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Reive BS, Lau V, Sánchez-Lafuente CL, Henri-Bhargava A, Kalynchuk LE, Tremblay MÈ, Caruncho HJ. The Inflammation-Induced Dysregulation of Reelin Homeostasis Hypothesis of Alzheimer's Disease. J Alzheimers Dis 2024:JAD240088. [PMID: 38995785 DOI: 10.3233/jad-240088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/14/2024]
Abstract
Alzheimer's disease (AD) accounts for most dementia cases, but we lack a complete understanding of the mechanisms responsible for the core pathology associated with the disease (e.g., amyloid plaque and neurofibrillary tangles). Inflammation has been identified as a key contributor of AD pathology, with recent evidence pointing towards Reelin dysregulation as being associated with inflammation. Here we describe Reelin signaling and outline existing research involving Reelin signaling in AD and inflammation. Research is described pertaining to the inflammatory and immunological functions of Reelin before we propose a mechanism through which inflammation renders Reelin susceptible to dysregulation resulting in the induction and exacerbation of AD pathology. Based on this hypothesis, it is predicted that disorders of both inflammation (including peripheral inflammation and neuroinflammation) and Reelin dysregulation (including disorders associated with upregulated Reelin expression and disorders of Reelin downregulation) have elevated risk of developing AD. We conclude with a description of AD risk in various disorders involving Reelin dysregulation and inflammation.
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Affiliation(s)
- Brady S Reive
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| | - Victor Lau
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| | | | - Alexandre Henri-Bhargava
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Vancouver Island Health Authority, Victoria, BC, Canada
- Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Lisa E Kalynchuk
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| | - Marie-Ève Tremblay
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Mental Health Research Cluster, University of Victoria, Victoria, BC, Canada
| | - Hector J Caruncho
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Mental Health Research Cluster, University of Victoria, Victoria, BC, Canada
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Mechanisms Involved in Epileptogenesis in Alzheimer's Disease and Their Therapeutic Implications. Int J Mol Sci 2022; 23:ijms23084307. [PMID: 35457126 PMCID: PMC9030029 DOI: 10.3390/ijms23084307] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Revised: 04/09/2022] [Accepted: 04/11/2022] [Indexed: 12/22/2022] Open
Abstract
Epilepsy and Alzheimer's disease (AD) incidence increases with age. There are reciprocal relationships between epilepsy and AD. Epilepsy is a risk factor for AD and, in turn, AD is an independent risk factor for developing epilepsy in old age, and abnormal AD biomarkers in PET and/or CSF are frequently found in late-onset epilepsies of unknown etiology. Accordingly, epilepsy and AD share pathophysiological processes, including neuronal hyperexcitability and an early excitatory-inhibitory dysregulation, leading to dysfunction in the inhibitory GABAergic and excitatory glutamatergic systems. Moreover, both β-amyloid and tau protein aggregates, the anatomopathological hallmarks of AD, have proepileptic effects. Finally, these aggregates have been found in the resection material of refractory temporal lobe epilepsies, suggesting that epilepsy leads to amyloid and tau aggregates. Some epileptic syndromes, such as medial temporal lobe epilepsy, share structural and functional neuroimaging findings with AD, leading to overlapping symptomatology, such as episodic memory deficits and toxic synergistic effects. In this respect, the existence of epileptiform activity and electroclinical seizures in AD appears to accelerate the progression of cognitive decline, and the presence of cognitive decline is much more prevalent in epileptic patients than in elderly patients without epilepsy. Notwithstanding their clinical significance, the diagnosis of clinical seizures in AD is a challenge. Most are focal and manifest with an altered level of consciousness without motor symptoms, and are often interpreted as cognitive fluctuations. Finally, despite the frequent association of epilepsy and AD dementia, there is a lack of clinical trials to guide the use of antiseizure medications (ASMs). There is also a potential role for ASMs to be used as disease-modifying drugs in AD.
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Beyond Seizure Control: Treating Comorbidities in Epilepsy via Targeting of the P2X7 Receptor. Int J Mol Sci 2022; 23:ijms23042380. [PMID: 35216493 PMCID: PMC8875404 DOI: 10.3390/ijms23042380] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 02/17/2022] [Accepted: 02/18/2022] [Indexed: 12/17/2022] Open
Abstract
Epilepsy is one of the most common chronic diseases of the central nervous system (CNS). Treatment of epilepsy remains, however, a clinical challenge with over 30% of patients not responding to current pharmacological interventions. Complicating management of treatment, epilepsy comes with multiple comorbidities, thereby further reducing the quality of life of patients. Increasing evidence suggests purinergic signalling via extracellularly released ATP as shared pathological mechanisms across numerous brain diseases. Once released, ATP activates specific purinergic receptors, including the ionotropic P2X7 receptor (P2X7R). Among brain diseases, the P2X7R has attracted particular attention as a therapeutic target. The P2X7R is an important driver of inflammation, and its activation requires high levels of extracellular ATP to be reached under pathological conditions. Suggesting the therapeutic potential of drugs targeting the P2X7R for epilepsy, P2X7R expression increases following status epilepticus and during epilepsy, and P2X7R antagonism modulates seizure severity and epilepsy development. P2X7R antagonism has, however, also been shown to be effective in treating conditions most commonly associated with epilepsy such as psychiatric disorders and cognitive deficits, which suggests that P2X7R antagonisms may provide benefits beyond seizure control. This review summarizes the evidence suggesting drugs targeting the P2X7R as a novel treatment strategy for epilepsy with a particular focus of its potential impact on epilepsy-associated comorbidities.
