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J Stroke > Volume 28(1); 2026 > Article
Takashima, Kiyohara, Nakamura, Ozaki, Yoshino, Hashimoto, Hidaka, Sahara, Irie, Wakisaka, Matsuo, Kamouchi, Kitazono, Ago, and for the Fukuoka Stroke Registry Investigators: RNF213 p.R4810K Variant and Intracranial Atherosclerosis: Increased Risk in Obese Variant Carriers
Dear Sir:
Acute ischemic stroke (AIS) is a leading cause of disability and mortality, warranting detailed investigation into its underlying mechanisms. A major subtype of AIS is atherothrombotic brain infarction, which often results from intracranial atherosclerotic disease (ICAD). In addition to traditional atherosclerotic risk factors, emerging evidence suggests a role for genetic contributors [1]. The p.R4810K variant of the ring finger protein 213 gene (RNF213, mysterin), a susceptibility gene for Moyamoya disease, has also been associated with ICAD, particularly in the anterior circulation [2]. This variant is relatively prevalent among East Asian populations, especially in Japan, where approximately 1%-2% of the general population carries the RNF213 p.R4810K allele [2]. Consequently, the “two-hit hypothesis” has been proposed, suggesting that additional genetic or environmental factors are necessary to trigger vascular stenosis. The search for such secondary factors is ongoing [3]. This study aimed to evaluate the association between RNF213 p.R4810K and ICAD and to investigate, in line with the two-hit hypothesis, effect modification by traditional atherosclerotic risk factors, using data from a multicenter stroke registry.
We analyzed 14,471 patients with AIS or transient ischemic attack enrolled in the Fukuoka Stroke Registry [4]. Details of patient selection are provided in the Supplementary Methods and in the Supplementary Figure 1. The study design was approved by the Institutional Review Boards of all participating hospitals. Written informed consent was obtained from all patients or their legal representatives. Genetic testing for RNF213 p.R4810K (rs112735431) was performed using the Melt Analysis of Mismatch Amplification Mutation Assays [5]. Patients were classified as wild-type (G/G) or variant carriers (G/A or A/A). ICAD was defined as ≥50% stenosis or occlusion of major intracranial arteries on magnetic resonance angiography or computed tomography angiography [6], as initially interpreted independently at each participating hospital by at least one radiologist and one stroke neurologist. For the sensitivity analysis, intracranial atherosclerotic stenosis (ICAS) was defined as ≥50% stenosis without occlusion.
Logistic regression analysis was used to estimate odds ratios (ORs) and 95% confidence intervals for each outcome. Exploratory interaction analyses were also conducted using multiplicative terms to assess potential effect modification by traditional atherosclerotic risk factors. Body mass index (BMI) was categorized into four groups (<18.5, 18.5-24.9, 25.0-29.9, and ≥30.0 kg/m2) [7]. Heterogeneity was further explored by stratifying the analyses by BMI. Patients were divided into eight subgroups based on RNF213 p.R4810K carrier status and BMI category. Interaction effects were tested by including multiplicative interaction terms in the corresponding logistic regression models. Two-tailed P values <0.05 were considered statistically significant. All statistical analyses were performed using STATA version 16.0 (StataCorp., College Station, TX, USA). Further details on the ethics statement, genotyping procedures, ICAD definitions, clinical variables, and statistical analyses are provided in the Supplementary Methods.
The mean age of the 14,471 patients was 73 (±12) years, and 8,593 (59.4%) were men. Of all participants, 14,100 (97.4%) were non-carriers and 371 (2.6%) were carriers of the p.R4810K variant (Supplementary Table 1). A total of 3,347 patients (23.1%) had ICAD, including 2,358 (16.3%) with anterior circulation lesions (anterior-intracranial atherosclerotic disease [a-ICAD]) and 1,686 (11.7%) with posterior circulation lesions (posterior-intracranial atherosclerotic disease [p-ICAD]). Among those with ICAD, 150 were variant carriers and 3,197 were non-carriers (Supplementary Table 2). The RNF213 p.R4810K variant was significantly associated with an increased risk of ICAD, including both a-ICAD and p-ICAD, even after adjusting for age, sex, and vascular risk factors (Supplementary Table 3). When stratified by covariates, significant heterogeneity was observed in the ORs for ICAD among variant carriers by age (P for heterogeneity <0.001) and BMI categories (P=0.027) (Supplementary Table 4). Table 1 presents baseline characteristics by BMI category, including the distribution of RNF213 variant carriers and ICAD prevalence. Both RNF213 variant carrier and ICAD prevalence tended to increase with higher BMI. In the subgroup analysis across the four BMI categories, the risk of ICAD among variant carriers increased progressively with increasing BMI. Significant heterogeneity was observed for overall ICAD and a-ICAD but not for p-ICAD (Figure 1). When the ICAD risk was analyzed across variant and BMI categories, an increasing trend was observed only among variant carriers, with no such trend among non-carriers (P for interaction=0.014) (Table 2). These findings were consistent with the sensitivity analyses using ICAS as the outcome (Supplementary Tables 5 and 6).
Based on our findings, the RNF213 p.R4810K variant was significantly associated with an increased risk of both a-ICAD and p-ICAD. This association appeared particularly strong for a-ICAD in younger individuals and those with a higher BMI. Our results suggest that an elevated BMI, that is, obesity, may increase the risk of a-ICAD among RNF213 p.R4810K carriers (Figure 1 and Table 2). RNF213 encodes an E3 ubiquitin ligase that modulates signaling pathways involving nuclear factor of activated T cells and hypoxia-inducible factor, both of which are implicated in obesity, angiogenesis, and atherosclerosis [8,9]. Reduced RNF213 function due to the variant [10] may therefore increase susceptibility to vascular disease under conditions of metabolic stress. Although the mechanism by which these factors selectively promote a-ICAD remains unclear, regional vascular characteristics, such as differences in shear stress, may contribute. Further investigation should focus on identifying obesity-related genetic or environmental factors—such as insulin resistance, chronic inflammation, and dysregulated lipid metabolism—as potential second-hit modifiers in RNF213-related a-ICAD.
Although the RNF213 variant precedes clinical events and may support causal inference, this study was cross-sectional and conducted in a single region of Japan, which may limit the temporal and geographic generalizability of our findings. Although exploratory, the interaction analysis revealed patterns that warrant further investigation. These findings suggest that RNF213 p.R4810K carriers may be particularly susceptible to ICAD in the context of obesity, helping to clarify the heterogeneous vascular phenotypes associated with RNF213 and guiding future research on modifiable cofactors. Further investigation into obesity-related genetic and environmental factors may elucidate the mechanisms underlying RNF213-related vasculopathy and support the development of novel therapeutic strategies for RNF213 p.R4810K carriers.

