AESurv: autoencoder survival analysis for accurate early prediction of coronary heart disease.

Coronary heart disease (CHD) is one of the leading causes of mortality and morbidity in the United States. Accurate time-to-event CHD prediction models with high-dimensional DNA methylation and clinical features may assist with early prediction and intervention strategies. We developed a state-of-the-art deep learning autoencoder survival analysis model (AESurv) to effectively analyze high-dimensional blood DNA methylation features and traditional clinical risk factors by learning low-dimensional representation of participants for time-to-event CHD prediction. We demonstrated the utility of our model in two cohort studies: the Strong Heart Study cohort (SHS), a prospective cohort studying cardiovascular disease and its risk factors among American Indians adults; the Women's Health Initiative (WHI), a prospective cohort study including randomized clinical trials and observational study to improve postmenopausal women's health with one of the main focuses on cardiovascular disease. Our AESurv model effectively learned participant representations in low-dimensional latent space and achieved better model performance (concordance index-C index of 0.864 ± 0.009 and time-to-event mean area under the receiver operating characteristic curve-AUROC of 0.905 ± 0.009) than other survival analysis models (Cox proportional hazard, Cox proportional hazard deep neural network survival analysis, random survival forest, and gradient boosting survival analysis models) in the SHS. We further validated the AESurv model in WHI and also achieved the best model performance. The AESurv model can be used for accurate CHD prediction and assist health care professionals and patients to perform early intervention strategies. We suggest using AESurv model for future time-to-event CHD prediction based on DNA methylation features.

Established and Emerging Nucleic Acid Therapies for Familial Hypercholesterolemia.

Familial hypercholesterolemia (FH) is a genetic disease that leads to elevated low-density lipoprotein cholesterol levels and risk of coronary heart disease. Current therapeutic options for FH remain relatively limited and only partially effective in both lowering low-density lipoprotein cholesterol and modifying coronary heart disease risk. The unique characteristics of nucleic acid therapies to target the underlying cause of the disease can offer solutions unachievable with conventional medications. DNA- and RNA-based therapeutics have the potential to transform the care of patients with FH. Recent advances are overcoming obstacles to clinical translation of nucleic acid-based medications, including greater stability of the formulations as well as site-specific delivery, making gene-based therapy for FH an alternative approach for treatment of FH.

2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines.

AIM: The "2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation" provides recommendations to guide clinicians in the treatment of patients with atrial fibrillation. METHODS: A comprehensive literature search was conducted from May 12, 2022, to November 3, 2022, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. Additional relevant studies, published through November 2022, during the guideline writing process, were also considered by the writing committee and added to the evidence tables, where appropriate. STRUCTURE: Atrial fibrillation is the most sustained common arrhythmia, and its incidence and prevalence are increasing in the United States and globally. Recommendations from the "2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" and the "2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" have been updated with new evidence to guide clinicians. In addition, new recommendations addressing atrial fibrillation and thromboembolic risk assessment, anticoagulation, left atrial appendage occlusion, atrial fibrillation catheter or surgical ablation, and risk factor modification and atrial fibrillation prevention have been developed.

Physical Activity Over the Lifecourse and Cardiovascular Disease.

Despite improvements in cardiovascular care in recent decades, cardiovascular disease (CVD) remains a leading cause of death worldwide. At its core, CVD is a largely preventable disease with diligent risk factor management and early detection. As highlighted in the American Heart Association's Life's Essential 8, physical activity plays a central role in CVD prevention at an individual and population level. Despite pervasive knowledge of the numerous cardiovascular and noncardiovascular health benefits of physical activity, physical activity has steadily decreased over time and unfavorable changes in physical activity occur throughout people's lives. Here, we use a lifecourse framework to examine the evidence reporting on the association of physical activity with CVD. From in utero to older adults, we review and discuss the evidence detailing how physical activity may prevent incident CVD and mitigate CVD-related morbidity and death across all life stages.

Variation in secondary prevention of coronary heart disease: the INTERASPIRE study.

