Normal Cognition Research Articles

Designed Directional Growth of Ti-Metal-Organic Frameworks for Decoding Alzheimer's Disease-Specific Exosome Metabolites.

Exosomes, a growing focus for liquid biopsies, contain diverse molecular cargos. In particular, exosome metabolites with valuable information have exhibited great potential for improving the efficiency of liquid biopsies for addressing complex medical conditions. In this work, we design the directional growth of Ti-metal-organic frameworks on polar-functionalized magnetic particles. This design facilitates the rapid synergistic capture of exosomes with the assistance of an external magnetic field and additionally synergistically enhances the ionization of their metabolites during mass spectrometry detection. Benefiting from this dual synergistic effect, we identified three high-performance exosome metabolites through the differential comparison of a large number of serum samples from individuals with Alzheimer's disease (AD) and normal cognition. Notably, the accuracy of AD identification ranges from 93.18 to 100% using a single exosome metabolite and reaches a flawless 100% with three metabolites. These findings emphasize the transformative potential of this work to enhance the precision and reliability of AD diagnosis, ushering in a new era of improved diagnostic accuracy.

Abstract TP22: Delirium, Infection, and Risk of Dementia in Patients With and Without Cerebral Small Vessel Disease

Background: The increased risk of dementia after delirium and infection might be influenced by cerebral small vessel disease-SVD. We determined associations between hospitalisations with delirium, and with infection on follow-up after TIA/minor stroke and 5-year dementia risk, stratified by moderate/severe SVD on baseline brain imaging. Methods: In a population-based study (n=94 567) of TIA/minor stroke (NIHSS<3) ascertained 2002-2012 (Oxford Vascular Study-OXVASC), hospitalisations on follow-up were identified from the Oxford Cognitive Comorbidity, Frailty and Ageing Research Database-ORCHARD. Delirium and infection were defined by ICD-10 coding supplemented by hand-searching of hospital records. Dementia was diagnosed using clinical/cognitive assessment, medical records and death certificates. Dementia risk was determined using time-varying Cox analysis with multivariable adjustment. Findings: Among 1,369 patients (n=655 TIA, n=714 minor stroke, mean/SD age=72/13 years, 674 female, 364 moderate/severe SVD), 209 (15%) developed dementia. Hospitalisation during follow-up occurred in 891 (65%) patients of whom 103 (12%) had ≥1 delirium episode and 236 (26%) had ≥1 infection episode. Hospitalisation without delirium/infection did not predict subsequent dementia (HR=1.01,95%CI:0.86-1.20). In contrast, hospitalisation with delirium predicted subsequent dementia independently of infection in patients with and without SVD (HR=2.64,1.47-4.74 vs. 3.41,1.91-6.09, both p<0.001) especially in those with normal baseline cognition (HR=4.01,2.23-7.19 vs 3.94,1.95-7.93,both p<0.001). However, hospitalisation with infection only predicted dementia in those with moderate/severe SVD (HR=1.75,1.04-2.94 vs 0.68,0.39-1.20,p diff =0.023). Interpretation: The increased risk of dementia after delirium is unrelated to the presence of SVD, whereas infection increases risk only in patients with SVD, suggesting differences in underlying mechanisms and in potential preventive strategies.

Correlation between serum ANGPTL4 levels and white matter hyperintensity and cognitive impairment in patients with cerebral small vessel disease.

To investigate the correlation between serum angiopoietin-like protein 4 (ANGPTL4) levels, white matter hyperintensity (WMH), and cognitive impairment (CI) in patients with cerebral small vessel disease (CSVD). This cross-sectional study enrolled 171 patients with CSVD who attended the First Affiliated Hospital of Xinxiang Medical University from December 2021 to July 2022. All subjects underwent a 3.0T head magnetic resonance imaging, neuropsychology assessment, and blood sampling. Serum ANGPTL4 levels were detected by enzyme-linked immunosorbent assay and the severity of WMH was assessed by the Fazekas scale. According to the Montreal Cognitive Assessment (MoCA) scale, subjects were divided into normal cognition group (NC, n=80) and CI group (n=91). According to the total Fazekas scores, subjects were divided into a mild WMH group (n=84), a moderate WMH group (n=70), and a severe WMH group (n=17). Serum ANGPTL4 levels were significantly higher in the CI group than in the NC group (p<.05) and were negatively correlated with mini-mental state examination scores and MoCA scores (r=-0.26, -0.341, p<.05). Serum ANGPTL4 levels increased significantly in the mild to moderate WMH group but tended to decrease in the severe WMH group. Binary logistic regression analysis showed that ANGPTL4 was an independent influencing factor for CSVD-CI (OR=2.062, 95% CI (1.591-2.674), p<.001). The area under curve of ANGPTL4 for CSVD-CI was 0.847 (0.791-0.903). ANGPTL4 may be involved in the process of white matter damage and CI in CSVD patients and shows a diagnostic value for CSVD-CI.

