New-Onset Age of Nonalcoholic Fatty Liver Disease and Cancer Risk

The association of metabolic syndrome score trajectory patterns with risk of all cancer types

BACKGROUND

Metabolic syndrome (MetS) elevates cancer risk. However, a single MetS assessment does not fully reveal the long-term association with cancer. Inflammation, alongside MetS, could synergistically expedite both the onset and advancement of cancer. This study aims to investigate MetS score trajectories and cancer risk in a large, prospective cohort study.

METHODS

The authors prospectively examined the relationship between MetS score trajectory patterns and new-onset cancer in 44,115 participants. Latent mixture modeling was used to identify the MetS score trajectories. Cox proportional hazards regression models were used to evaluate the association between MetS score trajectory patterns and the risk of overall and site-specific cancers.

RESULTS

Four MetS score trajectory patterns were identified: low-stable (n = 4657), moderate-low (n = 18,018), moderate-high (n = 18,288), and elevated-increasing (n = 3152). Compared to participants with a low-stable trajectory pattern, the elevated-increasing trajectory pattern was associated with an elevated risk of overall (hazard ratio [HR], 1.27; 95% confidence interval [CI], 1.04-1.55), breast (HR, 2.11; 95% CI, 1.04-4.34), endometrial (HR, 3.33; 95% CI, 1.16-6.77), kidney (HR, 4.52; 95% CI, 1.17-10.48), colorectal (HR, 2.54; 95% CI, 1.27-5.09), and liver (HR, 1.61; 95% CI, 1.09-4.57) cancers. Among participants with chronic inflammation (C-reactive protein levels ≥3 mg/L), the elevated-increasing trajectory pattern was significantly associated with subsequent breast, endometrial, colorectal, and liver cancers.

CONCLUSIONS

Trajectories of MetS scores are associated with the occurrence of cancers, especially breast, endometrial, kidney, colorectal, and liver cancers, emphasizing the importance of long-term monitoring and evaluation of MetS.

PLAIN LANGUAGE SUMMARY

The association between long-term elevated metabolic syndrome (MetS) scores and a heightened risk of various cancers is a pivotal finding of our study. Our research further indicates that individuals with MetS, particularly when coupled with chronic inflammation, are at an increased risk of cancer. We propose that sustained monitoring and management of MetS could be beneficial in reducing cancer risk.

Steatotic Liver Disease: Pathophysiology and Emerging Pharmacotherapies

Steatotic liver disease (SLD) displays a dynamic and complex disease phenotype. Consequently, the metabolic dysfunction-associated steatotic liver disease (MASLD)/metabolic dysfunction-associated steatohepatitis (MASH) therapeutic pipeline is expanding rapidly and in multiple directions. In parallel, noninvasive tools for diagnosing and monitoring responses to therapeutic interventions are being studied, and clinically feasible findings are being explored as primary outcomes in interventional trials. The realization that distinct subgroups exist under the umbrella of SLD should guide more precise and personalized treatment recommendations and facilitate advancements in pharmacotherapeutics. This review summarizes recent updates of pathophysiology-based nomenclature and outlines both effective pharmacotherapeutics and those in the pipeline for MASLD/MASH, detailing their mode of action and the current status of phase 2 and 3 clinical trials. Of the extensive arsenal of pharmacotherapeutics in the MASLD/MASH pipeline, several have been rejected, whereas other, mainly monotherapy options, have shown only marginal benefits and are now being tested as part of combination therapies, yet others are still in development as monotherapies. Although the Food and Drug Administration (FDA) has recently approved resmetirom, additional therapeutic approaches in development will ideally target MASH and fibrosis while improving cardiometabolic risk factors. Due to the urgent need for the development of novel therapeutic strategies and the potential availability of safety and tolerability data, repurposing existing and approved drugs is an appealing option. Finally, it is essential to highlight that SLD and, by extension, MASLD should be recognized and approached as a systemic disease affecting multiple organs, with the vigorous implementation of interdisciplinary and coordinated action plans. SIGNIFICANCE STATEMENT: Steatotic liver disease (SLD), including metabolic dysfunction-associated steatotic liver disease and metabolic dysfunction-associated steatohepatitis, is the most prevalent chronic liver condition, affecting more than one-fourth of the global population. This review aims to provide the most recent information regarding SLD pathophysiology, diagnosis, and management according to the latest advancements in the guidelines and clinical trials. Collectively, it is hoped that the information provided furthers the understanding of the current state of SLD with direct clinical implications and stimulates research initiatives.

