Method for predicting onset of moyamoya disease

Abstract

To provide a method, a composition, and a kit for predicting the onset of moyamoya disease in a subject carrying a genetic mutation responsible for moyamoya disease.SOLUTION: Disclosed herein is a method for predicting the onset of moyamoya disease, the method including measuring the expression level of GATA2 in a sample derived from a subject carrying the p.R4810K mutation in the RNF213 gene. Also disclosed is a composition or a kit for predicting the onset of moyamoya disease in a subject carrying the p.R4810K mutation in the RNF213 gene, the composition or kit including a reagent for measuring the expression level of GATA2.SELECTED DRAWING: None

Description

[Technical field]

[0001] The present disclosure relates to predicting the onset of Moyamoya disease. [Background technology]

[0002] Moyamoya disease is a rare and intractable disease in which cerebral blood vessels narrow, causing cerebral infarction and cerebral hemorrhage. The genetic mutation that causes moyamoya disease has been identified, and it is known that it is passed down from parent to child, and that moyamoya disease occurs frequently in certain families. However, not all people who carry the genetic mutation develop moyamoya disease, and even in the same family, there are people who develop moyamoya disease and people who do not. There is no technology to distinguish between people who develop moyamoya disease and those who do not, and people of families who carry the genetic mutation for moyamoya disease must live their daily lives with anxiety, knowing that they may develop moyamoya disease. Summary of the Invention [Problem to be solved by the invention]

[0003] The present disclosure aims to provide methods, compositions, and kits for predicting the onset of Moyamoya disease in subjects carrying a genetic mutation that causes Moyamoya disease. [Means for solving the problem]

[0004] In one aspect, the present disclosure provides a method for predicting the onset of Moyamoya disease, comprising measuring GATA2 expression levels in a sample taken from a subject carrying the p.R4810K mutation in the RNF213 gene.

[0005] In one aspect, the present disclosure provides a composition for predicting the onset of Moyamoya disease in a subject carrying the p.R4810K mutation in the RNF213 gene, comprising a reagent for measuring GATA2 expression levels.

[0006] In one aspect, the present disclosure provides a kit for predicting the onset of Moyamoya disease in a subject carrying the p.R4810K mutation in the RNF213 gene, comprising a reagent for measuring GATA2 expression levels. Effect of the Invention

[0007] The present disclosure makes it possible to predict whether a subject carrying a genetic mutation that causes Moyamoya disease will develop Moyamoya disease. [Brief description of the drawings]

[0008] [Figure 1] Figure 1 shows pedigrees of four Moyamoya disease families with incomplete penetrance. Solid symbols: Moyamoya disease (MMD), dotted symbols: non-affected RNF213 p.R4810K mutation carriers, 1 / 4 solid symbols: bilateral middle cerebral artery stenosis. Below the symbols are shown symptoms at onset (TIA: transient ischemic attack, CI: cerebral infarction, seizure: epileptic seizure, no symptom: asymptomatic), age at onset, and genotype of p.R4810K mutation (heterozygote: GA). Relative GATA2 expression is shown below. SAS = sleep apnea syndrome; PCA inv = posterior cerebral artery stenosis / occlusion; 43 LOC: loss of consciousness at age 43. Diamonds represent multiple individuals, with the numbers inside indicating the number of individuals. [Diagram 2] Figure 2 shows the discrimination between Moyamoya disease patients and non-onset mutation carriers by GATA2 expression levels. (Left) Comparison of GATA2 expression levels between age- and sex-matched patients (MMD), non-onset mutation carriers (Carriers), and controls (Controls). (Right) ROC analysis of GATA2 expression levels between patients and carriers. [Diagram 3]Figure 3 shows a comparison of GATA2 expression levels between patients with moyamoya disease and other patients with cerebrovascular stenosis in cases of heterozygous p.R4810K mutation. (Left) Only cases of heterozygous p.R4810K mutation. U-: unilateral, B-: bilateral, Carrier: mutation present but no vascular stenosis, ICAD: cerebrovascular stenosis not meeting the diagnostic criteria for moyamoya disease, MMD: moyamoya disease. (Right) All cases (regardless of the presence or absence of p.R4810K mutation). Control: no vascular disorder, family: relatives with moyamoya disease but no vascular disorder, ICAD: cerebrovascular stenosis not meeting the diagnostic criteria for moyamoya disease, MMD: moyamoya disease. [Figure 4] Figure 4 shows the relationship between GATA2 expression levels and disease severity. (Top left) Relationship between GATA2 expression levels and age in controls. (Top right) Age at onset. (Bottom left) Percentage of unilateral or bilateral disease. (Bottom right) Percentage of asymptomatic subjects. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Unless otherwise specified, terms used herein have the meanings commonly understood by those skilled in the art of organic chemistry, medicine, pharmacology, molecular biology, microbiology, etc. Below, definitions of some terms used herein are provided, but these definitions take precedence over the common understanding herein.

[0010] Moyamoya disease is a rare and intractable disease in which cerebral blood vessels are narrowed, causing cerebral infarction and cerebral hemorrhage. A known genetic mutation that causes moyamoya disease is the p.R4810K (c.14429G>A) mutation in the RNF213 (also known as Mysterin) gene, that is, a substitution of arginine at position 4810 of RNF213 with lysine (substitution of guanine at position 14429 of the coding DNA of RNF213 with adenine). A representative amino acid sequence of human RNF213 (NP_001243000.2) is shown in SEQ ID NO: 1, and the mRNA sequence (NM_001256071.3) is shown in SEQ ID NO: 2 (positions 160 to 15783 code for RNF213).

