Background: Identification of the unknown pathogenic factor driving atherosclerosis not only enhances the development of disease biomarkers but also facilitates the discovery of new therapeutic targets, thus contributing to the improved management of coronary artery disease (CAD). We aimed to identify causative protein biomarkers in CAD etiology based on proteomics and 2-sample Mendelian randomization (MR) design. Methods: Serum samples from 33 first-onset CAD patients and 31 non-CAD controls were collected and detected using protein array. Differentially expressed analyses were used to identify candidate proteins for causal inference. We used 2-sample MR to detect the causal associations between the candidate proteins and CAD. Network MR was performed to explore whether metabolic risk factors for CAD mediated the risk of identified protein. Vascular expression of candidate protein in situ was also detected. Results: Among the differentially expressed proteins identified utilizing proteomics, we found that circulating Golgi protein 73 (GP73) was causally associated with incident CAD and other atherosclerotic events sharing similar etiology. Network MR approach showed low-density lipoprotein cholesterol and glycated hemoglobin serve as mediators in the causal pathway, transmitting 42.1% and 8.7% effects from GP73 to CAD, respectively. Apart from the circulating form of GP73, both mouse model and human specimens imply that vascular GP73 expression was also upregulated in atherosclerotic lesions and concomitant with markers of macrophage and phenotypic switching of vascular smooth muscle cells (VSMCs). Conclusions: Our study supported GP73 as a biomarker and causative for CAD. GP73 may involve in CAD pathogenesis mainly via dyslipidemia and hyperglycemia, which may enrich the etiological information and suggest future research direction on CAD.

UNASSIGNED: The aim of this research was to ascertain the correlations between alexithymia, social support, depression, and glycemic control in patients diagnosed with type 2 diabetes mellitus. Additionally, this study sought to delve into the potential mediating effects of social support and depression in the relationship between alexithymia and glycemic control.
UNASSIGNED: A purposive sampling methodology was employed to select a cohort of 318 patients afflicted with type 2 diabetes mellitus, hailing from a care establishment situated in Chengdu City. This investigation embraced a cross-sectional framework, wherein instruments such as the General Information Questionnaire, the Toronto Alexithymia Scale 20, the Social Support Rating Scale, and the Hamilton Depression Scale were judiciously administered. The primary objective of this endeavor was to unravel the interplay that exists amongst alexithymia, social support, depression, and glycemic control. The inquiry discerned these interrelationships through both univariate and correlational analyses, subsequently delving into a comprehensive exploration of the mediating ramifications engendered by social support and depression in the nexus between alexithymia and glycemic control.
UNASSIGNED: The HbA1c level of patients diagnosed with type 2 diabetes mellitus was recorded as (8.85 ± 2.107), and their current status with regards to alexithymia, social support, and depression were measured as (58.05 ± 4.382), (34.29 ± 4.420), and (7.17 ± 3.367), respectively. Significant correlations were found between HbA1c and alexithymia (R=0.392, P<0.01), social support (R=-0.338, P<0.01), and depression (R=0.509, P<0.01). Moreover, alexithymia correlation with social support (R=-0.357, P<0.01) and with depression (R=0.345, P<0.01). Regarding the mediation analysis, the direct effect of alexithymia on HbA1c was calculated to be 0.158, while the indirect effect through social support and depression were 0.086 and 0.149, respectively. The total effect value was determined to be 0.382, with the mediating effect accounting for 59.95%, and the direct effect accounting for 40.31%.
UNASSIGNED: Alexithymia exerts both direct and indirect adverse effects on glycemic control, thereby exacerbating disease outcomes. Hence, it is imperative to prioritize the mental health status of individuals with type 2 diabetes to enhance overall well-being, ameliorate diabetes-related outcomes, elevate patients\' quality of life, and alleviate the psychological distress and financial burden associated with the condition.

