OBJECTIVE: To reveal the effects and potential mechanisms by which synaptic vesicle glycoprotein 2A (SV2A) influences the distribution of amyloid precursor protein (APP) in the trans-Golgi network (TGN), endolysosomal system, and cell membranes and to reveal the effects of SV2A on APP amyloid degradation. METHODS: Colocalization analysis of APP with specific tagged proteins in the TGN, ensolysosomal system, and cell membrane was performed to explore the effects of SV2A on the intracellular transport of APP. APP, β-site amyloid precursor protein cleaving enzyme 1 (BACE1) expressions, and APP cleavage products levels were investigated to observe the effects of SV2A on APP amyloidogenic processing. RESULTS: APP localization was reduced in the TGN, early endosomes, late endosomes, and lysosomes, whereas it was increased in the recycling endosomes and cell membrane of SV2A-overexpressed neurons. Moreover, Arl5b (ADP-ribosylation factor 5b), a protein responsible for transporting APP from the TGN to early endosomes, was upregulated by SV2A. SV2A overexpression also decreased APP transport from the cell membrane to early endosomes by downregulating APP endocytosis. In addition, products of APP amyloid degradation, including sAPPβ, Aβ _1-42, and Aβ _1-40, were decreased in SV2A-overexpressed cells. CONCLUSION These results demonstrated that SV2A promotes APP transport from the TGN to early endosomes by upregulating Arl5b and promoting APP transport from early endosomes to recycling endosomes-cell membrane pathway, which slows APP amyloid degradation.
Amyloid beta-Protein Precursor/genetics* ; Membrane Glycoproteins/genetics* ; Animals ; Protein Transport ; Nerve Tissue Proteins/genetics* ; Humans ; Mice ; Endosomes/metabolism* ; trans-Golgi Network/metabolism*

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.

Objective:To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods:This study analyzed plasma metabolomics data from 2 183 healthy adults in the China Kadoorie Biobank (CKB), measured using targeted mass spectrometry. Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality. Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease (CVD) risks, cancer, and other-cause mortality. Stepwise regression was used to identify key metabolites independently associated with all-cause mortality, and the area under the receiver operating characteristic curve (AUC) was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results:The mean age of the participants was (53.2±9.8) years, 65.1% of whom were female. During a median follow-up of 14.5 years, 231 deaths occurred. A total of 44 metabolites were significantly associated with the risk of all-cause mortality [false discovery rate (FDR)-adjusted P<0.05], primarily including triglycerides, ceramides, and amino acids. Additionally, 29 and 15 metabolites were found to be associated with cancer and other-cause mortality, respectively, but no metabolites were significantly associated with CVD mortality after FDR corrections. Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance. Specifically, incorporating metabolites into the traditional model, which already included laboratory biomarkers, increased the AUC to 0.798 (95% CI: 0.755-0.843), an improvement of 0.088 compared to the traditional model ( P<0.001). Conclusions:Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models. These findings provide new insights into the physiological mechanisms of aging and offer valuable clues for personalized health risk assessment.

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.

Objective:To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods:This study analyzed plasma metabolomics data from 2 183 healthy adults in the China Kadoorie Biobank (CKB), measured using targeted mass spectrometry. Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality. Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease (CVD) risks, cancer, and other-cause mortality. Stepwise regression was used to identify key metabolites independently associated with all-cause mortality, and the area under the receiver operating characteristic curve (AUC) was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results:The mean age of the participants was (53.2±9.8) years, 65.1% of whom were female. During a median follow-up of 14.5 years, 231 deaths occurred. A total of 44 metabolites were significantly associated with the risk of all-cause mortality [false discovery rate (FDR)-adjusted P<0.05], primarily including triglycerides, ceramides, and amino acids. Additionally, 29 and 15 metabolites were found to be associated with cancer and other-cause mortality, respectively, but no metabolites were significantly associated with CVD mortality after FDR corrections. Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance. Specifically, incorporating metabolites into the traditional model, which already included laboratory biomarkers, increased the AUC to 0.798 (95% CI: 0.755-0.843), an improvement of 0.088 compared to the traditional model ( P<0.001). Conclusions:Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models. These findings provide new insights into the physiological mechanisms of aging and offer valuable clues for personalized health risk assessment.

