Current Alzheimer research最新文献

{"title":"Post-Hoc Assessment of Cognitive Efficacy in Alzheimer's Disease Using a Latent Growth Mixture Model in AMBAR, a Phase 2B Randomized Controlled Trial.","authors":"Nicolai D Ayasse, Walter F Stewart, Richard B Lipton, David Gomez-Ulloa, M Chris Runken","doi":"10.2174/0115672050316936240905064215","DOIUrl":"10.2174/0115672050316936240905064215","url":null,"abstract":"<p><strong>Background: </strong>Disease progression in Alzheimer's Dementia (AD) is typically characterized by accelerated cognitive and functional decline, where heterogeneous trajectories can impact the observed treatment response.</p><p><strong>Methods: </strong>We hypothesized that unobserved heterogeneity could obscure treatment benefits in AD. The effect of unobserved heterogeneity was empirically quantified within the Alzheimer's Management By Albumin Replacement (AMBAR) phase 2b trial data. The ADAS-Cog 12 cognition endpoint was reanalyzed in a 2-class latent growth mixture model initially fit to the treatment arm. The model with the best fit was then applied across both treatment arms to a larger (n=1000) simulated dataset that was representative of AMBAR trial cognitive data.</p><p><strong>Results: </strong>Two classes of patients were observed: a stable cognitive trajectory class and a highly variable class. Removal of the latter (n=48, 22%) from the analysis and refitting efficacy models comparing the stable class to full placebo yielded significant treatment efficacy on cognition (p=0.007, Cohen's D=-0.4). Comparison of the stable class of each arm within the simulated dataset revealed a significant difference in treatment efficacy favoring the simulated stable treatment arm.</p><p><strong>Conclusion: </strong>This post hoc exploratory analysis suggests that prespecified strategies for addressing unobserved heterogeneity may yield improved effect detection in AD trials. The generalizability of the analytic strategy is limited by latent stratification in only the treatment arm, a requirement given the small placebo arm in AMBAR. This limitation was partially addressed by the simulation modeling.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":"353-365"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142335702","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}

{"title":"hdWGCNA and Cellular Communication Identify Active NK Cell Subtypes in Alzheimer's Disease and Screen for Diagnostic Markers through Machine Learning.","authors":"Guobin Song, Haoyang Wu, Haiqing Chen, Shengke Zhang, Qingwen Hu, Haotian Lai, Claire Fuller, Guanhu Yang, Hao Chi","doi":"10.2174/0115672050314171240527064514","DOIUrl":"10.2174/0115672050314171240527064514","url":null,"abstract":"<p><strong>Background: </strong>Alzheimer's disease (AD) is a recognized complex and severe neurodegenerative disorder, presenting a significant challenge to global health. Its hallmark pathological features include the deposition of β-amyloid plaques and the formation of neurofibrillary tangles. Given this context, it becomes imperative to develop an early and accurate biomarker model for AD diagnosis, employing machine learning and bioinformatics analysis.</p><p><strong>Methods: </strong>In this study, single-cell data analysis was employed to identify cellular subtypes that exhibited significant differences between the diseased and control groups. Following the identification of NK cells, hdWGCNA analysis and cellular communication analysis were conducted to pinpoint NK cell subset with the most robust communication effects. Subsequently, three machine learning algorithms-LASSO, Random Forest, and SVM-RFE-were employed to jointly screen for NK cell subset modular genes highly associated with AD. A logistic regression diagnostic model was then designed based on these characterized genes. Additionally, a protein-protein interaction (PPI) networks of model genes was established. Furthermore, unsupervised cluster analysis was conducted to classify AD subtypes based on the model genes, followed by the analysis of immune infiltration in the different subtypes. Finally, Spearman correlation coefficient analysis was utilized to explore the correlation between model genes and immune cells, as well as inflammatory factors.</p><p><strong>Results: </strong>We have successfully identified three genes (RPLP2, RPSA, and RPL18A) that exhibit a high association with AD. The nomogram based on these genes provides practical assistance in diagnosing and predicting patients' outcomes. The interconnected genes screened through PPI are intricately linked to ribosome metabolism and the COVID-19 pathway. Utilizing the expression of modular genes, unsupervised cluster analysis unveiled three distinct AD subtypes. Particularly noteworthy is subtype C3, characterized by high expression, which correlates with immune cell infiltration and elevated levels of inflammatory factors. Hence, it can be inferred that the establishment of an immune environment in AD patients is closely intertwined with the heightened expression of model genes.</p><p><strong>Conclusion: </strong>This study has not only established a valuable diagnostic model for AD patients but has also delved deeply into the pivotal role of model genes in shaping the immune environment of individuals with AD. These findings offer crucial insights into early AD diagnosis and patient management strategies.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":"120-140"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141162977","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}

