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Heneka MT, Gauthier S, Chandekar SA, Hviid Hahn-Pedersen J, Bentsen MA, Zetterberg H. Neuroinflammatory fluid biomarkers in patients with Alzheimer's disease: a systematic literature review. Mol Psychiatry 2025; 30:2783-2798. [PMID: 40050444 PMCID: PMC12092255 DOI: 10.1038/s41380-025-02939-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2024] [Revised: 01/08/2025] [Accepted: 02/19/2025] [Indexed: 05/22/2025]
Abstract
INTRODUCTION Neuroinflammation is associated with both early and late stages of the pathophysiology of Alzheimer's disease (AD). Fluid biomarkers are gaining significance in clinical practice for diagnosis in presymptomatic stages, monitoring, and disease prognosis. This systematic literature review (SLR) aimed to identify fluid biomarkers for neuroinflammation related to clinical stages across the AD continuum and examined long-term outcomes associated with changes in biomarkers. METHODS The SLR was conducted per the Cochrane Handbook for Systematic Reviews of Interventions and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We used PubMed®, Embase®, and Cochrane Collaboration databases to search for articles in English (between 2012 and 2022) on AD or mild cognitive impairment due to AD, using "neuroinflammation" or other "immune" search strings. Two independent reviewers screened titles and examined data from full-text articles for the SLR. RESULTS After the initial screening, 54 studies were prioritized for data extraction based upon their relevance to the SLR research questions. Nine studies for YKL-40, seven studies for sTREM2, and 11 studies for GFAP examined the relationship between the neuroinflammatory biomarkers and the clinical stage of the disease. Nine longitudinal studies further explored the association of fluid biomarkers with long-term clinical outcomes of disease. Cerebrospinal fluid (CSF) levels of YKL-40 were elevated in patients with AD dementia, while CSF sTREM2 levels were more strongly associated with preclinical and early symptomatic stages of AD. Plasma GFAP levels remained consistently elevated both in patients with AD dementia and individuals in preclinical stages with β-amyloid pathology. Longitudinal changes in plasma GFAP appeared to be predictive of cognitive decline in patients over time. DISCUSSION Neuroinflammatory biomarkers are associated with AD progression. More longitudinal studies in the preclinical and MCI stages of AD are needed to validate fluid biomarkers for diagnosis, disease monitoring, and prognosis in clinical practice.
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Affiliation(s)
- Michael T Heneka
- Luxembourg Centre for Systems Biomedicine, Université du Luxembourg, Belvaux, Luxembourg.
| | - Serge Gauthier
- AD and Related Disorders Research Unit, McGill Center for Studies in Aging, Departments of Neurology & Neurosurgery, Psychiatry, and Medicine at McGill, Montreal, QC, Canada
| | | | | | | | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, University College London Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at University College London, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
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Prandin G, Valente M, Zhang L, Malhotra P, Sacco S, Foschi M, Ornello R, Pirera E, Toraldo F, Maisano D, Del Regno C, Komauli F, Jaramillo AG, AL‐Karadsheh H, Zahid H, Klein P, Abdalkader M, Manganotti P, Lobotesis K, Nguyen TN, Banerjee S, Gigli GL, Merlino G, D'Anna L. Age-Specific Differences in Inflammatory Biomarkers and Their Impact on Futile Recanalization After Mechanical Thrombectomy: An Inverse Probability Weighting Analysis. Eur J Neurol 2025; 32:e70182. [PMID: 40353608 PMCID: PMC12067390 DOI: 10.1111/ene.70182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2025] [Revised: 04/05/2025] [Accepted: 04/22/2025] [Indexed: 05/14/2025]
Abstract
BACKGROUND Mechanical thrombectomy (MT) is the standard treatment for large vessel occlusion (LVO) stroke. However, a substantial proportion of patients experience poor functional outcomes despite successful reperfusion, namely futile recanalization (FR). This study aimed to evaluate the predictive value of inflammatory biomarkers, measured on admission and at 24 h, in identifying the risk of FR and to assess age-specific differences influencing this outcome. METHODS This international, multicenter, observational study included patients with anterior circulation LVO stroke treated with MT. Strict inclusion criteria were applied to minimize confounding factors related to inflammation. Inflammatory biomarkers were assessed at admission and 24 h post-procedure. Inverse probability weighting (IPW) was utilized to balance baseline characteristics between patients with FR and effective recanalization (ER). Least absolute shrinkage and selection operator (LASSO) regression was applied to identify independent predictors, and restricted cubic splines were used to determine optimal biomarker cut-offs. RESULTS Among 885 patients, 470 (53%) experienced FR. In multivariate analysis, 24-h CRP (OR 1.01, 95% CI 1.01-1.02, p = 0.018) and 24-h NLR (OR 1.11, 95% CI 1.02-1.22, p = 0.019) were significant predictors of FR, with cut-offs of 8.55 and 4.58, respectively. In patients aged < 80 years, 24-h CRP and NLR were most predictive (cut-offs: 17.09 and 5.59). In patients aged ≥ 80 years, admission SIRI emerged as the most significant predictor (OR 1.24, 95% CI 1.06-1.50, p = 0.015), with an optimal cut-off value of 2.53. CONCLUSIONS Inflammatory biomarkers exhibit significant predictive value for FR following MT, with distinct age-specific patterns. These findings underscore the importance of tailoring predictive models and interventions to optimize clinical outcomes.