[0011] The method of the present disclosure predicts the onset of Moyamoya disease in a subject carrying the p.R4810K mutation of the RNF213 gene. In the present disclosure, the subject is a mammal, preferably a primate, more preferably a human. The subject may carry the p.R4810K mutation heterozygously (G / A) or homozygously (A / A). In one embodiment, the subject is a subject carrying the p.R4810K mutation heterozygously. The subject may or may not belong to a family with a Moyamoya disease patient. In one embodiment, the subject is a subject belonging to a family with a Moyamoya disease patient.

[0012] The p.R4810K mutation may be detected by any method that a person skilled in the art can use to detect genetic mutations. The p.R4810K mutation can be detected, for example, by using an oligonucleotide that can bind to a genomic or mRNA sequence adjacent to the location of the c.14429G>A mutation in the RNF213 gene, or a genomic or mRNA sequence that includes the location of the mutation. Such methods include, for example, PCR-RFLP (restriction fragment length polymorphism), PCR-SSCP (single-strand conformation polymorphism), PCR-SSO (sequence specific oligonucleotide), ARMS (amplification refracting mutation system)-PCR, TaqMan, etc., which utilize PCR (polymerase chain reaction). TM Examples of such methods include PCR, ASP (allele specific primer)-PCR, direct sequencing, ASO (allele specific oligonucleotide) hybridization, SNaPshot (registered trademark) method, and Invader method.

[0013] The method of the present disclosure includes measuring the expression level of GATA2 in a sample collected from a subject. GATA2 is a transcription factor that binds to DNA to control gene expression. A representative amino acid sequence of human GATA2 is shown in SEQ ID NO: 3. GATA2 mRNA has a major variant, variant 1 (NM_001145661.2), and a minor variant, variant 2 (NM_032638.5). The sequences of variant 1 and variant 2 are shown in SEQ ID NO: 4 (436 to 1878 encode GATA2) and 5 (349 to 1791 encode GATA2). Both variant 1 and variant 2 encode the amino acid sequence of SEQ ID NO: 3, but differ in the 5' untranslated region (particularly, 1 to 390 of SEQ ID NO: 4). It is desirable to measure the expression level of GATA2 by a method capable of detecting both variant 1 and variant 2.

[0014] The GATA2 expression level can be examined by measuring GATA2 mRNA or protein. Measurement methods include PCR (polymerase chain reaction), RNA sequencing (RNA-Seq), microarrays, and immunological methods such as immunostaining, ELISA, Western blot, and dot blot. Preferably, the measurement of the GATA2 expression level includes the measurement of GATA2 mRNA. In this specification, the term PCR is used to include any method using PCR, such as RT-PCR (reverse transcription PCR), qPCR (quantitative PCR), and real-time PCR. In one embodiment, the GATA2 expression level is measured by PCR. Those skilled in the art can appropriately prepare or select reagents such as oligonucleotides such as primers or probes suitable for measurement, and antibodies used in immunological methods, based on the sequence of GATA2 mRNA or protein. When detecting both variant 1 and variant 2 of GATA2 mRNA, a reagent for measurement may be designed for a portion common to the two variants. For example, an oligonucleotide such as a primer or probe may be designed for a portion common to variant 1 and variant 2.

[0015] The sample is not particularly limited as long as it contains the target mRNA or protein in a state in which the GATA2 expression level can be measured. Examples of the sample include blood (e.g., peripheral blood) and tissue (e.g., vascular tissue). In one embodiment, the sample is a blood sample, preferably a peripheral blood sample. Use of a peripheral blood sample makes it possible to easily predict the onset of the disease. Those skilled in the art can perform the necessary treatment on the sample taken from the subject according to the method for measuring the GATA2 expression level.

[0016] Whether a subject will develop Moyamoya disease can be predicted by comparing the subject's GATA2 expression level with a reference value. If the GATA2 expression level is higher than the reference value, the subject can be predicted to develop Moyamoya disease. The prediction is not limited to the expression "will develop" or "will not develop", but can be presented in similar positive and negative terms such as "highly likely to develop" or "lowly likely to develop", which can be used interchangeably.

[0017] The reference value may be a value determined from the GATA2 expression levels in multiple subjects who carry the p.R4810K mutation and are known to have or have not developed Moyamoya disease. Those skilled in the art can determine an appropriate reference value by considering factors such as the type of sample and the method for measuring the GATA2 expression level. The reference value may also be set for a group of subjects subgrouped according to characteristics. For example, the reference value may be set according to gender, age group, or race.

[0018] The reference value may be a GATA2 expression level that can divide a plurality of subjects who have the p.R4810K mutation and are known to have or not have Moyamoya disease into an onset group and a non-onset group with a statistically significant difference. The value can be calculated, for example, using receiver operating characteristic analysis (ROC analysis). Alternatively, the reference value may be a value that can separate a certain percentage (e.g., 10%, 20%, 30%, 40%, or 50%) from the top of the GATA2 expression levels of a plurality of subjects who have the p.R4810K mutation and are known to have or not have Moyamoya disease. The statistically significant difference between the two groups may be analyzed by any method. Examples of statistical analysis methods include chi-square test and Fisher exact test.

