Moyamoya disease

Moyamoya disease is a chronic, occlusive cerebrovascular disease, characterized by bilateral steno-occlusive changes at the terminal portion of the internal carotid artery and an abnormal vascular network at the base of the brain.

Moyamoya vessels are a distinctive feature of Moyamoya disease. In response to the reduced blood flow caused by arterial narrowing, the brain attempts to compensate by developing a network of small, fragile, and often disorganized collateral blood vessels. These small blood vessels are known as “Moyamoya vessels.

These diagnostic criteria of the moyamoya disease, stated by the Research Committee on Spontaneous Occlusion of the Circle of Willis (moyamoya disease) in Japan, are well established and generally accepted as the definition of this rare entity. On the contrary to the diagnosis of definitive moyamoya disease, there is some confusion in the terminology and understanding of quasi-moyamoya disease; moyamoya disease in association with various disease entities, such as atherosclerosis, autoimmune diseases, Down syndrome, etc. Although clinical management is not affected by these semantic distinctions, terminological confusion may interfere with international collaboration in the clinical investigation of these rare conditions 1).

The perforating arteries in the basal ganglia and thalamus markedly dilate and function as an important collateral circulation, called “moyamoya” vessels. The posterior cerebral artery is also involved in a certain subgroup of patients. Therefore, cerebral hemodynamics is often impaired especially in the frontal lobe, leading to transient ischemic attack (TIa) and cerebral infarction. Furthermore, the dilated, fragile moyamoya vessels often rupture and cause intracranial hemorrhage 2) 3).

Unknown etiology.

A study indicated a higher overall autoimmune disease prevalence in unilateral than in bilateral MMD. Unilateral MMD may be more associated with autoimmune disease than bilateral MMD. Different pathogenetic mechanisms may underlie moyamoya vessel formation in unilateral and bilateral MMD 4).

The p.R4810K mutation in RNF213 gene confers a risk of MMD, but other factors remain largely unknown. Mineharu et al. tested the association of gut microbiota with MMD. Fecal samples were collected from 27 patients with MMD, 7 patients with non-moyamoya intracranial large artery disease (ICAD) and 15 control individuals with other disorders, and 16S rRNA were sequenced. Although there was no difference in alpha diversity or beta diversity between patients with MMD and controls, the cladogram showed Streptococcaceae was enriched in patient samples. The relative abundance analysis demonstrated that 23 species were differentially abundant between patients with MMD and controls. Among them, increased abundance of Ruminococcus gnavus > 0.003 and decreased abundance of Roseburia inulinivorans < 0.002 were associated with higher risks of MMD (odds ratio 9.6, P = 0.0024; odds ratio 11.1, P = 0.0051). Also, Ruminococcus gnavus was more abundant and Roseburia inulinivorans was less abundant in patients with ICAD than controls (P = 0.046, P = 0.012). The relative abundance of Ruminococcus gnavus or Roseburia inulinivorans was not different between the p.R4810K mutant and wildtype. The data demonstrated that gut microbiota was associated with both MMD and ICAD 5).

The histopathological features of the middle cerebral artery (MCA) and superficial temporal artery (STA) from moyamoya disease (MMD) and their relationships with gender, age, angiography stage were explored. The causes and the clinical significance of vasculopathy of STA were also discussed. The clinical data and specimens of MCA and STA from 30 MMD patients were collected. Twelve samples of MCA and STA from non-MMD patients served as control group. Histopathological examination was then performed by measuring the thickness of intima and media, and statistical analysis was conducted. The MCA and STA specimens from MMD group had apparently thicker intima and thinner media than those from the control group. There was no significant pathological difference between the hemorrhage group and non-hemorrhage group, and between the males and females in MMD patients. Neither the age nor the digital subtraction angiography (DSA) stage was correlated with the thickness of intima in MCA and STA. MMD is a systemic vascular disease involving both intracranial and extracranial vessels. Preoperative external carotid arteriography, especially super-selective arteriography of the STA, benefits the selection of donor vessel 6).

Quantification of the severity of vasculopathy and its impact on parenchymal hemodynamics is a necessary prerequisite for informing management decisions and evaluating intervention response in patients with moyamoya.