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Affiliation(s)
- Gabriele Prandin
- Clinical Unit of Neurology, Department of Medicine, Surgery and Health SciencesUniversity Hospital and Health Services of Trieste, ASUGI, University of TriesteTriesteItaly
- Department of Brain SciencesImperial College LondonLondonUK
| | - Mariarosaria Valente
- Stroke UnitUdine University HospitalUdineItaly
- Clinical NeurologyUdine University Hospital and DMED, University of UdineUdineItaly
| | - Liqun Zhang
- Department of NeurologySt George's University of LondonLondonUK
| | | | - Simona Sacco
- Department of Biotechnological and Applied Clinical SciencesUniversity of L'aquilaL'AquilaItaly
| | - Matteo Foschi
- Department of Biotechnological and Applied Clinical SciencesUniversity of L'aquilaL'AquilaItaly
| | - Raffaele Ornello
- Department of Biotechnological and Applied Clinical SciencesUniversity of L'aquilaL'AquilaItaly
| | - Edoardo Pirera
- Internal Medicine and Stroke Care Ward, Department of Promoting Health, Maternal‐Infant, Excellence and Internal and Specialized Medicine (ProMISE) “G. D'alessandro”University of PalermoPalermoItaly
| | | | | | | | | | | | | | - Hamza Zahid
- Department of NeurologySt George's University of LondonLondonUK
| | - Piers Klein
- Department of Neurology, RadiologyBoston Medical CenterBostonMassachusettsUSA
| | - Mohamad Abdalkader
- Department of Neurology, RadiologyBoston Medical CenterBostonMassachusettsUSA
| | - Paolo Manganotti
- Clinical Unit of Neurology, Department of Medicine, Surgery and Health SciencesUniversity Hospital and Health Services of Trieste, ASUGI, University of TriesteTriesteItaly
| | - Kyriakos Lobotesis
- Neuroradiology, Department of ImagingCharing Cross Hospital, Imperial College London, NHS Healthcare TrustLondonUK
| | - Thanh N. Nguyen
- Department of Neurology, RadiologyBoston Medical CenterBostonMassachusettsUSA
| | - Soma Banerjee
- Department of Brain SciencesImperial College LondonLondonUK
- Department of Stroke and NeuroscienceCharing Cross Hospital, Imperial College Healthcare NHS TrustLondonUK
| | - Gian Luigi Gigli
- Clinical NeurologyUdine University Hospital and DMED, University of UdineUdineItaly
| | - Giovanni Merlino
- Stroke UnitUdine University HospitalUdineItaly
- Clinical NeurologyUdine University Hospital and DMED, University of UdineUdineItaly
| | - Lucio D'Anna
- Department of Brain SciencesImperial College LondonLondonUK
- Department of Stroke and NeuroscienceCharing Cross Hospital, Imperial College Healthcare NHS TrustLondonUK
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Zhang F, Han X, Mu Q, Zailani H, Liu WC, Do QL, Wu Y, Wu N, Kang Y, Su L, Liu Y, Su KP, Wang F. Elevated cerebrospinal fluid biomarkers of neuroinflammation and neuronal damage in essential hypertension with secondary insomnia: Implications for Alzheimer's disease risk. Brain Behav Immun 2025; 125:158-167. [PMID: 39733863 DOI: 10.1016/j.bbi.2024.12.157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2024] [Revised: 12/20/2024] [Accepted: 12/26/2024] [Indexed: 12/31/2024] Open
Abstract
Essential hypertension (EH) with secondary insomnia is associated with increased risks of neuroinflammation, neuronal damage, and Alzheimer's disease (AD). However, its relationship with specific cerebrospinal fluid (CSF) biomarkers of neuronal damage and neuroinflammation remains unclear. This case-control study compared CSF biomarker levels across three groups: healthy controls (HC, n = 64), hypertension-controlled (HTN-C, n = 54), and hypertension-uncontrolled (HTN-U, n = 107) groups, all EH participants experiencing secondary insomnia. CSF samples from knee replacement patients were analyzed for key biomarkers, and sleep quality was assessed via the Pittsburgh Sleep Quality Index (PSQI). Our findings showed that the HTN-U group had significantly higher CSF levels of proinflammatory cytokines IL-6, TNF-α, and IL-17 than the HC and HTN-C groups (all p < 0.01). These cytokines correlated positively with secondary insomnia measures, with IL-6 (r = 0.285, p = 0.003), IL-17 (r = 0.324, p = 0.001), and TNF-α (r = 0.274, p = 0.005) linked to PSQI scores. In the HTN-U group, elevated IL-6, TNF-α, and IL-17 levels were also positively associated with neurofilament light (NF-L) and negatively with β-amyloid 42 (Aβ42), both key AD markers (all p < 0.05). Additionally, secondary insomnia was negatively correlated with Aβ42 (r = -0.225, p = 0.021) and positively with NF-L (r = 0.261, p = 0.007). Higher CSF palmitic acid (PA) levels observed in the HTN-U group were linked to poorer sleep quality (r = 0.208, p = 0.033). In conclusion, EH with secondary insomnia is associated with CSF biomarkers of neuronal damage, neuroinflammation, and neurodegeneration, suggesting a potential increase in AD risk among this population.
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Affiliation(s)
- Feng Zhang
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing 100096, China
| | - Xiaoli Han
- Clinical Nutrition Department, Friendship Hospital of Urumqi, Urumqi 830049, China
| | - Qingshuang Mu
- Xinjiang Key Laboratory of Neurological Disorder Research, the Second Affiliated Hospital of Xinjiang Medical University, Urumqi 830063, China
| | - Halliru Zailani
- Mind-Body Interface Research Center (MBI-Lab), China Medical University Hospital, Taichung, Taiwan; Graduate Institute of Nutrition, China Medical University, Taichung, Taiwan; Department of Biochemistry, Ahmadu Bello University, Zaria, Nigeria
| | - Wen-Chun Liu
- Mind-Body Interface Research Center (MBI-Lab), China Medical University Hospital, Taichung, Taiwan; Department of Nursing, National Tainan Junior College of Nursing, Tainan, Taiwan
| | - Quang Le Do
- Mind-Body Interface Research Center (MBI-Lab), China Medical University Hospital, Taichung, Taiwan; Graduate Institute of Nutrition, China Medical University, Taichung, Taiwan
| | - Yan Wu
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing 100096, China
| | - Nan Wu
- Institute of Polygenic Disease, Qiqihar Medical University, Qiqihar 161006, China
| | - Yimin Kang
- Medical Neurobiology Lab, Inner Mongolia Medical University, Huhhot 010110, China
| | - Lidong Su
- Medical Neurobiology Lab, Inner Mongolia Medical University, Baotou 014010, China
| | - Yanlong Liu
- School of Mental Health, Wenzhou Medical University, Wenzhou 325035, China.
| | - Kuan-Pin Su
- Mind-Body Interface Research Center (MBI-Lab), China Medical University Hospital, Taichung, Taiwan; College of Medicine, China Medical University, Taichung, Taiwan; Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan; An-Nan Hospital, China Medical University, Tainan, Taiwan.
| | - Fan Wang
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing 100096, China.
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Zhang C, Su Y, Zeng X, Zhu X, Gao R, Liu W, Du R, Chen C, Liu J. Risk Factors and Diagnostic Model Construction of Chronic Pain with Cognitive Impairment. J Pain Res 2024; 17:4331-4342. [PMID: 39712461 PMCID: PMC11662672 DOI: 10.2147/jpr.s485000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2024] [Accepted: 12/06/2024] [Indexed: 12/24/2024] Open
Abstract
Background Cognitive impairment (CI) is frequently observed in patients with chronic pain (CP). CP progression increases the risk of dementia and accelerates Alzheimer's disease pathogenesis. However, risk diagnostic models and biomarkers for CP-related CI remain insufficient. Previous research has highlighted the relationships between several complete blood count parameters for CP or CI-related diseases, such as Alzheimer's disease, while the specific values of complete blood count parameters in CP-related CI patients remain unclear. This study aimed to explore the correlation between complete blood count parameters and CP-related CI to establish a risk diagnostic model for the early detection of CP-related CI. Methods This cross-sectional study was conducted at West China Hospital, Sichuan University. The Montreal Cognitive Assessment (MoCA) was used to classify patients into either the CP with CI group or the CP without CI group. Univariate analysis and multivariate logistic regression analysis were used to screen the related factors of CP-related CI for constructing a risk diagnostic model, and the model was evaluated using receiver operating characteristic (ROC) curve analysis. Results The study ultimately included 163 eligible patients. Based on analysis, age (OR, 1.037 [95% CI, 1.007-1.070]; P=0.018), duration of pain (OR, 2.546 [95% CI, 1.099-6.129]; P=0.032), VAS score (OR, 1.724 [95% CI, 0.819-3.672]; P=0.153), LMR (OR, 0.091 [95% CI, 0.024-0.275]; P<0.001), absolute neutrophil value (OR, 0.306 [95% CI, 0.115-0.767]; P=0.014), and lymphocyte percentage (OR, 6.551 [95% CI, 2.143-25.039]; P=0.002) were identified as critical factors of CP-related CI. The diagnostic model was evaluated by the ROC curve, demonstrating good diagnostic value with an area under the curve (AUC) of 0.803, a sensitivity of 0.603 and a specificity of 0.871. Conclusion The risk diagnostic model developed in this study for CP-related CI has significant value and enables clinicians to customize interventions based on each patient's needs.
