The numbers behind the review are sobering. The disease burden follows a distinct geographical gradient, with prevalence highest in Latin America at 44.4 percent, followed by the Middle East and North Africa at around 39 percent, moderate levels in Asia, and lowest in Western Europe at 25.1 percent. Among people with type 2 diabetes, prevalence soars even higher, reaching up to 80.6 percent in Eastern Europe and 71.2 percent in the Middle East. Children and adolescents are increasingly affected too, with global prevalence between 7 and 14 percent, rising as high as 47 percent among obese children. In China, a nationwide study of 500,000 adults revealed that MASLD prevalence climbed from 30.0 percent in 2015 to 43.2 percent in 2023, with the fastest increase occurring among young people aged 18 to 40, whose prevalence jumped from 19.1 percent to 30.2 percent over just eight years. Men carried roughly twice the risk of women, and farmers showed the highest occupational prevalence at 52.1 percent, suggesting that physical activity may offer some protection.

What makes these statistics particularly alarming is that MASLD is not merely a liver disease. The review emphasizes that it forms part of a complex cardiovascular-renal-hepatic-metabolic syndrome, interweaving with cardiovascular disease, type 2 diabetes, and chronic kidney disease in ways that affect multiple organ systems throughout the body. At the center of this web sits insulin resistance, widely recognized as one of the core driving factors of the disease. The relationship is bidirectional: MASLD is both a hepatic manifestation of insulin resistance and, conversely, hepatic steatosis can exacerbate systemic insulin resistance, creating a vicious cycle that drives disease progression.

The mechanistic story the review tells is elegant and increasingly well understood. Under normal physiological conditions, insulin performs two seemingly contradictory jobs in the liver: it suppresses glucose output by inhibiting gluconeogenesis and glycogenolysis, while simultaneously promoting de novo lipogenesis and inhibiting fatty acid oxidation. When insulin resistance develops, the liver becomes insensitive to insulin’s glucose-suppressing effects, leading to increased hepatic glucose release and hyperglycemia. Crucially, however, the lipogenic arm of insulin signaling may remain intact or even become enhanced. The result is a metabolic paradox: the liver converts excess glucose into fatty acids, esterifies them into triglycerides, and accumulates them as hepatic fat. Meanwhile, insulin-resistant adipose tissue ramps up lipolysis, flooding the liver with free fatty acids that further fuel triglyceride synthesis. These excess fatty acids do not simply sit inert in hepatocytes; they activate inflammatory pathways and oxidative stress, damaging liver cells and worsening insulin resistance in a self-reinforcing loop.

As the disease progresses from simple steatosis to metabolic dysfunction-associated steatohepatitis, or MASH, the review describes how accumulated fat generates lipotoxicity that activates Kupffer cells and other immune cells, triggering release of pro-inflammatory cytokines such as TNF-α and IL-6. Excessive fatty acid oxidation and mitochondrial dysfunction increase reactive oxygen species production, causing oxidative stress that activates inflammatory and fibrotic signaling pathways. The interplay among lipotoxicity, inflammation, and oxidative stress ultimately drives programmed cell death in hepatocytes. Damage-associated molecular patterns released by dying cells then activate Kupffer cells and hepatic stellate cells, intensifying inflammation and fibrosis, and ultimately leading to liver fibrosis. This cascade explains why accurately assessing insulin resistance status holds such practical value for early identification, risk stratification, and targeted intervention.

The gold standard for measuring insulin resistance, the hyperinsulinemic-euglycemic clamp technique, is too cumbersome and expensive for widespread clinical use. In its absence, researchers have developed a suite of surrogate markers calculated from routine biochemical parameters, and the review evaluates four of the most prominent: HOMA-IR, the triglyceride-glucose index and its derivatives, the TG/HDL-C ratio, and METS-IR. Each has distinct strengths and limitations, and the review’s comparative analysis reveals a field in rapid evolution.

HOMA-IR, calculated from fasting glucose and fasting insulin levels, remains the classic surrogate marker. It correlates significantly with the clamp technique, with a correlation coefficient of -0.820 after log transformation. In a 2010 Brazilian study of non-diabetic individuals, a HOMA-IR cutoff of 2.0 achieved an area under the ROC curve of 0.840 for MASLD diagnosis, with sensitivity and specificity of 85 percent and 83 percent respectively. Beyond diagnosis, HOMA-IR has emerged as an independent predictor of progressive liver fibrosis, with each unit increase associated with a 14 percent higher fibrosis risk in non-diabetic Egyptian patients. A 2022 meta-analysis of 19 prospective cohorts involving 161,032 participants found elevated HOMA-IR significantly associated with non-fatal major adverse cardiovascular events. Perhaps most strikingly, a 2025 Chinese community cohort of 8,035 people demonstrated that HOMA-IR accounts for 31.07 percent of the total association between MASLD and incident atherosclerotic cardiovascular disease, a proportion significantly greater than that attributable to high-sensitivity C-reactive protein at 14.70 percent. This suggests insulin resistance may serve as the central pathophysiological mediator linking hepatic metabolic dysfunction to cardiovascular risk.

