Visit-to-visit fasting plasma glucose variability is associated with left ventricular adverse remodeling in diabetic patients with STEMI

Impact of acute glycemic variability on short-term outcomes in patients with ST-segment elevation myocardial infarction: a multicenter population-based study

BACKGROUND

Given the increasing attention to glycemic variability (GV) and its potential implications for cardiovascular outcomes. This study aimed to explore the impact of acute GV on short-term outcomes in Chinese patients with ST-segment elevation myocardial infarction (STEMI).

METHODS

This study enrolled 7510 consecutive patients diagnosed with acute STEMI from 274 centers in China. GV was assessed using the coefficient of variation of blood glucose levels. Patients were categorized into three groups according to GV tertiles (GV1, GV2, and GV3). The primary outcome was 30-day all-cause death, and the secondary outcome was major adverse cardiovascular events (MACEs). Cox regression analyses were conducted to determine the independent correlation between GV and the outcomes.

RESULTS

A total of 7136 patients with STEMI were included. During 30-days follow-up, there was a significant increase in the incidence of all-cause death and MACEs with higher GV tertiles. The 30-days mortality rates were 7.4% for GV1, 8.7% for GV2 and 9.4% for GV3 (p = 0.004), while the MACEs incidence rates was 11.3%, 13.8% and 15.8% for the GV1, GV2 and GV3 groups respectively (p < 0.001). High GV levels during hospitalization were significantly associated with an increased risk of 30-day all-cause mortality and MACEs. When analyzed as a continuous variable, GV was independently associated with a higher risk of all-cause mortality (hazard ratio [HR] 1.679, 95% confidence Interval [CI] 1.005-2.804) and MACEs (HR 2.064, 95% CI 1.386-3.074). Additionally, when analyzed as categorical variables, the GV3 group was found to predict an increased risk of MACEs, irrespective of the presence of diabetes mellitus (DM).

CONCLUSION

Our study findings indicate that a high GV during hospitalization was significantly associated with an increased risk of 30-day all-cause mortality and MACE in Chinese patients with STEMI. Moreover, acute GV emerged as an independent predictor of increased MACEs risk, regardless of DM status.

Visit-to-Visit Variability in Fasting Blood Glucose Predicts the New-Onset Heart Failure: Results From Two Large Chinese Cohorts

Previous studies have hypothesized an association between higher fasting blood glucose (FBG) and heart failure (HF). However, FBG values fluctuate continuously over time, the association between FBG variability and the risk of HF is uncertain. We investigated the relationship between visit-to-visit variability in FBG and the risk of new-onset HF. This cohort study used data from a prospective Kailuan cohort (recruited during 2006-2007) and a retrospective cohort of family medicine patients from Hong Kong (recruited during 2000-2003) were followed up until December 31st, 2016, and December 31st, 2019, respectively, for the outcome of incident HF. Four indexes of variability were used, including standard deviation (SD), coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV). Cox regression was used to identify HF. In total, 98,554 and 22,217 subjects without preexisting HF from the Kailuan and Hong Kong cohorts were analyzed, respectively, with 1218 cases of incident HF in the former and 4,041 in the latter. Subjects in the highest quartile of FBG-CV had the highest risk of incident HF in both cohorts (Kailuan: HR 1.245, 95% CI 1.055-1.470); Hong Kong: HR 1.362, 95%CI 1.145-1.620; compared with the lowest quartile). Similar results were observed when using FBG-ARV, FBG-VIM, and FBG-SD. Meta-analysis showed similar results (highest versus lowest quartile: HR 1.30, 95%CI 1.15-1.47, P < 0.0001). As observed from 2 large, geographically distinct Chinese cohorts, a higher FBG variability was independently associated with higher risk of incident HF.

Correlation Between Glycemic Variability and Diabetic Complications: A Narrative Review

Diabetes mellitus is a metabolic disorder with a complex etiology in which glycemic dynamics are disturbed and the body is unable to maintain the process of glucose homeostasis through the pancreas. Persistent symptoms of high blood glucose or low blood glucose may lead to diabetic complications, such as neuropathy, nephropathy, retinopathy, and cardiovascular diseases. Glycemic variability which can represent the presence of excessive glycemic excursions is an indicator for evaluating glucose homoeostasis. Limiting glycemic variability has gradually become an emerging therapeutic target in improve diabetes metabolism and prevent associated complications. This article reviews the progress of research on the various quantifiable parameters of glycemic variability and their relationships with vascular lesions and mechanisms.

