Severe Fatty Liver Research Articles

Association between severity of Nonalcoholic fatty liver and left ventricular diastolic dysfunction assessed by tissue Doppler echocardiography

Association between severity of Nonalcoholic fatty liver and left ventricular diastolic dysfunction assessed by tissue Doppler echocardiography

Machine Learning Models for Predicting Significant Liver Fibrosis in Patients with Severe Obesity and Nonalcoholic Fatty Liver Disease.

Although noninvasive tests can be used to predict liver fibrosis, their accuracy is limited for patients with severe obesity and nonalcoholic fatty liver disease (NAFLD). We developed machine learning (ML) models to predict significant liver fibrosis in patients with severe obesity through noninvasive tests. This prospective study included 194 patients with severe obesity who underwent wedge liver biopsy and metabolic bariatric surgery at Taipei Medical University Hospital between September 2016 and December 2020. Significant liver fibrosis was defined as a fibrosis score ≥ 2. Patients were randomly divided into a training group (70%) and a validation group (30%). ML models, including support vector machine, random forest, k-nearest neighbor, XGBoost, and logistic regression, were trained to predict significant liver fibrosis, using DM status, AST, ALT, ultrasonographic fibrosis scores, and liver stiffness measurements (LSM). An ensemble model including these ML models was also used for prediction. Among the ML models, the XGBoost model exhibited the highest AUROC of 0.77, with a sensitivity, specificity, and accuracy of 61.5%, 75.8%, and 69.5%, in validation set, while LSM, AST, ALT showed strongest effects on the model. The ensemble model outperformed all ML models in terms of sensitivity, specificity, and accuracy of 73.1%, 90.9%, and 83.1%. For patients with severe obesity and NAFLD, the XGBoost model and the ensemble model exhibit high predictive performance for significant liver fibrosis. These models may be used to screen for significant liver fibrosis in this patient group and monitor treatment response after metabolic bariatric surgery.

Disrupted Post-Transcriptional Regulation of Gene Expression as a Hallmark of Fatty Liver Progression

It is known that both transcriptional and post-transcriptional mechanisms control messenger RNA (mRNA) levels. Compared to transcriptional regulations, our understanding of how post-transcriptional regulations adapt during fatty liver progression at the whole-transcriptome level is unclear. While traditional RNA-seq analysis uses only reads mapped to exons to determine gene expression, recent studies support the idea that intron-mapped reads can be reliably used to estimate gene transcription. In this study, we analyzed differential gene expression at both the exon and intron levels using two liver RNA-seq datasets from mice that were fed a high-fat diet for seven weeks (mild fatty liver) or thirty weeks (severe fatty liver). We found that the correlation between gene transcription and mature mRNA levels was much lower in mice with mild fatty liver as compared with mice with severe fatty liver. This result indicates broad post-transcriptional regulations for early fatty liver and such regulations are compromised for severe fatty liver. Specifically, gene ontology analysis revealed that genes involved in synapse organization and cell adhesion were transcriptionally upregulated, while their mature mRNAs were unaffected in mild fatty liver. Further characterization of post-transcriptionally suppressed genes in early fatty liver revealed that their mRNAs harbor a significantly longer 3′ UTR, one of the major features that may subject RNA transcripts to nonsense-mediated RNA decay (NMD). We further show that the expression of representative genes that were post-transcriptionally suppressed were upregulated in mice with a hepatocyte-specific defect of NMD. Finally, we provide data supporting a time-dependent decrease in NMD activity in the liver of a diet-induced metabolic-dysfunction-associated fatty liver disease mouse model. In summary, our study supports the conclusion that NMD is essential in preventing unwanted/harmful gene expression at the early stage of fatty liver and such a mechanism is lost due to decreased NMD activity in mice with severe fatty liver.