{"title":"Radio-Anatomical Assessment of Cerebellum Volume in Individuals with Alzheimer's Disease.","authors":"Musa Acar, Busra Seker, Sultan Ugur","doi":"10.2174/0115672050365323241217175349","DOIUrl":"10.2174/0115672050365323241217175349","url":null,"abstract":"<p><strong>Introduction: </strong>Alzheimer's disease is a chronic brain disease that includes memory and language disorders. This disease, which is considered the most common cause of dementia worldwide, accounts for 60-80% of all dementia cases. Recent studies suggest that the cerebellum may play a role in cognitive functions as well as motor functions.</p><p><strong>Materials and methods: </strong>The study was conducted on 40 Alzheimer's patients and 40 healthy individuals. In our study, volumetric evaluation of the cerebellum was performed.</p><p><strong>Results: </strong>As expected, significant differences were found in cerebellar volume reduction in AD patients compared to healthy controls. Significant volume increase was observed in some regions of the cerebellum in Alzheimer's patients compared to healthy individuals.</p><p><strong>Conclusion: </strong>The findings supported the role of the cerebellum in cognitive functions. Volume reductions may assist clinicians in making an early diagnosis of AD.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":"599-606"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142934323","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}

{"title":"Capgras Syndrome in Dementia: A Systematic Review of Case Studies.","authors":"Charikleia Margariti, Margareta-Theodora Mircea","doi":"10.2174/0115672050335918240919073012","DOIUrl":"10.2174/0115672050335918240919073012","url":null,"abstract":"<p><strong>Background: </strong>In an ageing population, dementia has become an imminent healthcare emergency. Capgras syndrome, the most common delusion of misidentification (DMS), is frequently found alongside dementia. Previous research showed that Capgras syndrome has significant negative effects on people living with dementia and their carers due to its complex presentation and impact on their lives. This qualitative systematic review explores the evidence base of the effective management and treatment of Capgras syndrome in dementia.</p><p><strong>Aims: </strong>As per our knowledge, this is the first systematic review exploring the symptomatology of Capgras syndrome across different types of dementia. Additionally, it aims to identify the treatments used and their efficacy.</p><p><strong>Methods: </strong>Four databases (EMBASE, MEDLINE, PsycINFO, and CINHAL) were screened in March, 2023. Twenty-six studies met the inclusion criteria and were included in the review. Thematic analysis was performed to explore and synthesise the qualitative findings of the studies.</p><p><strong>Results: </strong>Three conceptual themes were identified: diagnostic tools, Capgras syndrome symptomatology, and Capgras syndrome treatment. Results showed that Capgras syndrome in dementia is not diagnosed and treated in a standardised manner. Following the pharmacological intervention, 28% of cases showed resolution of symptoms, and another 28% experienced improvement. However, 7% of cases reported worsening symptoms, and 10.7% experienced no change. While some patients had positive outcomes with specific medications, others either did not respond or experienced a deterioration of their condition.</p><p><strong>Conclusion: </strong>The results highlight that there is no single treatment approach for Capgras syndrome in people living with dementia. This underscores the need for person-centred care, where treatment is tailored to individual needs. The review also reveals a heavy reliance on antipsychotic medications and a noticeable lack of psychosocial interventions. Given the limited benefits and significant risks associated with antipsychotics, future research should prioritise developing and testing psychosocial approaches. Additionally, establishing standardised diagnostic criteria and consistent outcome measures for Capgras syndrome in dementia is crucial for evaluating treatment effectiveness and improving care.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":"312-323"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142484928","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}