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Affiliation(s)
- Changteng Zhang
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
- The Research Units of West China (2018RU012)-Chinese Academy of Medical Sciences, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Ying Su
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
- The Research Units of West China (2018RU012)-Chinese Academy of Medical Sciences, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Xianzheng Zeng
- Department of Pain Management, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Xiaoyu Zhu
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
- The Research Units of West China (2018RU012)-Chinese Academy of Medical Sciences, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Rui Gao
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
- The Research Units of West China (2018RU012)-Chinese Academy of Medical Sciences, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Wangyang Liu
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
- The Research Units of West China (2018RU012)-Chinese Academy of Medical Sciences, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Runzi Du
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
- The Research Units of West China (2018RU012)-Chinese Academy of Medical Sciences, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Chan Chen
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
- The Research Units of West China (2018RU012)-Chinese Academy of Medical Sciences, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Jin Liu
- Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
- The Research Units of West China (2018RU012)-Chinese Academy of Medical Sciences, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
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Park T, Hwang J, Liu S, Chaudhuri S, Han SW, Yi D, Byun MS, Huang YN, Rosewood T, Jung G, Kim MJ, Ahn H, Lee JY, Kim YK, Cho M, Bice PJ, Craft H, Risacher SL, Gao H, Liu Y, Kim S, Park YH, Lee DY, Saykin AJ, Nho K. Genome-wide transcriptome analysis of Aβ deposition on PET in a Korean cohort. Alzheimers Dement 2024; 20:8787-8801. [PMID: 39513963 DOI: 10.1002/alz.14348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2024] [Accepted: 09/19/2024] [Indexed: 11/16/2024]
Abstract
INTRODUCTION Despite the recognized importance of including ethnic diversity in Alzheimer's disease (AD) research, substantial knowledge gaps remain, particularly in Asian populations. METHODS RNA sequencing was performed on blood samples from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease (KBASE) to perform differential gene expression (DGE), gene co-expression network, gene-set enrichment, and machine learning analyses for amyloid beta (Aβ) deposition on positron emission tomography. RESULTS DGE analysis identified 265 dysregulated genes associated with Aβ deposition and replicated three AD-associated genes in an independent Korean cohort. Network analysis identified two modules related to pathways including a natural killer (NK) cell-mediated immunity. Machine learning analysis showed the classification of Aβ positivity improved with the inclusion of gene expression data. DISCUSSION Our results in a Korean population suggest Aβ deposition-associated genes are enriched in NK cell-mediated immunity, providing a better understanding of AD molecular mechanisms and yielding potential diagnostic and therapeutic strategies. HIGHLIGHTS Dysregulated genes were associated with amyloid beta (Aβ) deposition on positron emission tomography in a Korean cohort. Dysregulated genes in Alzheimer's disease were replicated in an independent Korean cohort. Gene network modules were associated with Aβ deposition. Natural killer (NK) cell proportion in blood was associated with Aβ deposition. Dysregulated genes were related to a NK cell-mediated immunity.
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Affiliation(s)
- Tamina Park
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Jiyun Hwang
- Genome and Health Big Data Laboratory Graduate School of Public Health, , Seoul National University, Seoul, South Korea
| | - Shiwei Liu
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Soumilee Chaudhuri
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Medical Neuroscience Graduate Program, Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Sang Won Han
- Department of Neurology, Chuncheon Sacred Heart Hospital, Hallym University College of Medicine, Chuncheon-si, South Korea
| | - Dahyun Yi
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, South Korea
| | - Min Soo Byun
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | - Yen-Ning Huang
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Thea Rosewood
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Gijung Jung
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
| | - Min Jeong Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
| | - Hyejin Ahn
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
| | - Jun-Young Lee
- Department of Psychiatry, Seoul National University Boramae Medical Center, Seoul, South Korea
| | - Yu Kyeong Kim
- Department of Psychiatry, Seoul National University Boramae Medical Center, Seoul, South Korea
| | - MinYoung Cho
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Paula J Bice
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Hannah Craft
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Shannon L Risacher
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Genome and Health Big Data Laboratory Graduate School of Public Health, , Seoul National University, Seoul, South Korea
| | - Hongyu Gao
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Center for Medical Genomics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Center for Medical Genomics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - SangYun Kim
- Department of Neurology, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seongnam-si, South Korea
| | - Young Ho Park
- Department of Neurology, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seongnam-si, South Korea
| | - Dong Young Lee
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | - Andrew J Saykin
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Genome and Health Big Data Laboratory Graduate School of Public Health, , Seoul National University, Seoul, South Korea
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Kwangsik Nho
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
- School of Informatics and Computing, Indiana University, Indianapolis, Indiana, USA
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Zhai Y, Li N, Zhang Y, Li H, Wu L, Wei C, Ji J, Zheng D. Identification of JAZF1, KNOP1, and PLEKHA1 as causally associated genes and drug targets for Alzheimer's disease: a summary data-based Mendelian randomization study. Inflammopharmacology 2024; 32:3913-3923. [PMID: 39455528 DOI: 10.1007/s10787-024-01583-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2024] [Accepted: 10/07/2024] [Indexed: 10/28/2024]
Abstract
BACKGROUND There is a growing body of evidence indicating the significant role of the immune system and immune cells in the progression of Alzheimer's disease (AD). However, the exact role of genes from various immune cell types in AD remains unclear. We aimed to utilize summary data-based Mendelian randomization (SMR) to explore the potential causal relationships between genes in specific immune cells and the risk of AD. METHODS By utilizing data sets of expression quantitative trait loci (eQTL) for 14 different immune cell types and large-scale AD genome-wide association study (GWAS), we employed SMR to identify key genes associated with AD within specific immune cells. Sensitivity analyses, including F-statistic, colocalization, and assessment of horizontal pleiotropy, were further conducted to validate the discovered genes. In addition, replication analyses were performed in AD GWAS from the FinnGen consortium. Finally, we further identified existing drugs that target or interact with the druggable genes and reviewed the studies about the associations between these drugs and AD. RESULTS SMR analysis revealed 342 genes associated with AD across 14 immune cell types. Further sensitivity analyses identified nine genes, CTSH, FCER1G, FNBP4, HLA-E, JAZF1, KNOP1, PLEKHA1, RP11-960L18.1, and ZNF638 that had significant associations with AD across nine specific immune cell types. JAZF1, KNOP1 and PLEKHA1 were replicated in an independent analysis using the GWAS data. The review on gene-related drugs also supported these findings. CONCLUSIONS Our research suggests that the expression of the genes JAZF1, KNOP1, and PLEKHA1 in specific immune cell types is related to the risk of AD.
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Affiliation(s)
- Yuhan Zhai
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Ning Li
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Yujie Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Haibin Li
- Department of Cardiac Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
- Heart Center and Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Lijuan Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Cuibai Wei
- Department of Neurology, Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, Beijing, China.
| | - Jianguang Ji
- Faculty of Health Science, University of Macau, Taipa, Macao SAR, China.
- Center for Primary Health Care Research, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden.
| | - Deqiang Zheng
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China.
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China.
