Li Rao

Review Article Mitophagy in cardiovascular diseases: a literature review Ran Zhang, Junyan Zhang, Shuangliang Ma, Li Rao, Zhongxiu Chen

Background: Coronary heart disease (CHD) remains a leading cause of morbidity and mortality worldwide. Mitochondria-associated endoplasmic reticulum membranes (MAMs) have recently emerged as critical mediators in cardiovascular pathophysiology; however, their specific contributions to CHD pathogenesis remain largely unexplored. Objective: This study aimed to identify and validate MAM-related biomarkers in CHD through integrated analysis of transcriptomic sequencing data and Mendelian randomization, and to elucidate their underlying mechanisms. Methods: We analyzed two gene expression microarray datasets (GSE113079 and GSE42148) and one genome-wide association study (GWAS) dataset (ukb-d-I9_CHD) to identify differentially expressed genes (DEGs) associated with CHD. MAM-related DEGs were filtered using weighted gene co-expression network analysis (WGCNA). Functional enrichment analysis, Mendelian randomization, and machine learning algorithms were employed to identify biomarkers with direct causal relationships to CHD. A diagnostic model was constructed to evaluate the clinical utility of the identified biomarkers. Additionally, we validated the two hub genes in peripheral blood samples from CHD patients and normal controls, as well as in aortic tissue samples from a low-density lipoprotein receptor-deficient (LDLR−/−) atherosclerosis mouse model. Results: We identified 4174 DEGs, from which 3326 MAM-related DEGs (DE-MRGs) were further filtered. Mendelian randomization analysis coupled with machine learning identified two biomarkers, DHX36 and GPR68, demonstrating direct causal relationships with CHD. These biomarkers exhibited excellent diagnostic performance with areas under the receiver operating characteristic (ROC) curve exceeding 0.9. A molecular interaction network was constructed to reveal the biological pathways and molecular mechanisms involving these biomarkers. Furthermore, validation using peripheral blood from CHD patients and aortic tissues from the Ldlr−/− atherosclerosis mouse model corroborated these findings. Conclusions: This study provides evidence supporting a mechanistic link between MAM dysfunction and CHD pathogenesis, identifying candidate biomarkers that have the potential to serve as diagnostic tools and therapeutic targets for CHD. While the validated biomarkers offer valuable insights into the molecular pathways underlying disease development, additional studies are needed to confirm their clinical relevance and therapeutic potential in larger, independent cohorts.

Background: Patients classified as having a high bleeding risk (HBR) and undergoing percutaneous coronary intervention (PCI) face a significantly greater incidence of net adverse clinical events (NACEs) than non-HBR patients do. Existing risk assessment models, such as the CRUSADE and TIMI scores, do not adequately address the unique risks faced by the HBR population. There is an urgent need for a precise and comprehensive predictive model tailored to PCI-HBR patients to guide clinical decision-making and improve patient outcomes. Methods: This study aimed to develop a machine learning-based predictive model for long-term NACE in PCI-HBR patients. We utilized data from the Prognostic Analysis and an Appropriate Antiplatelet Strategy for Patients with Percutaneous Coronary Intervention and High Bleeding Risk registry database. Feature selection and interpretation were performed via a SHapley Additive exPlanations (SHAP) model based on recursive feature elimination. Model construction and evaluation were conducted via four algorithms: logistic regression, random forest, gradient boosting, and XGBoost. Results: A total of 1512 PCI-HBR patients were included in the study. The XGBoost model demonstrated the highest predictive performance, achieving an area under the receiver operating characteristic curve of 0.85. The SHAP model identified 24 significant variables contributing to the prediction of NACE, including clinical parameters, laboratory findings, and echocardiographic data. Conclusions: Our machine learning-based model offers a promising tool for predicting long-term NACE in PCI-HBR patients. The model’s high predictive accuracy and interpretability have the potential to enhance clinical decision-making and improve patient care. Further validation in larger, diverse populations is warranted to confirm these findings.

