Recent studies strongly suggest that gut microbiome can influence brain functions and contribute to the development of Alzheimer's disease (AD). However, reported changes in the gut microbiomes in AD patients from different countries are not similar, and more research is needed to reveal the relationships between human microbiomes and AD in diverse ethnic populations. There is also an assumption that microbiome-associated peripheral inflammation might drive the development of sporadic AD. This cross-sectional study is aimed at analyzing the gut microbial profile and exploring potential associations with blood cytokines and some clinical parameters among individuals diagnosed with Alzheimer's in Kazakhstan. Consistent with previous studies, we have found that the microbial landscape in AD reveals specific alterations in the gut microbiome. Specifically, the AD patient group showed a decreased Firmicutes/Bacteroidetes ratio. The differential abundance analysis highlighted a dysbiosis in the gut microbiota of AD patients, marked by a reduced presence of Bifidobacterium, particularly B. breve. In our study, AD patients' altered gut microbiota composition notably features an increased presence of Pseudomonadota like Phyllobacterium and inflammatory bacteria such as Synergistetes and the Christensenellaceae family. The metabolic profiling of the AD microbiome reveals a predominant presence of pathways related to sugar, carrier molecules, tetrapyrrole, pyrimidine biosynthesis, and nucleic acid processing. This analysis also highlighted a marked reduction in SCFA, carbohydrate, polysaccharide, polyamine, and myo-inositol degradation pathways. The increases in the proinflammatory cytokines IL-1a, IL-8, IL-17A, IL-12p40, TNF-β, MCP-1, IL-2, and IL-12p70 and the anti-inflammatory cytokines IL-10 and IL-13 were observed in AD patients. Key variables driving the separation of AD and controls include inflammatory markers (IL-1a and IL-8), growth factors (EGF), lipids (LDL), BMI, and gut microbes, like genus Tyzzerella and Turicibacter and species Parabacteroides distasonis and Bacteroides eggerthii. We have also demonstrated that almost all cytokines strongly correlate with serum adiponectin levels and specific microbial taxa in AD patients. Thus, our findings identify potential microbial and inflammatory signatures in an ethnically distinct cohort of AD patients. These could serve as AD biomarkers and microbiota-based therapeutic targets for treating AD.
最近的研究有力地表明,肠道微生物组可影响大脑功能并导致阿尔茨海默病(AD)的发生。然而,来自不同国家的阿尔茨海默病患者肠道微生物组的变化报道并不相似,因此需要更多的研究来揭示不同种族人群中人类微生物组与阿尔茨海默病之间的关系。还有一种假设认为,微生物组相关的外周炎症可能会驱动散发性 AD 的发病。这项横断面研究旨在分析哈萨克斯坦阿尔茨海默氏症患者的肠道微生物特征,并探索其与血液细胞因子和一些临床参数之间的潜在关联。与之前的研究一致,我们发现,阿兹海默症患者的肠道微生物组发生了特定的改变。具体来说,AD 患者组显示出固着菌/类杆菌比例下降。丰度差异分析凸显了AD患者肠道微生物群的菌群失调,其特征是双歧杆菌,尤其是布氏双歧杆菌的数量减少。在我们的研究中,AD 患者肠道微生物群组成改变的显著特点是假单胞菌群(如 Phyllobacterium)和炎症细菌(如 Synergistetes 和 Christensenellaceae 家族)的数量增加。AD 微生物群的代谢图谱显示,与糖、载体分子、四吡咯、嘧啶生物合成和核酸加工相关的途径占主导地位。这项分析还突显了 SCFA、碳水化合物、多糖、多胺和肌醇降解途径的明显减少。在AD患者中观察到促炎细胞因子IL-1a、IL-8、IL-17A、IL-12p40、TNF-β、MCP-1、IL-2和IL-12p70以及抗炎细胞因子IL-10和IL-13的增加。导致AD与对照组分离的关键变量包括炎症标志物(IL-1a和IL-8)、生长因子(EGF)、血脂(低密度脂蛋白)、体重指数和肠道微生物,如Tyzzerella和Turisibacter属以及Parabacteroides distasonis和Bacteroides eggerthii种。我们还证明,几乎所有细胞因子都与 AD 患者的血清脂肪连接蛋白水平和特定微生物类群密切相关。因此,我们的研究结果在不同种族的 AD 患者群中发现了潜在的微生物和炎症特征。这些特征可作为 AD 生物标志物和基于微生物群的 AD 治疗靶点。
{"title":"Inflammatory Manifestations Associated With Gut Dysbiosis in Alzheimer's Disease.","authors":"Samat Kozhakhmetov, Aiym Kaiyrlykyzy, Zharkyn Jarmukhanov, Elizaveta Vinogradova, Gulnaz Zholdasbekova, Dinara Alzhanova, Jeanette Kunz, Almagul Kushugulova, Sholpan Askarova","doi":"10.1155/2024/9741811","DOIUrl":"https://doi.org/10.1155/2024/9741811","url":null,"abstract":"<p><p>Recent studies strongly suggest that gut microbiome can influence brain functions and contribute to the development of Alzheimer's disease (AD). However, reported changes in the gut microbiomes in AD patients from different countries are not similar, and more research is needed to reveal the relationships between human microbiomes and AD in diverse ethnic populations. There is also an assumption that microbiome-associated peripheral inflammation might drive the development of sporadic AD. This cross-sectional study is aimed at analyzing the gut microbial profile and exploring potential associations with blood cytokines and some clinical parameters among individuals diagnosed with Alzheimer's in Kazakhstan. Consistent with previous studies, we have found that the microbial landscape in AD reveals specific alterations in the gut microbiome. Specifically, the AD patient group showed a decreased Firmicutes/Bacteroidetes ratio. The differential abundance analysis highlighted a dysbiosis in the gut microbiota of AD patients, marked by a reduced presence of <i>Bifidobacterium</i>, particularly <i>B. breve</i>. In our study, AD patients' altered gut microbiota composition notably features an increased presence of Pseudomonadota like <i>Phyllobacterium</i> and inflammatory bacteria such as Synergistetes and the Christensenellaceae family. The metabolic profiling of the AD microbiome reveals a predominant presence of pathways related to sugar, carrier molecules, tetrapyrrole, pyrimidine biosynthesis, and nucleic acid processing. This analysis also highlighted a marked reduction in SCFA, carbohydrate, polysaccharide, polyamine, and myo-inositol degradation pathways. The increases in the proinflammatory cytokines IL-1a, IL-8, IL-17A, IL-12p40, TNF-<i>β</i>, MCP-1, IL-2, and IL-12p70 and the anti-inflammatory cytokines IL-10 and IL-13 were observed in AD patients. Key variables driving the separation of AD and controls include inflammatory markers (IL-1a and IL-8), growth factors (EGF), lipids (LDL), BMI, and gut microbes, like genus <i>Tyzzerella</i> and <i>Turicibacter</i> and species <i>Parabacteroides distasonis</i> and <i>Bacteroides eggerthii</i>. We have also demonstrated that almost all cytokines strongly correlate with serum adiponectin levels and specific microbial taxa in AD patients. Thus, our findings identify potential microbial and inflammatory signatures in an ethnically distinct cohort of AD patients. These could serve as AD biomarkers and microbiota-based therapeutic targets for treating AD.</p>","PeriodicalId":13802,"journal":{"name":"International Journal of Alzheimer's Disease","volume":"2024 ","pages":"9741811"},"PeriodicalIF":0.0,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11436273/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142346167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23eCollection Date: 2024-01-01DOI: 10.1155/2024/2052142