{"title":"ROCK Inhibitor Fasudil Attenuates Neuroinflammation and Associated Metabolic Dysregulation in the Tau Transgenic Mouse Model of Alzheimer's Disease.","authors":"Xiaosen Ouyang, Roberto Collu, Gloria A Benavides, Ran Tian, Victor Darley-Usmar, Weiming Xia, Jianhua Zhang","doi":"10.2174/0115672050317608240531130204","DOIUrl":"10.2174/0115672050317608240531130204","url":null,"abstract":"<p><strong>Background: </strong>The pathological manifestations of Alzheimer's disease (AD) include not only brain amyloid β protein (Aβ) containing neuritic plaques and hyperphosphorylated tau (p-- tau) containing neurofibrillary tangles but also microgliosis, astrocytosis, and neurodegeneration mediated by metabolic dysregulation and neuroinflammation.</p><p><strong>Methods: </strong>While antibody-based therapies targeting Aβ have shown clinical promise, effective therapies targeting metabolism, neuroinflammation, and p-tau are still an urgent need. Based on the observation that Ras homolog (Rho)-associated kinases (ROCK) activities are elevated in AD, ROCK inhibitors have been explored as therapies in AD models. This study determines the effects of fasudil, a ROCK inhibitor, on neuroinflammation and metabolic regulation in the P301S tau transgenic mouse line PS19 that models neurodegenerative tauopathy and AD. Using daily intraperitoneal (i.p.) delivery of fasudil in PS19 mice, we observed a significant hippocampal-specific decrease of the levels of phosphorylated tau (pTau Ser202/Thr205), a decrease of GFAP+ cells and glycolytic enzyme Pkm1 in broad regions of the brain, and a decrease in mitochondrial complex IV subunit I in the striatum and thalamic regions.</p><p><strong>Results: </strong>Although no overt detrimental phenotype was observed, mice dosed with 100 mg/kg/day for 2 weeks exhibited significantly decreased mitochondrial outer membrane and electron transport chain (ETC) protein abundance, as well as ETC activities.</p><p><strong>Conclusion: </strong>Our results provide insights into dose-dependent neuroinflammatory and metabolic responses to fasudil and support further refinement of ROCK inhibitors for the treatment of AD.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":"183-200"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12257955/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141444016","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}

{"title":"Artificial Intelligence in Eye Movements Analysis for Alzheimer's Disease Early Diagnosis.","authors":"Shadi Farabi Maleki, Milad Yousefi, Navid Sobhi, Ali Jafarizadeh, Roohallah Alizadehsani, Juan Manuel Gorriz-Saez","doi":"10.2174/0115672050322607240529075641","DOIUrl":"10.2174/0115672050322607240529075641","url":null,"abstract":"<p><p>As the world's population ages, Alzheimer's disease is currently the seventh most common cause of death globally; the burden is anticipated to increase, especially among middle-class and elderly persons. Artificial intelligence-based algorithms that work well in hospital environments can be used to identify Alzheimer's disease. A number of databases were searched for English- language articles published up until March 1, 2024, that examined the relationships between artificial intelligence techniques, eye movements, and Alzheimer's disease. A novel non-invasive method called eye movement analysis may be able to reflect cognitive processes and identify anomalies in Alzheimer's disease. Artificial intelligence, particularly deep learning, and machine learning, is required to enhance Alzheimer's disease detection using eye movement data. One sort of deep learning technique that shows promise is convolutional neural networks, which need further data for precise classification. Nonetheless, machine learning models showed a high degree of accuracy in this context. Artificial intelligence-driven eye movement analysis holds promise for enhancing clinical evaluations, enabling tailored treatment, and fostering the development of early and precise Alzheimer's disease diagnosis. A combination of artificial intelligence-based systems and eye movement analysis can provide a window for early and non-invasive diagnosis of Alzheimer's disease. Despite ongoing difficulties with early Alzheimer's disease detection, this presents a novel strategy that may have consequences for clinical evaluations and customized medication to improve early and accurate diagnosis.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":"155-165"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141263035","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}

