Immune cells and Alzheimer's disease: a bidirectional two-sample Mendelian randomization study

Immune cells and Alzheimer's disease: a bidirectional two-sample Mendelian randomization study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Immune cells and Alzheimer's disease: a bidirectional two-sample Mendelian randomization study Jian Zhang, Yueling Zhang, Hao Wang, Zhilin Huang, Shuyu Xie, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3831902/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Immune cells play a crucial role in the pathogenesis of Alzheimer's disease (AD). Although the relationship between immune cells and AD is uncertain, it is clinically important, as immune cells could be targets for therapy. The current study aimed to systematically explore the bidirectional relationship between immune cells and AD. Genetic instruments for AD and 731 immune cell traits were derived from large-scale genome-wide association studies. We performed a bidirectional two-sample Mendelian randomization (MR) study to explore causation. In the forward MR analysis (immune cells as exposure and AD as outcome), we found 41 immune cell traits causally associated with AD. The reverse MR analysis (AD as exposure and immune cell as outcome) indicated that AD affected 57 immune cell traits. Our results indicated that a variety of immune cells were causally associated with AD. Among them, resting Tregs, CD25 hi , CD20 and CD33 were linked to the development of AD, while activated Tregs, secreted Tregs and HLA DR were protective factors for AD. Future studies are needed to develop the above immunophenotypes as biomarkers and therapeutic targets in AD. Figures Figure 1 Figure 2 Introduction Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, memory loss, and behavioral changes. It is the most common cause of dementia, accounting for approximately 60-80% of all dementia cases.[1] The prevalence of AD is increasing worldwide due to the aging population. According to the World Health Organization, it is estimated that approximately 55 million people globally are living with dementia, and there are nearly 10 million new cases every year[2]. AD poses a significant economic burden on health care systems and societies. The costs associated with diagnosis, management, and long-term care are substantial. In addition, caregiving responsibilities often affect family members, leading to emotional, physical, and financial strain. In 2019, dementia cost economies globally 1.3 trillion US dollars; approximately 50% of these costs are attributable to care provided by informal carers (e.g. family members and close friends), who provide on average 5 hours of care and supervision per day.[2] Currently, there is no cure for AD, but several treatment methods, such as, cholinesterase inhibitors and N-methyl-D-aspartate (NMDA) receptor antagonists can be used to manage symptoms and slow disease progression.[3] These medications help improve cognitive function and enhance daily living activities. Additionally, nonpharmacological interventions, such as cognitive stimulation therapy and physical exercise, have shown promising results in improving quality of life for individuals with AD.[4] In recent years, emerging evidence has suggested that immune cells play a crucial role in the pathogenesis of AD.[5] Immune cells, including microglia, astrocytes, and peripheral immune cells, are intimately involved in AD.[6] Microglia, the resident immune cells of the central nervous system, are responsible for maintaining brain homeostasis and immune surveillance. Whether microglia are beneficial or if they are insufficient to combat AD is still not clear. Perhaps microglia are effective in the early stages but lose their efficacy or even become detrimental in the later stages.[7] Another study showed that the activation of microglia can protect against the accumulation of tau aggregates in nondemented individuals with underlying AD pathology.[8] Astrocytes, another type of glial cell, also have both neuroprotective and neurotoxic effects depending on the disease stage and microenvironmental factors.[9] Additionally, infiltration of peripheral immune cells, such as monocytes and T lymphocytes, into the brain further exacerbates neuroinflammation and neurodegeneration.[10] Following AD onset, the phenotype and function of immune cells undergo significant changes. Microglia switch from a homeostatic to a disease-associated phenotype characterized by a pro-inflammatory state and reduced phagocytic capacity. Astrocytes become reactive and release excessive levels of cytokines, exacerbating neuroinflammation. Moreover, peripheral immune cells display altered trafficking patterns and exhibit a proinflammatory phenotype in the brain. Current research focuses on elucidating the molecular mechanisms underlying immune cell dysfunction in AD and exploring potential therapeutic interventions.[11] The interplay between AD and immune cells will offer new insights into disease mechanisms and potential therapeutic targets and hold promise for future AD therapies. Mendelian randomization (MR) is a statistical technique that uses genetic variants as instrumental variables to assess the causal relationship between an exposure and an outcome. It exploits naturally occurring genetic variation that is randomly allocated at conception to mimic an experimental manipulation. MR has become increasingly popular in recent years as a way to investigate causal pathways in epidemiological research and has been used to study a wide range of exposures and outcomes. In this study, a bidirectional two-sample MR analysis was performed to determine the causal association between immune cell traits and AD. Methods Data availability and ethical statement All data used in this study are publicly available from the respective GWAS. Ethics approval was not needed for this study since we used publicly available anonymized aggregated data. Data Data on immune cell traits from GWAS summary statistics can be publicly accessed through the GWAS catalog (registration numbers GCST90001391 to GCST90002121).