Oscillating Glucose Induces the Increase in Inflammatory Stress through Ninjurin-1 Up-Regulation and Stimulation of Transport Proteins in Human Endothelial Cells

Clinical data implicate fluctuations of high levels of plasma glucose in cardiovascular diseases. Endothelial cells (EC) are the first cells of the vessel wall exposed to them. Our aim was to evaluate the effects of oscillating glucose (OG) on EC function and to decipher new molecular mechanisms involved. Cultured human ECs (EA.hy926 line and primary cells) were exposed to OG (5/25 mM alternatively at 3 h), constant HG (25 mM) or physiological concentration (5 mM, NG) for 72 h. Markers of inflammation (Ninj-1, MCP-1, RAGE, TNFR1, NF-kB, and p38 MAPK), oxidative stress (ROS, VPO1, and HO-1), and transendothelial transport proteins (SR-BI, caveolin-1, and VAMP-3) were assessed. Inhibitors of ROS (NAC), NF-kB (Bay 11-7085), and Ninj-1 silencing were used to identify the mechanisms of OG-induced EC dysfunction. The results revealed that OG determined an increased expression of Ninj-1, MCP-1, RAGE, TNFR1, SR-B1, and VAMP-3 andstimulated monocyte adhesion. All of these effects were induced bymechanisms involving ROS production or NF-kB activation. NINJ-1 silencing inhibited the upregulation of caveolin-1 and VAMP-3 induced by OG in EC. In conclusion, OG induces increased inflammatory stress, ROS production, and NF-kB activation and stimulates transendothelial transport. To this end, we propose a novel mechanism linking Ninj-1 up-regulation to increased expression of transendothelial transport proteins.

HbA1c level is associated with the development of heart failure with recovered ejection fraction in hospitalized heart failure patients with type 2 diabetes

BACKGROUND

Due to advances in medical treatments, a substantial proportion of heart failure (HF) patients with reduced left ventricular ejection fraction (EF, HFrEF) have experienced partial or complete recovery of EF, termed HFrecEF, and markedly improved clinical outcomes. In the present study, we sought to investigate the relationship between glycemic control and the incidence of HFrecEF in hospitalized HFrEF patients with type 2 diabetes mellitus (T2DM).

METHODS

A total of 463 hospitalized T2DM patients with HFrEF were consecutively enrolled. Follow-up echocardiogram was performed after around 12 months. Patients who had an absolute EF improvement ≥10% and a second EF > 40% were classified into HFrecEF, and those who did not meet these criteria were defined as persistent HFrEF.

RESULTS

During the 12-month follow-up, 44.5% of T2DM patients developed HFrecEF. Patients with HFrecEF had significantly lower HbA1c level than those with persistent HFrEF (6.5% [IQR 5.8% ∼ 7.2%] vs. 6.7% [IQR 6.1% ∼ 7.8%], P = 0.003), especially in HF of an ischemic etiology. HbA1c levels were inversely correlated with changes in EF during follow-up. After multivariate adjustment, every 1% increase in HbA1c conferred a 17.4% (OR: 0.826 [95% CI 0.701-0.968]) lower likelihood of HFrecEF. Compared to patients with good glycemic control (HbA1c ≤ 6.2%), those with poor glycemic control (HbA1c > 7.1%) had a 52.0% (OR: 0.480 [95% CI 0.281-0.811] decreased likelihood of HFrecEF.

CONCLUSIONS

This study demonstrates that uncontrolled HbA1c level is associated with compromised development of HFrecEF in T2DM patients with HF, especially in those with an ischemic etiology.

Elevation of hemoglobin A1c increases the risk of decline in left ventricular systolic function among patients with coronary artery disease

AIMS

The aim of this study was to investigate the association of HbA1c and left ventricular (LV) systolic function among patients with coronary artery disease (CAD).

METHODS

CAD patients from the Cardiorenal ImprovemeNt II (CIN-II, NCT05050877) registry were included in the study. They were separated into four groups based on HbA1c levels (Q1: HbA1c<5.7%; Q2: 5.7% ≤ HbA1c < 6.1%; Q3: 6.1% ≤ HbA1c < 6.9%; Q4: HbA1c ≥ 6.9%). The endpoint was decline in LV systolic function, defined as an absolute decrease in LV ejection fraction (LVEF) ≥10% from baseline to follow-up with 3-12 months. The association of HbA1c and LVEF was assessed by logistics regression models.