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Tenchov R, Sasso JM, Zhou QA. Alzheimer's Disease: Exploring the Landscape of Cognitive Decline. ACS Chem Neurosci 2024; 15:3800-3827. [PMID: 39392435 PMCID: PMC11587518 DOI: 10.1021/acschemneuro.4c00339] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 09/26/2024] [Accepted: 10/04/2024] [Indexed: 10/12/2024] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory loss, and impaired daily functioning. The pathology of AD is marked by the accumulation of amyloid beta plaques and tau protein tangles in the brain, along with neuroinflammation and synaptic dysfunction. Genetic factors, such as mutations in APP, PSEN1, and PSEN2 genes, as well as the APOE ε4 allele, contribute to increased risk of acquiring AD. Currently available treatments provide symptomatic relief but do not halt disease progression. Research efforts are focused on developing disease-modifying therapies that target the underlying pathological mechanisms of AD. Advances in identification and validation of reliable biomarkers for AD hold great promise for enhancing early diagnosis, monitoring disease progression, and assessing treatment response in clinical practice in effort to alleviate the burden of this devastating disease. In this paper, we analyze data from the CAS Content Collection to summarize the research progress in Alzheimer's disease. We examine the publication landscape in effort to provide insights into current knowledge advances and developments. We also review the most discussed and emerging concepts and assess the strategies to combat the disease. We explore the genetic risk factors, pharmacological targets, and comorbid diseases. Finally, we inspect clinical applications of products against AD with their development pipelines and efforts for drug repurposing. The objective of this review is to provide a broad overview of the evolving landscape of current knowledge regarding AD, to outline challenges, and to evaluate growth opportunities to further efforts in combating the disease.
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Affiliation(s)
- Rumiana Tenchov
- CAS, a division of the American Chemical
Society, Columbus Ohio 43210, United States
| | - Janet M. Sasso
- CAS, a division of the American Chemical
Society, Columbus Ohio 43210, United States
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8
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Liu S, Zhang C, Zhang Y, Wu Z, Wu P, Tian S, Zhang M, Lang L, Li L, Wang R, Liu H, Zhang J, Mao X, Li S. Causal association between blood leukocyte counts and vascular dementia: a two-sample bidirectional Mendelian randomization study. Sci Rep 2024; 14:19582. [PMID: 39179767 PMCID: PMC11344047 DOI: 10.1038/s41598-024-70446-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 08/16/2024] [Indexed: 08/26/2024] Open
Abstract
While previous observational studies have suggested a link between leukocyte counts and vascular dementia (VD), the causal relationship between leukocyte counts and various subtypes of VD remains elusive. This study aimed to investigate the causal relationship between five types of leukocyte counts and VD, with the goal of improving prevention and treatment strategies. In this study, leukocyte counts were used as the exposure variable, with genome-wide association study (GWAS) data sourced from both the UK Biobank and the Blood Cell Consortium. Additionally, GWAS data for five subtypes of vascular dementia were obtained from the FinnGen database. We conducted rigorous statistical analysis and visualization using Mendelian randomization (MR) to elucidate the potential causal relationship between leukocyte counts and vascular dementia. This study, utilizing MR analysis with data from the UK Biobank and Blood Cell Consortium, identified significant causal associations between increased lymphocyte counts and VD. Specifically, lymphocyte counts were found to be causally related to multiple and mixed VD subtypes. Sensitivity analyses, including MR-Egger regression and MR-PRESSO tests, confirmed the robustness of these findings, with no evidence of reverse causality or significant horizontal pleiotropy detected. The results underscore a potential inflammatory or immunological mechanism in the pathogenesis of VD, highlighting lymphocytes as a key component in their etiology. This investigation establishes a robust association between elevated lymphocyte and leukocyte counts and an increased risk of VD, emphasizing the roles of inflammation, immune activation, and hematological factors in disease pathogenesis.
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Affiliation(s)
- Shufang Liu
- Department of Nuclear Medicine, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
- Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Chenwei Zhang
- NHC Key Laboratory of Pneumoconiosis, Shanxi Key Laboratory of Respiratory Diseases, Department of Pulmonary and Critical Care Medicine, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
- First Clinical Medical College, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Yukai Zhang
- NHC Key Laboratory of Pneumoconiosis, Shanxi Key Laboratory of Respiratory Diseases, Department of Pulmonary and Critical Care Medicine, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Zhifang Wu
- Department of Nuclear Medicine, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
- Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Ping Wu
- Department of Nuclear Medicine, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
- Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Shouyuan Tian
- Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China
| | - Min Zhang
- Department of Nuclear Medicine, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
- Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Limin Lang
- Department of Nuclear Medicine, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
- Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Li Li
- Department of Nuclear Medicine, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
- Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Ruonan Wang
- Department of Nuclear Medicine, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
- Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Shanxi Medical University, Taiyuan, Shanxi, China
| | | | - Jingfen Zhang
- First Clinical Medical College, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Xiaolu Mao
- Shengjing Hospital of China Medical University, Shenyang , Liaoning, China
| | - Sijin Li
- Department of Nuclear Medicine, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
- Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Shanxi Medical University, Taiyuan, Shanxi, China.
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9
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Sanchez-Rodriguez LM, Khan AF, Adewale Q, Bezgin G, Therriault J, Fernandez-Arias J, Servaes S, Rahmouni N, Tissot C, Stevenson J, Jiang H, Chai X, Carbonell F, Rosa-Neto P, Iturria-Medina Y. In-vivo neuronal dysfunction by Aβ and tau overlaps with brain-wide inflammatory mechanisms in Alzheimer's disease. Front Aging Neurosci 2024; 16:1383163. [PMID: 38966801 PMCID: PMC11223503 DOI: 10.3389/fnagi.2024.1383163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 05/09/2024] [Indexed: 07/06/2024] Open
Abstract
The molecular mechanisms underlying neuronal dysfunction in Alzheimer's disease (AD) remain uncharacterized. Here, we identify genes, molecular pathways and cellular components associated with whole-brain dysregulation caused by amyloid-beta (Aβ) and tau deposits in the living human brain. We obtained in-vivo resting-state functional MRI (rs-fMRI), Aβ- and tau-PET for 47 cognitively unimpaired and 16 AD participants from the Translational Biomarkers in Aging and Dementia cohort. Adverse neuronal activity impacts by Aβ and tau were quantified with personalized dynamical models by fitting pathology-mediated computational signals to the participant's real rs-fMRIs. Then, we detected robust brain-wide associations between the spatial profiles of Aβ-tau impacts and gene expression in the neurotypical transcriptome (Allen Human Brain Atlas). Within the obtained distinctive signature of in-vivo neuronal dysfunction, several genes have prominent roles in microglial activation and in interactions with Aβ and tau. Moreover, cellular vulnerability estimations revealed strong association of microglial expression patterns with Aβ and tau's synergistic impact on neuronal activity (q < 0.001). These results further support the central role of the immune system and neuroinflammatory pathways in AD pathogenesis. Neuronal dysregulation by AD pathologies also associated with neurotypical synaptic and developmental processes. In addition, we identified drug candidates from the vast LINCS library to halt or reduce the observed Aβ-tau effects on neuronal activity. Top-ranked pharmacological interventions target inflammatory, cancer and cardiovascular pathways, including specific medications undergoing clinical evaluation in AD. Our findings, based on the examination of molecular-pathological-functional interactions in humans, may accelerate the process of bringing effective therapies into clinical practice.