Impact of rosuvastatin on metabolic syndrome patients with moderate to severe metabolic associated fatty liver disease without overt diabetes: A randomized clinical trial

ObjectiveThis investigation aimed to evaluate the efficacy and safety of rosuvastatin in treating moderate to severe metabolic associated fatty liver disease (MAFLD). MethodsThis prospective, open-label, randomized study included non-diabetic participants with metabolic syndrome and intrahepatocellular lipid (IHCL) levels >10 %, as determined by proton magnetic resonance spectroscopy (1H-MRS). The primary objective was the effect of a 52-week rosuvastatin treatment (10 mg/day) on IHCL content. Secondary objectives included the association between IHCL reduction and lipid metabolism parameters, along with safety indices such as glycemic control and hepatic and renal function. ResultsThirty-two participants completed the study. Rosuvastatin resulted in a significant absolute (△IHCL: 7.61 ± 4.51 vs. 1.54 ± 5.33, p = 0.002) and relative reduction in IHCL (△IHCL%: −42.28 ± 24.90 % vs. −8.91 ± 31.93 %, p = 0.003) compared to the control. Reduction in IHCL correlated significantly with decreases in low-density lipoprotein cholesterol (LDL-C) (r = 0.574, p < 0.01), apolipoprotein B (ApoB) (r = 0.660, p < 0.001), and free fatty acids (FFA) (r = 0.563, p = 0.005). No significant safety differences were observed between groups. ConclusionsRosuvastatin significantly reduced hepatic steatosis in individuals with moderate to severe MAFLD and metabolic syndrome over 52 weeks, while maintaining a favorable safety profile.

Self-management in patients with metabolic dysfunction-associated steatotic liver disease: influencing factors and impact on readmission

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) is a common chronic liver disease.ObjectiveThis study aimed to investigate the self-management ability of patients with MASLD, analyse related factors that may affect self-management ability and evaluate the impact of this ability on readmission.MethodsThe study recruited patients with MASLD admitted to the Department of Infectious Diseases, First Affiliated Hospital of Wenzhou Medical University, between February and October 2021 using the random sampling method. The MASLD diagnosis was based on the guidelines for the prevention and treatment of MASLD. An analysis of patients’ self-management ability was conducted using the self-management ability scale for patients with MASLD. Multiple linear regression analysis was used to analyse the factors influencing this self-management ability, and the readmission rate within 1 year was tracked. The patients were rediagnosed as having MASLD upon readmission to the hospital.ResultsA total of 241 baseline data items and self-management scale scores for patients with MASLD were collected and investigated. In our study, the normal score range for the self-management scale was 31–155 points, and the self-management scale scores for patients with MASLD was 91.24 ± 16.98, with a low level of self-management accounting for 52.7% and a medium level accounting for 44.8%. The results of the multiple linear regression analysis revealed that marital status, smoking history, fatty liver severity and education were the main factors affecting self-management ability (P < 0.05). The readmission rates were 18.25%, 7.48% and 0%, respectively, after 1 year of follow-up; the difference in survival distribution was statistically significant (P < 0.05).ConclusionThe self-management ability of patients with MASLD is relatively low and is primarily influenced by factors such as marital status, smoking history, the severity of fatty liver disease and level of education, which also affect the readmission rate of patients within 1 year.

Deep Learning With Ultrasound Images Enhance the Diagnosis of Nonalcoholic Fatty Liver

ObjectiveThis research aimed to improve diagnosis of non-alcoholic fatty liver disease (NAFLD) by deep learning with ultrasound Images and reduce the impact of the professional competence and personal bias of the diagnostician. MethodThree convolutional neural network models were used to classify and identify the ultrasound images to obtain the best network. Then, the features in the ultrasound images were extracted and a new convolutional neural network was created based on the best network. Finally, the accuracy of several networks was compared and the best network was evaluated using AUC. ResultsModels of VGG16, ResNet50, and Inception-v3 were individually applied to classify and identify 710 ultrasound images containing NAFLD, demonstrating accuracies of 66.2%, 58.5%, and 59.2%, respectively. To further improve the classification accuracy, two features are presented: the ultrasound echo attenuation coefficient (θ), derived from fitting brightness values within sliding region of interest (ROIs), and the ratio of Doppler effect (ROD), identified through analyzing spots exhibiting the Doppler effect. Then, a multi-input deep learning network framework based on the VGG16 model is established, where the VGG16 model processes ultrasound image, while the fully connected layers handle θ and ROD. Ultimately, these components are combined to jointly generate predictions, demonstrating robust diagnostic capabilities for moderate to severe fatty liver (AUC = 0.95). Moreover, the average accuracy is increased from 64.8% to 77.5%, attributed to the introduction of two advanced features with domain knowledge. ConclusionThis research holds significant potential in aiding doctors for more precise and efficient diagnosis of ultrasound images related to NAFLD.

