CAD Risk Research Articles

A novel scoring system for predicting disease severity without CT imaging in acute diverticulitis

PurposeClinical scoring could help physicians identify patients with suspected acute diverticulitis who would benefit from further evaluation using computed tomography imaging. The aim of the study was to identify risk factors for complicated acute diverticulitis and create a risk score to predict disease severity in acute diverticulitis.MethodsPatients diagnosed with CT-verified acute diverticulitis between 2015 and 2017 were included. Data on patients’ clinical and laboratory findings and medical histories were collected retrospectively. Risk factors for complicated acute diverticulitis were identified using univariate and multivariate analyses. Continuous laboratory values were categorised by cut-off points determined using receiver operating characteristic (ROC) analysis. The Acute Diverticulitis Severity Score was formulated using logistic regression analysis.ResultsOf the total 513 patients included in the study, 449 (88%) had UAD, and 64 (12%) had CAD. Older age, significant comorbidities, C-reactive protein level, leucocyte count, vomiting, and body temperature were found to be independently associated with a higher risk for CAD. The novel Acute Diverticulitis Severity Score could reliably detect patients with CAD. The area under the ROC curve was 0.856 (p < 0.001) in discriminating disease severity. While higher scores indicate radiological studies, patients with low scores face an almost non-existent risk for complicated disease, making such studies possibly redundant.ConclusionsThe Acute Diverticulitis Severity Score accurately separated patients with uncomplicated disease from those at risk for complicated disease. This score can be applied in daily clinical practice to select patients requiring further investigation, consequently reducing healthcare costs and burdens.

HPV and coronary diseases in menopausal women: an integrative review.

High-risk human papillomavirus (HPV) infection is associated with cervical cancer while low-risk HPV strains mostly cause benign lesions. Multiple studies have also associated HPV with coronary artery (CAD) disease in women. Furthermore, the climacteric period in women, triggers chronic inflammation and has major implications for CAD and associated lipid disorders. The association of HPV with coronary artery disease in climacteric women has few studies, and the objective of this review is to gather and analyse scientific data on the subject. This is an integrative review performed on PubMed and Google Scholar using the keywords "HPV", "coronary heart disease" and "climacteric", among these keywords the boolean operator AND and the publication date filter. (2018 onwards). Five articles were found, whose main results show presence of high-risk vaginal HPV in climacteric women. Climacterium and HPV were associated with a three-fold increased risk of CAD, as well as with factors related to menopause that promote atheroma formation, lipid disorders and chronic inflammation. Thus, these results support the association between HPV infection and CAD in climacteric women, possibly via chronic inflammation, hormonal factors related to menopause and dyslipidemia.

Value of Platelet-to-Lymphocyte Ratio in Acute Coronary Syndrome for Predicting In-Hospital Complications and Mortality

Background: Acute coronary syndrome (ACS) refers to a spectrum of urgent heart conditions caused by a sudden decrease in blood flow to the heart. This condition demands immediate medical attention as it can lead to severe complications, including heart attack and death. The platelet-to-lymphocyte ratio (PLR) has recently gained attention as a potential biomarker for assessing the inflammatory status in ACS patients. Inflammation plays a crucial role in the pathophysiology of ACS, and biomarkers like PLR can offer insights into the severity and prognosis of the disease. Methods: This study was a prospective cross-sectional analysis conducted in Sulaymaniyah city, spanning from December 2021 to December 2022. The study included 100 patients who were diagnosed with ACS and subsequently hospitalized. Data collection involved comprehensive clinical histories, physical examinations, and laboratory analyses. Among the laboratory tests, complete blood counts were performed to calculate the PLR for each patient. Based on their PLR levels, patients were categorized into two primary groups for comparative analysis. Results: In a study of 100 ACS patients (mean age 61.54 years, 69% male), elevated PLR correlated with lower oxygen saturation, more frequent STE-ACS (70.6%), and higher in-hospital complications, including mortality (11.8%). No significant links were found between PLR and traditional CAD risk factors. Conclusion: The findings of this study underscore the potential prognostic value of PLR in ACS patients. Elevated PLR was significantly associated with worse oxygen saturation, a higher prevalence of STE-ACS, and an increased occurrence of in-hospital complications and mortality.

Neuroradiological manifestations in hospitalized patients with COVID-19: An Italian national multicenter study on behalf of AINR (Associazione Italiana di Neuroradiologia) and SIRM (Società Italiana di Radiologia Medica).