Objective:To explore the relationship between BMI and levels of plasma amino acids and acylcarnitines in Chinese adults.Methods:Based on 2 182 individuals with targeted mass spectrometry metabolomic measurements from the first resurvey of the China Kadoorie Biobank, we assessed the linear and nonlinear associations between BMI and plasma levels of 20 amino acids and 40 acylcarnitines using linear regression models and restricted cubic spline models, and identified BMI-related metabolic pathways. We conducted one-sample Mendelian randomization (MR) with BMI genetic risk scores as the instrumental variable further to explore the potential causal relationships between BMI and 20 amino acids and 40 acylcarnitines, and tested for horizontal pleiotropy using the MR-Egger method.Results:Observational analyses found that BMI was associated with increased plasma levels of 3 branched-chain amino acids (isoleucine, leucine, and valine), 2 aromatic amino acids (phenylalanine and tyrosine), 3 other amino acids (cysteine, glutamate, lysine), and 7 acylcarnitines (C3, C4, C5, C10, C10:1, C14, and C16), and with decreased circulating levels of asparagine, serine, and glycine. Pathway analysis identified 7 BMI-related amino acids metabolic pathways (false discovery rate corrected all P<0.05), including branched-chain amino acids and aromatic amino acids biosynthesis, glutathione metabolism, etc. BMI showed a nonlinear relationship with leucine, valine, and threonine, and a linear relationship with other amino acids and acylcarnitines. One-sample MR analyses revealed that BMI was associated with elevated levels of tyrosine and 4 acylcarnitines [C5-DC(C6-OH), C5-M-DC, C12-DC, and C14], with tyrosine and acylcarnitine C14 positively correlated with BMI in both observational [the β values (95% CIs) were 0.057 (0.044-0.070) and 0.018 (0.005-0.032), respectively] and One-sample MR analyses [the β values (95% CIs) were 0.102 (0.035-0.169) and 0.104 (0.036-0.173), respectively]. The MR analyses of the current study satisfied the 3 core assumptions of instrumental variable. Conclusions:BMI was associated with circulating 11 amino acids and 7 acylcarnitines in Chinese adults, involving several pathways such as branched-chain amino acid and aromatic amino acid metabolism, fatty acid metabolism, and oxidative stress. There may be a causal relationship between BMI and tyrosine and acylcarnitine C14.

Objective:To describe the distribution of lipoprotein (a) [Lp(a)] levels in non-arteriosclerotic cardiovascular disease (ASCVD) population in China and explore its influencing factors.Methods:This study was based on a nested case-control study in the CKB study measured plasma biomarkers. Lp(a) levels was measured using a polyclonal antibody-based turbidimetric assay certified by the reference laboratory and ≥75.0 nmol/L defined as high Lp(a). Multiple logistic regression model was used to examine the factors related to Lp(a) levels.Results:Among the 5 870 non-ASCVD population included in the analysis, Lp(a) levels showed a right-skewed distribution, with a M ( Q1, Q3) of 17.5 (8.8, 43.5) nmol/L. The multiple logistic regression analysis found that female was associated with high Lp(a) ( OR=1.23, 95% CI: 1.05-1.43). The risk of increased Lp(a) levels in subjects with abdominal obesity was significantly reduced ( OR=0.68, 95% CI: 0.52-0.89). As TC, LDL-C, apolipoprotein A1(Apo A1), and apolipoprotein B(Apo B) levels increased, the risk of high Lp(a) increased, with OR (95% CI) for each elevated group was 2.40 (1.76-3.24), 2.68 (1.36-4.93), 1.29 (1.03-1.61), and 1.65 (1.27-2.13), respectively. The risk of high Lp(a) was reduced in the HDL-C lowering group with an OR (95% CI) of 0.76 (0.61-0.94). In contrast, an increase in TG levels and the ratio of Apo A1/Apo B(Apo A1/B) was negatively correlated with the risk of high Lp(a), with OR (95% CI) of 0.73 (0.60-0.89) for elevated triglyceride group, and OR (95% CI) of 0.60 (0.50-0.72) for the Apo A1/B ratio increase group (linear trend test P≤0.001 except for Apo A1). However, no correlation was found between Lp(a) levels and lifestyle factors such as diet, smoking, and physical activity. Conclusions:Lp(a) levels were associated with sex and abdominal obesity, but less with lifestyle behaviors.

Pyroptosis is the programmed death of cells accompanied by an inflammatory response and is widely involved in the development of a variety of diseases, such as infectious diseases, cardiovascular diseases, and neurodegeneration. It has been shown that cellular scorching is involved in the pathogenesis of pulmonary arterial hypertension ( PAH) in cardiovascular diseases. Patients with PAH have perivascular inflammatory infiltrates in lungs, pulmonary vasculopathy exists in an extremely inflam-matory microenvironment, and pro-inflammatory factors in cellular scorching drive pulmonary vascular remodelling in PAH patients. This article reviews the role of cellular scorch in the pathogenesis of PAH and the related research on drugs for the treatment of PAH, with the aim of providing new ideas for clinical treatment of PAH.

