Metabolic-immune crosstalk in myocardial infarction: RLF and SMCHD1 identified as causal therapeutic targets via integrated lactylation-MR analysis

Atrial fibrillation (AF) is a common persistent arrhythmia characterized by rapid and chaotic atrial electrical activity, potentially leading to severe complications such as thromboembolism, heart failure, and stroke, significantly affecting patient quality of life and safety. As the global population ages, the prevalence of AF is on the rise, placing considerable strains on individuals and healthcare systems. This study utilizes bioinformatics and Mendelian Randomization (MR) to analyze transcriptome data and genome-wide association study (GWAS) summary statistics, aiming to identify biomarkers causally associated with AF and explore their potential pathogenic pathways. We obtained AF microarray datasets GSE41177 and GSE79768 from the Gene Expression Omnibus (GEO) database, merged them, and corrected for batch effects to pinpoint differentially expressed genes (DEGs). We gathered exposure data from expression quantitative trait loci (eQTL) and outcome data from AF GWAS through the IEU Open GWAS database. We employed inverse variance weighting (IVW), MR-Egger, weighted median, and weighted model approaches for MR analysis to assess exposure-outcome causality. IVW was the primary method, supplemented by other techniques. The robustness of our results was evaluated using Cochran's Q test, MR-Egger intercept, MR-PRESSO, and leave-one-out sensitivity analysis. A "Veen" diagram visualized the overlap of DEGs with significant eQTL genes from MR analysis, referred to as common genes (CGs). Additional analyses, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and immune cell infiltration studies, were conducted on these intersecting genes to reveal their roles in AF pathogenesis. The combined dataset revealed 355 differentially expressed genes (DEGs), with 228 showing significant upregulation and 127 downregulated. Mendelian randomization (MR) analysis identified that the autocrine motility factor receptor (AMFR) [IVW: OR = 0.977; 95% CI, 0.956-0.998; P = 0.030], leucine aminopeptidase 3 (LAP3) [IVW: OR = 0.967; 95% CI, 0.934-0.997; P = 0.048], Rab acceptor 1 (RABAC1) [IVW: OR = 0.928; 95% CI, 0.875-0.985; P = 0.015], and tryptase beta 2 (TPSB2) [IVW: OR = 0.971; 95% CI, 0.943-0.999; P = 0.049] are associated with a reduced risk of atrial fibrillation (AF). Conversely, GTPase-activating SH3 domain-binding protein 2 (G3BP2) [IVW: OR = 1.030; 95% CI, 1.004-1.056; P = 0.024], integrin subunit beta 2 (ITGB2) [IVW: OR = 1.050; 95% CI, 1.017-1.084; P = 0.003], glutaminyl-peptide cyclotransferase (QPCT) [IVW: OR = 1.080; 95% CI, 1.010-0.997; P = 1.154], and tripartite motif containing 22 (TRIM22) [IVW: OR = 1.048; 95% CI, 1.003-1.095; P = 0.035] are positively associated with AF risk. Sensitivity analyses indicated a lack of heterogeneity or horizontal pleiotropy (P > 0.05), and leave-one-out analysis did not reveal any single nucleotide polymorphisms (SNPs) impacting the MR results significantly. GO and KEGG analyses showed that CG is involved in processes such as protein polyubiquitination, neutrophil degranulation, specific and tertiary granule formation, protein-macromolecule adaptor activity, molecular adaptor activity, and the SREBP signaling pathway, all significantly enriched. The analysis of immune cell infiltration demonstrated associations of CG with various immune cells, including plasma cells, CD8T cells, resting memory CD4T cells, regulatory T cells (Tregs), gamma delta T cells, activated NK cells, activated mast cells, and neutrophils. By integrating bioinformatics and MR approaches, genes such as AMFR, G3BP2, ITGB2, LAP3, QPCT, RABAC1, TPSB2, and TRIM22 are identified as causally linked to AF, enhancing our understanding of its molecular foundations. This strategy may facilitate the development of more precise biomarkers and therapeutic targets for AF diagnosis and treatment.