Treatment with 1.25% cholesterol enriched diet produces severe fatty liver disease characterized by advanced fibrosis and inflammation and impaired autophagy in mice

Nonalcoholic fatty liver disease (NAFLD) is reaching pandemic proportions due to overnutrition. The understanding of advanced stages that recapitulate the human pathology is of great importance to get a better mechanistic insight. We hypothesized that feeding of WT (C57BL) mice with a diet containing a high content of fat (21%), sugar (41.5%) and 1.25% of cholesterol (called from now on high fat, sucrose and cholesterol diet, HFSCD) will reproduce the characteristics of disease severity. Analysis of 16 weeks HFSCD-fed mice demonstrated increased liver weight and plasmatic liver damage markers compared with control diet (CD)-fed mice. HFSCD-fed mice developed greater hepatic triglyceride, cholesterol and NEFA content, inflammation and NAFLD activity score (NAS) indicating an advanced disease. HFSCD-fed mice displayed augmented hepatic total CD3+ T and Th9 lymphocytes, as well as reduced Th2 lymphocytes and CD206 anti-inflammatory macrophages. Moreover, T cells and anti-inflammatory macrophages correlated positively and inversely, respectively, with intrahepatic cholesterol content. Consistently, circulating cytotoxic CD8+ T lymphocytes, Th1, and B cell levels were elevated in HFSCD-fed WT mice. Hepatic and adipose tissue expression analysis demonstrated changes in fibrotic and metabolic genes related with cholesterol, triglycerides, and fatty acid synthesis in HFSCD-fed WT. These mice also exhibited reduced antioxidant capacity and autophagy and elevated ERK signaling pathway activation and CHOP levels. Our results indicate that the feeding with a cholesterol-enriched diet in WT mice produces an advanced NAFLD stage with fibrosis, characterized by deficient autophagy and ER stress along with inflammasome activation partially via ERK pathway activation.

To Treat or Not to Treat: A Twist in Paxlovid-Induced Liver Injury Amidst Severe Fatty Liver Disease

To Treat or Not to Treat: A Twist in Paxlovid-Induced Liver Injury Amidst Severe Fatty Liver Disease

The impact of type 2 diabetes on polycystic ovary syndrome in patients undergoing sleeve gastrectomy.

