffer cells, disrupts hepatocyte membrane integrity, and triggers chronic inflammation (108). Therefore, oxidative stress-related biomarkers serve as intermediate indicators of the pathogenesis of NAFLD, with potential diagnostic and prognostic value.

Uric acid has a dual biological role: at low concentrations, it acts as an antioxidant, while at higher concentrations, it becomes a pro-oxidative and pro-inflammatory mediator (109). Hyperuricemia is closely associated with the onset and progression of NAFLD, contributing to liver damage by activating immune responses, promoting insulin resistance, and exacerbating oxidative stress (110). Studies have shown that even within the normal range, uric acid levels are an independent risk factor for NAFLD (OR (95% CI): 1.46 (1.17-1.82) to 2.13 (1.42-3.18)) (111). Uric acid is not only related to the severity of liver damage in NAFLD but also holds potential as a predictive biomarker for disease progression. A study in Korea found a positive correlation between serum uric acid levels and the five-year incidence of NAFLD, suggesting its potential as an early diagnostic marker (112). Furthermore, a meta-analysis showed that the SUA threshold for NAFLD was 308 μmol/L, with a sensitivity of 94.12% (71.3-99.9) and a specificity of 70.6% (44.0-89.7) (113). However, the diagnostic performance of uric acid may vary among different populations, and further analysis of its cut-off value variability is needed to ensure its accuracy and reliability in broad clinical applications.

The role of iron metabolism biomarkers in NAFLD is also significant, particularly with hemoglobin (Hb) and ferritin. Ferritin catalyzes the production of free radicals, which may exacerbate oxidative stress (114). Animal studies have demonstrated that iron overload in NASH models significantly affects the progression of NAFLD, and iron-reducing treatment has shown protective effects against NASH (115). In NAFLD patients, Hb is considered an important predictor of liver fibrosis, especially in lean NAFLD (BMI < 25 kg/m²), where Hb is the only independent predictor (116). Thus, Hb can serve as a serum biomarker for NAFLD patients with normal weight, assisting in diagnosis and disease progression assessment.