BackgroundDiabetic nephropathy (DN) is influenced by dysregulated adipokines, which play a key role in inflammation, immune responses, and lipid metabolism. However, the precise molecular mechanisms linking adipokine dysregulation, immune cell infiltration, and metabolic reprogramming in DN remain poorly understood. Celastrol, a bioactive lipid regulator, has been shown to mitigate renal immune-inflammatory damage by inhibiting the PI3K/Akt/NF-κB signaling pathway. Yet, its specific impact on adipokine-mediated immune responses and lipid metabolism in DN is unclear. This study aims to elucidate the interplay between adipokine-mediated target genes in DN and investigate how celastrol modulates these interactions.MethodsGene expression profiles of DN patients were obtained from GEO datasets (GSE30122 and GSE30528) and analyzed for differentially expressed genes (DEGs) using the limma package. Gene set variation analysis (GSVA) was conducted to assess lipid metabolism pathways, while Mendelian randomization (MR) and Pearson correlation evaluated the association between DEGs and adipokines. Immune cell infiltration was analyzed using the IOBR R package (MCP-counter and xCell methods), followed by MR analysis of DN-related immune responses. Celastrol target genes were identified using the SEA database.ResultsA total of 70 intersecting DEGs were identified. GSVA revealed that brown and beige adipocyte differentiation pathways were downregulated, while adipocyte-related pathways were upregulated in DN (p < 0.05). MR analysis demonstrated that adiponectin was negatively associated with DN (OR = 0.77, P = 0.005), whereas leptin (OR = 1.92, P = 0.016) and resistin (OR = 1.43, P < 0.001) were positively associated. Three key genes, MAGI2, FGF9, and THBS2 were linked to DN risk and T cell infiltration. THBS2 was positively correlated with T cell infiltration (OR = 0.51, P = 6.7e-06), while FGF9 (OR = -0.8, P = 2.2e-16) and MAGI2 (OR = 0.75, P = 1.3e-13) were negatively correlated. 22 celastrol target genes, including MAGI2, FGF9, and THBS2, were identified.ConclusionOur findings reveal that celastrol modulates DN progression through adipokine-immune crosstalk, with FGF9, MAGI2, and THBS2 emerging as key regulatory genes. These insights provide new avenues for biomarker discovery and therapeutic implications in the development of DN.

Background: Myocardial infarction (MI) is one of the leading threats to human health. N6-methyladenosine (m6A) modification, as a pivotal regulator of messenger RNA stability, protein expression, and cellular processes, exhibits important roles in the development of cardiac remodeling and cardiomyocyte contractile function.Methods: The expression levels of m6A regulators were analyzed using the GSE5406 database. We analyzed genome-wide association study data and single-cell sequencing data to confirm the functional importance of m6A regulators in MI. Three molecular subtypes with different clinical characteristics were established to tailor treatment strategies for patients with MI. We applied pathway analysis and differentially expressed gene (DEG) analysis to study the changes in gene expression and identified four common DEGs. Furthermore, we constructed the protein–protein interaction network and confirmed several hub genes in three clusters of MI. To lucubrate the potential functions, we performed a ClueGO analysis of these hub networks.Results: In this study, we identified that the levels of FTO, YTHDF3, ZC3H13, and WTAP were dramatically differently expressed in MI tissues compared with controls. Bioinformatics analysis showed that DEGs in MI were significantly related to modulating calcium signaling and chemokine signaling, and m6A regulators were related to regulating glucose measurement and elevated blood glucose levels. Furthermore, genome-wide association study data analysis showed that WTAP single-nucleotide polymorphism was significantly related to the progression of MI. In addition, single-cell sequencing found that WTAP is widely expressed in the heart tissues. Moreover, we conducted consensus clustering for MI in view of the dysregulated m6A regulators’ expression in MI. According to the expression levels, we found MI patients could be clustered into three subtypes. Pathway analysis showed the DEGs among different clusters in MI were assigned to HIF-1, IL-17, MAPK, PI3K-Akt signaling pathways, etc. The module analysis detected several genes, including BAG2, BAG3, MMP2, etc. We also found that MI-related network was significantly related to positive and negative regulation of angiogenesis and response to heat. The hub networks in MI clusters were significantly related to antigen processing and ubiquitin-mediated proteolysis, RNA splicing, and stability, indicating that these processes may contribute to the development of MI.Conclusion: Collectively, our study could provide more information for understanding the roles of m6A in MI, which may provide a novel insight into identifying biomarkers for MI treatment and diagnosis.