Semira Abdi Beshir, Nadia Hussain, Vineetha Bharathan Menon, Amal H I Al Haddad, Rahaf Adnan Kh Al Zeer, Asim Ahmed Elnour
Alzheimer's disease (AD) is a progressive neurodegenerative disorder caused by the accumulation of amyloid-beta (Aβ) proteins and neurofibrillary tangles in the brain. There have been recent advancements in antiamyloid therapy for AD. This narrative review explores the recent advancements and challenges in antiamyloid therapy. In addition, a summary of evidence from antiamyloid therapy trials is presented with a focus on lecanemab. Lecanemab is the most recently approved monoclonal antibody that targets Aβ protofibrils for the treatment of patients with early AD and mild cognitive impairment (MCI). Lecanemab was the first drug shown to slow cognitive decline in patients with MCI or early onset AD dementia when administered as an infusion once every two weeks. In the Clarity AD trial, lecanemab was associated with infusion-site reactions (26.4%) and amyloid-related imaging abnormalities (12.6%). The clinical relevance and long-term side effects of lecanemab require further longitudinal observation. However, several challenges must be addressed before the drug can be routinely used in clinical practice. The drug's route of administration, need for imaging and genetic testing, affordability, accessibility, infrastructure, and potential for serious side effects are some of these challenges. Lecanemab's approval has fueled interest in the potential of other antiamyloid therapies, such as donanemab. Future research must focus on developing strategies to prevent AD; identify easy-to-use validated plasma-based assays; and discover newer user-friendly, and cost-effective drugs that target multiple pathways in AD pathology.
阿尔茨海默病(AD)是一种进行性神经退行性疾病,由淀粉样β(Aβ)蛋白和神经纤维缠结在大脑中的积累引起。抗淀粉样蛋白疗法在治疗多发性硬化症方面取得了最新进展。本综述探讨了抗淀粉样蛋白疗法的最新进展和挑战。此外,还总结了抗淀粉样蛋白疗法试验的证据,重点介绍了来卡尼单抗。来卡尼单抗是最近获批的针对Aβ原纤维的单克隆抗体,用于治疗早期AD和轻度认知障碍(MCI)患者。莱卡单抗是第一种被证明能减缓 MCI 或早期 AD 痴呆症患者认知能力下降的药物,每两周输注一次。在 Clarity AD 试验中,来卡尼单抗与输液部位反应(26.4%)和淀粉样蛋白相关成像异常(12.6%)有关。莱卡奈单抗的临床意义和长期副作用需要进一步的纵向观察。然而,在将该药物常规用于临床实践之前,还必须解决几个难题。药物的给药途径、成像和基因检测的需要、可负担性、可及性、基础设施以及潜在的严重副作用就是其中的一些挑战。莱卡单抗的获批激发了人们对其他抗淀粉样蛋白疗法(如多那尼单抗)潜力的兴趣。未来的研究必须专注于开发预防渐冻人症的策略;确定易于使用的基于血浆的有效检测方法;以及发现针对渐冻人症病理中多种途径的更新、更易于使用且更具成本效益的药物。
{"title":"Advancements and Challenges in Antiamyloid Therapy for Alzheimer's Disease: A Comprehensive Review.","authors":"Semira Abdi Beshir, Nadia Hussain, Vineetha Bharathan Menon, Amal H I Al Haddad, Rahaf Adnan Kh Al Zeer, Asim Ahmed Elnour","doi":"10.1155/2024/2052142","DOIUrl":"10.1155/2024/2052142","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is a progressive neurodegenerative disorder caused by the accumulation of amyloid-beta (A<i>β</i>) proteins and neurofibrillary tangles in the brain. There have been recent advancements in antiamyloid therapy for AD. This narrative review explores the recent advancements and challenges in antiamyloid therapy. In addition, a summary of evidence from antiamyloid therapy trials is presented with a focus on lecanemab. Lecanemab is the most recently approved monoclonal antibody that targets A<i>β</i> protofibrils for the treatment of patients with early AD and mild cognitive impairment (MCI). Lecanemab was the first drug shown to slow cognitive decline in patients with MCI or early onset AD dementia when administered as an infusion once every two weeks. In the Clarity AD trial, lecanemab was associated with infusion-site reactions (26.4%) and amyloid-related imaging abnormalities (12.6%). The clinical relevance and long-term side effects of lecanemab require further longitudinal observation. However, several challenges must be addressed before the drug can be routinely used in clinical practice. The drug's route of administration, need for imaging and genetic testing, affordability, accessibility, infrastructure, and potential for serious side effects are some of these challenges. Lecanemab's approval has fueled interest in the potential of other antiamyloid therapies, such as donanemab. Future research must focus on developing strategies to prevent AD; identify easy-to-use validated plasma-based assays; and discover newer user-friendly, and cost-effective drugs that target multiple pathways in AD pathology.</p>","PeriodicalId":13802,"journal":{"name":"International Journal of Alzheimer's Disease","volume":"2024 ","pages":"2052142"},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11288696/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141855448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Neurodegenerative disorders such as Alzheimer’s disease (AD) represent an increasingly significant public health concern. As clinical diagnosis faces challenges, biomarkers are becoming increasingly important in research, trials, and patient assessments. While biomarkers like amyloid-β peptide, tau proteins, CSF levels (Aβ, tau, and p-tau), and neuroimaging techniques are commonly used in AD diagnosis, they are often limited and invasive in monitoring and diagnosis. For this reason, blood-based biomarkers are the optimal choice for detecting neurodegeneration in brain diseases due to their noninvasiveness, affordability, reliability, and consistency. This literature review focuses on plasma neurofilament light (NfL) and CSF NfL as blood-based biomarkers used in recent AD diagnosis. The findings revealed that the core CSF biomarkers of neurodegeneration (T-tau, P-tau, and Aβ42), CSF NFL, and plasma T-tau were strongly associated with Alzheimer’s disease, and the core biomarkers were strongly associated with mild cognitive impairment due to Alzheimer’s disease. Elevated levels of plasma and cerebrospinal fluid NfL were linked to decreased [18F]FDG uptake in corresponding brain areas. In participants with Aβ positivity (Aβ+), NfL correlated with reduced metabolism in regions susceptible to Alzheimer’s disease. In addition, CSF NfL levels correlate with brain atrophy and predict cognitive changes, while plasma total tau does not. Plasma P-tau, especially in combination with Aβ42/Aβ40, is promising for symptomatic AD stages. Though not AD-exclusive, blood NfL holds promise for neurodegeneration detection and assessing treatment efficacy. Given the consistent levels of T-tau, P-tau, Aβ42, and NFL in CSF, their incorporation into both clinical practice and research is highly recommended.
