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Research Article 研究文章

Causal relationships between new 412 gut microbiota, 731 inflammatory cells,91 inflammatory proteins and circulating leukocytes and subarachnoid hemorrhage: a Multi-omics, Bidirectional Mendelian randomization study and Meta-analysis
新增 412 个肠道微生物群、731 个炎症细胞、91 种炎症蛋白和循环白细胞与蛛网膜下腔出血之间的因果关系：一项多组学、双向孟德尔随机化研究和 Meta 分析

https://doi.org/10.21203/rs.3.rs-3562537/v1

This work is licensed under a CC BY 4.0 License
本作品采用 CC BY 4.0 许可协议进行许可

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Background 背景介绍

A neurological emergency with potentially fatal outcomes is subarachnoid hemorrhage (SAH). Arachnoid and soft meninges are separated by a tiny gap called the subarachnoid space. The term "SAH" describes a clinical state brought on by bleeding into the subarachnoid space as a result of diseased or damaged blood vessels rupturing at the base or surface of the brain.
蛛网膜下腔出血（SAH）是一种可能导致致命后果的神经系统急症。蛛网膜和软脑膜之间有一个微小的间隙，称为蛛网膜下腔。蛛网膜下腔出血 "一词描述的是由于病变或受损的血管在大脑底部或表面破裂而导致蛛网膜下腔出血所引发的临床状态。

Methods 方法

To obtain preliminary results, this study integrated the use of several omics with Mendelian randomization analysis and MR-IVW, MR Egger, MR weight median, and MR weight mode. Reverse Mendelian randomization analysis using subarachnoid hemorrhage as exposure. Lastly, to get a summary of the findings, conduct a meta-analysis on the preliminary data.
为了获得初步结果，本研究将几种全息图像与孟德尔随机分析以及 MR-IVW、MR Egger、MR 体重中位数和 MR 体重模式相结合。使用蛛网膜下腔出血作为暴露的反向孟德尔随机分析。最后，为了总结研究结果，对初步数据进行荟萃分析。

Results 成果

GBPA-Pyridoxal 5 photosphate biosynthatis I (OR = 1.48,95% CI, 1.04–2.12) and GBPA-glucose biosynthesis I(OR = 0.68,95% CI, 0.52–0.90)is positively correlated with SAH. The urokinase type plasma activator levels showed a positive correlation with SAH (OR = 1.17,95% CI, 1.04–1.32).CD80 on CD62L + Plasmacytoid Dendritic Cell, CD80 on plasmacytoid Dendritic Cell, CD123 on CD62L + plasmacytoid Dendritic Cell and SSC-A on Plasmacytoid Dendritic Cell were found to be associated with SAH.
GBPA-Pyridoxal 5 photosphate biosynthatis I（OR = 1.48，95% CI，1.04-2.12）和GBPA-glucose biosynthesis I（OR = 0.68，95% CI，0.52-0.90）与SAH呈正相关。CD62L + 浆细胞树突状细胞上的 CD80、浆细胞树突状细胞上的 CD80、CD62L + 浆细胞树突状细胞上的 CD123 和浆细胞树突状细胞上的 SSC-A 与 SAH 呈正相关。

Conclusion 结论

Using Mendelian randomization and meta-analysis, four inflammatory cells, one inflammatory protein, and two new gut microbiota-related pathways were shown to be connected to SAH in this investigation. suggesting that each of these could be a potential treatment target for SAH. This implies that controlling gut microbiota and using anti-inflammatory medications are essential for treating SAH.
通过孟德尔随机化和荟萃分析，本研究发现四种炎症细胞、一种炎症蛋白和两种新的肠道微生物相关通路与 SAH 有关，这表明其中每一种都可能是 SAH 的潜在治疗靶点。这意味着控制肠道微生物群和使用抗炎药物对治疗 SAH 至关重要。

Gut microbiota 肠道微生物群

Inflammation 炎症

Immune cell 免疫细胞

Mendelian randomization 孟德尔随机化

Meta analysis 元分析

Subarachnoid hemorrhage 蛛网膜下腔出血

Subarachnoid hemorrhage (SAH) is a neurological emergency that develops unexpectedly and frequently has disastrous consequences [1]. This illness is a clinical symptom brought on by the rupture of diseased or damaged blood vessels at the base or surface of the brain, which allows blood to enter the subarachnoid space directly [2]. The most frequent cause of a ruptured cerebral aneurysm that results in SAH development [3], presenting a serious risk to the health and welfare of a patient [4, 5]. Understanding the complex and crucial link between inflammatory cytokines [6] and subarachnoid hemorrhage (SAH) is essential to comprehending the pathophysiology of this illness. When a SAH occurs, the presence of blood in the subarachnoid space promotes an inflammatory reaction in the brain[7–9]. In reaction to this injury, a variety of cells release inflammatory cytokines, including interleukins [10, 11] and tumor necrosis factor-alpha (TNF-α)[12, 13]. Following SAH, these cytokines are important in the secondary damage cascade, since they contribute to increased permeability of the blood-brain barrier, cerebral vasospasm, and neuronal injury [14–16]. These inflammatory mediators can worsen SAH patients' overall prognosis and cause further problems. The interaction between inflammatory cytokines and SAH is being studied in order to find possible treatment targets that could reduce the negative consequences of this inflammatory response and enhance patient outcomes.
蛛网膜下腔出血（SAH）是一种突发性神经系统急症，经常会造成灾难性后果[1]。这种疾病是由于大脑底部或表面病变或受损的血管破裂，使血液直接进入蛛网膜下腔而引起的临床症状[2]。脑动脉瘤破裂导致 SAH 发生的最常见原因[3]，严重危害患者的健康和福利[4, 5]。了解炎性细胞因子[6]与蛛网膜下腔出血（SAH）之间复杂而关键的联系对于理解这种疾病的病理生理学至关重要。蛛网膜下腔出血发生时，蛛网膜下腔的血液会促进脑部的炎症反应[7-9]。针对这种损伤，多种细胞会释放炎性细胞因子，包括白细胞介素[10, 11]和肿瘤坏死因子-α（TNF-α）[12, 13]。SAH 后，这些细胞因子在继发性损伤级联中起着重要作用，因为它们会导致血脑屏障通透性增加、脑血管痉挛和神经元损伤[14-16]。这些炎症介质会恶化 SAH 患者的整体预后，并引发更多问题。目前正在研究炎性细胞因子与 SAH 之间的相互作用，以便找到可能的治疗靶点，减轻这种炎症反应的负面影响，改善患者的预后。

