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. 2023 Oct 17;11(10):e1048. doi: 10.1002/iid3.1048

Inflammatory bowel disease and the risk of intracerebral hemorrhage: A Mendelian randomization study and meta‐analysis

Yanju Song 1, Xuelun Zou 2, Yi Zeng 3, Le Zhang 2,4,5, Xinfa Mao 1,✉
PMCID: PMC10580698  PMID: 37904677

Abstract

Background

The link between inflammatory bowel disease (IBD) and intracerebral hemorrhage (ICH) is still unclear.

Aims

We conducted a Mendelian randomization research and meta‐analysis to explore the impact of IBD and its subtypes (Crohn's disease [CD], ulcerative colitis [UC]) on the risk of ICH.

Methods

Two large genome‐wide association analysis studies of International Inflammatory Bowel Disease Genetics Consortium (IIBDGC) and International Stroke Genetics Consortium as exposure (IBD, UC, and CD) and outcome (ICH) in the initial stage. IBD, CD, UC GWAS data from the FinnGen consortium were adopted for the replication phase, and ultimately, the results of the initial stage and replication phase data were combined in a meta‐analysis to evaluate the causal association between IBD and its subtypes and the risk of ICH.

Results

In the initial stage, we found that in the IVW (odds ratio [OR] = 0.83, 95% confidence interval [CI]: 0.71–0.96, p = .01), MR‐PRESSO (OR = 0.85, 95% CI: 0.75–0.97, p = .02) and MR.RAPS (OR = 0.86, 95% CI: 0.76–0.98, p = .02) method showed that UC is associated with the risk of ICH. The causal relationship between IBD, CD, and the risk of ICH cannot be found by the IVW method. IBD and its subtypes UC, CD, and risk of ICH cannot find the presence of heterogeneity and pleiotropy. In replication stage, IBD (OR = 0.74, 95% CI: 0.59–0.94, p = .0135) related to ICH, while the IVW approach did not establish a causal link in UC and CD. The meta‐analysis still indicated that UC (OR = 0.83, 95% CI: 0.72–0.93, p < .05) would lessen the risk of ICH while the causality between IBD, CD, and ICH was unable to be established.

Conclusion

UC was causally related to ICH, but IBD and CD are not associated with ICH. The precise pathophysiological mechanism needs to be thoroughly investigated in more detail.

Keywords: Crohn's disease, genome‐wide association analysis, inflammatory bowel disease, intracerebral hemorrhage, Mendelian randomization, ulcerative colitis

This study systematically investigated the causal relationship between IBD, CD, UC, and the risk of ICH for the first time. Our findings confirmed a potential causal relationship between UC and ICH. Our findings highlighted that rs3024493, rs34920465, and rs483905 may be treated as specific biomolecular markers of ICH with potential significance in predicting the occurrence of hypertension and ICH.

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1. INTRODUCTION

Inflammatory bowel disease (IBD) is a prevalent autoimmune disease of the intestines, which consists of Crohn's disease (CD) and ulcerative colitis (UC). The prevalence of CD ranges from 25 to 300 cases per 100,000 individuals, and that of UC ranges from 35 to 250 cases per 100,000 people. 1 Studies have revealed that IBD, which can afflict people of all ages and affect all bodily areas, is on the rise globally in both incidence and prevalence. 2 Patients with IBD are susceptible to genetic factors and environmental triggers that lead to an imbalance in the intestinal flora, resulting in the disruption of the intestinal barrier. 2 , 3 Inflammatory cytokines, including tumor necrosis factor alpha, C‐reactive protein, interleukins, and vascular endothelial growth factor, are released into the circulation, overwhelming the immune system and leading to systemic inflammation. 3 Inflammatory factors have the potential to penetrate the brain through the blood circulation through the blood–brain barrier, affecting the health of the cerebral vasculature. On the other hand, long‐term immune system dysregulation due to IBD may also accelerate cerebrovascular damage. Therefore, patients with IBD have a higher probability of being at risk for concurrent cerebrovascular disease.

We are gradually turning our attention to the role that the gut plays in cerebrovascular illness as a result of the thorough study of gut bacteria. 4 , 5 IBD, CD, and UC are all thought to be risk factors for stroke according to some meta‐analyses evaluating the relationship between these conditions and stroke. 6 , 7 A retrospective cohort research in Taiwan, China, involving 18,392 IBD patients and 73,568 healthy controls, revealed that IBD patients had an ischemic stroke 1.12 (95% CI: 1.02–1.23) times more frequently than individuals without IBD. 8 However, the relationship between IBD and cerebral hemorrhage, an important subtype of stroke, is unclear.