Supplementary materials

Supplementary materials related to this article can be found online at https://doi.org/10.5853/jos.2025.02607.
Supplementary Table 1.
Baseline characteristics between the RNF213 p.R4810K variant carriers and non-carriers
jos-2025-02607-Supplementary-Table-1,2.pdf
Supplementary Table 2.
Crude prevalence of ICAD distribution based on RNF213 p.R4810K variant
jos-2025-02607-Supplementary-Table-1,2.pdf
Supplementary Table 3.
Association of the RNF213 p.R4810K variant and ICAD
jos-2025-02607-Supplementary-Table-3,4.pdf
Supplementary Table 4.
Association of the RNF213 p.R4810K variant and ICAD stratified by covariates
jos-2025-02607-Supplementary-Table-3,4.pdf
Supplementary Table 5.
Association of the RNF213 p.R4810K variant and ICAS
jos-2025-02607-Supplementary-Table-5,6.pdf
Supplementary Table 6.
Comparison of ICAS risk across RNF213 p.R4810K variant and BMI categories (n=14,462)
jos-2025-02607-Supplementary-Table-5,6.pdf
Supplementary Figure 1.
Flowchart of patient selection for the main analysis.
jos-2025-02607-Supplementary-Fig-1.pdf

Notes

Funding statement
This study was supported by Grants-in-Aid for Scientific Research (KAKENHI) from the Japan Society for the Promotion of Science (JSPS) (grant numbers JP21K10330, JP21K19648, JP21H03165, and JP24K02669), Astellas Foundation for Research on Metabolic Disorders, and Grant of the Clinical Research Promotion Foundation (2023).
Conflicts of interest
The authors have no financial conflicts of interest.
Author contribution
Conceptualization: Masamitsu Takashima, Takuya Kiyohara, Kuniyuki Nakamura, Tetsuro Ago. Study design: Masamitsu Takashima, Takuya Kiyohara. Methodology: Masamitsu Takashima, Takuya Kiyohara. Data collection: Masamitsu Takashima, Takuya Kiyohara, Kuniyuki Nakamura, Yuichi Ozaki, Fumitaka Yoshino, Go Hashimoto, Masaoki Hidaka, Noriyuki Sahara, Tetsuro Ago. Investigation: Masamitsu Takashima, Takuya Kiyohara. Statistical analysis: Masamitsu Takashima, Takuya Kiyohara. Writing—original draft: Masamitsu Takashima, Takuya Kiyohara. Writing—review & editing: all authors. Funding acquisition: Takuya Kiyohara, Kuniyuki Nakamura, Yoshinobu Wakisaka, Takanari Kitazono, Masahiro Kamouchi, Ryu Matsuo, Tetsuro Ago. Approval of final manuscript: all authors.
Acknowledgments
We thank all study participants, Fukuoka Stroke Registry investigators, and all clinical research coordinators (Hisayama Research Institute for Lifestyle Diseases). The Steering Committee and Research Working Group members of the Fukuoka Stroke Registry are provided in the Appendix.

