Circulating hormones in biopsy-proven steatotic liver disease and steatohepatitis: A Multicenter Observational Study.

BACKGROUND: The role of metabolic/inflammatory hormonal systems in metabolic dysfunction associated steatotic liver disease (MASLD) remains to be fully elucidated. PURPOSE: To report the levels of the novel total and H-specific growth differentiation factor-15 (GDF-15) and other established hormonal systems and to describe hormonal patterns in controls and patients with MASLD and its stages. METHODS: This is a multicenter study from two Gastroenterology-Hepatology Departments (Greece and Australia) and one Bariatric-Metabolic Surgery Department (Italy). Overall, n = 455 serum samples of patients with biopsy-proven MASLD (n = 374) and Controls (n = 81) were recruited. RESULTS: We report for the first time that total and H-specific GDF-15 levels are higher in MASLD, at-risk metabolic dysfunction associated steatohepatitis (MASH), and severe fibrosis than in Controls. In addition, follistatin-like-3 (FSTL-3), free insulin-like growth factor-1 (IGF-1), leptin, and insulin levels were higher in MASLD patients than in Controls, while adiponectin levels were lower in MASLD subjects than in Controls. Activin-A, follistatin (FST), FSTL-3, and insulin levels significantly increased in severe fibrosis compared to no/mild fibrosis, while free IGF-1 decreased. In addition, adiponectin levels were lower in subjects without fibrosis vs. any fibrosis. Moreover, GDF-15 presented a strong positive association for the likelihood of having MASLD and at-risk MASH, while in adjusted analyses, FST and adiponectin showed inverse associations. Two different patterns of at-risk MASH were revealed through unsupervised analysis (total variation explained=54%). The most frequent pattern met in our sample (34.3%) was characterized by higher levels of total and H-specific GDF-15, follistatins, and activins, as well as low adiponectin levels. The second pattern revealed was characterized by high levels of free IGF-1, insulin, and leptin, with low levels of activin-A and adiponectin. Similar patterns were also generated in the case of overall MASLD. CONCLUSIONS: Total and H-specific GDF-15 levels increase as MASLD severity progresses. FSTL-3, free IGF-1, leptin, and insulin are also higher, whereas adiponectin and activin-A levels are lower in the MASLD group than in Controls. Hormonal systems, including GDF-15, may not only be involved in the pathophysiology but could also prove useful for the diagnostic workup of MASLD and its stages and may potentially be of therapeutic value.

The first external validation of the Dallas steatosis index in biopsy-proven Non-alcoholic fatty liver Disease: A multicenter study.

AIMS: A new non-invasive tool (NIT) for non-alcoholic fatty liver disease (NAFLD) proposed in 2022 by the multi-ethnic Dallas Heart Study, i.e. the Dallas Steatosis Index (DSI), was validated herein using for the first time the gold standard i.e. liver biopsy-proven NAFLD. METHODS: This is a multicenter study based on samples and data from two Gastroenterology-Hepatology Clinics (Greece and Australia) and one Bariatric-Metabolic Surgery Clinic (Italy). Overall, n = 455 patients with biopsy-proven NAFLD (n = 374) and biopsy-proven controls (n = 81) were recruited. RESULTS: The ability of DSI to correctly classify participants as NAFLD or controls was very good, reaching an Area Under the Curve (AUC) = 0.887. The cut-off point that could best differentiate the presence vs. absence of NAFLD corresponded to DSI = 0.0 (risk threshold: 50% | Sensitivity: 0.88; Positive Predictive Value (PPV): 93.0%; F1-score = 0.91). DSI demonstrated significantly better performance characteristics than other liver steatosis indexes. Decision curve analysis revealed that the benefit of DSI as a marker to indicate the need for invasive liver assessment was confirmed only when higher DSI values, i.e. ≥ 1.4, were used as risk thresholds. DSI performance to differentiate disease progression was inadequate (all AUCs < 0.700). CONCLUSIONS: DSI is more useful for disease screening (NAFLD vs. controls) than to differentiate diseases stages or progression. The value of any inclusion of DSI to guidelines needs to be further studied.

Liver biopsy-based validation, confirmation and comparison of the diagnostic performance of established and novel non-invasive steatotic liver disease indexes: Results from a large multi-center study.