[12] This study reports on the impact of approximately 22 million variants on 731 immune cell traits in a Sardinian population cohort of 3,757 individuals. The initial immune trait GWAS utilized data from individuals of European descent without overlapping cohorts. GWAS aggregated statistics for AD are from the European Alzheimer & Dementia Biobank (EADB) consortium, including 20,464 clinically diagnosed AD cases and 22,244 controls that have been collated from 15 European countries. The EADB GWAS results were meta-analyzed with a proxy-AD (based on questionnaire data in which individuals are asked whether their parents had dementia) GWASs of the UK Biobank (UKBB) dataset. This study was based on 39,106 clinically diagnosed AD cases, 46,828 proxy-ADD cases and 401,577 controls.[13] The GWAS identified 75 risk loci, 42 of which were novel at the time of analysis. Gene prioritization of the new loci identified 31 genes, which suggests new genetic pathways for disease association. Bidirectional Two-sample MR analysis The causal association between 731 immune cell traits and AD analyses was performed in R 4.3.1 software (http://www.Rproject.org). First, using 731 immune cell traits as exposure factors, with AD as the outcome, SNPs that met the genome-wide significance level (P < 5×10 −8 ) were selected as instrumental variables (IVs). Eligible IVs must met three key assumptions: (1) the genetic variant should be directly associated with the exposure (relevance assumption); (2) the genetic variant should not be directly related to confounding factors (independence assumption); and (3) the genetic variant should not have a direct association with the outcome (exclusion assumption).[14] Within the selected SNPs, a clumping method based on linkage disequilibrium (LD) clustering with a r 2 10000 was used to exclude correlated SNPs. The I 2 statistic, weighted by inverse variance, was employed to test for heterogeneity among the SNPs. For the two-sample MR analysis, employ the weighted method using inverse variance, as well as MR Egger, weighted median, simple mode, weighted mode, and MR-Presso (MR pleiotropy residual sum and outlier) methods for multiple sensitivity analyses to account for pleiotropy.[15-20] Subsequently, a reverse MR analysis was conducted with AD as the exposure factor and 731 immune cell traits as the outcome. Results Exploration of the causal effect of immune cell traits on AD To explore the causal effects of immune cell traits on AD, two-sample MR analysis was performed, and the IVW method was used as the main analysis. After forward MR analysis, we detected that 41 immune cell traits were causally associated with AD. Among them, 13 exhibited a protective effect against AD, while 28 were identified as risk factors for AD (Figure 1, Supplement 1-2). Exploration of the causal effect of AD onset on immune cell traits To explore the causal effects of AD on immune cell traits, two-sample MR analysis was performed, and the IVW method was used as the main analysis. In reverse MR analyses, 55 SNPs were selected as the genetic instruments for AD. The IVW result indicated that AD may increase 17 immune cell trait levels and decrease 40 immune cell trait levels. (Figure 2, Supplement 3-4). In addition, we performed heterogeneity test, pleiotropy analysis and sensitivity analysis to verify the reliability of the results. Heterogeneity test showed that there was no heterogeneity among IVs. The intercept of the MR-Egger and the global test of MR-PRESSO ruled out the possibility of horizontal pleiotropy. "Leave-one-out" method was used for sensitivity analysis, and there were no IVs that seriously affected the outcome variables. Funnel plots were performed and there was no publication bias. (Supplement 5-6). Discussion Based on large, publicly available genetic data, we systematically explored causal associations between 731 immune cell traits and AD. In this study, 41 immunophenotypes had significant causal effects on AD, and AD was found to have causal effects on 57 immunophenotypes. Regulatory T cells (Tregs) are a T-lymphocyte subset involved in the maintenance of immune peripheral tolerance. One study demonstrated that the activation of Tregs plays a beneficial role in the pathophysiology of AD by enhancing the clearance of amyloid-β plaques and improving cognitive performance in mice with AD-like pathology.[21] Another study considered AD to be characterized by chronic inflammation and suggested targeting Treg-mediated systemic immunosuppression for treating AD.[22] Tregs exist in several states, including resting, activated, and secreting states, each with different functions in the immune response. Resting Tregs are nonproliferating cells that suppress immune responses through contact-dependent mechanisms. Activated Tregs embody the cluster that originated after their exposure to self-antigens. Secreting Tregs have a well-described cytokine-secreting nonsuppressive function. A previous study demonstrated a significant decrease in resting Tregs in AD patients compared to healthy controls.[23] The decrease in resting Tregs could describe an impairment of the immune reserve, possibly representing a failure mechanism in Treg-mediated peripheral tolerance barrier efficacy.[23] Activated and secreted Tregs can suppress inflammation by secreting immunosuppressive cytokines such as IL-10, transforming growth factor-beta (TGF-β) and IL-35. These Tregs could have neuroprotective effects by mitigating neuroinflammation in AD.