The ACTB Variants and Alcohol Drinking Confer Joint Effect to Ischemic Stroke in Chinese Han Population

Identification of disulfidptosis-related genes and analysis of immune infiltration characteristics in ischemic strokes

Immune infiltration plays a pivotal role in the pathogenesis of ischemic stroke. A novel form of cell death known as disulfidptosis has emerged in recent studies. However, there is currently a lack of research investigating the regulatory mechanism of disulfidptosis-related genes in immune infiltration during ischemic stroke. Using machine learning methods, we identified candidate key disulfidptosis-related genes (DRGs). Subsequently, we performed an analysis of immune cell infiltration to investigate the dysregulation of immune cells in the context of ischemic stroke. We assessed their diagnostic value by employing receiver operating characteristic (ROC) curves. To gain further insights, we conducted functional enrichment analyses to elucidate the signaling pathways associated with these seven DRGs. We identified two distinct subclusters based on the expression patterns of these seven DRGs. The unique roles of these subclusters were further evaluated through KEGG analysis and immune infiltration studies. Furthermore, we validated the expression profiles of these seven DRGs using both single-cell datasets and external datasets. Lastly, molecular docking was performed to explore potential drugs for the treatment of ischemic stroke. We identified seven DRGs. The seven DRGs are related to immune cells. Additionally, these seven DRGs also demonstrate potential diagnostic value in ischemic stroke. Functional enrichment analysis highlighted pathways such as platelet aggregation and platelet activation. Two subclusters related to disulfidptosis were defined, and functional enrichment analysis of their differentially expressed genes (DEGs) primarily involved pathways like cytokine-cytokine receptor interaction. Single-cell analysis indicated that these seven DRGs were primarily distributed among immune cell types. Molecular docking results suggested that genistein might be a potential therapeutic drug. This study has opened up new avenues for exploring the causes of ischemic stroke and developing potential therapeutic targets.

Transcriptomic Analysis of Human Skeletal Muscle in Response to Aerobic Exercise and Protein Intake

This study aimed to provide a more comprehensive molecular insight into the effects of aerobic exercise (AE), protein intake (PI), and AE combined with PI on human skeletal muscle by comparing their transcriptomic profiles. Fourteen published datasets obtained from the Gene Expression Omnibus (GEO) database were used. The hub genes were identified in response to acute AE (ACTB, IL6), training AE (UBB, COL1A1), PI (EZH2), acute AE combined with PI (DDIT3), and training AE combined with PI (MYC). Both FOS and MYC were upregulated in response to acute AE, and they were, respectively, downregulated by higher PI and a combination of AE and PI. COL1A1 was upregulated by training AE but was downregulated by higher PI. Results from the gene set enrichment analysis (p < 0.05 and FDR < 25%) showed that AE and PI delivered their impacts on human skeletal muscle in analogous pathways, including aerobic respiration, mitochondrial complexes, extracellular matrix (ECM) remodeling, metabolic process, and immune/inflammatory responses, whereas, PI may attenuate the response of immune/inflammation and ECM remodeling which would be promoted by AE, irrespective of its types. Compared to PI alone, acute AE combined with PI would further promote protein turnover and synthesis, but suppress skeletal muscle contraction and movement.

β-Actin: An Emerging Biomarker in Ischemic Stroke

At present, the diagnosis of ischemic stroke mainly depends on neuroimaging technology, but it still has many limitations. Therefore, it is very important to find new biomarkers of ischemic stroke. Recently, β-actin has attracted extensive attention as a biomarker of a variety of cancers. Although several recent studies have been investigating its role in ischemic stroke and other cerebrovascular diseases, the understanding of this emerging biomarker in neurology is still limited. We examined human and preclinical studies to gain a comprehensive understanding of the literature on the subject. Most relevant literatures focus on preclinical research, and pay more attention to the role of β-actin in the process of cerebral ischemia, but some recent literatures reported that in human studies, serum β-actin increased significantly in the early stage of acute cerebral ischemia. This review will investigate the basic biology of β-actin, pay attention to the potential role of serum β-actin as an early diagnostic blood biomarker of ischemic stroke, and explore its potential mechanism in ischemic stroke and new strategies for stroke treatment in the future.

