High glutamine increases stroke risk by inducing the endothelial-to-mesenchymal transition in moyamoya disease.

At present, there is limited research on the mechanisms underlying moyamoya disease (MMD). Herein, we aimed to determine the role of glutamine in MMD pathogenesis, and 360 adult patients were prospectively enrolled. Human brain microvascular endothelial cells (HBMECs) were subjected to Integrin Subunit Beta 4 (ITGB4) overexpression or knockdown and atorvastatin. We assessed factors associated with various signaling pathways in the context of the endothelial-to-mesenchymal transition (EndMT), and the expression level of related proteins was validated in the superficial temporal arteries of patients. We found glutamine levels were positively associated with a greater risk of stroke (OR = 1.599, p = 0.022). After treatment with glutamine, HBMECs exhibited enhanced proliferation, migration, and EndMT, all reversed by ITGB4 knockdown. In ITGB4-transfected HBMECs, the MAPK-ERK-TGF-ß/BMP pathway was activated, with Smad4 knockdown reversing the EndMT. Furthermore, atorvastatin suppressed the EndMT by inhibiting Smad1/5 phosphorylation and promoting Smad4 ubiquitination in ITGB4-transfected HBMECs. We also found the protein level of ITGB4 was upregulated in the superficial temporal arteries of patients with MMD. In conclusion, our study suggests that glutamine may be an independent risk factor for hemorrhage or infarction in patients with MMD and targeting ITGB4 could potentially be therapeutic approaches for MMD.

Glymphatic Impairment Associated with Neurocognitive Dysfunction in Moyamoya Disease.

Glymphatic system alterations have been proved to be associated with cognitive dysfunction in neurodegenerative diseases. The glymphatic pathway has not been elucidated in moyamoya disease (MMD), which was recognized as a chronic hypoperfusion model for neurodegenerative disease. Here, we aimed to investigate the glymphatic system activity and its relation with neurocognition, and associated hallmarks in MMD. We prospectively recruited 30 MMD patients and 30 matched healthy controls (HC). Participants underwent MRI and neurocognition evaluation. The glymphatic function was assessed by diffusion tensor image analysis along perivascular space (DTI-ALPS) index. Gray matter volume (GMV) and microstructural alterations were calculated. Neurodegenerative-related serum biomarkers were examined. The mediation effect of ALPS index in the associations between variables and neurocognition were further explored. A lower ALPS index was identified in patients with MMD (P < 0.001). The decreased ALPS index was significantly correlated with declined neurocognitive performance. Moreover, the reduced ALPS index was notably linked with lower total GMV% and deep GMV% (P < 0.01). Microstructural changes in the periventricular areas were detected and associated with ALPS index in MMD. Serum neurodegenerative biomarkers (ApoE, Aß40, Aß42, and Aß42/Aß40) were significantly elevated and related to ALPS index. Additionally, the ALPS index significantly mediated the associations of microstructural alterations and ApoE level with neurocognitive dysfunction. The ALPS index was notably lower MMD in patients, suggesting the utility as a marker of potential glymphatic dysfunction. The index acted as a significant mediator in neurocognitive dysfunction. These findings indicated that glymphatic impairment may interact with MMD-related pathophysiological processes.

Multiomics and blood-based biomarkers of moyamoya disease: protocol of Moyamoya Omics Atlas (MOYAOMICS).

BACKGROUND: Moyamoya disease (MMD) is a rare and complex cerebrovascular disorder characterized by the progressive narrowing of the internal carotid arteries and the formation of compensatory collateral vessels. The etiology of MMD remains enigmatic, making diagnosis and management challenging. The MOYAOMICS project was initiated to investigate the molecular underpinnings of MMD and explore potential diagnostic and therapeutic strategies. METHODS: The MOYAOMICS project employs a multidisciplinary approach, integrating various omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, to comprehensively examine the molecular signatures associated with MMD pathogenesis. Additionally, we will investigate the potential influence of gut microbiota and brain-gut peptides on MMD development, assessing their suitability as targets for therapeutic strategies and dietary interventions. Radiomics, a specialized field in medical imaging, is utilized to analyze neuroimaging data for early detection and characterization of MMD-related brain changes. Deep learning algorithms are employed to differentiate MMD from other conditions, automating the diagnostic process. We also employ single-cellomics and mass cytometry to precisely study cellular heterogeneity in peripheral blood samples from MMD patients. CONCLUSIONS: The MOYAOMICS project represents a significant step toward comprehending MMD's molecular underpinnings. This multidisciplinary approach has the potential to revolutionize early diagnosis, patient stratification, and the development of targeted therapies for MMD. The identification of blood-based biomarkers and the integration of multiple omics data are critical for improving the clinical management of MMD and enhancing patient outcomes for this complex disease.