{"title":"A Review on the Use of Modern Computational Methods in Alzheimer's Disease-Detection and Prediction.","authors":"Arka De, Tusar Kanti Mishra, Sameeksha Saraf, Balakrushna Tripathy, Shiva Shankar Reddy","doi":"10.2174/0115672050301514240307071217","DOIUrl":"10.2174/0115672050301514240307071217","url":null,"abstract":"<p><p>Discoveries in the field of medical sciences are blooming rapidly at the cost of voluminous efforts. Presently, multidisciplinary research activities have been especially contributing to catering cutting-edge solutions to critical problems in the domain of medical sciences. The modern age computing resources have proved to be a boon in this context. Effortless solutions have become a reality, and thus, the real beneficiary patients are able to enjoy improved lives. One of the most emerging problems in this context is Alzheimer's disease, an incurable neurological disorder. For this, early diagnosis is made possible with benchmark computing tools and schemes. These benchmark schemes are the results of novel research contributions being made intermittently in the timeline. In this review, an attempt is made to explore all such contributions in the past few decades. A systematic review is made by categorizing these contributions into three folds, namely, First, Second, and Third Generations. However, priority is given to the latest ones as a handful of literature reviews are already available for the classical ones. Key contributions are discussed vividly. The objectives set for this review are to bring forth the latest discoveries in computing methodologies, especially those dedicated to the diagnosis of Alzheimer's disease. A detailed timeline of the contributions is also made available. Performance plots for certain key contributions are also presented for better graphical understanding.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":"845-861"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140103091","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}

{"title":"Analysis of Alzheimer's Disease-Related Mortality Rates Among the Elderly Populations Across the United States: An Analysis of Demographic and Regional Disparities from 1999 to 2020.","authors":"Abdul Hadi Khan, Eman Ijaz, Bushra Ubaid, Ilias Eddaki, Maliha Edhi, Muhammad Nauman Shah, George Perry","doi":"10.2174/0115672050338833240924113200","DOIUrl":"10.2174/0115672050338833240924113200","url":null,"abstract":"<p><strong>Introduction: </strong>Alzheimer's Disease (AD) is the leading cause of dementia and a significant public health concern, characterized by high incidence, mortality, and economic burden. This study analyzes the mortality patterns and demographic disparities in Alzheimer's disease-related deaths among the elderly population in the United States from 1999 through 2020.</p><p><strong>Methods: </strong>Alzheimer's disease mortality data for individuals 65 and older were obtained from the CDC WONDER database, utilizing ICD-10 codes G30.0, G30.1, G30.8, and G30.9 for identification. Demographic and regional variables included age, gender, race/ethnicity, place of death, urban- rural status, and geographic region. Crude death rates (CR) and age-adjusted mortality rates (AAMR) per 100,000 individuals were calculated. Joinpoint Regression Program 5.0.2 was used to analyze trends, calculating Annual Percentage Changes (APCs) and Average Annual Percentage Changes (AAPCs).</p><p><strong>Results: </strong>From 1999 to 2020, 1,852,432 deaths were attributed to AD among individuals aged 65 and older. The AAMR increased from 128.8 in 1999 to 254.3 in 2020, with an AAPC of 2.99% (95% CI = 2.61-3.48). The age-adjusted mortality rate (AAMR) was higher in females (218.5) than in males (163.5). Among racial and ethnic groups, non-Hispanic whites had the highest AAMR, followed by Non-Hispanic Blacks and Hispanics. Regionally, the West reported the highest AAMR, while the Northeast recorded the lowest. Most deaths occurred in nursing homes (57.3%), with a significant portion also occurring at decedents' homes (22.4%).</p><p><strong>Conclusion: </strong>AD mortality rates in the U.S. have risen significantly, with notable disparities across age, gender, race, and geographic regions. These findings highlight the need for targeted interventions and research to address the growing burden of AD, particularly among the most affected demographic groups.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":"384-394"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142515751","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}

