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We aimed to compare the associations of metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) with coronary artery calcification (CAC). Patients who simultaneously underwent ultrasonography to diagnose hepatic steatosis and cardiac computed tomography to detect CAC were included. The presence and severity of CAC were defined with CAC-score thresholds of > 0 and > 300, respectively, and patients were divided into the following groups: no MASLD or MAFLD (reference), MASLD-only, MAFLD-only, and overlapping groups. Overall, 1,060/2,773 (38.2%) patients had CAC, of which 196 (18.5%) had severe CAC. The MASLD and MAFLD prevalence rates were 32.6% and 45.2%, respectively, with an overlap of 30.7%. In an ASCVD risk score-adjusted model, both MASLD (adjusted odd ratios [aOR], 1.21; 95% confidence interval [CI], 1.02-1.44; p = 0.033) and MAFLD (aOR 1.20; 95% CI 1.01-1.42, p = 0.034) were associated with CAC, whereas only MASLD (aOR 1.38; 95% CI 1.01-1.89, p = 0.041) was associated with severe CAC. Compared to the reference group, the overlapping group showed an association with CAC (aOR 1.22; 95% CI 1.01-1.47; p = 0.038); however, the MASLD and MAFLD subgroups did not differ in their association with CAC. MASLD may predict a higher risk of ASCVD more effectively than MAFLD.

RNA splicing is an essential post-transcriptional mechanism that facilitates the excision of introns and the connection of exons to produce mature mRNA, which is essential for gene expression and proteomic diversity. In the liver, precise splicing regulation is critical for maintaining metabolic balance, detoxification, and protein synthesis. This review explores the mechanisms of RNA splicing and the role of splicing factors, particularly in the context of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD). This review also highlights how RNA splicing dysregulation can lead to aberrant splicing and impact the progression of liver diseases such as MASLD, with a particular focus on Metabolic Dysfunction-Associated Steatohepatitis (MASH), which represents the advanced stage of MASLD. Recent advances in the clinical application of antisense oligonucleotides (ASOs) to correct splicing errors offer promising therapeutic strategies for restoring normal liver function. Additionally, the dysregulation of splicing observed in liver diseases may serve as a potential diagnostic marker, offering new opportunities for early identification of individuals more susceptible to disease progression. This review provides insights into the molecular mechanisms that govern splicing regulation in the liver, with a particular emphasis on MASLD, and discusses potential therapeutic approaches targeting RNA splicing to treat MASLD and related metabolic disorders.

BACKGROUND AND AIMS: Telehealth has emerged as an important mode of cirrhosis care delivery, but its use and satisfaction among vulnerable populations (eg, racial/ethnic minorities, socioeconomically disadvantaged, substance use disorders) are unknown. We evaluated digital capacity, telehealth use, satisfaction and associated factors among patients receiving hepatology care via telehealth (telehepatology) across 2 Veterans Affairs and 1 safety-net Healthcare systems. METHODS: English- and Spanish-speaking adults with cirrhosis (N = 256) completed surveys on telehealth use and satisfaction, quality of life, pandemic stress, alcohol use and depression. Logistic regression analyses assessed telehealth use and general linear models evaluated telehealth satisfaction. RESULTS: The mean age was 64.5 years, 80.9% were male and 35.9% Latino; 44.5% had alcohol-associated cirrhosis; 20.8% had decompensated cirrhosis; 100% had digital (phone/computer) capacity; and 75.0% used telehepatology in the prior 6 months. On multivariable analysis, participants with alcohol-associated (vs not) cirrhosis were less likely and those with greater pandemic stress were more likely to use telehepatology (odds ratio = 0.46 and 1.41, respectively; P < .05). Better quality of life was associated with higher telehepatology satisfaction and older age was associated with lower satisfaction (β = 0.01 and -0.01, respectively; P < .05). Latinos had higher satisfaction, but alcohol use disorder was associated with less satisfaction with telehepatology visits (β = 0.22 and -0.02, respectively; P

BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) incidence is increasing and correlated with metabolic dysfunction-associated steatotic liver disease (MASLD; formerly nonalcoholic fatty liver disease), even in patients without advanced liver fibrosis who are more likely to be diagnosed with advanced disease stages and shorter survival time, and less likely to receive a liver transplant. Machine learning (ML) tools can characterize large datasets and help develop predictive models that can calculate individual HCC risk and guide selective screening and risk mitigation strategies. METHODS: Tableau and KNIME Analytics were used for descriptive analytics and ML tasks. ML models were developed using standard laboratory and clinical parameters. Sci-kit learn algorithms were used for model development. Data from University of California (UC), Davis, were used to develop and train a pilot predictive model, which was subsequently validated in an independent dataset from UC San Francisco. MASLD and HCC patients were identified by International Classification of Diseases-9/10 codes. RESULTS: Of the patients diagnosed with MASLD (n = 1561 training; n = 686 validation), HCC developed in 14% (n = 227) of the UC Davis training cohort and 25% (n = 176) of the UC San Francisco validation cohort. Liver fibrosis determined by the noninvasive Fibrosis-4 score was the strongest single predictor for HCC in the model. Using the validation cohort, the model predicted HCC development at 92.06% accuracy with an area under the curve of 0.97, F1-score of 0.84, 98.34% specificity, and 74.41% sensitivity. CONCLUSION: ML models can aid physicians in providing early HCC risk assessment in patients with MASLD. Further validation will translate to cost-effective, personalized care of at-risk patients.

Background & aimsPathologists quantify liver steatosis as the fraction of lipid droplet-containing hepatocytes out of all hepatocytes, whereas the magnetic resonance-determined proton density fat fraction (PDFF) reflects the tissue triacylglycerol concentration. We investigated the linearity, agreement, and correspondence thresholds between histological steatosis and PDFF across the full clinical spectrum of liver fat content associated with non-alcoholic fatty liver disease.MethodsUsing individual patient-level measurements, we conducted a systematic review and meta-analysis of studies comparing histological steatosis with PDFF determined by magnetic resonance spectroscopy or imaging in adults with suspected non-alcoholic fatty liver disease. Linearity was assessed by meta-analysis of correlation coefficients and by linear mixed modelling of pooled data, agreement by Bland-Altman analysis, and thresholds by receiver operating characteristic analysis. To explain observed differences between the methods, we used RNA-seq to determine the fraction of hepatocytes in human liver biopsies.ResultsEligible studies numbered 9 (N = 597). The relationship between PDFF and histology was predominantly linear (r = 0.85 [95% CI, 0.80-0.89]), and their values approximately coincided at 5% steatosis. Above 5% and towards higher levels of steatosis, absolute values of the methods diverged markedly, with histology exceeding PDFF by up to 3.4-fold. On average, 100% histological steatosis corresponded to a PDFF of 33.0% (29.5-36.7%). Targeting at a specificity of 90%, optimal PDFF thresholds to predict histological steatosis grades were ≥5.75% for ≥S1, ≥15.50% for ≥S2, and ≥21.35% for S3. Hepatocytes comprised 58 ± 5% of liver cells, which may partly explain the lower values of PDFF vs. histology.ConclusionsHistological steatosis and PDFF have non-perfect linearity and fundamentally different scales of measurement. Liver fat values obtained using these methods may be rendered comparable by conversion equations or threshold values.Impact and implicationsMagnetic resonance-proton density fat fraction (PDFF) is increasingly being used to measure liver fat in place of the invasive liver biopsy. Understanding the relationship between PDFF and histological steatosis fraction is important for preventing misjudgement of clinical status or treatment effects in patient care. Our analysis revealed that histological steatosis fraction is often significantly higher than PDFF, and their association varies across the spectrum of fatty liver severity. These findings are particularly important for physicians and clinical researchers, who may use these data to interpret PDFF measurements in the context of histologically evaluated liver fat content.