Gut microbiota in adults with moyamoya disease: characteristics and biomarker identification.

Background and purpose: When it comes to the onset of moyamoya disease (MMD), environmental variables are crucial. Furthermore, there is confusion about the relationship between the gut microbiome, an environmental variable, and MMD. Consequently, to identify the particular bacteria that cause MMD, we examined the gut microbiome of MMD individuals and healthy controls (HC). Methods: A prospective case-control investigation was performed from June 2021 to May 2022. The fecal samples of patients with MMD and HC were obtained. Typically, 16S rRNA sequencing was employed to examine their gut microbiota. The QIIME and R softwares were used to examine the data. The linear discriminant analysis effect size analysis was used to determine biomarkers. Multivariate analysis by linear models (MaAsLin)2 were used to find associations between microbiome data and clinical variables. Model performance was assessed using the receiver operating characteristic curve and the decision curve analysis. Results: This investigation involved a total of 60 MMD patients and 60 HC. The MMD group's Shannon and Chao 1 indices were substantially lower than those of the HC cohort. ß-diversity was significantly different in the weighted UniFrac distances. At the phylum level, the relative abundance of Fusobacteriota/Actinobacteria was significantly higher/lower in the MMD group than that in the HC group. By MaAsLin2 analysis, the relative abundance of the 2 genera, Lachnoclostridium and Fusobacterium, increased in the MMD group, while the relative abundance of the 2 genera, Bifidobacterium and Enterobacter decreased in the MMD group. A predictive model was constructed by using these 4 genera. The area under the receiver operating characteristic curve was 0.921. The decision curve analysis indicated that the model had usefulness in clinical practice. Conclusions: The gut microbiota was altered in individuals with MMD, and was characterized by increased abundance of Lachnoclostridium and Fusobacterium and decreased abundance of Bifidobacterium and Enterobacter. These 4 genera could be used as biomarkers and predictors in clinical practice.

Association between systemic immune-inflammatory markers and the risk of moyamoya disease: a case-control study.

Background:Systemic immune-inflammatory markers such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR) and systemic immune-inflammatory index (SII) are associated with the prognosis of many cardiovascular and neoplastic diseases. Moyamoya disease (MMD) is associated with inflammation, but the relationship between systemic immune-inflammatory markers between MMD is unclear. The aim of our study was to analyse the association between systemic immune-inflammatory markers and the risk of MMD and its subtypes.Methods:We consecutively recruited 360 patients with MMD and 89 healthy control subjects in a case-control study to calculate and analyse the association of systemic immune-inflammatory markers with the risk of MMD and its subtypes.Results:The risk of MMD increased with higher levels of NLR (OR 1.237, 95% CI [1.008, 1.520], p = .042). When NLR and SII were assessed as quartile-spaced subgroups, the third quartile grouping of NLR and SII had a higher risk of MMD than the first quartile grouping (NLR: OR 3.206, 95% CI [1.271, 8.088], p = .014; SII: OR 3.074,95% CI [1.232,7.672], p = .016). When NLR was combined with SII, the highest subgroup had a higher risk of MMD than the lowest subgroup (OR2.643, 95% CI [1.340, 5.212], p = .005). The risk of subtypes also increased with higher levels of NLR and SII. The association between the levels of NLR and SII with the staging of the Suzuki stage follows an inverted U-shape. The highest levels of NLR and SII were found in patients with MMD at Suzuki stages 3-4.Conclusion:The risk of MMD increases with elevated systemic immune-inflammatory markers. This study analysed the association of systemic immune-inflammatory markers with the risk of developing MMD and its subtypes, and identified novel inflammatory markers for MMD.

Systemic immune-inflammatory markers such as neutrophil­lymphocyte ratio and systemic immune-inflammatory index were higher in moyamoya disease (MMD) patients than in normal people.Systemic immune-inflammatory markers may be an independent risk factor for the onset of MMD.Systemic immune-inflammatory markers were associated with the progression of MMD, and their levels showed an inverted U shape with imaging stages.

The prognostic nutrition index is a predictor for long-term outcomes after revascularization in adult moyamoya disease.