Heart-brain mapping: Cardiac atrial function is associated with distinct cerebral regions with high free water in older adults

Left atrial (LA) dysfunction has been linked to cognitive impairment and cerebrovascular dysfunction. Higher brain free-water (FW) derived from diffusion-MRI was associated with early and subtle cerebrovascular dysfunction and more severe cognitive impairment. We hypothesized that LA dysfunction would correlate with higher brain free-water (FW) among healthy older adults. 56 community older adults (73.13 ± 3.56 years; 24 female) with normal cognition and without known cardiovascular disease who had undergone cardiac-MRI, brain-MRI, and neuropsychological assessments were included. Whole-brain voxel-level general linear models were constructed to correlate brain FW measures with LA indices. We found lower scores in LA function measures were related to higher grey matter (GM) FW in regions including orbital frontal and right temporal regions (p < 0.01, family-wise error corrected). In parallel, LA dysfunction was associated with higher FW in white matter (WM) fibres including superior longitudinal fasciculus, internal capsule, and superior corona radiata. However, LA dysfunction was not related to WM tissue reduction and GM cortical thinning. Moreover, these cardiac-related higher brain FW were associated with lower executive function and higher serum B-type natriuretic peptide (p < 0.05, Holm–Bonferroni corrected). These findings may have implications for anti-ageing preventive strategies targeting cardiac and cerebral vascular functions to improve heart and brain outcomes.

The associations between synaptic density and “A/T/N” biomarkers in Alzheimer’s disease: An 18F-SynVesT-1 PET/MR study

A newly developed SV2A radiotracer, 18F-SynVesT-1, was used in this study to investigate synaptic density and its association with Alzheimer’s disease (AD) “A/T/N” biomarkers. The study included a cohort of 97 subjects, consisting of 64 patients with cognitive impairment (CI) and 33 individuals with normal cognition (CU). All subjects underwent 18F-SynVesT-1 PET/MR and 18F-florbetapir PET/CT scans. Additionally, a subgroup of individuals also underwent 18F-MK-6240, 18F-FDG PET/CT, plasma Aβ42/Aβ40 and p-tau181 tests. The differences in synaptic density between the groups and the correlations between synaptic density and AD “A/T/N” biomarkers were analyzed. The results showed that compared to the CU group, the CI with Aβ+ (CI+) group exhibited the most pronounced synapse loss in the hippocampus, with some loss also observed in the neocortex. Furthermore, synaptic density in the hippocampus and parahippocampal gyrus showed associations with AD biomarkers detected by both imaging and plasma tests in the CI group. The associations between synaptic density and FDG uptake and hippocampal volume were also observed in the CI+ group. In conclusion, the study demonstrated significant synaptic density loss, as measured by the promising tracer 18F-SynVesT-1, and its close correlation with “A/T/N” biomarkers in patients with both Alzheimer’s clinical syndrome and pathological changes.

Feasibility of Remote Administration of the Uniform Data Set-Version 3 for Assessment of Older Adults With Mild Cognitive Impairment and Alzheimer's Disease.