The gut microbiome and the brain are intricately connected [17]. Changes in the gut microbiota's composition may have a major effect on SAH patients, according to recent studies [18]. Alterations in the gut microbiota have the potential to exacerbate the inflammatory response in SAH by causing systemic inflammation and influencing the immune system as a whole[19–21]. Furthermore, the modulation of blood pressure and immunological function—two critical aspects in SAH—as well as other systemic processes is mediated by the gut flora. Still indefinite is the relationship between subarachnoid hemorrhage and gut microbiota. In this work, we employed a bidirectional Mendelian randomization technique to investigate the effect of gut microbiota on SAH, to offer novel approaches for therapeutic intervention, and to uncover the causal link between gut microbiota and brain health.
肠道微生物群与大脑之间有着错综复杂的联系 [17]。根据最近的研究，肠道微生物群组成的变化可能会对 SAH 患者产生重大影响 [18]。肠道微生物群的改变有可能导致全身炎症并影响整个免疫系统，从而加剧 SAH 的炎症反应[19-21]。此外，肠道菌群还能调节血压和免疫功能（这是 SAH 的两个关键方面）以及其他系统过程。蛛网膜下腔出血与肠道微生物群之间的关系尚不明确。在这项工作中，我们采用了双向孟德尔随机技术来研究肠道微生物群对 SAH 的影响，为治疗干预提供新方法，并揭示肠道微生物群与大脑健康之间的因果联系。

In genetic and epidemiological research, Mendelian randomization (MR) is a potent and novel technique. It is a technique for examining the causal links between risk factors or exposure and certain outcomes or illnesses. This approach mainly uses exposure-related genetic variations as instrumental factors, mimicking the randomization process in natural settings or randomized controlled trials. In essence, Mendelian randomization evaluates the possible causative effects of exposure on certain outcomes by means of genetic variation. This approach offers more compelling evidence of causality than conventional observational studies since the latter are more prone to bias from confounding variables. In this work, we first used exposure analysis to examine the effects of immune cells, inflammatory cells, inflammatory proteins, and gut microbiota on subarachnoid hemorrhage. Then, we performed a meta-analysis based on the findings of Mendelian randomization analysis on subarachnoid hemorrhage. The results' credibility can be increased by combining Mendelian randomization with meta-analysis.[22]. Ultimately, the meta-analysis's findings were used to calculate how exposure affected the outcome. This work examined the impact of subarachnoid hemorrhage using multi-omics Mendelian analysis.
在遗传学和流行病学研究中，孟德尔随机化（Mendelian randomization，MR）是一种有效而新颖的技术。它是一种研究风险因素或暴露与某些结果或疾病之间因果关系的技术。这种方法主要利用与暴露相关的遗传变异作为工具因素，模仿自然环境或随机对照试验中的随机过程。从本质上讲，孟德尔随机法是通过基因变异来评估暴露对某些结果可能产生的因果效应。与传统的观察研究相比，这种方法能提供更有说服力的因果关系证据，因为后者更容易受到混杂变量的影响而产生偏差。在这项工作中，我们首先利用暴露分析来研究免疫细胞、炎症细胞、炎症蛋白和肠道微生物群对蛛网膜下腔出血的影响。然后，我们根据蛛网膜下腔出血的孟德尔随机分析结果进行了荟萃分析。将孟德尔随机分析与荟萃分析相结合，可以提高结果的可信度[22]。最终，荟萃分析的结果被用来计算暴露对结果的影响。这项工作利用多组学孟德尔分析法研究了蛛网膜下腔出血的影响。

Three key tenets underpin Mendelian randomization (MR): (1) the genetic instrument must show a strong correlation with the exposure (risk factor) being studied; (2) there must be no confounding variables that affect the risk factor and the outcome at the same time without being related to the genetic instrument linked to either of the two factors; and (3) the only path from the genetic instrument to the outcome must involve the risk factor of interest.
孟德尔随机法（Mendelian randomization，MR）有三个关键原则：（1）遗传工具必须与所研究的暴露（风险因素）有很强的相关性；（2）必须没有混杂变量同时影响风险因素和结果，而与这两个因素中任何一个相关的遗传工具无关；（3）从遗传工具到结果的唯一路径必须涉及相关的风险因素。