{"title":"Novel Biomarkers for Alzheimer’s Disease: Plasma Neurofilament Light and Cerebrospinal Fluid","authors":"Daniel Naawenkangua Abukuri","doi":"10.1155/2024/6668159","DOIUrl":"https://doi.org/10.1155/2024/6668159","url":null,"abstract":"Neurodegenerative disorders such as Alzheimer’s disease (AD) represent an increasingly significant public health concern. As clinical diagnosis faces challenges, biomarkers are becoming increasingly important in research, trials, and patient assessments. While biomarkers like amyloid-β peptide, tau proteins, CSF levels (Aβ, tau, and p-tau), and neuroimaging techniques are commonly used in AD diagnosis, they are often limited and invasive in monitoring and diagnosis. For this reason, blood-based biomarkers are the optimal choice for detecting neurodegeneration in brain diseases due to their noninvasiveness, affordability, reliability, and consistency. This literature review focuses on plasma neurofilament light (NfL) and CSF NfL as blood-based biomarkers used in recent AD diagnosis. The findings revealed that the core CSF biomarkers of neurodegeneration (T-tau, P-tau, and Aβ42), CSF NFL, and plasma T-tau were strongly associated with Alzheimer’s disease, and the core biomarkers were strongly associated with mild cognitive impairment due to Alzheimer’s disease. Elevated levels of plasma and cerebrospinal fluid NfL were linked to decreased [18F]FDG uptake in corresponding brain areas. In participants with Aβ positivity (Aβ+), NfL correlated with reduced metabolism in regions susceptible to Alzheimer’s disease. In addition, CSF NfL levels correlate with brain atrophy and predict cognitive changes, while plasma total tau does not. Plasma P-tau, especially in combination with Aβ42/Aβ40, is promising for symptomatic AD stages. Though not AD-exclusive, blood NfL holds promise for neurodegeneration detection and assessing treatment efficacy. Given the consistent levels of T-tau, P-tau, Aβ42, and NFL in CSF, their incorporation into both clinical practice and research is highly recommended.","PeriodicalId":13802,"journal":{"name":"International Journal of Alzheimer's Disease","volume":"6 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140972831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alzheimer's disease (AD) is a “progressive, neurodegenerative disease that occurs when nerve cells in the brain die.” There are only 4 drugs approved by the United States Food and Drug Administration (FDA). Three (donepezil, rivastigmine, and galantamine) out of these four drugs are anticholinesterase inhibitors, while the fourth one memantine is an N-methyl-D-aspartate (NMDA) receptor inhibitor. Currently, two immunotherapy drugs that target amyloid protein (donanemab and lecanemab) are being considered for the treatment of Alzheimer's disease at an early stage. All these drug molecules are still not the complete answer to the treatment of Alzheimer's disease. A recent report from the Office of National Statistics showed that AD is the leading cause of death in 2022. Therefore, there is an urgency to develop more drugs that can treat AD. Based on this urgency, we aim to investigate how bioactive and already approved drugs could be repurposed for inhibiting the anticholinesterase enzyme using computational studies. To achieve this, the data science tool—Python coding was compiled on Jupyter Notebook to mine bioactive compounds from the ChEMBL database. The most bioactive compounds obtained were further investigated using Molecular Operating Environment (MOE) software to carry out molecular docking and ligand analysis, and this was followed by molecular dynamics simulation production at 35 ns using GROMACS 2022.4 on Archer 2 machine. The molecular dynamic analysis was carried out using HeroMDanalysis software. Data mining of the ChEMBL database was carried out for lipase inhibitors, and this gave CHEMBL-ID 1240685, a peptide molecule, the most active compound at the time of data mining. Further literature studies gave Zoladex an FDA-approved drug for the treatment of breast cancer as another compound of interest. The in silico studies were carried out against the anticholinesterase enzyme using two FDA-approved drugs donepezil and galantamine as a template for comparing the in silico activities of the repurposed drugs. A very useful receptor for this study was PDB-1DX6, a cocrystallized galantamine inhibitor of acetylcholinesterase enzyme. The molecular docking analysis (using ligand interactions) and molecular dynamic analysis (root mean square deviation (RMSD) and root mean square fluctuation (RMSF)) showed that the two peptide molecules CHEMBL-1240685 and Zoladex gave the best binding energy and stability when compared to the FDA-approved drugs (donepezil and galantamine). Finally, further literature studies revealed that Zoladex affects memory reduction; therefore, it was dropped as a possible repurposed drug. Our research showed that CHEMBL-1240685 is a potential compound that could be investigated for the inhibition of anticholinesterase enzyme and might be another drug molecule that could be used to treat Alzheimer's disease.
