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OBJECTIVE: To identify internal structure validity evidence of a dysphagia screening questionnaire for caregivers of older adults with Alzheimer's disease dementia and/or vascular dementia. METHODS: The 24-question Dysphagia Screening in Older Adults with Dementia - Caregiver Questionnaire (RaDID-QC) was administered by interviewing 170 caregivers of older people with dementia, selected by convenience at the Outpatient Reference Center for Older People. Exploratory Factor Analysis (EFA) was used to assess the internal structure validity of the questionnaire, and Cronbach's alpha was used to analyze reliability. Questions with factor loadings lower than 0.45 in magnitude were removed from the final questionnaire. Multivariate multiple linear regression was used to assess the percentage of variance explained by the remaining questions. RESULTS: Kayser-Meyer-Olkin (KMO) and Bartlett's tests suggested that the questionnaire was adequate for EFA. Principal Component Analysis (PCA) suggested that 12 components captured at least 75 % of the total variance. The corresponding 12-factor EFA model showed a statistically significant fit, and 15 out of the 24 questions had factor loadings greater than 0.45. Cronbach's alpha was 0.74 for the 15 questions, which explained 71 % of the total variance in the complete dataset. The questionnaire has adequate internal structure validity and good reliability. Based on EFA, RaDID-QC decreased from 24 to 15 questions. Other internal validity and reliability parameters will be obtained by administering the questionnaire to larger target populations. CONCLUSION: The RaDID-QC applied to caregivers of older adults with dementia due to Alzheimer's disease and/or vascular dementia produced valid and reliable responses to screen dysphagia signs and symptoms.

Asunto(s)

Cuidadores , Trastornos de Deglución , Demencia , Humanos , Trastornos de Deglución/diagnóstico , Trastornos de Deglución/etiología , Encuestas y Cuestionarios/normas , Femenino , Masculino , Anciano , Reproducibilidad de los Resultados , Cuidadores/psicología , Persona de Mediana Edad , Demencia/complicaciones , Demencia/diagnóstico , Anciano de 80 o más Años , Análisis Factorial , Adulto , Tamizaje Masivo/métodos , Enfermedad de Alzheimer/complicaciones , Enfermedad de Alzheimer/diagnóstico , Demencia Vascular/diagnóstico

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BACKGROUND: The early diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains a significant challenge in neurology, with conventional methods often limited by subjectivity and variability in interpretation. Integrating deep learning with artificial intelligence (AI) in magnetic resonance imaging (MRI) analysis emerges as a transformative approach, offering the potential for unbiased, highly accurate diagnostic insights. OBJECTIVE: A meta-analysis was designed to analyze the diagnostic accuracy of deep learning of MRI images on AD and MCI models. METHODS: A meta-analysis was performed across PubMed, Embase, and Cochrane library databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, focusing on the diagnostic accuracy of deep learning. Subsequently, methodological quality was assessed using the QUADAS-2 checklist. Diagnostic measures, including sensitivity, specificity, likelihood ratios, diagnostic odds ratio, and area under the receiver operating characteristic curve (AUROC) were analyzed, alongside subgroup analyses for T1-weighted and non-T1-weighted MRI. RESULTS: A total of 18 eligible studies were identified. The Spearman correlation coefficient was -0.6506. Meta-analysis showed that the combined sensitivity and specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.84, 0.86, 6.0, 0.19, and 32, respectively. The AUROC was 0.92. The quiescent point of hierarchical summary of receiver operating characteristic (HSROC) was 3.463. Notably, the images of 12 studies were acquired by T1-weighted MRI alone, and those of the other 6 were gathered by non-T1-weighted MRI alone. CONCLUSION: Overall, deep learning of MRI for the diagnosis of AD and MCI showed good sensitivity and specificity and contributed to improving diagnostic accuracy.

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ANTECEDENTES: O diagnóstico precoce da doença de Alzheimer (DA) e do comprometimento cognitivo leve (CCL) continua sendo um desafio significativo na neurologia, com métodos convencionais frequentemente limitados pela subjetividade e variabilidade na interpretação. A integração da aprendizagem profunda com a inteligência artificial (IA) na análise de imagens de ressonância magnética surge como uma abordagem transformadora, oferecendo o potencial para insights diagnósticos imparciais e altamente precisos. OBJETIVO: Uma metanálise foi projetada para analisar a precisão diagnóstica do aprendizado profundo de imagens de ressonância magnética em modelos de DA e CCL. MéTODOS: Uma metanálise foi realizada nos bancos de dados das bibliotecas PubMed, Embase e Cochrane seguindo as diretrizes Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), com foco na precisão diagnóstica do aprendizado profundo. Posteriormente, a qualidade metodológica foi avaliada por meio do checklist QUADAS-2. Medidas diagnósticas, incluindo sensibilidade, especificidade, razões de verossimilhança, razão de chances diagnósticas e área sob a curva característica de operação do receptor (area under the receiver operating characteristic curve [AUROC]) foram analisadas, juntamente com análises de subgrupo para ressonância magnética ponderada em T1 e não ponderada em T1. RESULTADOS: Um total de 18 estudos elegíveis foram identificados. O coeficiente de correlação de Spearman foi de -0,6506. A metanálise mostrou que a sensibilidade e a especificidade combinadas, a razão de verossimilhança positiva, a razão de verossimilhança negativa e a razão de chances de diagnóstico foram 0,84, 0,86, 6,0, 0,19 e 32, respectivamente. A AUROC foi de 0,92. O ponto quiescente do resumo hierárquico da característica de operação do receptor (hierarchical summary of receiver operating characteristic [HSROC]) foi 3,463. Notavelmente, as imagens de 12 estudos foram adquiridas apenas por ressonância magnética ponderada em T1, e as dos outros 6 foram obtidas apenas por ressonância magnética não ponderada em T1. CONCLUSãO: Em geral, a aprendizagem profunda da ressonância magnética para o diagnóstico de DA e CCL mostrou boa sensibilidade e especificidade e contribuiu para melhorar a precisão diagnóstica.

