Metabolic syndrome components and acute pancreatitis: a case-control study in China

Acute pancreatitis and metabolic syndrome: genetic correlations and causal associations

BACKGROUND

Although there is a definite correlation between the Metabolic Syndrome (MetS) and Acute Pancreatitis (AP), cause is yet unknown. The current work combined linkage disequilibrium score (LDSC) regression and Mendelian randomization (MR) approaches to fill this important information gap.

METHODS

In this study, we harnessed the power of publicly available gene-wide association databases (GWAS) to explore the intricate relationship between MetS and its components with AP. The cornerstone of our analysis was the Inverse-Variance Weighted (IVW) method, serving as our primary analytical tool. In addition to IVW, we complemented our investigation with several other robust MR methods, including MR-Egger, Weighted Median, Maximum Likelihood, and MR-PRESSO. By employing this diverse set of analytical approaches, we sought to ensure the comprehensiveness and robustness of our findings.

RESULT

LDSC regression indicated a genetic correlation between MetS and AP. Univariate MR results indicated a genetic association between MetS (OR = 1.084; 95% CI, 1.005-1.170; P = 0.037), BMI (OR = 1.459; 95% CI, 1.325-1.606; P = 1.46E-14), WHR (OR = 1.189; 95% CI, 1.068-1.323; P = 1.56 E-03), TG (OR = 1.110; 95% CI, 1.001-1.231; P = 0.047), and FI (OR = 1.798; 95% CI, 1.245-2.595; P = 1.74E-03) were able to significantly increase the risk of AP. The results of multivariate MR analysis revealed that these causality associations still existed.

CONCLUSION

Our investigation has yielded compelling evidence that substantiates the presence of both a genetic correlation and a causal relationship between MetS and AP.

Prediction of severe hypertriglyceridemia-associated acute pancreatitis using a nomogram based on CT findings and blood biomarkers

Hypertriglyceridemia is a common cause of acute pancreatitis (AP). Fatty liver, a manifestation of metabolic syndrome, is related to the severity of AP. The present study aimed to construct an accurate predictive model for severe AP (SAP) by combining the fatty liver infiltration on a computerized tomography (CT) scan with a series of blood biomarkers in patients with hypertriglyceridemia-associated AP (HTG-AP). A total of 213 patients diagnosed with HTG-AP were included in the present retrospective study. Clinical information and imageological findings were retrospectively analyzed. The model was constructed from independent risk factors using univariate analysis, the least absolute shrinkage and selection operator method. Subsequently, the data from the training group of 111 patients with HTG-AP was analyzed using logistic regression analysis. The efficacy of the model was verified using an external validation group of 102 patients through the receiver operating characteristic curve (ROC). Independent predictors, including serum calcium, C-reactive protein, lactate dehydrogenase and liver-to-spleen CT attenuation ratio (L/S ratio), were incorporated into the nomogram model for SAP in HTG-AP. The model achieved a sensitivity of 91.3% and a specificity of 88.6% in the training group. Compared with the Ranson model, the established nomogram model exhibited a better discriminative ability in the training group [area under the curve (AUC): 0.957] and external validation group (AUC: 0.930), as well as better calibration and clinical benefits. The present study demonstrates that the constructed nomogram based on CT findings and blood biomarkers is useful for the accurate prediction of SAP in HTG-AP.

The advent of RNA-based therapeutics for metabolic syndrome and associated conditions: a comprehensive review of the literature

