Novel metabolic classification for extrahepatic complication of metabolic associated fatty liver disease: A data-driven cluster analysis with international validation

Clinical application of cluster analysis in patients with newly diagnosed type 2 diabetes

AIMS

Early prevention and treatment of type 2 diabetes mellitus (T2DM) is still a huge challenge for patients and clinicians. Recently, a novel cluster-based diabetes classification was proposed which may offer the possibility to solve this problem. In this study, we report our performance of cluster analysis of individuals newly diagnosed with T2DM, our exploration of each subtype's clinical characteristics and medication treatment, and the comparison carried out concerning the risk for diabetes complications and comorbidities among subtypes by adjusting for influencing factors. We hope to promote the further application of cluster analysis in individuals with early-stage T2DM.

METHODS

In this study, a k-means cluster algorithm was applied based on five indicators, namely, age, body mass index (BMI), glycosylated hemoglobin (HbA1c), homeostasis model assessment-2 insulin resistance (HOMA2-IR), and homeostasis model assessment-2 β-cell function (HOMA2-β), in order to perform the cluster analysis among 567 newly diagnosed participants with T2DM. The clinical characteristics and medication of each subtype were analyzed. The risk for diabetes complications and comorbidities in each subtype was compared by logistic regression analysis.

RESULTS

The 567 patients were clustered into four subtypes, as follows: severe insulin-deficient diabetes (SIDD, 24.46%), age-related diabetes (MARD, 30.86%), mild obesity-related diabetes (MOD, 25.57%), and severe insulin-resistant diabetes (SIRD, 20.11%). According to the results of the oral glucose tolerance test (OGTT) and biochemical indices, fasting blood glucose (FBG), 2-hour postprandial blood glucose (2hBG), HbA1c, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and triglyceride-glucose index (TyG) were higher in SIDD and SIRD than in MARD and MOD. MOD had the highest fasting C-peptide (FCP), 2-hour postprandial C-peptide (2hCP), fasting insulin (FINS), 2-hour postprandial insulin (2hINS), serum creatinine (SCr), and uric acid (UA), while SIRD had the highest triglycerides (TGs) and TyG-BMI. Albumin transaminase (ALT) and albumin transaminase (AST) were higher in MOD and SIRD. As concerms medications, compared to the other subtypes, SIDD had a lower rate of metformin use (39.1%) and a higher rate of α-glucosidase inhibitor (AGI, 61.7%) and insulin (74.4%) use. SIRD showed the highest frequency of use of sodium-glucose cotransporter-2 inhibitors (SGLT-2i, 36.0%) and glucagon-like peptide-1 receptor agonists (GLP-1RA, 19.3%). Concerning diabetic complications and comorbidities, the prevalence of diabetic kidney disease (DKD), cardiovascular disease (CVD), non-alcoholic fatty liver disease (NAFLD), dyslipidemia, and hypertension differed significantly among subtypes. Employing logistic regression analysis, after adjusting for unmodifiable (sex and age) and modifiable related influences (e.g., BMI, HbA1c, and smoking), it was found that SIRD had the highest risk of developing DKD (odds ratio, OR = 2.001, 95% confidence interval (CI): 1.125-3.559) and dyslipidemia (OR = 3.550, 95% CI: 1.534-8.215). MOD was more likely to suffer from NAFLD (OR = 3.301, 95%CI: 1.586-6.870).

CONCLUSIONS

Patients with newly diagnosed T2DM can be successfully clustered into four subtypes with different clinical characteristics, medication treatment, and risks for diabetes-related complications and comorbidities, the cluster-based diabetes classification possibly being beneficial both for prevention of secondary diabetes and for establishment of a theoretical basis for precision medicine.

Unraveling phenotypic heterogeneity in stanford type B aortic dissection patients through machine learning clustering analysis of cardiovascular CT imaging

OBJECTIVE

Aortic dissection remains a life-threatening condition necessitating accurate diagnosis and timely intervention. This study aimed to investigate phenotypic heterogeneity in patients with Stanford type B aortic dissection (TBAD) through machine learning clustering analysis of cardiovascular computed tomography (CT) imaging.