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Affiliation(s)
- Lazaro M. Sanchez-Rodriguez
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, QC, Canada
| | - Ahmed F. Khan
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, QC, Canada
| | - Quadri Adewale
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, QC, Canada
| | - Gleb Bezgin
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Joseph Therriault
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Jaime Fernandez-Arias
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Stijn Servaes
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Nesrine Rahmouni
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Cécile Tissot
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
- Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Jenna Stevenson
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Hongxiu Jiang
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
| | - Xiaoqian Chai
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
| | | | - Pedro Rosa-Neto
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Yasser Iturria-Medina
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, QC, Canada
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10
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Zuo CY, Hu Z, Hao XY, Li MJ, Shi JJ, Guo MN, Ma DR, Li SJ, Liang YY, Zhang C, Mao CY, Xu Y, Shi CH. The potential protective role of peripheral immunophenotypes in Alzheimer's disease: a Mendelian randomization study. Front Aging Neurosci 2024; 16:1403077. [PMID: 38903900 PMCID: PMC11188398 DOI: 10.3389/fnagi.2024.1403077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 05/17/2024] [Indexed: 06/22/2024] Open
Abstract
Introduction Alzheimer's disease (AD) is the most widespread neurodegenerative disease in the world. Previous studies have shown that peripheral immune dysregulation plays a paramount role in AD, but whether there is a protective causal relationship between peripheral immunophenotypes and AD risk remains ambiguous. Methods Two-sample Mendelian randomization (MR) was performed using large genome-wide association study (GWAS) genetic data to assess causal effects between peripheral immunophenotypes and AD risk. Utilizing the genetic associations of 731 immune cell traits as exposures. We adopted the inverse variance weighted method as the primary approach. The Weighted median and MR-Egger regression methods were employed as supplements. Various sensitivity analyses were performed to assess the robustness of the outcomes. Results Based on the IVW method, we identified 14 immune cell traits that significantly reduced the risk of AD, of which six demonstrated statistical significance in both IVW and Weighted median methods. Among the seven immune traits, four were related to regulatory T (Treg) cells : (1) CD25++ CD45RA- CD4 not regulatory T cell % T cell (odds ratio (OR) [95% confidence interval (CI)] = 0.96 [0.95, 0.98], adjusted P = 1.17E-02), (2) CD25++ CD45RA- CD4 not regulatory T cell % CD4+ T cell (OR [95% CI] = 0.97 [0.96, 0.99], adjusted P = 3.77E-02), (3) Secreting CD4 regulatory T cell % CD4 regulatory T cell (OR [95% CI] = 0.98 [0.97, 0.99], adjusted P = 7.10E-03), (4) Activated & secreting CD4 regulatory T cell % CD4 regulatory T cell(OR [95% CI] = 0.98 [0.97, 0.99], adjusted P = 7.10E-03). In addition, HLA DR++ monocyte % monocyte (OR [95% CI] = 0.93 [0.89, 0.98], adjusted P = 4.87E-02) was associated with monocytes, and HLA DR on myeloid Dendritic Cell (OR [95% CI] = 0.93 [0.89, 0.97], adjusted P = 1.17E-02) was related to dendritic cells (DCs). Conclusion These findings enhance the comprehension of the protective role of peripheral immunity in AD and provide further support for Treg and monocyte as potential targets for immunotherapy in AD.
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Affiliation(s)
- Chun-yan Zuo
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
| | - Zhengwei Hu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- Academy of Medical Sciences of Zhengzhou University, Zhengzhou, Henan, China
| | - Xiao-yan Hao
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- Academy of Medical Sciences of Zhengzhou University, Zhengzhou, Henan, China
| | - Meng-jie Li
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
| | - Jing-jing Shi
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
| | - Meng-nan Guo
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
| | - Dong-rui Ma
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
| | - Shuang-jie Li
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
| | - Yuan-yuan Liang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
| | - Chan Zhang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, Henan, China
| | - Cheng-yuan Mao
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, Henan, China
| | - Yuming Xu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, Henan, China
| | - Chang-he Shi
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, Henan, China
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11
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Guo S, Yang J. Bayesian genome-wide TWAS with reference transcriptomic data of brain and blood tissues identified 141 risk genes for Alzheimer's disease dementia. Alzheimers Res Ther 2024; 16:120. [PMID: 38824563 PMCID: PMC11144322 DOI: 10.1186/s13195-024-01488-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 05/27/2024] [Indexed: 06/03/2024]
Abstract
BACKGROUND Transcriptome-wide association study (TWAS) is an influential tool for identifying genes associated with complex diseases whose genetic effects are likely mediated through transcriptome. TWAS utilizes reference genetic and transcriptomic data to estimate effect sizes of genetic variants on gene expression (i.e., effect sizes of a broad sense of expression quantitative trait loci, eQTL). These estimated effect sizes are employed as variant weights in gene-based association tests, facilitating the mapping of risk genes with genome-wide association study (GWAS) data. However, most existing TWAS of Alzheimer's disease (AD) dementia are limited to studying only cis-eQTL proximal to the test gene. To overcome this limitation, we applied the Bayesian Genome-wide TWAS (BGW-TWAS) method to leveraging both cis- and trans- eQTL of brain and blood tissues, in order to enhance mapping risk genes for AD dementia. METHODS We first applied BGW-TWAS to the Genotype-Tissue Expression (GTEx) V8 dataset to estimate cis- and trans- eQTL effect sizes of the prefrontal cortex, cortex, and whole blood tissues. Estimated eQTL effect sizes were integrated with the summary data of the most recent GWAS of AD dementia to obtain BGW-TWAS (i.e., gene-based association test) p-values of AD dementia per gene per tissue type. Then we used the aggregated Cauchy association test to combine TWAS p-values across three tissues to obtain omnibus TWAS p-values per gene. RESULTS We identified 85 significant genes in prefrontal cortex, 82 in cortex, and 76 in whole blood that were significantly associated with AD dementia. By combining BGW-TWAS p-values across these three tissues, we obtained 141 significant risk genes including 34 genes primarily due to trans-eQTL and 35 mapped risk genes in GWAS Catalog. With these 141 significant risk genes, we detected functional clusters comprised of both known mapped GWAS risk genes of AD in GWAS Catalog and our identified TWAS risk genes by protein-protein interaction network analysis, as well as several enriched phenotypes related to AD. CONCLUSION We applied BGW-TWAS and aggregated Cauchy test methods to integrate both cis- and trans- eQTL data of brain and blood tissues with GWAS summary data, identifying 141 TWAS risk genes of AD dementia. These identified risk genes provide novel insights into the underlying biological mechanisms of AD dementia and potential gene targets for therapeutics development.
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Affiliation(s)
- Shuyi Guo
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
- Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Jingjing Yang
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA.
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12
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Li C, Stebbins RC, Noppert GA, Carney CX, Liu C, Sapp ARM, Watson EJ, Aiello AE. Peripheral immune function and Alzheimer's disease: a living systematic review and critical appraisal. Mol Psychiatry 2024; 29:1895-1905. [PMID: 38102484 PMCID: PMC11483233 DOI: 10.1038/s41380-023-02355-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 11/21/2023] [Accepted: 11/27/2023] [Indexed: 12/17/2023]
Abstract
BACKGROUND A growing body of literature examines the relationship between peripheral immune function and Alzheimer's Disease (AD) in human populations. Our living systematic review summarizes the characteristics and findings of these studies, appraises their quality, and formulates recommendations for future research. METHODS We searched the electronic databases PubMed, PsycINFO, and Web of Science, and reviewed references of previous reviews and meta-analyses to identify human studies examining the relationship between any peripheral immune biomarkers and AD up to September 7th, 2023. We examined patterns of reported statistical associations (positive, negative, and null) between each biomarker and AD across studies. Evidence for each biomarker was categorized into four groups based on the proportion of studies reporting different associations: corroborating a positive association with AD, a negative association, a null association, and presenting contradictory findings. A modified Newcastle-Ottawa scale (NOS) was employed to assess the quality of the included studies. FINDINGS In total, 286 studies were included in this review. The majority were cross-sectional (n = 245, 85.7%) and hospital-based (n = 248, 86.7%), examining relationships between 187 different peripheral immune biomarkers and AD. Cytokines were the most frequently studied group of peripheral immune biomarkers. Evidence supported a positive association with AD for six biomarkers, including IL-6, IL-1β, IFN-γ, ACT, IL-18, and IL-12, and a negative association for two biomarkers, including lymphocytes and IL-6R. Only a small proportion of included studies (n = 22, 7.7%) were deemed to be of high quality based on quality assessment. INTERPRETATION Existing research on peripheral immune function and AD exhibits substantial methodological variations and limitations, with a notable lack of longitudinal, population-based studies investigating a broad range of biomarkers with prospective AD outcomes. The extent and manner in which peripheral immune function can contribute to AD pathophysiology remain open questions. Given the biomarkers that we identified to be associated with AD, we posit that targeting peripheral immune dysregulation may present a promising intervention point to reduce the burden of AD.