[0019] The GATA2 expression level may be compared with multiple reference values. For example, in a plurality of subjects who have the p.R4810K mutation and whose clinical severity of Moyamoya disease is known, the clinical severity of each subject may be ranked into three or more stages, and two or more GATA2 expression levels that can separate the groups of each rank with a statistically significant difference may be used as the reference value. This allows the clinical severity of Moyamoya disease in the subject to be predicted. The statistically significant difference may be analyzed by any method. Examples of statistical analysis methods include the chi-square test and Fisher's exact test. Alternatively, the reference value may be multiple values ​​that can separate a certain percentage (e.g., 10%, 20%, 30%, 40%, or 50%) from the top of the GATA2 expression level of each subject in a plurality of subjects whose clinical severity of Moyamoya disease is known.

[0020] The comparison of GATA2 expression levels with the reference value may or may not involve statistical analysis, such as one-way ANOVA, two-way ANOVA, Dunnett's test, Tukey's test, etc.

[0021] In a subject predicted to develop Moyamoya disease, preventive treatment for cerebral infarction or intracranial hemorrhage can be administered to prevent the onset of cerebral infarction or intracranial hemorrhage. Preventive treatment for cerebral infarction includes administration of antithrombotic drugs. Antithrombotic drugs include antiplatelet drugs and anticoagulants. Antiplatelet drugs include aspirin, ticlopidine, and clopidogrel, and anticoagulants include warfarin, dabigatran, rivaroxaban, avixaban, and edoxaban. Preventive treatment for intracranial hemorrhage includes extracranial and intracranial vascular anastomosis.

[0022] In one embodiment, the reagent for measuring the GATA2 expression level is an oligonucleotide. Those skilled in the art can appropriately design oligonucleotides for measuring the GATA2 expression level. For example, the oligonucleotide can be designed to be used as a primer or a probe. In one embodiment, the oligonucleotide can bind to the sequence of GATA2 mRNA or a sequence complementary thereto. In one embodiment, the oligonucleotide can bind to the sequence of SEQ ID NO: 4 or a sequence complementary thereto. In one embodiment, the oligonucleotide can bind to the sequence of 391 to 3470 of SEQ ID NO: 4 or a sequence complementary thereto. In a further embodiment, the oligonucleotide can bind to the sequence of 436 to 1878 of SEQ ID NO: 4 or a sequence complementary thereto.

[0023] The oligonucleotides of the present disclosure are typically 100 nucleotides or less in length. In certain embodiments, the oligonucleotides are 10-50, 10-40, 10-35, 15-35, 15-30, or 20-30 nucleotides in length. In certain embodiments, the oligonucleotides are 15-35 nucleotides in length.

[0024] In the present specification, when an oligonucleotide is said to be capable of binding to a predetermined sequence, it is sufficient that the oligonucleotide can form a double strand with the predetermined sequence under stringent conditions appropriate for the method of measuring the GATA2 expression level, and does not need to have a sequence completely complementary to the predetermined sequence. Examples of complementary base pairs include adenine (A) and thymine (T), adenine (A) and uracil (U), and cytosine (C) and guanine (G).

[0025] In one embodiment, the oligonucleotide comprises or consists of a portion of the sequence of GATA2 mRNA or a sequence complementary thereto. In one embodiment, the oligonucleotide comprises or consists of a sequence having 80, 85, 90, 95, 96, 97, 98, or 99% or more sequence identity with the sequence of SEQ ID NO: 4 or a sequence complementary thereto. In one embodiment, the oligonucleotide comprises or consists of a portion of the sequence of SEQ ID NO: 4 or a sequence complementary thereto, or a sequence in which 1 to 10, 1 to 5, 1 to 3, 1 or 2 nucleotides are modified in the sequence of SEQ ID NO: 4 or a sequence complementary thereto. In a further embodiment, the oligonucleotide comprises or consists of a portion of the sequence of SEQ ID NO: 4 or a sequence complementary thereto. In one embodiment, the portion of the sequence of SEQ ID NO: 4 or a sequence complementary thereto is a portion of the sequence of 391 to 3470 of SEQ ID NO: 4 or a sequence complementary thereto. In a further embodiment, the portion of the sequence of SEQ ID NO: 4 or a sequence complementary thereto is a portion of the sequence of 436 to 1878 of SEQ ID NO: 4 or a sequence complementary thereto. A portion of the sequence of SEQ ID NO:4 or a sequence complementary thereto may be 10 to 50, 10 to 40, 10 to 35, 15 to 35, 15 to 30, or 20 to 30 nucleotides in length. When referring to a GATA2 mRNA sequence herein, the sequence includes the sequence in which U is replaced with T, unless inappropriate in the context. In one embodiment, the oligonucleotide comprises or consists of the sequence of SEQ ID NO:6 or 7.

[0026] In this disclosure, a nucleotide modification includes a deletion, substitution, insertion, and addition of a nucleotide. When more than one nucleotide is modified, each nucleotide modification is independently selected from a deletion, substitution, insertion, and addition.