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Abstract
Non-convulsive seizures (NCSs) are highly treatable, but appropriate
management is usually delayed because of inaccurate diagnoses as a
result of variable clinical presentations, including an altered mental
state. It is difficult to detect NCSs in patients with dementia. We
report a case of NCS superimposed on cognitive decline caused by
Alzheimer’s dementia. The patient’s history was carefully recorded. An
electroencephalogram was recorded with sphenoidal electrodes, which
showed epileptiform discharges in the right mesial temporal lobe and
focal, sharply contoured, slow wave activity in the left
fronto-temporal area, suggesting an epileptic origin contributing to
the patient’s cognitive decline. After treatment with antiepileptic
drugs, the patient’s cognitive functioning gradually improved. An
accurate diagnosis of NCS relies on performing a detailed inventory of
a patient’s history, thorough physical and neurological examinations,
and electroencephalogram recordings. In patients with cognitive
decline, testing for NCS should always be included in the differential
diagnosis of cognitive impairment, even in the case of dementia. Early
administration of antiepileptic drug therapy is the mainstay treatment
for reversing the condition and for preventing prolonged insults from
neurological sequelae.
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Affiliation(s)
- Yu-Shiue Chen
- Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Tsang-Shan Chen
- Department of Neurology, 71587Tainan Sin-Lau Hospital, Tainan Sin-Lau Hospital, Tainan, Taiwan
| | - Chin-Wei Huang
- Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
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Werber T, Bata Z, Vaszine ES, Berente DB, Kamondi A, Horvath AA. The Association of Periodontitis and Alzheimer's Disease: How to Hit Two Birds with One Stone. J Alzheimers Dis 2021; 84:1-21. [PMID: 34511500 DOI: 10.3233/jad-210491] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Alzheimer's disease (AD) is the leading cause of cognitive impairment in the elderly. Recent evidence suggests that preventive interventional trials could significantly reduce the risk for development of dementia. Periodontitis is the most common dental disease characterized by chronic inflammation and loss of alveolar bone and perialveolar attachment of teeth. Growing number of studies propose a potential link between periodontitis and neurodegeneration. In the first part of the paper, we overview case-control studies analyzing the prevalence of periodontitis among AD patients and healthy controls. Second, we survey observational libraries and cross-sectional studies investigating the risk of cognitive decline in patients with periodontitis. Next, we describe the current view on the mechanism of periodontitis linked neural damage, highlighting bacterial invasion of neural tissue from dental plaques, and periodontitis induced systemic inflammation resulting in a neuroinflammatory process. Later, we summarize reports connecting the four most common periodontal pathogens to AD pathology. Finally, we provide a practical guide for further prevalence and interventional studies on the management of cognitively high-risk patients with and without periodontitis. In this section, we highlight strategies for risk control, patient information, dental evaluation, reporting protocol and dental procedures in the clinical management of patients with a risk for periodontitis and with diagnosed periodontitis. In conclusion, our review summarizes the current view on the association between AD and periodontitis and provides a research and intervention strategy for harmonized interventional trials and for further case-control or cross-sectional studies.
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Affiliation(s)
- Tom Werber
- Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Zsofia Bata
- Department of Conservative Dentistry, Semmelweis University, Budapest, Hungary
| | - Eniko Szabo Vaszine
- Department of Conservative Dentistry, Semmelweis University, Budapest, Hungary
| | - Dalida Borbala Berente
- Faculty of Medicine, Semmelweis University, Budapest, Hungary.,Neurocognitive Research Center, National Institute of Mental Health, Neurology and Neurosurgery, Budapest, Hungary
| | - Anita Kamondi
- Neurocognitive Research Center, National Institute of Mental Health, Neurology and Neurosurgery, Budapest, Hungary.,Department of Neurology, Semmelweis University, Budapest, Hungary
| | - Andras Attila Horvath
- Neurocognitive Research Center, National Institute of Mental Health, Neurology and Neurosurgery, Budapest, Hungary.,Department of Anatomy, Histology and Embryology, Semmelweis University, Budapest, Hungary
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Liu Y, Li Z, Ge Q, Lin N, Xiong M. Deep Feature Selection and Causal Analysis of Alzheimer's Disease. Front Neurosci 2019; 13:1198. [PMID: 31802999 PMCID: PMC6872503 DOI: 10.3389/fnins.2019.01198] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Accepted: 10/22/2019] [Indexed: 01/05/2023] Open
Abstract
Deep convolutional neural networks (DCNNs) have achieved great success for image classification in medical research. Deep learning with brain imaging is the imaging method of choice for the diagnosis and prediction of Alzheimer’s disease (AD). However, it is also well known that DCNNs are “black boxes” owing to their low interpretability to humans. The lack of transparency of deep learning compromises its application to the prediction and mechanism investigation in AD. To overcome this limitation, we develop a novel general framework that integrates deep leaning, feature selection, causal inference, and genetic-imaging data analysis for predicting and understanding AD. The proposed algorithm not only improves the prediction accuracy but also identifies the brain regions underlying the development of AD and causal paths from genetic variants to AD via image mediation. The proposed algorithm is applied to the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset with diffusion tensor imaging (DTI) in 151 subjects (51 AD and 100 non-AD) who were measured at four time points of baseline, 6 months, 12 months, and 24 months. The algorithm identified brain regions underlying AD consisting of the temporal lobes (including the hippocampus) and the ventricular system.
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Affiliation(s)
- Yuanyuan Liu
- Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center, Houston, TX, United States
| | - Zhouxuan Li
- Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center, Houston, TX, United States
| | - Qiyang Ge
- Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center, Houston, TX, United States
| | - Nan Lin
- Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center, Houston, TX, United States
| | - Momiao Xiong
- Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center, Houston, TX, United States
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