Roles of Nicotine in the Development of Intracranial Aneurysm Rupture

Kamio, Yoshinobu; Miyamoto, Takeshi; Kimura, Toshikazu; Mitsui, Kazuha; Furukawa, Hajime; Zhang, Dingding; Yokosuka, Kimihiko; Korai, Masaaki; Kudo, Daisuke; Lukas, Ronald J.; Lawton, Michael T.; Hashimoto, Tomoki

doi:10.1161/strokeaha.118.021706

Cited by 36 publications

(27 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“… 33 Nicotine exposure may further promote aneurysmal rupture through actions on vascular smooth muscle cell nicotinic acetylcholine receptors containing α7 subunits. 34 Smoking might also affect CVD risk through antioestrogenic effects, observed in both women and men. 35–37 …”

Section: Discussionmentioning

confidence: 99%

Genetic predisposition to smoking in relation to 14 cardiovascular diseases

Larsson

Mason

Bäck

et al. 2020

European Heart Journal

115

View full text Add to dashboard Cite

Aims The aim of this study was to use Mendelian randomization (MR) to determine the causality of the association between smoking and 14 different cardiovascular diseases (CVDs). Methods and results Our primary genetic instrument comprised 361 single-nucleotide polymorphisms (SNPs) associated with smoking initiation (ever smoked regularly) at genome-wide significance. Data on the associations between the SNPs and 14 CVDs were obtained from the UK Biobank study (N = 367 643 individuals), CARDIoGRAMplusC4D consortium (N = 184 305 individuals), Atrial Fibrillation Consortium (2017 dataset; N = 154 432 individuals), and Million Veteran Program (MVP; N = 190 266 individuals). The main analyses were conducted using the random-effects inverse-variance weighted method and complemented with multivariable MR analyses and the weighted median and MR-Egger approaches. Genetic predisposition to smoking initiation was most strongly and consistently associated with higher odds of coronary artery disease, heart failure, abdominal aortic aneurysm, ischaemic stroke, transient ischaemic attack, peripheral arterial disease, and arterial hypertension. Genetic predisposition to smoking initiation was additionally associated with higher odds of deep vein thrombosis and pulmonary embolism in the UK Biobank but not with venous thromboembolism in the MVP. There was limited evidence of causal associations of smoking initiation with atrial fibrillation, aortic valve stenosis, thoracic aortic aneurysm, and intracerebral and subarachnoid haemorrhage. Conclusion This MR study supports a causal association between smoking and a broad range of CVDs, in particular, coronary artery disease, heart failure, abdominal aortic aneurysm, ischaemic stroke, transient ischaemic attack, peripheral arterial disease, and arterial hypertension.

show abstract

Section: Discussionmentioning

confidence: 99%

Genetic predisposition to smoking in relation to 14 cardiovascular diseases

Larsson

Mason

Bäck

et al. 2020

European Heart Journal

115

View full text Add to dashboard Cite

show abstract

“…Differences in aneurysm morphology and size have been proposed between smoking and non-smoking patients 8 , 9 . It is thought that nicotine promotes local inflammation and sustained angiogenesis, resulting in downstream changes and alteration of aneurysm morphology 10 . Here, we present a large cohort of 505 patients with anterior communicating artery (ACoA) aneurysms to assess morphological features associated with ruptured aneurysms, as well as, the association of patient characteristics, including age and tobacco use, with those morphological features.…”

Section: Introductionmentioning

confidence: 99%

Tobacco use and age are associated with different morphologic features of anterior communicating artery aneurysms