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Affiliation(s)
- Chihua Li
- Social Environment and Health Program, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA.
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
- Department of Epidemiology, School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
| | - Rebecca C Stebbins
- Robert N. Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York City, NY, USA
| | - Grace A Noppert
- Social Environment and Health Program, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Constanza X Carney
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Chunyu Liu
- Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Ashley R M Sapp
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Elijah J Watson
- Department of Anthropology, Northwestern University, Evanston, IL, USA
| | - Allison E Aiello
- Robert N. Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York City, NY, USA
- Department of Epidemiology, Mailman School of Public, Columbia University, New York City, NY, USA
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13
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Noordam R, Ao L, Stroo JF, Willems van Dijk K, van Heemst D. No evidence linking sleep traits with white blood cell counts: Multivariable-adjusted and Mendelian randomization analyses. Eur J Clin Invest 2024; 54:e14189. [PMID: 38429948 DOI: 10.1111/eci.14189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 02/12/2024] [Accepted: 02/22/2024] [Indexed: 03/03/2024]
Abstract
BACKGROUND Disturbances in habitual sleep have been associated with multiple age-associated diseases. However, the biological mechanisms underpinning these associations remain largely unclear. We assessed the possible involvement of the circulating immune system by determining the associations between sleep traits and white blood cell counts using multivariable-adjusted linear regression and Mendelian randomization. METHODS Cross-sectional multivariable-adjusted linear regression analyses were done using participants within the normal range of total white blood cell counts (>4.5 × 109 and <11.0 × 109/μL) from UK Biobank. For the sleep traits, we examined (short and long) sleep duration, chronotype, insomnia symptoms and daytime dozing. Two-sample Mendelian randomization analyses were done using instruments for sleep traits derived from European-ancestry participants from UK Biobank (over 410,000 participants) and using SNP-outcome data derived from European-ancestry participants from the Blood Cell Consortium (N = 563,946) to which no data from UK Biobank contributed. RESULTS Using data from 357,656 participants (mean [standard deviation] age: 56.5 [8.1] years, and 44.4% men), we did not find evidence that disturbances in any of the studied sleep traits were associated with differences in blood cell counts (total, lymphocytes, neutrophiles, eosinophiles and basophiles). Also, we did not find associations between disturbances in any of the studied sleep traits and white blood cell counts using Mendelian Randomization. CONCLUSION Based on the results from two different methodologies, disturbances in habitual sleep are unlikely to cause changes in blood cell counts and thereby differences in blood cell counts are unlikely to be underlying the observed sleep-disease associations.
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Affiliation(s)
- Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Linjun Ao
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Jasmijn F Stroo
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
- Division of Endocrinology, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
- Leiden Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Diana van Heemst
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
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14
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Jacobs T, Jacobson SR, Fortea J, Berger JS, Vedvyas A, Marsh K, He T, Gutierrez-Jimenez E, Fillmore NR, Gonzalez M, Figueredo L, Gaggi NL, Plaska CR, Pomara N, Blessing E, Betensky R, Rusinek H, Zetterberg H, Blennow K, Glodzik L, Wisniweski TM, de Leon MJ, Osorio RS, Ramos-Cejudo J. The neutrophil to lymphocyte ratio associates with markers of Alzheimer's disease pathology in cognitively unimpaired elderly people. Immun Ageing 2024; 21:32. [PMID: 38760856 PMCID: PMC11100119 DOI: 10.1186/s12979-024-00435-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 04/29/2024] [Indexed: 05/19/2024]
Abstract
BACKGROUND An elevated neutrophil-lymphocyte ratio (NLR) in blood has been associated with Alzheimer's disease (AD). However, an elevated NLR has also been implicated in many other conditions that are risk factors for AD, prompting investigation into whether the NLR is directly linked with AD pathology or a result of underlying comorbidities. Herein, we explored the relationship between the NLR and AD biomarkers in the cerebrospinal fluid (CSF) of cognitively unimpaired (CU) subjects. Adjusting for sociodemographics, APOE4, and common comorbidities, we investigated these associations in two cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the M.J. de Leon CSF repository at NYU. Specifically, we examined associations between the NLR and cross-sectional measures of amyloid-β42 (Aβ42), total tau (t-tau), and phosphorylated tau181 (p-tau), as well as the trajectories of these CSF measures obtained longitudinally. RESULTS A total of 111 ADNI and 190 NYU participants classified as CU with available NLR, CSF, and covariate data were included. Compared to NYU, ADNI participants were older (73.79 vs. 61.53, p < 0.001), had a higher proportion of males (49.5% vs. 36.8%, p = 0.042), higher BMIs (27.94 vs. 25.79, p < 0.001), higher prevalence of hypertensive history (47.7% vs. 16.3%, p < 0.001), and a greater percentage of Aβ-positivity (34.2% vs. 20.0%, p = 0.009). In the ADNI cohort, we found cross-sectional associations between the NLR and CSF Aβ42 (β = -12.193, p = 0.021), but not t-tau or p-tau. In the NYU cohort, we found cross-sectional associations between the NLR and CSF t-tau (β = 26.812, p = 0.019) and p-tau (β = 3.441, p = 0.015), but not Aβ42. In the NYU cohort alone, subjects classified as Aβ + (n = 38) displayed a stronger association between the NLR and t-tau (β = 100.476, p = 0.037) compared to Aβ- subjects or the non-stratified cohort. In both cohorts, the same associations observed in the cross-sectional analyses were observed after incorporating longitudinal CSF data. CONCLUSIONS We report associations between the NLR and Aβ42 in the older ADNI cohort, and between the NLR and t-tau and p-tau in the younger NYU cohort. Associations persisted after adjusting for comorbidities, suggesting a direct link between the NLR and AD. However, changes in associations between the NLR and specific AD biomarkers may occur as part of immunosenescence.