Does the concurrent type 2 diabetes mellitus (T2DM) aggravate the features and prognosis of PCOS in patients undergoing sleeve gastrectomy (SG)? For patients undergoing SG with obesity, concurrent T2DM is associated with aggravated metabolic but milder reproductive features of PCOS and did not attenuate the resumption of regular menstruation for up to 1 year after surgery. Women with T2DM have an increased risk of PCOS. However, whether concurrent T2DM further increases the disease burden and treatment difficulty of PCOS in patients with obesity requires further investigation. This was a single-center, two-arm, prospective, cohort study enrolling a total of 329 women with PCOS and scheduled for SG because of obesity at an university-affiliated hospital between January 2020 and August 2023, with a 1-year follow-up after surgery. Comparisons were made between patients with T2DM (PCOS+T2DM) and without (PCOS) to examine the impact of T2DM on the metabolic, reproductive, and psychological features of PCOS. The follow-up data of weight loss and menstruation were analyzed to determine the impact of T2DM on PCOS prognosis for up to 1 year after SG. After controlling for confounders, patients in the PCOS+T2DM group (n = 98) showed more severe insulin resistance, glucose intolerance, dyslipidemia, and non-alcoholic fatty liver disease (NAFLD) (NAFLD activity score 4.31 ± 1.15 versus 3.52 ± 1.42, P < 0.001) than those in the PCOS group (n = 149). In addition, the PCOS+T2DM group had a lower level of total testosterone (1.63 ± 0.69 versus 1.82 ± 0.76, P = 0.045), a lower ratio between luteinizing hormone and follicle-stimulating hormone (median 1.48 versus 1.68, P = 0.030), and a lower proportion of patients with polycystic ovarian morphology (88% versus 96%, P = 0.022) than the PCOS group. As a result, the two groups differed significantly in terms of the Rotterdam classification of PCOS (P = 0.009). No significant difference was detected by group in the psychological features of PCOS except a lower degree of emotional eating in the PCOS+T2DM group (P = 0.001). Although the PCOS+T2DM group took longer to resume regular menstruation after SG (P = 0.037), the two groups had similar proportions of patients with regular menstruation (85% versus 87%, P = 0.758) 1 year after SG, which was further confirmed by subgroup analyses by body mass index. The prognosis of PCOS after SG mainly focused on the results of menstruation rather than a complete evaluation of the remission of the disease. Our study showed that, for patients with obesity, concurrent T2DM is associated with aggravated metabolic but milder reproductive features of PCOS and did not attenuate the resumption of regular menstruation for up to 1 year after surgery. Our study also highlights the need for high-quality studies with a more comprehensive evaluation of the impact of T2DM on the prognosis of patients with PCOS after SG. This study was funded by the National Natural Science Foundation of China Grants (82100853), the Natural Science Foundation of Shandong Province of China (ZR2021QH028), and the Clinical Research Project of Shandong University (2020SDUCRCC024). The authors have no conflicts of interest. Chinese Clinical Trial Registry with No. ChiCTR1900026845.

Neural Network Classification Algorithm Based on Self-attention Mechanism and Ensemble Learning for MASLD Ultrasound Images

BackgroundUltrasound image examination has become the preferred choice for diagnosing metabolic dysfunction-associated steatotic liver disease (MASLD) due to its non-invasive nature. Computer-aided diagnosis (CAD) technology can assist doctors in avoiding deviations in the detection and classification of MASLD. MethodWe propose a hybrid model that integrates the pre-trained VGG16 network with an attention mechanism and a stacking ensemble learning model, which is capable of multi-scale feature aggregation based on the self-attention mechanism and multi-classification model fusion (Logistic regression, random forest, support vector machine) based on stacking ensemble learning. The proposed hybrid method achieves four classifications of normal, mild, moderate, and severe fatty liver based on ultrasound images. Result and conclusionOur proposed hybrid model reaches an accuracy of 91.34% and exhibits superior robustness against interference, which is better than traditional neural network algorithms. Experimental results show that, compared with the pre-trained VGG16 model, adding the self-attention mechanism improves the accuracy by 3.02%. Using the stacking ensemble learning model as a classifier further increases the accuracy to 91.34%, exceeding any single classifier such as LR (89.86%) and SVM (90.34%) and RF (90.73%). The proposed hybrid method can effectively improve the efficiency and accuracy of MASLD ultrasound image detection.

Physical frailty, genetic predisposition, and the risks of severe non-alcoholic fatty liver disease and cirrhosis: a cohort study.