Asunto(s)

Enfermedad de Alzheimer , Disfunción Cognitiva , Aprendizaje Profundo , Imagen por Resonancia Magnética , Sensibilidad y Especificidad , Humanos , Disfunción Cognitiva/diagnóstico por imagen , Disfunción Cognitiva/diagnóstico , Enfermedad de Alzheimer/diagnóstico por imagen , Enfermedad de Alzheimer/diagnóstico , Imagen por Resonancia Magnética/métodos , Diagnóstico Precoz , Curva ROC

RESUMEN

Alzheimer's disease (AD), a neurodegenerative disorder characterized by progressive cognitive decline, is the most common form of dementia. Currently, there is no single test that can diagnose AD, especially in understudied populations and developing countries. Instead, diagnosis is based on a combination of medical history, physical examination, cognitive testing, and brain imaging. Exosomes are extracellular nanovesicles, primarily composed of RNA, that participate in physiological processes related to AD pathogenesis such as cell proliferation, immune response, and neuronal and cardiovascular function. However, the identification and understanding of the potential role of long non-coding RNAs (lncRNAs) in AD diagnosis remain largely unexplored. Here, we clinically, cognitively, and genetically characterized a sample of 15 individuals diagnosed with AD (cases) and 15 controls from Barranquilla, Colombia. Advanced bioinformatics, analytics and Machine Learning (ML) techniques were used to identify lncRNAs differentially expressed between cases and controls. The expression of 28,909 lncRNAs was quantified. Of these, 18 were found to be differentially expressed and harbored in pivotal genes related to AD. Two lncRNAs, ENST00000608936 and ENST00000433747, show promise as diagnostic markers for AD, with ML models achieving > 95% sensitivity, specificity, and accuracy in both the training and testing datasets. These findings suggest that the expression profiles of lncRNAs could significantly contribute to advancing personalized AD diagnosis in this community, offering promising avenues for early detection and follow-up.

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Enfermedad de Alzheimer , ARN Largo no Codificante , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/genética , Humanos , ARN Largo no Codificante/genética , Femenino , Masculino , Anciano , Medicina de Precisión/métodos , Biomarcadores , Aprendizaje Automático , Anciano de 80 o más Años , Estudios de Casos y Controles , Perfilación de la Expresión Génica/métodos , Biología Computacional/métodos

RESUMEN

Background: The Addenbrooke's Cognitive Examination-Revised (ACE-R) is an accessible cognitive tool that supports the early detection of mild cognitive impairment (MCI), Alzheimer's disease (AD), and behavioral variant frontotemporal dementia (bvFTD). Objective: To investigate the diagnostic efficacy of the ACE-R in MCI, AD, and bvFTD through the identification of novel coefficients for differentiation between these diseases. Methods: We assessed 387 individuals: 102 mild AD, 37 mild bvFTD, 87 with amnestic MCI patients, and 161 cognitively unimpaired controls. The Mokken scaling technique facilitated the extraction out of the 26 ACE-R items that exhibited a common latent trait, thereby generating the Mokken scales for the AD group and the MCI group. Subsequently, we performed logistic regression, integrating each Mokken scales with sociodemographic factors, to differentiate between AD and bvFTD, as well as between AD or MCI and control groups. Ultimately, the Receiver Operating Characteristic curve analysis was employed to assess the efficacy of the coefficient's discrimination. Results: The AD-specific Mokken scale (AD-MokACE-R) versus bvFTD exhibited an Area Under the Curve (AUC) of 0.922 (88% sensitivity and specificity). The AD-MokACE-R versus controls achieved an AUC of 0.968 (93% sensitivity, 94% specificity). The MCI-specific scale (MCI-MokACE-R) versus controls demonstrated an AUC of 0.859 (78% sensitivity, 79% specificity). Conclusions: The ACE-R's capacity is enhanced through statistical methods and demographic integration, allowing for accurate differentiation between AD and bvFTD, as well as between MCI and controls. This new method not only reinforces its clinical value in early diagnosis but also surpasses traditional approaches noted in prior studies.