BACKGROUND: Stress-induced hyperglycemia (SIH) is associated with poor outcomes in cardiogenic shock (CS), and there have been inconsistent results among patients with or without diabetes mellitus (DM). The glycemic gap (GG) is derived by subtracting A1c-derived average glucose from blood glucose levels; it is a superior indicator of SIH. We aimed to explore the role of GG in the outcomes of patients with CS.
METHODS: Data on patients diagnosed with CS were extracted from the MIMIC-IV v2.0 database to investigate the relationship between GG and 30-day mortality (Number of absolute GG subjects = 359; Number of relative GG subjects = 357). CS patients from the Second Affiliated Hospital of Wenzhou Medical University were enrolled to explore the correlation between GG and lactic acid (Number of absolute GG subjects = 252; Number of relative GG subjects = 251). Multivariate analysis, propensity score-matched (PSM) analysis, inverse probability treatment weighting (IPTW), and Pearson correlation analysis were applied.
RESULTS: Absolute GG was associated with 30-day all-cause mortality in CS patients (HRadjusted: 1.779 95% CI: 1.137-2.783; HRPSM: 1.954 95% CI: 1.186-3.220; HRIPTW: 1.634 95% CI: 1.213-2.202). The higher the absolute GG level, the higher the lactic acid level (βadjusted: 1.448 95% CI: 0.474-2.423). A similar trend existed in relative GG (HRadjusted: 1.562 95% CI: 1.003-2.432; HRPSM: 1.790 95% CI: 1.127-2.845; HRIPTW: 1.740 95% CI: 1.287-2.352; βadjusted:1.294 95% CI: 0.369-2.219). Subgroup analysis showed that the relationship existed irrespective of DM. The area under the curve of GG combined with the Glasgow Coma Scale (GCS) for 30-day all-cause mortality was higher than that of GCS (absolute GG: 0.689 vs. 0.637; relative GG: 0.688 vs. 0.633). GG was positively related to the triglyceride-glucose index. Kaplan-Meier curves revealed that groups of higher GG with DM had the worst outcomes. The outcomes differed among races and GG levels (all P < 0.05).
CONCLUSIONS: Among patients with CS, absolute and relative GGs were associated with increased 30-day all-cause mortality, regardless of DM. The relationship was stable after multivariate Cox regression analysis, PSM, and IPTW analysis. Furthermore, they reflect the severity of CS to some extent. Hyperlactatemia and insulin resistance may underlie the relationship between stress-induced hyperglycemia and poor outcomes in CS patients. They both improve the predictive efficacy of the GCS.

To discuss the correlation between serum progesterone, glycosylated Hemoglobin (HbA1c), and insulin levels in pregnant women with Gestational Diabetes Mellitus (GDM) and the risk of Premature Rupture of Membranes (PROM).
A retrospective analysis was conducted on 52 patients diagnosed with GDM who also presented with PROM (Observation group) and compared with 89 patients diagnosed with GDM but not complicated with PROM (Control group). Progesterone, insulin, and HbA1c were detected. Risk factors for PROM in GDM patients were analyzed.
The observation group had higher HbA1c and fasting blood glucose levels. Poor blood glucose control and GWG are risk factors for PROM in GDM patients. PROM increases adverse pregnancy outcomes in GDM. HbA1c, insulin, and HOMA-IR can predict the risk of PROM in GDM.
The effective prediction of preterm PROM can be achieved through the monitoring of serum HbA1c, insulin levels, and insulin resistance in patients with GDM.

OBJECTIVE: To explore the relationship between changes in glycated hemoglobin (HbA1c) during the second and third trimesters and adverse pregnancy outcomes among women without hyperglycemia in pregnancy (HIP).
METHODS: A total of 1,057 pregnant women who underwent serum HbA1c and delivered at Women\'s Hospital, Zhejiang University School of Medicine from May 2022 to March 2023, were included in this study. They were divided into four groups. Associations were evaluated using multivariate logistic regression analysis.
RESULTS: In our study, an upward trend in HbA1c levels in the second trimester (HbA1c_S) and third trimester (HbA1c_T) among women without HIP was demonstrated. Multivariate logistics regression analysis showed significant associations: Pregnant women with HbA1c_S<5.5 %, HbA1c_T≥6.1 %, or with HbA1c_S≥5.5 %, HbA1c_T<6.1 % had a significant correlation with hypertensive disorders of pregnancy (HDP) (aOR:2.72, 95 %CI=1.24-5.97；aOR:2.59, 95 %CI=1.15-5.84). Furthermore, for each 1 % increase in the difference value of HbA1c between the second and third trimesters, the risk of HDP increased about 1.96 times, and the risk of delivering a large-for-gestational-age baby increased about 1.30 times.
CONCLUSIONS: Among pregnant women without HIP, elevated HbA1c levels in the second or third trimester are associated with increased risks of adverse pregnancy outcomes.