Updated mechanisms of MASLD pathogenesis

Metabolic dysfunction-associated steatotic liver disease (MASLD) has garnered considerable attention globally. Changing lifestyles, over-nutrition, and physical inactivity have promoted its development. MASLD is typically accompanied by obesity and is strongly linked to metabolic syndromes. Given that MASLD prevalence is on the rise, there is an urgent need to elucidate its pathogenesis. Hepatic lipid accumulation generally triggers lipotoxicity and induces MASLD or progress to metabolic dysfunction-associated steatohepatitis (MASH) by mediating endoplasmic reticulum stress, oxidative stress, organelle dysfunction, and ferroptosis. Recently, significant attention has been directed towards exploring the role of gut microbial dysbiosis in the development of MASLD, offering a novel therapeutic target for MASLD. Considering that there are no recognized pharmacological therapies due to the diversity of mechanisms involved in MASLD and the difficulty associated with undertaking clinical trials, potential targets in MASLD remain elusive. Thus, this article aimed to summarize and evaluate the prominent roles of lipotoxicity, ferroptosis, and gut microbes in the development of MASLD and the mechanisms underlying their effects. Furthermore, existing advances and challenges in the treatment of MASLD were outlined.

Unveiling the cancer risk nexus of the steatotic liver

Steatotic liver, characterized by the accumulation of fat in the liver, poses significant health risks including metabolic dysfunction-associated steatotic liver disease (MASLD) and an elevated risk of primary liver cancer. Emerging evidence indicates a robust association between steatotic liver and increased susceptibility to extrahepatic primary cancers and their metastases. The deposition of fat induces dynamic changes in hepatic microenvironments, thereby fostering inflammation and immune responses that enhance liver metastasis from extrahepatic primary cancers. This review explores the impact of steatotic liver on hepatic carcinogenesis and metastasis from extrahepatic cancers, with a specific focus on hepatocyte-derived factors and the immune microenvironment. By emphasizing novel conclusions, this article underscores the timely relevance of understanding these intricate connections.

Early and accurate diagnosis of steatotic liver by artificial intelligence (AI)-supported ultrasonography

OBJECTIVES

Steatotic liver disease is the most frequent chronic liver disease worldwide. Ultrasonography (US) is commonly employed for the assessment and diagnosis. Few information is available on the possible use of artificial intelligence (AI) to ameliorate the diagnostic accuracy of ultrasonography.

MATERIALS AND METHODS

An AI-based algorithm was developed using a dataset of US images. We prospectively enrolled 134 patients for algorithm validation. Patients underwent abdominal US and Proton Density Fat Fraction MRI scans (MRI-PDFF), assumed as reference technique. The hepatorenal index was manually calculated (HRIM) by 4 operators. An automatic hepatorenal index (HRIA) was obtained by the algorithm. The accuracy of HRIA to discriminate steatosis grades was evaluated by ROC analysis using MRI-PDFF cut-offs.

RESULTS

Overweight was 40 % of subjects (BMI 26.4 kg/cm2). The median HRIA was 1.11 (IQR 0.32) and the average of 4 manually calculated HRIM was 1.08 (IQR 0.26), with a 15 % inter-operator variability. Both HRIA (R = 0.79, P < 0.0001) and HRIM (R = 0.69, P < 0.0001) significantly correlated with liver fat percentage (MRI-PDFF). According to MRI-PDFF, 32 % of enrolled subjects had steatosis. Discrimination capacity by AUC between patient with steatosis and patient without steatosis was better for HRIA than HRIM (AUC: 0.87 vs. 0.82, respectively). ROC analysis showed an AUC = 0.98 for HRIA with 1.64 cut-off in distinguishing between mild and moderate/severe groups.

CONCLUSIONS

The use of AI improves accuracy and speed of ultrasonography in the diagnosis of liver steatosis. Further studies should evaluate the routine use of this technique in the management of liver steatosis at high cardio-metabolic risk.

Lipid droplets in steatotic liver disease

PURPOSE OF REVIEW

This review aims to discuss the most recent evidence exploring the role of lipid droplets in steatotic liver disease (SLD). We highlight the breadth of mechanisms by which lipid droplets may contribute to the progression of SLD with a particular focus on the role of lipid droplets as inducers of mechanical stress within hepatocytes and genetic mutations in lipid droplet associated proteins. Finally, this review provides an update on clinical trials exploring the therapeutic potential and strategies targeting lipid droplets.