[0027] An oligonucleotide is a compound that contains multiple nucleosides linked together by internucleoside bonds. The oligonucleotide of the present disclosure may be composed of natural nucleosides, non-natural nucleosides, or both. In addition, the internucleoside bonds of the oligonucleotide may be natural internucleoside bonds, non-natural internucleoside bonds, or both. Non-natural nucleosides include LNA (Locked Nucleic Acid / 2'-O,4'-C-Methylene-bridged Nucleic Acid), AmNA (Amido-Bridged Nucleic Acid), ENA (Ethylene-bridged Nucleic Acid), peptide nucleic acid, and morpholino nucleic acid; nucleosides containing non-natural bases such as 5-methylcytosine, 5-hydroxymethylcytosine, 6-methyladenine, 6-methylguanine, 4-thiouracil, and 5-fluorouracil; 2'-F, 2'-O(CH 2 ) 2 OCH 3 Examples of suitable internucleoside linkages include nucleosides containing sugar modifications such as methylaminoethyl ester (MOE). Examples of unnatural internucleoside linkages include phosphorothioate linkages, phosphorodithioate linkages, and alkylphosphonate linkages. Oligonucleotides may contain two or more types of nucleosides and / or internucleoside linkages. Oligonucleotides can be produced by methods for synthesizing oligonucleotides known to those skilled in the art, such as the phosphoramidite method.

[0028] The oligonucleotide may be labeled with an appropriate substance depending on the method for measuring the GATA2 expression level. Examples of the labeling substance include fluorescent substances (e.g., Cy3, Cy5), quenchers, luminescent substances (luciferin, etc.), enzymes (peroxidase, etc.), radioisotopes ( 3 H, 14 C. 32 P, and biotin. The oligonucleotide may also be immobilized on a solid phase.

[0029] The reagent for measuring the GATA2 expression level may be provided as a composition or kit for predicting the onset of Moyamoya disease. The composition or kit may include one or more reagents. In addition to the reagent, the composition may include additives such as buffers, stabilizers, and preservatives. The composition may be, for example, in liquid or lyophilized form. In addition to the reagent, the kit may include reagents and / or containers necessary for processing the sample collected from the subject and measuring the GATA2 expression level, and instructions. In one embodiment, the composition or kit includes two oligonucleotides that form one primer pair (forward primer and reverse primer). In addition to the primer pair, the composition or kit may include an additional oligonucleotide. The additional oligonucleotide is used, for example, as a probe.

[0030] Exemplary embodiments of the present disclosure are described below. [1] A method for predicting the onset of moyamoya disease, comprising measuring the GATA2 expression level in a sample taken from a subject carrying the p.R4810K mutation in the RNF213 gene. [2] The method according to item 1, comprising comparing the GATA2 expression level with a reference value. [3] The method according to item 2, wherein a subject is predicted to develop Moyamoya disease if the GATA2 expression level is higher than the reference value. [4] The method according to paragraph 3, further comprising predicting the clinical severity of the subject's Moyamoya disease. [5] Item 5. The method according to any one of items 1 to 4, wherein the measurement of the GATA2 expression level includes the measurement of GATA2 mRNA. [6] Item 6. The method according to any one of Items 1 to 5, wherein the sample is a blood sample. [7] 7. The method according to claim 6, wherein the blood sample is a peripheral blood sample.

[0031] [8] A composition for predicting the onset of Moyamoya disease in a subject carrying the p.R4810K mutation in the RNF213 gene, comprising a reagent for measuring GATA2 expression levels. [9] Item 9. The composition according to item 8, wherein the reagent comprises an oligonucleotide.

[10] Item 10. The composition of item 9, wherein the oligonucleotide is an oligonucleotide capable of binding to the sequence of SEQ ID NO: 4 or a sequence complementary thereto.

[11] Item 11. The composition according to item 9 or 10, wherein the oligonucleotide comprises or consists of a part of the sequence of SEQ ID NO: 4 or a sequence complementary thereto.

[12] Item 12. The composition according to any one of Items 9 to 11, wherein the oligonucleotide is 10 to 50 nucleotides in length.

[0032]

[13] A kit for predicting the onset of moyamoya disease in a subject carrying the p.R4810K mutation in the RNF213 gene, comprising a reagent for measuring GATA2 expression level.

[14] Item 14. The kit according to item 13, wherein the reagent comprises an oligonucleotide.

[15] Item 15. The kit according to item 14, wherein the oligonucleotide is an oligonucleotide capable of binding to the sequence of SEQ ID NO: 4 or a sequence complementary thereto.

[16] Item 16. The kit according to item 14 or 15, wherein the oligonucleotide comprises or consists of a part of the sequence of SEQ ID NO: 4 or a sequence complementary thereto.

[17] Item 17. The kit according to any one of Items 14 to 16, wherein the oligonucleotide is 10 to 50 nucleotides in length.

[0033]

[18] 1. A method of treating a subject, comprising: Predicting whether a subject will develop Moyamoya disease by the method described in any one of items 1 to 7; and To provide preventive treatment for cerebral infarction or intracranial hemorrhage to subjects predicted to develop moyamoya disease. A method comprising:

[19] Item 19. The method according to item 18, wherein the preventive treatment for cerebral infarction comprises administration of an antithrombotic agent.

[20] Item 19. The method according to item 18, wherein the preventive treatment of intracranial bleeding comprises extracranial / intracranial vascular anastomosis.

[0034] The present invention will be further illustrated by the following examples, which are not to be construed as limiting in any way. EXAMPLES

[0035] 1. Method patient Of the 19 families used in the previous linkage analysis study, 4 families showing incomplete penetrance of the p.R4810K mutation were used for the transcriptome analysis. There were 10 moyamoya disease patients and 5 non-affected mutation carriers (1 patient with very mild unilateral middle cerebral artery stenosis was considered non-affected). To validate the results of the transcriptome analysis, 43 moyamoya disease patients, 16 intracranial vascular disease patients, 19 non-affected mutation carriers, and 35 controls were prospectively collected and used as the validation cohort.

[0036] RNA extraction Total RNA was extracted from peripheral blood using the PAXgene Blood RNA Kit (#763134). RNA was extracted according to the protocol and frozen until analysis.