BACKGROUND AND PURPOSE: The prognostic nutrition index (PNI) has been associated with the prognosis of various medical disorders. This study aimed to explore the correlation between PNI and the long-term outcomes of adult patients afflicted with moyamoya disease (MMD). METHODS: This prospective study initially employed 138 adult patients diagnosed with MMD. After excluding 15 patients who did not meet the criteria, a total of 123 patients were included. Participants were divided into three groups based on the tertile of change in the PNI score. Statistical analysis compared clinical information and lab tests among the groups. The study was conducted between July 1 and December 31, 2019. RESULTS: After adjusting for multiple variables, patients in the upper two tertiles (tertiles 2-3) exhibited a significantly lower risk of adverse long-term outcomes compared to those in the lowest tertile (tertile 1) (OR, 0.089; 95% CI, 0.009-0.895; P = 0.040). Furthermore, adding PNI tertile to traditional risk factors substantially improved predicting adverse long-term outcomes (net reclassification improvement: 98.03%, P = 0.000; integrated discrimination improvement: 4.65%, P = 0.030). However, there was no statistically significant difference between the first PNI tertile (tertile 1) and the upper two tertiles (tertiles 2-3) in the Kaplan-Meier curve of stroke incidence (log-rank test, P = 0.244). CONCLUSIONS: A higher PNI level was significantly associated with a reduced risk of unfavorable long-term outcomes. Nevertheless, the PNI score did not predict stroke recurrence during extended follow-up. This study provides insights into a potential predictor of adverse long-term outcomes after revascularization in MMD patients. REGISTRATION NUMBER: ChiCTR2000031412.

Plasma urea cycle metabolite levels and the risk of moyamoya disease.

Background and purpose: Urea cycle metabolites are expected to be the biomarkers for cerebrovascular diseases. However, the effects of circulating urea cycle metabolites on the risk of MMD and its subcategories remain unclear. The aim of this study was to prospectively investigate the association between plasma urea cycle metabolites and the risk of MMD and its subcategories. Methods: We measured plasma urea cycle metabolite levels for 360 adult MMD patients and 89 matched healthy controls. Clinical and laboratory characteristics were obtained from the medical record. The study was conducted from July 2020 to December 2021. Results: After multivariate adjustment, the risk of MMD increased with each increment in ornithine level (per natural log [ornithine] increment: OR, 3.893; 95% CI, 1.366-11.090). The risk of MMD decreased with each increment in arginine level (per natural log [arginine] increment: OR, 0.109; 95% CI, 0.028-0.427), urea level (per natural log [urea] increment: OR, 0.261; 95% CI, 0.072-0.940), and global arginine bioavailability ratio (GABR) level (per natural log [GABR] increment: OR, 0.189; 95% CI, 0.074-0.484). The addition of plasma arginine (integrated discrimination improvement: 1.76%, p = 0.021) or GABR (integrated discrimination improvement: 1.76%, p = 0.004) to conventional risk factors significantly improved the risk reclassification for MMD. Conclusion: Plasma ornithine levels are positively associated with the risk of MMD. By contrast, the levels of arginine, urea, and GABR are inversely related to the risk of MMD. Plasma urea cycle metabolites might be potential biomarkers for the risk of MMD.

Corrigendum: Development and validation of a model for predicting the risk of brain arteriovenous malformation rupture based on three-dimensional morphological features.

[This corrects the article DOI: 10.3389/fneur.2022.979014.].

CT Angiography Radiomics Combining Traditional Risk Factors to Predict Brain Arteriovenous Malformation Rupture: a Machine Learning, Multicenter Study.

This study aimed to develop a machine learning model for predicting brain arteriovenous malformation (bAVM) rupture using a combination of traditional risk factors and radiomics features. This multicenter retrospective study enrolled 586 patients with unruptured bAVMs from 2010 to 2020. All patients were grouped into the hemorrhage (n = 368) and non-hemorrhage (n = 218) groups. The bAVM nidus were segmented on CT angiography images using Slicer software, and radiomic features were extracted using Pyradiomics. The dataset included a training set and an independent testing set. The machine learning model was developed on the training set and validated on the testing set by merging numerous base estimators and a final estimator based on the stacking method. The area under the receiver operating characteristic (ROC) curve, precision, and the f1 score were evaluated to determine the performance of the model. A total of 1790 radiomics features and 8 traditional risk factors were contained in the original dataset, and 241 features remained for model training after L1 regularization filtering. The base estimator of the ensemble model was Logistic Regression, whereas the final estimator was Random Forest. In the training set, the area under the ROC curve of the model was 0.982 (0.967-0.996) and 0.893 (0.826-0.960) in the testing set. This study indicated that radiomics features are a valuable addition to traditional risk factors for predicting bAVM rupture. In the meantime, ensemble learning can effectively improve the performance of a prediction model.