Frailty, defined as a phenotype of decreased physiological reserves and diminished ability to respond to stressors, has been linked to the development of chronic diseases. Epidemiological evidence connecting frailty to non-alcoholic fatty liver disease (NAFLD) and cirrhosis risks remain sparse. We aimed to assess the longitudinal associations of frailty with the risks of severe NAFLD and cirrhosis in middle-aged to older adults and further explore the modification role of genetic risk on these associations. This study included a total of 398386 participants from the UK Biobank. Incident cases of severe NAFLD and cirrhosis were ascertained through linked hospital records and death registries. Frailty status was assessed by a modified version of the frailty phenotype, encompassing five key components: weight loss, tiredness, physical activity, gait speed, and grip strength. Participants were classified as pre-frailty if they met one or two of these criteria, and as frailty if they met three or more. Genetic predisposition to NAFLD and cirrhosis was estimated by genetic risk score (GRS) and further categorized into high, intermediate, and low genetic risk levels according to tertiles of GRSs. Cox proportional hazards regression model was employed to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for their associations. The mean (standard deviation) age of the study population was 56.6 (8.03) years. 214408 (53.8%) of the participants was female; 14924 (3.75%) of participants met the criteria for frailty, 170498 (42.8%) for pre-frailty, and 212964 (53.5%) for non-frailty. Over a median follow-up of 12.0years, we documented 4439 incident severe NAFLD and 3323 incident cirrhosis cases, respectively. Compared with non-frailty, both pre-frailty (HR: 1.50; 95% CI: 1.40-1.60) and frailty (HR: 1.98; 95% CI: 1.77-2.21) were associated with increased risk of NAFLD. Similar associations were observed for cirrhosis, the corresponding HRs (95% CIs) for non-frailty, pre-frailty, and frailty were 1.00 (reference), 1.29 (1.20, 1.38), and 1.90 (1.66, 2.18). Such associations were consistent across all genetic risk levels, with no observed interactions between frailty and GRSs (all P for interactions ≥0.10). Compared with participants with frailty and a low level of genetic risk, the greatest risk increasement in developing severe NAFLD (HR: 3.36; 95% CI: 2.83-3.99) and cirrhosis (HR: 2.81; 95% CI: 2.29-3.44) was both observed in those with frailty and a high level of genetic risk. Our findings indicate that frailty is a significant predictor of severe NAFLD and cirrhosis, irrespective of genetic predisposition.

Application of Quantitative Ultrasonography and Artificial Intelligence for Assessing Severity of Fatty Liver: A Pilot Study.

Non-alcoholic fatty liver disease (NAFLD), prevalent among conditions like obesity and diabetes, is globally significant. Existing ultrasound diagnosis methods, despite their use, often lack accuracy and precision, necessitating innovative solutions like AI. This study aims to validate an AI-enhanced quantitative ultrasound (QUS) algorithm for NAFLD severity assessment and compare its performance with Magnetic Resonance Imaging Proton Density Fat Fraction (MRI-PDFF), a conventional diagnostic tool. A single-center cross-sectional pilot study was conducted. Liver fat content was estimated using an AI-enhanced quantitative ultrasound attenuation coefficient (QUS-AC) of Barreleye Inc. with an AI-based QUS algorithm and two conventional ultrasound techniques, FibroTouch Ultrasound Attenuation Parameter (UAP) and Canon Attenuation Imaging (ATI). The results were compared with MRI-PDFF values. The intraclass correlation coefficient (ICC) was also assessed. Significant correlation was found between the QUS-AC and the MRI-PDFF, reflected by an R value of 0.95. On other hand, ATI and UAP displayed lower correlations with MRI-PDFF, yielding R values of 0.73 and 0.51, respectively. In addition, ICC for QUS-AC was 0.983 for individual observations. On the other hand, the ICCs for ATI and UAP were 0.76 and 0.39, respectively. Our findings suggest that AC with AI-enhanced QUS could serve as a valuable tool for the non-invasive diagnosis of NAFLD.

Air pollution, life’s essential 8, and risk of severe non-alcoholic fatty liver disease among individuals with type 2 diabetes

BackgroundThe impacts of long-term exposure to air pollution on the risk of subsequent non-alcoholic fatty liver disease (NAFLD) among participants with type 2 diabetes (T2D) is ambiguous. The modifying role of Life’s Essential 8 (LE8) remains unknown.MethodsThis study included 23,129 participants with T2D at baseline from the UK Biobank. Annual means of nitrogen dioxide (NO2), nitrogen oxides (NOX), and particulate matter (PM2.5, PM2.5–10, PM10) were estimated using the land-use regression model for each participant. The associations between exposure to air pollution and the risk of severe NAFLD were evaluated using Cox proportional hazard models. The effect modification of LE8 was assessed through stratified analyses.ResultsDuring a median 13.6 years of follow-up, a total of 1,123 severe NAFLD cases occurred. After fully adjusting for potential covariates, higher levels of PM2.5 (hazard ratio [HR] = 1.12, 95%CI:1.02, 1.23 per interquartile range [IQR] increment), NO2 (HR = 1.15, 95%CI:1.04, 1.27), and NOX (HR = 1.08, 95%CI:1.01, 1.17) were associated with an elevated risk of severe NAFLD. In addition, LE8 score was negatively associated with the risk of NAFLD (HR = 0.97, 95% CI: 0.97, 0.98 per point increment). Compared with those who had low air pollution and high LE8, participants with a high air pollution exposure and low LE8 had a significantly higher risk of severe NAFLD.ConclusionsOur findings suggest that long-term exposure to air pollution was associated with an elevated risk of severe NAFLD among participants with T2D. A lower LE8 may increase the adverse impacts of air pollution on NAFLD.