[0037] Transcriptome analysis NEBNext® Poly(A) mRNA Magnetic Isolation Module was used to isolate mRNA from total RNA. Libraries were generated using NEBNext Ultra II RNA Library Prep Kit for Illumina. RNA-Seq was performed at 100bp single end using NovaSeq 6000 (NovaSeq6000 SP Reagent Kit v1.5 (100 Cycles)). Based on the amount of cells homogenized in RLT buffer (79216, Qiagen), total RNA was isolated using RNeasy Mini Kit (74106, Qiagen) and RNeasy Micro Kit (74004, Qiagen) according to the manufacturer's protocol, as well as on-column DNase digestion (79254, Qiagen). Total RNA quality and quantity were assessed on a 2100 Bioanalyzer instrument according to the manufacturer's protocol (Agilent RNA 6000 Nano (G2938-90034, Agilent Technologies) and Agilent RNA 6000 Pico (G2938-90046, Agilent Technologies). For total RNA samples with RIN > 7, TruSeq stranded mRNA libraries were generated according to the manufacturer's protocol (Document # 1000000040498 v00, Illumina). The generated stranded mRNA libraries were analyzed on a 2100 Bioanalyzer instrument according to the manufacturer's protocol "Agilent DNA 7500 kit" (G2938-90024, Agilent Technologies), diluted to 10 nM, and loaded for sequencing on the HiSeq 2500 and NovaSeq 6000 Illumina sequencing platforms.NovaSeq 6000 paired-end sequencing was performed using 54 cycles for Read 1, 19 cycles for Read i7, 10 cycles for Read i5, and 54 cycles for Read 2, using NovaSeq6000 SP Reagent Kit v1.5 (100 cycles) (20028401, Illumina). RNA libraries were prepared for sequencing using standard Illumina protocols. The average number of clusters was 69,958,858. Quality control was performed by Trimmomatic (LEADING:20, TRAILING:20, SLIDINGWINDOW:4:15, MINLEN:36) and adapter trimming was performed by ILLUMINACLIP:adapters.fa:2:10:10 (Bolger, Lohse and Usadel, 2014). Reads were mapped to the genome using GRCh38 (Dobin et al., 2013). RNA read counts were calculated by featureCounts (Liao, Smyth and Shi, 2014) and normalized by trimmed mean M value (TMM) using edgeR (Law et al., 2016).

[0038] Bayesian Network Analysis We used INGOR.0.14.0 (a new version of SiGN-BN) to estimate the Bayesian network. Supercomputing resources were provided by the Human Genome Center, Institute of Medical Science, The University of Tokyo (http: / / sc.hgc.jp / shirokane.html).

[0039] WGCNA analysis The gene network for moyamoya disease identified by the Bayesian network was also confirmed by WGCNA analysis, which was performed using R version 4.2.2.

[0040] RT-qPCR cDNA was synthesized by reverse transcription of mRNA. GATA2 gene expression was measured by RT-qPCR (StepOne Plus). The patient (CVD004) sample was used as the reference and the ratio was calculated as the value. The sequences of variant 1, the major variant of GATA2 mRNA, and variant 2, the minor variant, whose expression was measured by RT-qPCR, are shown in SEQ ID NOs: 4 and 5. CGGAACCGGAAGATGTCCAA (SEQ ID NO: 6) and TTGACAGCTCCTCGAAGCAC (SEQ ID NO: 7) were used as the forward and reverse primers. This primer set covers both variants.

[0041] statistical analysis Continuous variables were tested with Student's t-test, and categorical variables with chi-squared test. All analyses were performed using R version 4.0.5. One-way analysis of variance was used to test for differences in age at onset between the three GATA2 levels. The Cochran-Armitage trend test was used to test whether the proportion of asymptomatic patients decreased with increasing GATA2 levels. All statistical analyses were performed using R version 4.0.5. or Graphpad Prism 9.5.0.

[0042] 2. Results Transcriptome analysis RNA-Seq was performed on 10 moyamoya disease patients and 5 non-affected mutation carriers. Non-affected carriers were significantly younger than moyamoya disease patients. Differentially expressed genes (DEGs) between patients and carriers were analyzed. Only seven genes were significant after adjustment for multiple comparisons, and the heat map did not show any specific pattern between moyamoya disease patients and non-affected carriers. The small population size may have led to insufficient power, which may have hindered the identification of disease-related gene expression. Because the expression of some genes is closely related, grouping these genes would improve power. Therefore, we used WGCNA analysis to explore gene networks associated with increased penetrance of the p.R4810K mutation.

[0043] Bayesian Network Analysis It was suggested that the gene expression signature formed by multiple genes, rather than the expression of individual genes, influenced the penetrance of the p.R4810K mutation. To identify the signature, we used Bayesian network analysis. As a result, the GATA2 gene network (GATA2, HDC, SLC45A3, AKAP12) was shown to be highly expressed in affected individuals with familial moyamoya disease compared to carriers.

[0044] WGCNA analysis WGCNA analysis also revealed significantly increased expression of GATA2, SLC45A3, HDC, and AKAP12 in disease-affected individuals compared with carriers.