Metabolic syndrome (MetS) is a prevalent and intricate health condition affecting a significant global population, characterized by a cluster of metabolic and hormonal disorders disrupting lipid and glucose metabolism pathways. Clinical manifestations encompass obesity, dyslipidemia, insulin resistance, and hypertension, contributing to heightened risks of diabetes and cardiovascular diseases. Existing medications often fall short in addressing the syndrome's multifaceted nature, leading to suboptimal treatment outcomes and potential long-term health risks. This scenario underscores the pressing need for innovative therapeutic approaches in MetS management. RNA-based treatments, employing small interfering RNAs (siRNAs), microRNAs (miRNAs), and antisense oligonucleotides (ASOs), emerge as promising strategies to target underlying biological abnormalities. However, a summary of research available on the role of RNA-based therapeutics in MetS and related co-morbidities is limited. Murine models and human studies have been separately interrogated to determine whether there have been recent advancements in RNA-based therapeutics to offer a comprehensive understanding of treatment available for MetS. In a narrative fashion, we searched for relevant articles pertaining to MetS co-morbidities such as cardiovascular disease, fatty liver disease, dementia, colorectal cancer, and endocrine abnormalities. We emphasize the urgency of exploring novel therapeutic avenues to address the intricate pathophysiology of MetS and underscore the potential of RNA-based treatments, coupled with advanced delivery systems, as a transformative approach for achieving more comprehensive and efficacious outcomes in MetS patients.

Soat2 inhibitor avasimibe alleviates acute pancreatitis by suppressing acinar cell ferroptosis

Ferroptosis, characterized by lipid peroxidation, plays a significant role in the pathogenesis of acute pancreatitis (AP). While sterol O-acyltransferase 2 (Soat2) is known for its crucial regulatory role in cholesterol homeostasis, its involvement in the development of AP remains unreported. We conducted this study to identify the pivotal role of Soat2 in AP using transcriptomic databases. Subsequently, we confirmed its alterations through both in vitro and in vivo experimental models. Furthermore, we performed intervention with the Soat2 inhibitor avasimibe to evaluate pancreatic tissue pathology and serum enzymatic levels and observe inflammatory cell infiltration through immunohistochemistry. Additionally, changes in indicators related to ferroptosis were also observed. The results showed that in the AP mouse model, the protein and mRNA levels of Soat2 were significantly increased. Following avasimibe administration, there was a decrease in serum amylase levels, reduction in pancreatic tissue pathological damage, and attenuation of inflammatory cell infiltration. Furthermore, avasimibe administration resulted in downregulation of ferroptosis-related indicators. In conclusion, our findings suggest that the Soat2 inhibitor avasimibe protects against AP in mice through inhibition of the ferroptosis.

Predictive value of adipokines for the severity of acute pancreatitis: a meta-analysis

BACKGROUND

Severe acute pancreatitis (SAP) is a dangerous condition with a high mortality rate. Many studies have found an association between adipokines and the development of SAP, but the results are controversial. Therefore, we performed a meta-analysis of the association of inflammatory adipokines with SAP.

METHODS

We screened PubMed, EMBASE, Web of Science and Cochrane Library for articles on adipokines and SAP published before July 20, 2023. The quality of the literature was assessed using QUADAS criteria. Standardized mean differences (SMD) with 95% confidence intervals (CI) were calculated to assess the combined effect. Subgroup analysis, sensitivity analysis and publication bias tests were also performed on the information obtained.

RESULT

Fifteen eligible studies included 1332 patients with acute pancreatitis (AP). Pooled analysis showed that patients with SAP had significantly higher serum levels of resistin (SMD = 0.78, 95% CI:0.37 to 1.19, z = 3.75, P = 0.000). The difference in leptin and adiponectin levels between SAP and mild acute pancreatitis (MAP) patients were not significant (SMD = 0.30, 95% CI: -0.08 to 0.68, z = 1.53, P = 0.127 and SMD = 0.11, 95% CI: -0.17 to 0.40, z = 0.80, P = 0.425, respectively). In patients with SAP, visfatin levels were not significantly different from that in patients with MAP (SMD = 1.20, 95% CI: -0.48 to 2.88, z = 1.40, P = 0.162).

CONCLUSION

Elevated levels of resistin are associated with the development of SAP. Resistin may serve as biomarker for SAP and has promise as therapeutic target.