Asunto(s)

Enfermedad de Alzheimer , Disfunción Cognitiva , Demencia Frontotemporal , Pruebas Neuropsicológicas , Humanos , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/psicología , Femenino , Masculino , Disfunción Cognitiva/diagnóstico , Demencia Frontotemporal/diagnóstico , Demencia Frontotemporal/psicología , Anciano , Pruebas Neuropsicológicas/estadística & datos numéricos , Persona de Mediana Edad , Diagnóstico Diferencial , Sensibilidad y Especificidad

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The nervous system is rich in miRNAs, indicating an important role of these molecules in regulating processes associated with cognition, memory, and others. Therefore, qualitative and quantitative imbalances involving such miRNAs may be involved in dementia contexts, including Late-Onset Alzheimer's Disease (LOAD). To test the viability of circulating miRNAs (c-miRNAs) as biomarkers for LOAD, we proceed accordingly to the following reasoning. The first stage was to discover and identify profile of c-miRNAs by RNA sequencing (RNA-Seq). For this purpose, blood serum samples were used from LOAD patients (n = 5) and cognitively healthy elderly control group (CTRL_CH) (n = 5), all over 70 years old. We identified seven c-miRNAs differentially expressed (p ≤ 0.05) in the serum of LOAD patients compared to CTRL_CH (miR-10a-5p; miR-29b-2-5p; miR-125a-5p; miR-342-3p, miR-708-5p, miR-380-5p and miR-340-3p). Of these, five (p ≤ 0.01) were selected for in silico analysis (miR-10a-5p; miR-29b-2-5p; miR-125a-5p; miR-342-3p, miR-708-5p), for which 44 relevant target genes were found regulated by these c-miRNAs and related to LOAD. Through the analysis of these target genes in databases, it was possible to observe that they have functions related to the development and progress of LOAD, directly or indirectly connecting the different Alzheimer's pathways. Thus, this work found five promising serum c-miRNAs as options for biomarkers contributing to LOAD diagnosis. Our study shows the complex network between these molecules and LOAD, supporting the relevance of studies using c-miRNAs in dementia contexts.

Asunto(s)

Enfermedad de Alzheimer , Biomarcadores , MicroARNs , Humanos , Enfermedad de Alzheimer/sangre , Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/diagnóstico , MicroARNs/sangre , MicroARNs/genética , Masculino , Anciano , Biomarcadores/sangre , Femenino , Anciano de 80 o más Años

RESUMEN

BACKGROUND: Variants in APOE and PSEN1 (encoding apolipoprotein E and presenilin 1, respectively) alter the risk of Alzheimer's disease. We previously reported a delay of cognitive impairment in a person with autosomal dominant Alzheimer's disease caused by the PSEN1 E280A variant who also had two copies of the apolipoprotein E3 Christchurch variant (APOE3 Ch). Heterozygosity for the APOE3 Ch variant may influence the age at which the onset of cognitive impairment occurs. We assessed this hypothesis in a population in which the PSEN1 E280A variant is prevalent. METHODS: We analyzed data from 27 participants with one copy of the APOE3 Ch variant among 1077 carriers of the PSEN1 E280A variant in a kindred from Antioquia, Colombia, to estimate the age at the onset of cognitive impairment and dementia in this group as compared with persons without the APOE3 Ch variant. Two participants underwent brain imaging, and autopsy was performed in four participants. RESULTS: Among carriers of PSEN1 E280A who were heterozygous for the APOE3 Ch variant, the median age at the onset of cognitive impairment was 52 years (95% confidence interval [CI], 51 to 58), in contrast to a matched group of PSEN1 E280A carriers without the APOE3 Ch variant, among whom the median age at the onset was 47 years (95% CI, 47 to 49). In two participants with the APOE3 Ch and PSEN1 E280A variants who underwent brain imaging, 18F-fluorodeoxyglucose positron-emission tomographic (PET) imaging showed relatively preserved metabolic activity in areas typically involved in Alzheimer's disease. In one of these participants, who underwent 18F-flortaucipir PET imaging, tau findings were limited as compared with persons with PSEN1 E280A in whom cognitive impairment occurred at the typical age in this kindred. Four studies of autopsy material obtained from persons with the APOE3 Ch and PSEN1 E280A variants showed fewer vascular amyloid pathologic features than were seen in material obtained from persons who had the PSEN1 E280A variant but not the APOE3 Ch variant. CONCLUSIONS: Clinical data supported a delayed onset of cognitive impairment in persons who were heterozygous for the APOE3 Ch variant in a kindred with a high prevalence of autosomal dominant Alzheimer's disease. (Funded by Good Ventures and others.).