{"title":"In Silico Investigation of Novel Compounds as Inhibitors of Acetylcholinesterase Enzyme for the Treatment of Alzheimer's Diseases","authors":"Kassim Adebambo, Oghenekevwe (Claudia) Ojoh","doi":"10.1155/2024/2988685","DOIUrl":"https://doi.org/10.1155/2024/2988685","url":null,"abstract":"Alzheimer's disease (AD) is a “progressive, neurodegenerative disease that occurs when nerve cells in the brain die.” There are only 4 drugs approved by the United States Food and Drug Administration (FDA). Three (donepezil, rivastigmine, and galantamine) out of these four drugs are anticholinesterase inhibitors, while the fourth one memantine is an N-methyl-D-aspartate (NMDA) receptor inhibitor. Currently, two immunotherapy drugs that target amyloid protein (donanemab and lecanemab) are being considered for the treatment of Alzheimer's disease at an early stage. All these drug molecules are still not the complete answer to the treatment of Alzheimer's disease. A recent report from the Office of National Statistics showed that AD is the leading cause of death in 2022. Therefore, there is an urgency to develop more drugs that can treat AD. Based on this urgency, we aim to investigate how bioactive and already approved drugs could be repurposed for inhibiting the anticholinesterase enzyme using computational studies. To achieve this, the data science tool—Python coding was compiled on Jupyter Notebook to mine bioactive compounds from the ChEMBL database. The most bioactive compounds obtained were further investigated using Molecular Operating Environment (MOE) software to carry out molecular docking and ligand analysis, and this was followed by molecular dynamics simulation production at 35 ns using GROMACS 2022.4 on Archer 2 machine. The molecular dynamic analysis was carried out using HeroMDanalysis software. Data mining of the ChEMBL database was carried out for lipase inhibitors, and this gave CHEMBL-ID 1240685, a peptide molecule, the most active compound at the time of data mining. Further literature studies gave Zoladex an FDA-approved drug for the treatment of breast cancer as another compound of interest. The in silico studies were carried out against the anticholinesterase enzyme using two FDA-approved drugs donepezil and galantamine as a template for comparing the in silico activities of the repurposed drugs. A very useful receptor for this study was PDB-1DX6, a cocrystallized galantamine inhibitor of acetylcholinesterase enzyme. The molecular docking analysis (using ligand interactions) and molecular dynamic analysis (root mean square deviation (RMSD) and root mean square fluctuation (RMSF)) showed that the two peptide molecules CHEMBL-1240685 and Zoladex gave the best binding energy and stability when compared to the FDA-approved drugs (donepezil and galantamine). Finally, further literature studies revealed that Zoladex affects memory reduction; therefore, it was dropped as a possible repurposed drug. Our research showed that CHEMBL-1240685 is a potential compound that could be investigated for the inhibition of anticholinesterase enzyme and might be another drug molecule that could be used to treat Alzheimer's disease.","PeriodicalId":13802,"journal":{"name":"International Journal of Alzheimer's Disease","volume":"9 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139851260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alzheimer's disease (AD) is a “progressive, neurodegenerative disease that occurs when nerve cells in the brain die.” There are only 4 drugs approved by the United States Food and Drug Administration (FDA). Three (donepezil, rivastigmine, and galantamine) out of these four drugs are anticholinesterase inhibitors, while the fourth one memantine is an N-methyl-D-aspartate (NMDA) receptor inhibitor. Currently, two immunotherapy drugs that target amyloid protein (donanemab and lecanemab) are being considered for the treatment of Alzheimer's disease at an early stage. All these drug molecules are still not the complete answer to the treatment of Alzheimer's disease. A recent report from the Office of National Statistics showed that AD is the leading cause of death in 2022. Therefore, there is an urgency to develop more drugs that can treat AD. Based on this urgency, we aim to investigate how bioactive and already approved drugs could be repurposed for inhibiting the anticholinesterase enzyme using computational studies. To achieve this, the data science tool—Python coding was compiled on Jupyter Notebook to mine bioactive compounds from the ChEMBL database. The most bioactive compounds obtained were further investigated using Molecular Operating Environment (MOE) software to carry out molecular docking and ligand analysis, and this was followed by molecular dynamics simulation production at 35 ns using GROMACS 2022.4 on Archer 2 machine. The molecular dynamic analysis was carried out using HeroMDanalysis software. Data mining of the ChEMBL database was carried out for lipase inhibitors, and this gave CHEMBL-ID 1240685, a peptide molecule, the most active compound at the time of data mining. Further literature studies gave Zoladex an FDA-approved drug for the treatment of breast cancer as another compound of interest. The in silico studies were carried out against the anticholinesterase enzyme using two FDA-approved drugs donepezil and galantamine as a template for comparing the in silico activities of the repurposed drugs. A very useful receptor for this study was PDB-1DX6, a cocrystallized galantamine inhibitor of acetylcholinesterase enzyme. The molecular docking analysis (using ligand interactions) and molecular dynamic analysis (root mean square deviation (RMSD) and root mean square fluctuation (RMSF)) showed that the two peptide molecules CHEMBL-1240685 and Zoladex gave the best binding energy and stability when compared to the FDA-approved drugs (donepezil and galantamine). Finally, further literature studies revealed that Zoladex affects memory reduction; therefore, it was dropped as a possible repurposed drug. Our research showed that CHEMBL-1240685 is a potential compound that could be investigated for the inhibition of anticholinesterase enzyme and might be another drug molecule that could be used to treat Alzheimer's disease.