Association of Metabolic Syndrome Components and Colonic Diverticulosis in the Very Elderly: A Tertiary Health Network Study

Introduction There is scarce data about the association of metabolic syndrome (MetS) or its components with the development of colonic diverticulosis (CD) in the elderly. We aim to determine the association of MetS and its components with CD in the elderly aged ≥75 years. Methods We conducted a retrospective chart review at St. Luke's University Health Network to identify patients who underwent a colonoscopy between 2011 and 2020. We collected data on patient demographics, comorbidities, and colonoscopy findings. Statistical analyses were conducted to compute means and frequencies of patient characteristics and rates of CD, as well as to test for associations between potential risk factors and the presence of CD.  Results A total of 1239 patients were included with a median age of 80 years, 57.6% females, 89.5% Caucasians, 72.9% with CD, and 66.7% having a left-sided disease. On bivariate analysis, the older age group (p=0.02), Caucasian ethnicity (p=0.01), and hypertension (p=0.04) were found to be significant risk factors for developing CD. Multivariate regression analysis showed older age group and hypertension (OR=1.47, 95% CI: 1.66-2.02, p=0.02) were major risk factors. A significant proportion of patients with left-sided disease had Caucasian ethnicity (p<0.001), while female gender, obesity, and iron deficiency anemia were also seen more frequently, although without statistical significance.  Conclusion In the elderly (>75 years old), our study found hypertension to be associated with an increased risk of CD, while impaired fasting glucose (IFG) was protective. Most patients exhibited isolated left-sided diverticulosis, with pan-diverticulosis associated with higher proportions of adverse health indicators, including American Society of Anesthesiologists (ASA) score ≥3, IFG, hypertriglyceridemia, hypertension, and hypothyroidism. Further research with larger sample sizes in similar age groups is needed to expand upon these findings.

COVID-19 and acute pancreatitis clinical outcomes among hospitalized patients in the United States: A propensity matched analysis of national inpatient sample

BACKGROUND

Pancreatitis is one of the leading causes of gastrointestinal-related hospitalization, with significant morbidity and mortality. SARS-COV-2 virus can access the pancreas via angiotensin-converting enzymes and can cause direct and indirect injury to the pancreatic parenchyma. The objective of this study to understand clinical outcomes of hospitalized patients with COVID-19 with and without pancreatitis utilizing National Inpatient Sample database.

METHODS

We utilized the United States National Inpatient Sample database to study clinical outcomes in hospitalized patients with COVID-19 infection (a total of 1,659,040 hospitalized patients with 10,075 (0.6 %) with pancreatitis) between January 1 to December 31, 2020, along with propensity matching.

RESULTS

While after propensity matching, we did not find a statistical difference in in-hospital mortality amongst COVID-19 patients with pancreatitis compared to COVID-19 patients without pancreatitis (13.2 % vs 10.3 %, adjusted odds ratio: 0.7 [95 % CI 0.5-1], p = 0.11). Patients with COVID-19 and pancreatitis had more episodes of septic shock, higher incidence of acute kidney injury and acute kidney injury requiring hemodialysis. We also found an increased prevalence of NASH cirrhosis, alcohol liver cirrhosis, and a lesser incidence of pulmonary embolisms in the COVID-19 with pancreatitis cohort.

CONCLUSION

Worse in-hospital outcomes, including increased incidence of septic shock, acute kidney injury, and acute kidney injury requiring hemodialysis in hospitalized patients with COVID-19 infection and pancreatitis, emphasize the need for more research to understand the effect of COVID-19 disease in hospitalized patients with pancreatitis and in the role of vaccination to improve long term outcome in this patient population.

Application of a Machine Learning Predictive Model for Recurrent Acute Pancreatitis

BACKGROUND AND AIM

Acute pancreatitis is the main cause of hospitalization for pancreatic disease. Some patients tend to have recurrent episodes after experiencing an episode of acute pancreatitis. This study aimed to construct predictive models for recurrent acute pancreatitis (RAP).