[21] Our study suggests that secreting Tregs and activated Tregs have a protective effect against AD, which is consistent with previous studies. In our study, the risk of AD increased with an increase in the proportion of resting Tregs. However, the mechanisms underlying the association between resting Treg-related phenotypes and AD are not entirely clear. Further research is needed to elucidate the mechanisms underlying this relationship and explore the therapeutic potential of targeting resting Tregs in AD. Our study suggests that the increased proportion of CD25 hi CD45RA + CD4 T cells, not Tregs, in CD4 + and T cells is a risk factor for AD. CD25 hi CD45RA+ CD4 T cells, not Tregs, are a subset of immune cells that express high levels of CD25 and the naive T-cell marker CD45RA but do not exhibit Treg function. However, the exact mechanisms underlying the relationship between CD25 hi CD45RA + CD4 but not Treg cells and AD remain to be fully elucidated. Further research is needed to understand the specific roles of these cells in the pathogenesis of AD and their potential as therapeutic targets. CD45RA − CD4 + %CD4 + refers to the percentage of CD4 + T cells in which the surface marker CD45RA is not expressed or expressed at low levels among the total population of CD4 + T cells. It is a measure of the proportion of CD45RA − CD4 + cells among the total population of CD4 + T cells. EM DN (CD4 - CD8 - ) %DN refers to the percentage of double-negative (DN) T cells within the immune cell population that lack the expression of both CD4 and CD8 surface markers. CD28 + CD45RA + CD8 dim %CD8 dim refers to the percentage of CD8 dim T cells within the total population of CD8 + T cells that express both CD28 and CD45RA surface markers. Changes in the above percentage may be associated with AD. Our MR analysis shows that the increase in CD45RA − CD4 + %CD4 + and EM DN (CD4 - CD8 - ) %DN may be protective factors for AD, while the increase in CD28 + CD45RA + CD8 dim %CD8 dim may be a risk factor. The specific relationship and mechanisms involved require further research to be fully understood. Our study indicates that CD33 is a risk factor for AD, which is consistent with previous findings.[24] Previous studies have shown that CD33 expression is increased in microglia in the brains of AD patients, and CD33 inhibits the community and clearance of the microglia culture species Aβ42.[25] The expression level of CD33 mRNA in peripheral white blood cells of patients with late-onset Alzheimer's disease is increased.[26] Two other studies have shown that the rs3865444 risk allele is associated with greater cell surface expression of CD33 in monocytes in the population and that the CD33 rs3865444 polymorphism is associated with AD susceptibility in Chinese, European, and North American populations.[27, 28] Animal studies have shown that knocking out CD33 reduces the load of amyloid plaques in mouse models of AD, suggesting that AD gene therapy targeting CD33 may reduce amyloid beta accumulation and neuroinflammation.[29] In the future, inhibition of CD33 may be a therapeutic target for AD. Our study also found that CD20 is a risk factor for AD. However, few studies have explored the relationship between AD and CD20. For other cognitive disorders, researchers have explored the use of anti-CD20 antibodies as a therapeutic approach in delayed cognitive impairment following stroke in mouse models. They found that the pharmacologic ablation of B lymphocytes using an anti-CD20 antibody can prevent the appearance of delayed cognitive deficits.[30] Immunostaining from autopsies of human brain tissue has also shown a B-lymphocyte response in some stroke and dementia patients. In a similar way, anti-CD20 antibodies may selectively deplete B cells, thereby reducing their potential contribution to neuroinflammation and antibody-mediated pathology in AD. B-cell dysfunction and CD20-mediated signaling may contribute to the onset and progression of AD. Further studies are needed to elucidate the underlying mechanisms and evaluate the potential of CD20-targeted therapies for AD. Our study shows that CD25 on CD39+ CD4+ is a protective factor and CD4 on CD39+ CD4+ is a risk factor in AD. At present, there are few studies on the relationship between CD25, CD4 and AD, and further research is needed to clarify their role and mechanism. Our study shows that HLA DR, a member of the human leukocyte antigen (HLA) family, is a protective factor for AD. In 1987, McGeer et al. found that in the brain tissue of AD patients, the expression level of HLA-DR was significantly increased and positively correlated with the number of plaques, suggesting that HLA-DR may be involved in the pathophysiological processes of AD.[31] In addition, some researchers believe that HLA-DR plays an important role in the immune response to AD and is involved in antigen presentation and recognition in the immune system.[32] In chimeric AD mice, increased expression of HLA‐DR proteins is associated with a reduced risk of AD.[33] The mechanism behind this protective effect is not yet fully understood; perhaps HLA DR influences the development of AD by regulating the activation state of T cells and macrophages. Further research is needed to better understand the relationship between HLA-DR and AD risk, as well as the mechanisms underlying these associations. In addition, the study also conducted reverse MR analysis (using AD as the exposure and immune cell traits as the outcome) and confirmed that AD significantly changed the phenotype and function of immune cells. Our study has some limitations. First, because the GWASs used in our study were primarily based on patients of European descent, the generalization of our findings to other ethnicities may be limited. Second, due to the lack of individual information, we cannot conduct further stratified analysis of the population. The conclusions of this study are based on genetic instrumental variables, and causal inference is made using a variety of MR analysis methods. The results are robust and were not confounded by horizontal pleiotropy or other factors. Conclusion Our results indicated that a variety of immune cells were causally associated with AD. Among them, resting Tregs, CD25 hi , CD20 and CD33 were linked to the development of AD, while activated Tregs, secreted Tregs and HLA DR were protective factors for AD. Future studies are needed to develop the above immunophenotypes as biomarkers and therapeutic targets in AD. Declarations Ethics approval and consent to participate: Ethical approval was not required for this study as we used anonymized summary-level data that were available to the public. Consent for publication: Not Applicable. Availability of data and materials: All data used for this study is publicly available from the respective GWAS. Competing interests: None declared. Authors' contributions: Study conception and design were done by J.Z. and YL.Z. Analyses were carried out by all authors. Draft of the article was done by J.Z. and YL.Z. Supervision of the study was carried out by SL.S. and DY.K. Interpretation of results, critical editing, and article approval were done by all authors. 