RESULTS

CAD patients (n = 3,994) (age 62.9 ± 10.6 years; 22.2% female) were included in the final analysis. A decline in LV systolic function was recorded in 429 (11%) patients during follow-up. After fully adjusting for confounders, HbA1c was significantly associated with the high risk of decline in LV systolic function (OR 1.12 [95%CI 1.05-1.20] P = 0.001). By stratifying HbA1c as four groups, there is a significantly increased risk of decline in LV systolic function when HbA1c ≥6.1% (Q2, Q3 and Q4 vs Q1, with OR 1.22 [0.88-1.68] P = 0.235; OR 1.48 [1.07-2.05] P = 0.019; OR 1.60 [1.160-2.22] P = 0.004, respectively). Meanwhile, patients with decline in LV systolic function had a higher risk of cardiovascular death.

CONCLUSIONS

Elevated HbA1c is a predictor of decline in LV systolic function in CAD patients. Clinicians should be aware of the risk of decline in LV systolic function in CAD patients with elevated HbA1c, and take measures as soon as possible.

Day-to-day fasting plasma glucose variability on the short-term prognosis of ST-segment elevation myocardial infarction: A retrospective cohort study

BACKGROUND AND HYPOTHESIS

Glycemic variability in one fact that explain the differences in cardiovascular outcomes. The short-term fasting plasma glucose (FPG) variability may have an on major adverse cardiovascular events (MACE) in type 2 diabetes mellitus (T2DM) patients with ST-segment elevation myocardial infarction (STEMI).

METHODS

This study retrospectively analyzed T2DM patients who underwent emergent percutaneous coronary intervention (PCI) due to STEMI in Fuwai Hospital, Chinese Academy of Medical Sciences, Shenzhen, between January 2016 and March 2020. All patients underwent at least 5 FPG measurements during the perioperative period. FPG variability score (FPG-VS) was defined as the percentage of the number of FPG variations > 1 mmol/L between two adjacent FPG measurements. The Cox proportional-hazards model was used to estimate the relationship between FPG-VS and MACE. A validation set was utilized to further evaluate the prognostic value of FPG-VS in a standardized STEMI diabetic diet cohort following PCI intervention.

RESULTS

A total of 612 patients were included in the retrospective cohort study. In comparison to the minimum quintile, FPG-VS > 60% was associated with an increased risk of 30-day MACE. Moreover, compared to FPG-VS ≤ 20%, the FPG-VS > 80% group had a higher risk of MACE (odd ratio [OR] = 4.87, 95% confidence interval [CI]: 2.55-5.28), recurrent angina pectoris (OR = 5.43, 95% CI: 2.27-8.27), nonfatal myocardial infarction (OR = 5.00, 95% CI: 2.47-7.69), heart failure (OR = 3.70, 95% CI: 1.92-5.54), malignant arrhythmia (OR = 4.63, 95% CI: 1.12-6.25) and cardiac death (OR = 1.41, 95% CI: 0.17-1.97). Consistent results were obtained after adjustment for HbA1c, demonstrating the robustness of FPGFPG-VS. Moreover, the standard diet intervention group had a lower FPG-VS index as well as a lower incidence of MACE.

CONCLUSION

Higher FPG variability is associated with an increased risk of MACE within 30 days in diabetes patients receiving PCI for STEMI. A standardized diet may improve the prognosis of STEMI patients by reducing the FPG-VS.

Serum Uric Acid Is Associated with the Progression of Left Ventricular Diastolic Dysfunction in Apparently Healthy Subjects

Background

Left ventricular (LV) diastolic dysfunction (LVDD) is the defining feature of heart failure with preserved ejection fraction (HFpEF) and predicts subsequent incident heart failure (HF) and all-cause mortality. Mounting evidence reveals that cardiometabolic risk factors play critical roles in the development of LVDD. In this study, we sought to investigate the relation between serum uric acid (SUA) level and the progression of LVDD in apparently healthy patients.

Methods

A total of 1082 apparently healthy subjects without diagnosed cardiovascular disease and LVDD were consecutively enrolled. SUA levels were measured, and repeat echocardiography and tissue Doppler imaging (TDI) were performed at baseline and during 1-year follow-up.