Correlation of Serum N-Acetylneuraminic Acid with the Risk of Moyamoya Disease.

N-acetylneuraminic acid (Neu5Ac) is a functional metabolite and has been demonstrated to be a risk factor for cardiovascular diseases. It is not clear whether Neu5Ac is associated with a higher risk of cerebrovascular disorders, especially moyamoya disease (MMD). We sought to elucidate the association between serum Neu5Ac levels and MMD in a case-control study and to create a clinical risk model. In our study, we included 360 MMD patients and 89 matched healthy controls (HCs). We collected the participants' clinical characteristics, laboratory results, and serum Neu5Ac levels. Increased level of serum Neu5Ac was observed in the MMD patients (p = 0.001). After adjusting for traditional confounders, the risk of MMD (odds ratio [OR]: 1.395; 95% confidence interval [CI]: 1.141-1.706) increased with each increment in Neu5Ac level (per µmol/L). The area under the curve (AUC) values of the receiver operating characteristic (ROC) curves of the basic model plus Neu5Ac binary outcomes, Neu5Ac quartiles, and continuous Neu5Ac are 0.869, 0.863, and 0.873, respectively. Furthermore, including Neu5Ac in the model offers a substantial improvement in the risk reclassification and discrimination of MMD and its subtypes. A higher level of Neu5Ac was found to be associated with an increased risk of MMD and its clinical subtypes.

Association between methionine sulfoxide and risk of moyamoya disease.

Objective: Methionine sulfoxide (MetO) has been identified as a risk factor for vascular diseases and was considered as an important indicator of oxidative stress. However, the effects of MetO and its association with moyamoya disease (MMD) remained unclear. Therefore, we performed this study to evaluate the association between serum MetO levels and the risk of MMD and its subtypes. Methods: We eventually included consecutive 353 MMD patients and 88 healthy controls (HCs) with complete data from September 2020 to December 2021 in our analyzes. Serum levels of MetO were quantified using liquid chromatography-mass spectrometry (LC-MS) analysis. We evaluated the role of MetO in MMD using logistic regression models and confirmed by receiver-operating characteristic (ROC) curves and area under curve (AUC) values. Results: We found that the levels of MetO were significantly higher in MMD and its subtypes than in HCs (p < 0.001 for all). After adjusting for traditional risk factors, serum MetO levels were significantly associated with the risk of MMD and its subtypes (p < 0.001 for all). We further divided the MetO levels into low and high groups, and the high MetO level was significantly associated with the risk of MMD and its subtypes (p < 0.05 for all). When MetO levels were assessed as quartiles, we found that the third (Q3) and fourth (Q4) MetO quartiles had a significantly increased risk of MMD compared with the lowest quartile (Q3, OR: 2.323, 95%CI: 1.088-4.959, p = 0.029; Q4, OR: 5.559, 95%CI: 2.088-14.805, p = 0.001). Conclusion: In this study, we found that a high level of serum MetO was associated with an increased risk of MMD and its subtypes. Our study raised a novel perspective on the pathogenesis of MMD and suggested potential therapeutic targets.

Integrated analysis of the association between methionine cycle and risk of moyamoya disease.

OBJECTIVE: The role of methionine (Met) cycle in the pathogenesis and progression of cardiovascular and cerebrovascular diseases has been established, but its association with moyamoya disease (MMD) has rarely been studied. This study aimed to analyze the levels of Met cycle-related metabolites and constructed a risk model to explore its association with the risk of MMD. METHODS: In this prospective study, a total of 302 adult MMD patients and 88 age-matched healthy individuals were consecutively recruited. The serum levels of Met cycle-related metabolites were quantified by liquid chromatography-mass spectrometry (LC-MS). Participants were randomly divided into training set and testing set at a ratio of 1:1. The training set was used to construct the risk score model by LASSO regression. The association between Met cycle-related risk score and the risk of MMD was analyzed using logistic regression and assessed by ROC curves. The testing set was used for validation. RESULTS: The levels of methionine sulfoxide and homocysteine were significantly increased, while the levels of betaine and choline were significantly decreased in MMD and its subtypes compared to healthy controls (p < 0.05 for all). The training set was used to construct the risk model and the risk score of each participant has been calculated. After adjusting for potential confounders, the risk score was independently associated with the risk of MMD and its subtypes (p < 0.05 for all). We then divided the participants into low-risk and high-risk groups, the high-risk score was significantly associated with the risk of MMD and its subtypes (p < 0.05 for all). The risk scores were further assessed as tertiles, the highest tertile was significantly associated with a higher risk of MMD and its subtypes compared to the lowest (p < 0.05 for all). The results were validated in the testing set. CONCLUSION: This study has constructed and validated a risk model based on Met cycle-related metabolites, which was independently associated with the risk of MMD and its subtypes. The findings provided a new perspective on the risk evaluation and prevention of MMD.