This multicentric study aims to characterize and assess the occurrence of neuroradiological findings among patients with SARS-CoV-2 infection during the first Italian wave of the pandemic outbreak. Patients' data were collected between May 2020 and June 2020. Clinical and laboratory data, chest imaging, brain CT, and MRI imaging were included. Acquired data were centralized and analyzed in two hospitals: ASST Spedali Civili, Brescia, and IRRCS San Raffaele Research Hospital, Milan, Italy. COVID-19 patients were classified into two different subgroups, vascular and nonvascular. The vascular pattern was further divided into ischemic and hemorrhagic stroke groups. Four hundred and fifteen patients from 20 different Italian Centers were enrolled in the study. The most frequent symptom was focal neurological deficit, found in 143 patients (34.5%). The most frequent neuroradiological finding was ischemic stroke in 122 (29.4%) patients. Forty-four (10.6%) patients presented a cerebral hemorrhage. Forty-seven patients had non-stroke neuroimaging lesions (11.3%). The most common was PRES-like syndrome (28%), SWI hypointensities (22%), and encephalitis (19%). The stroke group had higher CAD risk (37.5% vs 20%, p = .016) and higher D-dimer levels (1875ng/mL vs 451ng/mL, p < .001) compared to the negative group. Our study describes the biggest cohort study in Italy on brain imaging of COVID-19 patients and confirms that COVID-19 patients are at risk of strokes, possibly due to a pro-thrombotic microenvironment. Moreover, apart from stroke, the other neuroradiological patterns described align with the ones reported worldwide.

Anxiety, a significant risk factor for coronary artery disease: what is the best index

BackgroundCoronary artery disease (CAD) is known as the leading cause of disability and death globally. Anxiety disorders are also recognized as common types of mental disorders that substantially impact global health. Iran ranks among the countries with a high incidence of CAD and anxiety disorders. Therefore, the present study aims to determine the potential association and epidemiological aspects of anxiety and CAD within the population of Mashhad, the second most popoulos city in Iran.MethodsThe present study is based on extracted data from the Mashhad stroke and heart atherosclerotic disorder (MASHAD) study which is a 10-year prospective cohort study intended to assess the effects of various CAD risk factors among Mashhad city residents. Anxiety scores were assessed at the baseline using Beck Anxiety Inventory and individuals were classified based on the BAI 4-factor structure model which included autonomic, cognitive, panic, and neuromotor components. Accordingly, the association between baseline anxiety scores and the BAI four-factor model with the risk of CAD events was analyzed using SPSS software version 21.ResultsBased on the results, 60.4% of the sample were female, and 5.6% were classified as having severe forms of anxiety. Moreover, severe anxiety was more prevalent in females. Results showed a 1.7% risk of CAD (p-value < 0.001) over 10 years with one unit increase in anxiety score. Based on the 4-factor model structure, we found that only panic disorder could significantly increase the risk of CAD by 1.1% over the 10-year follow-up (p-value < 0.001).ConclusionAnxiety symptoms, particularly panic disorder, are independently and significantly associated with an increased overall risk of developing CAD over a 10-year period. Therefore, further studies are warranted to investigate the mechanisms through which anxiety may cause CAD, as well as possible interventions to mitigate these processes.

LncRNA CDKN2B-AS1 regulates collagen expression

The long noncoding RNA CDKN2B-AS1 harbors a major coronary artery disease risk haplotype, which is also associated with progressive forms of the oral inflammatory disease periodontitis as well as myocardial infarction (MI). Despite extensive research, there is currently no broad consensus on the function of CDKN2B-AS1 that would explain a common molecular role of this lncRNA in these diseases. Our aim was to investigate the role of CDKN2B-AS1 in gingival cells to better understand the molecular mechanisms underlying the increased risk of progressive periodontitis. We downregulated CDKN2B-AS1 transcript levels in primary gingival fibroblasts with LNA GapmeRs. Following RNA-sequencing, we performed differential expression, gene set enrichment analyses and Western Blotting. Putative causal alleles were searched by analyzing associated DNA sequence variants for changes of predicted transcription factor binding sites. We functionally characterized putative functional alleles using luciferase-reporter and antibody electrophoretic mobility shift assays in gingival fibroblasts and HeLa cells. Of all gene sets analysed, collagen biosynthesis was most significantly upregulated (Padj=9.7 × 10− 5 (AUC > 0.65) with the CAD and MI risk gene COL4A1 showing strongest upregulation of the enriched gene sets (Fold change = 12.13, Padj = 4.9 × 10− 25). The inflammatory “TNFA signaling via NFKB” gene set was downregulated the most (Padj=1 × 10− 5 (AUC = 0.60). On the single gene level, CAPNS2, involved in extracellular matrix organization, was the top upregulated protein coding gene (Fold change = 48.5, P < 9 × 10− 24). The risk variant rs10757278 altered a binding site of the pathogen responsive transcription factor STAT1 (P = 5.8 × 10− 6). rs10757278-G allele reduced STAT1 binding 14.4% and rs10757278-A decreased luciferase activity in gingival fibroblasts 41.2% (P = 0.0056), corresponding with GTEx data. CDKN2B-AS1 represses collagen gene expression in gingival fibroblasts. Dysregulated collagen biosynthesis through allele-specific CDKN2B-AS1 expression in response to inflammatory factors may affect collagen synthesis, and in consequence tissue barrier and atherosclerotic plaque stability.

