Runmin Guo

Objective:: Resistance to 5-fluorouracil (5-FU) necessitates its administration in combination with other drugs to enhance the clinical outcome. Oxymatrine (OMT) exhibits antitumor and anti-inflammatory activities. This study aimed to investigate the synergistic antitumor effect of OMT with 5-FU in A549 cells. Methods:: The knockout of human Apurinic/Apyrimidinic Endonuclease 1 (APE1) in A549 cells was achieved using shRNA. The level of APE1 protein was determined via Western blotting. The levels of IL-2, IL-6, and IL-8 were detected using ELISA. The level of intracellular Reactive Oxygen Species (ROS) and cell cycle were analyzed by flow cytometry. Genome-wide transcriptome profiling was conducted using RNA- sequencing technology and bioinformatics analyses. Results:: OMT synergistically augmented the antitumor activity of 5-FU in A549 cells by inhibiting the functions of APE1. OMT differentially modulated the secretion of IL-8, IL-6, and IL-2 from A549 cells in the presence of 5-FU. The inhibition of IL-8 and IL-6 by OMT predominantly occurred via APE1, whereas the inhibition of IL-2 by OMT was APE1-independent. OMT inhibited ROS production independent of APE1 and induced G2/M arrest in APE1-deficient cells. A genome-wide transcriptome analysis identified novel gene targets (B3GNT3, CRABP2, RHOV, and PCSK9) regulated by OMT, which contribute to its antitumor activity. Discussion:: These findings uncover a multitarget mechanism underlying the synergistic antitumor effect of OMT and 5-FU, confirming APE1 as a key regulatory factor linking inflammatory cytokine secretion, ROS homeostasis, and cell cycle progression in lung cancer cells. The newly identified target genes further elaborate the molecular basis of OMT-mediated tumor suppression. This work provides a potential strategy to overcome 5-FU resistance and optimize combination therapy for lung cancer treatment. Conclusion:: This study addresses the issue of 5-FU chemoresistance in lung cancer by validating OMT as a functional synergistic adjuvant. The findings clarify the molecular mechanisms by which OMT enhances 5-FU antitumor efficacy, offering a credible experimental basis for the potential development of optimized combination therapeutic regimens for lung cancer.

This study aimed to compare fetal soft tissue thickness, particularly anterior abdominal wall thickness (AAWT), between GDM and non-GDM pregnancies, and to

Background: Macrophage migration inhibitory factor (MIF) rs1007888 is significantly associated with pancreatic β-cell function and insulin resistance in patients with gestational diabetes mellitus (GDM). The ArfGAP with RhoGAP domain, ankyrin repeat, and PH domain-containing protein 1 (ARAP1) rs1552224 locus has been identified as a risk locus for type 2 diabetes, and recent reports have linked it to elevated blood glucose levels and reduced insulin release upon glucose stimulation. Few studies have been conducted on these genetic variants and their risk of GDM. This study aimed to investigate the association between these two genetic variants (ARAP1) rs1552224 and (MIF) rs1007888 and the risk of developing GDM.Methods: A case-control study involving 500 GDM patients and 502 healthy controls was conducted. DNA was extracted, and rs1007888 and rs1552224 were systematically genotyped using the SNPscan™ genotyping kit. Statistical methods assessed genotype and allele differences linked to GDM risk, followed by a meta-analysis to evaluate the impact of regional factors on GDM.Results: Analyses of (MIF) rs1007888 showed no link to higher GDM risk, but meta-analysis found a significant association (OR>1), indicating a connection to increased GDM risk. ARAP1 rs1552224 was significantly linked to reduced GDM incidence (Allele Model A vs. C: OR = 0.624; 95% CI: 0.425-0.916; p-value = 0.016; Dominant Model AA vs. AC+CC: OR = 0.641; 95% CI: 0.429-0.959; p-value = 0.030), especially in women under 30, rs1552224 Aelle Model (A vs. C: OR = 0.490; 95% CI: 0.281-0.857; p -value = 0.012), Dominant Model (AA vs. AC + CC: OR = 0.523; 95% CI: 0.292-0.938; p -value = 0.030). and those with a BMI≥24, Aelle Model (A vs. C: OR = 0.345; 95% CI: 0.124-0.960; p-value = 0.042). Conversely, a meta-analysis suggested an increased GDM risk with the ARAP1 variant (OR>1).Conclusion: The meta-analysis results demonstrate that there is an enhanced likelihood of GDM associated with the MIF rs1007888 mutation. Moreover, our findings indicate that the ARAP1 rs1552224 variant, specifically the AC genotype and C allele, confers a decreased risk of developing gestational diabetes mellitus (GDM). The outcomes obtained give GDM testing a theoretical foundation.