[0045] GATA2 expression and clinical symptoms GATA2 expression was measured by RT-qPCR and compared between age- and sex-matched patients, non-affected mutation carriers, and controls. No difference was observed between carriers and controls, but GATA2 expression was significantly higher in patients than in carriers (Figure 2, left). ROC analysis showed an AUC of 0.74, and the cutoff value for distinguishing patients from carriers was 8.06 (Figure 2, right). GATA2 expression was also significantly different between moyamoya disease patients and patients with other cerebrovascular stenosis (Figure 3). When this value was applied to the family, all carriers were below 8.06, and all affected patients, except for one, were above 8.06 (Figure 1). When GATA2 expression was divided into low expression (0-8), medium expression (8-16), and high expression (16 or more), the higher the expression, the younger the age at onset (p = 0.035), the higher the proportion of bilateral lesions (trend p < 0.001), and the fewer asymptomatic subjects (trend p = 0.0047) (Figure 4, upper right, lower left, lower right). In controls, GATA2 expression was higher with age (Figure 4, upper left), so it is unlikely that the relationship between GATA2 expression and age at onset is influenced by age at blood sampling.

[0046] These results suggest that p.R4810K mutation carriers can be divided into those who develop moyamoya disease and those who do not, and that GATA2 expression levels correlate with the age at onset and severity of moyamoya disease. These results suggest that the onset of moyamoya disease can be predicted in p.R4810K mutation carriers based on GATA2 expression levels.