BackgroundEmerging evidence implicates exosomes in the pathogenesis of Alzheimer's disease (AD).ObjectiveThis study aimed to investigate the role of exosome-related genes in AD pathogenesis and evaluate their potential as diagnostic biomarkers.MethodsWe analyzed AD transcriptomic datasets (GSE5281, GSE138260, GSE29378) from the Gene Expression Omnibus database. Exosome-related differentially expressed genes (DEGs) were identified by intersecting the DEGs with exosome-related genes derived from GeneCards. The most AD-relevant exosome-related DEGs were screened using the least absolute shrinkage and selection operator regression and random forest algorithms. We then performed a two-sample Mendelian randomization (MR) analysis to evaluate potential causal effects of these candidate genes on AD risk, with the inverse-variance weighted method as the primary approach. Underlying molecular mechanisms were investigated through gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). The diagnostic potential of candidate genes was assessed via external validation.ResultsFour core exosome-related DEGs (TGFBR3, CXCR4, PSMB3, CD44) were identified. MR analysis demonstrated a significant causal effect of elevated TGFBR3 expression on AD risk (OR = 1.885, 95% CI 1.091-3.255, p = 0.023). Integrated GSEA and GSVA linked high TGFBR3 expression to synaptic impairment. Notably, TGFBR3 exhibited robust diagnostic accuracy across multiple external validation cohorts.ConclusionsTGFBR3, an exosome-related gene, may contribute to AD pathogenesis via synaptic dysfunction. Our findings support its potential as a diagnostic biomarker for AD.

Young patients with type 2 diabetes and myocardial infarction (MI) have higher long-term all-cause and cardiovascular mortality. In addition, the observed increased, mildly abnormal baseline lipid levels, but not lipid variability, are associated with an increased risk of atherosclerotic cardiovascular disease events, particularly MI. This study investigated differentially expressed genes (DEGs), which might be potential targets for young patients with MI and a high-fat diet (HFD). GSE114695 and GSE69187 were downloaded and processed using the limma package. A Venn diagram was applied to identify the same DEGs, and further pathway analysis was performed using Metascape. Protein-protein interaction (PPI) network analysis was then applied, and the hub genes were screened out. Pivotal miRNAs were predicted and validated using the miRNA dataset in GSE114695. To investigate the cardiac function of the screened genes, an MI mouse model, echocardiogram, and ELISA of hub genes were applied, and a correlation analysis was also performed. From aged mice fed HFD, 138 DEGs were extracted. From aged mice fed with chow, 227 DEGs were extracted. Pathway enrichment analysis revealed that DEGs in aging mice fed HFD were enriched in lipid transport and lipid biosynthetic process 1 d after MI and in the MAPK signaling pathway at 1 w after MI, suggesting that HFD has less effect on aging with MI. A total of 148 DEGs were extracted from the intersection between plaques fed with HFD and chow in young mice and MI_1d, respectively, which demonstrated increased inflammatory and adaptive immune responses, in addition to myeloid leukocyte activation. A total of 183 DEGs were screened out between plaques fed with HFD vs. chow in young mice and MI_1w, respectively, which were mainly enriched in inflammatory response, cytokine production, and myeloid leukocyte activation. After validation, PAK3, CD44, CD5, SOCS3, VAV1, and PIK3CD were demonstrated to be negatively correlated with LVEF; however, P2RY1 was demonstrated to be positively correlated. This study demonstrated that the screened hub genes may be therapeutic targets for treating STEMI patients and preventing MI recurrence, especially in young MI patients with HFD or diabetes.