Abstract 2122: A Multiomic Timecourse Atlas Of Murine Vascular Disease Smooth Muscle Cell Transition Phenotypes And Their Perturbation With Tcf21 Knockout

Background: Vascular smooth muscle cells (SMC) contribute to heritable CAD risk and undergo cell changes to fibroblast-like (FMC) and osteochondrogenic (CMC) phenotypes. We perform molecular characterization of this transition process over the course of atherosclerosis development to better understand how causal SMC CAD genes such as TCF21 drive the phenotypic transition process to alter CAD risk. Methods/Results: Deep multiomic profiling of aortic roots from control atherosclerosis model ( Myh11Cre ERT2 , ROSA tdT/+ , ApoE -/- ) mice with SMC specific lineage tracing on high fat diet were harvested for 7 scRNA and 6 scATAC time points across 16 weeks. Similarly, aortic roots from Tcf21 knockout ( Myh11Cre ERT2 , Tcf21 ΔSMC/ΔSMC , ROSA tdT/+ , ApoE -/- ) were collected at 3 timepoints for paired scRNA/scATAC. Waddington-Optimal Transport (WOT) mapped transcriptional trajectories across SMC lineage clusters which terminate in FMC and CMC phenotype clusters. PANDO/CellOracle frameworks were used to create gene regulatory networks with the ability to model SMC transition perturbations in silico . These analyses generated a multiomic timecourse atlas demonstrating the lineage traced phenotypic progression of SMC to FMC and CMC. Upon knockout of Tcf21 , we discern notable shifts in the SMC to FMC transition characterized by differential scRNA transcriptional pathways and scATAC shifts in transcription factor (TF) motif accessibility which also overlap with WOT predicted TF enrichment for each cell state. These integrative analyses revealed Tcf21 regulation of Cebpb and the Tead1 -Hippo pathways as novel mechanisms for mediating its role in modulation of disease related processes such as inflammation, response to TGF- β signaling and cell proliferation. Further mechanistic validation is performed through a combination of TF binding site analysis with TEAD1 and CEBPB ChIP-Seq in human coronary artery SMCs, dual luciferase reporter assays and proximity ligation assays. Conclusion: We construct a single cell atherosclerosis timecourse to model mouse SMC cell states and perturb CAD gene Tcf21 to elucidate the interplay between epigenetic and transcriptional mechanisms which affect key SMC transition elements such as CEBPB and the TEAD1 -Hippo axis.

Abstract 2075: Vascular Smooth Muscle Cell Derived Pdgfd Promotes Vascular Remodeling And Plaque Progression In Atherosclerosis

We have recently identified rs2019090 and PDGFD as the functional variant and gene mediating CAD risk at the 11q22.3 locus, with our initial analysis using a global knockout (KO) model showing that this gene may promote phenotypic changes in smooth muscle cells (SMCs) in the plaque and contribute to neointimal vascular calcification. Nonetheless, the specific cell-type and phenotypic states through which PDGFD may confer disease risk remains unexplored.To delineate the impact of SMC-derived PDGFD signalling on cell state transitions and plaque progression in atherosclerosis, we have developed a novel SMC-specific lineage tracing and Pdgfd KO mouse ( Pdgfd ΔSMC/ΔSMC , Myh11 CreERT2 , ROSA tdT/+ , ApoE -/- ) allowing us to confidently define the impact of SMC-derived Pdgfd in the vascular SMC lineage as well as in neighbouring populations. Leveraging our lineage tracing KO mutants on a hypercholesterolemic diet, we have employed single cell RNA sequencing (scRNAseq) and histological analyses to characterize the cellular and molecular effect of Pdgfd in vascular disease. SMC-specific Pdgfd deletion resulted in alterations in the distribution of transitioning SMC populations, as well as previously unexplored gene expression differences within these cell types. This was accompanied by a significant reduction in atherosclerotic burden and plaque size across the aorta, including aortic root as well as descending abdominal aorta. Histological analysis revealed decreased monocyte recruitment, show by quantifying CD68+ cells within the plaque. To explore this further we interrogated the scRNAseq dataset to identify major pathways of cell-cell communication and the impact of altered Pdgfd signalling across different cell types. Overall, these data reveal that SMC-derived PDGFD substantially alters lesional SMC cell phenotype transitions, as well as inflammatory cell recruitment, implicating it as a major regulator of atherosclerotic disease progression.