Due to its high death and disability rates, intracerebral hemorrhage (ICH), which causes roughly 29% of strokes, poses a severe threat to human health. 9 , 10 , 11 The risk factors that affect ICH are directly related to its high death rate and poor prognosis. 10 , 12 The dismal prognosis of ICH has not yet been improved despite steady in‐depth research on common risk factors for the disease, including hypertension, hyperlipidemia, excessive alcohol consumption, smoking, and so forth. 10 , 11 Therefore, early management may be able to somewhat lower the health risk of ICH if other risk factors are found.

Mendelian randomization (MR) study is a cutting‐edge epidemiological method to determine causality, which can explore the association between exposure and outcome from a genetic perspective, and discover risk factors or complications of disease, which is important for disease prevention. Therefore, to reduce the incidence of poor prognosis and prevent cerebral hemorrhage in patients with IBD, we propose to use MR studies to explore the association between IBD and its subtypes (CD and UC) and the risk of ICH. This will fill the gap in the research field of IBD and cerebrovascular disease, and make an important contribution to the accurate prediction of cerebrovascular events after reducing IBD.

2. METHODS

2.1. Research design and core assumptions

The main goal of this MR study is to establish causation through exposure, instrumental variables, and outcome. The exposure, instrumental variable, and outcome of the study were IBD and its subtypes, single‐nucleotide polymorphism (SNP) and ICH, respectively (Figure 1). Figure 2 illustrates three key assumptions that must be followed when utilizing MR in studies. First, there is a strong connection between instrumental variables (SNP) and exposure (IBD, CD, and UC). Second, there is no connection between confounders and instrumental variables (SNP). Confounding variables include smoking, binge drinking, hypertension, hypercholesterolemia, and sedentary behavior, among others. Finally, aside from exposures (IBD, CD, and UC), there are no other potential pathways through which instrumental variables (SNP) could affect the outcome (ICH). 12 , 13

Figure 1.

Figure 1

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Overview of the causal connections between IBD, including CD and UC as subtypes and ICH. CD, Crohn's disease; IBD, inflammatory bowel disease; ICH, intracerebral hemorrhage; IIBDGC, International Inflammatory Bowel Disease Genetics Consortium; ISGC, International Stroke Genetics Consortium; IVW, inverse variance weighted; UC, ulcerative colitis.

Figure 2.

Figure 2

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Three core assumptions of IBD, CD, UC with ICH in this two‐sample MR study. CD, Crohn's disease; IBD, inflammatory bowel disease; ICH, intracerebral hemorrhage; IVW, inverse variance weighted; UC, ulcerative colitis.

2.2. Source of population

To generate the exposures and outcomes used in this investigation, a genome‐wide association study (GWAS) was conducted on a large sample of European population genomes. The GWAS data for IBD, UC, and CD were obtained from the International Inflammatory Bowel Disease Genetics Consortium (IIBDGC), according to Table 1. This GWAS study looked into the genetic risk factors for the IBD, UC, and CD clinical phenotypes. This GWAS included a total of 34,652 European populations, 12,882 IBD patients, 21,770 controls, and 12,716,084 SNP sites. 14 It also included 27,432 individuals in UC (6968 cases and 20,464 non‐cases) and 20,883 individuals in CD (5956 cases and 14,927 non‐cases). The information on ICH was provided by a GWAS study which conducted by the International Stroke Genetics Consortium's (IGSC), with 3026 participants including 1545 cases and 1481 non‐cases. 15 FinnGen (https://finngen.gitbook.io/documentation/data-download) provided the data for the replication phase, which included 5673 cases and 213,119 controls with a total of 16,380,466 SNPs. Data on exposures and outcome were gathered from published GWAS, and the participants gave their informed consent and underwent an ethical review. Therefore, no additional ethical review of this study is needed.

Table 1.

Information fundamental for the inclusion of exposure and outcome data in GWAS.