In recent years, several studies have explored the effect of metformin on myocardial infarction (MI), but whether metformin has an improvement effect in patients with MI is controversial. This study was aimed to investigate the causal relationship between metformin and MI using Mendelian randomization (MR) analysis. The genome-wide significant (P<5×10-8) single-nucleotide polymorphisms (SNPs) in patients with metformin and patients with MI were screened from the Open genome-wide association study (GWAS) project as instrumental variables (IVs). The study outcomes mainly included MI, old MI, acute MI, acute transmural MI of inferior wall, and acute transmural MI of anterior wall. The inverse variance weighted (IVW) method was applied to assess the main causal effect, and weighted median, simple mode, weighted mode methods, and MR-Egger regression were auxiliary applied for supplementary proof. The causal relationship between metformin and MI was assessed using odds ratios (OR) and 95% confidence intervals (95% CI). A leave-one-out method was used to explore the effect of individual SNPs on the results of IVW analyses, and a funnel plot was used to analyze the potential bias of the study results, thus ensuring the robustness of the results. In total, 16, 84, 39, 26, and 34 SNPs were selected as IVs to assess the genetic association between metformin and outcomes of MI, old MI, acute MI, acute transmural MI of inferior wall, and acute transmural MI of anterior wall, respectively. Treatment with metformin does not affect the risk of acute transmural MI of anterior wall at the genetic level (P>0.05; OR for inverse variance weighted was 1.010). In the cases of MI, old MI, acute MI, and acute transmural MI of inferior wall, metformin may even be a risk factor for patients (P<0.05; ORs for inverse variance weighted were 1.078, 1.026, 1.022 and 1.018 respectively). There was no horizontal pleiotropy or heterogeneity among IVs. The results were stable when removing the SNPs one by one. Metformin is not protective against the risk of myocardial infarction in patients and may even be a risk factor for MI, old MI, acute MI, and acute transmural MI of inferior wall.

Introduction: Renal complications are frequently observed in patients with ankylosing spondylitis (AS), with IgA nephropathy (IgAN) being a particularly significant concern. Although anecdotal evidence suggests a potential association between AS and IgAN, robust epidemiological data remain limited. Previous studies have reported varying prevalence rates of IgAN among AS patients, but these studies are often constrained by small sample sizes and inconsistent methodologies. Establishing a causal relationship between AS and IgAN through conventional observational studies has proven challenging due to confounding factors and reverse causality. Mendelian randomization (MR) offers a promising alternative, utilizing genetic variants to explore causal relationships. This study employs MR combined with bioinformatics analysis to investigate the molecular link between AS and IgAN, aiming to identify potential therapeutic targets. Methods: Two publicly available datasets were utilized: a genome-wide association study (GWAS) of AS (dataset ID: ebi-a-GCST005529) with 9,069 AS cases and 13,578 controls, and IgAN data from the FinnGen project, which included 653 cases and 411,528 controls. Instrumental variables were selected based on stringent criteria. MR analysis was conducted using the inverse variance weighted, weighted median, and MR-Egger methods to assess the causal relationship between AS and IgAN. Reverse MR analysis and sensitivity analysis were conducted to validate the findings. Bioinformatics analysis involved acquiring gene expression data from the GEO database and identifying differentially expressed genes (DEGs) using the limma package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, protein-protein interaction (PPI) network construction, and hub gene identification were performed to elucidate the biological functions involved. Results: A total of 24 independent single-nucleotide polymorphisms (SNPs) associated with AS were identified through stringent SNP selection. MR analysis revealed a protective causal relationship between AS and IgAN (odds ratio = 0.552, 95% confidence interval, 0.339–0.900; p = 0.017). Analysis of DEGs identified 332 DEGs for IgAN and 5,521 DEGs for AS, with 59 common DEGs shared between the two diseases. Functional enrichment analysis highlighted significant changes in biological processes, cellular components, molecular functions, and KEGG pathways. PPI network analysis identified eight hub genes, including CX3CR1, which links AS and IgAN. External validation confirmed CX3CR1 as a crucial gene associated with both diseases. Conclusion: This study provides evidence of a protective causal relationship between AS and IgAN using MR analysis. Furthermore, bioinformatics analysis identifies CX3CR1 as a key gene, suggesting its role in mediating the protective link between AS and IgAN. These findings provide valuable insights into the molecular mechanisms underlying the connection between the two diseases and propose CX3CR1 as a potential therapeutic target for IgAN.