Asunto(s)

Enfermedad de Alzheimer , Apolipoproteína E3 , Presenilina-1 , Adulto , Anciano , Femenino , Humanos , Masculino , Persona de Mediana Edad , Edad de Inicio , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/diagnóstico por imagen , Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/patología , Apolipoproteína E3/genética , Encéfalo/patología , Encéfalo/diagnóstico por imagen , Colombia , Familia , Genes Dominantes , Heterocigoto , Tomografía de Emisión de Positrones , Presenilina-1/genética , Estudios Retrospectivos

RESUMEN

Dementia can disrupt how people experience and describe events as well as their own role in them. Alzheimer's disease (AD) compromises the processing of entities expressed by nouns, while behavioral variant frontotemporal dementia (bvFTD) entails a depersonalized perspective with increased third-person references. Yet, no study has examined whether these patterns can be captured in connected speech via natural language processing tools. To tackle such gaps, we asked 96 participants (32 AD patients, 32 bvFTD patients, 32 healthy controls) to narrate a typical day of their lives and calculated the proportion of nouns, verbs, and first- or third-person markers (via part-of-speech and morphological tagging). We also extracted objective properties (frequency, phonological neighborhood, length, semantic variability) from each content word. In our main study (with 21 AD patients, 21 bvFTD patients, and 21 healthy controls), we used inferential statistics and machine learning for group-level and subject-level discrimination. The above linguistic features were correlated with patients' scores in tests of general cognitive status and executive functions. We found that, compared with HCs, (i) AD (but not bvFTD) patients produced significantly fewer nouns, (ii) bvFTD (but not AD) patients used significantly more third-person markers, and (iii) both patient groups produced more frequent words. Machine learning analyses showed that these features identified individuals with AD and bvFTD (AUC = 0.71). A generalizability test, with a model trained on the entire main study sample and tested on hold-out samples (11 AD patients, 11 bvFTD patients, 11 healthy controls), showed even better performance, with AUCs of 0.76 and 0.83 for AD and bvFTD, respectively. No linguistic feature was significantly correlated with cognitive test scores in either patient group. These results suggest that specific cognitive traits of each disorder can be captured automatically in connected speech, favoring interpretability for enhanced syndrome characterization, diagnosis, and monitoring.

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Enfermedad de Alzheimer , Demencia Frontotemporal , Habla , Humanos , Demencia Frontotemporal/psicología , Demencia Frontotemporal/diagnóstico , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/psicología , Femenino , Masculino , Anciano , Persona de Mediana Edad , Estudios de Casos y Controles , Biomarcadores , Procesamiento de Lenguaje Natural , Aprendizaje Automático , Pruebas Neuropsicológicas , Función Ejecutiva/fisiología

RESUMEN

BACKGROUND: The number of individuals diagnosed with Alzheimer's disease (AD) has increased, and it is estimated to continue rising in the coming years. The diagnosis of this disease is challenging due to variations in onset and course, its diverse clinical manifestations, and the indications for measuring deposit biomarkers. Hence, there is a need to develop more precise and less invasive diagnostic tools. Multiple studies have considered using electroencephalography (EEG) entropy measures as an indicator of the onset and course of AD. Entropy is deemed suitable as a potential indicator based on the discovery that variations in its complexity can be associated with specific pathologies such as AD. METHODOLOGY: Following PRISMA guidelines, a literature search was conducted in 4 scientific databases, and 40 articles were analyzed after discarding and filtering. RESULTS: There is a diversity in entropy measures; however, Sample Entropy (SampEn) and Multiscale Entropy (MSE) are the most widely used (21/40). In general, it is found that when comparing patients with controls, patients exhibit lower entropy (20/40) in various areas. Findings of correlation with the level of cognitive decline are less consistent, and with neuropsychiatric symptoms (2/40) or treatment response less explored (2/40), although most studies show lower entropy with greater severity. Machine learning-based studies show good discrimination capacity. CONCLUSIONS: There is significant difficulty in comparing multiple studies due to their heterogeneity; however, changes in Multiscale Entropy (MSE) scales or a decrease in entropy levels are considered useful for determining the presence of AD and measuring its severity.

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Enfermedad de Alzheimer , Electroencefalografía , Entropía , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/fisiopatología , Humanos , Electroencefalografía/métodos

RESUMEN

The use of nanomaterials in medicine offers multiple opportunities to address neurodegenerative disorders such as Alzheimer's and Parkinson's disease. These diseases are a significant burden for society and the health system, affecting millions of people worldwide without sensitive and selective diagnostic methodologies or effective treatments to stop their progression. In this sense, the use of gold nanoparticles is a promising tool due to their unique properties at the nanometric level. They can be functionalized with specific molecules to selectively target pathological proteins such as Tau and α-synuclein for Alzheimer's and Parkinson's disease, respectively. Additionally, these proteins are used as diagnostic biomarkers, wherein gold nanoparticles play a key role in enhancing their signal, even at the low concentrations present in biological samples such as blood or cerebrospinal fluid, thus enabling an early and accurate diagnosis. On the other hand, gold nanoparticles act as drug delivery platforms, bringing therapeutic agents directly into the brain, improving treatment efficiency and precision, and reducing side effects in healthy tissues. However, despite the exciting potential of gold nanoparticles, it is crucial to address the challenges and issues associated with their use in the medical field before they can be widely applied in clinical settings. It is critical to ensure the safety and biocompatibility of these nanomaterials in the context of the central nervous system. Therefore, rigorous preclinical and clinical studies are needed to assess the efficacy and feasibility of these strategies in patients. Since there is scarce and sometimes contradictory literature about their use in this context, the main aim of this review is to discuss and analyze the current state-of-the-art of gold nanoparticles in relation to delivery, diagnosis, and therapy for Alzheimer's and Parkinson's disease, as well as recent research about their use in preclinical, clinical, and emerging research areas.