{"title":"In Silico Investigation of Novel Compounds as Inhibitors of Acetylcholinesterase Enzyme for the Treatment of Alzheimer's Diseases","authors":"Kassim Adebambo, Oghenekevwe (Claudia) Ojoh","doi":"10.1155/2024/2988685","DOIUrl":"https://doi.org/10.1155/2024/2988685","url":null,"abstract":"Alzheimer's disease (AD) is a “progressive, neurodegenerative disease that occurs when nerve cells in the brain die.” There are only 4 drugs approved by the United States Food and Drug Administration (FDA). Three (donepezil, rivastigmine, and galantamine) out of these four drugs are anticholinesterase inhibitors, while the fourth one memantine is an N-methyl-D-aspartate (NMDA) receptor inhibitor. Currently, two immunotherapy drugs that target amyloid protein (donanemab and lecanemab) are being considered for the treatment of Alzheimer's disease at an early stage. All these drug molecules are still not the complete answer to the treatment of Alzheimer's disease. A recent report from the Office of National Statistics showed that AD is the leading cause of death in 2022. Therefore, there is an urgency to develop more drugs that can treat AD. Based on this urgency, we aim to investigate how bioactive and already approved drugs could be repurposed for inhibiting the anticholinesterase enzyme using computational studies. To achieve this, the data science tool—Python coding was compiled on Jupyter Notebook to mine bioactive compounds from the ChEMBL database. The most bioactive compounds obtained were further investigated using Molecular Operating Environment (MOE) software to carry out molecular docking and ligand analysis, and this was followed by molecular dynamics simulation production at 35 ns using GROMACS 2022.4 on Archer 2 machine. The molecular dynamic analysis was carried out using HeroMDanalysis software. Data mining of the ChEMBL database was carried out for lipase inhibitors, and this gave CHEMBL-ID 1240685, a peptide molecule, the most active compound at the time of data mining. Further literature studies gave Zoladex an FDA-approved drug for the treatment of breast cancer as another compound of interest. The in silico studies were carried out against the anticholinesterase enzyme using two FDA-approved drugs donepezil and galantamine as a template for comparing the in silico activities of the repurposed drugs. A very useful receptor for this study was PDB-1DX6, a cocrystallized galantamine inhibitor of acetylcholinesterase enzyme. The molecular docking analysis (using ligand interactions) and molecular dynamic analysis (root mean square deviation (RMSD) and root mean square fluctuation (RMSF)) showed that the two peptide molecules CHEMBL-1240685 and Zoladex gave the best binding energy and stability when compared to the FDA-approved drugs (donepezil and galantamine). Finally, further literature studies revealed that Zoladex affects memory reduction; therefore, it was dropped as a possible repurposed drug. Our research showed that CHEMBL-1240685 is a potential compound that could be investigated for the inhibition of anticholinesterase enzyme and might be another drug molecule that could be used to treat Alzheimer's disease.","PeriodicalId":13802,"journal":{"name":"International Journal of Alzheimer's Disease","volume":" 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139791128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alzheimer's disease (AD) is a serious threat to the global health care system and is brought on by a series of factors that cause neuronal dysfunction and impairment in memory and cognitive decline. This study investigated the therapeutic potential of phytochemicals that belong to the ten regularly used spice plants, based on their binding affinity with AD-associated proteins. Comprehensive docking studies were performed using AutoDock Vina in PyRx followed by molecular dynamic (MD) simulations using AMBER 14. The docking study of the chosen molecules revealed the binding energies of their interactions with the target proteins, while MD simulations were carried out to verify the steadiness of bound complexes. Through the Lipinski filter and admetSAR analysis, the chosen compounds' pharmacokinetic characteristics and drug likeness were also examined. The pharmacophore mapping study was also done and analyzed for best selected molecules. Additionally, principal component analysis (PCA) was used to examine how the general motion of the protein changed. The results showed quercetin and myricetin to be potential inhibitors of AChE and alpha-amyrin and beta-chlorogenin to be potential inhibitors of BuChE, exhibiting best binding energies comparable to those of donepezil, used as a positive control. The multiple descriptors from the simulation study, root mean square deviation (RMSD), root mean square fluctuation (RMSF), hydrogen bond, radius of gyration (Rg), and solvent-accessible surface areas (SASA), confirm the stable nature of the protein-ligand complexes. Molecular mechanic Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculations indicated the energetically favorable binding of the ligands to the protein. Finally, according to pharmacokinetic properties and drug likeness, characteristics showed that quercetin and myricetin for AChE and alpha-amyrin and beta-chlorogenin for BuChE were found to be the most effective agents for treating the AD.