Risk of myocardial infarction and Osteoporosis: Insights from the 2015–2018 NHANES and Mendelian randomization Studies

IntroductionOmega-6 polyunsaturated fatty acids (PUFAs) represent almost 15% of the total energy intake in Western countries. Their effects on the cardiovascular (CV) risk factors are still controversial. Thus, we performed a systematic review and meta-analysis of randomized control trials (RCTs) as well as a Mendelian randomization (MR) analysis to evaluate the links and possible causality between supplementation or serum levels of omega-6 PUFA, CV disease (CVD) and cardiometabolic risk factors.Material and methodsSelected databases were searched until September 2019 to identify prospective studies investigating the effects of omega-6 PUFA supplementation on CVD events/mortality. Random-effects model meta-analysis was performed for quantitative data synthesis. Trial sequential analysis (TSA) was used to evaluate the optimal sample size to detect a 20% reduction in outcomes after administration of omega-6 PUFAs. The inverse variance weighted (IVW) method, weighted median-based method, MR-Egger and MR-Pleiotropy RESidual Sum and Outlier (PRESSO) were applied for MR.ResultsThe pooled estimate risk ratio (RR) of omega-6 PUFA supplementation was 0.94 for any CVD event (95% CI: 0.77–1.15, I2 = 66.2%), 1.06 for CVD death (95% CI: 0.73–1.55, I2 = 66.2%), 0.84 for coronary heart disease (CHD) events (95% CI: 0.61–1.16, I2 = 79.4%), 0.87 for myocardial infarction (MI) (95% CI: 0.74–1.01, I2 = 2.3%) and 1.36 for stroke (95% CI: 0.45–4.07, I2 = 55.3%). In contrast, MR showed that individuals with higher serum omega-6 acid – adrenic acid (AA) levels had a greater risk for CHD events (IVW β = 0.526), MI (IVW β = 0.606) and large artery stroke (IVW β = 1.694), as well as increased levels of fasting blood glucose (FBG) (IVW β = 0.417), low-density lipoprotein cholesterol (LDL-C) (IVW β = 0.806), high-density lipoprotein cholesterol (HDL-C) (IVW β = 0.820), and lower levels of triglycerides (TG) (IVW β = –1.064) and total cholesterol (TC) (IVW β = –1.064).ConclusionsOmega-6 PUFA supplementation did not affect the risk for CVD morbidity and mortality. Additionally, based on MR analysis we found that higher AA levels might even significantly increase the risk of CHD, MI and large artery stroke, as well as the levels of FBG and LDL-C, whereas they were negatively associated with TC and TG. Since a considerable chance of heterogeneity was observed for some of the results, further research is needed to elucidate the effects of omega-6 PUFAs on cardiometabolic outcomes.

This study aimed to address inconsistencies in results between the H9C2 myocardial hypoxia (MH) cell line and myocardial infarction (MI) rat models used in MI research. We identified differentially expressed genes (DEGs) and underlying molecular mechanisms using RNA sequencing technology. RNA sequencing was used to analyse DEGs in MI rat tissues and H9C2 cells exposed to hypoxia for 24h. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to identify key biological processes and pathways. Weighted correlation network analysis [weighted gene co-expression network analysis (WGCNA)] was used to construct gene co-expression networks, and hub genes were compared with published MI datasets [Gene Expression Omnibus (GEO)] for target identification. GO analysis revealed enrichment of immune inflammation and mitochondrial respiration processes among 5139 DEGs in MI tissues and 2531 in H9C2 cells. KEGG analysis identified 537 overlapping genes associated with metabolism and oxidative stress pathways. Cross-analyses using the published GSE35088 and GSE47495 datasets identified 40 and 16 overlapping genes, respectively, with nine genes overlapping across all datasets and our models. WGCNA identified a key module in the MI model enriched for mRNA processing and protein binding. GO analysis revealed enrichment of mRNA processing, protein binding and mitochondrial respiratory chain complex I assembly in MI and H9C2 MH models. Five relevant hub genes were identified via a cross-analysis between the 92 hub genes that showed a common expression trend in both models. This study reveals both shared and distinct transcriptomic responses in the MI and H9C2 models, highlighting the importance of model selection for studying myocardial ischaemia and hypoxia.