RECENT FINDINGS

The size, composition and location of hepatic lipid droplets strongly influence the pathological role of these organelles in SLD. Emerging studies are beginning to elucidate the importance of lipid droplet induced hepatocyte mechanical stress. Novel strategies targeting lipid droplets, including the effects of lipid droplet associated protein mutations, show promising therapeutic potential.

SUMMARY

Much more than a histological feature, lipid droplets are complex heterogenous organelles crucial to cellular metabolism with important causative roles in the development and progression of SLD. Lipid droplet induced mechanical stress may exacerbate hepatic inflammation and fibrogenesis and potentially contribute to the development of a pro-carcinogenic hepatic environment. The integration of advancements in genetics and molecular biology in upcoming treatments aspires to transcend symptomatic alleviation and address the fundamental causes and pathological development of SLD.

Systemic immune-inflammatory biomarkers (SII, NLR, PLR and LMR) linked to non-alcoholic fatty liver disease risk

Background

Systemic immune-inflammatory biomarkers including systemic immune inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) have been demonstrated to be associated with the risk and severity of various liver diseases. However, studies on their role and clinical significance in metabolic diseases, especially in nonalcoholic fatty liver disease (NAFLD), are limited and results are inconsistent.

Methods

10821 adults aged 20 years or older were enrolled in this cross-sectional study, sourced from six cycles of the National Health and Nutrition Examination Survey (NHANES). Survey-weighted logistic regression was employed to investigate the correlation between systemic immune-inflammatory biomarkers (SII, NLR, PLR, and LMR) and NAFLD risk. Restricted cubic spline regression models and segmented regression models were used to describe nonlinear relationships and threshold effects. Subgroup and sensitivity analyses were also conducted.

Results

After adjusting for all confounding variables, there was a significant positive association observed between ln-transformed SII (OR= 1.46, 95% CI: 1.27-1.69, P <0.001), NLR (OR= 1.25, 95% CI: 1.05-1.49, P =0.015), LMR (OR= 1.39, 95% CI: 1.14-1.69, P = 0.002) with NAFLD. A nonlinear dose-response relationship with an inverted "U"-shaped threshold of 4.64 was observed between ln(PLR) and NAFLD risk. When ln(PLR) was below 4.64, each unit increase in ln(PLR) was associated with a 0.55-fold increase in the risk of NAFLD (OR= 1.55, 95% CI: 1.05-2.31, P <0.05). Conversely, when ln(PLR) exceeded 4.64, each unit increase in ln(PLR) was associated with a 0.40-fold decrease in the risk of NAFLD (OR= 0.60, 95% CI. 0.44-0.81, P <0.05).

Conclusion

ln-transformed SII, NLR, and LMR were linearly associated with NAFLD risk. ln(PLR) showed an inverted "U"-shaped nonlinear dose-response relationship with the risk of NAFLD.

Temporal relationship between inflammation and metabolic disorders and their impact on cancer risk

Background

Inflammation and metabolic disorders are closely associated with cancer. Whether inflammation leads to metabolic disorders or vice versa during cancer initiation remains unclear. In this study, we explored this temporal relationship and the co-exposure effect on cancer risk.

Methods

This prospective study had two phases. Initially, we examined the temporal relationship between inflammation (high-sensitivity C-reactive protein (CRP)) and metabolic disorders (metabolic syndrome severity Z-score (MetS-Z)) using a 3.98-year survey and cross-lagged analysis. Subsequently, we assessed the connection of co-exposure to inflammation and metabolic disorders, and the risks of overall cancer, as well as specific obesity-related, non-obesity-related, digestive system, lung, and other cancers using an 11.04-year survey and Cox proportional hazard models.

Results

The cross-lagged analysis revealed that the path coefficient from baseline CRP to follow-up MetS-Z (β2 = 0.032; 95% confidence interval (CI) = 0.026, 0.046) was more significant than the path coefficient from baseline MetS-Z to follow-up CRP (β1 = 0.009; 95% CI = -0.001, 0.019). During the follow-up, 2304 cases of cancer occurred. Compared with the risk of cancer of patients with low average cumulative CRP and MetS-Z, patients with high value had a significantly increased risk (hazard ratio = 1.54, 95% CI = 1.30, 1.83). The mediation analysis showed that MetS-Z mediated the association between CRP levels and overall cancer (12.67%), digestive system cancer (10.16%), and obesity-related cancer risk (13.87%).

Conclusions

Inflammation had a greater impact on metabolic disorders than vice versa. Co-exposure to inflammation and metabolic disorders significantly increased the risk of cancer, particularly digestive system and obesity-related cancers.

Registration

Chinese Clinical Trial Registry: ChiCTR-TNRC-11001489.