BACKGROUND: Non-invasive tools (NIT) for metabolic-dysfunction associated liver disease (MASLD) screening or diagnosis need to be thoroughly validated using liver biopsies. PURPOSE: To externally validate NITs designed to differentiate the presence or absence of liver steatosis as well as more advanced disease stages, to confirm fully validated indexes (n = 7 NITs), to fully validate partially validated indexes (n = 5 NITs), and to validate for the first time one new index (n = 1 NIT). METHODS: This is a multi-center study from two Gastroenterology-Hepatology Departments (Greece and Australia) and one Bariatric-Metabolic Surgery Department (Italy). Overall, n = 455 serum samples of patients with biopsy-proven MASLD (n = 374, including 237 patients with metabolic-dysfunction associated steatohepatitis (MASH)) and Controls (n = 81) were recruited. A complete validation analysis was performed to differentiate the presence of MASLD vs. Controls, MASH vs. metabolic-dysfunction associated steatotic liver (MASL), histological features of MASH, and fibrosis stages. RESULTS: The index of NASH (ION) demonstrated the highest differentiation ability for the presence of MASLD vs. Controls, with the area under the curve (AUC) being 0.894. For specific histological characterization of MASH, no NIT demonstrated adequate performance, while in the case of specific features of MASH, such as hepatocellular ballooning and lobular inflammation, ION demonstrated the best performance with AUC being close to or above 0.850. For fibrosis (F) classification, the highest AUC was reached by the aspartate aminotransferase to platelet ratio index (APRI) being ~0.850 yet only with the potential to differentiate the severe fibrosis stages (F3, F4) vs. mild or moderate fibrosis (F0-2) with an AUC > 0.900 in patients without T2DM. When we excluded patients with morbid obesity, the differentiation ability of APRI was improved, reaching AUC = 0.802 for differentiating the presence of fibrosis F2-4 vs. F0-1. The recommended by current guidelines index FIB-4 seemed to differentiate adequately between severe (i.e., F3-4) and mild or moderate fibrosis (F0-2) with an AUC = 0.820, yet this was not the case when FIB-4 was used to classify patients with fibrosis F2-4 vs. F0-1. Trying to improve the predictive value of all NITs, using Youden's methodology, to optimize the suggested cut-off points did not materially improve the results. CONCLUSIONS: The validation of currently available NITs using biopsy-proven samples provides new evidence for their ability to differentiate between specific disease stages, histological features, and, most importantly, fibrosis grading. The overall performance of the examined NITs needs to be further improved for applications in the clinic.

How Comorbidities Affect Hospitalization from Influenza in the Pediatric Population.

Influenza is a contagious respiratory illness and can lead to hospitalization and even death. Understanding how comorbidities affect the severity of influenza can help clinical management. The aim of this study is to offer more information about comorbidities that might be associated with the severity of influenza in children. We used a statewide network in Rhode Island, USA, to extract data for laboratory-confirmed influenza cases among children 19 years old or younger. We identified 1169 lab-confirmed influenza cases. The most common comorbidities were asthma (17.1%), neurodevelopmental disorders (10.3%), gastrointestinal disorders (7.6%), atopic dermatitis (7%), and endocrine and metabolic diseases (6.8%). Interestingly, 80.8% (63 out of 78) of children who had an influenza-related hospital admission had at least one comorbidity, and among hospitalized children with influenza, the most common comorbidities were neurological diseases (28.2%, 22/78), gastrointestinal disorders (25.6%, 20/78), endocrine and metabolic diseases (24.4%, 19/78), and neurodevelopmental disorders (23.1%, 18/78). Children with endocrine or metabolic diseases were 8.23 times more likely to be admitted to the hospital, and children with neurological disorders were 6.35 times more likely to be admitted (OR: 8.23, 95% CI: 4.42-15.32 and OR: 6.35, 95% CI: 3.60-11.24, respectively). In summary, we identified specific comorbidities associated with influenza hospitalization and length of hospital stay, and these groups should be prioritized for public health interventions.

The association of obesity with health insurance coverage and demographic characteristics: a statewide cross-sectional study.

We evaluated the statewide burden of obesity and its complications among government and state funded programs (Medicare and Medicaid) and commercial insurance.We calculated the prevalence of obesity and the prevalence of relevant comorbidities among different demographic groups and based on health insurance, among adults (18-65 years old) who visited a statewide health network in the state of Rhode Island, in 2017.The overall prevalence of obesity among 74,089 individuals was 38.88% [Asians 16.77%, Whites 37.49%, Hispanics 44.23%, and Blacks 48.44%]. Medicare or Medicaid beneficiaries were 26% and 27%, respectively, more likely to have obesity than those who had commercial insurance (Odds Ratio:1.26, 95% confidence interval [CI]:1.20-1.32; Odds Ratio:1.27, 95%CI:1.22-1.32). Moreover, Medicaid and Medicare beneficiaries with obesity had a higher prevalence of diabetes compared with privately insured with obesity (10.58% and 10.44% vs 4.45%). Medicare beneficiaries with obesity had a statistically higher prevalence of ischemic heart disease (4.34%, 95%CI: 3.77-4.91) than privately insured (3.21%, 95%CI: 2.94-3.47).Based on statewide data among 18 to 65 years old adults, Medicare and Medicaid provide health coverage to 40% of individuals with obesity and 46% of those with the obesity-related comorbidities and complications. State and federal health care programs need to support and expand obesity-related services and coverage.