Figure 1.
Association of the RNF213 p.R4810K variant with ICAD across different BMI categories. The multivariable model was adjusted for age, sex, hypertension, diabetes mellitus, dyslipidemia, smoking, and drinking. ICAD, intracranial atherosclerotic disease; BMI, body mass index; OR, odds ratio; CI, confidence interval; Ph, P value for heterogeneity.
jos-2025-02607f1.jpg
Table 1.
Baseline characteristics and ICAD prevalence by BMI category
BMI category (kg/m2)
P for trend
<18.5 (n=1,584) 18.5-24.9 (n=9,141) 25.0-29.9 (n=3,174) ≥30.0 (n=563)
RNF213 variant carriers 38 (2.4) 219 (2.4) 87 (2.7) 27 (4.8) 0.005
ICAD overall 311 (19.6) 2,075 (22.7) 809 (25.5) 151 (26.8) <0.001
 Anterior-ICAD 237 (15.0) 1,445 (15.8) 570 (18.0) 105 (18.7) <0.001
 Posterior-ICAD 155 (9.8) 1,064 (11.6) 387 (12.2) 79 (14.0) 0.024
Age (yr) 80±12 74±12 70±12 64±14 <0.001
Male sex 629 (39.7) 5,568 (60.9) 2,066 (65.1) 325 (57.7) <0.001
Hypertension 1,171 (73.9) 7,274 (79.6) 2,783 (87.7) 515 (91.5) <0.001
Diabetes mellitus 307 (19.4) 2,706 (29.6) 1,217 (38.3) 273 (48.5) <0.001
Dyslipidemia 515 (32.5) 4,943 (54.1) 2,134 (67.2) 427 (75.8) <0.001
eGFR (mL/min/1.73 m2) 64.3±29.2 65.8±24.5 66.8±23.0 68.9±23.3 <0.001
Atrial fibrillation 578 (36.5) 2,222 (24.3) 606 (19.1) 105 (18.7) <0.001
Smoking 653 (41.2) 4,944 (54.1) 1,805 (56.9) 340 (60.4) <0.001
Drinking 326 (20.6) 3,218 (35.2) 1,222 (38.5) 170 (30.2) <0.001
Previous stroke or TIA 331 (20.9) 1,680 (18.4) 566 (17.8) 80 (14.2) <0.001
Coronary artery disease 227 (14.3) 1,346 (14.7) 481 (15.2) 70 (12.4) 0.391
Family history of stroke* 468 (30.7) 3,384 (38.1) 1,215 (39.4) 244 (44.0) <0.001
Ischemic stroke subtype
 Lacunar 213 (13.4) 1,624 (17.8) 675 (21.3) 138 (24.5) <0.001
 Atherothrombotic 206 (13.0) 1,517 (16.6) 579 (18.2) 99 (17.6) <0.001
 Cardioembolic 543 (34.3) 1,963 (21.5) 489 (15.4) 85 (15.1) <0.001
 Unclassified 554 (35.0) 3,348 (36.6) 1,153 (36.3) 194 (34.5) 0.484
TIA 68 (4.3) 689 (7.5) 278 (8.8) 47 (8.4) <0.001
Values are presented as n (%) or mean±standard deviation. Percentages are based on patients with available BMI values.
BMI, body mass index; ICAD, intracranial atherosclerotic disease; eGFR, estimated glomerular filtration rate; TIA, transient ischemic attack.
* Some variables may display different denominators depending on the number of missing data.
Table 2.
Comparison of ICAD risk across RNF213 p.R4810K variant and BMI categories (n=14,462)
RNF213 variant BMI category (kg/m2) No. of events/subjects (%) Multivariable-adjusted OR (95% CI) P
Non-carriers <18.5 305/1,546 (19.7) 0.94 (0.81-1.08) 0.352
Non-carriers 18.5-24.9 1,986/8,922 (22.3) 1.00 (reference)
Non-carriers 25.0-29.9 772/3,087 (25.0) 1.09 (0.99-1.20) 0.083
Non-carriers ≥30.0 133/536 (24.8) 1.07 (0.86-1.31) 0.554
Carriers <18.5 6/38 (15.8) 0.74 (0.31-1.79) 0.505
Carriers 18.5-24.9 89/219 (40.6) 2.61 (1.97-3.44) <0.001
Carriers 25.0-29.9 37/87 (42.5) 2.50 (1.62-3.88) <0.001
Carriers ≥30.0 18/27 (66.7) 6.49 (2.87-14.71) <0.001
The multivariable model was adjusted for age, sex, hypertension, diabetes mellitus, dyslipidemia, smoking, and drinking. P for interaction (genotype×BMI category)=0.014, testing the interaction between RNF213 p.R4810K carrier status and BMI categories on ICAD risk.
ICAD, intracranial atherosclerotic disease; BMI, body mass index; OR, odds ratio; CI, confidence interval.