Serum Kynurenic Acid and Kynurenine Are Negatively Associated with the Risk of Adult Moyamoya Disease.

Background and aim. Kynurenine (KYN) and kynurenic acid (KYNA) are key intermediate metabolites associated with inflammation and immune responses in the kynurenine pathway. It remains unknown whether KYN or KYNA is associated with the risk of adult moyamoya disease (MMD). The aim of this study was to prospectively investigate the association between serum KYN or KYNA and the risk of adult MMD. Methods. The study was conducted from July 2020 to December 2021. We measured serum KYN and KYNA levels for 360 adult MMD patients (259 cases of ischemic MMD, 101 cases of hemorrhagic MMD) and 89 age-sex-matched healthy controls. Clinical and laboratory characteristics were collected from the medical record. Results. After multivariate adjustment, decreased serum KYNA (OR, 0.085; 95% CI, 0.035−0.206; p = 0.000) or KYN (OR, 0.430; 95% CI, 0.225−0.820; p = 0.010) levels were associated with increased risk of MMD when upper and lower tertiles were compared. In addition, a higher trend of hemorrhagic MMD was found in MMD patients in KYNA tertile 1 compared with those in tertile 2 to 3 (OR, 0.584; 95% CI, 0.345−0.987; p = 0.044). Addition of serum KYNA (net reclassification improvement: 73.24%, p = 0.000; integrated discrimination improvement: 9.60%, p = 0.000) or KYN (integrated discrimination improvement: 1.70%, p = 0.037) to conventional risk factors significantly improved the risk prediction of MMD. In the exploratory analysis, we observed an interaction between KYN and age (≥40 versus <40 years) or homocysteine levels (≥13.0 versus <13.0 µmol/L) on the risk of MMD. Conclusions. Decreased serum KYNA or KYN levels were associated with an increased risk of adult MMD, suggesting that serum KYNA or KYN may be a valuable predictive biomarker for adult MMD.

Development and validation of a model for predicting the risk of brain arteriovenous malformation rupture based on three-dimensional morphological features.

Objective: Brain arteriovenous malformation (bAVM) is an important reason for intracranial hemorrhage. This study aimed at developing and validating a model for predicting bAVMs rupture by using three-dimensional (3D) morphological features extracted from Computed Tomography (CT) angiography. Materials and methods: The prediction model was developed in a cohort consisting of 412 patients with bAVM between January 2010 and December 2020. All cases were partitioned into training and testing sets in the ratio of 7:3. Features were extracted from the 3D model built on CT angiography. Logistic regression was used to develop the model, with features selected using L1 Regularization, presented with a nomogram, and assessed with calibration curve, receiver operating characteristic (ROC) curve and decision curve analyze (DCA). Results: Significant variations in associated aneurysm, deep located, number of draining veins, type of venous drainage, deep drainage, drainage vein entrance diameter (Dv), type of feeding arteries, middle cerebral artery feeding, volume, Feret diameter, surface area, roundness, elongation, mean density (HU), and median density (HU) were found by univariate analysis (p < 0.05). The prediction model consisted of associated aneurysm, deep located, number of draining veins, deep drainage, Dv, volume, Feret diameter, surface area, mean density, and median density. The model showed good discrimination, with a C-index of 0.873 (95% CI, 0.791-0.931) in the training set and 0.754 (95% CI, 0.710-0.795) in the testing set. Conclusions: This study presented 3D morphological features could be conveniently used to predict hemorrhage from unruptured bAVMs.

Association of circulating branched-chain amino acids with risk of moyamoya disease.