METHODS

Electronic medical records were collected to extract demographic and clinical features of patients with TBAD. Exclusion criteria ensured homogeneity and clinical relevance of the TBAD cohort. Controls were selected on the basis of age, comorbidity status, and imaging availability. Aortic morphological parameters were extracted from CT angiography and subjected to K-means clustering analysis to identify distinct phenotypes.

RESULTS

Clustering analysis revealed three phenotypes of patients with TBAD with significant correlations with population characteristics and dissection rates. This pioneering study used CT-based three-dimensional reconstruction to classify high-risk individuals, demonstrating the potential of machine learning in enhancing diagnostic accuracy and personalized treatment strategies. Recent advancements in machine learning have garnered attention in cardiovascular imaging, particularly in aortic dissection research. These studies leverage various imaging modalities to extract valuable features and information from cardiovascular images, paving the way for more personalized interventions.

CONCLUSION

This study provides insights into the phenotypic heterogeneity of patients with TBAD using machine learning clustering analysis of cardiovascular CT imaging. The identified phenotypes exhibit correlations with population characteristics and dissection rates, highlighting the potential of machine learning in risk stratification and personalized management of aortic dissection. Further research in this field holds promise for improving diagnostic accuracy and treatment outcomes in patients with aortic dissection.

Impact of nomenclature as metabolic associated steatotic liver disease on steatotic liver disease prevalence and screening: a prospective population survey in Asians

BACKGROUND AND AIM

The introduction of the latest nomenclature, metabolic associated steatotic liver disease (MASLD), proposed by the multi-society without Asian society consensus statement, aims to redefine the diagnostic criteria for metabolic associated fatty liver disease (MAFLD). However, its effect on the epidemiology in Asia remains unclear.

METHOD

We conducted a population-based cross-sectional survey on fatty liver disease using multistage stratified random sampling of participants from Guangzhou, a representative area in China (ChiCTR2000033376). Demographic, socioeconomic, lifestyle, and laboratory data were collected. Hepatic steatosis and the severity of fibrosis were assessed using FibroScan.

RESULTS

A total of 7388 individuals were recruited, the proportion of which meeting the definitions for nonalcoholic fatty liver disease (NAFLD), MAFLD, and MASLD were 2359 (31.9%), 2666 (36.1%), and 2240 (30.3%), respectively. One hundred and twenty (1.6%) patients had cryptogenic SLD, and 537 (7.3%) patients were diagnosed with MetALD. MASLD did not significantly differ from NAFLD and MAFLD, except that MAFLD patients had a lower proportion of males, hypertension, and diabetes and were less likely to consume tea (P < 0.05). Both cryptogenic SLD and MASLD non-MAFLD patients exhibited milder hepatic steatosis and a lower frequency of liver injury than NAFLD, MAFLD, or MASLD patients (all P < 0.05). An increased HOMA-IR (adjusted OR: 1.33, 95% CI: 1.10-2.03) was associated with higher risk of moderate-to-severe steatosis for MASLD non-MAFLD patients, while consuming more cups of tea (P for trend = 0.015) showed inverse associations.

CONCLUSION

Irrespective of terminology used is that fatty liver disease is highly prevalent in the Han Chinese population. Differences in insulin resistance and lifestyle risk factors are associated with redefinition disparities.

Unlocking the potential of stimuli-responsive biomaterials for bone regeneration

Bone defects caused by tumors, osteoarthritis, and osteoporosis attract great attention. Because of outstanding biocompatibility, osteogenesis promotion, and less secondary infection incidence ratio, stimuli-responsive biomaterials are increasingly used to manage this issue. These biomaterials respond to certain stimuli, changing their mechanical properties, shape, or drug release rate accordingly. Thereafter, the activated materials exert instructive or triggering effects on cells and tissues, match the properties of the original bone tissues, establish tight connection with ambient hard tissue, and provide suitable mechanical strength. In this review, basic definitions of different categories of stimuli-responsive biomaterials are presented. Moreover, possible mechanisms, advanced studies, and pros and cons of each classification are discussed and analyzed. This review aims to provide an outlook on the future developments in stimuli-responsive biomaterials.

