Comprehensive molecular analyses of an autoimmune-related gene predictive model and immune infiltrations using machine learning methods in moyamoya disease

A Transcriptomic Comparative Study of Cranial Vasculature

In genetic studies of cerebrovascular diseases, the optimal vessels to use as controls remain unclear. Our goal is to compare the transcriptomic profiles among 3 different types of control vessels: superficial temporal artery (STA), middle cerebral arteries (MCA), and arteries from the circle of Willis obtained from autopsies (AU). We examined the transcriptomic profiles of STA, MCA, and AU using RNAseq. We also investigated the effects of using these control groups on the results of the comparisons between aneurysms and the control arteries. Our study showed that when comparing pathological cerebral arteries to control groups, all control groups presented similar responses in the activation of immunological processes, the regulation of intracellular signaling pathways, and extracellular matrix productions, despite their intrinsic biological differences. When compared to STA, AU exhibited upregulation of stress and apoptosis genes, whereas MCA showed upregulation of genes associated with tRNA/rRNA processing. Moreover, our results suggest that the matched case-control study design, which involves control STA samples collected from the same subjects of matched aneurysm samples in our study, can improve the identification of non-inherited disease-associated genes. Given the challenges associated with obtaining fresh intracranial arteries from healthy individuals, our study suggests that using MCA, AU, or paired STA samples as controls are feasible strategies for future large-scale studies investigating cerebral vasculopathies. However, the intrinsic differences of each type of control should be taken into consideration when interpreting the results. With the limitations of each control type, it may be most optimal to use multiple tissues as controls.

Understanding external carotid artery collateralisation after cerebral revascularisation in moyamoya disease: insights from quantitative analysis

BACKGROUND

This study aims to quantitatively evaluate collateralisation angiogenesis ratio (CAR) of external carotid artery and intracranial arterial residual volumes (ARV) postcerebral revascularisation in moyamoya disease (MMD) and elucidate the factors influencing external carotid artery collateralisation.

METHODS

The study retrospectively analysed 297 patients diagnosed with MMD who underwent cerebral revascularisation at our University's Hospital, between January 2015 and May 2023. The clinical data, imaging results and surgical specifics for the patients were collected. Using a newly proposed digital subtraction angiography-based evaluation system, the CAR of external carotid artery and the intracranial ARV were evaluated quantitatively following standardised protocols.

RESULTS

The study included 136 male and 161 female patients. The severity of ischaemic (r=-0.297) and haemorrhagic (r=-0.270) MMD, as assessed by the Suzuki stage, demonstrated a significant negative correlation with intracranial ARV (p<0.001). However, no significant correlation was observed between the intracranial ARV and the modified Rankin Scale scores. Patients with fetal-type posterior cerebral arteries exhibited greater intracranial ARV compared with those without (p=0.003). Additionally, a positive correlation was observed between external carotid artery collateralisation and intracranial ARV post-revascularisation (r=0.340, p<0.001). The CAR of external carotid artery following cerebral revascularisation in patients with MMD remained independent correlation of the intracranial ARV (β=0.385, 95% CI (0.921 to 1.669), p<0.001) and Suzuki stage (β=0.211, 95% CI (0.009 to 0.030), p<0.001).

CONCLUSIONS

This study showed a complex association between ARV, the Suzuki stage and the collateralisation of the external carotid artery in patients with MMD who are undergoing revascularisation. These findings provide insights into MMD progression and revascularisation outcomes and may guide clinical decision-making to improve patient care.

Mass cytometry revealed the circulating immune cell landscape across different Suzuki stages of Moyamoya disease