Gene-diet interactions and cardiovascular diseases: a systematic review of observational and clinical trials

BACKGROUND

Both genetic background and diet are important determinants of cardiovascular diseases (CVD). Understanding gene-diet interactions could help improve CVD prevention and prognosis. We aimed to summarise the evidence on gene-diet interactions and CVD outcomes systematically.

METHODS

We searched MEDLINE^® via Ovid, Embase, PubMed^®, and The Cochrane Library for relevant studies published until June 6th 2022. We considered for inclusion cross-sectional, case-control, prospective cohort, nested case-control, and case-cohort studies as well as randomised controlled trials that evaluated the interaction between genetic variants and/or genetic risk scores and food or diet intake on the risk of related outcomes, including myocardial infarction, coronary heart disease (CHD), stroke and CVD as a composite outcome. The PROSPERO protocol registration code is CRD42019147031.

RESULTS AND DISCUSSION

We included 59 articles based on data from 29 studies; six articles involved multiple studies, and seven did not report details of their source population. The median sample size of the articles was 2562 participants. Of the 59 articles, 21 (35.6%) were qualified as high quality, while the rest were intermediate or poor. Eleven (18.6%) articles adjusted for multiple comparisons, four (7.0%) attempted to replicate the findings, 18 (30.5%) were based on Han-Chinese ethnicity, and 29 (49.2%) did not present Minor Allele Frequency. Fifty different dietary exposures and 52 different genetic factors were investigated, with alcohol intake and ADH1C variants being the most examined. Of 266 investigated diet-gene interaction tests, 50 (18.8%) were statistically significant, including CETP-TaqIB and ADH1C variants, which interacted with alcohol intake on CHD risk. However, interactions effects were significant only in some articles and did not agree on the direction of effects. Moreover, most of the studies that reported significant interactions lacked replication. Overall, the evidence on gene-diet interactions on CVD is limited, and lack correction for multiple testing, replication and sample size consideration.

The association between ACTB methylation in peripheral blood and coronary heart disease in a case-control study

Background

Coronary heart disease (CHD) brings a heavy burden to society worldwide. Novel and minimally invasive biomarkers for the risk evaluation of CHD are urgently needed. Previous study has revealed that blood-based hypomethylation of β-actin (ACTB) was associated with increased risk of stroke, but not reported in CHD yet.

Objectives

We aimed to explore the association between blood-based ACTB methylation and the risk of CHD in a case-control study in the Chinese population.

Methods

The methylation level of ACTB was quantitatively determined by mass spectrometry in 281 CHD patients and 272 controls. The association between ACTB methylation and CHD risk was estimated by logistic regression analyses adjusted for possible confounding effects.

Results

We found a significant association between hypermethylation of ACTB in peripheral blood and increased risk of CHD (odds ratios (ORs) per +10% methylation: 1.19–1.45, p < 0.013 for nine out of thirteen CpG sites), especially in male subjects and heart failure (HF) patients (ORs per +10% methylation: 1.20–1.43, 1.38–1.46; p < 0.030, 1.52 × 10⁻⁴, respectively). Hypermethylation of ACTB_CpG_2.3, ACTB_CpG_7.8, and ACTB_CpG_9.10 was observed in the CHD patients with minor to medium cardiac function impairment (NYHA I&II CHD cases) (ORs per +10% methylation: 1.38–1.44; p < 0.001). The combination of ACTB_CpG_2.3, ACTB_CpG_7.8, and ACTB_CpG_9.10 methylation levels could efficiently discriminate CHD cases, male CHD patients, HF and NYHA I&II CHD patients from controls (area under curve (AUC) = 0.75, 0.74, 0.73, and 0.77, respectively).

Conclusions

Our study reveals a strong association between blood-based ACTB hypermethylation and CHD risk. The combination of ACTB methylation and conventional risk factors might provide a novel strategy to improve risk assessment of CHD.