BACKGROUND AND AIMS: INTERASPIRE is an international study of coronary heart disease (CHD) patients, designed to measure if guideline standards for secondary prevention and cardiac rehabilitation are being achieved in a timely manner. METHODS: Between 2020 and 2023, adults hospitalized in the preceding 6-24 months with incident or recurrent CHD were sampled in 14 countries from all 6 World Health Organization regions and invited for a standardized interview and examination. Direct age and sex standardization was used for country-level prevalence estimation. RESULTS: Overall, 4548 (21.1% female) CHD patients were interviewed a median of 1.05 (interquartile range .76-1.45) years after index hospitalization. Among all participants, 24.6% were obese (40.7% centrally). Only 38.6% achieved a blood pressure (BP) < 130/80 mmHg and 16.6% a LDL cholesterol (LDL-C) of <1.4 mmol/L. Of those smoking at hospitalization, 48% persisted at interview. Of those with known diabetes, 55.2% achieved glycated haemoglobin (HbA1c) of <7.0%. A further 9.8% had undetected diabetes and 26.9% impaired glucose tolerance. Females were less likely to achieve the targets: BP (females 36.8%, males 38.9%), LDL-C (females 12.0%, males 17.9%), and HbA1c in diabetes (females 47.7%, males 57.5%). Overall, just 9.0% (inter-country range 3.8%-20.0%) reported attending cardiac rehabilitation and 1.0% (inter-country range .0%-2.4%) achieved the study definition of optimal guideline adherence. CONCLUSIONS: INTERASPIRE demonstrates inadequate and heterogeneous international implementation of guideline standards for secondary prevention in the first year after CHD hospitalization, with geographic and sex disparity. Investment aimed at reducing between-country and between-individual variability in secondary prevention will promote equity in global efforts to reduce the burden of CHD.

C-reactive protein modifies lipoprotein(a)-related risk for coronary heart disease: the BiomarCaRE project.

BACKGROUND AND AIMS: Recent investigations have suggested an interdependence of lipoprotein(a) [Lp(a)]-related risk for cardiovascular disease with background inflammatory burden. The aim the present analysis was to investigate whether high-sensitive C-reactive protein (hsCRP) modulates the association between Lp(a) and coronary heart disease (CHD) in the general population. METHODS: Data from 71 678 participants from 8 European prospective population-based cohort studies were used (65 661 without/6017 with established CHD at baseline; median follow-up 9.8/13.8 years, respectively). Fine and Gray competing risk-adjusted models were calculated according to accompanying hsCRP concentration (<2 and ≥2 mg/L). RESULTS: Among CHD-free individuals, increased Lp(a) levels were associated with incident CHD irrespective of hsCRP concentration: fully adjusted sub-distribution hazard ratios [sHRs (95% confidence interval)] for the highest vs. lowest fifth of Lp(a) distribution were 1.45 (1.23-1.72) and 1.48 (1.23-1.78) for a hsCRP group of <2 and ≥2 mg/L, respectively, with no interaction found between these two biomarkers on CHD risk (Pinteraction = 0.82). In those with established CHD, similar associations were seen only among individuals with hsCRP ≥ 2 mg/L [1.34 (1.03-1.76)], whereas among participants with a hsCRP concentration <2 mg/L, there was no clear association between Lp(a) and future CHD events [1.29 (0.98-1.71)] (highest vs. lowest fifth, fully adjusted models; Pinteraction = 0.024). CONCLUSIONS: While among CHD-free individuals Lp(a) was significantly associated with incident CHD regardless of hsCRP, in participants with CHD at baseline, Lp(a) was related to recurrent CHD events only in those with residual inflammatory risk. These findings might guide adequate selection of high-risk patients for forthcoming Lp(a)-targeting compounds.

SGK1 contributes to ferroptosis in coronary heart disease through the NEDD4L/NF-κB pathway.

The prevalence of coronary heart disease (CHD) has increased significantly with the aging population worldwide. It is unclear whether ferroptosis occurs during CHD. Hence, we aimed to investigate the potential mechanisms associated with ferroptosis in CHD. Bioinformatics was used to characterize differentially expressed genes (DEGs) in CHD-related datasets (GSE21610 and GSE66360). There were 76 and 689 DEGs in the GSE21610 and GSE66360, respectively, and they predominantly associated with immune and inflammatory responses. DDX3Y, EIF1AY, KDM5D, RPS4Y1, SGK1, USP9Y, and NSG1 were intersecting DEGs of GSE21610 and GSE66360. Their expression pattern in circulating endothelial cells (ECs) derived from healthy individuals and CHD patients are consistent with the results of bioinformatics analysis, especially SGK1. In vitro, SGK1 knockdown alleviated the Erastin-induced downregulation of SLC7A11, GPX4, GSH, and GSSG, as well as the upregulation of lipid peroxidation, Fe accumulation, and mitochondrial damage in mouse aortic ECs (MAECs). Notably, SGK1 may interact with NEDD4L according to the String database. Moreover, SGK1 promoted NEDD4L and p-P65 expression in MAECs. Interestingly, the effect of SGK1 knockdown on ferroptosis in MAECs was rescued by overexpression of NEDD4L or PMA (NF-κB pathway activator). In vivo, SGK1 knockdown facilitated the recovery of body weight, blood lipids, and aortic tissue structure in CHD animal models. Furthermore, SGK1 knockdown alleviated Fe accumulation in the aorta and inactivated the NEDD4L-NF-κB pathway. In conclusion, SGK1 contributes to EC ferroptosis by regulating the NEDD4L-NF-κB pathway. SGK1 could be recognized as a therapeutic target related to ferroptosis in CHD.