Survey of Medical Referral by Japanese Dentists for Patients With Hepatitis B, Hepatitis C, and Lichen Planus.

This study aimed to investigate the referral rates of oral lichen planus (OLP) and untreated hepatitis virus-infected patients by dentists to hepatologists. The study was conducted at three dental clinics in the Oita prefecture between November 2021 and June 2023. Two distinct groups of patients who visited the dentist for dental treatment were included: those with liver disease and concurrent hepatitis C virus (HCV) or hepatitis B virus (HBV) infection and those diagnosed with OLP. The rate of medical referrals to a hepatologist was investigated. Data on the number of patients, gender, age, diagnosis of liver disease, and referral practices were collected from the records submitted by each dental clinic. Information about the HCV and HBV infection status was collected through interviews with the dentists. A total of 1,665 patients were included, of which 10 were HCV-infected, five were HBV-infected, and six were diagnosed with OLP. None of the 15 patients with liver disease were referred to a hepatologist by their dentists. Nine out of the 10 HCV-infected patients had achieved sustained virological response (SVR) after antiviral treatment. Of the six patients with OLP, one had a history of HBV infection, one had severe fatty liver, and the remaining four had normal livers; five of the OLP patients were referred to a hepatologist (83.3%). A high referral rate from dentists to hepatologists was observed among the OLP patients. However, the study highlighted the difficulties in identifying hepatitis patients and establishing appropriate medical coordination in dental institutions.

Hepatic lipid accumulation is associated with multiple metabolic pathway alterations but not dyslipidemia and insulin resistance in central bearded dragons (Pogona vitticeps).

To investigate associations between hepatic fat accumulation, fibrosis, and plasma values of primary metabolites, biochemical measurands, insulin, and lipoproteins in bearded dragons. 48 adult central bearded dragons (Pogona vitticeps). Dragons were sedated with alfaxalone, and a blood sample was collected. Plasma was submitted for untargeted primary metabolomics using gas chromatography time-of-flight mass spectrometry, a biochemistry panel, and a lipoprotein panel determined by PAGE. Hepatic lipid content was quantified by liver attenuation measurements from CT images and digital image analysis of standardized histologic sections of the liver. Fibrosis was quantified by digital image analysis on Masson's trichrome-stained histologic sections. Severity was determined from pathologic review of liver sections according to a standardized grading system. Statistical associations were investigated using serial linear models adjusted for false discovery rate and multivariate statistics. Both hepatic fat and fibrosis had a significant effect on CT liver attenuation values. Several oligosaccharides (maltotriose, maltose, ribose, trehalose) and alkaline phosphatase were significantly and linearly increased with hepatic lipid content (all q < .05). On partial least square-discriminant analysis, β-hydroxybutyric acid was the most important discriminatory variable between fatty liver severity grades on histology. No significant associations were found with insulin, lipoproteins, and succinic acid. Bearded dragons with hepatic lipid accumulation experienced multiple metabolic pathway disruptions, some being compatible with mitochondrial dysfunction. No evidence of insulin resistance or dyslipidemia was found. Hepatic biopsy and histopathology remain recommended for reliably diagnosing and staging fatty liver disease in bearded dragons.

