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: 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.

Temporomandibular joint (TMJ) disc displacement is one of the most significant subtypes of temporomandibular joint disorders, but its etiology and mechanism are poorly understood. In this study, we elucidated the mechanisms by which destruction of inflamed collagen fibrils induces alterations in the mechanical properties and positioning of the TMJ disc. By constructing a rat model of TMJ arthritis, we observed anteriorly dislocated TMJ discs with aggravated deformity in vivo from five weeks to six months after a local injection of Freund's complete adjuvant. By mimicking inflammatory conditions with interleukin-1 beta in vitro, we observed enhanced expression of collagen-synthesis markers in primary TMJ disc cells cultured in a conventional two-dimensional environment. In contrast, three-dimensional (3D)-cultivated disc cell sheets demonstrated the disordered assembly of inflamed collagen fibrils, inappropriate arrangement, and decreased Young's modulus. Mechanistically, inflammation-related activation of the nuclear factor kappa-B (NF-κB) pathway occurs during the progression of TMJ arthritis. NF-κB inhibition reduced the collagen fibril destruction in the inflamed disc cell sheets in vitro, and early NF-κB blockade alleviated collagen degeneration and dislocation of the TMJ discs in vivo. Therefore, the NF-κB pathway participates in the collagen remodeling in inflamed TMJ discs, offering a potential therapeutic target for disc displacement.
Animals ; NF-kappa B/metabolism* ; Temporomandibular Joint Disorders/pathology* ; Temporomandibular Joint Disc/metabolism* ; Rats ; Rats, Sprague-Dawley ; Disease Models, Animal ; Male ; Collagen/metabolism* ; Cells, Cultured ; Joint Dislocations/pathology* ; Interleukin-1beta ; Arthritis, Experimental

Tumor treatment remains a significant medical challenge, with many traditional therapies causing notable side effects. Recent research has led to the development of immunotherapy, which offers numerous advantages. Bacteria inherently possess motility, allowing them to preferentially colonize tumors and modulate the tumor immune microenvironment, thus influencing the efficacy of immunotherapy. Bacterial outer membrane vesicles (OMVs) secreted by gram-negative bacteria are nanoscale lipid bilayer structures rich in bacterial antigens, pathogen-associated molecular patterns (PAMPs), various proteins, and vesicle structures. These features allow OMVs to stimulate immune system activation, generate immune responses, and serve as efficient drug delivery vehicles. This dual capability enhances the effectiveness of immunotherapy combined with chemotherapy or phototherapy, thereby improving anticancer drug efficacy. Current research has concentrated on engineering OMVs to enhance production yield, minimize cytotoxicity, and improve the safety and efficacy of treatments. Consequently, OMVs hold great promise for applications in tumor immunotherapy, tumor vaccine development, and drug delivery. This article provides an overview of the structural composition and immune mechanisms of OMVs, details various OMVs modification strategies, and reviews the progress in using OMVs for tumor treatment and their anti-tumor mechanisms. Additionally, it discusses the challenges faced in translating OMV-based anti-tumor therapies into clinical practice, aiming to provide a comprehensive understanding of OMVs' potential for in-depth research and clinical application.

Purinergic P2Y Receptor Antagonists ; Consensus ; Cardiovascular System ; Cardiology ; Asia

【Objective】 To estimate the prevalence, associated factors and patterns of multimorbidity of non-communicable diseases among adults in Shaanxi Province so as to provide evidence for the prevention and control of non-communicable diseases. 【Methods】 We used the data of adults aged 18 years and older collected in the baseline survey of Shaanxi Project in the Regional Ethnic Cohort Study in Northwest China. Multinomial logistic regression was used to explore the associated factors for multimorbidity. Exploratory factor analysis was used to extract patterns of multimorbidity. 【Results】 The prevalence of multimorbidity was 10.7% among the 44 442 participants. Age increase, being males, urban residence, and being overweight or obesity were positively associated with multimorbidity. Compared with women, men had a higher risk of multimorbidity. The OR and 95% CI was 1.25 (1.12-1.39). The risk of multimorbidity increased with age among adults. Compared with participants aged 18.0-34.9 years, the ORs and 95% CIs of those aged 35.0-44.9, 45.0-54.9, 55.0-64.9, and ≥65.0 years were 4.73 (3.47-6.46), 15.61 (11.60-21.00), 41.39 (30.76-55.70) and 90.04 (66.58-121.77), respectively. The primary multimorbidity patterns among adults in Shaanxi were cardiovascular-metabolic multimorbidity (5.4%), viscero-articular multimorbidity (1.0%), and respiratory multimorbidity (0.3%). 【Conclusion】 More than one in ten adults in Shaanxi Province had multimorbidity, and the predominant pattern of multimorbidity was cardiovascular-metabolic multimorbidity. The prevention and control of non-communicable diseases should be reinforced in middle-aged and older people, males, people living in the urban, and overweight or obese people. More attention should be paid to the prevention and control of cardiovascular-metabolic diseases.

The accurate annotation of transcription start sites(TSSs)and their usage are critical for the mechanistic understanding of gene regulation in different biological contexts.To fulfill this,specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner,and various computational tools have also been developed for in silico pre-diction of TSSs solely based on genomic sequences.Most of these computational tools cast the problem as a binary classification task on a balanced dataset,thus resulting in drastic false positive predictions when applied on the genome scale.Here,we present DeeReCT-TSS,a deep learning-based method that is capable of identifying TSSs across the whole genome based on both DNA sequence and conventional RNA sequencing data.We show that by effectively incorporating these two sources of information,DeeReCT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell types.Furthermore,we develop a meta-learning-based extension for simultaneous TSS annotations on 10 cell types,which enables the identification of cell type-specific TSSs.Finally,we demonstrate the high precision of DeeReCT-TSS on two independent datasets by correlating our predicted TSSs with experimentally defined TSS chromatin states.The source code for DeeReCT-TSS is available at https://github.-com/JoshuaChou2018/DeeReCT-TSS_release and https://ngdc.cncb.ac.cn/biocode/tools/BT007316.

Adventitia ; Atherosclerosis/genetics* ; Cell Communication ; Humans ; Hyperhomocysteinemia/genetics* ; Sequence Analysis, RNA