METHODS

A total of 531 patients who were hospitalized for the first episode of acute pancreatitis at the Affiliated Hospital of Southwest Medical University from January 2018 to December 2019 were enrolled in the study. We confirmed whether the patients had a second episode until December 31, 2021, through an electronic medical record system and telephone or WeChat follow-up. Clinical and follow-up data of patients were collected and randomly allocated to the training and test sets at a ratio of 7:3. The training set was used to select the best model, and the selected model was tested with the test set. The area under the receiver operating characteristic curves, sensitivity, specificity, positive predictive value, negative predictive value, accuracy, decision curve, and calibration plots were used to assess the efficacy of the models. Shapley additive explanation values were used to explain the model.

RESULTS

Considering multiple indices, XGBoost was the best model. The area under the receiver operating characteristic curves, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model in the test set were 0.779, 0.763, 0.883, 0.647, 0.341, and 0.922, respectively. According to the Shapley additive explanation values, drinking, smoking, higher levels of triglyceride, and the occurrence of ANC are associated with RAP.

CONCLUSION

The XGBoost model shows good performance in predicting RAP, which may help identify high-risk patients.

Lipid metabolism for predicting the recurrence of hypertriglyceridemic acute pancreatitis

Rationale and objectives

To investigate the predictive value of lipid metabolism in predicting the recurrence of hypertriglyceridemic acute pancreatitis (HTG-AP).

Materials and methods

A total of 892 patients were admitted to our hospital for acute pancreatitis (AP) from January 2017 to December 2020, of whom 198 diagnosed with HTG-AP were enrolled in this retrospective study. Demographic information, length of stay, smoking index, alcohol abuse, necrosis, severity, baseline lipid metabolism and other blood biochemical indicators were recorded. The risk factors of recurrence were evaluated using univariate and multivariate Cox proportional risk analyses, and the cumulative recurrence-free survival rate of patients were calculated using Kaplan Meier method and the differences between groups were compared using the log-rank test.

Results

Univariate and multivariate analysis showed that triglyceride (hazard ratio, 2.421; 95% CI, 1.152-5.076; P = 0.020), non high-density lipoprotein (hazard ratio, 4.630; 95% CI, 1.692-12.658; P = 0.003) and apolipoprotein A1 (hazard ratio, 1.735; 95% CI, 1.093-2.754; P = 0.019) were important predictors for recurrence of HTG-AP. Subsequently, patients were divided into four groups according to the cut off values of triglyceride, non high-density lipoprotein and apolipoprotein A1. It was found that the cumulative recurrence-free survival rate of patients in highest-risk group or high-risk group was significantly lower than that of medium-risk group (P < 0.001, P = 0.003) or low risk group (P < 0.001).

Conclusion

Serum triglycerides, non high-density lipoprotein and apolipoprotein A1 are independent predictors of recurrence in HTG-AP patients, which can provide reference for individualized treatment and prevention of recurrence in HTG-AP patients.

High Triglyceride-Glucose Index Is Associated with Poor Prognosis in Patients with Acute Pancreatitis

BACKGROUND

Acute pancreatitis (AP) is a common gastrointestinal disease worldwide. Severe acute pancreatitis (SAP) is characterized as persistent organ failure with a mortality rate as high as 20-30%. Early assessment of the severity and screening out possible SAP is of great significance. Given that there is still a lack of both convenient and practical tools for evaluating SAP, we conducted this study to explore the association between TyG index and acute pancreatitis prognosis.

METHODS

A total of 353 in-patients diagnosed with acute pancreatitis in the Second Hospital of Shandong University were retrospectively enrolled from January 2018 to November 2021 in this study. According to the Atlanta Classification, they were divided into two groups based on the AP severity. Demographic information and clinical materials were retrospectively collected. The TyG index calculation formula is as follows: ln [fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2]. Statistical analyses were performed using SPSS software (IBM version 22.0) and Medcalc software. Multivariable logistic regression analyses were used to investigate independent predictors for SAP. ROC curve was plotted to assess the predictive ability and cutoffs of TyG index.