BackgroundType 2 diabetes mellitus (T2DM), a major risk factor of coronary heart disease, is associated with an approximately twofold increase in the risk of myocardial infarction (MI). We studied co-expressed genes to demonstrate relationships between DM and MI and revealed the potential biomarkers and therapeutic targets of T2DM-related MI.MethodsDM and MI-related differentially expressed genes (DEGs) were identified by bioinformatic analysis, Gene Expression Omnibus (GEO) datasets GSE42148 and GSE61144 of MI patients, and the normal control and GSE26168 and GSE15932 of DM patients and normal controls, respectively. Further target prediction and network analysis method were used to detect protein-protein interaction (PPI) networks, gene ontology (GO) terms, and pathway enrichment of DEGs. Co-expressed DEGs of T2DM-related MI were analyzed as well.ResultsWe identified 210 upregulated and 127 downregulated DEGs in T2DM, as well as 264 upregulated and 242 downregulated DEGs in MI. Eighteen upregulated and four downregulated DEGs were identified as co-DEGs of T2DM and MI. Functional analysis revealed that T2DM-related DEGs were mostly enriched in the viral process and ubiquitin-mediated proteolysis, while MI-related DEGs were mostly enriched in protein phosphorylation and TNF signaling pathway. MPO, MMP9, CAMP, LTF, AZU1, DEFA4, STAT3, and PECAM1 were recognized as the hub genes of the co-DEGs with acceptable diagnostic values in T2DM and MI datasets. Adenosine receptor agonist IB-MECA was predicted to be a potential drug for T2DM-related MI with the highest CMap connectivity score.ConclusionOur study identified that the co-DEGs of MPO, MMP9, CAMP, LTF, AZU1, DEFA4, STAT3, and PECAM1 are significantly associated with novel biomarkers involved in T2DM-related MI. However, more experimental research and clinical trials are demanded to verify our results.

Objective: To analyze the clinical characteristics,diagnosis and treatment of pediatric myocardial infarction (MI) patients with coronary artery lesions (CAL) after Kawasaki disease (KD). Methods: Clinical data including baseline characteristics, KD and CAL information, clinical symptoms at MI onset, electrocardiogram (ECG) and imaging findings, MI treatment, and clinical outcomes of 41 MI patients with CAL after KD admitted to the Children's Hospital of Fudan University from January 2017 to August 2024 were analyzed retrospectively. Results: (1) Demographic characteristics: a total of 41 patients were included (36 males and 5 females). The age at MI was 4.6 (2.3, 5.7) years, and time from KD onset to MI was 397 (50, 1 095) d. (2) Treatment of acute KD: only 15 patients (37%) received standard initial treatment within 10 days of KD onset with intravenous immunoglobulin 2 g/kg. The other 26 cases (63%) received non-standard treatment or no treatment. (3) Treatment of CAL before MI: the time from KD onset to CAL was 14 (10, 116) d, with CAL not identified before MI onset in 15 patients. Among the 26 cases diagnosed with CAL prior to MI, 9 cases received only single or dual antiplatelet drug, of which 7 cases received oral dipyridamole. The remaining 16 cases received antiplatelet drug combined with warfarin, but only 1 case achieved the target international standardized ratio of 1.5-2.5. Out of all 41 cases, only 1 case (2%) received standard antithrombotic treatment before MI onset. (4) Clinical symptoms of MI: at MI onset, 32 patients presented with different clinical symptoms, with typical MI symptoms such as chest tightness, chest pain, precordial discomfort in 18 cases, and cardiopulmonary arrest accompanied by syncope or convulsions in 10 cases. Other non-specific symptoms included abdominal pain, nausea, vomiting and pallor. Nine patients were asymptomatic and were found to have silent MI on follow-up. (5) ECG and imaging findings: ECG showed ST-T changes in 33 cases, and abnormal Q waves, and arrhythmias in the remaining patients; echocardiography indicated coronary artery aneurysm with thrombosis in 27 cases, reduced left ventricular ejection fraction in 18 cases, abnormal wall motion in 15 cases, and ventricular aneurysm in 3 cases. Thirty-seven patients underwent coronary angiography and (or) multi-slice spiral CT angiography, with 39 occluded vessels and 3 severe stenosis (≥75%), all of which were caused by giant aneurism with thrombus formation. (6) Treatment of MI: of the 32 patients with acute MI, 9 patients received successful cardiopulmonary resuscitation, 7 patients received intravenous thrombolysis, and 1 patient underwent percutaneous coronary balloon angioplasty. All of these patients received dual antiplatelet drugs and low-molecular-weight heparin at therapeutic doses following MI treatment. Sixteen patients received coronary artery bypass graft (CABG) treatment, all of which were successful. (7) Outcomes: the follow-up time was 994 (215, 1 832) d. Thirty-one patients showed improvement, 5 patients experienced disease progression or no change, 1 patient died, and 4 patients were lost to follow-up. Conclusions: MI in children with CAL after KD often occurs within 1 year after the onset of KD. MI can present with atypical clinical symptoms in children. CABG is the main treatment option in children severe CAL after KD who developed MI.