Polymorphism of IL-12/IL-23 axis is associated with coronary heart disease.

IL12B encodes the shared p40 subunit (IL-12p40) of IL-12 and IL-23, which have diverse immune functions and are closely related to the occurrence and development of atherosclerosis (AS). However, the exact role of IL12B in coronary heart disease (CHD) was still unknown. A case-control association analysis was performed between five single nucleotide polymorphisms (SNPs) of IL12B (rs1003199, rs3212219, rs2569254, rs2853694 and rs3212227) and CHD in Chinese Han population (1824 patients with CHD vs. 2784 controls). Logistic regression analyses were used to study the relationships between SNPs and CHD, while multiple linear regression analyses were used to test the association between the SNP and the severity of CHD. In addition, the plasma IL12B concentration of CHD patients were detected by ELISA. We detected a significant association between one of the SNPs, rs2853694-G and CHD (padj = 2.075 × 10-5 , OR, 0.773 [95% CI, 0.686-0.870]). Stratified analysis showed that rs2853694 was associated with CHD in both male and female populations and was significantly associated with both early- and late-onset CHD. In addition, rs2853694 is also related to the different types of CHD including clinical-CHD and anatomical-CHD. Moreover, there are significant differences in serum IL12B concentrations between rs2853694-TT carriers and rs2853694-GT carriers in CHD patients (p = 0.010). A common variant of IL12B was found significantly associated with CHD and its subgroups. As a shared subunit of IL-12 and IL-23, IL-12p40 may play a key role in IL-12/IL-23 axis mediated AS, which is expected to be an effective therapeutic target for CHD.

A large study of metabolomics reveals common and distinct metabolic biomarkers for type 2 diabetes, coronary heart disease, and stroke.

We aimed at examining the shared and unique associations of metabolites with multiple cardiometabolic diseases (CMD), i.e. type 2 diabetes (T2D), coronary heart disease (CHD) and stroke. In this study, a total of 168 plasma metabolites were measured by targeted high-throughput nuclear magnetic resonance spectroscopy among 98,162 participants free of T2D, CHD, and stroke at baseline. Cox proportional hazard models estimated hazard ratios for one SD increase in metabolite concentration levels, and false discovery rate (at 10%) was used to correct for multiple comparisons. Over 12.1 years of follow-up on average, 3,463 T2D, 6,186 CHD, and 1,892 stroke events were recorded. Most lipoprotein metabolites were associated with risks of T2D and CHD but not with the risk of stroke, with stronger associations for T2D than for CHD. Phospholipids within intermediate-density lipoprotein or large low-density lipoprotein particles showed positive associations with CHD and inverse associations with T2D. Metabolites indicating very small very low-density lipoprotein, histidine, creatinine, albumin, and glycoprotein acetyls were associated with risks of all three conditions. This large-scale metabolomics study revealed common and distinct metabolic biomarkers for T2D, CHD and stroke, providing instrumental information to possibly implement precision medicine for preventing and treating these conditions.

Parental genetically predicted liability for coronary heart disease and risk of adverse pregnancy outcomes: a cohort study.