Diagnosing and treating recurrent pericardial effusion (PE) have been challenging in clinical practice. This study presents a middle-aged male with long-term refractory PE without apparent cause and non-specific symptoms, and eventually diagnosed as Hennekam lymphangiectasia with lymphedema syndrome (HKLLS). He underwent anti-tuberculosis diagnostic treatment and non-steroidal anti-inflammatory drugs for nonspecific PE, and thoracic duct exploration, terminal adhesion lysis, and anastomosis of the tributary vertebral vein of the thoracic duct for suspected protein-losing enteropathy and intestinal lymphangiectasia in other hospitals 17 and 11 years ago, but with no satisfactory outcomes. During the disease course, laboratory tests showed decreased blood albumin and increased stool α1-antitrypsin, while endoscopy biopsies were normal. The patient's complex medical history underscores the diagnostic challenges. The whole-exome sequencing identified two mutations within the collagen and calcium-binding EGF-like domain-containing protein 1 (CCBE1) gene, diagnosing HKLLS type 1. This case enriches the understanding of the link between HKLLS and recurrent PE, highlighting the significance of whole-exome sequencing in diagnosing recurrent PE when traditional methods fall short. It also reminds clinicians to consider rare genetic disorders like HKLLS in the differential diagnosis of recurrent PE, even without typical symptoms.

Purpose Spironolactone has been reported to increase the risk of upper gastrointestinal bleeding in patients. We aimed to validate this perspective in a population of patients undergoing percutaneous coronary intervention with high bleeding risk (PCI-HBR). Methods We prospectively included a total of 1616 PCI-HBR patients who were treated at West China Hospital of Sichuan University from May 2022 to July 2024. These patients were divided into a spironolactone treatment group (n = 301) and a non-spironolactone treatment group (n = 1315). A propensity score matching was performed at a 1:4 ratio, and Cox regression analysis was conducted on the matched data. Additionally, Kaplan–Meier curves were plotted to evaluate the direct correlation between spironolactone use and gastrointestinal bleeding. And the subgroup analysis is used to assess the robustness of the results. Results In this study, after propensity score matching, a total of 927 patients were included in the outcome analysis, with 259 in the spironolactone group and 668 in the non-spironolactone group. Throughout the follow-up period, 14 (5.4%) and 42 (6.3%) patients experienced BARC 2–5 gastrointestinal bleeding events in the spironolactone and non-spironolactone groups, respectively, while 6 (2.3%) and 24 (3.6%) patients experienced BARC 3–5 gastrointestinal bleeding. The incidence of BARC 2–5 gastrointestinal bleeding was comparable between the groups (14/259 [5.4%] vs. 42/668 [6.3%]; HR 0.88 [0.48–1.62], p = 0.689), as was the incidence of BARC 3–5 gastrointestinal bleeding (6/259 [2.3%] vs. 24/668 [3.6%]; HR 0.69 [0.28–1.68], p = 0.410). No statistically significant interactions were found between spironolactone use and clinical variables such as acute coronary syndrome, diabetes, and chronic kidney disease concerning the risk of gastrointestinal bleeding. Conclusions In summary, our prospective cohort study, which used propensity score matching, represents the first comprehensive investigation of spironolactone usage in PCI-HBR patients. Our results underscore that cardiologists need not routinely consider the risk of spironolactone-induced bleeding when making decisions about its use in patients. Larger randomized trials or analyses from existing randomized trials on spironolactone are warranted to draw definitive conclusions about the potential association between spironolactone and bleeding.

Cardiovascular disease has become to the main cause of death in the patients with end-stage renal disease (ESRD), and anemia is associated with increased cardiovascular morbidity and mortality in these patients. This study aimed to explore the impact of anemia on myocardial fibrosis using T1 mapping technique in patients with ESRD. A total of 128 subjects including 98 ESRD patients (65 with anemia, 33 without anemia) and 30 normal controls were enrolled. All subjects were underwent cardiovascular magnetic resonance to obtain cardiac cine and T1 mapping images. As potential markers of fibrosis, native T1 values and global longitudinal strain derived by feature-tracking technique were compared. Differences between 3 groups were analyzed using one-way analysis of variance. Associations between variables were assessed by Pearson and Spearman correlation coefficient appropriately. An independent association was identified by the multiple stepwise linear regression analysis. Intraclass correlation was applied to assess observer variability. In all ESRD patients, native T1 values were significantly longer than those of normal controls (global T1, 1357 ± 42 ms vs 1275 ± 48 ms, P < .001). Global T1 value in ESRD patients with anemia was significantly higher (1375 ± 36 ms) compared to that in ESRD patients without anemia (1322 ± 25 ms) and normal controls (1275 ± 48 ms), respectively (all P < .001). Global T1 correlated with hemoglobin negatively (R= −0.499, P < .001). Multiple stepwise linear regression analysis presented the anemia is independently associated with global T1 (R = 0.607, P < .001). Global longitudinal strain was remarkably reduced in ESRD patients with anemia in comparison to those without anemia (P < .001). Diffuse myocardial fibrosis could be detected by native T1 mapping in ESRD patients with long-term anemia. Anemia is an important factor in myocardial fibrosis in ESRD patients, and the evaluation of myocardial involvement is worth considering for clinical management.