Instrumental variables selection
工具变量选择

Firstly, we employed a genome-wide significance threshold of P < 5×10 − 8 to identify SNPs with strong associations in three key contexts(gut microbiota: P < 1×10 − 5): SNPs closely linked to SAH and immune cells,SNPs closely linked to SAH and inflammatory cytokines, SNPs closely linked to SAH and inflammatory proteins, and SNPs closely linked to SAH and the gut microbiota. As only a limited number of SNPs were discovered for some cytokines when used as the exposure variable, we opted for a more stringent cutoff (p < 5 × 10 − 5). Secondly, to mitigate the impact of linkage disequilibrium, we performed SNP clumping using specific parameters (kb = 10,000, r^2 = 0.001). In the presence of a palindromic SNP, it was promptly excluded. Thirdly, the proportion of variance in the exposure was determined through the R2 value of each SNP, and the instrument's strength was assessed using the F-statistic, thus mitigating potential issues associated with weak instrument bias. Finally, any SNPs that were unavailable in the outcome summary were replaced with suitable proxy SNPs (R2 > 0.9) obtained from LDlink.
首先，我们采用了P < 5×10 - 8的全基因组显著性阈值，以确定在三个关键环境（肠道微生物群：P < 1×10 - 5）中具有强关联性的SNPs：与 SAH 和免疫细胞密切相关的 SNPs、与 SAH 和炎症细胞因子密切相关的 SNPs、与 SAH 和炎症蛋白密切相关的 SNPs 以及与 SAH 和肠道微生物群密切相关的 SNPs。由于将某些细胞因子作为暴露变量时只发现了数量有限的 SNPs，因此我们选择了更严格的截止值（p < 5 × 10 - 5）。其次，为了减轻连锁不平衡的影响，我们使用特定参数（kb = 10,000，r^2 = 0.001）对 SNP 进行了聚类。如果存在回文 SNP，则会立即将其排除。第三，通过每个 SNP 的 R2 值确定暴露变异的比例，并使用 F 统计量评估工具的强度，从而减轻与弱工具偏差相关的潜在问题。最后，用从 LDlink 获得的合适的替代 SNP（R2 > 0.9）替换了结果汇总中无法获得的 SNP。

Data source 数据来源

This study used 4 types of exposure data and 2 types of outcome data. The new 412 types of intestinal flora data came from the research of Esteban A et al[23], and the 91 types of inflammatory proteins came from the research data of Zhao et al[24]. The 731 inflammatory cells are from the research of Valeria Orrù et al[25], and the blood white cell data are from the research data of MingHuei Chen et al[26]. The outcome data for both SAH are from the study of Sakaue S et al. All data are publicly available and have been reviewed by the ethics committee, so this study does not need to undergo ethical review.
本研究使用了 4 种暴露数据和 2 种结果数据。新增的 412 种肠道菌群数据来自 Esteban A 等人的研究[23]，91 种炎症蛋白来自 Zhao 等人的研究[24]。731 个炎症细胞数据来自 Valeria Orrù 等人的研究[25]，血液白细胞数据来自 MingHuei Chen 等人的研究[26]。两例 SAH 的结果数据均来自 Sakaue S 等人的研究。所有数据均可公开获得，并已通过伦理委员会审查，因此本研究无需进行伦理审查。

Statistical analysis 统计分析

The inverse variance weighting (IVW) method, which is well-known for its effectiveness and statistical power, was principally used in this work to evaluate causal relationships. However, this method is predicated on the notion that every genetic variation is a legitimate instrumental variable, which may not always hold true in practical situations. Therefore, to ensure consistent estimates of causal parameters, we also exploited alternative robust methods that do not require the validity of all genetic variants as instrumental variables. For example, the inverse variance weighted exhibits greater tolerance for invalid instrumental variables and can produce reliable estimates even if more than half of the weight is attributed to valid instrumental variables. The MR-Egger method provides consistent estimates of causal effects under the assumption that instrument strength is independent of direct effects (InSIDE). To assess potential directional pleiotropy, we examined the significance of the MR-Egger regression intercept (p < 0.05 indicates significance). Nonetheless, regression dilution is still a problem when the heterogeneity I2 statistic, which measures the violation of the No Measurement Error (NOME) of instrumental variables in the MR-Egger method, is low (I2 < 90%). To account for attenuation biases arising from violations of the NOME assumption, the SIMEX method proved valuable. Additionally, as part of the sensitivity analysis, simple mode and weighted mode analyzes were performed. The correlation of the instrumental variables associated with the exposure was assessed using the approximate F statistic derived from the summary-level data. When F > 10, the correlation is considered strong enough to mitigate the risk of weak instrumental variable bias. To measure heterogeneity among SNP-based estimates, we employed Cochrane's Q statistic in the IVW method. To further evaluate the robustness of SNPs, we further applied MR-weight and MR-mode to evaluate (when the number of SNPs > 2). We selected the primary evaluation method from among the above methods, consistent with the recommended strategy that considers the key assumptions of NOME and InSIDE. Once the recommended approach is identified, a concurrent sensitivity analysis of causal relationships is performed using alternative analysis techniques.
反方差加权法（IVW）以其有效性和统计能力而著称，在这项工作中主要用于评估因果关系。然而，这种方法的前提是每一个遗传变异都是一个合法的工具变量，而在实际情况中这一前提并不总是成立的。因此，为了确保因果参数估计的一致性，我们还利用了其他稳健方法，这些方法不要求所有遗传变异都是有效的工具变量。例如，反方差加权法对无效工具变量的容忍度更高，即使有效工具变量的权重超过一半，也能得出可靠的估计值。在工具强度独立于直接效应的假设条件下，MR-Egger 方法可提供一致的因果效应估计值（InSIDE）。为了评估潜在的定向多效性，我们检查了 MR-Egger 回归截距的显著性（p < 0.05 表示显著）。然而，当衡量 MR-Egger 方法中工具变量无测量误差（NOME）违反情况的异质性 I 2 统计量较低时，回归稀释仍是一个问题（I 2 < 90%). To account for attenuation biases arising from violations of the NOME assumption, the SIMEX method proved valuable. Additionally, as part of the sensitivity analysis, simple mode and weighted mode analyzes were performed. The correlation of the instrumental variables associated with the exposure was assessed using the approximate F statistic derived from the summary-level data. When F > 10），相关性被认为足够强，足以减轻弱工具变量偏差的风险。为了衡量基于 SNP 的估计值之间的异质性，我们在 IVW 方法中使用了 Cochrane's Q 统计量。为进一步评估 SNP 的稳健性，我们还采用了 MR-weight 和 MR 模式进行评估（当 SNP 数量大于 2 时）。我们从上述方法中选择了符合推荐策略的主要评估方法，该策略考虑了 NOME 和 InSIDE 的关键假设。一旦确定了推荐方法，我们将同时使用替代分析技术对因果关系进行敏感性分析。