Consortium Phenotype Number of SNP Cases Controls Sample size Population PMID
IIBDGC UC 12,255,197 6968 20,464 27,432 European 26192919
CD 12,276,506 5956 14,927 20,883 European 26192919
IBD 12,716,084 12,882 21,770 34,652 European 26192919
FinnGen UC 16,380,453 2251 210,300 212,551 European https://finngen.gitbook.io/documentation/data-download
CD 16,380,466 940 217,852 218,792 European
IBD 16,380,466 5673 213,119 218,792 European
ISGC ICH NA 1545 1481 3026 European 24656865
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Abbreviations: CD, Crohn's disease; IBD, inflammatory bowel disease; ICH, intracerebral hemorrhage; SNP, single‐nucleotide polymorphism; UC, ulcerative colitis.

2.3. Mendelian randomization

We used the MR method to conduct this investigation, and the procedure was as follows. First, we searched the PubMed database to find the sources of the GWAS data for the included IBD, UC, CD, and ICH. Representative published GWAS data were used to generate the GWAS of exposure and outcome. 14 , 15 The GWAS analysis of exposure and outcome included people from the same pedigree population, as well (European population). Second, we retrieved instrumental variables for IBD, UC, and CD from the GWAS data. p < 5 × 10−8, r 2 for .01, kb = 1000 is our extraction criterion for instrumental variables. Additionally, three or more SNPs that met the inclusion requirements were considered to be able to be included as instrumental variables. When the F‐statistic is greater than 10, we can overlook the bias of weak instrumental variables that are assessed using this statistic. 16 Then, using MR study methods such as inverse variance weighted (IVW), the weighted median estimate (WME), MR‐Robust Adjusted Profile Score (MR.RAPS), MR‐Pleiotropy Residual Sum and Outlier (MR‐PRESSO), and MR‐Egger regression method, the causal link between exposure and outcome was evaluated. 17 , 18 , 19 , 20 , 21 The IVW technique, which means SNP–outcome associations divided by SNP‐exposure associations, is the dominant method for determining causality with multiplicative random effects. 17 WME assumptions are based on 50% weights from valid SNPs. 18 The no measurement error hypothesis is answered by the MR‐Egger regression approach, which can still find stronger causation in the presence of erroneous instrumental variables. 19 When the intercept of MR‐Egger regression is zero, it shows that there is no genetic pleiotropy, which is another way to measure pleiotropy. 19 A cutting‐edge technique for determining causation is MR‐PRESSO. 21 , 22 The MR‐PRESSO global test can also determine whether directional pleiotropy exists in addition to causality. 22 The MR‐PRESSO outliers test may identify whether outliers are present or absent. 21 The robust causality evaluation approach MR.RAPS prevents weak instrumental variables, systematic polymorphisms, and particular polymorphisms from interfering with causality. 20 Finally, the outcomes of heterogeneity tests and pleiotropy validity analyses were used to assess the robustness and reliability of the causal linkages. As indicated earlier, MR‐Egger regression and the MR‐PRESSO global test were largely used to evaluate pleiotropy. 19 , 21 Heterogeneity was primarily found by the IVW method and MR‐Egger regression. The presence of heterogeneity or pleiotropy was taken into consideration when p < .05.

2.4. Meta‐analysis of FinnGen and IIBDGC data

To obtain reliable causal relationships, we performed a meta‐analysis of the different results obtained by MR analysis in initial stage and replication stage. The random effects model that was utilized in this meta‐analysis had a statistical significance cutoff of p < .05. The statistical test for heterogeneity (including subgroup analysis) was set at .05. Therefore, p < .05 indicates potential heterogeneity.

2.5. Statistical analysis

All statistical analyses for this study were carried out using the R and R studio packages “TwoSampleMR,” “Mendelian randomization,” and “MR‐PRESSO.” The statistical significance of causality for the causality evaluation in this study was established using a multiple test (Bonferroni correction) adjustment of a p value less than 0.0167(0.05/3). The level of statistical significance for further studies, such as the pleiotropy test and the examination of heterogeneity, was also set at .05.

