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

Introduction: Mounting evidence suggests that certain comorbidities may influence the clinical evolution of Alzheimer's dementia (AD).

Methods: We conducted logistic regression analyses on the medical history and cognitive health diagnoses of participants in the Australian Imaging, Biomarker & Lifestyle study (n = 2443) to investigate cross-sectional associations between various comorbidities and mild cognitive impairment (MCI)/AD.

Results: A mixture of associations were observed. Higher comorbidity of anxiety and other neurological disorders was associated with higher odds of AD, while arthritis, cancer, gastric complaints, high cholesterol, joint replacement, visual defect, kidney and liver disease were associated with lower odds of AD.

Discussion: This study underscores the links between specific comorbidities and MCI/AD. Further research is needed to elucidate the longitudinal comorbidity-MCI/AD associations and underlying mechanisms of these associations.

Highlights: Comorbidities that significantly increased AD odds included anxiety and other neurological disorders.Arthritis, cancer, gastric complaints, high cholesterol, joint replacement, visual defect, kidney and liver disease were associated with lower odds of AD.Alcohol consumption had the most significant confounding effect in the study.Visual-AD association was modified by age, sex, and APOE ε4 allele status.Anxiety-AD and depression-AD associations were modified by sex.

Introduction: This study aimed to determine whether the concomitance of hearing impairment and isolation with lack of conversation, which is considered self-evident but has not been investigated extensively, is associated with the occurrence of dementia.

Methods: A total of 2745 participants were divided into four groups according to the presence/absence of hearing impairment and isolation with lack of conversation. The association of dementia with hearing impairment and isolation with lack of conversation was analyzed using Cox proportional hazards regression.

Results: The combined hearing impairment and isolation with lack of conversation (hazard ratio: 1.69, 95% confidence interval: 1.09-2.61) and non-hearing impairment and isolation with lack of conversation (hazard ratio: 1.60, 95% confidence: 1.07-2.39) were associated with the development of dementia.

Discussion: These findings emphasize the importance of promoting high-quality social relationships throughout life by adopting preventive measures against isolation with lack of conversation from the early stage of awareness of hearing impairment.

Highlights: Dementia affects 12.9% of those with hearing impairment and isolation.Hearing impairment and isolation are associated with increased risk of dementia.Addressing these risk factors may help reduce the risk of developing dementia.Preventing isolation and promoting quality social relationships is important.

Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD), the two most common neurodegenerative dementias, both exhibit altered emotional processing. However, how vocal emotional expressions alter in and differ between DLB and AD remains uninvestigated. We collected voice data during story reading from 152 older adults comprising DLB, AD, and cognitively unimpaired (CU) groups and compared their emotional prosody in terms of valence and arousal dimensions. Compared with matched AD and CU participants, DLB patients showed reduced overall emotional expressiveness, as well as lower valence (more negative) and lower arousal (calmer), the extent of which was associated with cognitive impairment and insular atrophy. Classification models using vocal features discriminated DLB from AD and CU with an AUC of 0.83 and 0.78, respectively. Our findings may aid in discriminating DLB patients from AD and CU individuals, serving as a surrogate marker for clinical and neuropathological changes in DLB.

Highlights: DLB showed distinctive reduction in vocal expression of emotions.Cognitive impairment was associated with reduced vocal emotional expression in DLB.Insular atrophy was associated with reduced vocal emotional expression in DLB.Emotional expression measures successfully differentiated DLB from AD or controls.

Introduction: Initial dementia prevalence estimates have revealed a significant burden of the disease in Indigenous communities in Amazonas, Brazil. However, the need for culturally adapted cognitive tools poses a critical challenge when assessing cognitive performance in these communities. This study addressed this issue by culturally adapting and providing validity indicators for the Brazilian Indigenous Cognitive Assessment (BRICA) tool in Manaus, Brazil's urban multiethnic Indigenous community.