Bonferroni correction was applied taking into account the number of systemic inflammation modulators examined (P < 0.0012) as well as the gut microbiota. We determined suggestive association results as significant (P < 0.05) before applying multiple comparison correction (P < 0.0012). To assess the robustness of the effect size and pinpoint specific SNPs that have a disproportionate impact on the relationship, a leave-one-out sensitivity analysis was performed. This involves systematically removing each SNP, one at a time, and employing an IVW approach to assess the impact of the remaining SNPs. SNPs serving as instrumental variables with missing data in the exposure or outcome summary were excluded. Finally, we performed a meta-analysis on the data obtained from each Mendelian randomization analysis and summarized some positive data. Analyzes were performed using the TwoSample MR package (version 4.3.2). Please note that this study is not pre-registered on any platform.
考虑到所研究的全身炎症调节因子的数量（P < 0.0012）以及肠道微生物群，采用了 Bonferroni 校正。在应用多重比较校正（P < 0.0012）之前，我们将提示性关联结果确定为显著（P < 0.05）。为了评估效应大小的稳健性，并找出对这一关系产生不成比例影响的特定 SNP，我们进行了剔除敏感性分析。这包括系统性地逐个剔除每个 SNP，并采用 IVW 方法评估剩余 SNP 的影响。作为工具变量的 SNP，如果在暴露或结果汇总中数据缺失，也会被剔除。最后，我们对从每项孟德尔随机分析中获得的数据进行了荟萃分析，并总结了一些积极的数据。分析使用双样本 MR 软件包（4.3.2 版）进行。请注意，本研究未在任何平台上预先注册。

The causal relationship between gut microbiota and SAH
肠道微生物群与 SAH 的因果关系

The results of Mendelian randomization analysis were intersected to obtain the results of Mendelian randomization analysis with the same exposure, and these results were subjected to meta-analysis. Among the new 412 gut microbiota, there are a total of 2 statistically significant results of gut microbiota, including Gut bacterial pathway abundance (GBPA) – Pyridoxal 5 photosphate biosynthesis I and Gut bacterial pathway abundance-glucose amine biosynthesis I(Fig. 2). Pyridoxal 5 photosphate biosynthatis I is positively correlated with SAH (OR = 1.48,95% CI, 1.04–2.12), indicating that an increase in Pyridoxal 5 photosphate biosynthatis I will lead to the deterioration of SAH. Contrary to Pyridoxal 5 photosphate biosynthesis I, the results of IVW indicate a negative correlation between glucose biosynthesis I and SAH (OR = 0.68,95% CI, 0.52–0.90). The results of Pyridoxal 5 photosphate biosynthesis I (OR = 1.59,95% CI, 0.81–3.14) and glucose biosynthesis I (OR = 0.74,95% CI, 0.20–2.70) MR-Egger showed no significant level of pleiotropy. The results of the MR Weight median (OR = 1.44,95% CI, 1.11–1.86) and MR Weight mode (OR = 1.50,95% CI, 1.05–2.16) of Pyridoxal 5 photosphate biosynthesis I indicate a significant positive correlation between this gut microbiota and SAH. The results of MR Weight median (OR = 0.74,95% CI, 0.20–2.70) and MR Weight mode (OR = 0.56,95% CI, 0.29–1.06) for glucose biosynthesis I were negative. When using reverse MR to verify the reverse causal relationship, the results showed that SAH did not have enough SNPs for the next analysis (P < 5 * 10 − 8, r2 < 0.001, kb = 10000).
对孟德尔随机分析的结果进行交叉分析，得到相同暴露的孟德尔随机分析结果，并对这些结果进行荟萃分析。在新增的 412 个肠道微生物群中，共有 2 个具有统计学意义的肠道微生物群结果，包括肠道细菌通路丰度（GBPA）-5-光磷酸吡哆醛生物合成 I 和肠道细菌通路丰度-葡萄糖胺生物合成 I（图 2）。5 号光磷酸吡哆醛生物合成 I 与 SAH 呈正相关（OR = 1.48，95% CI，1.04-2.12），表明 5 号光磷酸吡哆醛生物合成 I 的增加会导致 SAH 的恶化。与 5 号光磷酸吡哆醛生物合成 I 相反，IVW 的结果表明葡萄糖生物合成 I 与 SAH 呈负相关（OR = 0.68，95% CI，0.52-0.90）。5 号光磷酸吡哆醛生物合成 I（OR = 1.59，95% CI，0.81-3.14）和葡萄糖生物合成 I（OR = 0.74，95% CI，0.20-2.70）的 MR-Egger 结果显示没有显著的多义性。5 号光磷酸吡哆醛生物合成 I 的 MR 重量中位数（OR = 1.44，95% CI，1.11-1.86）和 MR 重量模式（OR = 1.50，95% CI，1.05-2.16）结果表明，该肠道微生物群与 SAH 呈显著正相关。葡萄糖生物合成 I 的 MR 重量中位数（OR = 0.74，95% CI，0.20-2.70）和 MR 重量模式（OR = 0.56，95% CI，0.29-1.06）结果均为阴性。在使用反向 MR 验证反向因果关系时，结果显示 SAH 没有足够的 SNPs 进行下一步分析（P < 5 * 10 - 8，r2 < 0.001，kb = 10000）。

