Abstract
Background: Recent research advancements have indicated a potential association between gut microbiota and cerebrovascular diseases, although the precise causative pathways and the directionality of this association remain to be fully elucidated.
Objective: This study utilized a bidirectional two-sample Mendelian Randomization (MR) methodology to explore the causal impact of gut microbiota compositions on the risk of cerebrovascular disease.
Methods: Genome-wide Association Study (GWAS) data pertaining to gut microbiota were obtained from the MiBioGen consortium. For Ischemic Stroke (IS), Transient Ischemic Attack (TIA), Vascular Dementia (VD), and Subarachnoid Hemorrhage (SAH), GWAS summary data were sourced from the FinnGen consortium, the IEU Open GWAS project, and the GWAS catalog, respectively.
Results: Our MR analyses identified that specific bacterial strains, notably those involved in the production of Short-chain Fatty Acids (SCFAs), including Barnesiella, Ruminococcus torques group, and Coprobacter, serve as protective factors against IS, TIA, and SAH. Linkage Disequilibrium Score Regression (LDSC) analysis corroborated a significant genetic correlation between these gut microbiota strains and various forms of cerebrovascular disease. In contrast, reverse MR analysis failed to establish a bidirectional causal relationship between genetically inferred gut microbiota profiles and these cerebrovascular conditions.
Conclusion: This investigation has pinpointed particular strains of gut microbiota that play protective or detrimental roles in cerebrovascular disease pathogenesis. These findings offer valuable insights that could be pivotal for the clinical management, prevention, and treatment of cerebrovascular diseases.
[http://dx.doi.org/10.1097/WCO.0b013e32834f89b1] [PMID: 22222890]
[http://dx.doi.org/10.1161/STROKEAHA.119.024159] [PMID: 32078448]
[http://dx.doi.org/10.1016/S0140-6736(18)31269-8] [PMID: 30319114]
[http://dx.doi.org/10.2471/BLT.16.181636] [PMID: 27708464]
[http://dx.doi.org/10.1001/jamaneurol.2019.3933] [PMID: 31738373]
[http://dx.doi.org/10.1016/S0140-6736(15)00463-8] [PMID: 26595643]
[http://dx.doi.org/10.1016/S0140-6736(14)60772-8]
[http://dx.doi.org/10.1016/S0140-6736(22)00938-2] [PMID: 35985353]
[http://dx.doi.org/10.1177/0271678X20918031] [PMID: 32312168]
[http://dx.doi.org/10.1161/CIRCRESAHA.122.319983] [PMID: 35420913]
[http://dx.doi.org/10.1161/STROKEAHA.119.025140] [PMID: 31272315]
[http://dx.doi.org/10.1038/s12276-022-00728-w] [PMID: 35115674]
[http://dx.doi.org/10.1093/ije/dyaa009] [PMID: 32068838]
[http://dx.doi.org/10.1371/journal.pmed.1002739] [PMID: 30703100]
[http://dx.doi.org/10.1038/s41588-020-00763-1] [PMID: 33462485]
[http://dx.doi.org/10.1101/2022.03.03.22271360]
[http://dx.doi.org/10.1093/nar/gkac1010] [PMID: 36350656]
[http://dx.doi.org/10.7554/eLife.34408] [PMID: 29846171]
[http://dx.doi.org/10.1038/s41588-021-00931-x] [PMID: 34594039]
[http://dx.doi.org/10.1038/s41588-018-0058-3] [PMID: 29531354]
[http://dx.doi.org/10.1002/sim.6835] [PMID: 26661904]
[http://dx.doi.org/10.3389/fmicb.2023.1243811] [PMID: 37655340]
[http://dx.doi.org/10.1093/aje/kwt084] [PMID: 23863760]
[http://dx.doi.org/10.1093/ije/dyv080] [PMID: 26050253]
[http://dx.doi.org/10.1093/ije/dyx102] [PMID: 29040600]
[http://dx.doi.org/10.1038/s41588-018-0099-7] [PMID: 29686387]
[http://dx.doi.org/10.1093/ije/dyu005] [PMID: 24608958]
[http://dx.doi.org/10.1093/bioinformatics/btn209] [PMID: 18441000]
[http://dx.doi.org/10.1371/journal.pgen.1007081] [PMID: 29149188]
[http://dx.doi.org/10.1136/ebmental-2019-300117] [PMID: 31563865]
[http://dx.doi.org/10.1186/s12916-023-02761-6] [PMID: 36810112]
[http://dx.doi.org/10.1186/s12916-022-02657-x] [PMID: 36380372]
[http://dx.doi.org/10.3389/fcimb.2019.00004] [PMID: 30778376]
[http://dx.doi.org/10.1038/ncomms2266] [PMID: 23212374]
[http://dx.doi.org/10.1186/s12866-019-1552-1] [PMID: 31426765]
[http://dx.doi.org/10.1002/jpen.2295] [PMID: 34813118]
[http://dx.doi.org/10.1161/JAHA.115.002699] [PMID: 26597155]
[http://dx.doi.org/10.4103/0366-6999.222332] [PMID: 29336358]
[http://dx.doi.org/10.1371/journal.pone.0215262] [PMID: 31339887]
[http://dx.doi.org/10.1039/D0FO01006E] [PMID: 32432606]
[http://dx.doi.org/10.1039/D0FO03331F] [PMID: 33908936]
[http://dx.doi.org/10.3389/fmicb.2019.03067] [PMID: 32010111]
[http://dx.doi.org/10.1038/s41366-021-00904-4] [PMID: 34267323]
[http://dx.doi.org/10.3390/nu14010012] [PMID: 35010887]
[http://dx.doi.org/10.1016/j.scitotenv.2022.155199] [PMID: 35417730]
[http://dx.doi.org/10.1111/jcpe.12634] [PMID: 27717180]
[http://dx.doi.org/10.1073/pnas.0812874106] [PMID: 19234110]
[http://dx.doi.org/10.1073/pnas.1215927110] [PMID: 23401498]
[http://dx.doi.org/10.1161/HYPERTENSIONAHA.120.14800] [PMID: 32475312]
[http://dx.doi.org/10.1080/19490976.2020.1814107] [PMID: 32897773]
[http://dx.doi.org/10.1161/CIRCRESAHA.119.316448] [PMID: 32354259]
[http://dx.doi.org/10.1016/j.phrs.2019.104403] [PMID: 31425750]
[http://dx.doi.org/10.1016/j.phrs.2020.104809] [PMID: 32502642]
[http://dx.doi.org/10.1016/S1474-4422(19)30079-1] [PMID: 31097385]
[http://dx.doi.org/10.1097/MD.0000000000026749] [PMID: 34397717]
[http://dx.doi.org/10.1128/mbio.01085-22] [PMID: 35726919]
[http://dx.doi.org/10.1093/cvr/cvaa175] [PMID: 32569375]
[http://dx.doi.org/10.1093/eurjpc/zwac128] [PMID: 35727958]