<i>Circulation: Cardiovascular Interventions</i> Editors’ Picks

Although a growing number of studies have shown that elevated uric acid (UA) levels are associated with multiple cardiovascular risk factors and progression of coronary artery disease, the causal relationship between UA and the occurrence of myocardial infarction (MI) remains uncertain. The aim of this study was to investigate the relationship between UA and the risk of MI. We screened 23,080 patients in the National Health and Nutrition Examination Survey (NHANES) database for 2009-2018 and explored the association between UA and MI risk using multivariate logistic regression model. In addition, a two-way two-sample Mendelian randomization (TSMR) analysis was performed to examine the causal relationship of UA on MI, and inverse variance-weighted (IVW) results were used as the primary outcome in this study. Sensitivity analysis and horizontal multiple validity test were also performed to verify the reliability of the results. After multivariable adjustment, individuals with the severe elevation of UA levels have a significantly increased risk of MI (OR=2.843, 95%CI: 1.296-6.237, P=0.010). In TSMR analysis, the IVW method demonstrated a significant association between UA and increased risk of MI (OR=1.333, 95%CI: 1.079-1.647, P=0.008). Results from the MR-Egger intercept test, Cochran's Q test, and MR-PRESSO test all suggest the reliability of the IVW analysis. Reverse TSMR analysis did not indicate a causal relationship between genetic susceptibility to MI and UA levels (IVW: OR=1.001, 95%CI: 0.989-1.012, P=0.922). Based on cross-sectional study and Mendelian randomization analysis, it has been demonstrated that UA is an independent risk factor for MI. Elevated levels of UA increase the risk of MI, particularly in cases of severe elevation.

BackgroundCutaneous melanoma (CM) is strongly associated with ultraviolet (UV) radiation, which contributes to the transformation of melanocytes into melanoma by inducing specific DNA damage. Here, we investigated the causal relationship between CM and genes related to sun-damaged skin, exploring specific target genes through various bioinformatics analyses.MethodsThe Gene Expression Omnibus (GEO) database was used to obtain differential genes for CM and normal skin, and the Genome-Wide Association Studies (GWAS) analysis offered summary-level melanoma data for CM. Mendelian randomization (MR) analyses were used to examine the correlated linkage between CM and sun-exposed skin genes. The MR studies were conducted mainly using Inverse Variance Weighting (IVW), MR-Egger, Weighted Median, simple and weighted patterns to predict the correlation between sun-exposed skin and CM. Finally, the role of target genes in CM was revealed by pan-cancer analysis, expression and immune-infiltration evaluations, immuno-checking targeting analysis, immunotherapy response analysis, survival analysis, and protein-protein interactions (PPI) network and enrichment analyses.ResultUsing matrix data from the GSE15605, GSE46517, and GSE111452 datasets, bioinformatics analysis revealed 232 differentially expressed genes (DEGs) between CM and typical tissues. MR analysis indicated that only CTSS has a deleterious effect linking skin exposure to sunlight and CM. Analysis of CTSS expression in tumors and tissues, along with the construction of a prognostic model, revealed that CTSS expression was higher in both primary CM and metastatic CM compared to normal skin tissue. However, patients with higher CTSS expression had a higher prognosis. In addition, high CTSS expression was significantly and positively correlated with tumor mutation rate, tumor microenvironment, immune cell infiltration, immune checkpoints and immunotherapy efficacy.ConclusionUsing MR analysis, we found a positive causal relationship between the CTSS gene in sun-exposed skin and CM. Additionally, increased CTSS may provide a basis for biomarker prediction of CM prognosis, immune status and immunotherapy.