Moyamoya disease (MMD) is a cerebrovascular disorder marked by progressive arterial narrowing, categorized into six stages known as Suzuki stages based on angiographic features. Growing evidence indicates a pivotal role of systemic immune and inflammatory responses in the initiation and advancement of MMD. This study employs high-dimensional mass cytometry to reveal the immunophenotypic characteristics of peripheral blood immune cells (PBMCs) at various Suzuki stages, offering insights into the progression of MMD. PBMC samples from eight patients with early-stage MMD (Suzuki stages II and III) and eight patients with later-stage MMD (Suzuki stages IV, V, and VI) were analyzed using high-dimensional mass cytometry to evaluate the frequency and phenotype of immune cell subtypes. We identified 15 cell clusters and found that the immunological features of early-stage MMD and later-stage MMD are composed of cluster variations. In this study, we confirmed that, compared to later-stage MMD, the early-stage MMD group exhibits an increase in non-classical monocytes. As the Suzuki stage level increases, the proportions of plasmacytoid DCs and monocyte-derived DCs decrease. Furthermore, T cells, monocytes, DCs, and PMN-MDSCs in the early-stage MMD group show activation of the canonical NF-κB signaling pathway. We summarized and compared the similarities and differences between early-stage MMD patients and later-stage MMD patients. There is a potential role of circulating immune dysfunction and inflammatory responses in the onset and development of MMD.

Identification of lysosome-related hub genes as potential biomarkers and immune infiltrations of moyamoya disease by multiple bioinformatics methods and machine-learning strategies

Background

Moyamoya disease (MMD), characterized by chronic cerebrovascular pathology, poses a rare yet significant clinical challenge, associated with elevated rates of mortality and disability. Despite intensive research endeavors, the exact biomarkers driving its pathogenesis remain enigmatic.

Methods

The expression patterns of GSE189993 and GSE141022 were retrieved from the Gene Expression Omnibus (GEO) repository to procure differentially expressed genes (DEGs) between samples afflicted with MMD and those under control conditions. The Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine with Recursive Feature Elimination (SVM-RFE), and Random Forest (RF) algorithms were employed for identifying candidate diagnostic genes associated with MMD. Subsequently, these candidate genes underwent validation in an independent cohort (GSE157628). The CMAP database was ultimately employed to forecast drugs pertinent to MMD for clinical translation.

Results

A collective of 240 DEGs were discerned. Functional enrichment scrutiny unveiled the enrichment of the cholesterol metabolism pathway, salmonella infection pathway, and allograft rejection pathway within the MMD cohort. EPDR1, DENND3, and NCSTN emerged as discerned diagnostic biomarkers for MMD. The CMAP database was ultimately employed to scrutinize the ten most auspicious pharmaceutical compounds for managing MMD. Finally, after validation through in vitro experiments, EPDR1, DENND3, and NCSTN were identified as the key genes.

Conclusion

EPDR1, DENND3, and NCSTN have emerged as potential novel biomarkers for MMD. The involvement of T lymphocytes, neutrophilic granulocytes, dendritic cells, natural killer cells, and plasma cells could be pivotal in the pathogenesis and advancement of MMD.

Bioinformatics analysis reveals the landscape of immune cell infiltration and novel immune-related biomarkers in moyamoya disease

Objective: This study aimed to identify immune infiltration characteristics and new immunological diagnostic biomarkers in the cerebrovascular tissue of moyamoya disease (MMD) using bioinformatics analysis. Methods: GSE189993 and GSE141022 were downloaded from the GEO database. Differentially expressed gene and PPI analysis were performed. After performing WGCNA, the most significant module associated with MMD was obtained. Next, functional pathways according to GSEA, GO, and KEGG were enriched for the aforementioned core genes obtained from PPI and WGCNA. Additionally, immune infiltration, using the CIBERSORT deconvolution algorithm, immune-related biomarkers, and the relationship between these genes, was further explored. Finally, diagnostic accuracy was verified with ROC curves in the validation dataset GSE157628. Results: A total of 348 DEGs were screened, including 89 downregulated and 259 upregulated genes. The thistlel module was detected as the most significant module associated with MMD. Functional analysis of the core genes was chiefly involved in the immune response, immune system process, protein tyrosine kinase activity, secretory granule, and so on. Among 13 immune-related overlapping genes, 4 genes (BTK, FGR, PTPN11, and SYK) were identified as potential diagnostic biomarkers, where PTPN11 showed the highest specificity and sensitivity. Meanwhile, a higher proportion of eosinophils, not T cells or B cells, was demonstrated in the specific immune infiltration landscape of MMD. Conclusion: Immune activities and immune cells were actively involved in the progression of MMD. BTK, FGR, PTPN11, and SYK were identified as potential immune diagnostic biomarkers. These immune-related genes and cells may provide novel insights for immunotherapy in the future.