Triglyceride-Glucose Index (TyG index) and HbA1c are metabolic risk factors associated with insulin resistance (IR), which have been confirmed to be independently correlated with the incidence of hypertension. However, there is limited research specifically focusing on the interaction between these two metabolic risk factors in hypertensive populations. Currently, it remains unclear how the metabolic indicators TyG index and HbA1c affect BP control in individuals with hypertension. This study aims to investigate the value and interaction of TyG index and HbA1c in blood pressure (BP) control among hypertensive patients. The results are conducive to enhancing the effectiveness of clinical BP control for individuals with hypertension. This cohort study included 99,336 adults diagnosed with hypertension. Participants were grouped according to the median of TyG index and HbA1c. The main endpoint is inadequate BP control. Multivariable-adjusted risk ratios and multivariable Cox regression analysis were used to represent the relationship between BP control levels and metabolic risk factors. Finally, we evaluated the interaction between TyG index and HbA1c in the population with inadequate BP control. This study confirmed that TyG index and HbA1c, as metabolic risk factors, are independently associated with poor BP control (P < 0.05). In multivariable Cox regression analysis, it was found that TyG index and HbA1c were significantly associated with poor BP control. In the male elderly population, HbA1c was significantly associated with poor BP control (P = 0.029).

BACKGROUND: The relationship between gut microbiota and vertigo, specifically Benign Paroxysmal Vertigo (BPV) and Vertigo of Central (VC), remains underexplored.
UNASSIGNED: This study aims to investigate the causal relationships between gut microbiota and two types of vertigo, BPV and VC. Additionally, the study seeks to explore the mediation effects of metabolic, inflammatory, and psychological factors on these relationships. We hypothesize that specific taxa of gut microbiota have a causal effect on the risk of developing BPV and VC. The mediation effects of HbA1c, obesity, major depression, and interleukin-18 levels significantly influence the relationships between gut microbiota and vertigo.
METHODS: Utilizing a bidirectional two-sample Mendelian randomization approach, this study investigated causal associations between gut microbiota and the two types of vertigo. A network MR assessed mediation effects of HbA1c, major depression, obesity, and interleukin-18 levels, with data sourced from several consortia, including MiBioGen.
RESULTS: Distinct gut microbiota displayed varying influences on BPV and VC risks. A total of ten taxa affect BPV. Among these, two taxa have an odds ratio (OR) greater than 1, including one class, one order. Conversely, eight taxa have an OR less than 1, encompassing four families, three genera, and one order. The OR for these taxa ranges from 0.693 to 0.930, with p-values between 0.006 and 0.048. For VC, eight taxa were found to have an impact. Five of these taxa exhibit an OR greater than 1, including four genera and one phylum. The OR for these taxa ranges from 1.229 to 2.179, with p-values from 0.000 to 0.046. The remaining three taxa have an OR less than 1, comprising one family and two genera, with an OR range of 0.445 to 0.792 and p-values ranging from 0.013 to 0.050. The mediation analysis for BPV shows that major depression, obesity, and HbA1c are key mediators between specific taxa and BPV. Major depression mediates 28.77% of the effect of family Rhodospirillaceae on BPV. Obesity mediates 13.90% of the effect of class Lentisphaeria/order Victivallales. HbA1c mediates 11.79% of the effect of genus Bifidobacterium, 11.36% of family Bifidobacteriaceae/order Bifidobacteriales. For VC, interleukin-18 levels and major depression are significant mediators. Interleukin-18 levels mediate 6.56% of the effect of phylum Actinobacteria. Major depression mediates 6.51% of the effect of genus Alloprevotella.
CONCLUSIONS: The study highlights potential causal links between gut microbiota and vertigo, emphasizing metabolic and psychological mediators. These insights underscore the therapeutic potential of targeting gut health in vertigo management.