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The P522R protective variant of PLCG2 promotes the expression of antigen presentation genes by human microglia in an Alzheimer's disease mouse model. Alzheimers Dement. 2022;18(10):1765-78. https://doi.org/10.1002/alz.12577. Additional Declarations No competing interests reported. Supplementary Files Supplement1.ResultsofforwardMRanalysis.txt Supplement2.ResultsofforwardMRanalysisIVWonly.txt Supplement3.ResultsofreverseMRanalysis.txt Supplement4.ResultsofreverseMRanalysisIVWonly.txt Supplement5.zip Supplement6.zip Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3831902","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":265021706,"identity":"7ac1291a-56c9-4e7b-ab92-0146701a3d27","order_by":0,"name":"Jian Zhang","email":"","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Zhang","suffix":""},{"id":265021707,"identity":"a473785c-09b2-48e7-ba8c-dc45effe7b73","order_by":1,"name":"Yueling Zhang","email":"","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yueling","middleName":"","lastName":"Zhang","suffix":""},{"id":265021708,"identity":"b46d107b-af2b-4c72-9b8f-491c0ca9b398","order_by":2,"name":"Hao Wang","email":"","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Wang","suffix":""},{"id":265021709,"identity":"55ac2ab2-e44f-492e-9f0c-847fdbef355d","order_by":3,"name":"Zhilin Huang","email":"","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhilin","middleName":"","lastName":"Huang","suffix":""},{"id":265021710,"identity":"3d49631f-bdee-46a3-8813-abfee8b35250","order_by":4,"name":"Shuyu Xie","email":"","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shuyu","middleName":"","lastName":"Xie","suffix":""},{"id":265021711,"identity":"783a8685-ac6f-4b17-818e-45f2ff613033","order_by":5,"name":"Dongmei Fan","email":"","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Dongmei","middleName":"","lastName":"Fan","suffix":""},{"id":265021712,"identity":"de078393-adb3-4c66-9c9d-81c36b1718d6","order_by":6,"name":"Yiyun Chen","email":"","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yiyun","middleName":"","lastName":"Chen","suffix":""},{"id":265021713,"identity":"75a15adb-ef07-4a2c-841b-e6989b25d15e","order_by":7,"name":"Chongxu Zhong","email":"","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chongxu","middleName":"","lastName":"Zhong","suffix":""},{"id":265021714,"identity":"0386c1a5-a4db-42f1-a213-f52a12fca3de","order_by":8,"name":"Liufei Chen","email":"","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Liufei","middleName":"","lastName":"Chen","suffix":""},{"id":265021715,"identity":"b2cc7c7b-ff8c-4c62-a8d9-a56d2a257dad","order_by":9,"name":"Deyan Kong","email":"","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Deyan","middleName":"","lastName":"Kong","suffix":""},{"id":265021716,"identity":"350667c6-f27a-439d-b091-e05b965f2bbe","order_by":10,"name":"Shengliang Shi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwklEQVRIiWNgGAWjYFAC5gaGhAobZn5m5sMPiNTC2MDw4Ewau2Q7W5oB0VoYH7Yd4jc4z6MgQZQG+f6DDQyJbQekjQ/zMBgw1NhEE9RicCMR6Jdzd4zNDvMeeMBwLC23gaAWCaBfEsqeJZsd5kswYGw4TFgL2GEJbIfrNzfzgLQToYXhAMhhbYeZDZiJ1QLxy5k0ZonDwEBOIMYv8v2HDzD+AEVl/+HDDz7U2BDhMAYG9h9wZgIRykfBKBgFo2AUEAEACUVAT5ENosgAAAAASUVORK5CYII=","orcid":"","institution":"the Second Affiliated Hospital of Guangxi Medical University","correspondingAuthor":true,"prefix":"","firstName":"Shengliang","middleName":"","lastName":"Shi","suffix":""}],"badges":[],"createdAt":"2024-01-03 13:14:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3831902/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3831902/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49241615,"identity":"03c8d533-dfb2-4072-bbfa-677b3781afd4","added_by":"auto","created_at":"2024-01-05 18:26:44","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1920258,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot for the IVW results of bidirectional 2-sample MR analyses. AD as the outcome, and immune cell traits as exposure, forest plot showing the causal effect of immune cell traits on AD.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3831902/v1/2502cc753325462dfc8d826e.jpg"},{"id":49242911,"identity":"6697ccd7-7064-4463-89da-33f1bec81ff2","added_by":"auto","created_at":"2024-01-05 18:34:44","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2588091,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot for the IVW results of bidirectional 2-sample MR analyses. AD as exposure, forest plot showing the causal effect of AD on immune cell traits.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3831902/v1/4b97cbdd47a53540c433d844.jpg"},{"id":55906359,"identity":"b3e0cc7a-d420-44e9-9c32-36e32e4ae381","added_by":"auto","created_at":"2024-05-06 06:54:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":860917,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3831902/v1/e83e4388-fe02-4dd1-a094-9e6dae8198e3.pdf"},{"id":49241614,"identity":"a0db2f71-4229-4db7-a1db-f7bf472fc812","added_by":"auto","created_at":"2024-01-05 18:26:44","extension":"txt","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":53155,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement1.ResultsofforwardMRanalysis.txt","url":"https://assets-eu.researchsquare.com/files/rs-3831902/v1/9bbf86d45cb7ed5541eb96d5.txt"},{"id":49242910,"identity":"2da69d91-cadd-4c34-832d-57b166039cb0","added_by":"auto","created_at":"2024-01-05 18:34:44","extension":"txt","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":11202,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement2.ResultsofforwardMRanalysisIVWonly.txt","url":"https://assets-eu.researchsquare.com/files/rs-3831902/v1/e5666daf98b38ba90e694eb4.txt"},{"id":49241617,"identity":"59bfd2e9-b8aa-4515-8725-fe6407443b80","added_by":"auto","created_at":"2024-01-05 