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Abstract 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.

Summary: Background: Stroke is one of the most common neurological diseases in the world and is clinically manifested by transient or permanent brain dysfunction. It has a high mortality and disability rate, which severely affects people's health and diminishes the quality of life. However, there is no efficient treatment that can be considered curative and there are other less well-known theories of pathogenesis. Therefore, it is imperative to gain a full understanding of the pathophysiology of ischemia and to seek new therapeutic strategies. Methods: We first examined Kir4.1 channel and myelin based protein (MBP) expression in brain tissues from acute ischemic patients by Western blotting. We then established a transient ischemic mouse model (tMCAO) to conduct molecular, cell biological, transmission electron microscopy and pharmacokinetic studies, as well as in Kir4.1 cKO mice. Finally, neuroimaging and behavioral analyses were used to examine whether activation of Kir4.1 channel by luteolin could contribute to neuronal functional recovery in ischemic stroke. Findings: In acute ischemic stroke patients, we first demonstrated that Kir4.1 ion channels were greatly impaired and a severe demyelination of axons occurred in ischemic infarction area of cerebral cortex in these patients. Further evidence showed that the deficits of Kir4.1 channels in NG2 glia led to the myelin loss of axons in a transient ischemic mouse model (tMCAO). Treating ischemic mice with a natural botanical extract, luteolin augmented Kir4.1 channel currents in NG2 glia and consequently promoted remyelination of axons, alleviated the infarction area and ultimately improved motor function in a series of behavioral tests. Interpretation: Targeting Kir4.1 ion channels expressed in NG2 glial cells by luteolin treatment highlights an effective therapeutic strategy for a prompt brain functional recovery in ischemic stroke. Funding: This work was supported by grants from the Ministry of Science and Technology China Brain Initiative (2022ZD0204702, to X.T.), the National Natural Science Foundation of China (82271466, 82171279, 31970904 and 31571063), the Program for Professor of Special Appointment (Eastern Scholar for Dr. X.T.) at Shanghai Institutions for Higher Learning (1510000084), Shanghai Pujiang Talent Award (15PJ1404600), Shanghai Municipal Science and Technology Major Project (2018SHZDZX05) and Shanghai Science and Technology Project (17411954000).