References

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Appendices

Appendix. Steering Committee and Research Working Group members of the Fukuoka Stroke Registry

Takao Ishitsuka, MD, PhD (Fukuoka Mirai Hospital, Fukuoka, Japan); Setsuro Ibayashi, MD, PhD (Chair, Seiai Rehabilitation Hospital, Onojo, Japan); Kenji Kusuda, MD, PhD (Seiai Rehabilitation Hospital, Onojo, Japan); Kenichiro Fujii, MD, PhD (Japan Seafarers Relief Association Moji Ekisaikai Hospital, Kitakyushu, Japan); Tetsuhiko Nagao, MD, PhD (Safety Monitoring Committee, Seiai Rehabilitation Hospital, Onojo, Japan); Yasushi Okada, MD, PhD (Vice-Chair, National Hospital Organization Kyushu Medical Center, Fukuoka, Japan); Masahiro Yasaka, MD, PhD (Fukuoka Neurosurgical Hospital, Fukuoka, Japan); Hiroaki Ooboshi, MD, PhD (Fukuoka Dental College Medical and Dental Hospital, Fukuoka, Japan); Takanari Kitazono, MD, PhD (Principal Investigator, Kyushu University, Fukuoka, Japan); Katsumi Irie, MD, PhD (Hakujyuji Hospital, Fukuoka, Japan); Tsuyoshi Omae, MD, PhD (Imazu Red Cross Hospital, Fukuoka, Japan); Kazunori Toyoda, MD, PhD (National Cerebral and Cardiovascular Center, Suita, Japan); Hiroshi Nakane, MD, PhD (National Hospital Organization Fukuoka-Higashi Medical Center, Koga, Japan); Masahiro Kamouchi, MD, PhD (Kyushu University, Fukuoka, Japan); Hiroshi Sugimori, MD, PhD (National Hospital Organization Kyushu Medical Center, Fukuoka, Japan); Shuji Arakawa, MD, PhD (Steel Memorial Yawata Hospital, Kitakyushu, Japan); Kenji Fukuda, MD, PhD (St Mary’s Hospital, Kurume, Japan); Tetsuro Ago, MD, PhD (Kyushu University, Fukuoka, Japan); Jiro Kitayama, MD, PhD (Fukuoka Red Cross Hospital, Fukuoka, Japan); Shigeru Fujimoto, MD, PhD (Jichi Medical University, Shimotsuke, Japan); Shoji Arihiro, MD (Japan Labor Health and Welfare Organization Kyushu Rosai Hospital, Kitakyushu, Japan); Junya Kuroda, MD, PhD (National Hospital Organization Fukuoka-Higashi Medical Center, Koga, Japan); Yoshinobu Wakisaka, MD, PhD (Kyushu University Hospital, Fukuoka, Japan); Yoshihisa Fukushima, MD (St Mary’s Hospital, Kurume, Japan); Ryu Matsuo, MD, PhD (Secretariat, Kyushu University, Fukuoka, Japan); Fumi Irie, MD, PhD (Kyushu University, Fukuoka, Japan); Kuniyuki Nakamura, MD, PhD (Kyushu University Hospital, Fukuoka, Japan); and Takuya Kiyohara, MD, PhD (Kyushu University Hospital, Fukuoka, Japan).


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