Results

By dividing the study population based on quartiles of SUA, we found subjects in higher quartiles had greater increases in TDI-derived early diastolic velocity (e′) and E (peak LV filling velocity)/e′ ratios during 1-year follow-up. After multivariate adjustment, high SUA persisted to be an independent predictor for the subsequent worsening of LVDD (odds ratio: 1.351 [95% CI 1.125~1.625], per 100 μmol/L SUA). Subgroup analysis suggested that the association between SUA and LVDD development was more pronounced in subjects without other cardiometabolic risk factors involved. Factor analysis demonstrated that high SUA was the major cardiometabolic attribute in patients with LVDD progression.

Conclusion

Our findings suggest that high SUA is an independent cardiometabolic risk factor for the progression of LVDD in apparently healthy subjects.

Novel Strategies for Assessing Associations Between Selenium Biomarkers and Cardiometabolic Risk Factors: Concentration, Visit-to-Visit Variability, or Individual Mean? Evidence From a Repeated-Measures Study of Older Adults With High Selenium

Background and Aims

Previous studies have focused only on the cardiometabolic effects of selenium concentrations. We explored whether selenium levels and their visit-to-visit variability (VVV) and individual mean (IM) are independently associated with cardiometabolic risk factors.

Methods

A three-wave repeated-measures study of older adults with high selenium (n = 201) was conducted in Beijing from 2016 to 2018. Whole blood selenium and urinary selenium concentrations were measured. VVV and IM were used to profile the homeostasis of the selenium biomarkers. Four indicators, namely standard deviation, coefficient of variation, average real variability, and variability independent of the mean, were employed to characterize VVV. We considered 13 cardiometabolic factors: four lipid profile indicators, three blood pressure indices, glucose, uric acid, waistline, hipline, waist-hip ratio, and sex-specific metabolic syndrome score. Linear mixed-effects regression models with random intercepts for the participants were employed to explore the associations of the selenium concentrations, VVV, and IM with the cardiometabolic factors.

Results

The geometric mean whole blood and urinary selenium levels were 134.30 and 18.00 μg/L, respectively. Selenium concentrations were significantly associated with numerous cardiometabolic factors. Specifically, whole blood selenium was positively associated with total cholesterol [0.22, 95% confidence interval (CI): 0.12, 0.33], low-density lipoprotein cholesterol (LDL-C; 0.28, 95% CI: 0.13, 0.42), glucose (0.22, 95% CI: 0.10, 0.34), and uric acid (0.16, 95% CI: 0.04, 0.28). After adjustment for VVV, the IM of whole blood selenium was positively correlated with total cholesterol (0.002, 95% CI: 0.001, 0.004), triglycerides (0.007, 95% CI: 0.004, 0.011), and LDL-C (0.002, 95% CI: 0.000, 0.004). However, we did not observe any robust associations between the VVV of the selenium biomarkers and cardiometabolic risk factors after adjustment for IM.

Conclusion

Our findings suggest that selenium concentrations and their IMs are significantly associated with cardiometabolic risk factors among older adults with high selenium. Longer repeated-measures studies among the general population are required to validate our findings and elucidate the relevant underlying mechanisms.

Brown adipose tissue prevents glucose intolerance and cardiac remodeling in high-fat-fed mice after a mild myocardial infarction

BACKGROUND

Obesity increases the risk of developing impaired glucose tolerance (IGT) and type 2 diabetes (T2D) after myocardial infarction (MI). Brown adipose tissue (BAT) is important to combat obesity and T2D, and increasing BAT mass by transplantation improves glucose metabolism and cardiac function. The objective of this study was to determine if BAT had a protective effect on glucose tolerance and cardiac function in high-fat diet (HFD) fed mice subjected to a mild MI.

METHODS

Male C57BL/6 mice were fed a HFD for eight weeks and then divided into Sham (Sham-operated) and +BAT (mice receiving 0.1 g BAT into their visceral cavity). Sixteen weeks post-transplantation, mice were further subdivided into ±MI (Sham; Sham-MI; +BAT; +BAT-MI) and maintained on a HFD. Cardiac (echocardiography) and metabolic function (glucose and insulin tolerance tests, body composition and exercise tolerance) were assessed throughout 22 weeks post-MI. Quantitative PCR (qPCR) was performed to determine the expression of genes related to metabolic function of perigonadal adipose tissue (pgWAT), subcutaneous white adipose tissue (scWAT), liver, heart, tibialis anterior skeletal muscle (TA); and BAT.