[0047] Human GATA2 (SEQ ID NO:3) MEVAPEQPRWMAHPAVLNAQHPDSHPGLAHNYMEPAQLLPPDEVDVFFNHLDSQGNPYYANPAHARARVSYSPAHARLTGGQMCRPHLLHSPGLPWLDGGKAALSAAAAHHHNPWTVSP FSKTPLHPSAAGGPGGPLSVYPGAGGGSGGGSGSSVASLTPTAAHSGSHLFGFPPTPPKEVSPDPSTTGAASPASSSAGGSAARGEDKDGVKYQVSLTESMKMESGSPLRPGLATMGTQP ATHHPIPTYPSYVPAAAHDYSSGLFHPGGFLGGPASSFTPKQRSKARSCSEGRECVNCGATATPLWRRDGTGHYLCNACGLYHKMNGQNRPLIKPKRRLSAARRAGTCCANCQTTTTTLW RRNANGDPVCNACGLYYKLHNVNRPLTMKKEGIQTRNRKMSNKSKKSKKGAECFEELSKCMQEKSSPFSAAALAGHMAPVGHLPPFSHSGHILPTPTPIHPSSSLSFGPHPSSMVTAMG Human GATA2 mRNA variant 1 (NM_001145661.2) (SEQ ID NO: 4) 1 actgggtcaa gcacagccct gagcggccgc gtgtccgagg cccaggtgcc ctctagagcc 61 ctgtagttcc tgcccctctc tgcccctctc ggctcctgct gttccgccgc tgtcgtccga 121 accatcccaa cccccagtcc acccagacag cgcccgagct aggggaggga acggtctggg 181 agtcggcagc tggcgccagg gcggccggag gatgccgagg ggccggagcc gggagggccc 241 gaggccgagg cgcactctac ccccagctcc taccctgtaa gccccgccag cctccggacg 301 tgctgtccct gggcccgtcg ccctcggggc tcccgccgga actccttcac tctcagaggc 361 cgagtccctc ccctccccac ggctgcgtgt ggccgttgcc gtctgcaccc agaccctgag 421 ccgccgccgc cggccatgga ggtggcgccc gagcagccgc gctggatggc gcacccggcc 481 gtgctgaatg cgcagcaccc cgactcacac cacccgggcc tggcgcacaa ctacatggaa 541 cccgcgcagc tgctgcctcc agacgaggtg gacgtcttct tcaatcacct cgactcgcag 601 ggcaacccct actatgccaa ccccgctcac gcgcgggcgc gcgtctccta cagccccgcg 661 cacgcccgcc tgaccggagg ccagatgtgc cgcccacact tgttgcacag cccgggtttg 721 ccctggctgg acgggggcaa agcagccctc tctgccgctg cggcccacca ccacaacccc 781 tggaccgtga gccccttctc caagacgcca ctgcacccct cagctgctgg aggccctgga 841 ggcccactct ctgtgtaccc aggggctggg ggtgggagcg ggggaggcag cgggagctca 901 gtggcctccc tcacccctac agcagcccac tctggctccc accttttcgg cttcccaccc 961 acgccaccca aagaagtgtc tcctgaccct agcaccacgg gggctgcgtc tccagcctca 1021 tcttccgcgg ggggtagtgc agcccgagga gaggacaagg acggcgtcaa gtaccaggtg 1081 tcactgacgg agagcatgaa gatggaaagt ggcagtcccc tgcgcccagg cctagctact 1141 atgggcaccc agcctgctac acaccacccc atccccacct acccctccta tgtgccggcg 1201 gctgcccacg actacagcag cggactcttc caccccggag gcttcctggg gggaccggcc 1261 tccagcttca cccctaagca gcgcagcaag gctcgttcct gttcagaagg ccgggagtgt 1321 gtcaactgtg gggccacagc cacccctctc tggcggcggg acggcaccgg ccactacctg 1381 tgcaatgcct gtggcctcta ccacaagatg aatgggcaga accgaccact catcaagccc 1441 aagcgaagac tgtcggccgc cagaagagcc ggcacctgtt gtgcaaattg tcagacgaca 1501 accaccacct tatggcgccg aaacgccaac ggggaccctg tctgcaacgc ctgtggcctc 1561 tactacaagc tgcacaatgt taacaggcca ctgaccatga agaaggaagg gatccagact 1621 cggaaccgga agatgtccaa caagtccaag aagagcaaga aaggggcgga gtgcttcgag 1681 gagctgtcaa agtgcatgca ggagaagtca tcccccttca gtgcagctgc cctggctgga 1741 cacatggcac ctgtgggcca cctcccgccc ttcagccact ccggacacat cctgcccact 1801 ccgacgccca tccacccctc ctccagcctc tccttcggcc acccccaccc gtccagcatg 1861 gtgaccgcca tgggctaggg aacagatgga cgtcgaggac cgggcactcc cgggatgggt 1921 ggaccaaacc cttagcagcc cagcatttcc cgaaggccga caccactcct gccagcccgg 1981 ctcggcccag caccccctct cctggagggc gcccagcagc ctgccagcag ttactgtgaa 2041 tgttccccac cgctgagagg ctgcctccgc acctgaccgc tgcccaggtg gggtttcctg 2101 catggacagt tgtttggaga acaacaagga caactttatg tagagaaaag gaggggacgg 2161 ggcaaccatt tttagaagga aaaaggatta ggcaaaata atttattttg 2221 ctcttgtttc taacaaggac ttggagactt ggtggtctga gctgtcccaa gtcctccggt 2281 tcttctcgg gattggcggg tccacttgcc agggctctgg gggcagattt gtggggacct 2341 cagcctgcac cctcttctcc tctggcttcc ctctctgaaa tagccgaact ccaggctggg 2401 ctgagccaaa gccagagtgg ccacggccca gggagggtga gctggtgcct gctttgacgg 2461 gccaggccct ggagggcaga gacaatcacg ggcggtcctg cacagattcc caggccaggg 2521 ctgggtcaca ggaaggaaac aacattttct tgaaagggga aacgtctccc agatcgctcc 2581 cttggctttg aggccgaagc tgctgtgact gtgtcccctt actgagcgca agccacagcc 2641 tgtcttgtca ggtggaccct gtaaatacat cctttttctg ctaacccttc aaccccctcg 2701 cctccactc tgagacaaaa gaaaaaatat taaaaaaaatg cataggctta actcgctgat 2761 gagttaattg ttttattttt aaactctttt tgggtccagt tgattgtacg tagccacagg 2821 agccctgcta tgaaaggaat aaaacctaca cacaaggttg gagcttttgca attctttttg 2881 gaaaagagct gggatcccac agccctagta tgaaagctgg gggtggggag gggcctttgc 2941 tgcccttggt ttctggggc tggttggcat ttgctggcct ggcaggggt gaaggcagga 3001 gttgggggca ggtcaggacc aggacccagg gagaggctgt gtccctgctg gggtctcagg 3061 tccagcttta ctgtggctgt ctggatcctt cccaaggtac agctgtatat aaacgtgtcc 3121 cgagcttaga ttctgtatgc ggtgacggcg gggtgtggtg gcctgtgagg ggcccctggc 3181 ccaggaggag gattgtgctg atgtagtgac caagtgcaat atgggcgggc agtcgctgca 3241 gggagcacca cggccagaag taacttattt tgtactagtg tccgcataag aaaaagaatc 3301 ggcagtattt tctgttttta tgttttattt ggcttgtttt attttggatt agtgaactaa 3361 gttattgtta attatgtaca acatttatat attgtctgta aaaaatgtat gctatcctct 3421 tattccttta aagtgagtac tgttaagaat aataaaatac tttttgtgaa Human GATA2 mRNA Variant 2 (NM_032638.5) (SEQ ID NO: 5) 1 gagagagagg cagcgtgagc gccaggaagg tagcgaggcc agcgtcgccc cgggactcgc 61 tgctcaagtc tgtctattgc ctgccgccac atccatccta gcagggcccc gtcgcccacc 121 aggcggacaa aagcggtccg ctgaacacca tgcggccgct cggcgtgccg cccaggctct 181 gctggtgagc gccgccaccc cgcgcccagg tcccgcgagc ccgcctgccg cgcacctcgc 241 