{"title":"Unveiling Neuroprotective Potential of Spice Plant-Derived Compounds against Alzheimer's Disease: Insights from Computational Studies.","authors":"Md Murshid Alom, Rejwana Parvin Bonna, Ariful Islam, Md Wasim Alom, Md Ekhtiar Rahman, Md Omar Faruqe, Md Khalekuzzaman, Rashed Zaman, Md Asadul Islam","doi":"10.1155/2023/8877757","DOIUrl":"https://doi.org/10.1155/2023/8877757","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is a serious threat to the global health care system and is brought on by a series of factors that cause neuronal dysfunction and impairment in memory and cognitive decline. This study investigated the therapeutic potential of phytochemicals that belong to the ten regularly used spice plants, based on their binding affinity with AD-associated proteins. Comprehensive docking studies were performed using AutoDock Vina in PyRx followed by molecular dynamic (MD) simulations using AMBER 14. The docking study of the chosen molecules revealed the binding energies of their interactions with the target proteins, while MD simulations were carried out to verify the steadiness of bound complexes. Through the Lipinski filter and admetSAR analysis, the chosen compounds' pharmacokinetic characteristics and drug likeness were also examined. The pharmacophore mapping study was also done and analyzed for best selected molecules. Additionally, principal component analysis (PCA) was used to examine how the general motion of the protein changed. The results showed quercetin and myricetin to be potential inhibitors of AChE and alpha-amyrin and beta-chlorogenin to be potential inhibitors of BuChE, exhibiting best binding energies comparable to those of donepezil, used as a positive control. The multiple descriptors from the simulation study, root mean square deviation (RMSD), root mean square fluctuation (RMSF), hydrogen bond, radius of gyration (Rg), and solvent-accessible surface areas (SASA), confirm the stable nature of the protein-ligand complexes. Molecular mechanic Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculations indicated the energetically favorable binding of the ligands to the protein. Finally, according to pharmacokinetic properties and drug likeness, characteristics showed that quercetin and myricetin for AChE and alpha-amyrin and beta-chlorogenin for BuChE were found to be the most effective agents for treating the AD.</p>","PeriodicalId":13802,"journal":{"name":"International Journal of Alzheimer's Disease","volume":"2023 ","pages":"8877757"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516701/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41133796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-06eCollection Date: 2023-01-01DOI: 10.1155/2023/5336273
Maryam Behzad, Negin Zirak, Ghazal Hamidi Madani, Linda Baidoo, Ali Rezaei, Shima Karbasi, Mohammad Sadeghi, Mahan Shafie, Mahsa Mayeli, Alzheimer's Disease Neuroimaging Initiative
Background: According to recent studies, amyloid-β (Aβ) isoforms as cerebrospinal fluid (CSF) biomarkers have remarkable predictive value for cognitive decline in the early stages of Alzheimer's disease (AD). Herein, we aimed to investigate the correlations between several targeted proteomics in CSF samples with Aβ ratios and cognitive scores in patients in AD spectrum to search for potential early diagnostic utility.
Methods: A total of 719 participants were found eligible for inclusion. Patients were then categorized into cognitively normal (CN), mild cognitive impairment (MCI), and AD and underwent an assessment of Aβ and proteomics. Clinical Dementia Rating (CDR), Alzheimer's Disease Assessment Scale (ADAS), and Mini Mental State Exam (MMSE) were used for further cognitive assessment. The Aβ42, Aβ42/Aβ40, and Aβ42/38 ratios were considered as means of comparison to identify those peptides corresponding significantly to these established biomarkers and cognitive scores. The diagnostic utility of the IASNTQSR, VAELEDEK, VVSSIEQK, GDSVVYGLR, EPVAGDAVPGPK, and QETLPSK was assessed.
Results: All investigated peptides corresponded significantly to Aβ42 in controls. In those with MCI, VAELEDEK and EPVAGDAVPGPK were significantly correlated with Aβ42 (p value < 0.001). Additionally, IASNTQSR, VVSSIEQK, GDSVVYGLR, and QETLPSK were significantly correlated with Aβ42/Aβ40 and Aβ42/38 (p value < 0.001) in this group. This group of peptides similarly corresponded to Aβ ratios in those with AD. Eventually, IASNTQSR, VAELEDEK, and VVSSIEQK were significantly associated with CDR, ADAS-11, and ADAS-13, particularly in MCI group.
Conclusion: Our research suggests potential early diagnostic and prognostic utilities for certain peptides extracted from CSF-targeted proteomics research. The ethical approval of ADNI is available at ClinicalTrials.gov with Identifier: NCT00106899.