Computational fluid dynamics (CFD) analysis on eight patients (5 female, 3 male) with MMD treated by EDAS (encephalo-duro-arterio-synangiosis) between 2011 and 2012. All the eight patients presented with haemorrhage, with subsequent 4-12 month follow-up done using Magnetic Resonance Angiography (MRA) to capture auto-remodelling. Karunanithi et al. calculated percentage change in flow rate and pressure drop indicator (ΡDI) across the Left and Right ICA. Pressure drop indicator (PDI) is defined as the difference of pressure reduction within the carotid arteries, measured at post-op and follow up, using patient specific inflow rates. The measured percentage flow change and pressure reduction showed an increase at follow up for improved patients (characterised by angiography according to the method of Matsushima), who did not develop any complications after surgery. The inverse was observed in patients who were clinically classified as no change and retrogressed (according to the method of Matsushima) cases post-operation. This elucidates the findings of a new parameter that may well play a critical role as an assistive clinical decision making tool in MMD 7).

Artificial intelligence (AI) clustering was used to classify the articles into 5 clusters: (1) pathophysiology (23.5%); (2) clinical background (37.3%); (3) imaging (13.2%); (4) treatment (17.3%); and (5) genetics (8.7%). Many articles in the “clinical background” cluster were published from the 1970s. However, in the “treatment” and “genetics” clusters, the articles were published from the 2010s through 2021. In 2011, it was confirmed that a gene called Ringin protein 213 (RNF213) is a susceptibility gene for moyamoya disease. Since then, tremendous progress in genomic, transcriptomics, and epigenetics (e.g., methylation profiling) has resulted in new concepts for classifying moyamoya disease. The literature survey revealed that the pathogenesis involves aberrations of multiple signaling pathways through genetic mutations and altered gene expression 8).

Fujimura M, Tominaga T. Diagnosis of moyamoya disease: international standard and regional differences. Neurol Med Chir (Tokyo). 2015 Mar 15;55(3):189-93. doi: 10.2176/nmc.ra.2014-0307. Epub 2015 Feb 20. PubMed PMID: 25739428.
Suzuki J, Takaku a: Cerebrovascular “moyamoya” disease. disease showing abnormal net-like vessels in base of brain. Arch Neurol 20: 288–299, 1969
Kuroda S, Houkin K: Moyamoya disease: current concepts and future perspectives. Lancet Neurol 7: 1056–1066, 2008
Chen JB, Liu Y, Zhou LX, Sun H, He M, You C. Increased prevalence of autoimmune disease in patients with unilateral compared with bilateral moyamoya disease. J Neurosurg. 2015 Sep 25:1-6. [Epub ahead of print] PubMed PMID: 26406790.
Mineharu Y, Nakamura Y, Sato N, Kamata T, Oichi Y, Fujitani T, Funaki T, Okuno Y, Miyamoto S, Koizumi A, Harada KH. Increased abundance of Ruminococcus gnavus in gut microbiota is associated with moyamoya disease and non-moyamoya intracranial large artery disease. Sci Rep. 2022 Nov 24;12(1):20244. doi: 10.1038/s41598-022-24496-9. PMID: 36424438.
Sun SJ, Zhang JJ, Li ZW, Xiong ZW, Wu XL, Wang S, Shu K, Chen JC. Histopathological features of middle cerebral artery and superficial temporal artery from patients with moyamoya disease and enlightenments on clinical treatment. J Huazhong Univ Sci Technolog Med Sci. 2016 Dec;36(6):871-875. PubMed PMID: 27924520.
Karunanithi K, Han C, Lee CJ, Shi W, Duan L, Qian Y. Identification of a hemodynamic parameter for assessing treatment outcome of EDAS in Moyamoya disease. J Biomech. 2015 Jan 21;48(2):304-9. doi: 10.1016/j.jbiomech.2014.11.029. Epub 2014 Nov 29. PubMed PMID: 25498370.
Kuribara T, Akiyama Y, Mikami T, Komatsu K, Kimura Y, Takahashi Y, Sakashita K, Chiba R, Mikuni N. Macrohistory of Moyamoya Disease Analyzed Using Artificial Intelligence. Cerebrovasc Dis. 2022 Feb 1:1-14. doi: 10.1159/000520099. Epub ahead of print. PMID: 35104814.
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