Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring最新文献

Introduction: Timely detection and tracking of Alzheimer's disease (AD) -related cognitive decline has become a public health priority. We investigated whether the NIH Toolbox for Assessment of Neurological and Behavioral Function-Cognition Battery (NIHTB-CB) detects AD-related cognitive decline.

Methods: N = 171 participants (age 76.5 ± 8; 53% female, 34% Aβ-positive) from the ARMADA study completed the NIHTB-CB at baseline, 12 months, and 24 months. Linear mixed-effect models correcting for demographics were used to examine cross-sectional and longitudinal NIHTB-CB scores in individuals across the clinical AD spectrum.

Results: Compared to Aβ-negative healthy controls, Aβ-positive individuals with amnestic MCI or mild AD performed worse on all NIHTB-CB measures and showed an accelerated decline in processing speed, working memory, and auditory word comprehension tests.

Discussion: These findings support the use of the NIHTB-CB in early AD, but also imply that the optimal NIHTB-CB composite score to detect change over time may differ across clinical stages of AD. Future directions include replication of these findings in larger and more demographically diverse samples.

Highlights: We examined NIH Toolbox-Cognition Battery scores across the clinical AD spectrum.All NIH Toolbox tests detected cross-sectional cognitive impairment in MCI-to-mild AD.Three NIH Toolbox tests captured further decline over time in MCI-to-mild AD.The NIH Toolbox can facilitate timely detection of AD-related cognitive decline.

Introduction: This study aimed to identify cognitive tests that optimally relate to tau positron emission tomography (PET) signal in the inferior temporal cortex (ITC), a neocortical region associated with early tau accumulation in Alzheimer's disease (AD).

Methods: We analyzed cross-sectional data from the harvard aging brain study (HABS) (n = 128) and the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) study (n = 393). We used elastic net regression to identify the most robust cognitive correlates of tau PET signal in the ITC. Secondary analyses examined whether the cognitive correlates remained significantly associated with tau after adjusting for structural brain measures.

Results: Episodic memory measures, including both total and "process" scores, were the most robust correlates of ITC tau across both cohorts. These cognitive test scores remained significant after accounting for structural brain measures.

Discussion: These findings highlight the potential of specific episodic memory test scores to detect and monitor neuropathological changes associated with early AD.

Highlights: Machine learning identified cognitive correlates of early Alzheimer's disease tau burden.Both traditional and process scores predicted early tau burden.Episodic memory scores were among the strongest correlates.Cognitive scores remained significant after accounting for structural brain measures.

Introduction: Alzheimer's disease (AD) involves neuroinflammation and amyloid plaque deposition, yet the role of amyloid-reactive immune response in neurodegeneration remains unclear. We investigate amyloid-reactive T cell levels in the Epidemiology of Mild Cognitive Impairment Study in Taiwan (EMCIT) and Taiwan Precision Medicine Initiative of Cognitive Impairment and Dementia (TPMIC) cohorts.

Method: Using diverse amyloid peptide formulations, we established a polyfunctionality assay for five T cell functions and compared mild cognitive impairment (MCI) patients to control subjects in both cohorts.

Results: In both cohorts, MCI individuals exhibit higher amyloid-reactive T cell responses than controls. In the TPMIC cohort, CD4+ and CD8+ total response frequencies are notably elevated in MCI (CD4: 1.3%, CD8: 1.91%) versus controls (CD4: 0.15%, CD8: 0.28%; both p < 0.001). Amyloid-reactive T cell response outperforms plasma phosphorylated tau 181 (p-tau181) in discriminating MCI (area under the receiver operating characteristic curve CD4+: 0.97; CD8+: 0.96; p-tau181: 0.72; both p < 0.001).

Discussion: Amyloid-reactive T cell polyfunctional response distinguishes MCI from normal aging and could serve as a novel MCI biomarker.

Highlights: Amyloid-reactive polyfunctional T cell responses can be detected in the peripheral circulation.Amyloid-reactive T cell response is significantly enhanced in individuals with mild cognitive impairment compared to age-matched, cognitively unimpaired individuals.The unique discriminative accuracy of amyloid-reactive T cell response is significantly higher than phosphorylated tau181 and is not a result of overall T cell hyperreactivity.Future studies are needed to determine the predictive role of amyloid-reactive T cell responses in disease progression and if the amyloid-reactive immune response could be a therapeutic target for the treatment of neurodegeneration.