{"title":"CSF-Targeted Proteomics Indicate Amyloid-Beta Ratios in Patients with Alzheimer's Dementia Spectrum.","authors":"Maryam Behzad, Negin Zirak, Ghazal Hamidi Madani, Linda Baidoo, Ali Rezaei, Shima Karbasi, Mohammad Sadeghi, Mahan Shafie, Mahsa Mayeli, Alzheimer's Disease Neuroimaging Initiative","doi":"10.1155/2023/5336273","DOIUrl":"10.1155/2023/5336273","url":null,"abstract":"<p><strong>Background: </strong>According to recent studies, amyloid-<i>β</i> (A<i>β</i>) isoforms as cerebrospinal fluid (CSF) biomarkers have remarkable predictive value for cognitive decline in the early stages of Alzheimer's disease (AD). Herein, we aimed to investigate the correlations between several targeted proteomics in CSF samples with A<i>β</i> ratios and cognitive scores in patients in AD spectrum to search for potential early diagnostic utility.</p><p><strong>Methods: </strong>A total of 719 participants were found eligible for inclusion. Patients were then categorized into cognitively normal (CN), mild cognitive impairment (MCI), and AD and underwent an assessment of A<i>β</i> and proteomics. Clinical Dementia Rating (CDR), Alzheimer's Disease Assessment Scale (ADAS), and Mini Mental State Exam (MMSE) were used for further cognitive assessment. The A<i>β</i>42, A<i>β</i>42/A<i>β</i>40, and A<i>β</i>42/38 ratios were considered as means of comparison to identify those peptides corresponding significantly to these established biomarkers and cognitive scores. The diagnostic utility of the IASNTQSR, VAELEDEK, VVSSIEQK, GDSVVYGLR, EPVAGDAVPGPK, and QETLPSK was assessed.</p><p><strong>Results: </strong>All investigated peptides corresponded significantly to A<i>β</i>42 in controls. In those with MCI, VAELEDEK and EPVAGDAVPGPK were significantly correlated with A<i>β</i>42 (<i>p</i> value < 0.001). Additionally, IASNTQSR, VVSSIEQK, GDSVVYGLR, and QETLPSK were significantly correlated with A<i>β</i>42/A<i>β</i>40 and A<i>β</i>42/38 (<i>p</i> value < 0.001) in this group. This group of peptides similarly corresponded to A<i>β</i> ratios in those with AD. Eventually, IASNTQSR, VAELEDEK, and VVSSIEQK were significantly associated with CDR, ADAS-11, and ADAS-13, particularly in MCI group.</p><p><strong>Conclusion: </strong>Our research suggests potential early diagnostic and prognostic utilities for certain peptides extracted from CSF-targeted proteomics research. The ethical approval of ADNI is available at ClinicalTrials.gov with Identifier: NCT00106899.</p>","PeriodicalId":13802,"journal":{"name":"International Journal of Alzheimer's Disease","volume":"2023 ","pages":"5336273"},"PeriodicalIF":0.0,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925239/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10794632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Azam Sajjadi Nasab, Fatemeh Noorani, Zahra Paeizi, Leila Khani, Saba Banaei, Mohammad Sadeghi, Melika Shafeghat, Mahan Shafie, Mahsa Mayeli, The Alzheimer's Disease Neuroimaging Initiative Adni
Introduction: While cerebrospinal fluid (CSF) core biomarkers have been considered diagnostic biomarkers for a long time, special attention has been recently dedicated to lipoproteins and metabolites that could be potentially associated with Alzheimer's disease (AD) neurodegeneration. Herein, we aimed to investigate the relationship between the levels of CSF core biomarkers including Aβ-42, TAU, and P-TAU and plasma lipoproteins and metabolites of patients with AD from the baseline cohort of the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.
Method: Using the ADNI database, fourteen subclasses of lipoproteins as well as a number of lipids and fatty acids and low-molecular metabolites including amino acids, ketone bodies, and glycolysis-related metabolites in blood samples were measured as potential noninvasive markers, and their association with the CSF core biomarkers was statistically investigated controlling for age and gender.
Results: A total number of 251 AD subjects were included, among whom 71 subjects were negative for the Apo-E ε4 allele and 150 were positive. There was no significant difference between the two groups regarding cognitive assessments, CSF core biomarkers, and lipoproteins and metabolites except the level of Aβ-42 (p < 0.001) and phenylalanine (p = 0.049), which were higher in the negative group. CSF TAU and P-TAU were significantly correlated with medium and small HDL in the negative group, and with extremely large VLDL in the positive group. Our results also indicated significant correlations of metabolites including unsaturated fatty acids, glycerol, and leucine with CSF core biomarkers.
Conclusion: Based on our findings, a number of lipoproteins and metabolites were associated with CSF core biomarkers of AD. These correlations showed some differences in Apo-E ε4 positive and negative groups, which reminds the role of Apo-E gene status in the pathophysiology of AD development. However, further research is warranted to explore the exact association of lipoproteins and other metabolites with AD core biomarkers and pathology.