Hepatokine ITIH3 protects against hepatic steatosis by downregulating mitochondrial bioenergetics and de novo lipogenesis

Recent studies demonstrate that liver secretory proteins, also known as hepatokines, regulate normal development, obesity, and simple steatosis to non-alcoholic steatohepatitis (NASH) progression. Using a panel of ∼100 diverse inbred strains of mice and a cohort of bariatric surgery patients, we found that one such hepatokine, inter-trypsin inhibitor heavy chain 3 (ITIH3), was progressively lower in severe non-alcoholic fatty liver disease (NAFLD) disease states highlighting an inverse relationship between Itih3/ITIH3 expression and NAFLD severity. Follow-up animal and cell culture models demonstrated that hepatic ITIH3 overexpression lowered liver triglyceride and lipid droplet accumulation, respectively. Conversely, ITIH3 knockdown in mice increased the liver triglyceride in two independent NAFLD models. Mechanistically, ITIH3 reduced mitochondrial respiration and this, in turn, reduced liver triglycerides, via downregulated de novo lipogenesis. This was accompanied by increased STAT1 signaling and Stat3 expression, both of which are known to protect against NAFLD/NASH. Our findings indicate hepatokine ITIH3 as a potential biomarker and/or treatment for NAFLD.

A population-based prospective study on obesity-related non-communicable diseases in northern Iran: rationale, study design, and baseline analysis.

Iran is facing an epidemiological transition with the increasing burden of non-communicable diseases, such as obesity-related disorders and cardiovascular diseases (CVDs). We conducted a population-based prospective study to assess the prevalence and incidence rates of CVDs and obesity-related metabolic disorders and to evaluate the predictive ability of various CVD risk assessment tools in an Iranian population. We enrolled 5,799 participants in Amol, a city in northern Iran, in 2009-2010 and carried out the first repeated measurement (RM) after seven years (2016-2017). For all participants, demographic, anthropometric, laboratory, hepatobiliary imaging, and electrocardiography data have been collected in the enrollment and the RM. After enrollment, all participants have been and will be followed up annually for 20 years, both actively and passively. We adopted a multidisciplinary approach to overcome barriers to participation and achieved a 7-year follow-up success rate of 93.0% with an active follow-up of 5,394 participants aged 18-90 years. In the RM, about 64.0% of men and 81.2% of women were obese or overweight. In 2017, about 16.2% and 5.2% of men had moderate or severe non-alcoholic fatty liver disease, while women had a significantly higher prevalence of metabolic syndrome (35.9%), and type 2 diabetes mellitus (20.9%) than men. Of 160 deceased participants, 69 cases (43.1%) died due to CVDs over seven years. The most prevalent obesity-related chronic disease in the study was metabolic syndrome. Across the enrollment and RM phases, women exhibited a higher prevalence of obesity-related metabolic disorders. Focusing on obesity-related metabolic disorders in a population not represented previously and a multidisciplinary approach for enrolling and following up were the strengths of this study. The study outcomes offer an evidence base for future research and inform policies regarding non-communicable diseases in northern Iran.

Mesenchymal-specific Alms1 knockout in mice recapitulates metabolic features of Alström syndrome

ObjectiveAlström Syndrome (AS), caused by biallelic ALMS1 mutations, includes obesity with disproportionately severe insulin resistant diabetes, dyslipidemia, and fatty liver. Prior studies suggest that hyperphagia is accounted for by loss of ALMS1 function in hypothalamic neurones, whereas disproportionate metabolic complications may be due to impaired adipose tissue expandability. We tested this by comparing the metabolic effects of global and mesenchymal stem cell (MSC)-specific Alms1 knockout. MethodsGlobal Alms1 knockout (KO) mice were generated by crossing floxed Alms1 and CAG-Cre mice. A Pdgfrα-Cre driver was used to abrogate Alms1 function selectively in MSCs and their descendants, including preadipocytes. We combined metabolic phenotyping of global and Pdgfrα+ Alms1-KO mice on a 45% fat diet with measurements of body composition and food intake, and histological analysis of metabolic tissues. ResultsAssessed on 45% fat diet to promote adipose expansion, global Alms1 KO caused hyperphagia, obesity, insulin resistance, dyslipidaemia, and fatty liver. Pdgfrα-cre driven KO of Alms1 (MSC KO) recapitulated insulin resistance, fatty liver, and dyslipidaemia in both sexes. Other phenotypes were sexually dimorphic: increased fat mass was only present in female Alms1 MSC KO mice. Hyperphagia was not evident in male Alms1 MSC KO mice, but was found in MSC KO females, despite no neuronal Pdgfrα expression. ConclusionsMesenchymal deletion of Alms1 recapitulates metabolic features of AS, including fatty liver. This confirms a key role for Alms1 in the adipose lineage, where its loss is sufficient to cause systemic metabolic effects and damage to remote organs. Hyperphagia in females may depend on Alms1 deficiency in oligodendrocyte precursor cells rather than neurones. AS should be regarded as a forme fruste of lipodystrophy.

