Data-Independent Acquisition-Based Serum Proteomic Profiling of Adult Moyamoya Disease Patients Reveals the Potential Pathogenesis of Vascular Changes

Wang, Zongqi; Chen, Gang; Han, Qiang; Wang, Zhong; Huang, Yabo

doi:10.1007/s12031-022-02092-w

Cited by 4 publications

(2 citation statements)

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“…For example, one study found that interleukin-1 beta might act as a clinically useful biomarker in MMD [21] and another study found that lipoprotein metabolism might play a critical role in MMD [22]. In addition, by serum proteomic analysis of adult patients with MMD, Wang, Z., et al found that lipoprotein dysfunction might get involved in MMD [23]. These studies revealed the value of in-depth exploration of the connection between lipoprotein and MMD.…”

Section: Discussionmentioning

confidence: 99%

High lipoprotein(a) concentration is associated with moyamoya disease

Chen,

Song,

et al. 2024

Lipids Health Dis

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Background Moyamoya disease (MMD) has attracted the attention of scholars because of its rarity and unknown etiology. Methods Data for this study were sourced from the Second Affiliated Hospital of Nanchang University. Regression analyses were conducted to examine the association in Lipoprotein [Lp(a)] and MMD. R and IBM SPSS were conducted. Results A cohort comprising 1012 MMD patients and 2024 controls was established through the propensity score matching method. Compared with controls, MMD patients showed higher median Lp(a) concentrations [18.5 (9.6–37.8) mg/dL vs. 14.9 (7.8–30.5) mg/dL, P < 0.001]. The odds ratios and 95% confidence intervals for Lp(a) were calculated in three models: unadjusted model, model 1 (adjusted for body mass index and systolic blood pressure), and model 2 (adjusted for model 1 plus triglyceride, C-reactive protein, homocysteine, and low-density lipoprotein cholesterol). Results were [1.613 (1.299–2.002), P < 0.001], [1.598 (1.286–1.986), P < 0.001], and [1.661 (1.330–2.074), P < 0.001], respectively. Furthermore, age, sex, or hypertension status had nothing to do with this relationship. Conclusions Positive relationship exists between Lp(a) and MMD.

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Section: Discussionmentioning

confidence: 99%

High lipoprotein(a) concentration is associated with moyamoya disease

Chen,

Song,

et al. 2024

Lipids Health Dis

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“…The upregulation of haptoglobin and A1BG in MMD patients' cerebrospinal fluid suggests potential roles in inflammation and angiogenesis, making them promising novel biomarkers for further investigation [ 21 ]. Moreover, serum proteomics has revealed dysregulated lipid metabolism in both ischemic and hemorrhagic MMD patients, emphasizing its significance in vascular changes [ 22 ].In addition, the characterization of proteins in Moyamoya angiopathy (MMA) between the brain surface and dura mater has identified Filamin A as a potential key player, offering initial insights into MMA’s unique intracranial vasculopathy [ 23 ]. Investigation into RNF213’s role in MMD and antimicrobial activity has highlighted changes in proteins like MVP, CYR61, and DDAH1 upon RNF213 knockdown, suggesting potential connections between RNF213, immune responses, and MMD development, possibly involving nitric oxide production in combating Listeria infection [ 24 ].…”

Section: Proteomicsmentioning

confidence: 99%

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

Ge,

Yin,

Tao

et al. 2024

Chin Neurosurg Jl

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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.

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