Alterations in the gut mycobiome with coronary artery disease severity

BackgroundCoronary artery disease (CAD) is a prevalent cardiovascular condition, and numerous studies have linked gut bacterial imbalance to CAD. However, the relationship of gut fungi, another essential component of the intestinal microbiota, with CAD remains poorly understood. MethodsIn this cross-sectional study, we analyzed fecal samples from 132 participants, split into 31 healthy controls and 101 CAD patients, further categorized into stable CAD (38), unstable angina (41), and acute myocardial infarction (22) groups. We conducted internal transcribed spacer 1 (ITS1) and 16S sequencing to examine gut fungal and bacterial communities. FindingsBased on ITS1 analyses, Ascomycota and Basidiomycota were the dominant fungal phyla in all the groups. The α diversity of gut mycobiome remained unaltered among the control group and CAD subgroups; however, the structure and composition of the mycobiota differed significantly with the progression of CAD. The abundances of 15 taxa gradually changed with the occurrence and progression of the disease and were significantly correlated with major CAD risk factor indicators. The mycobiome changes were closely linked to gut microbiome dysbiosis in patients with CAD. Furthermore, disease classifiers based on gut fungi effectively identified subgroups with different degrees of CAD. Finally, the FUNGuild analysis further categorized these fungi into distinct ecological guilds. InterpretationIn conclusion, the structure and composition of the gut fungal community differed from healthy controls to various subtypes of CAD, revealing key fungi taxa alterations linked to the onset and progression of CAD. Our study highlights the potential role of gut fungi in CAD and may facilitate the development of novel biomarkers and therapeutic targets for CAD. FundingThis work was supported by the grants from the National Natural Science Foundation of China (No. 82170302, 92168117, 82370432), National clinical key specialty construction project- Cardiovascular Surgery, 2024 Reform and Development Program of Beijing Institute of Respiratory Medicine, the Beijing Natural Science Foundation (No. 7222068); the Reform and Development Program of Beijing Institute of Respiratory Medicine (No. Ggyfz202308); and the Clinical Research Incubation Program of Beijing Chaoyang Hospital Affiliated to Capital Medical University (No. CYFH202209).

LPA Gene Copy Number Variation and APOE Gene Polymorphism in Young Acute Myocardial Infarction

INTRODUCTION: An early onset of acute myocardial infarction (AMI) and a strong family history suggest the possibility of its genetic predisposition. Lipoprotein(a) (LPA) and Apolipoprotein E (APOE) genes are known to be involved in lipid metabolism which may contribute to the development of atherosclerosis leading to AMI. This study aims to assess the association between LPA gene copy number variation (CNV) and APOE gene polymorphism in young AMI patients. MATERIALS AND METHODS: A total of 40 DNAs were extracted from the buffy coat. APOE genotyping and detection of LPA gene CNV were performed using multiplex PCR technique and digital PCR. After tabulation of the results of the current study, meta-analyses were performed from selected studies among Asian populations using the Comprehensive Meta-analysis version 3 software program. RESULTS: No significant association was found between CNV of the LPA gene and the polymorphism of the APOE gene with Young AMI patients in the current study. However, our meta-analysis confirmed that the E4 allele increased the risk for CAD with the E3/E4 genotype [p=0.000, OR= 1.60 (95% CI: 1.41-1.83) significantly increased risk of CAD and individuals with E3/E3 genotype [p=0.000, OR=0.73 (95% CI: 0.66-0.81) were protective against CAD. The gain of LPA CNV was higher in YAMI [n=5 (25%)] than in control [n=2 (10%)] but they are not significant. CONCLUSION: There is no association between the LPA gene CNV and the presence of APOE polymorphism in young AMI, but our meta-analysis confirmed that the E4 allele increased the risk for CAD.