RESULTS

A total of 353 AP patients were respectively enrolled in this study, of which 47 suffered from SAP. Compared with the non-SAP group, TyG index was significantly higher in the SAP group (10.44 ± 1.55 vs 9.33 ± 1.44, P < 0.001). Multivariate logistic regression analysis showed that TyG index was an independent risk factor for SAP (OR 1.835, 95% CI 1.380-2.442 P < 0.001), with a cutoff of 8.76 for non-HTG/AAP and 11.81 for HTG/AAP by ROC curve. TyG index of patients who suffered from SIRS, OF, APFC, and ANC was higher than those without (P < 0.05).

CONCLUSIONS

The triglyceride-glucose index is an independent risk factor for SAP. High TyG index is closely related to SAP and AP-related complications.

Relationship between Cholesterol-Related Lipids and Severe Acute Pancreatitis: From Bench to Bedside

It is well known that hypercholesterolemia in the body has pro-inflammatory effects through the formation of inflammasomes and augmentation of TLR (Toll-like receptor) signaling, which gives rise to cardiovascular disease and neurodegenerative diseases. However, the interaction between cholesterol-related lipids and acute pancreatitis (AP) has not yet been summarized before. This hinders the consensus on the existence and clinical importance of cholesterol-associated AP. This review focuses on the possible interaction between AP and cholesterol-related lipids, which include total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and apolipoprotein (Apo) A1, from the bench to the bedside. With a higher serum level of total cholesterol, LDL-C is associated with the severity of AP, while the persistent inflammation of AP is allied with a decrease in serum levels of cholesterol-related lipids. Therefore, an interaction between cholesterol-related lipids and AP is postulated. Cholesterol-related lipids should be recommended as risk factors and early predictors for measuring the severity of AP. Cholesterol-lowering drugs may play a role in the treatment and prevention of AP with hypercholesterolemia.

CT Characteristics of Acute Pancreatitis with Preexisting Fatty Liver and Its Impact on Pancreatitis Severity and Persistent Systemic Inflammatory Response Syndrome

Purpose

To study the CT characteristics of acute pancreatitis (AP) associated with preexisting fatty liver (FL) and the impact of preexisting FL on the severity of AP and persistent systemic inflammatory response syndrome (SIRS).

Patients and Methods

A total of 189 patients with AP were divided into AP with and without preexisting FL. The CT features, clinical characteristics, severity of AP, and presence of persistent SIRS between the two groups were compared. Univariate and multivariate analyses were performed to determine the risk factors for predicting SIRS. The diagnostic performances of the risk factors were evaluated by receiver operating characteristic (ROC) curve analysis.

Results

Among the 189 patients, 49.7% (94/189) had preexisting FL. On CT, AP patients with preexisting FL were more likely to develop necrosis (23.4% vs 10.5%, p=0.021), local complications (45.7% vs 29.5%, p=0.025) and persistent SIRS (59.6% vs 27.4%, p<0.001). Multivariate analysis showed that preexisting FL (OR=2.863, 95% CI: 1.264–6.486, p=0.012), APACHE II≥6 (OR=1.334, 95% CI: 1.117–1.594, p=0.002), and MCTSI ≥4 (OR=1.489, 95% CI: 1.046–2.119, p=0.027) could be independent risk factors for persistent SIRS. The areas under the ROC curve of preexisting FL, APACHE II, and MCISI in diagnosing AP patients with persistent SIRS were 0.664, 0.703, and 0.783, respectively.

Conclusion

Patients with preexisting FL were more likely to develop necrosis and local complications on CT and present more severe AP and persistent SIRS. Preexisting FL can be an independent risk factor in predicting the presence of persistent SIRS in patients with AP.