Assess the feasibility and concurrent validity of a modified Uniform Data Set version 3 (UDSv3) for remote administration for individuals with normal cognition (NC), mild cognitive impairment (MCI), and early dementia. Participants (N =93) (age: 72.8 [8.9] years; education: 15.6 [2.5] years; 72% female; 84% White) were enrolled from the Wake Forest ADRC. Portions of the UDSv3 cognitive battery, plus the Rey Auditory Verbal Learning Test, were completed by telephone or video within ~6months of participant's in-person visit. Adaptations for phone administration (e.g., Oral Trails for Trail Making Test [TMT] and Blind Montreal Cognitive Assessment [MoCA] for MoCA) were made. Participants reported on the pleasantness, difficulty, and preference for each modality. Staff provided validity ratings for assessments. Participants' remote data were adjudicated by cognitive experts blinded to the in person-diagnosis (NC [N =44], MCI [N =35], Dementia [N =11], or other [N =3]). Remote assessments were rated as pleasant as in-person assessments by 74% of participants and equally difficult by 75%. Staff validity rating (video = 92%; phone = 87.5%) was good. Concordance between remote/in-person scores was generally moderate to good (r= .3 -.8; p< .05) except for TMT-A/OTMT-A (r= .3; p> .05). Agreement between remote/in-person adjudicated cognitive status was good (k= .61-.64). We found preliminary evidence that older adults, including those with cognitive impairment, can be assessed remotely using a modified UDSv3 research battery. Adjudication of cognitive status that relies on remotely collected data is comparable to classifications using in-person assessments.

Serum level of YWHAG as a diagnostic marker of cognitive impairment in Parkinson's disease patients.

Identifying reliable biomarkers for early detection and prediction of cognitive impairment in Parkinson's disease (PD) is crucial for optimal patient care. This study set out to investigate the potential of YWHAG as a diagnostic biomarker for cognitive impairment in PD. We enrolled a total of 331 PD patients and selected 241 patients that met the criteria for cognitive impairment analysis. The patients were classified into three groups: PD-NC: PD patients with normal cognition, PD-MCI: PD patients with mild cognitive impairment, and PD-D: PD patients with dementia. ELISA was employed to assess YWHAG expression, as well as the neurofilament light chain (NfL). Additionally, cognitive impairment was evaluated using MoCA scores. Correlation analysis and receiver operating curve analysis (ROC) were performed to clarify the relationship between YWHAG expression and cognitive impairment. Our findings revealed a significant upregulation of YWHAG expression in both the PD-MCI and PD-D groups compared to the PD-NC group. This observation aligned with the elevated expression of NfL in the PD-MCI and PD-D groups. YWHAG and NfL expression levels displayed negative correlations with MoCA scores and positive associations with age. Furthermore, ROC curve analysis demonstrated the diagnostic efficacy of YWHAG expression in distinguishing individuals with PD-NC, PD-MCI, and PD-D. Our findings indicate that YWHAG could serve as a promising biomarker for cognitive impairment in PD. The upregulation of YWHAG expression in PD-MCI and PD-D groups, its association with cognitive impairment, and its correlations with MoCA scores and NfL levels support its potential clinical utility.

Diagnosis Framework for Probable Alzheimer's Disease and Mild Cognitive Impairment Based on Multi-Dimensional Emotion Features.

Emotion and cognition are intercorrelated. Impaired emotion is common in populations with Alzheimer's disease (AD) and mild cognitive impairment (MCI), showing promises as an early detection approach. We aim to develop a novel automatic classification tool based on emotion features and machine learning. Older adults aged 60 years or over were recruited among residents in the long-term care facilities and the community. Participants included healthy control participants with normal cognition (HC, n = 26), patients with MCI (n = 23), and patients with probable AD (n = 30). Participants watched emotional film clips while multi-dimensional emotion data were collected, including mental features of Self-Assessment Manikin (SAM), physiological features of electrodermal activity (EDA), and facial expressions. Emotional features of EDA and facial expression were abstracted by using continuous decomposition analysis and EomNet, respectively. Bidirectional long short-term memory (Bi-LSTM) was used to train classification model. Hybrid fusion was used, including early feature fusion and late decision fusion. Data from 79 participants were utilized into deep machine learning analysis and hybrid fusion method. By combining multiple emotion features, the model's performance of AUC value was highest in classification between HC and probable AD (AUC = 0.92), intermediate between MCI and probable AD (AUC = 0.88), and lowest between HC and MCI (AUC = 0.82). Our method demonstrated an excellent predictive power to differentiate HC/MCI/AD by fusion of multiple emotion features. The proposed model provides a cost-effective and automated method that can assist in detecting probable AD and MCI from normal aging.