BACKGROUND: Adverse pregnancy outcomes (APO) may unmask or exacerbate a woman's underlying risk for coronary heart disease (CHD). We estimated associations of maternal and paternal genetically predicted liability for CHD with lifelong risk of APOs. We hypothesized that associations would be found for women, but not their male partners (negative controls). METHODS: We studied up to 83,969‬ women (and up to 55,568‬ male partners) from the Norwegian Mother, Father and Child Cohort Study or the Trøndelag Health Study with genotyping data and lifetime history of any APO in their pregnancies (1967-2019) in the Medical Birth Registry of Norway (miscarriage, stillbirth, hypertensive disorders of pregnancy, gestational diabetes, small for gestational age, large for gestational age, and spontaneous preterm birth). Maternal and paternal genetic risk scores (GRS) for CHD were generated using 148 gene variants (p-value < 5 × 10-8, not in linkage disequilibrium). Associations between GRS for CHD and each APO were determined using logistic regression, adjusting for genomic principal components, in each cohort separately, and combined using fixed effects meta-analysis. RESULTS: One standard deviation higher GRS for CHD in women was related to increased risk of any hypertensive disorders of pregnancy (odds ratio [OR] 1.08, 95% confidence interval [CI] 1.05-1.10), pre-eclampsia (OR 1.08, 95% CI 1.05-1.11), and small for gestational age (OR 1.04, 95% CI 1.01-1.06). Imprecise associations with lower odds of large for gestational age (OR 0.98, 95% CI 0.96-1.00) and higher odds of stillbirth (OR 1.04, 95% CI 0.98-1.11) were suggested. These findings remained consistent after adjusting for number of total pregnancies and the male partners' GRS and restricting analyses to stable couples. Associations for other APOs were close to the null. There was weak evidence of an association of paternal genetically predicted liability for CHD with spontaneous preterm birth in female partners (OR 1.02, 95% CI 0.99-1.05), but not with other APOs. CONCLUSIONS: Hypertensive disorders of pregnancy, small for gestational age, and stillbirth may unmask women with a genetically predicted propensity for CHD. The association of paternal genetically predicted CHD risk with spontaneous preterm birth in female partners needs further exploration.

Very short sleep duration reveals a proteomic fingerprint that is selectively associated with incident diabetes mellitus but not with incident coronary heart disease: a cohort study.

BACKGROUND: The molecular pathways linking short and long sleep duration with incident diabetes mellitus (iDM) and incident coronary heart disease (iCHD) are not known. We aimed to identify circulating protein patterns associated with sleep duration and test their impact on incident cardiometabolic disease. METHODS: We assessed sleep duration and measured 78 plasma proteins among 3336 participants aged 46-68 years, free from DM and CHD at baseline, and identified cases of iDM and iCHD using national registers. Incident events occurring in the first 3 years of follow-up were excluded from analyses. Tenfold cross-fit partialing-out lasso logistic regression adjusted for age and sex was used to identify proteins that significantly predicted sleep duration quintiles when compared with the referent quintile 3 (Q3). Predictive proteins were weighted and combined into proteomic scores (PS) for sleep duration Q1, Q2, Q4, and Q5. Combinations of PS were included in a linear regression model to identify the best predictors of habitual sleep duration. Cox proportional hazards regression models with sleep duration quintiles and sleep-predictive PS as the main exposures were related to iDM and iCHD after adjustment for known covariates. RESULTS: Sixteen unique proteomic markers, predominantly reflecting inflammation and apoptosis, predicted sleep duration quintiles. The combination of PSQ1 and PSQ5 best predicted sleep duration. Mean follow-up times for iDM (n = 522) and iCHD (n = 411) were 21.8 and 22.4 years, respectively. Compared with sleep duration Q3, all sleep duration quintiles were positively and significantly associated with iDM. Only sleep duration Q1 was positively and significantly associated with iCHD. Inclusion of PSQ1 and PSQ5 abrogated the association between sleep duration Q1 and iDM. Moreover, PSQ1 was significantly associated with iDM (HR = 1.27, 95% CI: 1.06-1.53). PSQ1 and PSQ5 were not associated with iCHD and did not markedly attenuate the association between sleep duration Q1 with iCHD. CONCLUSIONS: We here identify plasma proteomic fingerprints of sleep duration and suggest that PSQ1 could explain the association between very short sleep duration and incident DM.

Replacing device-measured sedentary time with physical activity is associated with lower risk of coronary heart disease regardless of genetic risk.