The hemoglobin glycation index (HGI) has been demonstrated to serve as a substitute for the individual bias in glycosylated hemoglobin A1c (HbA1c). Our objective was to assess the correlation between HGI and cardiovascular (CV) outcomes in patients with diabetes and coronary artery disease (CAD).
We sequentially recruited 11921 patients with diabetes and CAD at Fuwai Hospital. The patients were categorized into five groups based on their HGI quintiles, ranging from Q1 to Q5. The primary endpoint was the occurrence of major adverse cardiac events (MACEs), which included CV death and nonfatal myocardial infarction.
During the median 3-year follow-up, 327 (2.7%) MACEs were observed. A U-shaped relationship between HGI and 3-year MACEs was demonstrated by restricted cubic spline (RCS) after multivariable adjustment (nonlinear P = 0.014). The Kaplan-Meier curves demonstrated that the Q2 group had the lowest risk of MACE (P = 0.006). When comparing the HGI Q2 group, multivariable Cox regression models showed that both low (Q1) and high (Q4 or Q5) HGI were linked to a higher risk of MACEs (all P < 0.05). Patients with a low HGI (Q1) had a significantly increased risk of all-cause and CV death, with a 1.70-fold increase in both cases (both P < 0.05).
In individuals with diabetes and established CAD, HGI levels were found to have a U-shaped relationship with the occurrence of MACEs over a period of three years. Significantly, those with low HGI had an increased risk of CV death.

Glycosylated haemoglobin index (HGI) has been shown to correlate with the prognosis of metabolic diseases, but the relationship with mortality remains unclear. This study included 18,285 US adults who participated in the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018. During the median follow-up period of 115 months, a total of 2572 all-cause deaths and 671 cardiovascular disease (CVD) deaths occurred. The restricted cubic spline revealed a U-shaped correlation between HGI and all-cause and CVD mortality. After adjusting for all covariates, the optimal inflection point values in all-cause and CVD deaths were 0.17 and 0.02, respectively. In the left side of the inflection point, the risk of all-cause mortality and CVD mortality decreased by approximately 24% (HR 0.76, 95% CI 0.69, 0.84) and 25% (HR 0.75, 95% CI 0.60, 0.96) with the increase in HGI. Conversely, in the right of the inflection point, an increase of 1 unit in the HGI was linked with a 17% (HR 1.17, 95% CI 1.07, 1.27) and 31% (HR 1.31, 95% CI 1.15, 1.49) increase in all-cause and CVD mortality. Our study showed that HGI is an important tool for predicting the risk of all-cause mortality and CVD death in US adults and there is a U-shaped relationship between HGI and mortality.

We evaluated the effect of sodium-glucose cotransporter 2 (SGLT2) inhibition on prostate cancer by evidence triangulation. Using Mendelian randomization, we found that genetically proxied SGLT2 inhibition reduced the risk of overall (odds ratio = 0.56, 95% confidence interval [CI] = 0.38 to 0.82; 79,148 prostate cancer cases and 61,106 controls), advanced, and early-onset prostate cancer. Using electronic healthcare data (nSGLT2i = 24,155; nDPP4i = 24,155), we found that the use of SGLT2 inhibitors was associated with a 23% reduced risk of prostate cancer (hazard ratio = 0.77, 95% CI = 0.61 to 0.99) in men with diabetes. Using data from two prospective cohorts (n4C = 57,779; nUK_Biobank = 165,430), we found little evidence to support the association of HbA1c with prostate cancer, implying a non-glycemic effect of SGLT2 inhibition on prostate cancer. In summary, this study provides multiple layers of evidence to support the beneficial effect of SGLT2 inhibition on reducing prostate cancer risk. Future trials are warranted to investigate whether SGLT2 inhibitors can be recommended for prostate cancer prevention.