Gesture imitation performance in community-dwelling older people: assessment of a gesture imitation task in the screening and diagnosis of mild cognitive impairment and dementia.

Gesture imitation, a simple tool for assessing visuospatial/visuoconstructive functions, is reportedly useful for screening and diagnosing dementia. However, gesture imitation performance in healthy older adults is largely unknown, as are the factors associated with lower performance. To address these unknowns, we examined the gesture imitation performance of a large number of community-dwelling older adults aged ≥65 years in Arao City, Kumamoto Prefecture (southern Japan). The examiner presented the participants with eight gesture patterns and considered it a success if they could imitate them within 10 s. The success rate of each gesture imitation was calculated for three diagnostic groups: cognitively normal (CN) (n = 1184), mild cognitive impairment (MCI) (n = 237), and dementia (n = 47). Next, we reorganised the original gesture imitation battery by combining six selected gestures with the following scoring method: if the participants successfully imitated the gestures, immediately or within 5 s, two points were assigned. If they succeeded within 5-10 s, one point was assigned. The sensitivity and specificity of the battery were investigated to detect the dementia and MCI groups. Factors associated with gesture imitation battery scores were examined. Except one complex gesture, the success rate of imitation in the CN group was high, approximately 90%. The sensitivity and specificity of the gesture imitation battery for discriminating between the dementia and CN groups and between the MCI and CN groups were 70%/88%, and 45%/75%, respectively. Ageing, male sex, and a diagnosis of dementia or MCI were associated with lower scores on the gesture imitation battery. Gesture imitation tasks alone may not be sufficient to detect MCI. However, by combining gestures with set time limits, gesture imitation tasks can be a low-burden and effective method for detecting dementia, even in community medicine, such as during health check-ups.

Mild behavioral impairment in early Alzheimer’s disease and its association with APOE and BDNF risk genetic polymorphisms

BackgroundMild behavioral impairment (MBI) has been commonly reported in early Alzheimer’s disease (AD) but rarely using biomarker-defined samples. It is also unclear whether genetic polymorphisms influence MBI in such individuals. We thus aimed to examine the association between the cognitive status of participants (amnestic mild cognitive impairment (aMCI-AD) vs cognitively normal (CN) older adults) and MBI severity. Within aMCI-AD, we further examined the association between APOE and BDNF risk genetic polymorphisms and MBI severity.MethodsWe included 62 aMCI-AD participants and 50 CN older adults from the Czech Brain Aging Study. The participants underwent neurological, comprehensive neuropsychological examination, APOE and BDNF genotyping, and magnetic resonance imaging. MBI was diagnosed with the Mild Behavioral Impairment Checklist (MBI-C), and the diagnosis was based on the MBI-C total score ≥ 7. Additionally, self-report instruments for anxiety (the Beck Anxiety Inventory) and depressive symptoms (the Geriatric Depression Scale-15) were administered. The participants were stratified based on the presence of at least one risk allele in genes for APOE (i.e., e4 carriers and non-carriers) and BDNF (i.e., Met carriers and non-carriers). We used linear regressions to examine the associations.ResultsMBI was present in 48.4% of the aMCI-AD individuals. Compared to the CN, aMCI-AD was associated with more affective, apathy, and impulse dyscontrol but not social inappropriateness or psychotic symptoms. Furthermore, aMCI-AD was related to more depressive but not anxiety symptoms on self-report measures. Within the aMCI-AD, there were no associations between APOE e4 and BDNF Met and MBI-C severity. However, a positive association between Met carriership and self-reported anxiety appeared.ConclusionsMBI is frequent in aMCI-AD and related to more severe affective, apathy, and impulse dyscontrol symptoms. APOE and BDNF polymorphisms were not associated with MBI severity separately; however, their combined effect warrants further investigation.