RESULTS

+BAT prevented the increase in left ventricle mass (LVM) and exercise intolerance in response to MI. Similar to what is observed in humans, Sham-MI mice developed IGT post-MI, but this was negated in +BAT-MI mice. IGT was independent of changes in body composition. Genes involved in inflammation, insulin resistance, and metabolism were significantly altered in pgWAT, scWAT, and liver in Sham-MI mice compared to all other groups.

CONCLUSIONS

BAT transplantation prevents IGT, the increase in LVM, and exercise intolerance following MI. MI alters the expression of several metabolic-related genes in WAT and liver in Sham-MI mice, suggesting that these tissues may contribute to the impaired metabolic response. Increasing BAT may be an important intervention to prevent the development of IGT or T2D and cardiac remodeling in obese patients post-MI.

Associations of hypoglycemia, glycemic variability and risk of cardiac arrhythmias in insulin-treated patients with type 2 diabetes: a prospective, observational study

Background

Insulin-treated patients with type 2 diabetes (T2D) are at risk of hypoglycemia, which is associated with an increased risk of cardiovascular disease and mortality. Using a long-term monitoring approach, we investigated the association between episodes of hypoglycemia, glycemic variability and cardiac arrhythmias in a real-life setting.

Methods

Insulin-treated patients with T2D (N = 21, [mean ± SD] age 66.8 ± 9.6 years, BMI 30.1 ± 4.5 kg/m², HbA1c 6.8 ± 0.4% [51.0 ± 4.8 mmol/mol]) were included for a one-year observational study. Patients were monitored with continuous glucose monitoring ([mean ± SD] 118 ± 6 days) and an implantable cardiac monitor (ICM) during the study period.

Results

Time spend in hypoglycemia was higher during nighttime than during daytime ([median and interquartile range] 0.7% [0.7–2.7] vs. 0.4% [0.2–0.8]). The ICMs detected 724 episodes of potentially clinically significant arrhythmias in 12 (57%) participants, with atrial fibrillation and pauses accounting for 99% of the episodes. No association between hypoglycemia and cardiac arrhythmia was found during daytime. During nighttime, subject-specific hourly incidence of cardiac arrhythmias tended to increase with the occurrence of hypoglycemia (incident rate ratio [IRR] 1.70 [95% CI 0.36–8.01]) but only slightly with increasing time in hypoglycemia (IRR 1.04 [95% CI 0.89–1.22] per 5 min). Subject-specific incidence of cardiac arrhythmias during nighttime increased with increasing glycemic variability as estimated by coefficient of variation whereas it decreased during daytime (IRR 1.33 [95% CI 1.05–1.67] and IRR 0.77 [95% CI 0.59–0.99] per 5% absolute increase, respectively).

Conclusions

Cardiac arrhythmias were common in insulin-treated patients with T2D and were associated with glycemic variability, whereas arrhythmias were not strongly associated with hypoglycemia.

Trial registration: NCT03150030, ClinicalTrials.gov, registered May 11, 2017. https://clinicaltrials.gov/ct2/show/NCT03150030

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01425-0.

Optimal glucose, HbA1c, glucose-HbA1c ratio and stress-hyperglycaemia ratio cut-off values for predicting 1-year mortality in diabetic and non-diabetic acute myocardial infarction patients

Background

Stress-induced hyperglycaemia at time of hospital admission has been linked to worse prognosis following acute myocardial infarction (AMI). In addition to glucose, other glucose-related indices, such as HbA1c, glucose-HbA1c ratio (GHR), and stress-hyperglycaemia ratio (SHR) are potential predictors of clinical outcomes following AMI. However, the optimal blood glucose, HbA1c, GHR, and SHR cut-off values for predicting adverse outcomes post-AMI are unknown. As such, we determined the optimal blood glucose, HbA1c, GHR, and SHR cut-off values for predicting 1-year all cause mortality in diabetic and non-diabetic ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) patients.

Methods

We undertook a national, registry-based study of patients with AMI from January 2008 to December 2015. We determined the optimal blood glucose, HbA1c, GHR, and SHR cut-off values using the Youden’s formula for 1-year all-cause mortality. We subsequently analyzed the sensitivity, specificity, positive and negative predictive values of the cut-off values in the diabetic and non-diabetic subgroups, stratified by the type of AMI.