Introduction: The potassium voltage-gated channel subfamily Q member 1 (KCNQ1) gene is recognized as a type 2 diabetes mellitus (T2DM) susceptibility gene. However, there is limited data regarding the association between KCNQ1 gene polymorphisms and gestational diabetes mellitus (GDM) susceptibility in China. To explore the association between KCNQ1 gene polymorphisms and GDM susceptibility in a Chinese population.Methods: We conducted a case-control study including 500 pregnant women with GDM and 502 pregnant women with normal glucose tolerance (as controls). Blood samples and clinical data were collected. KCNQ1 gene rs2237897, rs163184, rs151290, and rs2237892 were genotyped by SNPscan™ genotyping assay. Using SPSS V.26.0, statistical analysis was performed to explore the association of KCNQ1 gene polymorphisms with GDM and genotypes with blood glucose levels. Meta-analysis was further validated in different populations.Results: After being adjusted for confounding factors (age, parity, pre-pregnancy BMI (pre-BMI) and blood pressure) and Bonferroni correction, rs2237897 showed an association with decreased GDM risk in codominant heterozygous (CT vs. CC: OR = 0.537; 95% CI: 0.354-0.816; P = 0.004) and overdominant models (CT vs. CC+TT: OR = 0.533; 95% CI: 0.355-0.801; P = 0.002) in pregnant women aged < 30 years. However, rs2237892, rs151290, and rs163184 did not found associations with GDM after Bonferroni correction. Meta-analysis showed that rs2237892 was associated with decreased GDM risk in different races in dominant (TC+TT vs. CC: OR = 0.830; 95% CI: 0.699-0.985; P = 0.033), recessive (TT vs. CT+CC: OR = 0.733; 95% CI: 0.612-0.877; P = 0.001), codominant homozygous (TT vs. CC: OR = 0.679; 95% CI: 0.562-0.820; P < 0.001), codominant heterozygous (TC vs. CC: OR = 0.843; 95% CI: 0.753-0.945; P = 0.003) and allele models (T vs. C: OR = 0.852; 95% CI: 0.740-0.982; P = 0.027).Conclusion: KCNQ1 rs2237897 is associated with decreased GDM risk in a Chinese population. Although rs2237892 did not found association with GDM risk in our subjects, meta-analysis confirmed that rs2237892 is associated with reduced GDM risk across different populations. Further studies are needed to confirm these findings and elucidate the mechanisms.

The aim of this study is to explore the relationship between the MTNR1B gene variants rs1387153 and rs10830963 and the risk of gestational diabetes mellitus (GDM). Additionally, the study sought to investigate gene-environment interactions, assess the cumulative genetic risk through the application of Genetic Risk Scores (GRSs), and establish a predictive model for GDM. A case-control study was conducted with 500 GDM patients and 502 controls. MTNR1B gene variants were genotyped using SNPscan™. Associations between clinical data, genetic models, haplotype and GDM risk or blood glucose levels were analyzed using statistical tests. Gene-environment interactions were preliminarily analyzed with GMDR and logistic regression. SNP-age interactions were further explored through stratified analysis and GRS. A predictive model was developed using logistic regression, validated with bootstrap resampling, and its clinical utility was evaluated with decision curve analysis. The study has identified a significant association between the MTNR1B gene variants rs1387153 and rs10830963 and an increased risk of GDM, particularly in women under 30 years of age (all OR > 1, P < 0.05; rs1387153 TT vs. CC: OR = 2.969, P < 0.001, rs10830963 GG vs. CC: OR = 3.066, P < 0.001). The gene-age interaction was found to be statistically significant (P < 0.05). The analysis of the TC haplotype (OR > 1, P < 0.001) and the GRS, specifically in the top quartile of GRS (OR > 3, P < 0.001), further corroborates the cumulative impact of these variants on the risk of GDM among pregnant women under 30 years. The variants also significantly increase postprandial blood glucose levels in pregnant women under 30 years of age (P < 0.05). A predictive model that includes MTNR1B polymorphisms, maternal age, and pre-pregnancy BMI has shown good predictive accuracy for GDM risk (C-Statistics = 0.682, P < 0.001). The study highlights the key role of MTNR1B gene variants rs1387153 and rs10830963 in GDM risk among young pregnant women under the age of 30, with no correlation observed in pregnant women aged 30 and above. The gene-age interaction and GRS provide additional insights into GDM risk. These findings serve as a significant inspiration for future research on populations with MTNR1B gene variations, hopefully prompting more researchers to pay attention to adopting appropriate research, screening, prevention, and intervention strategies for pregnant women with diabetes at different age stages.