Objective To investigate the distribution of traditional Chinese medicine(TCM)constitution in chronic hepatitis B(CHB)patients complicated with metabolism associated fatty liver disease(MAFLD),and to explore the correlation of the complication of MAFLD with TCM constitution and body composition,thus to determine their predictive values for the complication of MAFLD in CHB patients.Methods A retrospective study was adopted.The study started from the collection of the clinical data of 235 outpatients who attended the Department of Hepatology of Guangdong Provincial Hospital of Integrated Traditional Chinese and Western Medicine from January 2022 to December 2023,and was diagnosed as CHB following the diagnostic criteria.According to the controlled attenuation parameter(CAP)value,134 cases of CHB patients were allocated to the non-MAFLD group(CAP＜238 dB/m)and 101 cases were allocated to the MAFLD group(CAP≥238 dB/m).And then the distribution of TCM constitution in the two groups was observed.In addition,according to the body mass index(BMI)value,the patients were divided into the non-obese group(141 cases,BMI＜24.0 kg/m2)and the overweight/obese group(94 cases,BMI≥24.0 kg/m2).And then the logistic regression was used to analyze the independent risk factors for the complication of MAFLD in CHB patients,multivariate logistic regression was used to analyze the influencing factors,and receiver operating characteristic(ROC)curve was used to analyze the predictive value of the influencing factors for the complication of MAFLD in CHB patients and to determine their optimal cut-off values.Results(1)The constitutions of CHB patients in the MAFLD group were predominated by balanced constitution(36.6%),damp-heat constitution(20.8%),and phlegm-damp constitution(14.9%),which accounted for 72.3%in total.(2)In CHB patients complicated with MAFLD,the overweight/obese group had higher levels of γ-glutamyl-transpeptidase(γ-GT),BMI,total body fat mass(TBFM),total muscle mass(TMM),total body water(TBW),interacel1ular water(ICW),extracellular water(ECW),body fat ratio(BFR),visceral fat area(VFA),basal metabolism(BM),and trunk fat mass(TFM)than the non-obese group,and the differences were statistically significant(P＜0.05 or P＜0.01).(3)The results of multivariate logistic regression analysis showed that the white blood cell(WBC)count,blood uric acid(UA),triglyceride(TG),high-density lipoprotein cholesterol(HDL-C),and VFA were the influencing factors for the complication of MAFLD in the CHB patients in clinic.(4)The results of ROC curve analysis showed that in CHB patients,the areas under the ROC curve(AUC)for age,TG,UA,and VFA were 0.532,0.680,0.738,and 0.859 respectively;the optimal cut-off values of VFA in CHB patients,non-obese CHB patients,and overweight/obese CHB patients were 74.98,66.5 and 112.2 cm2 respectively,and the optimal cut-off values of VFA in patients with balanced constitution,phlegm-damp constitution,and damp-heat constitution were 85.50,66.50,and 74.98 cm2 respectively.The AUC values of VFA in various populations were significantly higher than those of age,TG,and UA,and the combined prediction by multivariate analysis has higher predictive value than that by univariate analysis.Conclusion The AUC value of VFA for predicting the risk of MAFLD is the highest in patients with CHB,and the possibility of the complication of MAFLD increased with the increase of the cut-off point level of VFA.The optimal cut-off values of VFA varies in non-obese group and overweight/obese group of CHB patients and in CHB patients with different TCM constitution.

Objective:To screen interleukin(IL)-1β secretion-related membrane transporters by macrophage experiment in vitro and conventional knockout mice.Methods:THP-1 cell line was differentiated to obtain human THP-1-derived macrophages,and the primary macrophages were obtained from human peripheral blood.FVB wild-type mice with the same sex and age were used as the controls of MRP1 knockout mice.The macrophages in abdominal cavity and bone marrow of mice were cultivated.The cells were treated with ABCC1/MRP1,ABCG2/BCRP,ABCB1/P-gp,OATP1B1,and MATE transporter inhibitors,then stimulated by lipopolysaccharide and adenosine triphosphate.The secretion level of IL-iβ was detected by ELISA,Western blot,and immunofluorescence.Results:After inhibiting ABCC1/MRP1 transporter,the secretion of IL-1β decreased significantly,while inhibition of the other 4 transporters had no effect.In animal experiment,the level of IL-1 β secreted by macrophages in bone marrow of MRP1 knockout mice was significantly lower than control group(P＜0.05).Conclusion:ABCC1/MRP1 transporter is a newly discovered IL-1β secretion pathway,which is expected to become a new target for solving clinical problems such as cytokine release syndrome.