3. RESULTS

3.1. Inclusion of SNP information

There were 146 SNPs included in the IBD, 84 of which were not present in the ICH (blue markers in Supporting Information: Table 1). Eight SNPs were also eliminated because they were intermediate allele frequencies (rs10917547, rs11574906, rs12141431, rs1505992, rs35730213, rs4712528, rs6927172, rs75159542). As a result, 54 SNPs were examined to IBD and the risk of ICH. The GWAS data for UC included 110 SNPs in total, of which 79 SNPs were not present in the GWAS data for ICH (marked in blue in Supporting Information: Table 2). Additionally, five SNPs—rs10917547, rs35730213, rs484356, rs9823546, and rs9891174—were eliminated from the study of the causative connection between UC and ICH risk because they were palindromic and had intermediate allele frequencies. This left only 26 SNPs. Forty‐six of the 99 SNPs that were screened from the CD data for the examination of the causal association between CD and ICH risk were not appropriate for further investigation, and were therefore excluded (blue markers in Supporting Information: Table 3). Seven SNPs, including rs11564236, rs12141431, rs12194825, rs12692254, rs7205423, rs78487399, and rs9292782, were also eliminated because they were palindromic and had intermediate allele frequencies. As a result, only 46 SNPs were used for further research. All F‐statistics are more than 10, as shown in Supporting Information: Tables 1, 2, 3, indicating that the impact of weak instrumental variables can be disregarded.

Table 2.

Heterogeneity test of IBD with its subtypes and ICH.

Consortium Exposure Outcome Heterogeneity Test (IVW) Heterogeneity Test (MR‐Egger)
Q Q_df p Value Q Q_df p Value
IIBCGC UC ICH 34.47926 24 .0765 34.51577 25 .0973
CD 51.07060 44 .2156 51.17552 45 .2442
IBD 69.40437 52 .0537 69.88780 53 .0599
FinnGen UC ICH 1.90209 4 .7538 1.79700 3 .6156
CD 15.65299 11 .1545 15.08598 10 .1290
IBD 3.21776 6 .7811 3.21708 5 .6666
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Abbreviations: CD, Crohn's disease; IBD, Inflammatory bowel disease; ICH, intracerebral hemorrhage; SNP, single‐nucleotide polymorphism; UC, ulcerative colitis.

Table 3.

Pleiotropy test and outliers test of IBD with its subtypes and ICH.

Consortium Exposure Outcome Pleiotropy test (MR‐Egger) Pleiotropy test (MR‐PRESSO)
Egger intercept SE p Value global test p Value Outliers
IIBDGC UC ICH −0.00716720 0.04495936 .8747 40.38702 .139 NA
CD 0.00674580 0.02243727 .7651 60.29537 .254 NA
IBD 0.01562338 0.02595979 .5499 82.15943 .050 NA
FinnGen UC ICH 0.02962400 0.09138500 .7671 8.78220 .635 NA
CD 0.05110900 0.08336600 .5535 149.11262 .202 NA
IBD −0.00167000 0.06387100 .9802 149.11262 .019 NA
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Abbreviations: CD, Crohn's disease; IBD, Inflammatory bowel disease; ICH, intracerebral hemorrhage; SNP, single‐nucleotide polymorphism; UC, ulcerative colitis.

3.2. Three core assumptions are satisfied

First, from Supporting Information: Table 1, we observe that instrumental variables (SNP) and exposure (IBD, CD, and UC) have a close relationship (p < 5 × 10−8). Second, we conducted individual PhenoScanner websites (http://www.phenoscanner.medschl.cam.ac.uk/) on each instrumental variable and found no confounding variables (smoking, excessive drinking, hypertension, hypercholesterolemia, and sedentary behavior) related to the instrumental variables (p < 1 × 10−5 and r 2 < 0.8). Finally, the MR‐PRESSO global test and MR‐Egger regression test did not reveal the presence of pleiotropy (Tables 2 and 3), indicating that instrumental variables only affect the findings through exposure and that there are no other possible pathways.

3.3. UC associates with the risk of ICH

The causative relationship between IBD and its subtypes and the risk of ICH was examined using MR studies, and it was found that utilizing the IVW approach, UC may reduce that risk of ICH (OR = 0.83, 95% CI: 0.71–0.96, p = .01) (Figure 3). The results of the MR‐PRESSO (OR = 0.85, 95% CI: 0.75–0.97, p = .02) and MR.RAPS (OR = 0.86, 95% CI:0.76–0.98, p = .02) techniques also suggest that UC may decrease the risk of ICH.

Figure 3.

Figure 3

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Five methods to assess the causal relationship between IBD and its UC, CD, and the risk of ICH. IBD, inflammatory bowel disease; ICH, intracerebral hemorrhage; CD, Crohn's disease; MR‐PRESSO, MR‐Pleiotropy Residual Sum and Outlier; MR.RAPS, MR‐Robust Adjusted Profile Score; UC, ulcerative colitis; WME, weighted median estimation.

