Metabolic dysfunction-associated fatty liver disease (MAFLD) is an increasingly common liver disease worldwide. MAFLD is diagnosed based on the presence of steatosis on images, histological findings, or serum marker levels as well as the presence of at least one of the three metabolic features: overweight/obesity, type 2 diabetes mellitus, and metabolic risk factors. MAFLD is not only a liver disease but also a factor contributing to or related to cardiovascular diseases (CVD), which is the major etiology responsible for morbidity and mortality in patients with MAFLD. Hence, understanding the association between MAFLD and CVD, surveillance and risk stratification of MAFLD in patients with CVD, and assessment of the current status of MAFLD management are urgent requirements for both hepatologists and cardiologists. This Taiwan position statement reviews the literature and provides suggestions regarding the epidemiology, etiology, risk factors, risk stratification, nonpharmacological interventions, and potential drug treatments of MAFLD, focusing on its association with CVD.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Objective: Previous studies have shown that certain severe mental illnesses (SMIs) increase the risk of dementia, but those that increase the risk to a greater degree in comparison with other SMIs are unknown. Furthermore, physical illnesses may alter the risk of developing dementia, but these cannot be well-controlled. Methods: Using the Taiwan National Health Insurance Research Database, patients with schizophrenia, bipolar disorder and major depressive disorder (MDD) were recruited. We also recruited normal healthy subjects as the control group.All subjects were aged over 60 years, and the duration of follow-up was from 2008 to 2015. Multiple confounders were adjusted, including physical illnesses and other variables. Use of medications, especially benzodiazepines, was analyzed in a sensitivity analysis. Results: 36,029 subjects (MDD: 23,371, bipolar disorder: 4,883, schizophrenia: 7,775) and 108,084 control subjects were recruited after matching according to age and sex. The results showed that bipolar disorder had the highest hazard ratio (HR) (HR: 2.14, 95% confidence interval [CI]: 1.99−2.30), followed by schizophrenia (HR: 2.06, 95% CI: 1.93−2.19) and MDD (HR: 1.60, 95% CI: 1.51−1.69). The results remained robust after adjusting for covariates, and sensitivity analysis showed similar results. Anxiolytics use did not increase the risk of dementia in any of the three groups of SMI patients. Conclusion SMIs increase the risk of dementia, and among them, bipolar disorder confers the greatest risk of developing dementia. Anxiolytics may not increase the risk of developing dementia in patients with an SMI, but still need to be used with caution in clinical practices.

Mounting evidence indicates that melatonin has possible activity against different tumors. Pazopanib is an anticancer drug used to treat renal cell carcinoma (RCC). This study tested the anticancer activity of melatonin combined with pazopanib on RCC cells and explored the underlying mechanistic pathways of its action. Methods: The 786-O and A-498 human RCC cell lines were used as cell models. Cell viability and tumorigenesis were detected with the MTT and colony formation assays, respectively. Apoptosis and autophagy were assessed using TUNEL, annexin V/propidium iodide, and acridine orange staining with flow cytometry. The expression of cellular signaling proteins was investigated with western blotting. The in vivo growth of tumors derived from RCC cells was evaluated using a xenograft mouse model. Results: Together, melatonin and pazopanib reduced cell viability and colony formation and promoted the apoptosis of RCC cells. Furthermore, the combination of melatonin and pazopanib triggered more mitochondrial, caspase-mediated, and LC3-II-mediated autophagic apoptosis than melatonin or pazopanib alone. The combination also induced higher activation of the p38 mitogen-activated protein kinase (p38MAPK) in the promotion of autophagy and apoptosis by RCC cells than melatonin or pazopanib alone. Finally, tumor xenograft experiments confirmed that melatonin and pazopanib cooperatively inhibited RCC growth in vivo and predicted a possible interaction between melatonin/pazopanib and LC3-II. Conclusion: The combination of melatonin and pazopanib inhibits the growth of RCC cells by inducing p38MAPK-mediated mitochondrial and autophagic apoptosis. Therefore, melatonin might be a potential adjuvant that could act synergistically with pazopanib for RCC treatment.

Background/Aims: Hypopharyngeal multichannel intraluminal impedance-pH (HMII-pH) technology incorporating 2 trans-upper esophageal sphincter impedance channels has been developed to detect pharyngeal reflux. We used the HMII-pH technique to validate the candidate pharyngeal acid reflux (PAR) episodes based on the dual-pH tracings and determined the interobserver reproducibility. Methods: We conducted a cross-sectional study in tertiary centers in Taiwan. Ninety patients with suspected laryngopharyngeal reflux and 28 healthy volunteers underwent HMII-pH test when off acid suppressants. Candidate PAR episodes were characterized by pharyngeal pH drops of at least 2 units and reaching a nadir pH of 5 within 30 seconds during esophageal acidification. Two experts manually independently identified candidate PAR episodes based on the dual-pH tracings. By reviewing the HMII-pH tracings, HMII-pH-proven PAR episodes were subsequently confirmed. The consensus reviews of HMII-pH-proven PAR episodes were considered to be the reference standard diagnosis. The interobserver reproducibility was assessed. Results: A total of 105 candidate PAR episodes were identified. Among them 84 (80.0%; 95% CI, 71.0-87.0%) were HMII-pH-proven PAR episodes (82 in 16 patients and 2 in 1 healthy subject). Patients tended to have more HMII-pH-proven PAR episodes than healthy controls (median and percentile values [25th, 75th, and 95th percentiles]: 0 [0, 0, 3] vs 0 [0, 0, 0], P = 0.067). The concordance rate in diagnosing HMII-pH-proven PAR episodes between 2 independent observers was 92.2%. Conclusion Our preliminary data showed that 80.0% (71.0-87.0%) of the proposed candidate PAR episodes were HMII-pH-proven PAR episodes, among which the interobserver reproducibility was good.