Gestational diabetes mellitus (GDM) has seen a significant rise and has become a growing concern worldwide, especially in Asian populations. Genetic factors, such as variations in the CDKAL1 gene, have been linked to its development. However, existing research on this connection is limited and inconclusive, highlighting the need for further investigation. This study aims to explore the association between CDKAL1 gene polymorphisms and GDM risk in a Chinese population using a comprehensive case-control study and meta-analysis. The SNPscan™ genotyping assay was used to genotype rs7754840 and rs7756992, in 502 control participants and 500 GDM patients. ANOVA, T-test, chi-square test, logistic regression, and other statistical tests were used to determine the differences in genotypes and alleles and their associations to the risk of GDM. Additionally, a meta-analysis of existing studies on CDKAL1 polymorphisms and GDM was performed to provide a broader context and resolve inconsistencies in the literature. The GDM group had a significantly older average mean age and higher blood pressure, and fasting plasma glucose levels than the control group (P < 0.05). CDKAL1 rs7754840 showed significant associations under codominant homozygous model (CC vs. GG: OR = 1.748; 95% CI: 1.178–2.593; P = 0.006). After adjusting, these results indicated an association between CDKAL1 rs7754840 and increased risk of GDM in the codominant model (OR = 1.715; 95% CI: 1.133–2.595; P = 0.011). However, further analysis revealed no significant associations under all genetic models for CDKAL1 rs7756992. The study found that individuals under 30 with the rs7754840 CC genotype had higher fasting glucose and postprandial glucose levels (P < 0.05) compared to those with the GG genotype. Figure 3 A demonstrated a modest association between the CDKAL1 and GDM susceptibility (OR 1.16, 95% CI 1.104–1.29, P = 0.0258). Individuals with the CDKAL1 rs7754840 polymorphism was associated to an increased risk of GDM, whereas rs7756992 did not show significant association with GDM risk. These results provide a theoretical foundation for GDM testing to mitigate its associated complications by enhancing our ability to predict, prevent and manage GDM. Ultimately improving outcomes for both mothers and their children. This research contributes to the growing evidence of genetic predisposition to GDM and highlights the importance of CDKAL1 as a potential genetic marker for GDM risk assessment.

Background: Although the association between HHEX, IGF2BP2, and FTO polymorphisms and the risk of GDM has been investigated in several studies, the findings have been inconsistent across different populations. The study aimed to investigate the association between genetic polymorphisms and GDM risk in a Chinese population.Methods: 502 control volunteers and 500 GDM patients were enrolled. IGF2BP2 rs11705701 and rs4402960, FTO rs9939609, and HHEX rs1111875 and rs5015480 were all genotyped using the SNPscan™ genotyping assay. The independent sample t-test, logistic regression, and chi-square test were used to assess the variations in genotype and allele and their relationships with the risk of GDM. The blood glucose level, gestational week of delivery, and newborn weight were compared using a one-way ANOVA.Results: After adjusting for confounding factors, the results show that the rs1111875 heterozygous (OR=1.370; 95% CI: 1.040-1.805; P = 0.025) and overdominant (OR=1.373; 95% CI: 1.049-1.796; P = 0. 021) models are significantly associated with an increased risk of GDM, especially for the age ≥ 30 years group: heterozygote (OR=1.646; 95% CI: 1.118-2.423; P=0.012) and overdominant (OR=1.553; 95% CI: 1.064-2.266; P = 0.022) models. In the age ≥ 30 years, the rs5015480 overdominant model (OR=1.595; 95% CI: 1.034-2.459; P = 0.035) and the rs9939609 heterozygote model (OR=1.609; 95% CI: 1.016-2.550; P=0.043), allele (OR=1. 504; 95% CI: 1.006-2.248; P = 0.047), dominant model (OR=1.604; 95% CI: 1.026-2.505; P = 0.038), and overdominant model (OR=1.593; 95% CI: 1.007-2.520; P = 0.047) were associated with a significantly increased risk of GDM; Additionally, people with the TC genotype of rs1111875 had a substantially higher 1-hour blood glucose level than TT genotype (P < 0.05). The results of the meta-analysis showed that the A allele of rs11705701 was associated with an increased risk of diabetes mellitus (P < 0.05).Conclusion: The study indicates that the TC genotype of rs1111875 is linked to a higher risk of GDM, particularly in women aged 30 years or older. Additionally, rs5015480 and rs9939609 were significantly associated with GDM in the same age group. These SNPs may therefore be more closely linked to GDM in older mothers.

Gestational diabetes mellitus (GDM) poses a significant global health concern, impacting both maternal and fetal well-being. Early detection and treatment are imperative to mitigate adverse outcomes during pregnancy. This review delves into the pivotal role of insulin function and the influence of genetic variants, including SLC30A8, CDKAL1, TCF7L2, IRS1, and GCK, in GDM development. These genetic variations affect beta-cell function and insulin activity in crucial tissues, such as muscle, disrupting glucose regulation during pregnancy. We propose a hypothesis that this variation may disrupt zinc transport, consequently impairing insulin production and secretion, thereby contributing to GDM onset. Furthermore, we discussed the involvement of inflammatory pathways, such as TNF-alpha and IL-6, in predisposing individuals to GDM. Genetic modulation of these pathways may exacerbate glucose metabolism dysregulation observed in GDM patients. We also discussed how GDM affects cardiovascular disease (CVD) through a direct correlation between pregnancy and cardiometabolic function, increasing atherosclerosis, decreased vascular function, dyslipidemia, and hypertension in women with GDM history. However, further research is imperative to unravel the intricate interplay between inflammatory pathways, genetics, and GDM. This understanding is pivotal for devising targeted gene therapies and pharmacological interventions to rectify genetic variations in SLC30A8, CDKAL1, TCF7L2, IRS1, GCK, and other pertinent genes. Ultimately, this review offers insights into the pathophysiological mechanisms of GDM, providing a foundation for developing strategies to mitigate its impact.