Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Objective To establish an ideal modeling method for diarrhea predominant irritable bowel syndrome(IBS-D)with anxiely and depression in rats,and to provide a basis for the clinical study of IBS-D.Methods 60 rats were used in this study.(1)At first,20 rats were randomly divided into blank,3%acetic acid enema,4%acetic acid enema,and 5%acetic acid enema groups.After the modeling and observation period,the diarrhea status and the degree of colon injury caused by different modeling concentrations were observed by diarrhea related index and colon histopathology.(2)After the optimal modeling concentration was assessed,40 rats were randomly divided into control(a),acetic acid enema(b),acetic acid+binding(c),and acetic acid+binding+tail clip(d)groups and correspondingly treated for 8 days.After the treatments,the general condition,diarrhea-related index,open field test(OFT)score,and colonic histopathology of rats were evaluated.Results(1)Compared with the blank group,the fecal trait score of 4%acetic acid enema group was increased on days 1 to 3 after intervention(P＜0.001),and gradually decreased on days 4 to 7 after intervention.After 1 week,there was no significant difference between the fecal trait score and that of the blank group(P＞0.05).Body weight was lower(P＜0.01),fecal water content was higher(P＜0.001).Compared with blank group,body weight of the 5%acetic acid enema group was decreased(P＜0.001),the fecal trait score and diarrhea index were increased(P＜0.01).No significant difference was found between 3%acetic acid enema and blank groups.The pathological colon tissue showed that,compared with the blank group,the mucosal structure of the 4%acetic acid enema group was complete with a small amount of inflammatory cell infiltration,and the pathological tissue score showed no significant difference(P＞0.05),whereas the 5%acetic acid enema had a medium to large amount of inflammatory cell infiltration,and the pathological tissue score was increased(P＜0.01).(2)Compared with group a,group b had lower body weight(P＜0.001),and higher fecal trait score,fecal water content and diarrhea index(P＜0.01).Compared with a and b groups,the body weight of c and d groups was lower(P＜0.001),the fecal traits score,fecal water content,and diarrhea index were increased(P＜0.01),and the colon running time was decreased(P＜0.01).Compared with group c,Fecal water content in group D was higher(P＜0.001).In the OFT score,compared with a and b groups,the OFT distance,standing times,and upright times in c and d groups were lower(P＜0.05).Compared with c,the OFT distance,standing times,and upright times in d group were lower(P＜0.05).The pathological tissue of colon showed that the mucosal structure of the four groups was complete,and there were different degrees of inflammatory cell infiltration.The pathological tissue scores of groups c and d were higher than those of groups a and b(P＜0.05).Conclusions The 4%acetic acid concentration is appropriate for IBS-D modeling.After superposition and binding,the IBS-D diarrhea and internal hypersensitivity characteristic state can be better simulated.After superposition of a tail clip,the IBS-D model of liver stagnation and spleen deficiency can be established successfully.

Objective:This paper aims to analyze the current status,characteristics,and problems of the policy text of China's chronic disease from the perspective of full-cycle,and provide a reference for subsequent policy optimization.Methods:The author selected 104 policy documents on chronic disease published at the national level from 2009 to 2023,used content analysis method,constructed a two-dimensional analysis framework of"policy tools-full-cycle management",and carried out one-dimensional quantitative analysis and two-dimensional cross-analysis.Results:The application of policy tools is obviously unbalanced,with supply-type policy tools accounting for as much as 63.23％,and demand-type policy tools used the least,only 10.51％.In the dimension of full-cycle management,the proportions of prevention,prevention and treatment,treatment,treatment and rehabilitation,health care,and full-cycle stages are 21.01％,24.58％,28.89％,7.32％,4.69％and 13.51％respectively.It is noteworthy that the proportions of the treatment and rehabilitation,and health care stages are relatively low.All stages of chronic disease health management interact frequently with supply-type policies,and the treatment and rehabilitation,health care and full-cycle stages cross less with demand-type policy tools.Conclusion:It is necessary to adjust the proportion of policy tools,strengthen their internal coordination,improve the top-level design of treatment and rehabilitation and health care,enhance the synergistic interaction between various types of policy tools and full-cycle management,and improve the overall effectiveness of policies.

Objective To investigate the current status of frailty in patients on maintenance hemodialysis(MHD),and explore the correlation of frailty with anxiety and depression.Methods General information,clinical data and blood biochemical data of 101 cases who underwent MHD in Department of Nephrology,Shunde Hospital Affiliated to Jinan University from January 2023 to January 2024 were collected.FRAIL scale was applied to evaluate the frailty of the patients,and they were accordingly classified into frailty group and non-frailty group(including pre-frail and non-frail participants).Anxiety and depression were evaluated by GAD-7 and PHQ-9 scale.Univariate analysis and logistic regression were used to explore the association of frailty with anxiety,depression and other possible influencing factors.Results Among the 101 cases,29 cases(28.71%)were includedin frailty group and 72 cases(71.29%)in non-frailty group.There were 42 patients with depression(41.58%)and 25 with anxiety(24.75%).In the frailty group,the prevalence of depression was 65.52%and that of anxiety 55.17%.There were significant differences in age,grip strength,exercise,stroke and coronary heart disease,anxiety and depression,ferritin and CRP between the two groups(P＜0.01).Multivariate regression analysis showed that depression,anxi-ety,no exercise,stroke and high ferritin concentration were independent risk factors for frailty in MHD patients(P＜0.05).Conclusion In patients on MHD,frailty is closely associated with depression,anxiety,and lack of exercise,and stroke as well as high ferritin concentration are independent risk factors for frailty.