Abstract MP14: Gestational Diabetes Mellitus, Circulating Metabolites, and Risk of Future Cardiovascular Disease in US Women

Introduction: Gestational diabetes mellitus (GDM) is associated with higher lifetime cardiovascular disease (CVD) risk in women, even without subsequent type 2 diabetes (T2D). Dysregulation of lipid and amino acid metabolism precedes CVD and has been associated with T2D in women with GDM history. However, the precise metabolic pathways contributing to the persistent CVD risk after GDM remain unknown. Hypothesis: A metabolomic signature of GDM history is associated with higher CVD risk. Methods: Using elastic net regression, we constructed a postpartum (24-72 hours after delivery) metabolomic signature of GDM using maternal plasma metabolomics data in the Boston Birth Cohort (BBC; 161 GDM; 1,178 non-GDM; 64% Black). The GDM signature was internally validated in the BBC using leave-one-out cross-validation and externally replicated in a subset of Nurses’ Health Study II (NHS2; 392 prior GDM; 2,326 no GDM; 98% White) with available postpartum (a median of 17.5 years after delivery) plasma metabolomics data. CVD was defined as a composite of coronary artery disease (CAD; coronary artery bypass grafting, myocardial infarction, and coronary death) and stroke. Cox proportional hazards model was used to examine associations between the GDM signature and incident CVD in both NHS2 and Nurses’ Health Study (NHS; no data on GDM history; 95% White). A genome-wide association study (GWAS) was conducted in NHS2 and NHS to identify genes implicated in the GDM signature. Results: The externally validated GDM signature consists of 44 metabolites (21 lipids, 10 amino acids, and others). Women with prior GDM had a higher signature score than those without in both BBC (p=2х10 -20 ) and NHS2 (p=0.004). In NHS2 (n=2,718), 97 CVD cases (17 cases in 392 women with prior GDM) were documented in 23 years of follow-up. The GDM signature was significantly associated with higher risk of CVD (HR = 1.31 [1.04-1.65] for per-SD increase in the signature score) and CAD (HR = 1.81 [1.30-2.52]) but not stroke (HR = 1.05 [0.76-1.45]) after adjusting for age, race, body mass index (BMI), blood pressure, baseline T2D, medication use, and lifestyle factors. The associations did not change after additionally adjusting for GDM history and incident T2D. The GDM signature mediated associations between GDM and CAD (5.7%; p=0.048) and CVD (4.4%; p=0.038). In NHS (n=4,469), 874 CVD cases were documented in 31 years of follow-up. The GDM signature was associated with incident CAD (adjusted HR = 1.18 [1.07-1.29]) but not CVD and stroke. In GWAS, we identified genetic loci harboring genes ( FADS1 , FADS2 , and SOX2-OT ) related to fatty acid metabolism, blood lipid levels, glycemic traits, BMI, and insomnia. Conclusions: We identified and validated a metabolomic signature associated with GDM history, which was associated an increased risk of future CVD, especially CAD. Ongoing work is underway to replicate these findings in other racial and ethnic groups.

Abstract 58: Multi-Ancestry Genome-Wide Association Study of Age-at-Onset in Heart Failure

Background: Heart failure (HF) is a life-threatening syndrome with growing impact on the global population. It is estimated that &gt;8 million people in the US will be living with HF by 2030. Aging is a major risk factor for HF. Age-at-onset (AAO) is one of the critical traits in cohort studies of age-related diseases. Large-scale genome-wide association studies (GWAS) of HF AAO can provide insights into genetic effects on disease progression and transitions to severe stages. Methods: The multi-ancestry study consisted of a discovery cohort from the Million Veteran Program (MVP) including 67845, 17687, 4936, and 527 HF patients in European, African, Hispanic, and Asian Americans, respectively. HF AAO was determined by the first HF diagnosis date with a measured left ventricle ejection fraction within 90 days. Within each group, a GWAS of AAO was conducted using common SNPs (minor allele frequency&gt;1%) imputed to the 1000 Genome Project panel, adjusted for sex and top 10 ancestry-specific principal components (PCs) of genome-wide SNPs. A meta-analysis of GWAS summary statistics was performed to identify genome-wide significant (GWS, p&lt;5x10 -8 ) loci. In the replication study, 20453 HF patients of European ancestry from the UK Biobank (UKB) study were identified using HF diagnosis codes extracted from in-patient Hospital Episode Statistics and National Death Registry. The age at the first use of a HF diagnosis code was used to approximate the AAO in the GWAS adjusted for sex and top 10 PCs. The sentinel SNPs of GWS locus from the discovery phase were examined for replication in the UKB cohort. Results: From the multi-ancestry GWAS of HF AAO in MVP, four GWS loci were identified in chromosomes 3 (3:49862418, p=3.41x10 -11 ), 9 (9:22124744, p=1.18x10 -11 ), 15 (15:78868398, p=1.60x10 -9 ) and 19 (19:45411941, p=4.15x10 -38 ). All but the chromosome 19 locus were replicated in the UKB, with the most significant replication in the chromosome 3 locus (p=8.74x10 -5 ). The chromosome 3 locus has been associated with multiple phenotypes including metabolic diseases, inflammation, and lung function. The 9p21 locus is a well-established locus of coronary heart disease, which is a key antecedent of HF. The chromosome 15 locus maps to the CHRNA gene cluster, which is associated with pulmonary function and disease, as well as aging. The chromosome 19 locus is located within the APOE gene, which plays an important role in aging, Alzheimer’s disease, and lipid metabolism. The allelic effects of younger HF AAO are in the same direction of elevated disease risk at corresponding loci (e.g., younger AAO and higher CAD risk for 9p21). Conclusion: The significant genetic associations with AAO of HF revealed the pathways and mechanisms regulating HF progression and transition into clinical stages. They may lead to novel targets for treatment and prevention which could eventually reduce the burden of HF among the aging population in the US.