The causal relationship between inflammatory proteins and SAH
炎症蛋白与 SAH 的因果关系

By the IVW method for Mendelian randomization analysis of 91 inflammatory proteins, only one type of inflammatory protein (Urokinase type plasminogen activator levels, Fig. 3) had statistical significance. Meta analysis of the IVW results of urokinase type plasma activator levels showed a positive correlation with SAH (OR = 1.17,95% CI, 1.04–1.32), while the results of MR Egger showed no significant level pleiotropy (OR = 1.05,95% CI, 0.83–1.33). The results of MR Weight media were negative (OR = 1.10,95% CI, 0.92–1.32), and the results of MR Weight mode were negative (OR = 1.09,95% CI, 0.91–1.30). When using reverse MR to verify the reverse causal relationship, the results showed that SAH did not have enough SNPs for the next analysis (P < 5 * 10 − 8, r2 < 0.001, kb = 10000).
通过IVW方法对91种炎症蛋白进行孟德尔随机分析，只有一种炎症蛋白（尿激酶型血浆酶原激活剂水平，图3）具有统计学意义。对尿激酶型血浆活酶水平的 IVW 结果进行的 Meta 分析表明，它与 SAH 呈正相关（OR = 1.17，95% CI，1.04-1.32），而 MR Egger 的结果显示没有显著的水平褶皱（OR = 1.05，95% CI，0.83-1.33）。MR Weight 媒介的结果是负的（OR = 1.10，95% CI，0.92-1.32），MR Weight 模式的结果是负的（OR = 1.09，95% CI，0.91-1.30）。在使用反向 MR 验证反向因果关系时，结果显示 SAH 没有足够的 SNPs 进行下一步分析（P < 5 * 10 - 8，r2 < 0.001，kb = 10000）。

The causal relationship between 731 inflammatory cells, circulating white blood cells and SAH
731 炎症细胞、循环白细胞与 SAH 之间的因果关系

After MR analysis and meta-analysis, a total of 4 types of inflammatory related cells were found to be associated with SAH, including CD80 on CD62L + Plasmacytoid Dendritic Cell, CD80 on plasmacytoid Dendritic Cell, CD123 on CD62L + plasmacytoid Dendritic Cell and SSC-A on Plasmacytoid Dendritic Cell (Fig. 4, Fig. 5). Only two SNPs were included in the analysis for CD80 on CD62L + Plasmacytoid Dendritic Cell, CD80 on Plasmacytoid Dendritic Cell, and CD123 on CD62L + Plasmacytoid Dendritic Cell, and further analysis is not possible. The results of IVW showed a positive correlation between CD80 on CD62L + plasmacytoid Dendritic Cell (OR = 1.29, 95% CI, 1.12–1.48), CD80 on plasmacytoid Dendritic Cell (OR = 1.29, 95% CI, 1.12–1.48), CD123 on CD62L + plasmacytoid Dendritic Cell (OR = 1.27, 95% CI, 1.12–1.45) and SAH. The IVW results of SSC-A on Plasmacytoid Dendritic Cell showed a positive correlation with SAH (OR = 1.19,95% CI, 1.07–1.32). The results of MR Egger showed that there was no horizontal pleiotropy (OR = 1.05,95% CI, 0.69–1.60), and the results of MR Weight median (OR = 0.96,95% CI, 0.63–1.44) and MR Weight mode (OR = 0.94,95% CI, 0.64–1.3) were not statistically significant. In MR analysis of circulating white blood cells, no cell was statistically significant. In reverse Mendelian randomization analysis of inflammatory cells, the results showed that SAH did not have enough SNPs for the next analysis (P < 5 * 10 − 8, r2 < 0.001, kb = 10000)
经过MR分析和荟萃分析，发现共有4种炎症相关细胞与SAH相关，包括CD62L +浆细胞树突状细胞上的CD80、浆细胞树突状细胞上的CD80、CD62L +浆细胞树突状细胞上的CD123和浆细胞树突状细胞上的SSC-A（图4、图5）。CD62L + 浆细胞树突状细胞上的 CD80、浆细胞树突状细胞上的 CD80 和 CD62L + 浆细胞树突状细胞上的 CD123 仅有两个 SNPs 被纳入分析，无法进行进一步分析。IVW 结果显示，CD62L + 浆细胞树突状细胞上的 CD80（OR = 1.29，95% CI，1.12-1.48）、浆细胞树突状细胞上的 CD80（OR = 1.29，95% CI，1.12-1.48）、CD62L + 浆细胞树突状细胞上的 CD123（OR = 1.27，95% CI，1.12-1.45）与 SAH 呈正相关。浆细胞树突状细胞上的 SSC-A 的 IVW 结果显示与 SAH 呈正相关（OR = 1.19，95% CI，1.07-1.32）。MR Egger的结果显示，不存在水平多重性（OR = 1.05，95% CI，0.69-1.60），MR Weight median（OR = 0.96，95% CI，0.63-1.44）和MR Weight mode（OR = 0.94，95% CI，0.64-1.3）的结果无统计学意义。在循环白细胞的 MR 分析中，没有一个细胞具有统计学意义。在炎症细胞的反向孟德尔随机分析中，结果显示 SAH 没有足够的 SNPs 进行下一步分析（P < 5 * 10 - 8，r2 < 0.001，kb = 10000）。