The Clock Drawing Task reveals executive dysfunction in the dialysis population – an underrecognized and underestimated problem

Aim of the study The study aimed to assess the prevalence of executive function impairment among patients with chronic kidney disease (CKD) undergoing dialysis, with no subjective cognitive problems and with normal global cognition on the Mini-Mental State Examination (MMSE). We also investigated the relationship between cardiovascular risk factors and cognitive test results. Rationale for the study Patients with CKD, including those undergoing renal replacement therapy, are at a higher risk of developing cognitive impairment (CI) than the general population. Recent research has shown CI to be a growing problem among CKD patients worldwide. Yet, it remains underdiagnosed, even though it may significantly influence the lives of patients. Materials and methods In this cross-sectional, prospective study, 58 dialysis patients with no cognitive decline on the MMSE screening were assessed for executive function impairment using the Executive Clock-Drawing Task (CLOX). Moreover, past medical history, demographic data, and laboratory test results were collected. Results The mean patient age was 59.47 ± 14.98 years, and the mean duration of dialysis was 45.93 ± 48.49 months. The prevalence of executive function impairment amounted to 8.6%. Moreover, remarkably similar pattern of clock drawing was observed, with numbers written outside the clock face in the CLOX1 test. Conclusions Executive dysfunctions in dialysis patients may manifest itself before the onset of global cognitive impairment. There appear to be a deficit in the spatial domain as well. Better education may play a protective role.

Home medication inventory method to assess over-the-counter (OTC) medication possession and use: A pilot study on the feasibility of in-person and remote modalities with older adults

BackgroundThere is a need for reproducible methods to measure over-the-counter (OTC) medication possession and use. This is because OTC medications are self-managed, variably monitored by healthcare professionals, and in certain populations such as older adults some OTC medications may introduce risk and cause more harm than benefit. Objective(s): To develop and assess the feasibility of the Home Medication Inventory Method (HMIM), a novel method to measure possession and use of OTC medications. MethodsWe benchmarked, adapted, and standardized prior approaches to medication inventory to develop a method capable of addressing the limitations of existing methods. We then conducted a pilot study of the HMIM among older adults. Eligible participants were aged ≥60 years, reported purchasing or considering purchasing OTC medication, and screened for normal cognition. Interviews were conducted both in person and remotely. When possible, photographs of all OTC medications were obtained with participant consent and completion times were recorded for both in-person and remote modalities. ResultsIn total 51 participants completed the pilot study. Home medication inventories were conducted in-person (n = 15) and remotely (n = 36). Inventories were completed in a mean (SD) of 20.2 min (12.7), and 96 % of inventories completed within 45 min. A total of 390 OTC medications were possessed by participants, for a mean (SD) of 7.6 (6.3) per participant. No differences in duration of interviews or number of medications reported were identified between in-person and remote modalities. Anticholinergic medications, a class targeted in the pilot as potentially harmful to older adults, were possessed by 31 % of participants, and 14 % of all participants reported use of such a medication within the previous 2 weeks. ConclusionsImplementing the HMIM using in-person and remote modalities is a feasible and ostensibly reproducible method for collecting OTC medication possession and use information. Larger studies are necessary to further generalize HMIM feasibility and reliability in diverse populations.

Multimodal classification of Alzheimer's disease and mild cognitive impairment using custom MKSCDDL kernel over CNN with transparent decision-making for explainable diagnosis

The study presents an innovative diagnostic framework that synergises Convolutional Neural Networks (CNNs) with a Multi-feature Kernel Supervised within-class-similar Discriminative Dictionary Learning (MKSCDDL). This integrative methodology is designed to facilitate the precise classification of individuals into categories of Alzheimer's Disease, Mild Cognitive Impairment (MCI), and Cognitively Normal (CN) statuses while also discerning the nuanced phases within the MCI spectrum. Our approach is distinguished by its robustness and interpretability, offering clinicians an exceptionally transparent tool for diagnosis and therapeutic strategy formulation. We use scandent decision trees to deal with the unpredictability and complexity of neuroimaging data. Considering that different people's brain scans are different, this enables the model to make more detailed individualised assessments and explains how the algorithm illuminates the specific neuroanatomical regions that are indicative of cognitive impairment. This explanation is beneficial for clinicians because it gives them concrete ideas for early intervention and targeted care. The empirical review of our model shows that it makes diagnoses with a level of accuracy that is unmatched, with a classification efficacy of 98.27%. This shows that the model is good at finding important parts of the brain that may be damaged by cognitive diseases.