{"title":"A Comprehensive Investigation of the Potential Role of Lipoproteins and Metabolite Profile as Biomarkers of Alzheimer's Disease Compared to the Known CSF Biomarkers.","authors":"Azam Sajjadi Nasab, Fatemeh Noorani, Zahra Paeizi, Leila Khani, Saba Banaei, Mohammad Sadeghi, Melika Shafeghat, Mahan Shafie, Mahsa Mayeli, The Alzheimer's Disease Neuroimaging Initiative Adni","doi":"10.1155/2023/3540020","DOIUrl":"https://doi.org/10.1155/2023/3540020","url":null,"abstract":"<p><strong>Introduction: </strong>While cerebrospinal fluid (CSF) core biomarkers have been considered diagnostic biomarkers for a long time, special attention has been recently dedicated to lipoproteins and metabolites that could be potentially associated with Alzheimer's disease (AD) neurodegeneration. Herein, we aimed to investigate the relationship between the levels of CSF core biomarkers including A<i>β</i>-42, TAU, and P-TAU and plasma lipoproteins and metabolites of patients with AD from the baseline cohort of the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.</p><p><strong>Method: </strong>Using the ADNI database, fourteen subclasses of lipoproteins as well as a number of lipids and fatty acids and low-molecular metabolites including amino acids, ketone bodies, and glycolysis-related metabolites in blood samples were measured as potential noninvasive markers, and their association with the CSF core biomarkers was statistically investigated controlling for age and gender.</p><p><strong>Results: </strong>A total number of 251 AD subjects were included, among whom 71 subjects were negative for the <i>Apo-E ε</i>4 allele and 150 were positive. There was no significant difference between the two groups regarding cognitive assessments, CSF core biomarkers, and lipoproteins and metabolites except the level of A<i>β</i>-42 (<i>p</i> < 0.001) and phenylalanine (<i>p</i> = 0.049), which were higher in the negative group. CSF TAU and P-TAU were significantly correlated with medium and small HDL in the negative group, and with extremely large VLDL in the positive group. Our results also indicated significant correlations of metabolites including unsaturated fatty acids, glycerol, and leucine with CSF core biomarkers.</p><p><strong>Conclusion: </strong>Based on our findings, a number of lipoproteins and metabolites were associated with CSF core biomarkers of AD. These correlations showed some differences in <i>Apo-E ε</i>4 positive and negative groups, which reminds the role of <i>Apo-E</i> gene status in the pathophysiology of AD development. However, further research is warranted to explore the exact association of lipoproteins and other metabolites with AD core biomarkers and pathology.</p>","PeriodicalId":13802,"journal":{"name":"International Journal of Alzheimer's Disease","volume":"2023 ","pages":"3540020"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019964/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9199540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alzheimer's disease (AD) is a neurodegenerative condition that is pathologically characterized by the presence of amyloid plaques and neurofibrillary tangles. Animal models of AD have been useful in understanding the disease process and in investigating the effects of compounds on pathology and behavior. APP/PS1 mice develop amyloid plaques and show memory impairment. Cyclic glycine-proline (cGP) is a cyclic dipeptide that is likely produced from a tripeptide, glycine-proline-glutamate, which itself is generated after proteolytic cleavage of insulin-like growth factor-1. Here, we show that cGP improves spatial memory and reduces amyloid plaque burden in APP/PS1 mice. The results thus suggest that cGP could potentially provide beneficial effects in AD.
{"title":"Cyclic Glycine-Proline Improves Memory and Reduces Amyloid Plaque Load in APP/PS1 Transgenic Mouse Model of Alzheimer's Disease.","authors":"Tushar Arora, Shiv K Sharma","doi":"10.1155/2023/1753791","DOIUrl":"https://doi.org/10.1155/2023/1753791","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is a neurodegenerative condition that is pathologically characterized by the presence of amyloid plaques and neurofibrillary tangles. Animal models of AD have been useful in understanding the disease process and in investigating the effects of compounds on pathology and behavior. APP/PS1 mice develop amyloid plaques and show memory impairment. Cyclic glycine-proline (cGP) is a cyclic dipeptide that is likely produced from a tripeptide, glycine-proline-glutamate, which itself is generated after proteolytic cleavage of insulin-like growth factor-1. Here, we show that cGP improves spatial memory and reduces amyloid plaque burden in APP/PS1 mice. The results thus suggest that cGP could potentially provide beneficial effects in AD.</p>","PeriodicalId":13802,"journal":{"name":"International Journal of Alzheimer's Disease","volume":"2023 ","pages":"1753791"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9995210/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9454290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ibrahim M Abbass, Dae Choi, Christopher Wallick, Sheila Seleri Assunção
Introduction: An Alzheimer's disease (AD) dementia diagnosis is often preceded by an extended period of cognitive decline. Few studies have examined healthcare resource use (HRU) during an extended period before AD dementia diagnosis.
Methods: In a historical claims-based cohort study, propensity score-matched cohorts of patients with and without AD dementia were observed for a 5-year prediagnosis period and a 1-year postdiagnosis period. Demographics, clinical characteristics, and HRU were compared between groups.
Results: Individuals in the AD dementia group displayed a greater level of medical complexity in the year before diagnosis of AD dementia relative to those in the matched cohort. Both all-cause and AD dementia complication-related HRU increased gradually, with a marked spike at the time of initial AD dementia diagnosis. Discussion. Further research into the natural history of patients with AD dementia is necessary to improve identification of early AD and to better understand its broader impact.
{"title":"Trends in Healthcare Resource Use Preceding Diagnosis of Alzheimer's Disease Dementia.","authors":"Ibrahim M Abbass, Dae Choi, Christopher Wallick, Sheila Seleri Assunção","doi":"10.1155/2023/8154701","DOIUrl":"https://doi.org/10.1155/2023/8154701","url":null,"abstract":"<p><strong>Introduction: </strong>An Alzheimer's disease (AD) dementia diagnosis is often preceded by an extended period of cognitive decline. Few studies have examined healthcare resource use (HRU) during an extended period before AD dementia diagnosis.</p><p><strong>Methods: </strong>In a historical claims-based cohort study, propensity score-matched cohorts of patients with and without AD dementia were observed for a 5-year prediagnosis period and a 1-year postdiagnosis period. Demographics, clinical characteristics, and HRU were compared between groups.</p><p><strong>Results: </strong>Individuals in the AD dementia group displayed a greater level of medical complexity in the year before diagnosis of AD dementia relative to those in the matched cohort. Both all-cause and AD dementia complication-related HRU increased gradually, with a marked spike at the time of initial AD dementia diagnosis. <i>Discussion</i>. Further research into the natural history of patients with AD dementia is necessary to improve identification of early AD and to better understand its broader impact.</p>","PeriodicalId":13802,"journal":{"name":"International Journal of Alzheimer's Disease","volume":"2023 ","pages":"8154701"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9840544/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10539354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}