About 5–10% of strokes are subarachnoid hemorrhages, a form of stroke in which a blood vessel at the base or surface of the brain bursts [27], causing blood to flow into the subarachnoid space with concomitant clinical symptoms [28]. The most common cause of SAH (85%) is an intracranial aneurysm; other causes include cerebral arteriovenous anomalies, anomalous vascular retinopathy of the base of the brain, dural arteriovenous fistulae, entrapment aneurysms, vasculitis, thrombosis in the intracranial venous system, intratumoral tumors, blood disorders, coagulopathies, and complications from anticoagulants, among others[29–31]. For some of the patients, the cause is uncertain. Subarachnoid hemorrhage (SAH) caused by ruptured aneurysm is mainly located at the bifurcation of the cerebral basal arteries, particularly near the Willis circle[32, 33]. Even if the patient survives, they may still have lasting neurological impairments, which can have a significant negative impact on their quality of life. To this day, the mechanisms leading to aneurysm rupture remain highly complex. The main contributing factors include aneurysm size larger than 7 millimeters, presence of inflammation, genetic syndromes, and hypertension[3, 34]. Studies have shown that there are five types of gut microbes that are closely related to SAH[35]. However, in this study, only two gut microbiome-related pathways were summarized through meta-analysis and were associated with subarachnoid hemorrhage (Fig. 2). Among them, the gut bacterial pathway abundance pyridoxal-5-phosphate biosynthesis I may be considered a risk factor for SAH (OR > 1). When the level of pyridoxal-5-phosphate biosynthesis I increases, it will promote the development of SAH. The MR Egger analysis showed that there was no significant level of pleiotropy in pyridoxal 5-phosphate biosynthatis I (Fig. 2). That indicates the credibility of the results. The gut bacterial pathway ambiguity glucose biosynthesis I may serve as a protective factor for SAH. The results of the meta-analysis indicate that OR = 0.68, indicating that the higher the glucose biosynthesis I, the lower the risk of SAH. The results of MR Egger also indicate that there is currently no significant level of pleiotropy.
大约 5-10%的中风是蛛网膜下腔出血，这是一种脑卒中，是指脑底部或表面的血管破裂[27]，导致血液流入蛛网膜下腔，并伴随临床症状[28]。SAH 最常见的病因（85%）是颅内动脉瘤，其他病因包括脑动静脉畸形、脑底部异常血管视网膜病变、硬脑膜动静脉瘘、夹层动脉瘤、脉管炎、颅内静脉系统血栓形成、瘤内肿瘤、血液病、凝血病和抗凝剂并发症等[29-31]。部分患者的病因尚不明确。动脉瘤破裂导致的蛛网膜下腔出血（SAH）主要位于大脑基底动脉分叉处，尤其是威利斯圈附近[32, 33]。即使患者存活下来，他们仍可能存在持久的神经功能损伤，这对他们的生活质量会产生严重的负面影响。时至今日，导致动脉瘤破裂的机制仍然非常复杂。主要诱因包括动脉瘤大小超过 7 毫米、存在炎症、遗传综合征和高血压[3, 34]。研究表明，有五种肠道微生物与 SAH 密切相关[35]。然而，在本研究中，通过荟萃分析总结出的与蛛网膜下腔出血相关的肠道微生物通路只有两条（图 2）。其中，肠道细菌途径丰度吡哆醛-5-磷酸生物合成 I 可被视为 SAH 的风险因素（OR > 1）。当吡哆醛-5-磷酸生物合成 I 水平升高时，将促进 SAH 的发生。MR Egger 分析表明，5-磷酸吡哆醛生物合成 I 不存在显著的多态性（图 2）。这表明结果是可信的。肠道细菌途径模糊葡萄糖生物合成 I 可能是 SAH 的保护因素。荟萃分析结果表明，OR = 0.68，表明葡萄糖生物合成 I 越高，SAH 风险越低。MR Egger 的结果还表明，目前不存在显著的多效应水平。

Inflammation is primarily associated with various neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease[36]. In the pathogenesis of SAH, inflammation plays a crucial role, with studies showing that there is neuronal damage caused by both cellular and molecular inflammation in the subarachnoid space[37]. Congenital immune responses may promote a series of inward-outward inflammatory reactions in the subarachnoid space. Experts have proposed that postoperative inflammation in patients with hemorrhagic aneurysms can increase the probability of adverse clinical events, especially due to elevated levels of inflammatory factors such as IL-6 and TNF-α[37, 38]. Furthermore, in brain injury and the inflammatory mechanisms associated with brain injury, high levels of IL-6 and TNF-α in the cortex are associated with post-SAH red blood cell lysis[39].
炎症主要与阿尔茨海默病和帕金森病等各种神经退行性疾病有关[36]。在 SAH 的发病机制中，炎症起着至关重要的作用，研究表明，蛛网膜下腔的细胞和分子炎症都会造成神经元损伤[37]。先天性免疫反应可能会促进蛛网膜下腔一系列由内而外的炎症反应。有专家提出，出血性动脉瘤患者术后炎症会增加不良临床事件的发生概率，尤其是由于 IL-6 和 TNF-α 等炎症因子水平的升高[37, 38]。此外，在脑损伤和与脑损伤相关的炎症机制中，大脑皮层中高水平的 IL-6 和 TNF-α 与脑出血后红细胞溶解有关[39]。