Children With Asparaginase-associated Pancreatitis Present Elevated Levels of Insulin, Total Cholesterol, and HOMA-IR Before Starting Acute Lymphoblastic Leukemia Treatment

Asparaginase-associated pancreatitis frequently occurs in children with cancer. It is unknown if other factors can influence the development of pancreatitis. A total of 33 pediatric patients with a confirmed diagnosis of acute lymphoblastic leukemia were included in this study. Before acute lymphoblastic leukemia drug treatment, the metabolic parameters (glucose, insulin, homeostasis model assessment insulin resistance, total cholesterol, triglycerides) and body mass index percentile were compared. Children who had acute pancreatitis had higher levels of insulin, homeostasis model assessment insulin resistance, and total cholesterol, compared with children who did not develop acute pancreatitis. These metabolic alterations could play a role in the development of pancreatitis.

Development and validation of a prediction model for moderately severe and severe acute pancreatitis in pregnancy

BACKGROUND

The severity of acute pancreatitis in pregnancy (APIP) is correlated with higher risks of maternal and fetal death.

AIM

To develop a nomogram that could predict moderately severe and severe acute pancreatitis in pregnancy (MSIP).

METHODS

Patients with APIP admitted to West China Hospital between January 2012 and December 2018 were included in this study. They were divided into mild acute pancreatitis in pregnancy (MAIP) and MSIP. Characteristic parameters and laboratory results were collected. The training set and test set were randomly divided at a ratio of 7:3. Least absolute shrinkage and selection operator regression was used to select potential prognostic factors. A nomogram was developed by logistic regression. A random forest model was used to validate the stability of the prediction factors. Receiver operating characteristic curves and calibration curves were used to evaluate the model’s predictive performance.

RESULTS

A total of 190 patients were included in this study. A total of 134 patients (70.5%) and 56 patients (29.5%) were classified as having MAIP and MSIP, respectively. Four independent predictors (lactate dehydrogenase, triglyceride, cholesterol, and albumin levels) were identified for MSIP. A nomogram prediction model based on these factors was established. The model had areas under the curve of 0.865 and 0.853 in the training and validation sets, respectively. The calibration curves showed that the nomogram has a good consistency.

CONCLUSION

A nomogram including lactate dehydrogenase, triglyceride, cholesterol, and albumin levels as independent predictors was built with good performance for MSIP prediction.

Metabolic syndrome as a common comorbidity in adults with hypothalamic dysfunction

OBJECTIVE

Hypothalamic dysfunction (HD) results in various endocrine disorders and is associated with an increased risk of metabolic comorbidities. This study aimed to analyze the clinical characteristics and metabolic abnormalities of adults with HD of various causes.

METHODS

This study retrospectively reviewed adults with HD treated at our center between August 1989 and October 2020. Metabolic characteristics of patients were compared to those of age-, sex-matched lean, and body mass index (BMI)-matched controls.

RESULTS

Temperature dysregulation (61.0%) was the most common hypothalamic physiological dysfunction. At least one anterior pituitary hormone deficiency was observed in 50 patients (84.7%), with hypogonadotropic hypogonadism being the most frequently observed. Metabolic syndrome was confirmed in 31 patients (52.5%) and was significantly more prevalent in those with panhypopituitarism or overweight/obesity. Metabolic syndrome (MetS) was significantly more common in patients with HD than in both lean and BMI-matched controls (P < 0.001 and P = 0.030, respectively). Considering the components of MetS, elevated fasting glucose levels were significantly more common in patients with HD than in BMI-matched controls (P = 0.029). Overweight/obesity and panhypopituitarism were significant risk factors for MetS in the multivariate analysis on patients with HD. Moreover, in the multivariate analysis on patients and BMI-matched control, HD was a significant risk factor of MetS (P=0.035, OR 2.919) after adjusted for age, sex and BMI.

CONCLUSIONS

Temperature dysregulation and hypogonadotropic hypogonadism are the most common physiological and endocrine dysfunctions, respectively. MetS and unfavorable metabolic profiles were prevalent in adults with HD. HD was a significant risk factor of MetS after adjusted for BMI.