Optimized strategy among diet, exercise, and pharmacological interventions for nonalcoholic fatty liver disease: A network meta-analysis of randomized controlled trials

BACKGROUND

Emerging treatment methods, including exercise, diet, and drugs, for nonalcoholic fatty liver disease have been proposed. However, the differences in their efficacy have not been determined. We aimed to compare the effects of these treatments excluding surgery via a systematic review and network meta-analysis of randomized controlled trials.

DATA SOURCE

The data sources included PubMed, Embase, Web of Science and Cochrane up to February 1st, 2023. The endpoints consisted of body mass index (BMI), serum markers of metabolism and liver injury markers, liver fat content, and stiffness.

RESULTS

A total of 174 studies with 10,183 patients were included in this meta-analysis. In terms of improving BMI, Pan-agonist of peroxisome proliferator-activated receptors (PPAR) is the best treatment with the highest SUCRA (surface under the cumulative ranking) of 84.8% (mean = -3.40, 95% CI -5.55, -1.24) by the comparative effectiveness ranking. GLP-1 (glucagon-like peptide-1) has the best effect in improving the liver fat content based on the MRI-PDFF, steatosis score (SUCRA 99.7%, mean = -2.19, 95% CI -2.90, -1.48) and ballooning score (SUCRA 61.2%, mean = -0.82, 95% CI -4.46, 2.83).

CONCLUSIONS

Pan-agonist of PPAR was the most efficacious regimen in lowering BMIs, whereas GLP-1R agonists achieved the highest efficacy of steatosis improvement in this network meta-analysis.

Palm oil as part of a high-fat diet: advances and challenges, or possible risks of pathology?

Nutritional status disorders have the most significant impact on the development of cardiovascular and oncologic diseases; therefore, the interest in the study of palm oil as among the leading components of nutrition has been increasing. The data examined in this review were sourced from the Scopus, SCIE (Web of Science), PubMed and PubMed Central, MEDLINE, CAPlus/SciFinder, and Embase databases; experts in the field; bibliographies; and abstracts from review analyses from the past 15 years. This review summarizes recent research data focusing on the quantitative and qualitative composition of nutrition of modern humans; concepts of the relationship between high-fat diets and disorders of insulin functioning and transport and metabolism of fatty acids; analyses of data regarding the palmitic acid (16:0) to oleic acid (18:1) ratio; and the effect of diet based on palm oil consumption on cardiovascular risk factors and lipid and lipoprotein levels. Several studies suggest a potential vector contributing to the transmission of maternal, high-fat-diet-induced, addictive-like behaviors and obesogenic phenotypes across generations. The relationship between cholesterol accumulation in lysosomes that may lead to lysosome dysfunction and inhibition of the autophagy process is analyzed, as is the progression of inflammatory diseases, atherosclerosis, nonalcoholic liver inflammation, and obesity with associated complications. Data are discussed from analyses of differences between rodent models and human population studies in the investigated different effects of palm oil consumption as a high-fat diet component. A conclusion is reached that the results cannot be generalized in human population studies because no similar effects were observed. Although there are numerous published reports, more studies are necessary to elucidate the complex regulatory mechanisms in digestive and nutrition processes, because there are great differences in lipoprotein profiles between rodents and humans, which makes it difficult to reproduce the pathology of many diseases caused by different types of the high-fat diet.

Accurate and sensitive low-density lipoprotein (LDL) detection based on the proximity ligation assisted rolling circle amplification (RCA)

Metabolic-associated fatty liver disease (MAFLD) is one of the leading causes of mortality from chronic diseases worldwide, and it is strongly linked to dyslipidemia. Dyslipidemia typically presents as an elevated concentration of low density lipoprotein (LDL). Hence, accurate quantification of LDL particles is crucial for predicting the risks of cardiovascular illnesses. Nevertheless, conventional techniques can merely provide indirect measurements of LDL particle concentrations through the detection of cholesterol or proteins within LDL particles, and they often require significant effort and time. Therefore, an accurate and effective method for identifying intact LDL particles is highly desired. We have devised a method that allows for the measurement of LDL concentration without the need for isolation. This method relies on proximity ligation rolling circle amplification (RCA). This technique enables the direct and precise measurement of the concentration of "actual" LDL particles, rather than measuring the cholesterol content inside LDL. It has a detection limit of 7.3 μg dL-1, which also meets the requirements for analyzing lipoproteins in clinical samples. Hence, this platform exhibits immense potential in clinical applications and health management.