The rupture of aneurysms causes SAH, which promotes the increase in neutrophils and inflammatory cytokines IL-6 in the brain. At the same time, an increase in IL-6 is also associated with local and periphery inflammation[40, 41]. Infiltration of inflammatory immune cells provides a potential target for treatment of SAH patients[40]. It is widely believed that IL-6 is a contributor to brain damage, potentially leading to adverse clinical outcomes with poor prognosis[42]. In the context of neuroinflammation, IL-6 is significantly associated with EBI following aneurysmal SAH. In addition, soluble gp130 (sgp130) is an IL-6 antagonist that can inhibit the production of IL-6. Conversely, IL-6 is an agonist receptor for the IL-6R. When SAH occurs, gp130 can limit the elevation of IL-6. However, when gp130 levels decline, it may contribute to cerebrovascular spasm and corresponding neuroinflammation damage[43]. Some studies have shown that recently marketed IL-6 signaling inhibitors are full-length gp130. Other studies have confirmed that proteins related to the innate immune system will be activated by the IL-6 signal and tissue-specific sgp130[44]. Some immune cells and corresponding chemokines associated with sgp130 can inhibit neuroinflammation[45, 46]. There is evidence to suggest that the main sgp130 isoform specifically binds to the IL-6/IL-6R complex, thereby inhibiting its proinflammatory function[47]. In addition, there is a related mechanism where the thioredoxin-interacting protein (TXNIP) interacts with the NLRP3 inflammasome containing the pyrin domain of the NOD-like receptor family, promoting the generation of interleukin IL-1β. The NLRP3 inflammasome belongs to the innate immune system. The NLRP3 inflammasome is essentially a complex involved in the mechanism of innate immune response, but under conditions of runaway activation, the NLRP3 inflammasome will abnormally activate the immune system and inflammation, typical examples being abnormal metabolism of mitochondria and accumulation of ROS[48]. Some studies have shown that the NLRP3 inflammasome may promote the generation of IL-1β and IL-18, which will exacerbate the post-SAH inflammation response and promote the progression of EBI[49, 50]. By inhibiting the NLRP3-related inflammatory response, it is possible to inhibit neuronal inflammation and promote recovery of neurological function[51]. Intracellular activation of NLRP3 leads to accumulation of ROS, which activates inflammasome[52]. Some strong antioxidants, such as melatonin, can inhibit EBI and inflammation after SAH[53], thereby improving the prognosis of SAH[51]. Melatonin also suppresses the levels of inflammatory cytokines such as IL-1β, IL-6 and TNF-α. These inflammatory signaling molecules promote progression of brain diseases after SAH[54]. There are multiple immune and inflammatory processes that occur in different segments after SAH, which may be related to the production of inflammatory cytokines and immunoregulatory molecules. In our study, we discovered a new inflammase-related molecule, the Urokinase type plasminogen activator. MR and meta-analysis confirmed that the Urokinase type plasminogen activator will affect SAH, and increasing the Urokinase type plasminogen activator will promote the progression of SAH, indicating that this will be a new therapeutic target.
动脉瘤破裂导致 SAH，会促进脑内中性粒细胞和炎症细胞因子 IL-6 的增加。同时，IL-6 的增加还与局部和外周炎症有关[40, 41]。炎性免疫细胞的浸润为 SAH 患者的治疗提供了潜在靶点[40]。人们普遍认为，IL-6 是造成脑损伤的一个因素，有可能导致预后不良的不良临床结果[42]。在神经炎症的背景下，IL-6 与动脉瘤性 SAH 后的 EBI 显著相关。此外，可溶性 gp130（sgp130）是一种 IL-6 拮抗剂，可抑制 IL-6 的产生。相反，IL-6 是 IL-6R 的激动受体。当发生 SAH 时，gp130 可限制 IL-6 的升高。然而，当 gp130 水平下降时，可能会导致脑血管痉挛和相应的神经炎症损伤[43]。一些研究表明，最近上市的 IL-6 信号抑制剂是全长的 gp130。其他研究证实，与先天性免疫系统相关的蛋白质会被 IL-6 信号和组织特异性 sgp130 激活[44]。与 sgp130 相关的一些免疫细胞和相应的趋化因子可抑制神经炎症[45, 46]。有证据表明，主要的 sgp130 异构体能特异性地与 IL-6/IL-6R 复合物结合，从而抑制其促炎功能[47]。此外，还有一种相关机制，即硫氧还蛋白相互作用蛋白（TXNIP）与含有 NOD 样受体家族吡林结构域的 NLRP3 炎症小体相互作用，促进白细胞介素 IL-1β 的生成。NLRP3 炎症体属于先天性免疫系统。NLRP3 炎性体本质上是参与先天免疫反应机制的复合物，但在失控激活的情况下，NLRP3 炎性体会异常激活免疫系统和炎症，典型的例子是线粒体代谢异常和 ROS 的积累[48]。一些研究表明，NLRP3 炎症小体可促进 IL-1β 和 IL-18 的生成，从而加剧 SAH 后的炎症反应并促进 EBI 的进展[49, 50]。通过抑制 NLRP3 相关炎症反应，可以抑制神经元炎症，促进神经功能的恢复[51]。细胞内 NLRP3 的激活会导致 ROS 的积累，从而激活炎性体[52]。一些强抗氧化剂，如褪黑素，可以抑制 SAH 后的 EBI 和炎症[53]，从而改善 SAH 的预后[51]。褪黑素还能抑制 IL-1β、IL-6 和 TNF-α 等炎症细胞因子的水平。 这些炎症信号分子会促进 SAH 后脑部疾病的进展[54]。SAH 后不同节段出现多种免疫和炎症过程，这可能与炎症细胞因子和免疫调节分子的产生有关。在我们的研究中，我们发现了一种新的炎症相关分子--尿激酶型纤溶酶原激活剂。磁共振和荟萃分析证实，尿激酶型纤溶酶原激活剂会影响 SAH，而增加尿激酶型纤溶酶原激活剂会促进 SAH 的进展，这表明这将是一个新的治疗靶点。