Advanced detection of coronary artery disease via deep learning analysis of plasma cytokine data.

The 2017 World Health Organization Fact Sheet highlights that coronary artery disease is the leading cause of death globally, responsible for approximately 30% of all deaths. In this context, machine learning (ML) technology is crucial in identifying coronary artery disease, thereby saving lives. ML algorithms can potentially analyze complex patterns and correlations within medical data, enabling early detection and accurate diagnosis of CAD. By leveraging ML technology, healthcare professionals can make informed decisions and implement timely interventions, ultimately leading to improved outcomes and potentially reducing the mortality rate associated with coronary artery disease. Machine learning algorithms create non-invasive, quick, accurate, and economical diagnoses. As a result, machine learning algorithms can be employed to supplement existing approaches or as a forerunner to them. This study shows how to use the CNN classifier and RNN based on the LSTM classifier in deep learning to attain targeted "risk" CAD categorization utilizing an evolving set of 450 cytokine biomarkers that could be used as suggestive solid predictive variables for treatment. The two used classifiers are based on these "45" different cytokine prediction characteristics. The best Area Under the Receiver Operating Characteristic curve (AUROC) score achieved is (0.98) for a confidence interval (CI) of 95; the classifier RNN-LSTM used "450" cytokine biomarkers had a great (AUROC) score of 0.99 with a confidence interval of 0.95 the percentage 95, the CNN model containing cytokines received the second best AUROC score (0.92). The RNN-LSTM classifier considerably beats the CNN classifier regarding AUROC scores, as evidenced by a p-value smaller than 7.48 obtained via an independent t-test. As large-scale initiatives to achieve early, rapid, reliable, inexpensive, and accessible individual identification of CAD risk gain traction, robust machine learning algorithms can now augment older methods such as angiography. Incorporating 65 new sensitive cytokine biomarkers can increase early detection even more. Investigating the novel involvement of cytokines in CAD could lead to better risk detection, disease mechanism discovery, and new therapy options.

IDF23-0359 Role of 25(OH)vitamin D with CAD Risk Factors, Glycation Biomarkers, Insulin Resistance and Syntax Score in T2DM with CAD

IDF23-0359 Role of 25(OH)vitamin D with CAD Risk Factors, Glycation Biomarkers, Insulin Resistance and Syntax Score in T2DM with CAD

CxsAssociation study between single nucleotide polymorphism in thrombospondins THBS1 gene and THBS2 gene and coronary artery disease in Indian population

BackgroundCoronary artery disease (CAD) is a complex medical condition characterized by atherosclerotic plaque accumulation in coronary arteries, leading to narrowed blood vessels and impaired blood flow. Endothelial dysfunction, smooth muscle cell proliferation, and various risk factors contribute to CAD development. Matricellular proteins, including thrombospondins (THBS), play crucial roles in vascular processes and cardiac function.MethodsA case–control study was conducted among 296 participants from Era's Lucknow Medical College and Hospital, India, to investigate genetic variations in THBS1 (N700S) and THBS2 (3′ UTR T → G) in relation to CAD. Genomic DNA was isolated, and PCR–RFLP was employed for genotyping. Clinical and biochemical parameters were assessed, and statistical analyses were performed using SPSS software.ResultsThe study revealed that age, serum cholesterol, HDL, VLDL, and LDL were significantly associated with CAD in the Indian population. However, no statistically significant associations were found between triglyceride and serum creatinine levels, as well as the studied THBS1 and THBS2 genetic polymorphisms, and CAD. The analysis of genotypic and allelic frequencies did not indicate significant associations with CAD risk.ConclusionsThis study suggests that specific genetic variations in THBS1 and THBS2 may not be strongly linked to the development or risk of CAD in the studied Indian population. The associations observed between age, lipid profiles, and CAD highlight the multifactorial nature of CAD susceptibility. Further research with larger sample sizes and diverse populations is warranted to validate these findings and explore additional genetic factors contributing to CAD in specific populations.