BACKGROUND: Excess sedentary time (ST) is recognized as an important modifiable risk factor for coronary heart disease (CHD). However, whether the associations of genetic susceptibility with CHD incidence can be modified by replacing wearable-device-measured ST with physical activity (PA) is unknown. OBJECTIVES: To examine the associations of wearable-device-measured ST replaced by PA with incident CHD across strata of genetic susceptibility. METHODS: This study included 77,500 White British (57% female) with valid wrist-worn accelerometry and without prevalent CHD/stroke from UK Biobank. Genetic susceptibility to CHD was quantified through weighted polygenic risk scores for CHD based on 300 single-nucleotide polymorphisms. Wrist-worn accelerometer data were used to derive ST, light PA, and moderate-to-vigorous PA (MVPA). RESULTS: Reallocation of 60 min/day of ST into the same amount of MVPA was associated with approximately 9% lower relative risk of CHD for all participants and across strata of genetic risk: replacement of 1 min/day of ST associated with <1% lower relative risk of CHD. No evidence of interaction (p: 0.784) was found between genetic risk and ST for CHD risk. Reallocating 60 min/day of ST into the same MVPA time was associated with greater absolute CHD risk reductions at high genetic risk (0.27%) versus low genetic risk (0.15%). CONCLUSIONS: Replacing any amount of ST with an equal amount of MVPA time is associated with a lower relative risk of CHD, irrespective of genetic susceptibility to CHD. Reductions in CHD absolute risk for replacing ST with MVPA are greater at high genetic risk versus low genetic risk.

Role of inflammatory signaling pathways involving the CD40-CD40L-TRAF cascade in diabetes and hypertension-insights from animal and human studies.

CD40L-CD40-TRAF signaling plays a role in atherosclerosis progression and affects the pathogenesis of coronary heart disease (CHD). We tested the hypothesis that CD40L-CD40-TRAF signaling is a potential therapeutic target in hyperlipidemia, diabetes, and hypertension. In mouse models of hyperlipidemia plus diabetes (db/db mice) or hypertension (1 mg/kg/d angiotensin-II for 7 days), TRAF6 inhibitor treatment (2.5 mg/kg/d for 7 or 14 days) normalized markers of oxidative stress and inflammation. As diabetes and hypertension are important comorbidities aggravating CHD, we explored whether the CD40L-CD40-TRAF signaling cascade and their associated inflammatory pathways are expressed in CHD patients suffering from comorbidities. Therefore, we analyzed vascular bypass material (aorta or internal mammary artery) and plasma from patients with CHD with diabetes and/or hypertension. Our Olink targeted plasma proteomic analysis using the IMMUNO-ONCOLOGY panel revealed a pattern of step-wise increase for 13/92 markers of low-grade inflammation with significant changes. CD40L or CD40 significantly correlated with 38 or 56 other inflammatory targets. In addition, specific gene clusters that correlate with the comorbidities were identified in isolated aortic mRNA of CHD patients through RNA-sequencing. These signaling clusters comprised CD40L-CD40-TRAF, immune system, hemostasis, muscle contraction, metabolism of lipids, developmental biology, and apoptosis. Finally, immunological analysis revealed key markers correlated with comorbidities in CHD patients, such as CD40L, NOX2, CD68, and 3-nitrotyrosine. These data indicate that comorbidities increase inflammatory pathways in CHD, and targeting these pathways will be beneficial in reducing cardiovascular events in CHD patients with comorbidities.

​Comprehensive mendelian randomization analysis of plasma proteomics to identify new therapeutic targets for the treatment of coronary heart disease and myocardial infarction.

BACKGROUND: Ischemic heart disease is one of the leading causes of mortality worldwide, and thus calls for development of more effective therapeutic strategies. This study aimed to identify potential therapeutic targets for coronary heart disease (CHD) and myocardial infarction (MI) by investigating the causal relationship between plasma proteins and these conditions. METHODS: A two-sample Mendelian randomization (MR) study was performed to evaluate more than 1600 plasma proteins for their causal associations with CHD and MI. The MR findings were further confirmed through Bayesian colocalization, Summary-data-based Mendelian Randomization (SMR), and Transcriptome-Wide Association Studies (TWAS) analyses. Further analyses, including enrichment analysis, single-cell analysis, MR analysis of cardiovascular risk factors, phenome-wide Mendelian Randomization (Phe-MR), and protein-protein interaction (PPI) network construction were conducted to verify the roles of selected causal proteins. RESULTS: Thirteen proteins were causally associated with CHD, seven of which were also causal for MI. Among them, FES and PCSK9 were causal proteins for both diseases as determined by several analytical methods. PCSK9 was a risk factor of CHD (OR = 1.25, 95% CI: 1.13-1.38, P = 7.47E-06) and MI (OR = 1.36, 95% CI: 1.21-1.54, P = 2.30E-07), whereas FES was protective against CHD (OR = 0.68, 95% CI: 0.59-0.79, P = 6.40E-07) and MI (OR = 0.65, 95% CI: 0.54-0.77, P = 5.38E-07). Further validation through enrichment and single-cell analysis confirmed the causal effects of these proteins. Moreover, MR analysis of cardiovascular risk factors, Phe-MR, and PPI network provided insights into the potential drug development based on the proteins. CONCLUSIONS: This study investigated the causal pathways associated with CHD and MI, highlighting the protective and risk roles of FES and PCSK9, respectively. FES. Specifically, the results showed that these proteins are promising therapeutic targets for future drug development.