A systematic review and meta-analysis examined the impact of gut microbiota in Alzheimer's disease (AD) pathogenesis. Dysbiosis may influence neurodegeneration by affecting gut permeability and neurotrophic factors, leading to cognitive decline. The study analyzed microbiome differences between patients with AD and healthy individuals, as well as the impact of various interventions in both preclinical and clinical studies. Of 60 studies reviewed, 12 were excluded from the meta-analysis due to unsuitable data or lack of control groups. Meta-analyses revealed significant cognitive impairment in AD patients and animal models, with specific tests identifying these deficits. Notably, Bacteroides levels were higher in patients with AD, whereas probiotics improved Prevotella levels. Natural treatments increased Bacteroidetes and reduced Firmicutes in animal models. The findings emphasize the need for standardized methods to develop therapies targeting the gut microbiota to restore cognition in AD. Understanding individual dysbiosis could further clarify the cognitive effects of the gut-brain axis.

Highlights: Dysbiosis in the gut microbiota is linked to cognitive decline in Alzheimer's disease (AD).Patients with AD show significant differences in Bacteroides levels compared to healthy individuals.Probiotic treatments increase Prevotella levels in AD animal models.Natural agents boost Bacteroidetes and reduce Firmicutes in AD animal models.Human studies show no consistent effects of gut microbiota interventions on cognitive function in AD.

Introduction: We investigated the feasibility and validity of the remotely-administered neuropsychological battery from the National Alzheimer's Coordinating Center Uniform Data Set (UDS T-Cog).

Methods: Two hundred twenty Penn Alzheimer's Disease Research Center participants with unimpaired cognition, mild cognitive impairment, and dementia completed the T-Cog during their annual UDS evaluation. We assessed administration feasibility and diagnostic group differences cross-sectionally across telephone versus videoconference modalities, and compared T-Cog to prior in-person UDS scores longitudinally.

Results: Administration time averaged 54 min and 79% of participants who initiated a T-Cog completed all 12 subtests; completion time and rates differed by diagnostic group but not by modality. Performance varied expectedly across groups with moderate to strong associations between most T-Cog measures and in-person correlates, although select subtests demonstrated lower comparability.

Discussion: The T-Cog is feasibly administered and shows preliminary validity in a cognitively heterogeneous cohort. Normative data from this cohort should be expanded to more diverse populations to enhance utility and generalizability.

Highlights: This study examined the feasibility and validity of the remote Uniform Data Set (also known as the T-Cog) and contributes key normative data for widespread use.A remote neuropsychological battery was feasibly administered with high overall engagement and completion rates, adequate reliability compared to in-person testing, and evidence of validity across diagnostic groups.Typical barriers to administration included hearing impairment, technology issues, and distractions; hearing difficulties were particularly common among cognitively impaired groups.Certain tests were less closely related to their in-person correlates and should be used with caution.

Introduction: Early detection of cognitive impairment enables interventions to slow cognitive decline. Existing neuropsychological paper-and-pencil tests may not adequately assess cognition in real-life environments. A fully-immersive and automated virtual reality (VR) system-Cognitive Assessment using VIrtual REality (CAVIRE)-was developed to assess all six cognitive domains. This case-control study aims to evaluate the ability of CAVIRE to differentiate cognitively-healthy individuals from those with cognitive impairment.

Methods: One hundred nine Asian individuals 65-84 years of age were recruited at a primary care setting in Singapore. Based on the Montreal Cognitive Assessment (MoCA), participants were grouped as either Cognitively Healthy (MoCA ≥26, n = 60) or Cognitively Impaired (MoCA <26, n = 49). Subsequently, all participants completed the CAVIRE assessment.

Results: Cognitively-healthy participants achieved higher VR scores and required shorter completion time across all six cognitive domains (all p's < 0.005). Receiver-operating characteristic curve analysis showed area under the curve of 0.7267.

Discussion: The results demonstrated the potential of CAVIRE as a cognitive screening tool in primary care.

Highlights: CAVIRE is a virtual reality (VR) system that assesses the six cognitive domains.CAVIRE can distinguish healthy individuals from individuals with cognitive impairment.It has potential as a cognitive screening tool for older people in primary care.

Introduction: Plasma phosphorylated tau-181 (p-tau181) associations with global cognition and memory are clear, but the link between p-tau181 with other cognitive domains and subjective cognitive decline (SCD) across the clinical spectrum of Alzheimer's disease (AD) and how this association changes based on genetic and demographic factors is poorly understood.

Methods: Participants were drawn from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and included 1185 adults >55 years of age with plasma p-tau181 and neuropsychological test data. Linear regression models related plasma p-tau181 to neuropsychological composite and SCD scores with follow-up models examining plasma p-tau181 interactions with cognitive diagnosis, apolipoprotein E (APOE) ε4 carrier status, age, and sex on cognitive outcomes.

Results: Higher plasma p-tau181 level was associated with worse memory, executive functioning, and language abilities, and greater informant-reported SCD. Visuospatial abilities and self-report SCD were not associated with plasma p-tau181. Associations were generally stronger in mild cognitive impairment (MCI) or dementia, APOE ε4 carriers, women, and younger participants.