Methods: Using a three-stage process and a stakeholder-engaged approach, the BRICA tool was culturally adapted in an urban multiethnic Indigenous community from Manaus, Brazil. The content validity index (CVI) examined inter-rater concordance between experts, while criterion and concurrent validity were performed using diagnostic consensus criteria in 141 Indigenous participants aged ≥ 50 years.

Results: Findings showed evidence of content validity in terms of equivalence aspects (scale CVI [S-CVI] 0.93) and relevance ratings (S-CVI 0.85) between expert panels. The identified cut-off score of ≤ 33/39 on the BRICA demonstrated a sensitivity of 94.4%, specificity of 99.2%, positive predictive value of 94.4%, and negative predictive value of 99.2% for dementia diagnosis.

Discussion: Using a stakeholder-engaged approach, we culturally adapted the BRICA tool for a Brazilian urban multiethnic Indigenous community. This comprehensive adaptation process resulted in favorable indicators of content, construct, and criteria validity for the BRICA tool. By addressing the existing bias in cognitive assessment within Indigenous communities, the BRICA tool represents a noteworthy breakthrough. Its implementation exhibits potential for improving the early detection and management of dementia among Indigenous groups.

Highlights: Culturally sensitive tools are essential to assess cognition in Indigenous populations.An expert panel and stakeholders' perspectives were incorporated to design the Brazilian Indigenous Cognitive Assessment (BRICA) tool.A cognitive screening tool was adapted and validated using a stakeholder approach.BRICA is the first culturally sensitive cognitive tool for urban Brazilian Indigenous individuals.

Gamma-hydroxy-butyric acid (GABA) and glutamate are neurotransmitters with essential importance for cognitive processing. Here, we investigate relationships between GABA, glutamate, and brain ß-amyloid (Aß) burden before clinical manifestation of Alzheimer's disease (AD). Thirty cognitively healthy adults (age 69.9 ± 6 years) received high-resolution atlas-based ¹H-magnetic resonance spectroscopic imaging (MRSI) at ultra-high magnetic field strength of 7 Tesla for gray matter-specific assessment of GABA and glutamate. We assessed Aß burden with positron emission tomography and risk factors for AD. Higher gray matter GABA and glutamate related to higher Aß-burden (ß = 0.60, p < 0.05; ß = 0.64, p < 0.02), with positive effect modification by apolipoprotein-E-epsilon-4-allele (APOE4) (p = 0.01-0.03). GABA and glutamate negatively related to longitudinal change in verbal episodic memory performance (ß = -0.48; p = 0.02; ß = -0.50; p = 0.01). In vivo measures of GABA and glutamate reflect early AD pathology at old age, in an APOE4-dependent manner. GABA and glutamate may represent promising biomarkers and potential targets for early therapeutic intervention and prevention.

Highlights: Gray matter-specific metabolic imaging with high-resolution atlas-based MRSI at 7 Tesla.Higher GABA and glutamate relate to ß-amyloid burden, in an APOE4-dependent manner.Gray matter GABA and glutamate identify older adults with high risk of future AD.GABA and glutamate might reflect altered synaptic and neuronal activity at early AD.

The relationship between sex-specific blood biomarkers and memory changes in middle-aged adults remains unclear. We aimed to investigate this relationship using the data from the Framingham Heart Study (FHS). We conducted association analysis, partial correlation analysis, and causal dose-response curves using blood biomarkers and other data from 793 middle-aged participants (≤ 60 years) from the FHS Offspring Cohort. The results revealed associations of adiponectin and fasting blood glucose with midlife memory change, along with a U-shaped relationship of high-density lipoprotein cholesterol with memory change. No significant associations were found for the other blood biomarkers (e.g., amyloid beta protein 42) with memory change. To our knowledge, this is the first sex-specific network analysis of blood biomarkers related to midlife memory change in a prospective cohort study. Our findings highlight the importance of targeting cardiometabolic risks and the need to validate midlife-specific biomarkers that can accelerate the development of primary preventive strategies.