Results

There were 5841 STEMI and 4105 NSTEMI in the study. In STEMI patients, glucose, GHR, and SHR were independent predictors of 1-year all-cause mortality [glucose: OR 2.19 (95% CI 1.74–2.76); GHR: OR 2.28 (95% CI 1.80–2.89); SHR: OR 2.20 (95% CI 1.73–2.79)]. However, in NSTEMI patients, glucose and HbA1c were independently associated with 1-year all-cause mortality [glucose: OR 1.38 (95% CI 1.01–1.90); HbA1c: OR 2.11 (95% CI 1.15–3.88)]. In diabetic STEMI patients, SHR performed the best in terms of area-under-the-curve (AUC) analysis (glucose: AUC 63.3%, 95% CI 59.5–67.2; GHR 68.8% 95% CI 64.8–72.8; SHR: AUC 69.3%, 95% CI 65.4–73.2). However, in non-diabetic STEMI patients, glucose, GHR, and SHR performed equally well (glucose: AUC 72.0%, 95% CI 67.7–76.3; GHR 71.9% 95% CI 67.7–76.2; SHR: AUC 71.7%, 95% CI 67.4–76.0). In NSTEMI patients, glucose performed better than HbA1c for both diabetic and non-diabetic patients in AUC analysis (For diabetic, glucose: AUC 52.8%, 95% CI 48.1–57.6; HbA1c: AUC 42.5%, 95% CI 37.6–47. For non-diabetic, glucose: AUC 62.0%, 95% CI 54.1–70.0; HbA1c: AUC 51.1%, 95% CI 43.3–58.9). The optimal cut-off values for glucose, GHR, and SHR in STEMI patients were 15.0 mmol/L, 2.11, and 1.68 for diabetic and 10.6 mmol/L, 1.72, and 1.51 for non-diabetic patients respectively. For NSTEMI patients, the optimal glucose values were 10.7 mmol/L for diabetic and 8.1 mmol/L for non-diabetic patients.

Conclusions

SHR was the most consistent independent predictor of 1-year all-cause mortality in both diabetic and non-diabetic STEMI, whereas glucose was the best predictor in NSTEMI patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01395-3.

Comprehensive elaboration of glycemic variability in diabetic macrovascular and microvascular complications

Diabetes mellitus is the major risk factor for the development of macrovascular and microvascular complications. It is increasingly recognized that glycemic variability (GV), referring to oscillations in blood glucose levels and representing either short-term or long-term GV, is involved in the pathogenesis of diabetic complications and has emerged as a possible independent risk factor for them. In this review, we summarize the metrics and measurement of GV in clinical practice, as well as comprehensively elaborate the role and related mechanisms of GV in diabetic macrovascular and microvascular complications, aiming to provide the mechanism-based therapeutic strategies for clinicians to manage diabetes mellitus.

Bioinformatic Reconstruction and Analysis of Gene Networks Related to Glucose Variability in Diabetes and Its Complications

Glucose variability (GV) has been recognized recently as a promoter of complications and therapeutic targets in diabetes. The aim of this study was to reconstruct and analyze gene networks related to GV in diabetes and its complications. For network analysis, we used the ANDSystem that provides automatic network reconstruction and analysis based on text mining. The network of GV consisted of 37 genes/proteins associated with both hyperglycemia and hypoglycemia. Cardiovascular system, pancreas, adipose and muscle tissues, gastrointestinal tract, and kidney were recognized as the loci with the highest expression of GV-related genes. According to Gene Ontology enrichment analysis, these genes are associated with insulin secretion, glucose metabolism, glycogen biosynthesis, gluconeogenesis, MAPK and JAK-STAT cascades, protein kinase B signaling, cell proliferation, nitric oxide biosynthesis, etc. GV-related genes were found to occupy central positions in the networks of diabetes complications (cardiovascular disease, diabetic nephropathy, retinopathy, and neuropathy) and were associated with response to hypoxia. Gene prioritization analysis identified new gene candidates (THBS1, FN1, HSP90AA1, EGFR, MAPK1, STAT3, TP53, EGF, GSK3B, and PTEN) potentially involved in GV. The results expand the understanding of the molecular mechanisms of the GV phenomenon in diabetes and provide molecular markers and therapeutic targets for future research.