Nevertheless, the IVW method failed to find evidence of a connection between CD (OR = 0.99, 95% CI: 0.92–1.08, p = .90), IBD (OR = 0.97, 95% CI: 0.86–1.09, p = .62), and the risk of ICH. Additionally, no association between CD and ICH risk was found using the MR‐Egger regression (OR = 0.97, 95% CI: 0.80–1.18, p = .75), WME (OR = 0.93, 95% CI: 0.82–1.05, p = .24), MR‐PRESSO (OR = 0.98, 95% CI: 0.91–1.06, p = .62), or MR.RAPS (OR = 0.97, 95% CI: 0.90–1.05, p = .51). Similarly, the MR‐Egger regression (OR = 0.89, 95% CI: 0.65–1.22, p = .46), WME (OR = 0.91, 95% CI: 0.77–1.07, p = .24), MR‐PRESSO (OR = 0.97, 95% CI: 0.87–1.08, p = .59), and MR.RAPS (OR = 0.91, 95% CI: 0.87–1.09, p = .64) methods failed to show a connection between IBD and the risk of ICH.

3.4. Meta‐analysis of IIBDGC and FinnGen GWAS data confirm that UC related to the risk of ICH

We used FinnGen data as replication data to assess the causal relationship between IBD and its subtypes and the risk of ICH, as shown in Figure 4. We found that IBD (OR = 0.74, 95% CI: 0.59–0.94, p = .0135) may lower the risk of ICH; however, the IVW method did not show a causal link between UC (OR = 0.83, 95% CI: 0.65–1.05, p = .1230), CD (OR = 0.92, 95% CI: 0.80–1.07, p = .2798), and ICH. The results of our meta‐analysis of the FinnGen and IIBDGC data, however, continued to support the notion that UC (OR = 0.83, 95% CI: 0.72–0.93, p < .05) would reduce the risk of ICH, but we were unable to establish a causal relationship between CD (OR = 0.98, 95% CI: 0.91–1.05, p > .05), IBD (OR = 0.91, 95% CI: 0.81–1.00, p > .05), and risk of ICH.

Figure 4.

Figure 4

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Meta‐analysis show the causality of IBD, UC, and CD with the risk of ICH. CD, Crohn's disease; IBD, inflammatory bowel disease; ICH, intracerebral hemorrhage; IIBDGC, International Inflammatory Bowel Disease Genetics Consortium; MR‐PRESSO, MR‐Pleiotropy Residual Sum and Outlier; UC, ulcerative colitis; WME, weighted median estimation.

3.5. Heterogeneity test and pleiotropy test show robust causality between IBD, UC, CD, and ICH risk

We searched for heterogeneity between IBD (p IVW = .0537, p MR‐Egger = .0599), CD (p IVW = .2156, p MR‐Egger = .2442), UC (p IVW = .0765, p MR‐Egger = .0973), and risk of ICH using IVW and MR‐Egger regression, as shown in Table 2, but we were unable to find any. Additionally, we searched for pleiotropy using the MR‐Egger regression and MR‐PRESSO global test, but once more, no overlap between the causative effects of IBD (p MR‐Egger = .550, p MR‐PRESSO = .050), UC (p MR‐Egger = .875, p MR‐PRESSO = .139), CD (p MR‐Egger = .765, p MR‐PRESSO = .254), and ICH was found. There are no outliers revealed using the MR‐PRESSO outlier test.

4. DISCUSSION

This study aims to evaluate the genetic relationship between IBD, UC, and CD and the risk of ICH using a sizable sample of GWAS data. We found that UC may reduce the risk of ICH in the initial phase, but there was no causal relationship between IBD and CD and the risk of ICH. And in the replication phase, we did not discovery a relationship between UC, CD, and ICH, but found that IBD may reduce the risk between ICH. To obtain robust results, we further performed a meta‐analysis to confirm the relationship between UC and ICH, but the relationship between IBD, CD, and ICH was not confirmed. Finally, the validity and robustness of the causative links between IBD, UC, CD, and ICH risk were confirmed by heterogeneity tests and pleiotropy analyses.