lncRNA ADAMTS9-AS1/circFN1 Competitively Binds to miR-206 to Elevate the Expression of ACTB, Thus Inducing Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a genetic cardiac disease and can result in substantial disability. The current study explored the potentials of long noncoding RNA- (lncRNA-) circular RNA- (circRNA-) microRNA- (miRNA-) messenger RNA (mRNA) networks in HCM. Firstly, HCM-related microarray data were procured from the GEO database, with differentially expressed genes (DEGs) obtained. HCM-related target genes were retrieved in combination with GeneCards and CTD databases, and candidate target genes were subsequently obtained by intersection screening. Further, an interaction network diagram of candidate target genes was constructed using the STRING database, and the hub genes in the network were determined according to the core degree. The “ClusterProfiler” package of the R software was adopted for GO and KEGG analyses of candidate target genes, to analyze the potential molecular pathways in HCM. Next, upstream miRNA, lncRNA, and circRNA of ACTB were predicted with RNAInter, mirDIP, TargetScan, DIANA-LncBase, and StarBase databases, followed by construction of lncRNA/circRNA-miRNA-mRNA coexpression networks. ACTB, miR-206, circFN1, and ADAMTS9-AS1 expression in peripheral blood samples from HCM patients and normal healthy controls were detected using RT-qPCR. Moreover, rat cardiomyocyte cell lines H9c2 and HEK293 cells were selected for in vitro verification of competitive endogenous RNA (ceRNA) regulation mechanism. A total of 15 candidate target genes related to HCM were screened using the online databases. Further protein-protein interaction analysis identified ACTB as the hub gene for HCM. The targeted binding relationship between miR-206, miR-145-5p, miR-1-3p, and ACTB was found. Furthermore, ADAMTS9-AS1 and circFN1 were discovered as the upstream genes of miR-206. Moreover, ADAMTS9-AS1, circFN1, and ACTB were found to be poorly expressed, and miR-206 was highly expressed in HCM. In vitro experimentation further confirmed that ADAMTS9-AS1 and circFN1 could competitively bind to miR-206, thereby augmenting ACTB expression. Taken all, ADAMTS9-AS1/circFN1-miR-206-ACTB regulatory network may involve in HCM occurrence, providing a novel theoretical basis for in-depth understanding of mechanism of HCM.

The variants at FLNA and FLNB contribute to the susceptibility of hypertension and stroke with differentially expressed mRNA

BACKGROUND

Filamin A and filamin B were involved in vascular development and remodeling. Herein, it is important to explore the associations of FLNA and FLNB variants with hypertension and stroke.

METHODS

The associations of two single-nucleotide polymorphisms (SNPs) at FLNA and five SNPs at FLNB with hypertension and stroke were examined in two case-control studies and a cohort study in Chinese Han population. Risks were estimated as odds ratio (OR) and hazard ratio (HR) by Logistic and Cox regression analysis respectively. In addition, filamin B, FLNA and FLNB mRNA expression were measured.

RESULTS

In the case-control study of hypertension, FLNA rs2070816 (CT + TT vs. CC) and rs2070829 (CG + GG vs. CC) were significantly associated with hypertension in <55 years group (OR = 1.338, P = 0.018; OR = 1.615, P = 0.005) and FLNB rs839240 (AG + GG vs. AA) was significantly associated with hypertension in females (OR = 0.828, P = 0.041) and nonsmokers (OR = 0.829, P = 0.020). In the follow-up study, rs2070829 GG genotype carriers presented a higher risk of hypertension than CC/CG in males (HR = 1.737, P = 0.014) and smokers (HR = 1.949, P = 0.012). In the case-control study of stroke, FLNB rs1131356 variation was significantly associated with ischemic stroke (IS) and intracerebral hemorrhage (ICH), ORs of additive model were 1.342 and 1.451, with P values of 0.001 and 0.007. The FLNA transcript 2, FLNB transcript 3, transcript 4 mRNA, and filamin B expression levels were significantly different between IS cases and hypertension controls and among the genotypes of rs839240 in hypertensive individuals (P < 0.05).

CONCLUSIONS

Our findings support the genetic contribution of FLNA and FLNB to hypertension, and stroke with differentially mRNA expression.

ACTB Methylation in Blood as a Potential Marker for the Pre-clinical Detection of Stroke: A Prospective Nested Case-Control Study

Background

Stroke is the second leading cause of death worldwide. If risk of stroke could be evaluated early or even at a preclinical stage, the mortality rate could be reduced dramatically. However, the identified genetic factors only account for 5-10% of the risk of stroke. Studies on the risk factors of stroke are urgently needed. We investigated the correlation between blood-based β-actin (ACTB) methylation and the risk of stroke in a prospective nested case-control study.