Prevalence and risk factors of MAFLD and its metabolic comorbidities in community-based adults in China: A cross-sectional study

AIMS

There is a growing interest in the co-management of metabolic dysfunction-associated fatty liver disease (MAFLD) and its metabolic comorbidities. However, there is insufficient epidemiological data regarding MAFLD and its metabolic comorbidities in China. This study aims to investigate the prevalence and risk factors of MAFLD and its metabolic comorbidities.

METHODS

9171 participants were recruited in this cross-sectional study, utilizing a multistage, stratified sampling method. All participants underwent a comprehensive assessment. The diagnosis of MAFLD was based on vibration-controlled transient elastography (VCTE). The prevalence of MAFLD and its metabolic comorbidities was calculated. Binary and ordinary logistic regressions were conducted.

RESULTS

The overall weighted prevalence of MAFLD was 21.18%. Of the 2081 adults with MAFLD, 1866 (89.67%) had more than one metabolic comorbidity, and only 215 (10.33%) did not have comorbidity. Among the population with MAFLD, the prevalence of dyslipidemia, hypertension, hyperuricemia, and diabetes was 67.47%, 43.73%, 39.10%, and 33.88%, respectively. Advanced age, male gender, overweight/obesity, excessive alcohol consumption, and elevated HOMA-IR levels were positively correlated with the number of MAFLD-related metabolic comorbidities.

CONCLUSIONS

A significant proportion of individuals diagnosed with MAFLD presented with metabolic comorbidities. Therefore, engaging in the co-management of MAFLD and its metabolic comorbidities is imperative.

AKR1B1 drives hyperglycemia-induced metabolic reprogramming in MASLD-associated hepatocellular carcinoma

Background & Aims

The mechanism behind the progressive pathological alteration in metabolic dysfunction-associated steatotic liver disease/steatohepatitis (MASLD/MASH)-associated hepatocellular carcinoma (HCC) is poorly understood. In the present study, we investigated the role of the polyol pathway enzyme AKR1B1 in metabolic switching associated with MASLD/MASH and in the progression of HCC.

Methods

AKR1B1 expression was estimated in the tissue and plasma of patients with MASLD/MASH, HCC, and HCC with diabetes mellitus. The role of AKR1B1 in metabolic switching in vitro was assessed through media conditioning, lentiviral transfection, and pharmacological probes. A proteomic and metabolomic approach was applied for the in-depth investigation of metabolic pathways. Preclinically, mice were subjected to a high-fructose diet and diethylnitrosamine to investigate the role of AKR1B1 in the hyperglycemia-mediated metabolic switching characteristic of MASLD-HCC.

Results

A significant increase in the expression of AKR1B1 was observed in tissue and plasma samples from patients with MASLD/MASH, HCC, and HCC with diabetes mellitus compared to normal samples. Mechanistically, in vitro assays revealed that AKR1B1 modulates the Warburg effect, mitochondrial dynamics, the tricarboxylic acid cycle, and lipogenesis to promote hyperglycemia-mediated MASLD and cancer progression. A pathological increase in the expression of AKR1B1 was observed in experimental MASLD-HCC, and expression was positively correlated with high blood glucose levels. High-fructose diet + diethylnitrosamine-treated animals also exhibited statistically significant elevation of metabolic markers and carcinogenesis markers. AKR1B1 inhibition with epalrestat or NARI-29 inhibited cellular metabolism in in vitro and in vivo models.

Conclusions

Pathological AKR1B1 modulates hepatic metabolism to promote MASLD-associated hepatocarcinogenesis. Aldose reductase inhibition modulates the glycolytic pathway to prevent precancerous hepatocyte formation.

Impact and implications

This research work highlights AKR1B1 as a druggable target in metabolic dysfunction-associated steatotic liver disease (MASLD) and hepatocellular carcinoma (HCC), which could provide the basis for the development of new chemotherapeutic agents. Moreover, our results indicate the potential of plasma AKR1B1 levels as a prognostic marker and diagnostic test for MASLD and associated HCC. Additionally, a major observation in this study was that AKR1B1 is associated with the promotion of the Warburg effect in HCC.