18:26:44","extension":"txt","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":71661,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement3.ResultsofreverseMRanalysis.txt","url":"https://assets-eu.researchsquare.com/files/rs-3831902/v1/d675728462effd1801377fd0.txt"},{"id":49241616,"identity":"747b65ef-8124-4fce-bb3b-3b0e8726b09c","added_by":"auto","created_at":"2024-01-05 18:26:44","extension":"txt","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":15150,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement4.ResultsofreverseMRanalysisIVWonly.txt","url":"https://assets-eu.researchsquare.com/files/rs-3831902/v1/de02ecbf4ec55ddd108ff501.txt"},{"id":49241621,"identity":"2af541e1-a101-40e1-92dc-2cbdaf40cd36","added_by":"auto","created_at":"2024-01-05 18:26:44","extension":"zip","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1224530,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement5.zip","url":"https://assets-eu.researchsquare.com/files/rs-3831902/v1/39a9abe56c5df61118b2d275.zip"},{"id":49241622,"identity":"da9db85d-8641-46fa-86de-344480503ab2","added_by":"auto","created_at":"2024-01-05 18:26:45","extension":"zip","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":2744997,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement6.zip","url":"https://assets-eu.researchsquare.com/files/rs-3831902/v1/9b69307adbb083bf9cb5c500.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Immune cells and Alzheimer's disease: a bidirectional two-sample Mendelian randomization study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlzheimer\u0026apos;s disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, memory loss, and behavioral changes. It is the most common cause of dementia, accounting for approximately 60-80% of all dementia cases.[1]\u0026nbsp;The prevalence of AD is increasing worldwide due to the aging population. According to the World Health Organization, it is estimated that approximately 55 million people globally are living with dementia, and there are nearly 10 million new cases every year[2]. AD poses a significant economic burden on health care systems and societies. The costs associated with diagnosis, management, and long-term care are substantial. In addition, caregiving responsibilities often affect family members, leading to emotional, physical, and financial strain. In 2019, dementia cost economies globally 1.3 trillion US dollars; approximately 50% of these costs are attributable to care provided by informal carers (e.g. family members and close friends), who provide on average 5 hours of care and supervision per day.[2]\u0026nbsp;Currently, there is no cure for AD, but several treatment methods, such as, cholinesterase inhibitors and N-methyl-D-aspartate (NMDA) receptor antagonists can be used to manage symptoms and slow disease progression.[3]\u0026nbsp;These medications help improve cognitive function and enhance daily living activities. Additionally, nonpharmacological interventions, such as cognitive stimulation therapy and physical exercise, have shown promising results in improving quality of life for individuals with AD.[4]\u003c/p\u003e\n\u003cp\u003eIn recent years, emerging evidence has suggested that immune cells play a crucial role in the pathogenesis of AD.[5]\u0026nbsp;Immune cells, including microglia, astrocytes, and peripheral immune cells, are intimately involved in AD.[6]\u0026nbsp;Microglia, the resident immune cells of the central nervous system, are responsible for maintaining brain homeostasis and immune surveillance. Whether microglia are beneficial or if they are insufficient to combat AD is still not clear. Perhaps microglia are effective in the early stages but lose their efficacy or even become detrimental in the later stages.[7]\u0026nbsp;Another study showed that the activation of microglia can protect against the accumulation of tau aggregates in nondemented individuals with underlying AD pathology.[8]\u0026nbsp;Astrocytes, another type of glial cell, also have both neuroprotective and neurotoxic effects depending on the disease stage and microenvironmental factors.[9]\u0026nbsp;Additionally, infiltration of peripheral immune cells, such as monocytes and T lymphocytes, into the brain further exacerbates neuroinflammation and neurodegeneration.[10]\u0026nbsp;Following AD onset, the phenotype and function of immune cells undergo significant changes. Microglia switch from a homeostatic to a disease-associated phenotype characterized by a pro-inflammatory state and reduced phagocytic capacity. Astrocytes become reactive and release excessive levels of cytokines, exacerbating neuroinflammation. Moreover, peripheral immune cells display altered trafficking patterns and exhibit a proinflammatory phenotype in the brain. Current research focuses on elucidating the molecular mechanisms underlying immune cell dysfunction in AD and exploring potential therapeutic interventions.[11]\u0026nbsp;The interplay between AD and immune cells will offer new insights into disease mechanisms and potential therapeutic targets and hold promise for future AD therapies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMendelian randomization (MR) is a statistical technique that uses genetic variants as instrumental variables to assess the causal relationship between an exposure and an outcome. It exploits naturally occurring genetic variation that is randomly allocated at conception to mimic an experimental manipulation. MR has become increasingly popular in recent years as a way to investigate causal pathways in epidemiological research and has been used to study a wide range of exposures and outcomes. In this study, a bidirectional two-sample MR analysis was performed to determine the causal association between immune cell traits and AD.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eData availability and ethical statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data used in this study are publicly available from the respective GWAS. Ethics approval was not needed for this study since we used publicly available anonymized aggregated data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData on immune cell traits from GWAS summary statistics can be publicly accessed through the GWAS catalog (registration numbers GCST90001391 to GCST90002121).