Associations of cerebrospinal fluid complement proteins with Alzheimer’s pathology, cognition, and brain structure in non-dementia elderly

BackgroundCerebrospinal fluid (CSF) complement activation is a key part of neuroinflammation that occurs in the early stages of Alzheimer’s disease (AD). However, the associations of CSF complement proteins with AD pathology, cognition, and structural neuroimaging biomarkers for AD have been rarely investigated.MethodsA total of 210 participants (125 mild cognitive impairment [MCI] patients and 85 normal controls) were included from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database who measured AD pathology, cognition, and neuroimaging at baseline and every 12 months. The mixed-effect linear models were utilized to investigate longitudinal associations of CSF complement proteins with AD pathology, cognition, and neuroimaging in cognitively normal (CN) and mild cognitive impairment (MCI) subjects. Causal mediation analyses were conducted to explore the potential mediators between CSF complement proteins and cognitive changes.ResultsWe found that the subjects with low CSF complement protein levels at baseline had worse outcomes in AD pathology, indicated by their lowest concentrations observed in A + and A + T + individuals. The reduced CSF complement proteins were associated with faster accumulation of tau among CN subjects and with cognitive decline and greater brain atrophy of specific regions among MCI subjects. Furthermore, mediation analyses showed that the effects of CSF complement proteins on cognitive performance were partially mediated by regional brain structures (mediation proportions range from 19.78 to 94.92%; p < 0.05).ConclusionsThis study demonstrated that CSF complement proteins were involved in the early progression of AD. Our results indicated that regional brain atrophy might be a plausible way to connect CSF complement protein levels and cognition.

Ultra-Widefield Imaging of the Retinal Macrovasculature in Parkinson Disease Versus Controls With Normal Cognition Using Alpha-Shapes Analysis.

To investigate retinal vascular characteristics using ultra-widefield (UWF) scanning laser ophthalmoscopy in Parkinson disease (PD). Individuals with an expert-confirmed clinical diagnosis of PD and controls with normal cognition without PD underwent Optos California UWF imaging. Patients with diabetes, uncontrolled hypertension, glaucoma, dementia, other movement disorders, or known retinal or optic nerve pathology were excluded. Images were analyzed using Vasculature Assessment and Measurement Platform for Images of the Retina (VAMPIRE-UWF) software, which describes retinal vessel width gradient and tortuosity, provides vascular network fractal dimensions, and conducts alpha-shape analysis to further characterize vascular morphology (complexity, Opαmin; spread, OpA). In the PD cohort, 53 eyes of 38 subjects were assessed; in the control cohort, 51 eyes of 33 subjects were assessed. Eyes with PD had more tortuous retinal arteries in the superotemporal quadrant (P = 0.043). In eyes with PD, alpha-shape analysis revealed decreased OpA, indicating less retinal vasculature spread compared to controls (P = 0.032). Opαmin was decreased in PD (P = 0.044), suggesting increased vascular network complexity. No differences were observed in fractal dimension in any region of interest. This pilot study suggests that retinal vasculature assessment on UWF images using alpha-shape analysis reveals differences in retinal vascular network spread and complexity in PD and may be a more sensitive metric compared to fractal dimension. Retinal vasculature assessment using these novel methods may be useful in understanding ocular manifestations of PD and the development of retinal biomarkers.

The Care Needs of Patients With Cognitive Impairment in Late-Stage Parkinson's Disease.