Application of the magnetic resonance 3D multiecho Dixon sequence for quantifying hepatic iron overload and steatosis in patients with thalassemia

ObjectiveTo investigate the feasibility and diagnostic efficacy of a 3D multiecho Dixon (qDixon) research application for simultaneously quantifying the liver iron concentration (LIC) and steatosis in thalassemia patients. Materials and methodsThis prospective study enrolled participants with thalassemia who underwent 3 T MRI of the liver for the evaluation of hepatic iron overload. The imaging protocol including qDixon and conventional T2* mapping based on 2D multiecho gradient echo (ME GRE) sequences respectively. Regions of interest (ROIs) were drawn in the liver on the qDixon maps to obtain R2* and proton density fat fraction (PDFF). The reference R2* value was measured and calculated on conventional T2* mapping using the CMRtools software. Correlation analysis, Linear regression analysis, and Bland–Altman analysis were performed. Results84 patients were finally included in this study. The median R2*-ME-GRE was 366.97 (1/s), range [206.68 (1/s), 522.20 (1/s)]. 8 patients had normal hepatic iron deposition, 16 had Insignificant, 42 had mild, 18 had moderate. The median of R2*-qDixon was 376.88 (1/s) [219.33 (1/s), 491.75 (1/s)]. A strong correlation was found between the liver R2*-qDixon and the R2*-ME-GRE (r = 0.959, P < 0.001). The median value of PDFF was 1.76% (1.10%, 2.95%). 8 patients had mild fatty liver, and 1 had severe fatty liver. ConclusionMR qDixon research sequence can rapidly and accurately quantify liver iron overload, that highly consistent with the measured via conventional GRE sequence, and it can also simultaneously detect hepatic steatosis, this has great potential for clinical evaluation of thalassemia patients.

Association of urinary chlorpyrifos, paraquat, and cyproconazole levels with the severity of fatty liver based on MRI

BackgroundThe objective of this study was to detect the urinary levels of chlorpyrifos, paraquat, and cyproconazole in residents living in Fuyang City and to analyze the correlation between these urinary pesticides levels and the severity of fatty liver disease (FLD).MethodsAll participants’ fat fraction (FF) values were recorded by MRI (Magnetic resonance imaging). First-morning urine samples were collected from 53 participants from Fuyang Peoples’Hospital. The levels of three urinary pesticides were measured using β-glucuronidase hydrolysis followed by a. The results were analyzed by using Pearson correlation analysis and binary logistic regression analysis to reveal the correlation between three urinary pesticides and the severity of fatty liver.Results53 individuals were divided into 3 groups based on the results from MRI, with 20 cases in the normal control group, 16 cases in the mild fatty liver group, and 17 cases in the moderate and severe fatty liver group. Urinary chlorpyrifos level was increased along with the increase of the severity of fatty liver. Urinary paraquat level was significantly higher both in the low-grade fatty liver group and moderate & serve grade fatty liver group compared with the control group. No significant differences in urinary cyproconazole levels were observed among the three groups. Furthermore, urinary chlorpyrifos and paraquat levels were positively correlated with FF value. And chlorpyrifos was the risk factor that may be involved in the development of FLD and Receiver Operating Characteristic curve (ROC curve) analysis showed that chlorpyrifos and paraquat may serve as potential predictors of FLD.ConclusionThe present findings indicate urinary chlorpyrifos and paraquat were positively correlated with the severity of fatty liver. Moreover, urinary chlorpyrifos and paraquat have the potential to be considered as the predictors for development of FLD. Thus, this study may provide a new perspective from the environmental factors for the diagnosis, prevention, and treatment of FLD.