[12]\u0026nbsp;This study reports on the impact of approximately 22 million variants on 731 immune cell traits in a Sardinian population cohort of 3,757 individuals. The initial immune trait GWAS utilized data from individuals of European descent without overlapping cohorts.\u003c/p\u003e\n\u003cp\u003eGWAS aggregated statistics for AD are from the European Alzheimer \u0026amp; Dementia Biobank (EADB) consortium, including 20,464 clinically diagnosed AD cases and 22,244 controls that have been collated from 15 European countries. The EADB GWAS results were meta-analyzed with a proxy-AD (based on questionnaire data in which individuals are asked whether their parents had dementia) GWASs of the UK Biobank (UKBB) dataset. This study was based on 39,106 clinically diagnosed AD cases, 46,828 proxy-ADD cases and 401,577 controls.[13] The GWAS identified 75 risk loci, 42 of which were novel at the time of analysis. Gene prioritization of the new loci identified 31 genes, which suggests new genetic pathways for disease association.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBidirectional Two-sample MR analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe causal association between 731 immune cell traits and AD analyses was performed in R 4.3.1 software (http://www.Rproject.org). First, using 731 immune cell traits as exposure factors, with AD as the outcome, SNPs that met the genome-wide significance level (P \u0026lt; 5\u0026times;10\u003csup\u003e\u0026minus;8\u003c/sup\u003e) were selected as instrumental variables (IVs). Eligible IVs must met three key assumptions: (1) the genetic variant should be directly associated with the exposure (relevance assumption); (2) the genetic variant should not be directly related to confounding factors (independence assumption); and (3) the genetic variant should not have a direct association with the outcome (exclusion assumption).[14]\u0026nbsp;Within the selected SNPs, a clumping method based on linkage disequilibrium (LD) clustering with a r\u003csup\u003e2\u003c/sup\u003e \u0026lt; 0.001 threshold and clump window \u0026gt; 10000 was used to exclude correlated SNPs. The I\u003csup\u003e2\u003c/sup\u003e statistic, weighted by inverse variance, was employed to test for heterogeneity among the SNPs. For the two-sample MR analysis, employ the weighted method using inverse variance, as well as MR Egger, weighted median, simple mode, weighted mode, and MR-Presso (MR pleiotropy residual sum and outlier) methods for multiple sensitivity analyses to account for pleiotropy.[15-20] Subsequently, a reverse MR analysis was conducted with AD as the exposure factor and 731 immune cell traits as the outcome.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eExploration of the causal effect of immune cell traits on AD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo explore the causal effects of immune cell traits on AD, two-sample MR analysis was performed, and the IVW method was used as the main analysis. After forward MR analysis, we detected that 41 immune cell traits were causally associated with AD. Among them, 13 exhibited a protective effect against AD, while 28 were identified as risk factors for AD (Figure 1, Supplement 1-2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExploration of the causal effect of AD onset on immune cell traits\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo explore the causal effects of AD on immune cell traits, two-sample MR analysis was performed, and the IVW method was used as the main analysis. In reverse MR analyses, 55 SNPs were selected as the genetic instruments for AD. The IVW result indicated that AD may increase 17 immune cell trait levels and decrease 40 immune cell trait levels. (Figure 2, Supplement 3-4).\u003c/p\u003e\n\u003cp\u003eIn addition, we performed heterogeneity test, pleiotropy analysis and sensitivity analysis to verify the reliability of the results. Heterogeneity test showed that there was no heterogeneity among IVs. The intercept of the MR-Egger and the global test of MR-PRESSO ruled out the possibility of horizontal pleiotropy. \u0026quot;Leave-one-out\u0026quot; method was used for sensitivity analysis, and there were no IVs that seriously affected the outcome variables. Funnel plots were performed and there was no publication bias. (Supplement 5-6).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eBased on large, publicly available genetic data, we systematically explored causal associations between 731 immune cell traits and AD. In this study, 41 immunophenotypes had significant causal effects on AD, and AD was found to have causal effects on 57 immunophenotypes.\u003c/p\u003e\n\u003cp\u003eRegulatory T cells (Tregs) are a T-lymphocyte subset involved in the maintenance of immune peripheral tolerance. One study demonstrated that the activation of Tregs plays a beneficial role in the pathophysiology of AD by enhancing the clearance of amyloid-\u0026beta; plaques and improving cognitive performance in mice with AD-like pathology.[21]\u0026nbsp;Another study considered AD to be characterized by chronic inflammation and suggested targeting Treg-mediated systemic immunosuppression for treating AD.[22]\u0026nbsp;Tregs exist in several states, including resting, activated, and secreting states, each with different functions in the immune response. Resting Tregs are nonproliferating cells that suppress immune responses through contact-dependent mechanisms. Activated Tregs embody the cluster that originated after their exposure to self-antigens. Secreting Tregs have a well-described cytokine-secreting nonsuppressive function. A previous study demonstrated a significant decrease in resting Tregs in AD patients compared to healthy controls.[23]\u0026nbsp;The decrease in resting Tregs could describe an impairment of the immune reserve, possibly representing a failure mechanism in Treg-mediated peripheral tolerance barrier efficacy.