Cognitive impairment is common in Parkinson's disease (PD), but care needs and resource use for those with significant cognitive impairment are not well established. 675 participants with PD from the international Care of Late-Stage Parkinsonism (CLaSP) study were grouped into those without (n = 333, 49%) and with cognitive impairment (MMSE < 24/30 or diagnosis of dementia or Mild Cognitive Impairment; n = 342, 51%) and their clinical features, care needs and healthcare utilisation compared. The relationship between cognition and healthcare consultations was investigated through logistic regression. Cognitive impairment was associated with more motor and non-motor symptoms, less antiparkinsonian but higher rates of dementia and antipsychotic medication, worse subjective health status and greater caregiver burden. A considerable proportion did not have a pre-established cognitive diagnosis. Care needs were high across the whole sample but higher in the cognitive impairment group. Home care and care home use was higher in the cognitive impairment group. However, use of healthcare consultations was similar between the groups and significantly fewer participants with cognitive impairment had had recent PD Nurse consultations. Worse cognitive impairment was associated with lower frequency of recent PD nurse and multidisciplinary therapy consultation (physiotherapy, massage, occupational therapy, speech training and general nursing). Those with cognitive impairment have more severe PD, higher care needs and greater social care utilisation than those with normal cognition, yet use of health care services is similar or less. Cognitive impairment appears to be a barrier to PD nurse and multidisciplinary therapy consultations. This challenges current models of care: alternative models of care may be required to serve this population. Parkinson's disease is a long-term progressive health condition. Over time, many people with Parkinson's develop problems with thinking and memory, called cognitive impairment. This can negatively impact the daily lives of the person with Parkinson's and their caregiver. It is also thought to be a barrier to accessing healthcare. How people with Parkinson's who have cognitive impairment use healthcare and detail of their care needs is not well known.We analysed data from a large sample of people with advanced Parkinson's from six European countries to investigate their symptoms, care needs and healthcare use. We compared those with cognitive impairment to (342 people) to those without cognitive impairment (333 people).We found that those with cognitive impairment had more severe Parkinson's across a range of symptoms compared to those without cognitive impairment. They also had more care needs, reported their health status to be worse, and their caregivers experienced greater strain from caring. Whilst use of other healthcare services was similar between the two groups, those with cognitive impairment were less likely to have recently seen a Parkinson's nurse than those without cognitive impairment. Further analysis showed an association between cognitive impairment and not having seen a Parkinson's nurse or therapist recently, taking psychiatric symptoms, functional disability and care home residence into account. Therapists included were physiotherapy, massage, occupational therapy, speech training and general nursing. These findings highlight unmet need. We suggest that healthcare should be more targeted to help this group of people, given their higher care needs.

Comparison of Commonly Measured Plasma and Cerebrospinal Fluid Proteins and Their Significance for the Characterization of Cognitive Impairment Status.

Although cerebrospinal fluid (CSF) amyloid-β42 peptide (Aβ42) and phosphorylated tau (p-tau) and blood p-tau are valuable for differential diagnosis of Alzheimer's disease (AD) from cognitively normal (CN) there is a lack of validated biomarkers for mild cognitive impairment (MCI). This study sought to determine how plasma and CSF protein markers compared in the characterization of MCI and AD status. This cohort study included Alzheimer's Disease Neuroimaging Initiative (ADNI) participants who had baseline levels of 75 proteins measured commonly in plasma and CSF (257 total, 46 CN, 143 MCI, and 68 AD). Logistic regression, least absolute shrinkage and selection operator (LASSO) and Random Forest (RF) methods were used to identify the protein candidates for the disease classification. We observed that six plasma proteins panel (APOE, AMBP, C3, IL16, IGFBP2, APOD) outperformed the seven CSF proteins panel (VEGFA, HGF, PRL, FABP3, FGF4, CD40, RETN) as well as AD markers (CSF p-tau and Aβ42) to distinguish the MCI from AD [area under the curve (AUC) = 0.75 (plasma proteins), AUC = 0.60 (CSF proteins) and AUC = 0.56 (CSF p-tau and Aβ42)]. Also, these six plasma proteins performed better than the CSF proteins and were in line with CSF p-tau and Aβ42 in differentiating CN versus MCI subjects [AUC = 0.89 (plasma proteins), AUC = 0.85 (CSF proteins) and AUC = 0.89 (CSF p-tau and Aβ42)]. These results were adjusted for age, sex, education, and APOEϵ4 genotype. This study suggests that the combination of 6 plasma proteins can serve as an effective marker for differentiating MCI from AD and CN.

Early Diagnosing and Transformation Prediction of Alzheimer's Disease Using Multi-Scaled Self-Attention Network on Structural MRI Images with Occlusion Sensitivity Analysis.