We sought to determine whether the biomarkers of chronic inflammation predict cognitive decline in a prospective observational study. We measured baseline serum soluble urokinase plasminogen activator receptor (suPAR) and high sensitivity C-reactive protein (hs-CRP) levels in 282 participants of the University of Michigan Memory and Aging Project. Cognitive function was measured using the Montreal Cognitive Assessment (MoCA) and the Clinical Dementia Rating (CDR) scale for up to five time points. SuPAR and hs-CRP levels were not significantly higher in participants with mild cognitive impairment (n = 97) or dementia (n = 59), compared to those with normal cognitive function (n = 126). Overall, 14% of participants experienced significant cognitive decline over the study period. The change in MoCA or CDR scores over time did not differ significantly according to baseline suPAR or hs-CRP levels. Chronic systemic inflammation, as measured by serum suPAR or hs-CRP levels, is unlikely to contribute significantly to cognitive decline.

Introduction: Identifying mild cognitive impairment (MCI) patients at risk for dementia could facilitate early interventions. Using electronic health records (EHRs), we developed a model to predict MCI to all-cause dementia (ACD) conversion at 5 years.

Methods: Cox proportional hazards model was used to identify predictors of ACD conversion from EHR data in veterans with MCI. Model performance (area under the receiver operating characteristic curve [AUC] and Brier score) was evaluated on a held-out data subset.

Results: Of 59,782 MCI patients, 15,420 (25.8%) converted to ACD. The model had good discriminative performance (AUC 0.73 [95% confidence interval (CI) 0.72-0.74]), and calibration (Brier score 0.18 [95% CI 0.17-0.18]). Age, stroke, cerebrovascular disease, myocardial infarction, hypertension, and diabetes were risk factors, while body mass index, alcohol abuse, and sleep apnea were protective factors.

Discussion: EHR-based prediction model had good performance in identifying 5-year MCI to ACD conversion and has potential to assist triaging of at-risk patients.

Highlights: Of 59,782 veterans with mild cognitive impairment (MCI), 15,420 (25.8%) converted to all-cause dementia within 5 years.Electronic health record prediction models demonstrated good performance (area under the receiver operating characteristic curve 0.73; Brier 0.18).Age and vascular-related morbidities were predictors of dementia conversion.Synthetic data was comparable to real data in modeling MCI to dementia conversion.

Key points: An electronic health record-based model using demographic and co-morbidity data had good performance in identifying veterans who convert from mild cognitive impairment (MCI) to all-cause dementia (ACD) within 5 years.Increased age, stroke, cerebrovascular disease, myocardial infarction, hypertension, and diabetes were risk factors for 5-year conversion from MCI to ACD.High body mass index, alcohol abuse, and sleep apnea were protective factors for 5-year conversion from MCI to ACD.Models using synthetic data, analogs of real patient data that retain the distribution, density, and covariance between variables of real patient data but are not attributable to any specific patient, performed just as well as models using real patient data. This could have significant implications in facilitating widely distributed computing of health-care data with minimized patient privacy concern that could accelerate scientific discoveries.

Introduction: Alzheimer's disease (AD) is a heterogeneous disorder characterized by complex underlying neuropathology that is not fully understood. This study aimed to identify cognitive progression subtypes and examine their correlation with clinical outcomes.

Methods: Participants of this study were recruited from the Framingham Heart Study. The Subtype and Stage Inference (SuStaIn) method was used to identify cognitive progression subtypes based on eight cognitive domains.

Results: Three cognitive progression subtypes were identified, including verbal learning (Subtype 1), abstract reasoning (Subtype 2), and visual memory (Subtype 3). These subtypes represent different domains of cognitive decline during the progression of AD. Significant differences in age of onset among the different subtypes were also observed. A higher SuStaIn stage was significantly associated with increased mortality risk.

Discussion: This study provides a characterization of AD heterogeneity in cognitive progression, emphasizing the importance of developing personalized approaches for risk stratification and intervention.

Highlights: We used the Subtype and Stage Inference (SuStaIn) method to identify three cognitive progression subtypes.Different subtypes have significant variations in age of onset.Higher stages of progression are associated with increased mortality risk.