Objective: Branched-Chain Amino Acids (BCAAs) has been identified as a risk factor for circulatory disease. Nevertheless, the effects and mechanisms of BCAAs on the risk of moyamoya disease (MMD) remain unrecognized. Hence, we aimed to elucidate the association between circulating BCAAs and the risk of MMD and clinical subtypes. Methods: We conducted a case-control study of 360 adult MMD patients and 89 matched healthy controls consecutively recruited between September 2020 and December 2021. Serum level of BCAAs was quantified by liquid chromatography-mass spectrometry. The associations between BCAAs and risk of MMD were evaluated. Results: Increased level of serum BCAAs was observed in MMD patients (P < 0.001). After adjusting for traditional confounders, the elevated BCAAs level was significantly associated with the risk of MMD (Q4 vs. Q1: odds ratio, 3.10 [95% CI, 1.29-7.50]). The risk of subtypes in MMD also increased with each increment in the quartiles of BCAAs. Furthermore, BCAAs offered substantial improvement in risk reclassification and discrimination for MMD and subtypes. Conclusion: Higher level of circulating BCAAs was associated with increased risk of MMD and clinical subtypes. This study will help to elucidate the pathogenesis of MMD, which may provide the support for facilitating the treatments and preventions.

Hypo-high density lipoproteinemia is a predictor for recurrent stroke during the long-term follow-up after revascularization in adult moyamoya disease.

Objective: Previous studies have reported that hypo-high-density lipoproteinemia (HHDL) was an independent risk factor for the cerebrovascular event. However, the risk of HHDL for stroke recurrence in moyamoya disease (MMD) during long-term follow-up after revascularization remains poorly understood. We aim to investigate the association between HHDL and stroke recurrence in adult patients with MMD. Methods: A total of 138 adult patients with MMD were prospectively recruited from 1 July to 31 December 2019. After excluding 15 patients who did not meet the inclusion criteria, all the 123 patients were enrolled. Participants were grouped according to the stroke recurrence and HHDL presentation, respectively. Clinical data and laboratory examinations were compared by the statistical analysis. The Kaplan-Meier survival analysis was conducted to compare the stroke-free survival rates between participants with HHDL and those without. Univariate and multivariate logistic regression analyses were performed to identify independent factors of the neurological status. Univariate and multivariate Cox regression analyses were conducted to identify the predictors for the recurrent stroke. Results: Participants with recurrent stroke group showed a lower level of high-density lipoprotein (HDL) (p = 0.030). More participants in the recurrent stroke group had HHDL (p = 0.045). What is more, there was statistical significance in the Kaplan-Meier curve of stroke incidence between the normal HDL group and the HHDL group (log-rank test, p = 0.034). Univariate logistic analysis results showed that HHDL (OR 0.916, 95% CI 0.237-3.543; p = 0.899) and HDL (OR 0.729, 95% CI 0.094-5.648; p = 0.763) were not predictive factors for the neurological status. In the multivariate Cox regression analysis, diabetes (HR 4.195, 95% CI 1.041-16.899; p = 0.044), HDL (HR 0.061, 95% CI 0.006-0.626; p = 0.019), and HHDL (HR 3.341, 95% CI 1.110-10.051; p = 0.032) were independent risk factors for the recurrent stroke. Conclusions: Hypo-high-density lipoproteinemia might be a predictor or the potential therapeutic target for recurrent stroke during the long-term follow-up after revascularization in adult patients with MMD.

Circulating choline pathway nutrients and risk of moyamoya disease.

Background: Circulating choline pathway nutrients play a critical role in first stroke and recurrent stroke. However, there is limited information available on the effects of choline pathway nutrients on the risk of moyamoya disease (MMD) and its subtypes. We investigated the association between circulating choline and betaine and the incident risk of MMD and its subtypes. Methods: The case-control study enrolled 385 patients with MMD [i.e., 110 transient ischemic attack (TIA)-type MMD, 157 infarction-type MMD, and 118 hemorrhagic-type MMD] and 89 matched healthy controls. Results: Serum choline and betaine were inversely related to the risk of MMD and its subtypes. The risk of MMD was decreased with each increment in choline level [per 1 µmol increase: odds ratio (OR), 0.756; 95% CI, 0.678-0.843] and betaine level (per 1 µmol increase: OR, 0.952; 95% CI, 0.932-0.972), respectively. When choline and betaine were assessed as quartiles, compared with the lowest quartile of serum choline and betaine levels, those in the highest quartile had a significantly decreased risk of MMD (choline, Q4 vs. Q1: OR, 0.023; 95% CI, 0.005-0.118; betaine, Q4 vs. Q1: OR, 0.058; 95% CI, 0.018-0.184). Conclusions: Serum choline and betaine were associated with the decreased risk of MMD and its subtypes.