[23]\u0026nbsp;Activated and secreted Tregs can suppress inflammation by secreting immunosuppressive cytokines such as IL-10, transforming growth factor-beta (TGF-\u0026beta;) and IL-35. These Tregs could have neuroprotective effects by mitigating neuroinflammation in AD.[21]\u0026nbsp;Our study suggests that secreting Tregs and activated Tregs have a protective effect against AD, which is consistent with previous studies. In our study, the risk of AD increased with an increase in the proportion of resting Tregs. However, the mechanisms underlying the association between resting Treg-related phenotypes and AD are not entirely clear. Further research is needed to elucidate the mechanisms underlying this relationship and explore the therapeutic potential of targeting resting Tregs in AD.\u003c/p\u003e\n\u003cp\u003eOur study suggests that the increased proportion of CD25\u003csup\u003ehi\u003c/sup\u003e CD45RA\u003csup\u003e+\u003c/sup\u003e CD4\u0026nbsp;T cells,\u0026nbsp;not\u0026nbsp;Tregs,\u0026nbsp;in CD4\u003csup\u003e+\u003c/sup\u003e and T\u0026nbsp;cells\u0026nbsp;is a risk\u0026nbsp;factor\u0026nbsp;for AD. CD25\u003csup\u003ehi\u003c/sup\u003e CD45RA+ CD4\u0026nbsp;T cells,\u0026nbsp;not\u0026nbsp;Tregs, are\u0026nbsp;a subset of immune cells that express high levels of CD25 and the naive T-cell marker CD45RA but do not exhibit Treg function. However, the exact mechanisms underlying the relationship between CD25\u003csup\u003ehi\u003c/sup\u003e CD45RA\u003csup\u003e+\u003c/sup\u003e CD4\u0026nbsp;but\u0026nbsp;not\u0026nbsp;Treg cells\u0026nbsp;and AD remain to be fully elucidated. Further research is needed to understand the specific roles of these cells in the pathogenesis of AD and their potential as therapeutic targets.\u003c/p\u003e\n\u003cp\u003eCD45RA\u003csup\u003e\u0026minus;\u003c/sup\u003e CD4\u003csup\u003e+\u003c/sup\u003e %CD4\u003csup\u003e+\u003c/sup\u003e refers to the percentage of CD4\u003csup\u003e+\u003c/sup\u003e T cells in which the surface marker CD45RA is not expressed or expressed at low levels among the total population of CD4\u003csup\u003e+\u003c/sup\u003e T cells. It is a measure of the proportion of CD45RA\u003csup\u003e\u0026minus;\u003c/sup\u003e CD4\u003csup\u003e+\u003c/sup\u003e cells among the total population of CD4\u003csup\u003e+\u003c/sup\u003e T cells. EM DN (CD4\u003csup\u003e-\u003c/sup\u003eCD8\u003csup\u003e-\u003c/sup\u003e) %DN refers to the percentage of double-negative (DN) T cells within the immune cell population that\u0026nbsp;lack\u0026nbsp;the expression of both CD4 and CD8 surface markers. CD28\u003csup\u003e+\u003c/sup\u003e CD45RA\u003csup\u003e+\u003c/sup\u003e CD8\u003csup\u003edim\u003c/sup\u003e %CD8\u003csup\u003edim\u003c/sup\u003e refers to the percentage of CD8\u003csup\u003edim\u003c/sup\u003e T cells within the total population of CD8\u003csup\u003e+\u003c/sup\u003e T cells that express both CD28 and CD45RA surface markers. Changes in\u0026nbsp;the\u0026nbsp;above percentage may be associated with AD. Our MR\u0026nbsp;analysis shows that the increase\u0026nbsp;in\u0026nbsp;CD45RA\u003csup\u003e\u0026minus;\u003c/sup\u003e CD4\u003csup\u003e+\u003c/sup\u003e %CD4\u003csup\u003e+\u003c/sup\u003e and EM DN (CD4\u003csup\u003e-\u003c/sup\u003eCD8\u003csup\u003e-\u003c/sup\u003e) %DN may be protective factors for AD, while the increase\u0026nbsp;in\u0026nbsp;CD28\u003csup\u003e+\u003c/sup\u003e CD45RA\u003csup\u003e+\u003c/sup\u003e CD8\u003csup\u003edim\u003c/sup\u003e %CD8\u003csup\u003edim\u003c/sup\u003e may be a risk factor. The specific relationship and mechanisms involved require further research to be fully understood.\u003c/p\u003e\n\u003cp\u003eOur study indicates that CD33 is a risk factor for AD, which is consistent with previous findings.[24]\u0026nbsp;Previous studies have shown that CD33 expression is increased in microglia in the brains of AD patients, and CD33 inhibits the community and clearance of the microglia culture species A\u0026beta;42.[25]\u0026nbsp;The expression level of CD33 mRNA in peripheral white blood cells of patients with late-onset Alzheimer\u0026apos;s disease is increased.[26]\u0026nbsp;Two other studies have shown that the rs3865444 risk allele is associated with greater cell surface expression of CD33 in monocytes in the population and that the CD33 rs3865444 polymorphism is associated with AD susceptibility in Chinese, European, and North American populations.[27, 28]\u0026nbsp;Animal studies have shown that knocking out CD33 reduces the load of amyloid plaques in mouse models of AD, suggesting that AD gene therapy targeting CD33 may reduce amyloid beta accumulation and neuroinflammation.[29]\u0026nbsp;In the future, inhibition of CD33 may be a therapeutic target for AD.\u003c/p\u003e\n\u003cp\u003eOur study also\u0026nbsp;found\u0026nbsp;that CD20 is a risk factor for AD. However, few studies have explored the relationship between AD and CD20. For other cognitive disorders, researchers have explored the use of anti-CD20 antibodies as a therapeutic approach in delayed cognitive impairment following stroke in mouse models. They found that the pharmacologic ablation of B\u0026nbsp;lymphocytes using an anti-CD20 antibody can prevent the appearance of delayed cognitive deficits.[30]\u0026nbsp;Immunostaining from autopsies of human brain tissue has also shown a B-lymphocyte response in some stroke and dementia patients. In a similar way, anti-CD20 antibodies may selectively deplete B cells, thereby reducing their potential contribution to neuroinflammation and antibody-mediated pathology in AD. B-cell dysfunction and CD20-mediated signaling may contribute to the onset and progression of AD. Further studies are needed to elucidate the underlying mechanisms and evaluate the potential of CD20-targeted therapies for AD.\u003c/p\u003e\n\u003cp\u003eOur study\u0026nbsp;shows\u0026nbsp;that CD25 on CD39+ CD4+ is a protective factor and CD4 on CD39+ CD4+ is a risk factor in AD. At present, there are\u0026nbsp;few\u0026nbsp;studies on the relationship between CD25, CD4 and AD,\u0026nbsp;and\u0026nbsp;further\u0026nbsp;research is\u0026nbsp;needed to clarify their role and mechanism.