Search

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Due to the extremely intrinsic heterogeneity among glioma patients, the outcomes of these patients are tremendously different. Therefore, the exploitation of novel biomarker classification of glioma is vitally important for deep insight into the essence and predicting the prognosis of glioma. We aim to analyze the correlation between TP73 mRNA expression, DNA methylated alteration and the prognosis of WHO grade II/III glioma, utilizing bioinformatics to evaluate its significance as a risk‐factor in predicting the prognosis of these glioma patients. The analysis found that TP73 expression was positively correlated with the grade of glioma, and showed a strong correlation with glioma molecular classification, which revealed significantly higher TP73 expression in IDH‐wildtype than in IDH‐mutant subtype of WHO grade II/III glioma. Cox regression analysis indicated that high expression of TP73 shared an independent high‐risk factor impacting the prognosis of WHO grade II/III glioma. We discovered 8 DNA promoter methylation sites with prognostic significance, which were negatively associated with TP73 expression, and positively associated with beneficial overall survival (OS) and progression‐free survival (PFS). Integrating with four independent glioma datasets, subsequent Meta‐analysis verified that low expression of TP73 was closely related to favorable OS, especially in IDH‐mutant subtype. Moreover, we found that 1p/19qCodel/TP73low subgroup shared the most favorable OS, 1p/19qNon−codel/TP73high subgroup suffered the worst OS. Meanwhile, the enrichment analysis of TP73‐related differential mRNAs demonstrated that TP73 aberration in WHO grade II/III glioma might be closely related to cell cycle and P53 signaling pathways. Finally, TP73 expression of 53 glioma specimens was measured by qRT‐PCR, which was consistent with the previous analytical result, and TP73 high‐expression subgroup suffered worse PFS than TP73 low‐expression subgroup. In summary, our funding supports that TP73 gene can perform as a reliable biomarker to evaluate the survival outcome of patients diagnosed with WHO grade II/III glioma. [ABSTRACT FROM AUTHOR]