Structural magnetic resonance imaging (sMRI) is vital for early Alzheimer's disease (AD) diagnosis, though confirming specific biomarkers remains challenging. Our proposed Multi-Scale Self-Attention Network (MUSAN) enhances classification of cognitively normal (CN) and AD individuals, distinguishing stable (sMCI) from progressive mild cognitive impairment (pMCI). This study leverages AD structural atrophy properties to achieve precise AD classification, combining different scales of brain region features. The ultimate goal is an interpretable algorithm for this method. The MUSAN takes whole-brain sMRI as input, enabling automatic extraction of brain region features and modeling of correlations between different scales of brain regions, and achieves personalized disease interpretation of brain regions. Furthermore, we also employed an occlusion sensitivity algorithm to localize and visualize brain regions sensitive to disease. Our method is applied to ADNI-1, ADNI-2, and ADNI-3, and achieves high performance on the classification of CN from AD with accuracy (0.93), specificity (0.82), sensitivity (0.96), and area under curve (AUC) (0.95), as well as notable performance on the distinguish of sMCI from pMCI with accuracy (0.85), specificity (0.84), sensitivity (0.74), and AUC (0.86). Our sensitivity masking algorithm identified key regions in distinguishing CN from AD: hippocampus, amygdala, and vermis. Moreover, cingulum, pallidum, and inferior frontal gyrus are crucial for sMCI and pMCI discrimination. These discoveries align with existing literature, confirming the dependability of our model in AD research. Our method provides an effective AD diagnostic and conversion prediction method. The occlusion sensitivity algorithm enhances deep learning interpretability, bolstering AD research reliability.

Predictors and outcomes of fluctuations in the clinical dementia rating scale.

Reversion, or change in cognitive status from impaired to normal, is common in aging and dementia studies, but it remains unclear what factors predict reversion. We investigated whether reverters, defined as those who revert from a Clinical Dementia Rating® (CDR®) scale score of 0.5 to CDR 0) differed on cognition and biomarkers from unimpaired participants (always CDR 0) and impaired participants (converted to CDR>0 and had no reversion events). Models evaluated relationships between biomarker status, apolipoprotein E (APOE) ε4 status, and cognition. Additional models described predictors of reversion and predictors of eventual progression to CDR>0. CDR reversion was associated with younger age, better cognition, and negative amyloid biomarker status. Reverters that eventually progressed to CDR>0 had more visits, were older, and were more likely to have an APOE ε4 allele. CDR reversion occupies a transitional phase in disease progression between cognitive normality and overt dementia. Reverters may be ideal candidates for secondary prevention Alzheimer's disease (AD) trials. Reverters had more longitudinal cognitive decline than those who remained cognitively normal. Predictors of reversion: younger age, better cognition, and negative amyloid biomarker status. Reverting from CDR 0.5 to 0 is a risk factor for future conversion to CDR>0. CDR reversion may be a transitional phase in Alzheimer's Disease progression. CDR reverters may be ideal for Alzheimer's disease secondary prevention trials.

Measuring Multidimensional Aspects of Health in the Oldest Old Using the NIH Toolbox: Results From the ARMADA Study.

The percentage of older adults living into their 80s and beyond is expanding rapidly. Characterization of typical cognitive performance in this population is complicated by a dearth of normative data for the oldest old. Additionally, little attention has been paid to other aspects of health, such as motor, sensory, and emotional functioning, that may interact with cognitive changes to predict quality of life and well-being. The current study used the NIH Toolbox (NIHTB) to determine age group differences between persons aged 65-84 and 85+ with normal cognition. Participants were recruited in two age bands (i.e., 65-84 and 85+). All participants completed the NIHTB Cognition, Motor, Sensation, and Emotion modules. Independent-samples t-tests determined age group differences with post-hoc adjustments using Bonferroni corrections. All subtest and composite scores were then regressed on age and other demographic covariates. The 65-84 group obtained significantly higher scores than the 85+ group across all cognitive measures except oral reading, all motor measures except gait speed, and all sensation measures except pain interference. Age remained a significant predictor after controlling for covariates. Age was not significantly associated with differences in emotion scores. Results support the use of the NIHTB in persons over 85 with normal cognition. As expected, fluid reasoning abilities and certain motor and sensory functions decreased with age in the oldest old. Inclusion of motor and sensation batteries is warranted when studying trajectories of aging in the oldest old to allow for multidimensional characterization of health.