The triglyceride-glucose index, or TyG, calculated from just fasting triglycerides and fasting glucose, has emerged as a simpler alternative particularly suited to primary care and large-scale screening. Its diagnostic performance is comparable to HOMA-IR, but derived indices that incorporate anthropometric measures show superior accuracy. TyG-BMI achieved an area under the curve of 0.883 in a high-altitude Chinese population and 0.92 in a cohort of over 70,000 people, significantly outperforming the basic TyG index at 0.83. Analysis of nearly 100,000 individuals from the UK Biobank revealed that MASLD patients in the highest quartile of TyG-WHtR, which incorporates waist-to-height ratio, carried a 39 percent higher risk of cardiovascular events, a 37 percent higher risk of all-cause mortality, and a 57 percent higher risk of cardiovascular death. The TG/HDL-C ratio, while simpler still, shows relatively good diagnostic value with an area under the curve of 0.795 in a southwestern Chinese cohort, improving to 0.890 when combined with ALT, AST, and albumin in a predictive model. However, its ability to predict liver fibrosis remains contested, with studies reaching divergent conclusions possibly due to differences in fibrosis assessment methods, sample sizes, and cohort characteristics.

METS-IR, the Metabolic Score for Insulin Resistance, integrates fasting glucose, triglycerides, HDL-C, and body mass index into a single composite score. It correlates significantly with the clamp technique and has demonstrated excellent performance across diverse populations. A large Korean cohort study found METS-IR comparable to HOMA-IR in predicting MASLD prevalence but significantly better at predicting MASLD incidence. A 2024 NHANES-based study confirmed a diagnostic area under the curve of 0.831, higher than HOMA-IR’s 0.767, with each unit increase associated with approximately 16 percent higher risk. In children and adolescents, a 2025 South Korean study found METS-IR’s diagnostic efficacy at 0.91, significantly superior to TyG at 0.69 and TG/HDL-C at 0.71. Perhaps most notably, METS-IR was the only insulin resistance indicator significantly associated with both all-cause mortality and cardiovascular mortality in a 2024 NHANES analysis, and a 2023 Chinese elderly cohort showed that every quartile increase in METS-IR raised cardiovascular disease risk by 38 percent and new-onset stroke risk by 51 percent.

Despite these advances, the review identifies substantial barriers before insulin resistance-related indicators can be routinely incorporated into clinical practice. The lack of standardization remains a major obstacle: optimal cutoff values vary dramatically across populations, influenced by race, age, sex, body mass index, and diabetes status. HOMA-IR cutoffs range from 1.79 in Iranian men to 2.88 in Italian populations, and METS-IR thresholds differ between Mexican and Italian cohorts by more than 14 points. Most markers are surrogate measures susceptible to physiological variation from diet, physical activity, circadian rhythms, stress, and medication use. More fundamentally, they primarily reflect systemic metabolic dysfunction rather than liver-specific insulin resistance, limiting their pathophysiological specificity for MASLD. The review’s authors propose a two-step screening strategy for high-risk individuals, using METS-IR or TyG-BMI for initial assessment followed by FIB-4 scoring and elastography for those who screen positive. Looking ahead, they anticipate that multicenter prospective cohort studies, head-to-head comparisons, machine learning integration, and genetic adjustments incorporating variants such as PNPLA3 will enable dynamic, individualized risk prediction models. Over the next five years, they expect MASLD risk assessment to shift from fixed cutoff values toward personalized prediction, with insulin resistance markers becoming integral components of broader metabolic health frameworks that integrate longitudinal trajectories, genetic risk information, and continuously updated clinical data, ultimately advancing precision prevention strategies for a disease that now touches nearly two in five adults worldwide.

Subject of Research: Advances in the application of insulin resistance-related indicators in the clinical evaluation of metabolic dysfunction-associated steatotic liver disease

Article Title: Advances in the application of insulin resistance-related indicators in the clinical evaluation of metabolic dysfunction-associated steatotic liver disease

Article References: Li, Y., Li, H., Zhang, B., Wu, Q., & Long, H. (2026). Advances in the application of insulin resistance-related indicators in the clinical evaluation of metabolic dysfunction-associated steatotic liver disease. Frontiers in Gastroenterology, 5, Article 1859647. https://doi.org/10.3389/fgstr.2026.1859647

Image Credits: AI Generated

DOI: 10.3389/fgstr.2026.1859647

Keywords: Advances, application, insulin, resistance-related, indicators, clinical, evaluation, metabolic, dysfunction-associated, steatotic, liver, disease