Asunto(s)

Oro , Nanopartículas del Metal , Enfermedades Neurodegenerativas , alfa-Sinucleína , Proteínas tau , Humanos , Oro/química , Nanopartículas del Metal/química , Nanopartículas del Metal/uso terapéutico , Proteínas tau/metabolismo , Animales , Enfermedades Neurodegenerativas/tratamiento farmacológico , Enfermedades Neurodegenerativas/diagnóstico , Enfermedad de Parkinson/diagnóstico , Enfermedad de Parkinson/tratamiento farmacológico , Enfermedad de Alzheimer/tratamiento farmacológico , Enfermedad de Alzheimer/diagnóstico , Sistemas de Liberación de Medicamentos/métodos , Biomarcadores

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INTRODUCTION: While Latin America (LatAm) is facing an increasing burden of dementia due to the rapid aging of the population, it remains underrepresented in dementia research, diagnostics, and care. METHODS: In 2023, the Alzheimer's Association hosted its eighth satellite symposium in Mexico, highlighting emerging dementia research, priorities, and challenges within LatAm. RESULTS: Significant initiatives in the region, including intracountry support, showcased their efforts in fostering national and international collaborations; genetic studies unveiled the unique genetic admixture in LatAm; researchers conducting emerging clinical trials discussed ongoing culturally specific interventions; and the urgent need to harmonize practices and studies, improve diagnosis and care, and use affordable biomarkers in the region was highlighted. DISCUSSION: The myriad of topics discussed at the 2023 AAIC satellite symposium highlighted the growing research efforts in LatAm, providing valuable insights into dementia biology, genetics, epidemiology, treatment, and care.

Asunto(s)

Demencia , Humanos , Demencia/terapia , Demencia/diagnóstico , Demencia/genética , Demencia/epidemiología , América Latina/epidemiología , México/epidemiología , Enfermedad de Alzheimer/terapia , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/genética , Investigación Biomédica , Congresos como Asunto

RESUMEN

INTRODUCTION: Low educational attainment is a potential risk factor for Alzheimer's disease (AD) development. Alpha-secretase ADAM10 plays a central role in AD pathology, attenuating the formation of beta-amyloid peptides and, therefore, their aggregation into senile plaques. This study seeks to investigate ADAM10 as a blood-based biomarker in mild cognitive impairment (MCI) and AD in a diverse group of community-dwelling older adults, focusing on those with limited educational attainment. METHODS: Participants were recruited from public health services. Cognition was evaluated using Mini-Mental State Examination (MMSE) and Addenbrooke's Cognitive Examination - Revised (ACE-R) batteries. Blood samples were collected to analyze plasma ADAM10 levels. A logistic regression was conducted to verify the influence of plasma ADAM10 on the AD diagnosis. RESULTS: Significant differences in age, years of education, prescribed medications, and cognitive test scores were found between the MCI and AD groups. Regarding cognitive performance, both ACE-R and MMSE scores displayed significant differences between groups, with post hoc analyses highlighting these distinctions, particularly between AD and cognitively unimpaired individuals. Elevated plasma ADAM10 levels were associated with a 4.5-fold increase in the likelihood of a diagnosis of MCI and a 5.9-fold increase in the likelihood of a diagnosis of AD. These findings suggest ADAM10 levels in plasma as a valuable biomarker for assessing cognitive status in older individuals with low education attainment. CONCLUSION: This study underscores the potential utility of plasma ADAM10 levels as a blood-based biomarker for cognitive status, especially in individuals with low educational backgrounds, shedding light on their relevance in AD development and diagnosis.

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Proteína ADAM10 , Enfermedad de Alzheimer , Biomarcadores , Disfunción Cognitiva , Escolaridad , Humanos , Proteína ADAM10/sangre , Enfermedad de Alzheimer/sangre , Enfermedad de Alzheimer/diagnóstico , Anciano , Masculino , Femenino , Disfunción Cognitiva/sangre , Disfunción Cognitiva/diagnóstico , Biomarcadores/sangre , Anciano de 80 o más Años , Proteínas de la Membrana/sangre , Pruebas Neuropsicológicas , Pruebas de Estado Mental y Demencia , Secretasas de la Proteína Precursora del Amiloide/sangre

RESUMEN

The field of blood-based biomarkers for Alzheimer's disease (AD) has advanced at an incredible pace, especially after the development of sensitive analytic platforms that can facilitate large-scale screening. Such screening will be important when more sophisticated diagnostic methods are scarce and expensive. Thus, blood-based biomarkers can potentially reduce diagnosis inequities among populations from different socioeconomic contexts. This large-scale screening can be performed so that older adults at risk of cognitive decline assessed using these methods can then undergo more complete assessments with classic biomarkers, increasing diagnosis efficiency and reducing costs to the health systems. Blood-based biomarkers can also aid in assessing the effect of new disease-modifying treatments. This paper reviews recent advances in the area, focusing on the following leading candidates for blood-based biomarkers: amyloid-beta (Aß), phosphorylated tau isoforms (p-tau), neurofilament light (NfL), and glial fibrillary acidic (GFAP) proteins, as well as on new candidates, Neuron-Derived Exosomes contents (NDEs) and Transactive response DNA-binding protein-43 (TDP-43), based on data from longitudinal observational cohort studies. The underlying challenges of validating and incorporating these biomarkers into routine clinical practice and primary care settings are also discussed. Importantly, challenges related to the underrepresentation of ethnic minorities and socioeconomically disadvantaged persons must be considered. If these challenges are overcome, a new time of cost-effective blood-based biomarkers for AD could represent the future of clinical procedures in the field and, together with continued prevention strategies, the beginning of an era with a lower incidence of dementia worldwide.