Investigation about the correlation between the severity of metabolic-associated fatty liver disease and adherence to the Mediterranean diet

BACKGROUND

Metabolic-associated fatty liver disease (MAFLD) is defined by fatty liver combined with a disturbed metabolic state. Mediterranean diet (MedDiet) contains anti-inflammatory, anti-oxidative, and anti-fibrotic components and is seemingly beneficial in the management of MAFLD. We aimed to evaluate the correlation between adherence to MedDiet and the severity of MAFLD.

MATERIALS AND METHODS

Totally 101 adult patients diagnosed with MAFLD were enrolled in this cross-sectional study. Persian version of Mediterranean Diet Adherence Screener (MEDAS), demographics, clinical, laboratory, and FibroScan findings were collected. Correlation and regression analyses were performed.

RESULTS

The mean of participants' age was 49.37 ± 12.14 (51.48 % male subjects). Six patients (5 diabetic and 1 pre-diabetic) had advanced fibrosis. Overall, 48.5 % had good adherence to MedDiet [the least MEDAS-1 (15.8 %) and the highest MEDAS-13 (99 %)]. The adherence score was significantly higher in married, female, non-smoker, and diabetic subjects, and patients with hypertension. Adherence to MedDiet had insignificant correlations with hepatic fibrosis (P = 0.888), steatosis (P = 0.208), waist-to-height ratio (P = 0.853), and FIB-4 score (P = 0.919). Vitamin D level had just significant inverse associations with steatosis score (r = -0.21, P = 0.037) and no significant association was found with fibrosis score (r = -0.036, P = 0.717) and MedDiet adherence (r = 0.055, P = 0.581). According to the multiple regression analyses, less fruit intake, lower platelet count and DM had significant positive correlations with MAFLD severity (P < 0.001).

CONCLUSION

Adherence to Mediterranean diet, particularly a higher fruit intake, is associated with a lower severity of MAFLD. Dietary modification based on taste, economic state, and culture should be deliberated in different geographic areas along with nutritional education.

Unsupervised cluster analysis of clinical and metabolite characteristics in patients with chronic complications of T2DM: an observational study of real data

Introduction

The aim of this study was to cluster patients with chronic complications of type 2 diabetes mellitus (T2DM) by cluster analysis in Dalian, China, and examine the variance in risk of different chronic complications and metabolic levels among the various subclusters.

Methods

2267 hospitalized patients were included in the K-means cluster analysis based on 11 variables [Body Mass Index (BMI), Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), Glucose, Triglycerides (TG), Total Cholesterol (TC), Uric Acid (UA), microalbuminuria (mAlb), Insulin, Insulin Sensitivity Index (ISI) and Homa Insulin-Resistance (Homa-IR)]. The risk of various chronic complications of T2DM in different subclusters was analyzed by multivariate logistic regression, and the Kruskal-Wallis H test and the Nemenyi test examined the differences in metabolites among different subclusters.

Results

Four subclusters were identified by clustering analysis, and each subcluster had significant features and was labeled with a different level of risk. Cluster 1 contained 1112 inpatients (49.05%), labeled as "Low-Risk"; cluster 2 included 859 (37.89%) inpatients, the label characteristics as "Medium-Low-Risk"; cluster 3 included 134 (5.91%) inpatients, labeled "Medium-Risk"; cluster 4 included 162 (7.15%) inpatients, and the label feature was "High-Risk". Additionally, in different subclusters, the proportion of patients with multiple chronic complications was different, and the risk of the same chronic complication also had significant differences. Compared to the "Low-Risk" cluster, the other three clusters exhibit a higher risk of microangiopathy. After additional adjustment for 20 covariates, the odds ratios (ORs) and 95% confidence intervals (95%CI) of the "Medium-Low-Risk" cluster, the "Medium-Risk" cluster, and the"High-Risk" cluster are 1.369 (1.042, 1.799), 2.188 (1.496, 3.201), and 9.644 (5.851, 15.896) (all p<0.05). Representatively, the "High-Risk" cluster had the highest risk of DN [OR (95%CI): 11.510(7.139,18.557), (p<0.05)] and DR [OR (95%CI): 3.917(2.526,6.075), (p<0.05)] after 20 variables adjusted. Four metabolites with statistically significant distribution differences when compared with other subclusters [Threonine (Thr), Tyrosine (Tyr), Glutaryl carnitine (C5DC), and Butyryl carnitine (C4)].