There is still uncertainty regarding the likely mechanisms linking UC to the risk of ICH. A review of a previous study in Sweden revealed a significant risk of hemorrhagic stroke during the 1–5‐year follow‐up period following discharge from a UC hospitalization of 1.45 (95% CI: 1.03–1.97). 23 A meta‐analysis of the relationship between IBD and stroke also revealed a favorable relationship between the two (R = 1.29, 95% CI, 1.16–1.43), as well as a favorable relationship between UC, CD, and stroke risk. 10 Similarly, a different meta‐analysis discovered that IBD may raise the risk of stroke. Furthermore, in a subgroup analysis, it was discovered that IBD increased the risk of stroke in both Asians and Caucasians (Asian group: OR/RR = 1.36, 95% CI: 1.05−1.23, p = .094; Caucasian group: OR/RR = 1.13; CI: 1.07−1.74, p < .001). 9 Thus, the pathophysiological mechanisms in UC that influence the risk of ICH are connected to the mechanisms in IBD that raise the risk of stroke. High levels of pro‐inflammatory cytokines, including tumor necrosis factor, interleukin (IL)‐1, and IL‐6, are related with the primary noninfectious systemic inflammation and hypercoagulable condition that characterize parenteral symptoms of IBD. 24 , 25 Due to the body's protracted inflammatory condition, venous thrombotic events and pulmonary embolism are more likely to occur. 26 Significant platelet alterations, a rise in neutrophil extracellular traps, induced endothelial dysfunction, a hypercoagulable condition, and underlying gut flora disruptions are all brought on by UC. 26 Additionally, UC increases the risk of thrombosis by causing endothelial dysfunction, inadequate endothelium anticoagulation, and a decrease in circulating endothelial progenitor cells. 27 , 28 On the other hand, ICH shows pathophysiological changes that are different from ischemic stroke. Extracellular matrix breakdown, thinning of the vessel wall, and easily ruptured vessels are the main alterations of ICH, as opposed to increased thrombotic risk and endothelial dysfunction of IBD and even UC. 29 This could be a pathway through which UC lowers the risk of ICH, but more research is required to confirm the specific mechanism.

However, there are a few limitations within this study. First of all, it should be cautiously expanded to other communities as this study was specifically focused on people of European descent. Second, despite the fact that the data for this study were taken from GWAS data, it was not possible to stratify the sample for analysis. This was because exact information about the characteristics of the population under research, such as health status, age, smoking, and alcohol use, could not be obtained. Second, the bias caused by pleiotropy is a significant flaw in MR investigations. It is challenging to rule out the idea that any SNP in our research may, in addition to having an effect on UC, also have an impact on the risk of cerebral hemorrhage through a separate mechanism. Although we searched for pleiotropy using the MR‐PRESSO global test and MR‐Egger regression, we were unable to detect it. Finally, a larger study is required to identify and examine potential processes linking UC and ICH risk.

5. CONCLUSION

There is a causal relationship between UC and the risk of ICH even while IBD and UC did not. Future research needs to go into great detail on the mechanism through which UC influences ICH.

AUTHOR CONTRIBUTIONS

Yanju Song and Xinfa Mao designed the research and decided on the manuscript's structure. Xuelun Zou and Yanju Song chose the references and participated in the writing. Yanju Song compiled the GWAS data. Yanju Song contributed to the analysis of these Mendelian randomization results. Xinfa Mao, Yi Zeng, and Le Zhang contributed to the manuscript's revision and completion. All authors participated in and approved the final draft of the manuscript.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.

Supporting information

Forest plot for this study in IIBDGC databases.

Click here for additional data file. (49.8KB, tiff)

Supporting information.

Click here for additional data file. (24.3KB, xlsx)

ACKNOWLEDGMENTS

The Natural Science Foundation of Hunan Province China (No. 2020JJ5930), the Science and Technology Plan Project of Hunan Province China (No. 2021ZK4220), the Graduate Education Teaching Reform Project of Central South University (No. 512190131).

Song Y, Zou X, Zeng Y, Zhang L, Mao X. Inflammatory bowel disease and the risk of intracerebral hemorrhage: a Mendelian randomization study and meta‐analysis. Immun Inflamm Dis. 2023;11:e1048. 10.1002/iid3.1048

DATA AVAILABILITY STATEMENT

Requests for any data can be made to the authors.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Forest plot for this study in IIBDGC databases.

Click here for additional data file. (49.8KB, tiff)

Supporting information.

Click here for additional data file. (24.3KB, xlsx)

Data Availability Statement

Requests for any data can be made to the authors.

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