Methods

The methylation level of ACTB was quantitatively determined by mass spectrometry in 139 stroke cases who developed stroke within 2 years after recruitment and 147 age- and sex-matched controls who remained stroke-free in a median follow-up of 2.71 years.

Results

We observed a highly significant correlation between hypomethylation of one CpG site of ACTB and increased risk of stroke in an onset-time-dependent manner (for onset time ≤ 1.5 years: odds ratio (OR) per + 10% methylation = 0.76, P = 0.001; for onset time ≤ 1.32 years: OR per + 10% methylation = 0.59, P = 7.82 × 10^-7; for onset time ≤ 1 year: OR per + 10% methylation = 0.43, P = 3.00 × 10^-6), and the increased cumulative incidence of stroke (log-rank P = 3.13 × 10^-7). Neighboring CpG sites showed an inverse correlation with age and drinking status in controls (P < 0.05) but not in stroke cases.

Conclusion

We firstly reported the blood-based ACTB methylation as a marker for the risk evaluation and preclinical detection of stroke, which can be further modified by age and drinking.

The Epidemiological and Mechanistic Understanding of the Neurological Manifestations of COVID-19: A Comprehensive Meta-Analysis and a Network Medicine Observation

The clinical characteristics and biological effects on the nervous system of infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain poorly understood. The aim of this study is to advance epidemiological and mechanistic understanding of the neurological manifestations of coronavirus disease 2019 (COVID-19) using stroke as a case study. In this study, we performed a meta-analysis of clinical studies reporting stroke history, intensive inflammatory response, and procoagulant state C-reactive protein (CRP), Procalcitonin (PCT), and coagulation indicator (D-dimer) in patients with COVID-19. Via network-based analysis of SARS-CoV-2 host genes and stroke-associated genes in the human protein-protein interactome, we inspected the underlying inflammatory mechanisms between COVID-19 and stroke. Finally, we further verified the network-based findings using three RNA-sequencing datasets generated from SARS-CoV-2 infected populations. We found that the overall pooled prevalence of stroke history was 2.98% (95% CI, 1.89-4.68; I 2=69.2%) in the COVID-19 population. Notably, the severe group had a higher prevalence of stroke (6.06%; 95% CI 3.80-9.52; I 2 = 42.6%) compare to the non-severe group (1.1%, 95% CI 0.72-1.71; I 2 = 0.0%). There were increased levels of CRP, PCT, and D-dimer in severe illness, and the pooled mean difference was 40.7 mg/L (95% CI, 24.3-57.1), 0.07 μg/L (95% CI, 0.04-0.10) and 0.63 mg/L (95% CI, 0.28-0.97), respectively. Vascular cell adhesion molecule 1 (VCAM-1), one of the leukocyte adhesion molecules, is suspected to play a vital role of SARS-CoV-2 mediated inflammatory responses. RNA-sequencing data analyses of the SARS-CoV-2 infected patients further revealed the relative importance of inflammatory responses in COVID-19-associated neurological manifestations. In summary, we identified an elevated vulnerability of those with a history of stroke to severe COVID-19 underlying inflammatory responses (i.e., VCAM-1) and procoagulant pathways, suggesting monotonic relationships, thus implicating causality.

The Probability of Ischaemic Stroke Prediction with a Multi-Neural-Network Model

As is known, cerebral stroke has become one of the main diseases endangering people’s health; ischaemic strokes accounts for approximately 85% of cerebral strokes. According to research, early prediction and prevention can effectively reduce the incidence rate of the disease. However, it is difficult to predict the ischaemic stroke because the data related to the disease are multi-modal. To achieve high accuracy of prediction and combine the stroke risk predictors obtained by previous researchers, a method for predicting the probability of stroke occurrence based on a multi-model fusion convolutional neural network structure is proposed. In such a way, the accuracy of ischaemic stroke prediction is improved by processing multi-modal data through multiple end-to-end neural networks. In this method, the feature extraction of structured data (age, gender, history of hypertension, etc.) and streaming data (heart rate, blood pressure, etc.) based on a convolutional neural network is first realized. A neural network model for feature fusion is then constructed to realize the feature fusion of structured data and streaming data. Finally, a predictive model for predicting the probability of stroke is obtained by training. As shown in the experimental results, the accuracy of ischaemic stroke prediction reached 98.53%. Such a high prediction accuracy will be helpful for preventing the occurrence of stroke.