Asunto(s)

Enfermedad de Alzheimer , Disfunción Cognitiva , Humanos , Anciano , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/psicología , Péptidos beta-Amiloides , Disfunción Cognitiva/diagnóstico , Estudios de Cohortes , Biomarcadores , Proteínas tau

RESUMEN

Alzheimer's disease (AD) is the most common type and accounts for 60%-70% of the reported cases of dementia. MicroRNAs (miRNAs) are small non-coding RNAs that play a crucial role in gene expression regulation. Although the diagnosis of AD is primarily clinical, several miRNAs have been associated with AD and considered as potential markers for diagnosis and progression of AD. We sought to match AD-related miRNAs in cerebrospinal fluid (CSF) found in the GeoDataSets, evaluated by machine learning, with miRNAs listed in a systematic review, and a pathway analysis. Using machine learning approaches, we identified most differentially expressed miRNAs in Gene Expression Omnibus (GEO), which were validated by the systematic review, using the acronym PECO-Population (P): Patients with AD, Exposure (E): expression of miRNAs, Comparison (C): Healthy individuals, and Objective (O): miRNAs differentially expressed in CSF. Additionally, pathway enrichment analysis was performed to identify the main pathways involving at least four miRNAs selected. Four miRNAs were identified for differentiating between patients with and without AD in machine learning combined to systematic review, and followed the pathways analysis: miRNA-30a-3p, miRNA-193a-5p, miRNA-143-3p, miRNA-145-5p. The pathways epidermal growth factor, MAPK, TGF-beta and ATM-dependent DNA damage response, were regulated by these miRNAs, but only the MAPK pathway presented higher relevance after a randomic pathway analysis. These findings have the potential to assist in the development of diagnostic tests for AD using miRNAs as biomarkers, as well as provide understanding of the relationship between different pathophysiological mechanisms of AD.

Asunto(s)

Enfermedad de Alzheimer , Minería de Datos , Aprendizaje Automático , MicroARNs , Enfermedad de Alzheimer/líquido cefalorraquídeo , Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/diagnóstico , Humanos , MicroARNs/líquido cefalorraquídeo , MicroARNs/genética , Biomarcadores/líquido cefalorraquídeo

RESUMEN

While Alzheimer's disease (AD) diagnosis, management, and care have become priorities for healthcare providers and researcher's worldwide due to rapid population aging, epidemiologic surveillance efforts are currently limited by costly, invasive diagnostic procedures, particularly in low to middle income countries (LMIC). In recent years, wastewater-based epidemiology (WBE) has emerged as a promising tool for public health assessment through detection and quantification of specific biomarkers in wastewater, but applications for non-infectious diseases such as AD remain limited. This early review seeks to summarize AD-related biomarkers and urine and other peripheral biofluids and discuss their potential integration to WBE platforms to guide the first prospective efforts in the field. Promising results have been reported in clinical settings, indicating the potential of amyloid ß, tau, neural thread protein, long non-coding RNAs, oxidative stress markers and other dysregulated metabolites for AD diagnosis, but questions regarding their concentration and stability in wastewater and the correlation between clinical levels and sewage circulation must be addressed in future studies before comprehensive WBE systems can be developed.

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Enfermedad de Alzheimer , Humanos , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/epidemiología , Péptidos beta-Amiloides , Monitoreo Epidemiológico Basado en Aguas Residuales , Aguas Residuales , Estudios Prospectivos , Biomarcadores

RESUMEN

INTRODUCTION: Verbal fluency tasks are common in Alzheimer's disease (AD) assessments. Yet, standard valid response counts fail to reveal disease-specific semantic memory patterns. Here, we leveraged automated word-property analysis to capture neurocognitive markers of AD vis-à-vis behavioral variant frontotemporal dementia (bvFTD). METHODS: Patients and healthy controls completed two fluency tasks. We counted valid responses and computed each word's frequency, granularity, neighborhood, length, familiarity, and imageability. These features were used for group-level discrimination, patient-level identification, and correlations with executive and neural (magnetic resonanance imaging [MRI], functional MRI [fMRI], electroencephalography [EEG]) patterns. RESULTS: Valid responses revealed deficits in both disorders. Conversely, frequency, granularity, and neighborhood yielded robust group- and subject-level discrimination only in AD, also predicting executive outcomes. Disease-specific cortical thickness patterns were predicted by frequency in both disorders. Default-mode and salience network hypoconnectivity, and EEG beta hypoconnectivity, were predicted by frequency and granularity only in AD. DISCUSSION: Word-property analysis of fluency can boost AD characterization and diagnosis. HIGHLIGHTS: We report novel word-property analyses of verbal fluency in AD and bvFTD. Standard valid response counts captured deficits and brain patterns in both groups. Specific word properties (e.g., frequency, granularity) were altered only in AD. Such properties predicted cognitive and neural (MRI, fMRI, EEG) patterns in AD. Word-property analysis of fluency can boost AD characterization and diagnosis.