Association between different insulin resistance surrogates and all-cause mortality in patients with coronary heart disease and hypertension: NHANES longitudinal cohort study.

BACKGROUND: Studies on the relationship between insulin resistance (IR) surrogates and long-term all-cause mortality in patients with coronary heart disease (CHD) and hypertension are lacking. This study aimed to explore the relationship between different IR surrogates and all-cause mortality and identify valuable predictors of survival status in this population. METHODS: The data came from the National Health and Nutrition Examination Survey (NHANES 2001-2018) and National Death Index (NDI). Multivariate Cox regression and restricted cubic splines (RCS) were performed to evaluate the relationship between homeostatic model assessment of IR (HOMA-IR), triglyceride glucose index (TyG index), triglyceride glucose-body mass index (TyG-BMI index) and all-cause mortality. The recursive algorithm was conducted to calculate inflection points when segmenting effects were found. Then, segmented Kaplan-Meier analysis, LogRank tests, and multivariable Cox regression were carried out. Receiver operating characteristic (ROC) and calibration curves were drawn to evaluate the differentiation and accuracy of IR surrogates in predicting the all-cause mortality. Stratified analysis and interaction tests were conducted according to age, gender, diabetes, cancer, hypoglycemic and lipid-lowering drug use. RESULTS: 1126 participants were included in the study. During the median follow-up of 76 months, 455 participants died. RCS showed that HOMA-IR had a segmented effect on all-cause mortality. 3.59 was a statistically significant inflection point. When the HOMA-IR was less than 3.59, it was negatively associated with all-cause mortality [HR = 0.87,95%CI (0.78, 0.97)]. Conversely, when the HOMA-IR was greater than 3.59, it was positively associated with all-cause mortality [HR = 1.03,95%CI (1.00, 1.05)]. ROC and calibration curves indicated that HOMA-IR was a reliable predictor of survival status (area under curve = 0,812). No interactions between HOMA-IR and stratified variables were found. CONCLUSION: The relationship between HOMA-IR and all-cause mortality was U-shaped in patients with CHD and hypertension. HOMA-IR was a reliable predictor of all-cause mortality in this population.

Risk analysis of the association between different hemoglobin glycation index and poor prognosis in critical patients with coronary heart disease-A study based on the MIMIC-IV database.

BACKGROUND: The hemoglobin glycation index (HGI) is the difference between the observed and predicted values of glycosylated hemoglobin (HbA1c), which is closely associated with a variety of poor prognoses. However, there are still no studies on the correlation between HGI and poor prognosis in patients with critical coronary artery disease. The purpose of this study was to analyze the correlation between HGI and all-cause mortality in patients with critical coronary artery disease using the MIMIC-IV database. METHODS: The HGI was calculated by constructing a linear regression equation between HbA1c and fasting plasma glucose (FPG). A Kaplan‒Meier survival analysis model was constructed based on the HGI quartiles to clarify the differences in all-cause mortality rates between groups, and the log-rank test was used to assess the differences between groups. The hazard ratio (HR) of HGI as a risk factor for outcome events was assessed using the Cox proportional risk model and restricted cubic spline (RCS), with the Q2 group serving as the reference group. RESULTS: A total of 5260 patients were included in this study. The 30-day mortality rate of the patients was 4.94% and the mortality rate within 365 days was 13.12%. A low HGI was significantly associated with 30-day mortality (HR, 1.96; 95% CI, (1.38, 2.78); P < 0.001) and 365-day mortality (HR, 1.48; 95% CI, (1.19, 1.85); P < 0.001) in patients with critical coronary artery disease in the completely adjusted Cox proportional risk model. In addition, high levels of HGI were associated with 365-day mortality (HR, 1.31; 95% CI, (1.02, 1.69); P < 0.05). RCS analysis revealed a U-shaped relationship between HGI and outcome events. According to the stratified analysis, the interaction test revealed that the correlation between HGI and outcome events remained stable. CONCLUSION: There was a significant correlation between HGI and all-cause mortality in patients with critical coronary artery disease, particularly in those with low HGI. HGI can be used as a potential indicator for assessing the short- and long-term risk of mortality in such patients.