Conclusion

Patients with chronic complications of T2DM had significant clustering characteristics, and the risk of target organ damage in different subclusters was significantly different, as were the levels of metabolites. Which may become a new idea for the prevention and treatment of chronic complications of T2DM.

Liver fat as risk factor of hepatic and cardiometabolic diseases

Non-alcoholic fatty liver disease (NAFLD) is a disorder characterized by excessive accumulation of fat in the liver that can progress to liver inflammation (non-alcoholic steatohepatitis [NASH]), liver fibrosis, and cirrhosis. Although most efforts for drug development are focusing on the treatment of the latest stages of NAFLD, where significant fibrosis and NASH are present, findings from studies suggest that the amount of liver fat may be an important independent risk factor and/or predictor of development and progression of NAFLD and metabolic diseases. In this review, we first describe the current tools available for quantification of liver fat in humans and then present the clinical and pathophysiological evidence that link liver fat with NAFLD progression as well as with cardiometabolic diseases. Finally, we discuss current pharmacological and non-pharmacological approaches to reduce liver fat and present open questions that have to be addressed in future studies.

Association between the lean nonalcoholic fatty liver disease and risk of incident type 2 diabetes in a healthy population of Northwest China: a retrospective cohort study with a 2-year follow-up period

Aims

We aimed to explore the metabolic features of lean nonalcoholic fatty liver disease (Lean-NAFLD) and its association with the risk of incident type 2 diabetes in young and middle-aged people.

Methods

We conducted a retrospective cohort study of 3001 participants who were enrolled in a health check-up program from January 2018 to December 2020 in the Health Management Center of Karamay People's Hospital. The age, sex, height, weight, body mass index (BMI), blood pressure, waist circumference (WC), fasting plasma glucose (FPG), lipid profiles, serum uric acid and alanine aminotransferase (ALT) of the subjects were collected. The cutoff point of BMI for lean nonalcoholic fatty liver disease is <25 kg/m². A COX proportional hazard regression model was used to analyze the risk ratio of lean nonalcoholic fatty liver disease to type 2 diabetes mellitus.

Results

Lean NAFLD participants had many metabolic abnormalities, such as overweight and obesity with nonalcoholic fatty liver disease. Compared with lean participants without nonalcoholic fatty liver disease, the fully adjusted hazard ratio (HR) for lean participants with nonalcoholic fatty liver disease was 3.83 (95% CI 2.02-7.24, p<0.01). In the normal waist circumference group (man<90cm, woman<80 cm), compared with lean participants without NAFLD, the adjusted hazard ratios (HRs) of incident type 2 diabetes for lean participants with NAFLD and overweight or obese participants with NAFLD were 1.93 (95% CI 0.70-5.35, p>0.05) and 4.20 (95% CI 1.44-12.22, p<0.05), respectively. For excess waist circumference (man≥90 cm, woman ≥80 cm) compared with lean participants without NAFLD, the adjusted hazard ratios (HRs) of incident type 2 diabetes for lean participants with NAFLD and overweight or obese participants with NAFLD were 3.88 (95% CI 1.56-9.66, p<0.05) and 3.30 (95% CI 1.52-7.14, p<0.05), respectively.

Conclusion

Abdominal obesity is the strongest risk factor for type 2 diabetes in lean nonalcoholic fatty liver disease.

The Inter-Organ Crosstalk Reveals an Inevitable Link between MAFLD and Extrahepatic Diseases

Fatty liver is known to be associated with extra-hepatic diseases including atherosclerotic cardiovascular disease and extra-hepatic cancers, which affect the prognosis and quality of life of the patients. The inter-organ crosstalk is mediated by metabolic abnormalities such as insulin resistance and visceral adiposity. Recently, metabolic dysfunction-associated fatty liver disease (MAFLD) was proposed as a new definition for fatty liver. MAFLD is characterized by the inclusion criteria of metabolic abnormality. Therefore, MAFLD is expected to identify patients at high risk of extra-hepatic complications. In this review, we focus on the relationships between MAFLD and multi-organ diseases. We also describe the pathogenic mechanisms of the inter-organ crosstalk.

