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.

Objectives: Hip fracture is a global public concern exhibiting high mortality rates but often underrecognized. We compared the mortality rates, risk, and secular trend of hip fractures with common cancers in females and males, aiming to call attention to hip fractures. Methods: In 2010–2020, 193,767 patients with the first diagnosed hip fractures and the top 5 prevalent cancers in each sex and aged 50 years and above were included. Age-standardized mortality rates were adjusted to the WHO Standard Population and the sex-specific relative risk of mortality was computed using Cox proportional hazards models, adjusted for potential confounders. The trend analyses used joinpoint regression to compute annual percent changes in age-standardized mortality rates. Results The 1-year and 5-year age-standardized mortality rates and sex-specific mortality risk of hip fracture are greater than those of breast cancer (hazard ratio [HR]: 0.93, 95% confidence interval [CI]: 0.90 to 0.97) and thyroid cancer (HR: 0.55, 95% CI: 0.47 to 0.64) in females and prostate cancer (HR: 0.56, 95% CI: 0.53 to 0.58) in males. Moreover, mortality rates in lung cancer, male liver cancer, female breast cancer, and male prostate cancer have decreased in the past decade. For hip fracture, the mortality rates have significantly decreased in females, while in males, we observed only a decreasing trend in 1-year hip fracture mortality, not in 5-year Conclusions: Hip fractures exhibit higher mortality compared to female breast and thyroid cancers and male prostate cancer. More attention is needed to enhance the management and prevention of hip fractures.

Objectives: Hip fracture is a global public concern exhibiting high mortality rates but often underrecognized. We compared the mortality rates, risk, and secular trend of hip fractures with common cancers in females and males, aiming to call attention to hip fractures. Methods: In 2010–2020, 193,767 patients with the first diagnosed hip fractures and the top 5 prevalent cancers in each sex and aged 50 years and above were included. Age-standardized mortality rates were adjusted to the WHO Standard Population and the sex-specific relative risk of mortality was computed using Cox proportional hazards models, adjusted for potential confounders. The trend analyses used joinpoint regression to compute annual percent changes in age-standardized mortality rates. Results The 1-year and 5-year age-standardized mortality rates and sex-specific mortality risk of hip fracture are greater than those of breast cancer (hazard ratio [HR]: 0.93, 95% confidence interval [CI]: 0.90 to 0.97) and thyroid cancer (HR: 0.55, 95% CI: 0.47 to 0.64) in females and prostate cancer (HR: 0.56, 95% CI: 0.53 to 0.58) in males. Moreover, mortality rates in lung cancer, male liver cancer, female breast cancer, and male prostate cancer have decreased in the past decade. For hip fracture, the mortality rates have significantly decreased in females, while in males, we observed only a decreasing trend in 1-year hip fracture mortality, not in 5-year Conclusions: Hip fractures exhibit higher mortality compared to female breast and thyroid cancers and male prostate cancer. More attention is needed to enhance the management and prevention of hip fractures.

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.

Objectives: Hip fracture is a global public concern exhibiting high mortality rates but often underrecognized. We compared the mortality rates, risk, and secular trend of hip fractures with common cancers in females and males, aiming to call attention to hip fractures. Methods: In 2010–2020, 193,767 patients with the first diagnosed hip fractures and the top 5 prevalent cancers in each sex and aged 50 years and above were included. Age-standardized mortality rates were adjusted to the WHO Standard Population and the sex-specific relative risk of mortality was computed using Cox proportional hazards models, adjusted for potential confounders. The trend analyses used joinpoint regression to compute annual percent changes in age-standardized mortality rates. Results The 1-year and 5-year age-standardized mortality rates and sex-specific mortality risk of hip fracture are greater than those of breast cancer (hazard ratio [HR]: 0.93, 95% confidence interval [CI]: 0.90 to 0.97) and thyroid cancer (HR: 0.55, 95% CI: 0.47 to 0.64) in females and prostate cancer (HR: 0.56, 95% CI: 0.53 to 0.58) in males. Moreover, mortality rates in lung cancer, male liver cancer, female breast cancer, and male prostate cancer have decreased in the past decade. For hip fracture, the mortality rates have significantly decreased in females, while in males, we observed only a decreasing trend in 1-year hip fracture mortality, not in 5-year Conclusions: Hip fractures exhibit higher mortality compared to female breast and thyroid cancers and male prostate cancer. More attention is needed to enhance the management and prevention of hip fractures.