Association of plasma proteomics with incident coronary heart disease in individuals with and without type 2 diabetes: results from the population-based KORA study.

BACKGROUND: Coronary heart disease (CHD) is a major global health concern, especially among individuals with type 2 diabetes (T2D). Given the crucial role of proteins in various biological processes, this study aimed to elucidate the aetiological role and predictive performance of protein biomarkers on incident CHD in individuals with and without T2D. METHODS: The discovery cohort included 1492 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 study with 147 incident CHD cases (45 vs. 102 cases in the group with T2D and without T2D, respectively) during 15.6 years of follow-up. The validation cohort included 888 participants from the KORA-Age1 study with 70 incident CHD cases (19 vs. 51 cases in the group with T2D and without T2D, respectively) during 6.9 years of follow-up. We measured 233 plasma proteins related to cardiovascular disease and inflammation using proximity extension assay technology. Associations of proteins with incident CHD were assessed using Cox regression and Mendelian randomization (MR) analysis. Predictive models were developed using priority-Lasso and were evaluated on top of Framingham risk score variables using the C-index, category-free net reclassification index (cfNRI), and relative integrated discrimination improvement (IDI). RESULTS: We identified two proteins associated with incident CHD in individuals with and 29 in those without baseline T2D, respectively. Six of these proteins are novel candidates for incident CHD. MR suggested a potential causal role for hepatocyte growth factor in CHD development. The developed four-protein-enriched model for individuals with baseline T2D (ΔC-index: 0.017; cfNRI: 0.253; IDI: 0.051) and the 12-protein-enriched model for individuals without baseline T2D (ΔC-index: 0.054; cfNRI: 0.462; IDI: 0.024) consistently improved CHD prediction in the discovery cohort, while in the validation cohort, significant improvements were only observed for selected performance measures (with T2D: cfNRI: 0.633; without T2D: ΔC-index: 0.038; cfNRI: 0.465). CONCLUSIONS: This study identified novel protein biomarkers associated with incident CHD in individuals with and without T2D and reaffirmed previously reported protein candidates. These findings enhance our understanding of CHD pathophysiology and provide potential targets for prevention and treatment.

The relationship between triglyceride-glucose index and prospective key clinical outcomes in patients hospitalised for coronary artery disease.

BACKGROUND: The triglyceride-glucose (TyG) index is regarded as a dependable alternative for assessing insulin resistance (IR), given its simplicity, cost-effectiveness, and strong correlation with IR. The relationship between the TyG index and adverse outcomes in patients with coronary heart disease (CHD) is not well established. This study examines the association of the TyG index with long-term adverse outcomes in hospitalized CHD patients. METHODS: In this single-center prospective cohort study, 3321 patients hospitalized with CHD were included. Multivariate Cox regression models were employed to assess the associations between the TyG index and the incidence of all-cause mortality and major adverse cardiovascular events (MACEs). To examine potential nonlinear associations, restricted cubic splines and threshold analysis were utilized. RESULTS: During a follow-up period of 9.4 years, 759 patients (22.9%) succumbed to mortality, while 1291 (38.9%) experienced MACEs. Threshold analysis demonstrated a significant "U"-shaped nonlinear relationship with MACEs, with different hazard ratios observed below and above a TyG index of 8.62 (below: HR 0.71, 95% CI 0.50-0.99; above: HR 1.28, 95% CI 1.10-1.48). Notably, an increased risk of all-cause mortality was observed only when the TyG index exceeded 8.77 (HR 1.53, 95% CI 1.19-1.96). CONCLUSIONS: This study reveals a nonlinear association between the TyG index and both all-cause mortality and MACEs in hospitalized CHD patients with CHD. Assessing the TyG index, particularly focusing on individuals with extremely low or high TyG index values, may enhance risk stratification for adverse outcomes in this patient population.

Oral-gut microbial transmission promotes diabetic coronary heart disease.