Asunto(s)

Enfermedad de Alzheimer , Demencia Frontotemporal , Humanos , Enfermedad de Alzheimer/diagnóstico , Pruebas Neuropsicológicas , Encéfalo/diagnóstico por imagen , Memoria , Imagen por Resonancia Magnética , Demencia Frontotemporal/diagnóstico , Trastornos de la Memoria

RESUMEN

There are doubts about vehicle driving restriction for patients with Alzheimer's disease. A scoping review was carried out using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-ScR) methodology. Relevant databases were searched for articles published between 2000 and 2022 in English, Spanish, or Portuguese. Articles were included if they specifically addressed driving, risk of accidents, permission or licence to drive a motor vehicle in a context of important cognitive decline, or if addressed traffic legislation on driving and dementia. Twenty-three articles were selected for full reading, six of which were observational studies and only one with an interventionist method. All articles were carried out in high-income countries such as the UK, the US, and Australia. As a conclusion, there is no psychometric test in the literature sensitive enough to assess vehicle driving competence in older adults with cognitive deficits. Based on selected studies, there is no robust evidence to make recommendation for or against the cessation of vehicular driving for patients with mild cognitive decline or with mild dementia. In some situations, vehicle driving cessation can impact patients and their families. In addition, legal regulations regarding vehicle driving for older adults and people with dementia are scarce worldwide. Despite the scarcity of studies addressing the theme of vehicle driving in the context of dementia, there is some level of consensual reasoning that patients with moderate to severe dementia should halt driving activities, but the same does not apply for patients with mild levels of cognitive impairment, including mild dementia.

Asunto(s)

Enfermedad de Alzheimer , Conducción de Automóvil , Anciano , Humanos , Enfermedad de Alzheimer/diagnóstico , Trastornos del Conocimiento , Disfunción Cognitiva/diagnóstico , Demencia/diagnóstico , Demencia/psicología , Estudios Observacionales como Asunto

RESUMEN

BACKGROUND: Studies have shown that A Disintegrin and Metalloproteinase 10 (ADAM10) is the main α-secretase in the non-amyloidogenic cleavage of the amyloid precursor protein (APP), avoiding the production of amyloid-ß peptide (Aß), one of the pathological hallmarks of Alzheimer's disease (AD). OBJECTIVE: To investigate ADAM10 from cerebrospinal fluid (CSF) and plasma/serum as a potential biomarker for AD. METHODS: A systematic review was carried out in the MEDLINE/PubMed, Web of Science, Embase, and Scopus databases using the terms and Boolean operators: "Alzheimer" AND "ADAM10" AND "biomarker". Citation searching was also adopted. The inclusion criteria were original studies of ADAM10 in blood or CSF in patients with AD. The risk of bias was assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. The analysis methods were registered in the PROSPERO database (#CRD42021274239). RESULTS: Of the 97 records screened, 17 were included. There is strong evidence for lower levels of ADAM10 in platelets of persons with AD compared to cognitively healthy participants. On the other hand, higher levels of ADAM10 were found in plasma. Regarding CSF, controversial results were found with lower and higher levels of ADAM10 in persons with AD compared to healthy older adults. The differences may be due to diverse reasons, including different sample collection and processing and different antibodies, highlighting the importance of standardizing the experiments and choosing the appropriate antibodies for ADAM10 detection. CONCLUSION: Evidence shows that ADAM10 levels are altered in platelets, plasma, serum, and CSF of individuals with AD. The alteration was evident in all stages of the disease, and therefore, the protein may represent a complementary biomarker for the disease. However, more studies must be performed to establish cut-off values for ADAM10 levels to discriminate AD participants from cognitively unimpaired older adults.

Asunto(s)

Enfermedad de Alzheimer , Humanos , Anciano , Enfermedad de Alzheimer/diagnóstico , Estudios Transversales , Proteína ADAM10/metabolismo , Péptidos beta-Amiloides/líquido cefalorraquídeo , Biomarcadores , Secretasas de la Proteína Precursora del Amiloide/metabolismo , Proteínas de la Membrana/líquido cefalorraquídeo