cctgctccca gctctactcc aggccccgtc cgcccggggg cgccgcccac cgcgcctcgc 301 tcgggccgtt gccgtctgca cccagaccct gagccgccgc cgccggccat ggaggtggcg 361 cccgagcagc cgcgctggat ggcgcacccg gccgtgctga atgcgcagca ccccgactca 421 caccacccgg gcctggcgca caactacatg gaacccgcgc agctgctgcc tccagacgag 481 gtggacgtct tcttcaatca cctcgactcg cagggcaacc cctactatgc caaccccgct 541 cacgcgcggg cgcgcgtctc ctacagcccc gcgcacgccc gcctgaccgg aggccagatg 601 tgccgcccac acttgttgca cagcccgggt ttgccctggc tggacggggg caaagcagcc 661 ctctctgccg ctgcggccca ccaccacaac ccctggaccg tgagcccctt ctccaagacg 721 ccactgcacc cctcagctgc tggaggccct ggaggcccac tctctgtgta cccaggggct 781 gggggtggga gcgggggagg cagcgggagc tcagtggcct ccctcacccc tacagcagcc 841 cactctggct cccacctttt cggcttccca cccacgccac ccaaagaagt gtctcctgac 901 cctagcacca cgggggctgc gtctccagcc tcatcttccg cggggggtag tgcagcccga 961 ggagaggaca aggacggcgt caagtaccag gtgtcactga cggagagcat gaagatggaa 1021 agtggcagtc ccctgcgccc aggcctagct actatgggca cccagcctgc tacacaccac 1081 cccatcccca cctacccctc ctatgtgccg gcggctgccc acgactacag cagcggactc 1141 ttccaccccg gaggcttcct ggggggaccg gcctccagct tcacccctaa gcagcgcagc 1201 aaggctcgtt cctgttcaga aggccgggag tgtgtcaact gtggggccac agccacccct 1261 ctctggcggc gggacggcac cggccactac ctgtgcaatg cctgtggcct ctaccacaag 1321 atgaatgggc agaaccgacc actcatcaag cccaagcgaa gactgtcggc cgccagaaga 1381 gccggcacct gttgtgcaaa ttgtcagacg acaaccacca ccttatggcg ccgaaacgcc 1441 aacggggacc ctgtctgcaa cgcctgtggc ctctactaca agctgcacaa tgttaacagg 1501 ccactgacca tgaagaagga agggatccag actcggaacc ggaagatgtc caacaagtcc 1561 aagaagagca agaaaggggc ggagtgcttc gaggagctgt caaagtgcat gcaggagaag 1621 tcatccccct tcagtgcagc tgccctggct ggacacatgg cacctgtggg ccacctcccg 1681 cccttcagcc actccggaca catcctgccc actccgacgc ccatccaccc ctcctccagc 1741 ctctccttcg gccaccccca cccgtccagc atggtgaccg ccatgggcta gggaacagat 1801 ggacgtcgag gaccgggcac tcccgggatg ggtggaccaa acccttagca gcccagcatt 1861 tcccgaaggc cgacaccact cctgccagcc cggctcggcc cagcaccccc tctcctggag 1921 ggcgcccagc agcctgccag cagttactgt gaatgttccc caccgctgag aggctgcctc 1981 cgcacctgac cgctgcccag gtggggtttc ctgcatggac agttgtttgg agaacaacaa 2041 ggacaacttt atgtagagaa aaggagggga cgggacagac gaaggcaacc atttttagaa 2101 ggaaaaagga ttaggcaaaa ataatttatt ttgctcttgt ttctaacaag gacttggaga 2161 cttggtggtc tgagctgtcc caagtcctcc ggttcttcct cgggattggc gggtccactt 2221 gccagggctc tgggggcaga tttgtgggga cctcagcctg caccctcttc tcctctggct 2281 tccctctctg aaatagccga actccaggct gggctgagcc aaagccagag tggccacggc 2341 ccagggaggg tgagctggtg cctgctttga cgggccaggc cctggagggc agagacaatc 2401 acgggcggtc ctgcacagat tcccaggcca gggctgggtc acaggaagga aacaacattt 2461 tcttgaaagg ggaaacgtct cccagatcgc tcccttggct ttgaggccga agctgctgtg 2521 actgtgtccc cttactgagc gcaagccaca gcctgtcttg tcaggtggac cctgtaaata 2581 catccttttt ctgctaaccc ttcaaccccc tcgcctccta ctctgagaca aaagaaaaaa 2641 tattaaaaaa atgcataggc ttaactcgct gatgagttaa ttgttttatt tttaaactct 2701 ttttgggtcc agttgattgt acgtagccac aggagccctg ctatgaaagg aataaaacct 2761 acacacaagg ttggagcttt gcaattcttt ttggaaaaga gctgggatcc cacagcccta 2821 gtatgaaagc tgggggtggg gaggggcctt tgctgccctt ggtttctggg ggctggttgg 2881 catttgctgg cctggcaggg ggtgaaggca ggagttgggg gcaggtcagg accaggaccc 2941 agggagaggc tgtgtccctg ctggggtctc aggtccagct ttactgtggc tgtctggatc 3001 cttcccaagg tacagctgta tataaacgtg tcccgagctt agattctgta tgcggtgacg 3061 gcggggtgtg gtggcctgtg aggggcccct ggcccaggag gaggattgtg ctgatgtagt 3121 gaccaagtgc aatatgggcg ggcagtcgct gcagggagca ccacggccag aagtaactta 3181 ttttgtacta gtgtccgcat aagaaaaaga atcggcagta ttttctgttt ttatgtttta 3241 tttggcttgt tttattttgg attagtgaac taagttattg ttaattatgt acaacattta 3301 tatattgtct gtaaaaaatg tatgctatcc tcttattcct ttaaagtgag tactgttaag 3361 aataataaaa tacttttgt gaa

Claims

1. A method for predicting the onset of moyamoya disease, comprising measuring the GATA2 expression level in a sample taken from a subject carrying the p.R4810K mutation in the RNF213 gene.

2. The method of claim 1, comprising comparing the GATA2 expression level with a reference value.

3. The method according to claim 2, wherein the subject is predicted to develop Moyamoya disease if the GATA2 expression level is higher than the reference value.

4. 4. The method of claim 3, further comprising predicting the clinical severity of Moyamoya disease in the subject.

5. The method of claim 1 , wherein measuring the GATA2 expression level comprises measuring GATA2 mRNA.

6. The method according to any one of claims 1 to 5, wherein the sample is a blood sample.

7. The method of claim 6, wherein the blood sample is a peripheral blood sample.

8. A composition for predicting the onset of Moyamoya disease in a subject carrying the p.R4810K mutation in the RNF213 gene, comprising a reagent for measuring GATA2 expression levels.

9. A kit for predicting the onset of moyamoya disease in a subject carrying the p.R4810K mutation in the RNF213 gene, comprising a reagent for measuring GATA2 expression level.

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