Discussion: Higher levels of plasma p-tau181 are associated with worse neuropsychological test performance across multiple cognitive domains; however, these associations vary based on disease stage, genetic risk status, age, and sex.

Highlights: Greater plasma p-tau181 was associated with lower cognition across most domains.Associations between p-tau181 and cognition were modified by age and sex.Level of p-tau181 was more strongly associated with cognition in people with mild cognitive impairment (MCI) and apolipoprotein E (APOE) ε4.

Introduction: Testing cognitive functions in Indians with low literacy and linguistic diversity is challenging. We describe the adaptation process of a comprehensive neurocognitive test battery to suit both literate and illiterate aging rural Indians.

Methods: Following the International Test Commission (ITC) guidelines for cross-cultural adaptation, we adapted the COGNITO battery. This involved translating instructions, linguistic elements, and stimuli of each test from the original English version with the help of bilingual experts. Five stimuli across eight subtests were adapted to maintain construct equivalence and cultural relevance.

Results: The Kannada version of COGNITO, a digitally administered tool, was feasible and effective measure for assessing cognitive functions in Kannada-speaking aging individuals from a rural Indian population.

Discussion: We emphasize the importance of maintaining semantic and theoretical construct equivalence with the source tool, and ensuring cultural and socioeconomic congruence for the cross-cultural adaptation of computerized cognitive batteries.

Highlights: Assessed cognitive functions in rural elderly with low literacy and high linguistic diversity.Followed International Test Commission (ITC) guidelines for cross-cultural adaptation to suit literate and illiterate aging rural Indians.Maintained semantic and theoretical construct equivalence with the source tool, ensuring cultural and socioeconomic congruence for cross-cultural adaptation of cognitive batteries.

Introduction: Little is known regarding the relationship between anticholinergic medications and frailty in dementia with Lewy bodies (DLB).

Methods: Anticholinergic Cognitive Burden Scale (ACB) and Claims-based Frailty Index scores were calculated for 12 months prior to the dementia diagnosis using electronic medical record and claims data. Logistic regression was used to estimate the association between ACB and odds of frailty.

Results: Compared to controls (n = 525), a diagnosis of DLB (n = 175; adjusted odds ratio [aOR]: 15.1, 95% confidence interval [CI]: 7.0-33.9) or Alzheimer's disease (AD: n = 525; aOR = 7.7, 95% CI: 4.4-13.7) was associated with an increased odds of frailty. Patients with DLB had greater prescriptions for anticholinergic medications than patients with AD (p _B < 0.001; 23%  vs 9.7%). ACB was positively correlated with frailty for all groups (r = 0.30 to 0.47, p < 0.001).

Discussion: Cumulative anticholinergic burden may be a modifiable predictor of frailty among older adults, including those newly diagnosed with dementia.

Highlights: Patients with newly diagnosed dementia with Lewy bodies (DLB) are more likely to have prescriptions for anticholinergic medications relative to patients newly diagnosed with Alzheimer's disease (AD) and older adults without documented cognitive impairment.In the year prior to a documented dementia diagnosis, 74% of patients with DLB and 66% of patients with AD had evidence of frailty.Anticholinergic medication burden was associated with frailty among all older adults in the study, including those without a dementia diagnosis.

Introduction: This study evaluates the clinical value of a deep learning-based artificial intelligence (AI) system that performs rapid brain volumetry with automatic lobe segmentation and age- and sex-adjusted percentile comparisons.

Methods: Fifty-five patients-17 with Alzheimer's disease (AD), 18 with frontotemporal dementia (FTD), and 20 healthy controls-underwent cranial magnetic resonance imaging scans. Two board-certified neuroradiologists (BCNR), two board-certified radiologists (BCR), and three radiology residents (RR) assessed the scans twice: first without AI support and then with AI assistance.

Results: AI significantly improved diagnostic accuracy for AD (area under the curve -AI: 0.800, +AI: 0.926, p < 0.05), with increased correct diagnoses (p < 0.01) and reduced errors (p < 0.03). BCR and RR showed notable performance gains (BCR: p < 0.04; RR: p < 0.02). For the diagnosis FTD, overall consensus (p < 0.01), BCNR (p < 0.02), and BCR (p < 0.05) recorded significantly more correct diagnoses.

Discussion: AI-assisted volumetry improves diagnostic performance in differentiating AD and FTD, benefiting all reader groups, including BCNR.

Highlights: Artificial intelligence (AI)-supported brain volumetry significantly improved the diagnostic accuracy for Alzheimer's disease (AD) and frontotemporal dementia (FTD), with notable performance gains across radiologists of varying expertise levels.The presented AI tool is readily clinically available and reduces brain volumetry processing time from 12 to 24 hours to under 5 minutes, with full integration into picture archiving and communication systems, streamlining the workflow and facilitating real-time clinical decision making.AI-supported rapid brain volumetry has the potential to improve early diagnosis and to improve patient management.