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Affiliation(s)
- Tovia Jacobs
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, Division of Brain Aging, 145 East 32Nd Street, New York, NY, 10016, USA
| | - Sean R Jacobson
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, Division of Brain Aging, 145 East 32Nd Street, New York, NY, 10016, USA
- VA Boston Cooperative Studies Program, MAVERIC, VA Boston Healthcare System, Boston, MA, USA
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Hospital de La Santa Creu y Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Jeffrey S Berger
- Divisions of Cardiology and Hematology, Department of Medicine, New York University (NYU) Grossman School of Medicine, New York, NY, USA
| | - Alok Vedvyas
- Department of Neurology, New York University (NYU) Grossman School of Medicine, New York, NY, USA
| | - Karyn Marsh
- Department of Neurology, New York University (NYU) Grossman School of Medicine, New York, NY, USA
| | - Tianshe He
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, Division of Brain Aging, 145 East 32Nd Street, New York, NY, 10016, USA
| | | | - Nathanael R Fillmore
- VA Boston Cooperative Studies Program, MAVERIC, VA Boston Healthcare System, Boston, MA, USA
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Moses Gonzalez
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, Division of Brain Aging, 145 East 32Nd Street, New York, NY, 10016, USA
| | - Luisa Figueredo
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, Division of Brain Aging, 145 East 32Nd Street, New York, NY, 10016, USA
| | - Naomi L Gaggi
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, Division of Brain Aging, 145 East 32Nd Street, New York, NY, 10016, USA
| | - Chelsea Reichert Plaska
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, Division of Brain Aging, 145 East 32Nd Street, New York, NY, 10016, USA
- Nathan Kline Institute, 140 Old Orangeburg Rd, Orangeburg, NY, 10962, USA
| | - Nunzio Pomara
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, Division of Brain Aging, 145 East 32Nd Street, New York, NY, 10016, USA
- Nathan Kline Institute, 140 Old Orangeburg Rd, Orangeburg, NY, 10962, USA
- Department of Pathology, New York University (NYU) Grossman School of Medicine, New York, NY, USA
| | - Esther Blessing
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, Division of Brain Aging, 145 East 32Nd Street, New York, NY, 10016, USA
| | - Rebecca Betensky
- Department of Neurology, New York University (NYU) Grossman School of Medicine, New York, NY, USA
| | - Henry Rusinek
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, Division of Brain Aging, 145 East 32Nd Street, New York, NY, 10016, USA
- Department of Radiology, New York University (NYU) Grossman School of Medicine, New York, NY, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Inst. of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Lab, Sahlgrenska University Hospital, Mölndal, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute On Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, People's Republic of China
| | - Lidia Glodzik
- Department of Neurology, New York University (NYU) Grossman School of Medicine, New York, NY, USA
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Thomas M Wisniweski
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, Division of Brain Aging, 145 East 32Nd Street, New York, NY, 10016, USA
- Department of Neurology, New York University (NYU) Grossman School of Medicine, New York, NY, USA
- Department of Pathology, New York University (NYU) Grossman School of Medicine, New York, NY, USA
| | - Mony J de Leon
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, USA
- Retired director of Center for Brain Health, New York University (NYU) Grossman School of Medicine, New York, NY, USA
| | - Ricardo S Osorio
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, Division of Brain Aging, 145 East 32Nd Street, New York, NY, 10016, USA.
- Nathan Kline Institute, 140 Old Orangeburg Rd, Orangeburg, NY, 10962, USA.
| | - Jaime Ramos-Cejudo
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, Division of Brain Aging, 145 East 32Nd Street, New York, NY, 10016, USA.
- VA Boston Cooperative Studies Program, MAVERIC, VA Boston Healthcare System, Boston, MA, USA.
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15
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Jacobs T, Jacobson SR, Fortea J, Berger JS, Vedvyas A, Marsh K, He T, Gutierrez-Jimenez E, Fillmore NR, Bubu OM, Gonzalez M, Figueredo L, Gaggi NL, Plaska CR, Pomara N, Blessing E, Betensky R, Rusinek H, Zetterberg H, Blennow K, Glodzik L, Wisniewski TM, Leon MJ, Osorio RS, Ramos-Cejudo J. The neutrophil to lymphocyte ratio associates with markers of Alzheimer's disease pathology in cognitively unimpaired elderly people. RESEARCH SQUARE 2024:rs.3.rs-4076789. [PMID: 38559231 PMCID: PMC10980096 DOI: 10.21203/rs.3.rs-4076789/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Background An elevated neutrophil-lymphocyte ratio (NLR) in blood has been associated with Alzheimer's disease (AD). However, an elevated NLR has also been implicated in many other conditions that are risk factors for AD, prompting investigation into whether the NLR is directly linked with AD pathology or a result of underlying comorbidities. Herein, we explored the relationship between the NLR and AD biomarkers in the cerebrospinal fluid (CSF) of cognitively unimpaired (CU) subjects. Adjusting for sociodemographics, APOE4, and common comorbidities, we investigated these associations in two cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the M.J. de Leon CSF repository at NYU. Specifically, we examined associations between the NLR and cross-sectional measures of amyloid-β42 (Aβ42), total tau (t-tau), and phosphorylated tau181 (p-tau), as well as the trajectories of these CSF measures obtained longitudinally. Results A total of 111 ADNI and 190 NYU participants classified as CU with available NLR, CSF, and covariate data were included. Compared to NYU, ADNI participants were older (73.79 vs. 61.53, p < 0.001), had a higher proportion of males (49.5% vs. 36.8%, p = 0.042), higher BMIs (27.94 vs. 25.79, p < 0.001), higher prevalence of hypertensive history (47.7% vs. 16.3%, p < 0.001), and a greater percentage of Aβ-positivity (34.2% vs. 20.0%, p = 0.009). In the ADNI cohort, we found cross-sectional associations between the NLR and CSF Aβ42 (β=-12.193, p = 0.021), but not t-tau or p-tau. In the NYU cohort, we found cross-sectional associations between the NLR and CSF t-tau (β = 26.812, p = 0.019) and p-tau (β = 3.441, p = 0.015), but not Aβ42. In the NYU cohort alone, subjects classified as Aβ+ (n = 38) displayed a stronger association between the NLR and t-tau (β = 100.476, p = 0.037) compared to Aβ- subjects or the non-stratified cohort. In both cohorts, the same associations observed in the cross-sectional analyses were observed after incorporating longitudinal CSF data. Conclusions We report associations between the NLR and Aβ42 in the older ADNI cohort, and between the NLR and t-tau and p-tau181 in the younger NYU cohort. Associations persisted after adjusting for comorbidities, suggesting a direct link between the NLR and AD. However, changes in associations between the NLR and specific AD biomarkers may occur as part of immunosenescence.
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Affiliation(s)
- Tovia Jacobs
- New York University (NYU) Grossman School of Medicine
| | | | - Juan Fortea
- Hospital de la Santa Creu y Sant Pau, Universitat Autònoma de Barcelona
| | | | - Alok Vedvyas
- New York University (NYU) Grossman School of Medicine
| | - Karyn Marsh
- New York University (NYU) Grossman School of Medicine
| | - Tianshe He
- New York University (NYU) Grossman School of Medicine
| | | | | | | | | | | | - Naomi L Gaggi
- New York University (NYU) Grossman School of Medicine
| | | | - Nunzio Pomara
- New York University (NYU) Grossman School of Medicine
| | | | | | - Henry Rusinek
- New York University (NYU) Grossman School of Medicine
| | | | | | | | | | - Mony J Leon
- New York University (NYU) Grossman School of Medicine
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Juul-Madsen K, Parbo P, Ismail R, Ovesen PL, Schmidt V, Madsen LS, Thyrsted J, Gierl S, Breum M, Larsen A, Andersen MN, Romero-Ramos M, Holm CK, Andersen GR, Zhao H, Schuck P, Nygaard JV, Sutherland DS, Eskildsen SF, Willnow TE, Brooks DJ, Vorup-Jensen T. Amyloid-β aggregates activate peripheral monocytes in mild cognitive impairment. Nat Commun 2024; 15:1224. [PMID: 38336934 PMCID: PMC10858199 DOI: 10.1038/s41467-024-45627-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 01/31/2024] [Indexed: 02/12/2024] Open
Abstract
The peripheral immune system is important in neurodegenerative diseases, both in protecting and inflaming the brain, but the underlying mechanisms remain elusive. Alzheimer's Disease is commonly preceded by a prodromal period. Here, we report the presence of large Aβ aggregates in plasma from patients with mild cognitive impairment (n = 38). The aggregates are associated with low level Alzheimer's Disease-like brain pathology as observed by 11C-PiB PET and 18F-FTP PET and lowered CD18-rich monocytes. We characterize complement receptor 4 as a strong binder of amyloids and show Aβ aggregates are preferentially phagocytosed and stimulate lysosomal activity through this receptor in stem cell-derived microglia. KIM127 integrin activation in monocytes promotes size selective phagocytosis of Aβ. Hydrodynamic calculations suggest Aβ aggregates associate with vessel walls of the cortical capillaries. In turn, we hypothesize aggregates may provide an adhesion substrate for recruiting CD18-rich monocytes into the cortex. Our results support a role for complement receptor 4 in regulating amyloid homeostasis.