BACKGROUND: Diabetes is a predominant driver of coronary artery disease worldwide. This study aims to unravel the distinct characteristics of oral and gut microbiota in diabetic coronary heart disease (DCHD). Simultaneously, we aim to establish a causal link between the diabetes-driven oral-gut microbiota axis and increased susceptibility to diabetic myocardial ischemia-reperfusion injury (MIRI). METHODS: We comprehensively investigated the microbial landscape in the oral and gut microbiota in DCHD using a discovery cohort (n = 183) and a validation chohort (n = 68). Systematically obtained oral (tongue-coating) and fecal specimens were subjected to metagenomic sequencing and qPCR analysis, respectively, to holistically characterize the microbial consortia. Next, we induced diabetic MIRI by administering streptozotocin to C57BL/6 mice and subsequently investigated the potential mechanisms of the oral-gut microbiota axis through antibiotic pre-treatment followed by gavage with specific bacterial strains (Fusobacterium nucleatum or fecal microbiota from DCHD patients) to C57BL/6 mice. RESULTS: Specific microbial signatures such as oral Fusobacterium nucleatum and gut Lactobacillus, Eubacterium, and Roseburia faecis, were identified as potential microbial biomarkers in DCHD. We further validated that oral Fusobacterium nucleatum and gut Lactobacillus are increased in DCHD patients, with a positive correlation between the two. Experimental evidence revealed that in hyperglycemic mice, augmented Fusobacterium nucleatum levels in the oral cavity were accompanied by an imbalance in the oral-gut axis, characterized by an increased coexistence of Fusobacterium nucleatum and Lactobacillus, along with elevated cardiac miRNA-21 and a greater extent of myocardial damage indicated by TTC, HE, TUNEL staining, all of which contributed to exacerbated MIRI. CONCLUSION: Our findings not only uncover dysregulation of the oral-gut microbiota axis in diabetes patients but also highlight the pivotal intermediary role of the increased abundance of oral F. nucleatum and gut Lactobacillus in exacerbating MIRI. Targeting the oral-gut microbiota axis emerges as a potent strategy for preventing and treating DCHD. Oral-gut microbial transmission constitutes an intermediate mechanism by which diabetes influences myocardial injury, offering new insights into preventing acute events in diabetic patients with coronary heart disease.

Multiple triglyceride-derived metabolic indices and incident cardiovascular outcomes in patients with type 2 diabetes and coronary heart disease.

BACKGROUND: Triglyceride (TG) and its related metabolic indices are recognized as important biomarker gauging cardiovascular diseases. This study aimed to explore the association between multiple TG-derived metabolic indices including the atherogenic index of plasma (AIP), triglyceride-glucose (TyG) index, triglyceride glucose-body mass index (TyG-BMI) and cardiovascular outcomes to identify valuable predictors for cardiovascular prognosis in patients with type 2 diabetes (T2DM) and coronary heart disease (CHD). METHODS: Data of 1034 patients with T2DM and CHD from China-Japan Friendship Hospital between January 2019 and March 2022 were collected and analyzed. Multivariate Cox proportional hazards models and restricted cubic spline (RCS) analysis were conducted to examine the associations between AIP, TyG index, TyG-BMI and major adverse cardiac and cerebrovascular events (MACCEs). The area under the receiver operating characteristic (ROC) curve (AUC) was used to screen the most valuable predictor. Kaplan-Meier curve analysis was employed to examine the relationship between the predictor and prognosis. The goodness-of-fit of models was evaluated using the calibration curve and χ2 likelihood ratio test. Subgroup analysis and interaction test were performed to control for confounding factors. RESULTS: The overall incidence of MACCEs was 31.04% during a median of 13.3 months of follow-up. The results showed that AIP, TyG index and TyG-BMI were all positively correlated with the risk of MACCEs in patients with T2DM and CHD (P < 0.05). Furthermore, ROC (AUC = 0.899) suggested that AIP had the strongest ability to predict the risk of MACCEs, and the highest AIP values enhanced the risk by 83.5% in the population. RCS model demonstrated that AIP was nonlinearly associated with the incident cardiovascular outcomes (P for nonlinear = 0.0118). The Kaplan-Meier analysis for MACCEs grouped by the AIP tertiles indicated that the probability of cumulative incidences of MACCEs was significantly higher in patients with a higher AIP (all Log rank P < 0.001). Meanwhile, the calibration curve demonstrated an excellent goodness-of-fit of the multivariate model (χ2 = 13.210, P = 0.105). Subgroup analysis revealed that the trend of positive association of AIP with cardiovascular risk was similar across subgroups except in non-hypertensive individuals. CONCLUSION: Our study, for the first time, may provide valuable information that multiple TG-derived metabolic indices play a crucial role in the risk of MACCEs and it is recommended to monitor the AIP for lipid management in patients with established T2DM and CHD.