Meticulous understanding of the mechanisms underpinning mitral regurgitation in atrial fibrillation (AF) patients is crucial to optimize therapeutic strategies. The morphologic characteristics of mitral valves in atrial functional mitral regurgitation (FMR) patients with and without left ventricular (LV) dysfunction were evaluated by high volume rate (HVR) three-dimensional transesophageal echocardiography (3D-TEE). In our study, 68 of 265 AF patients who underwent 3D-TEE were selected, including 36 patients with AF, FMR, and preserved LV function (AFMR group) and 32 patients with AF, FMR, and LV dysfunction (VFMR group). In addition, 36 fever patients without heart disease were included in the control group. Group comparisons were performed by one-way analysis of variance for continuous variables. The left atrium (LA) was enlarged in the AFMR and VFMR groups compared with the control group. The mitral annulus (MA) in the AFMR group was enlarged and flattened compared with the control group and was smaller than in the VFMR group. The annulus area fraction was significantly diminished in the AFMR and VFMR groups, indicative of reduced MA contractility. The posterior mitral leaflet (PML) angle was smallest in the AFMR group and largest in the control group, whereas the distal anterior mitral leaflet angle did not significantly differ among the three groups. LA remodeling causes expansion of the MA and reduced MA contractility, disruption of the annular saddle shape, and atriogenic PML tethering. Comparison of atrial FMR patients with and without LV dysfunction indicates that atriogenic PML tethering is an important factor that aggravates FMR. HVR 3D-TEE improves the 3D temporal resolution greatly.

Background. Dilated cardiomyopathy is a primary myocardial disease and one of the critical causes of heart failure. It is the most common indication for heart transplantation worldwide, and most idiopathic dilated cardiomyopathies are sporadic and multifactorial. Evidence has supported that several inflammatory cytokines and immune responses are involved in its pathological process. Interleukin-32 is a proinflammatory cytokine and is elevated during the worsening cardiac function. Herein, we evaluated the correlation between interleukin-32 gene polymorphisms (rs12934561 and rs28372698) and the susceptibility to dilated cardiomyopathy. Methods. We enrolled 418 dilated cardiomyopathy patients and 437 healthy controls. The polymerase chain reaction-restriction fragment length polymorphism method was used for genotyping the two single-nucleotide polymorphisms (SNPs), and SPSS software was used for statistical analyses. Results. The C allele and CC genotype frequencies of rs12934561 were remarkably elevated in dilated cardiomyopathy patients compared to controls (both ). The A allele and AA genotype frequencies of rs28372698 significantly decreased in dilated cardiomyopathy patients ( and , respectively). Compared to TT/TC genotype carriers of rs12934561, CC homozygotes presented an increased risk of dilated cardiomyopathy when the left ventricular ejection fraction no more than 30% ( ). Conclusions. The IL-32 gene polymorphisms might implicate in DCM risk in the Chinese Han population, and rs12934561 could be a potential forecasting factor for screening high-risk population for DCM.

Aims: This study aimed to investigate the influencing factors of frailty in elderly patients with multimorbidity and to develop a predictive risk model for frailty in elderly patients with multimorbidity.Methods: In total, 3836 elderly patients with multimorbidity who were admitted to the medical wards of five grade A tertiary hospitals in Sichuan Province from March 2020 to June 2021 were selected. Based on the general data of patients with multimorbidity, the independent risk factors for frailty were obtained using logistic analysis, and a risk prediction model of frailty was developed.Results: Independent risk factors for frailty in patients with multimorbidity were age, types of medication, and comorbidity with chronic heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic cerebrovascular disease (CCVD); and the protective factors for frailty were body mass index (BMI), exercise and education level. The expression of the model was Z = −2.054 + 0.016 × age − 0.029 × BMI − 0.153 × education level‐1.059 × exercise + 0.203 × types of medication + 0.788 × comorbidity with CHF + 0.950 × comorbidity with COPD + 0.363 × comorbidity with CCVD.Conclusion: Age, BMI, education level, exercise, types of medication, and comorbidity with CHF, COPD and CCVD can affect frailty risk in elderly patients with multimorbidity, which may be helpful to predict the frailty risk of elderly patients with multimorbidity. Geriatr Gerontol Int 2022; 22: 471–476.