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Affiliation(s)
- Kristian Juul-Madsen
- Department of Biomedicine, Aarhus University, The Skou Building, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark
- Max-Delbrueck-Center for Molecular Medicine, Robert-Rössle-Str. 10, 13125, Berlin, Germany
| | - Peter Parbo
- Department of Nuclear Medicine, Odense University Hospital, J. B. Winsløws Vej 4, DK-5000, Odense C, Denmark
| | - Rola Ismail
- Department of Nuclear medicine and PET, Vejle Hospital, Beriderbakken 4, DK-7100, Vejle, Denmark
| | - Peter L Ovesen
- Max-Delbrueck-Center for Molecular Medicine, Robert-Rössle-Str. 10, 13125, Berlin, Germany
| | - Vanessa Schmidt
- Max-Delbrueck-Center for Molecular Medicine, Robert-Rössle-Str. 10, 13125, Berlin, Germany
| | - Lasse S Madsen
- Department of Nuclear Medicine & PET Centre, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, DK-8200, Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 11, DK-8200, Aarhus N, Denmark
- Center of Functionally Integrative Neuroscience, Aarhus University and Aarhus University Hospital, Building 1710, Universitetsbyen 3, DK-8200, Aarhus C, Denmark
| | - Jacob Thyrsted
- Department of Biomedicine, Aarhus University, The Skou Building, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark
| | - Sarah Gierl
- Department of Biomedicine, Aarhus University, The Skou Building, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark
| | - Mihaela Breum
- Department of Biomedicine, Aarhus University, The Skou Building, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark
| | - Agnete Larsen
- Department of Biomedicine, Aarhus University, The Skou Building, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark
| | - Morten N Andersen
- Department of Biomedicine, Aarhus University, The Skou Building, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark
- Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 11, DK-8200, Aarhus N, Denmark
- Department of Hematology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, DK-8200, Aarhus N, Denmark
| | - Marina Romero-Ramos
- Department of Biomedicine, Aarhus University, The Skou Building, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark
- NEURODIN AU IDEAS Center, Department of Biomedicine, Aarhus University, The Skou Building, Høegh-Guldbergs Gade 10, DK-8200, Aarhus C, Denmark
| | - Christian K Holm
- Department of Biomedicine, Aarhus University, The Skou Building, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark
| | - Gregers R Andersen
- Department of Molecular Biology and Genetics, Aarhus University, Universitetsbyen 81, DK-8000, Aarhus C, Denmark
| | - Huaying Zhao
- Laboratory of Dynamics and Macromolecular Assembly, National Institute of Biomedical Imaging and Bioengineering, Building 31, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Peter Schuck
- Laboratory of Dynamics and Macromolecular Assembly, National Institute of Biomedical Imaging and Bioengineering, Building 31, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Jens V Nygaard
- Department of Biological and Chemical Engineering, Aarhus University, Gustav Wieds vej 10 D, DK-8200, Aarhus C, Denmark
| | - Duncan S Sutherland
- Interdisiciplinary Nanoscience Center, Aarhus University, The iNANO House, Gustav Wieds Vej 14, DK-8200, Aarhus C, Denmark
- Center for Cellular Signal Patterns, Aarhus University, The iNANO House, Gustav Wieds Vej 14, DK-8200, Aarhus C, Denmark
| | - Simon F Eskildsen
- Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 11, DK-8200, Aarhus N, Denmark
- Center of Functionally Integrative Neuroscience, Aarhus University and Aarhus University Hospital, Building 1710, Universitetsbyen 3, DK-8200, Aarhus C, Denmark
| | - Thomas E Willnow
- Department of Biomedicine, Aarhus University, The Skou Building, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark
- Max-Delbrueck-Center for Molecular Medicine, Robert-Rössle-Str. 10, 13125, Berlin, Germany
| | - David J Brooks
- Department of Nuclear Medicine & PET Centre, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, DK-8200, Aarhus N, Denmark
- Department of Brain Sciences, Imperial College London, Burlington Danes, The Hammersmith Hospital, Du Cane Road, London, W12 0NN, UK
- Institute of Translational and Clinical Research, University of Newcastle, Framlington Place, Newcastle upon Tyne, NE2 4HH, UK
| | - Thomas Vorup-Jensen
- Department of Biomedicine, Aarhus University, The Skou Building, Høegh-Guldbergs Gade 10, DK-8000, Aarhus C, Denmark.
- NEURODIN AU IDEAS Center, Department of Biomedicine, Aarhus University, The Skou Building, Høegh-Guldbergs Gade 10, DK-8200, Aarhus C, Denmark.
- Interdisiciplinary Nanoscience Center, Aarhus University, The iNANO House, Gustav Wieds Vej 14, DK-8200, Aarhus C, Denmark.
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17
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Khan MA, Khan ZA, Shoeb F, Fatima G, Khan RH, Khan MM. Role of de novo lipogenesis in inflammation and insulin resistance in Alzheimer's disease. Int J Biol Macromol 2023; 242:124859. [PMID: 37187418 DOI: 10.1016/j.ijbiomac.2023.124859] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 05/04/2023] [Accepted: 05/10/2023] [Indexed: 05/17/2023]
Abstract
Patients with Alzheimer's disease (AD) display both peripheral tissue and brain insulin resistance, the later could be a potential risk factor for cognitive dysfunction. While certain degree of inflammation is required for inducing insulin resistance, underlying mechanism(s) remains unclear. Evidence from diverse research domains suggest that elevated intracellular fatty acids of de novo pathway can induce insulin resistance even without triggering inflammation; however, the effect of saturated fatty acids (SFAs) could be detrimental due the development of proinflammatory cues. In this context, evidence suggest that while lipid/fatty acid accumulation is a characteristic feature of brain pathology in AD, dysregulated de novo lipogenesis could be a potential source for lipid/fatty acid accumulation. Therefore, therapies aimed at regulating de novo lipogenesis could be effective in improving insulin sensitivity and cognitive function in patients with AD.
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Affiliation(s)
- Mohsin Ali Khan
- Research and Development Unit, Era's Lucknow Medical College and Hospital, Faculty of Medicine, Era University, Lucknow, UP, India
| | - Zaw Ali Khan
- Research and Development Unit, Era's Lucknow Medical College and Hospital, Faculty of Medicine, Era University, Lucknow, UP, India
| | - Fouzia Shoeb
- Department of Personalized and Molecular Medicine, Faculty of Medicine, Era University, Lucknow, UP, India
| | - Ghizal Fatima
- Laboratory of Chronobiology, Department of Biotechnology, Faculty of Medicine, Era University, Lucknow, UP, India
| | - Rizwan Hasan Khan
- Interdisciplinary Biotechnology Unit, Faculty of Life sciences, Aligarh Muslim University, Aligarh, UP, India
| | - Mohammad M Khan
- Laboratory of Chronobiology, Department of Biotechnology, Faculty of Medicine, Era University, Lucknow, UP, India; Laboratory of Translational Neurology and Molecular Psychiatry, Era's Lucknow Medical College and Hospital, Department of Biotechnology, Faculty of Science, Era University, Sarfarazganj, Lucknow, UP, India.
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