Zhang

Lai

Can

et al. 2021

Sci Rep

View full text Add to dashboard Cite

We present a cohort of patients with anterior communicating artery (ACoA) aneurysms to investigate morphological characteristics and clinical factors associated with rupture of the aneurysms. 505 patients with ACoA aneurysms were identified at the Brigham and Women’s Hospital and Massachusetts General Hospital between 1990 and 2016, with available CT angiography (CTA). Three-dimensional (3D) reconstructions were performed to evaluate aneurysmal morphologic features, including location, projection, irregularity, the presence of daughter dome, height, height/width ratio, and relationships between surrounding vessels. Patient risk factors assessed included patient age, sex, tobacco use, alcohol use, and family history of aneurysms and aneurysmal subarachnoid hemorrhage. Logistic regression was used to build a predictive ACoA score for rupture. Morphologic features associated with ruptured ACoA aneurysms were the presence of a daughter dome (OR 21.4, 95% CI 10.6–43.1), smaller neck diameter (OR 0.55, 95% CI 0.42–0.71), larger aspect ratio (OR 3.57, 95% CI 2.05–6.24), larger flow angle (OR 1.03, 95% CI 1.02–1.05), and smaller ipsilateral A2-ACoA angle (OR 0.98, 95% CI 0.97–1.00). Tobacco use was predominantly associated with morphological factors intrinsic to the aneurysm that were associated with rupture while younger age was also associated with morphologic features extrinsic to the aneurysm that were associated with rupture. The ACoA score had good predictive capacity for rupture with AUC = 0.92 using the 0.632 bootstrap cross-validation for correction of overfitting bias. Ruptured ACoA aneurysms were associated with morphological features that are simple to assess using a simple scoring system. Tobacco use and younger age were predominantly associated with intrinsic and extrinsic morphological features characteristic of rupture, respectively.

show abstract

“…[57][58][59] Indeed two genes in our model, LRRN3 and GPR15, are among the top differentially expressed genes in blood between current and never smokers according to a meta-analysis by Huan et al 60 Their presence in our predictive model may be because of the higher proportion of smokers in IA group or because these genes are capturing biological mechanisms related to smoking that are important in IA pathogenesis, such as endothelial dysfunction. [61][62][63] Still, when we performed covariate analysis using MatchIt to create subgroups with similar distributions of covariates between IA and control groups, we found that no one subgroup had signi cantly higher misclassi cation rates. For instance, 61% of all subjects in "Subclass 5" were smokers, and this subgroup had a misclassi cation rate of 13%.…”

Section: Discussionmentioning

confidence: 91%

Classification Models using Circulating Neutrophil Transcripts Can Detect Unruptured Intracranial Aneurysm

Poppenberg

Tutino

Li³

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Intracranial aneurysms (IAs) are dangerous because of their potential to rupture. We previously found significant RNA expression differences in circulating neutrophils between patients with and without unruptured IAs and trained machine learning models to predict presence of IA using 40 neutrophil transcriptomes. Here, we aim to develop a predictive model for unruptured IA using neutrophil transcriptomes from a larger population and more robust machine learning methods. Methods: Neutrophil RNA extracted from the blood of 134 patients (55 with IA, 79 IA-free controls) was subjected to next-generation RNA sequencing. In a randomly-selected training cohort (n=94), the Least Absolute Shrinkage and Selection Operator (LASSO) selected transcripts, from which we constructed prediction models via 4 well-established supervised machine-learning algorithms (K-Nearest Neighbors, Random Forest, and Support Vector Machines with Gaussian and cubic kernels). We tested the models in the remaining samples (n=40) and assessed model performance by receiver-operating-characteristic (ROC) curves. Real-time quantitative polymerase chain reaction (RT-qPCR) of 9 IA-associated genes was used to verify gene expression in a subset of 49 neutrophil RNA samples. We also examined the potential influence of demographics and comorbidities on model prediction. Results: Feature selection using LASSO in the training cohort identified 37 IA-associated transcripts. Models trained using these transcripts had a maximum accuracy of 90% in the testing cohort. The testing performance across all methods had an average area under ROC curve (AUC)=0.97, an improvement over our previous models. The Random Forest model performed best across both training and testing cohorts. RT-qPCR confirmed expression differences in 7 of 9 genes tested. Gene ontology and IPA network analyses performed on the 37 model genes reflected dysregulated inflammation, cell signaling, and apoptosis processes. In our data, demographics and comorbidities did not affect model performance. Conclusions: We improved upon our previous IA prediction models based on circulating neutrophil transcriptomes by increasing sample size and by implementing LASSO and more robust machine learning methods. Future studies are needed to validate these models in larger cohorts and further investigate effect of covariates.

show abstract

Roles of Nicotine in the Development of Intracranial Aneurysm Rupture

Cited by 36 publications

References 41 publications

Genetic predisposition to smoking in relation to 14 cardiovascular diseases

Genetic predisposition to smoking in relation to 14 cardiovascular diseases

Tobacco use and age are associated with different morphologic features of anterior communicating artery aneurysms

Classification Models using Circulating Neutrophil Transcripts Can Detect Unruptured Intracranial Aneurysm

Contact Info

Product

Resources

About