Which risk factor best predicts coronary artery disease using artificial neural network method?

BackgroundCoronary artery disease (CAD) is recognized as the leading cause of death worldwide. This study analyses CAD risk factors using an artificial neural network (ANN) to predict CAD.MethodsThe research data were obtained from a multi-center study, namely the Iran-premature coronary artery disease (I-PAD). The current study used the medical records of 415 patients with CAD hospitalized in Razi Hospital, Birjand, Iran, between May 2016 and June 2019. A total of 43 variables that affect CAD were selected, and the relevant data was extracted. Once the data were cleaned and normalized, they were imported into SPSS (V26) for analysis. The present study used the ANN technique.ResultsThe study revealed that 48% of the study population had a history of CAD, including 9.4% with premature CAD and 38.8% with CAD. The variables of age, sex, occupation, smoking, opium use, pesticide exposure, anxiety, sexual activity, and high fasting blood sugar were found to be significantly different among the three groups of CAD, premature CAD, and non-CAD individuals. The neural network achieved success with five hidden fitted layers and an accuracy of 81% in non-CAD diagnosis, 79% in premature diagnosis, and 78% in CAD diagnosis. Anxiety, acceptance, eduction and gender were the four most important factors in the ANN model.ConclusionsThe current study shows that anxiety is a high-prevalence risk factor for CAD in the hospitalized population. There is a need to implement measures to increase awareness about the psychological factors that can be managed in individuals at high risk for future CAD.

Mediation effect of antithrombin III between chronic renal insufficiency and chronic coronary artery disease in T2DM patients.

The study aimed to investigate the potential effect of Antithrombin III (ATIII) between chronic renal insufficiency and chronic coronary artery disease (chronic CAD) in type 2 diabetes mellitus (T2DM) patients. T2DM patients hospitalized in ZhongDa Hospital from 2013 to 2018 were enrolled. Relationships between renal function, ATIII, and chronic CAD risk were explored using multivariate regression models. Multiplicative and additive interactions were investigated between ATIII and renal function for CAD risk, and the role of ATIII was determined by bootstrap mediation analysis in patients with chronic renal dysfunction. A total of 4197 patients were included in the study, with a chronic CAD prevalence of 23.02%. Low ATIII level was statistically associated with chronic renal insufficiency and elevated CAD risk even after adjustments (P < 0.05). A positive correlation between renal function and ATIII was demonstrated, and each 1 SD increase in renal function, ATIII increased by 2.947% (2.406-3.488%, P < 0.001) and 0.969% (0.297-1.642%, P < 0.001) in crude and adjusted models respectively. Patients with decreased renal function and ATIII were at the highest chronic CAD risk (OR = 1.51, 95%CI:1.15-1.98, P < 0.05), while no multiplicative and additive interaction effects were significant. Bootstrap mediation analysis estimated that ATIII mediated approximately 4.27% of the effect of chronic renal insufficiency on chronic CAD risk. ATIII may serve as a mediator between chronic renal insufficiency and chronic CAD, providing mechanistic clues for renal-heart association and new insight into clinical therapies.

Prevalence and trend of multiple coronary artery disease risk factors and their 5-year incidence rate among adult population of Kerman: results from KERCADR study