{"title":"Multifunctional Tasks and an Energy Crisis are Crucial Players in Determining the Vulnerability of the Entorhinal Cortex to Early Damage in Alzheimer's Disease.","authors":"Senthilkumar Sivanesan, Matthew D Howell, Vibha Kaushik, Rajadas Jayakumar, Shree Mukilan Pari, Pankaj Goyal","doi":"10.2174/0115672050324909240823104209","DOIUrl":"10.2174/0115672050324909240823104209","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is a devastating neurological disorder that affects synaptic transmission between neurons. Several theories and concepts have been postulated to explain its etiology and pathogenesis. The disease has no cure, and the drugs available to manage AD symptoms provide only modest benefits. It originates in the brain's entorhinal cortex (EC), with tau pathology that poses overt symptoms for decades and then spreads to other connected areas and networks to cause severe cognitive decline. Despite decades of research, the reason why the EC is the first region to be affected during AD pathophysiology remains unknown. The EC is well connected with surrounding areas to support the brain's structural and functional integrity, participate in navigation, working memory, memory consolidation, olfaction, and olfactory-auditory coordination. These actions require massive energy expenditure, thus, the EC is extremely vulnerable to severe hypometabolism and an energy crisis. The crucial events/factors that make the EC vulnerable to pathological sequelae more than other brain regions have not been thoroughly explored. An in- -depth analysis of available research on the role of the EC in AD could provide meaningful insights into the susceptibility of this region and its role in propagating AD. In this review article, we highlight how the functional complexities of the EC account for its vulnerability to AD.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":"295-311"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142305463","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}

{"title":"Assessing the Stability of Clusters of Neuropsychiatric Symptoms in Alzheimer's Disease and Mild Cognitive Impairment.","authors":"Sara Scarfo, Yashar Moshfeghi, William J McGeown","doi":"10.2174/0115672050309014240705113444","DOIUrl":"10.2174/0115672050309014240705113444","url":null,"abstract":"<p><strong>Aim: </strong>The aim of the study was to investigate the factors that underpin neuropsychiatric symptoms and how they might evolve over time in people with Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) dementia.</p><p><strong>Background: </strong>Neuropsychiatric symptoms are psychiatric and behavioural manifestations that occur in people with AD. These are highly prevalent along the continuum of the disease, including at the stage of MCI, as well as before cognitive decline. Various small- and large-scale projects have investigated the underlying factors that underpin these symptoms; however, the identification of clear clusters is still a matter of debate; furthermore, no study has investigated how the clusters might change across the development of AD pathology by comparing different time points.</p><p><strong>Objective: </strong>Our objective was to investigate the factors that underpin neuropsychiatric symptoms in Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) and to assess how the loadings might differ based on considerations such as the disease stage of the samples.</p><p><strong>Methods: </strong>Data was obtained from the Alzheimer's Disease Neuroimaging Initiative database (adni. loni.usc.edu), using scores from the Neuropsychiatric Inventory, followed up yearly from baseline until month 72. Participant groups included those with MCI or AD dementia, or a mixture of both, with all participants presenting with at least one neuropsychiatric symptom. A series of exploratory Principal Component and Factor (Principal Axis) Analyses were performed using Direct Oblimin rotation.</p><p><strong>Results: </strong>The best-fitting structure was interpreted for each time point. A consistent, unique structure could not be identified, as the factors were unstable over time, both within the MCI and AD groups. However, some symptoms showed a tendency to load on the same factors across most measurements (i.e., agitation with irritability, depression with anxiety, elation with disinhibition, delusions with hallucinations).</p><p><strong>Conclusion: </strong>Although the analyses revealed some degree of co-occurrence of neuropsychiatric symptoms across time points/samples, there was also considerable variation. In the AD group, more discrete syndromes were evident at the early time points, whereas a more complex picture of co-occurring symptoms, with differences likely reflecting disease staging, was seen at later time points. As a clear and distinctive factor structure was not consistently identified across time points/ samples, this highlights the potential importance of sample selection (e.g., disease stage and/or heterogeneity) when studying, for example, the neurobiological underpinnings of neuropsychiatric symptoms.</p>","PeriodicalId":94309,"journal":{"name":"Current Alzheimer research","volume":" ","pages":"258-275"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141636392","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}