Objectives: Hip fracture is a global public concern exhibiting high mortality rates but often underrecognized. We compared the mortality rates, risk, and secular trend of hip fractures with common cancers in females and males, aiming to call attention to hip fractures. Methods: In 2010–2020, 193,767 patients with the first diagnosed hip fractures and the top 5 prevalent cancers in each sex and aged 50 years and above were included. Age-standardized mortality rates were adjusted to the WHO Standard Population and the sex-specific relative risk of mortality was computed using Cox proportional hazards models, adjusted for potential confounders. The trend analyses used joinpoint regression to compute annual percent changes in age-standardized mortality rates. Results The 1-year and 5-year age-standardized mortality rates and sex-specific mortality risk of hip fracture are greater than those of breast cancer (hazard ratio [HR]: 0.93, 95% confidence interval [CI]: 0.90 to 0.97) and thyroid cancer (HR: 0.55, 95% CI: 0.47 to 0.64) in females and prostate cancer (HR: 0.56, 95% CI: 0.53 to 0.58) in males. Moreover, mortality rates in lung cancer, male liver cancer, female breast cancer, and male prostate cancer have decreased in the past decade. For hip fracture, the mortality rates have significantly decreased in females, while in males, we observed only a decreasing trend in 1-year hip fracture mortality, not in 5-year Conclusions: Hip fractures exhibit higher mortality compared to female breast and thyroid cancers and male prostate cancer. More attention is needed to enhance the management and prevention of hip fractures.

Adenosine-to-inosine (A-to-I), one of the most prevalent RNA modifications, has recently garnered significant attention. The A-to-I modification actively contributes to biological and pathological processes by affecting the structure and function of various RNA molecules, including double-stranded RNA, transfer RNA, microRNA, and viral RNA. Increasing evidence suggests that A-to-I plays a crucial role in the development of human disease, particularly in cancer, and aberrant A-to-I levels are closely associated with tumorigenesis and progression through regulation of the expression of multiple oncogenes and tumor suppressor genes. Currently, the underlying molecular mechanisms of A-to-I modification in cancer are not comprehensively understood. Here, we review the latest advances regarding the A-to-I editing pathways implicated in cancer, describing their biological functions and their connections to the disease.
Humans ; Adenosine/genetics* ; Inosine/genetics* ; RNA Editing ; Neoplasms/pathology* ; Animals ; MicroRNAs/metabolism*

Traditional Chinese medicine (TCM) serves as a treasure trove of ancient knowledge, holding a crucial position in the medical field. However, the exploration of TCM's extensive information has been hindered by challenges related to data standardization, completeness, and accuracy, primarily due to the decentralized distribution of TCM resources. To address these issues, we developed a platform for TCM knowledge discovery (TCMKD, https://cbcb.cdutcm.edu.cn/TCMKD/). Seven types of data, including syndromes, formulas, Chinese patent drugs (CPDs), Chinese medicinal materials (CMMs), ingredients, targets, and diseases, were manually proofread and consolidated within TCMKD. To strengthen the integration of TCM with modern medicine, TCMKD employs analytical methods such as TCM data mining, enrichment analysis, and network localization and separation. These tools help elucidate the molecular-level commonalities between TCM and contemporary scientific insights. In addition to its analytical capabilities, a quick question and answer (Q&A) system is also embedded within TCMKD to query the database efficiently, thereby improving the interactivity of the platform. The platform also provides a TCM text annotation tool, offering a simple and efficient method for TCM text mining. Overall, TCMKD not only has the potential to become a pivotal repository for TCM, delving into the pharmacological foundations of TCM treatments, but its flexible embedded tools and algorithms can also be applied to the study of other traditional medical systems, extending beyond just TCM.

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.