More and more studies have confirmed the role of inflammation in subarachnoid hemorrhage (SAH). However, due to its complex activation mechanism and vast immune system, the exact pathway of inflammation in SAH still needs further verification. Research suggests that the high incidence of bacterial pneumonia in asymptomatic aneurysmal SAH patients may be attributed to impaired immune response and decreased T cell count. Clinical studies have shown that some cases of secondary SAH may be mediated by immune-related diseases, especially immune hyperactivity disorders such as autoimmune hemolytic anemia, Crohn's disease, and hyperthyroidism[55]. Some clinical studies have also shown that SAH patients after surgical treatment may experience short-term immune dysfunction. Inhibition of certain immune cells, such as CD4+, CD8 + T cells, natural killer cells (NKs), and regulatory T cells (Tregs), will lead to worse prognosis in patients[56]. One clinical study has shown that injection of low-dose interleukin-2 (IL-2) in SAH patients can significantly inhibit the differentiation of Treg cells, thereby suppressing post-SAH neuroinflammation. Some pathological studies have indicated that reducing pro-inflammatory factors and neutrophils in the blood can promote neurological function recovery[57]. Research has shown that regulatory T cells have two main functions: inhibiting the proliferation of normal T cells and releasing cytokines[58]. Immunosuppressive regulatory T cells can inhibit pro-inflammatory factors (tumor necrosis factor-alpha and interferon-gamma) and promote the generation of anti-inflammatory factors (interleukin-10) to suppress inflammatory responses[59–61]. In this study, meta-analysis of MR results revealed that CD80 on CD62L + plasmacytoid Dendritic Cell, CD80 on plasmacytoid Dendritic Cell, CD123 on CD62L + plasmacytoid Dendritic Cell and SSC-A on plasmacytoid Dendritic Cell was positively correlated with SAH. This suggests that these four types of inflammatory cells may exacerbate the symptoms of SAH (OR > 1, Fig. 4 and Fig. 5). No significant statistical differences were found in the meta-analysis of immune cells.
越来越多的研究证实了炎症在蛛网膜下腔出血（SAH）中的作用。然而，由于其复杂的激活机制和庞大的免疫系统，炎症在 SAH 中的确切途径仍有待进一步验证。研究表明，无症状动脉瘤性 SAH 患者细菌性肺炎的高发病率可能与免疫反应受损和 T 细胞数量减少有关。临床研究表明，一些继发性 SAH 病例可能是由免疫相关疾病介导的，尤其是免疫亢进性疾病，如自身免疫性溶血性贫血、克罗恩病和甲状腺功能亢进等[55]。一些临床研究也表明，手术治疗后的 SAH 患者可能会出现短期免疫功能紊乱。某些免疫细胞，如 CD4+、CD8 + T 细胞、自然杀伤细胞（NKs）和调节性 T 细胞（Tregs）受到抑制，会导致患者预后恶化[56]。一项临床研究表明，SAH 患者注射低剂量白细胞介素-2（IL-2）可明显抑制 Treg 细胞的分化，从而抑制 SAH 后的神经炎症。一些病理研究表明，减少血液中的促炎因子和中性粒细胞可促进神经功能的恢复[57]。研究表明，调节性 T 细胞有两个主要功能：抑制正常 T 细胞的增殖和释放细胞因子[58]。免疫抑制调节性 T 细胞可抑制促炎因子（肿瘤坏死因子-α 和干扰素-γ），促进抗炎因子（白细胞介素-10）的生成，从而抑制炎症反应[59-61]。本研究对 MR 结果的荟萃分析显示，CD62L + 浆细胞树突状细胞上的 CD80、浆细胞树突状细胞上的 CD80、CD62L + 浆细胞树突状细胞上的 CD123 和浆细胞树突状细胞上的 SSC-A 与 SAH 呈正相关。这表明这四种炎症细胞可能会加重 SAH 的症状（OR > 1，图 4 和图 5）。免疫细胞的荟萃分析未发现明显的统计学差异。

In this study, two new gut microbiota related pathways, one inflammatory protein, and four inflammatory cells were identified to be associated with SAH through Mendelian randomization and meta-analysis. Indicating that these may all serve as therapeutic targets for SAH. This suggests that anti-inflammatory and regulating gut microbiota are crucial when treating SAH.
在这项研究中，通过孟德尔随机化和荟萃分析，确定了两种新的肠道微生物群相关途径、一种炎症蛋白和四种炎症细胞与 SAH 相关。这表明这些都可能成为 SAH 的治疗靶点。这表明，抗炎和调节肠道微生物群对治疗 SAH 至关重要。

Subarachnoid hemorrhage 蛛网膜下腔出血

SAH

Mendelian randomization 孟德尔随机化

MR

Inverse variance weighted      
逆方差加权

IVW

Single nucleotide polymorphism  
单核苷酸多态性

SNPs

Gut bacterial pathway abundance 
肠道细菌途径丰度

GBPA

Intracerebral Hemorrhage      
脑内出血

ICH

Tumor Necrosis Factor-alpha   
肿瘤坏死因子-α

TNF-α

Interleukin 6  白细胞介素 6

IL-6

Interleukin-2  白细胞介素-2

IL-2

Natural killer cells            自然杀伤细胞

NKs

Tegulatory T cells              调节性 T 细胞

Tregs 菌群

Ethics approval and consent to participate
伦理批准和参与同意书

Not applicable.  不适用。

Consent for publication 同意出版

Not applicable.  不适用。

Availability of data and materials
数据和材料的可用性

The datasets generated and/or analysed during the current study are available in the in this website (https:// pheweb. org/ UKB- SAIGE/) and IEU OpenGWAS (https://gwas. mrcieu.ac.uk/), and Phenoscanner (http:// www. pheno scanner. medschl. cam. ac. uk/).
本研究期间生成和/或分析的数据集可在本网站 (https:// pheweb. org/ UKB- SAIGE/) 和 IEU OpenGWAS (https://gwas. mrcieu.ac.uk/) 以及 Phenoscanner (http:// www. pheno scanner. medschl. cam. ac. uk/) 上查阅。

Competing interests  竞争利益

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
作者声明，本研究在进行过程中不存在任何可能被视为潜在利益冲突的商业或经济关系。

Funding 资金筹措

We have no funding in this study
本研究没有资金支持

Author contributions  作者供稿

Congzhi designed the study and edited the manuscript. Yun Li reviewed and edited the manuscript. All authors contributed to the article and approved the submitted version.
丛治设计了该研究并编辑了手稿。李云审阅并编辑了稿件。所有作者均对文章有贡献，并批准了提交的版本。

Acknowledgements 致谢

We want to acknowledge the participants and investigators of the UK Biobank study.
我们向英国生物数据库研究的参与者和调查人员表示感谢。

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