BackgroundCoronary artery diseases (CADs) are the most important non‑communicable diseases (NCDs), which cause the highest number of deaths around the world. Hypertension (HTN), dyslipidemia (DL), diabetes mellitus (DM), obesity (OB), low physical activity (LPA), smoking, opium consumption (OC) and anxiety are the most important CAD risk factors, which are more dangerously present in combination in some patients.MethodsA total of 5835 people aged 15 to 75 years were enrolled in the phase 1 (2012) and followed up to the phase 2 (2017) of the population-based Kerman coronary artery diseases risk factors study (KERCADRS). The prevalence and pattern of different combinations of CAD risk factors (double to quintuple) and their 5-year incidence rates were assessed.ResultsThe prevalence of single CAD risk factors (RFs) in phase 2 was 50.2% (DL), 47.1% (LPA), 28.1% (abdominal obesity), 21.2% (OB), 16.5% (HTN), 9.2% (smoking), 9.1% (OC), and 8.4% (DM). The most frequent combination of risk factors was LPA plus DL (23.9%), metabolic syndrome (19.6%), and DL plus OB (17.8%). The 5-year incidence rates of multiple comorbidities (in persons per 100 person-years) was DL plus LPA (2.80%), HTN plus DL (1.53%), and abdominal obesity (AOB) plus DL (1.47%). The most participants (84.4%) suffered from at least one RF, while 54.9% had at least two and 29.9% had at least three RFs.ConclusionThe results showed that a large portion of the study population suffers from multiple CAD RFs. The findings underscore the importance of identifying multiple CAD risk factors to reduce the overall burden of these NCDs.

Comparison between myocardial infarction with non-obstructive coronaries (MINOCA) and myocardial infarct patients with coronary artery disease (MI-CAD): A single-center retrospective cohort study.

The coronary angiography results in a group of patients with myocardial infarction (MI) are normal or near-normal; which is diagnosed as myocardial infarction with non-obstructive coronary arteries (MINOCA). This study aimed to compare the mortality rate and risk factors between MINOCA and myocardial infarction with obstructive coronary artery (MI-CAD). This retrospective cohort study was conducted from January 1, 2018, to December 31, 2019. A total of 679 patients admitted to Afshar Hospital in Yazd with a diagnosis of ST-elevation myocardial infarction (STEMI) from 2018-2019 who underwent primary Percutaneous Coronary Intervention (PCI) were enrolled in the study. Demographic, and clinical variables, ECG finding and one-year mortality, were extracted using MI registry data from the Yazd Cardiac Research Center. The estimated frequency of MINOCA was 4.6%. Patients with MINOCA (47.14±6.2) were younger than patients with MI-CAD (57.61±9.1) (P <0.0001). MINOCA patients (47.4±9.47) had a considerably greater left ventricular ejection fraction (LVEF) than MI-CAD patients (43.5±6.8) (P =0.018). The majority site of MI in MINOCA patients was located in the non-anterior wall (p <0.0001). A comparison of MINOCA and MI-CAD patients' one-year mortalityrevealed no significant difference (P =0.07). The prevalence of patients with MINOCA in Yazd was similar to other communities. Although these patients probably do not have a better prognosis, despite being younger and having better LV systolic function and lower CAD risk factors.

Haptoglobin genotype is a risk factor for coronary artery disease in prediabetes: A case-control study

ObjectiveCoronary artery disease (CAD) prediction remains inconsistent with many unappreciated risk factors. Haptoglobin genotype determines the haptoglobin protein's effectiveness to bind free hemoglobin and prevent oxidative stress, a contributor to atherosclerosis. The haptoglobin 2-2 genotype increases the prevalence of cardiovascular disease (CVD) approximately five times compared to the 1-1 genotype in individuals with diabetes. The risk is unknown in prediabetes. The purpose of this study was to determine an association between haptoglobin genotype and CAD in prediabetes. MethodsThe researchers used case-control convenience sampling from two cardiovascular disease prevention clinics in Memphis, TN, and Spokane, WA, from January 1, 2016 to March 31, 2020. Participants were ages 35–70, had prediabetes, and free of chronic inflammatory or infectious diseases. Cases had a history of subclinical or clinical CAD, while controls did not have a history of CAD. Differences between cases and controls and among haptoglobin genotypes were analyzed using t-tests and ANOVA for continuous variables and chi-square or Fisher's exact tests for categorical variables. Associations among Hp genotypes and CAD were estimated using logistic regression. ResultsThe sample (N = 178; 72 cases and 106 controls) was 96 % white and 64 % male. Cases had lower total cholesterol (p = 0.0001) and high-sensitivity C-reactive protein (p = 0.021). Except for CAD, haptoglobin genotype was independent of any demographic or clinical variable. Haptoglobin 2-2 genotype had 4.0 times higher odds of CAD than haptoglobin 1-1 (p = 0.01). ConclusionHaptoglobin 2-2 genotype had approximately four times higher odds of having CAD compared to the haptoglobin 1-1 genotype. Cases had more desirable clinical profiles, likely attributable to more aggressive treatment of traditional risk factors than controls. Haptoglobin genotype is a potentially important CAD risk factor in prediabetes (88 million Americans). Further studies are needed for interventions to reduce the oxidative stress associated with the Hp 2-2 genotype and glycosylated hemoglobin and for CAD reduction.