\u003c/p\u003e\n\u003cp\u003eOur study shows that HLA DR, a member of the human leukocyte antigen (HLA) family, is a protective factor for AD. In 1987, McGeer et al. found that in the brain tissue of AD patients, the expression level of HLA-DR was significantly increased and positively correlated with the number of plaques, suggesting that HLA-DR may be involved in the pathophysiological processes of AD.[31]\u0026nbsp;In addition, some researchers believe that HLA-DR plays an important role in the immune response to AD\u0026nbsp;and\u0026nbsp;is involved in antigen presentation and recognition in the immune system.[32]\u0026nbsp;In chimeric AD mice, increased expression of HLA‐DR proteins is associated with a reduced risk of AD.[33]\u0026nbsp;The mechanism behind this protective effect is not yet fully understood; perhaps HLA DR influences the development of AD by regulating the activation state of T cells and macrophages. Further research is needed to better understand the relationship between HLA-DR and AD risk, as well as the mechanisms underlying these associations.\u003c/p\u003e\n\u003cp\u003eIn addition, the study also conducted reverse MR analysis (using AD as the exposure and immune cell traits as the outcome) and confirmed that AD significantly changed the phenotype and function of immune cells.\u003c/p\u003e\n\u003cp\u003eOur study has some limitations. First, because the GWASs used in our study\u0026nbsp;were\u0026nbsp;primarily based on patients of European descent, the generalization of our findings to other ethnicities may be limited. Second, due to the lack of individual information, we cannot conduct further stratified analysis of the population.\u003c/p\u003e\n\u003cp\u003eThe conclusions of this study are based on genetic instrumental variables, and causal inference is made using a variety of MR analysis methods. The results are robust and were not confounded by horizontal pleiotropy or other factors.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur results indicated that\u0026nbsp;a\u0026nbsp;variety of immune cells were\u0026nbsp;causally associated with AD. Among them, resting Tregs,\u0026nbsp;CD25\u003csup\u003ehi\u003c/sup\u003e, CD20 and CD33 were linked to the development of AD, while activated Tregs, secreted Tregs and HLA DR were protective factors for AD. Future studies are needed to develop the above immunophenotypes as biomarkers and therapeutic targets in AD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003col start=\"1\" style=\"list-style-type: lower-alpha;\"\u003e\n \u003cli\u003eEthics approval and consent to participate: Ethical approval was not required for this study as we used anonymized summary-level data that were available to the public.\u003c/li\u003e\n \u003cli\u003eConsent for publication: Not Applicable.\u003c/li\u003e\n \u003cli\u003eAvailability of data and materials: All data used for this study is publicly available from the respective GWAS.\u003c/li\u003e\n \u003cli\u003eCompeting interests: None declared.\u003c/li\u003e\n \u003cli\u003eAuthors\u0026apos; contributions: Study conception and design were done by J.Z. and YL.Z. Analyses were carried out by all authors. Draft of the article was done by J.Z. and YL.Z. Supervision of the study was carried out by SL.S. and DY.K. Interpretation of results, critical editing, and article approval were done by all authors.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe project was supported by the National Natural Science Foundation of China (No. 32060189).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlzheimer\u0026apos;s disease facts and figures. Alzheimers Dement. 2023;19(4):1598-695. https://doi.org/10.1002/alz.13016.\u003c/li\u003e\n\u003cli\u003eWorld_Health_Organization. Dementia. 15 March 2023. https://www.who.int/news-room/fact-sheets/detail/dementia.\u003c/li\u003e\n\u003cli\u003eCummings J, Lee G, Ritter A, Sabbagh M, Zhong K. Alzheimer\u0026apos;s disease drug development pipeline: 2019. 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Alzheimers Dement. 2022;18(10):1765-78. https://doi.org/10.1002/alz.12577.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3831902/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3831902/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eImmune cells play a crucial role in the pathogenesis of Alzheimer's disease (AD). Although the relationship between immune cells and AD is uncertain, it is clinically important, as immune cells could be targets for therapy. The current study aimed to systematically explore the bidirectional relationship between immune cells and AD. Genetic instruments for AD and 731 immune cell traits were derived from large-scale genome-wide association studies. We performed a bidirectional two-sample Mendelian randomization (MR) study to explore causation. In the forward MR analysis (immune cells as exposure and AD as outcome), we found 41 immune cell traits causally associated with AD. The reverse MR analysis (AD as exposure and immune cell as outcome) indicated that AD affected 57 immune cell traits. Our results indicated that a variety of immune cells were causally associated with AD. Among them, resting Tregs, CD25\u003csup\u003ehi\u003c/sup\u003e, CD20 and CD33 were linked to the development of AD, while activated Tregs, secreted Tregs and HLA DR were protective factors for AD. Future studies are needed to develop the above immunophenotypes as biomarkers and therapeutic targets in AD.\u003c/p\u003e","manuscriptTitle":"Immune cells and Alzheimer's disease: a bidirectional two-sample Mendelian randomization study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-05 18:26:39","doi":"10.21203/rs.3.rs-3831902/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9d220813-c9f7-4197-b6bc-cc31ee6addc7","owner":[],"postedDate":"January 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-06T06:53:23+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-05 18:26:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3831902","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3831902","identity":"rs-3831902","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}