Background/Aims:  Rituximab is known to be associated with high hepatitis B virus (HBV) reactivation rate in patients with resolved HBV infection and hematologic malignancy. However, data regarding HBV reactivation (HBVr) in rheumatic patients receiving rituximab is limited. To assess the HBVr rate in hepatitis B surface antigen (HBsAg)-negative patients receiving rituximab for autoimmune diseases in a large real-world cohort. Methods:  From March 2006 to December 2019, 900 patients with negative HBsAg receiving at least one cycle of rituximab for autoimmune diseases in a tertiary medical center in Taiwan were retrospectively reviewed. Clinical outcome and factors associated with HBVr were analyzed. Results: After a median follow-up period of 3.3 years, 21 patients developed HBVr, among whom 17 patients were positive for hepatitis B core antibody (anti-HBc) and four were negative. Thirteen patients had clinical hepatitis flare, while eight patients had HBsAg seroreversion without hepatitis. Old age, anti-HBc positivity, undetectable serum hepatitis B surface antibody level at rituximab initiation and a higher average rituximab dose were associated with a higher HBVr rate. There was no significant difference in the HBVr risk between rheumatoid arthritis and other autoimmune diseases. Among anti-HBc-negative patients, subjects without HBV vaccination at birth had an increased risk of HBVr (4/368, 1.1%) compared with those who received vaccination (0/126, 0%). Conclusions In HBV endemic areas where occult HBV is prevalent, anti-HBc-negative patients, may still be at risk for HBVr after rituximab exposure. HBVr may still be considered in HBsAgnegative patients developing abnormal liver function after rituximab exposure, even in patients with negative anti-HBc.

Objective: The impact of serotonergic system on obsessive-compulsive disorder (OCD) is well studied. However, the correlation between OC presentations and autonomic nervous system (ANS) is still unclear. Furthermore, whether the correlation might be modulated by serotonin is also uncertain. Methods: We recruited eighty-nine healthy subjects. Serotonin transporter (SERT) availability by [ 123 I]ADAM and heart rate variability (HRV) tests were measured. Symptoms checklist-90 was measured for the OC presentations. The interaction between HRV and SERT availability were calculated and the correlation between HRV and OC symptoms were analyzed after stratified SERT level into two groups, split at medium. Results: The interactions were significant in the factors of low frequency (LF), high frequency (HF), and root mean square of successive differences (RMSSD). Furthermore, the significantly negative correlations between OC symptoms and the above HRV indexes existed only in subjects with higher SERT availability. Conclusion OC symptoms might be correlated with ANS regulations in subjects with higher SERT availability.

Objective: Weight gain is an important risk factor for morbidity and mortality among patients with schizophrenia. We speculated that positive symptoms, related to dopaminergic hyperactivity and altered mesolimbic function, are associated with weight gain. Methods: Twenty-two antipsychotic-naïve, first-episode patients with schizophrenia were enrolled. The Positive and Negative Syndrome Scale was completed at enrollment and follow-up. Body mass index (BMI) was also measured. Results: The increase in BMI, after 6.04 ± 2.16 years of follow-up, was associated with positive symptoms, but not negative symptoms, before treatment with antipsychotics in antipsychotic-naïve patients with schizophrenia. Conclusion This finding implied that dopaminergic hyperactivity could be an important factor to predict the treatment outcome. Body weight control is important for the health management of patients with schizophrenia with more severe positive symptoms.

Objective: Patients with opioid use disorder (OUD) have impaired attention, inhibition control, and memory function. The aldehyde dehydrogenase 2 (ALDH2 ) gene has been associated with OUD and ALDH2 gene polymorphisms may affect aldehyde metabolism and cognitive function in other substance use disorder. Therefore, we aimed to investigate whether ALDH2 genotypes have significant effects on neuropsychological functions in OUD patients undergoing methadone maintenance therapy (MMT). Methods: OUD patients undergoing MMT were investigated and followed-up for 12 weeks. ALDH2 gene polymorphisms were genotyped. Connors’ Continuous Performance Test (CPT) and the Wechsler Memory Scale-Revised (WMS-R) were administered at baseline and after 12 weeks of MMT. Multivariate linear regressions and generalized estimating equations (GEEs) were used to examine the correlation between the ALDH2 genotypes and performance on the CPTs and WMS-R. Results: We enrolled 86 patients at baseline; 61 patients completed the end-of-study assessments. The GEE analysis showed that, after the 12 weeks of MMT, OUD patients with the ALDH2 *1/*2＋*2/*2 (ALDH2 inactive) genotypes had significantly higher commission error T-scores (p = 0.03), significantly lower hit reaction time T-scores (p = 0.04), and significantly lower WMS-R visual memory index scores (p = 0.03) than did patients with the ALDH2 1 */*1 (ALDH2 active) genotype. Conclusion OUD patients with the ALDH2 inactive genotypes performed worse in cognitive domains of attention, impulse control, and memory than did those with the ALDH2 active genotype. We conclude that the ALDH2 gene is important in OUD and is associated with neuropsychological performance after MMT.