Novel metabolic phenotypes for extrahepatic complication of nonalcoholic fatty liver disease

BACKGROUND AND AIMS

Phenotypic heterogeneity among patients with NAFLD is poorly understood. We aim to identify clinically important phenotypes within NAFLD patients and assess the long-term outcomes among different phenotypes.

METHODS

We analyzed the clinical data of 2311 participants from the Third National Health and Nutrition Examination Survey (NHANES III) and their linked mortality data through December 2019. NAFLD was diagnosed by ultrasonographic evidence of hepatic steatosis without other liver diseases and excess alcohol use. A 2-stage cluster analysis was applied to identify clinical phenotypes. We used Cox proportional hazard models to explore all-cause and cause-specific mortality between clusters.

RESULTS

We identified 3 NAFLD phenotypes. Cluster 1 was characterized by young female patients with better metabolic profiles and lower prevalence of comorbidities; Cluster 2 by obese females with significant insulin resistance, diabetes, inflammation, and advanced fibrosis and Cluster 3 by male patients with hypertension, atherogenic dyslipidemia, and liver and kidney damage. In a median follow-up of 26 years, 989 (42.8%) all-cause mortality occurred. Cluster 1 patients presented the best prognosis, whereas Cluster 2 and 3 had higher risks of all-cause (Cluster 2-adjusted HR: 1.48, 95% CI: 1.16-1.90; Cluster 3-adjusted HR: 1.29, 95% CI: 1.01-1.64) and cardiovascular (Cluster 2-adjusted HR: 2.01, 95% CI: 1.18-3.44; Cluster 3-adjusted HR: 1.75, 95% CI: 1.03-2.97) mortality.

CONCLUSIONS

Three phenotypically distinct and clinically meaningful NAFLD subgroups have been identified with different characteristics of metabolic profiles. This study reveals the substantial disease heterogeneity that exists among NAFLD patients and underscores the need for granular assessments to define phenotypes and improve clinical practice.

Prevalence and Risk Factors of Metabolic-Associated Fatty Liver Disease Among Hospital Staff

Background

The prevalence of metabolism-related fatty liver disease (MAFLD) has been rarely reported in hospital staffs. The aim of this study was to assess the prevalence and risk factors for MAFLD in hospital staffs aged ≥18 years.

Methods

Based on type B ultrasonic, hospital staffs who underwent medical examinations at the second Affiliated Hospital of Hainan Medical University from January 2022 to March 2022 were classified into health control group (661 subjects) and MAFLD group (223 subjects), demographic, biochemical and blood examination information were compared between 2 groups. Independent risk factors for MAFLD were determined by logistic regression. Predictive values of risk factors of MAFLD were evaluated by receiver operating characteristic (ROC) curves.

Results

The prevalence of MAFLD was 33.7%. Older age (OR=1.08, p<0.001), H. pylori infection (OR=0.234, p=0.02), triglyceride-glucose (TyG) (OR=7.001, p<0.001), low-density lipoprotein cholesterol (LDL-C) (OR=2.076, p=0.028), red blood cell (RBC) (OR=2.386, p=0.001), eating out (OR=0.048, p=0.001), regular exercise (OR=23.017, p<0.001), and overweight (OR=3.891, p=0.003) were independently associated factors for MAFLD. The AUC of model predicting MAFLD is 0.910 [95% CI (0.886, 0.934)], with 0.794 sensitivity, 0.908 specificity. The diagnostic value of model was higher in the female MAFLD group after stratified analysis according to gender. The model showed that TyG was the factor contributing more to MAFLD. The diagnostic value of TyG was higher in the female MAFLD group than male MAFLD group.

Conclusion

The prevalence of MAFLD among hospital staffs was 33.7%. TyG can be used to predict MAFLD especially for female hospital staffs for early intervention.