RESUMEN

PURPOSE: Early impairments in spoken discourse abilities have been identified in Alzheimer's disease (AD). However, the impact of AD on spoken discourse and the associated neuroanatomical correlates have mainly been studied in populations with higher levels of education, although preliminary evidence seems to indicate that socioeconomic status (SES) and level of education have an impact on spoken discourse. The purpose of this study was to analyze microstructural variables in spoken discourse in people with AD with low-to-middle SES and low level of education and to study their association with gray matter (GM) density. METHOD: Nine women with AD and 10 matched (age, SES, and education) women without brain injury (WWBI) underwent a neuropsychological assessment, which included two spoken discourse tasks, and structural magnetic resonance imaging. Microstructural variables were extracted from the discourse samples using NILC-Metrix software. Brain density, measured by voxel-based morphometry, was compared between groups and then correlated with the differentiating microstructural variables. RESULTS: The AD group produced a lower diversity of verbal time moods and fewer words and sentences than WWBI but a greater diversity of pronouns, prepositions, and lexical richness. At the neural level, the AD group presented a lower GM density bilaterally in the hippocampus, the inferior temporal gyrus, and the anterior cingulate gyrus. Number of words and sentences produced were associated with GM density in the left parahippocampal gyrus, whereas the diversity of verbal moods was associated with the basal ganglia and the anterior cingulate gyrus bilaterally. CONCLUSIONS: The present findings are mainly consistent with previous studies conducted in groups with higher levels of SES and education, but they suggest that atrophy in the left inferior temporal gyrus could be critical in AD in populations with lower levels of SES and education. This research provides evidence on the importance of pursuing further studies including people with various SES and education levels. WHAT IS ALREADY KNOWN ON THIS SUBJECT: Spoken discourse has been shown to be affected in Alzheimer disease, but most studies have been conducted on individuals with middle-to-high SES and high educational levels. WHAT THIS STUDY ADDS: The study reports on microstructural measures of spoken discourse in groups of women in the early stage of AD and healthy women, with low-to-middle SES and lower levels of education. CLINICAL IMPLICATIONS OF THIS STUDY: This study highlights the importance of taking into consideration the SES and education level in spoken discourse analysis and in investigating the neural correlates of AD. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.24905046.

Asunto(s)

Enfermedad de Alzheimer , Humanos , Femenino , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/psicología , Encéfalo , Hipocampo/patología , Escolaridad , Clase Social , Imagen por Resonancia Magnética/métodos

RESUMEN

Alzheimer's disease (AD) is a well-known chronic neurodegenerative disorder that leads to the progressive death of brain cells, resulting in memory loss and the loss of other critical body functions. In March 2019, one of the major pharmaceutical companies and its partners announced that currently, there is no drug to cure AD, and all clinical trials of the new ones have been cancelled, leaving many people without hope. However, despite the clear message and startling reality, the research continued. Finally, in the last two years, the Food and Drug Administration (FDA) approved the first-ever medications to treat Alzheimer's, aducanumab and lecanemab. Despite researchers' support of this decision, there are serious concerns about their effectiveness and safety. The validation of aducanumab by the Centers for Medicare and Medicaid Services is still pending, and lecanemab was authorized without considering data from the phase III trials. Furthermore, numerous reports suggest that patients have died when undergoing extended treatment. While there is evidence that aducanumab and lecanemab may provide some relief to those suffering from AD, their impact remains a topic of ongoing research and debate within the medical community. The fact is that even though there are considerable efforts regarding pharmacological treatment, no definitive cure for AD has been found yet. Nevertheless, it is strongly believed that modern nanotechnology holds promising solutions and effective clinical strategies for the development of diagnostic tools and treatments for AD. This review summarizes the major hallmarks of AD, its etiological mechanisms, and challenges. It explores existing diagnostic and therapeutic methods and the potential of nanotechnology-based approaches for recognizing and monitoring patients at risk of irreversible neuronal degeneration. Overall, it provides a broad overview for those interested in the evolving areas of clinical neuroscience, AD, and related nanotechnology. With further research and development, nanotechnology-based approaches may offer new solutions and hope for millions of people affected by this devastating disease.

Asunto(s)

Enfermedad de Alzheimer , Anciano , Humanos , Estados Unidos , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/tratamiento farmacológico , Medicare , Encéfalo , Nanotecnología

RESUMEN

In Alzheimer's disease (AD), the age of onset (AoO) exhibits considerable variability, spanning from 40 to 90 years. Specifically, individuals diagnosed with AD and exhibiting symptoms prior to the age of 65 are typically classified as early onset (EOAD) cases. Notably, the apolipoprotein E (APOE) ε4 allele represents the most extensively studied genetic risk factor associated with AD. We clinically characterized and genotyped the APOEε4 allele from 101 individuals with a diagnosis of EOAD, and 69 of them were affected carriers of the autosomal dominant fully penetrant PSEN1 variant c.1292C>A (rs63750083, A431E) (PSEN1+ group), while there were 32 patients in which the genetic cause was unknown (PSEN1- group). We found a correlation between the AoO and the APOEε4 allele; patients carrying at least one APOEε4 allele showed delays, in AoO in patients in the PSEN1+ and PSEN1- groups, of 3.9 (p = 0.001) and 8.6 years (p = 0.012), respectively. The PSEN1+ group presented higher frequencies of gait disorders compared to PSEN1- group, and apraxia was more frequent with PSEN1+/APOE4+ than in the rest of the subgroup. This study shows what appears to be an inverse effect of APOEε4 in EOAD patients, as it delays AoO and modifies clinical manifestations.

Asunto(s)

Enfermedad de Alzheimer , Adulto , Anciano , Anciano de 80 o más Años , Humanos , Persona de Mediana Edad , Edad de Inicio , Alelos , Enfermedad de Alzheimer/diagnóstico , Apolipoproteína E4/genética , Genotipo , Presenilina-1/genética