MCI Patients Research Articles

Electrophysiological correlates of objective memory impairments in community‐dwelling older adults at risk of dementia

AbstractBackgroundThe electrophysiological correlates of Short‐Term Memory Binding (STMB) have been previously investigated in older adults at risk of dementia (i.e., Mild Cognitive Impairment ‐MCI). Pietto et al. (2016) reported reduced early electrophysiological activity (100‐250 ms) over fronto‐central (FC) and parieto‐occipital (PO) regions in MCI patients recruited from clinic. We investigated if such an electrophysiological pattern is also observed in a larger sample of community‐dwelling older adults with MCI who had not sought medical advice.MethodsA sample of 215 community‐dwelling older adults were recruited into the study. They were assessed with a battery of cognitive tests including CERAD (Aguirre‐Acevedo et al., 2016), the Addenbrooke’s Cognitive Examination (ACE‐R), the STMB Task, clinical, and functional scales. The STMB task assesses the ability to detect changes between two consecutive visual arrays of coloured shapes. Changes consisted of shapes swapping colours (the binding condition). Time‐locked EEG signals were collected while participants performed the STMB task. Monte Carlo tests and non‐parametric bootstrapping running 1000 permutations revealed electrodes and time windows of relevance.ResultsA group of 108 participants met classical criteria for MCI (Petersen, 2004; Winblad et al., 2004). They showed impaired STMB abilities. ERP analyses revealed significant Group x Time Windows interactions (p<0.01). Early ERP showed reduced neural recruitment (MCI<HC) on the left PO and right centro‐parietal (CP) (300‐500ms) regions during shape‐colour encoding, and on PO bilaterally and left FC during retrieval (150‐450ms). Late ERP showed increased neural recruitment (MCI>HC) on right fronto‐central (FC) regions (900‐1200ms) during shape‐colour encoding, and on left FC and PO regions (872‐1200ms) during retrieval.ConclusionAltered spatio‐temporal dynamics underpinning STMB deficits in MCI patients followed a pattern similar to that described by Pietto et al. (2016). Of note, we observed hyper‐recruitment for late ERP linked to encoding and retrieval over anterior and posterior regions of the STMB network. Such hyper‐recruitment may reflect compensatory changes in the early stages of MCI. These results confirm the usefulness of EEG‐based cognitive biomarkers to screen community‐dwelling older adults at risk of dementia.Aguirre‐Acevedo et al. (2016). Int. Psychogeriatr, 28(3), 503‐510.Pietto et al. (2016). Journal of Alzheimer’s Disease, 53(4), 1325‐1340.

Interpreting trial results in an era of disease‐modifying therapies: Efficacy of approved anti‐amyloid drugs in the context of the long‐term Alzheimer’s trajectory

AbstractBackgroundEarly‐stage Alzheimer’s disease (AD) typically presents with slow progression of clinical symptoms. Approved high‐potency anti‐amyloid‐β (Aβ) therapies have demonstrated changes in the disease trajectory in these early stages and offer potential benefits beyond the period for which they have been studied in trials.MethodsBased on published results, the time‐slowing of disease progression based on change in CDR sum of boxes (CDR‐SB) was approximated. Disease progression modeling using long‐term cohort data was used to estimate the natural history trajectory of CDR‐SB in AD from the preclinical stages to severe dementia. Modeling of trial inclusion criteria was used to estimate the interval of the natural history trajectory of AD that were included in trials and different scenarios for long‐term treatment effects were explored.ResultsIn positive phase 3 studies, the high‐potency anti‐Aβ therapies appeared to slow disease progression 20‐30% resulting in a 4‐6‐month delay of progression during the 18‐month study period. Included patient populations were found to differ substantially, with the EMERGE and ENGAGE studies including an earlier group of patients than CLARITY‐AD. Consistent with trial subgroup analyses, natural‐history modeling suggested that more progressed patients would see an apparent greater absolute benefit during 18 months, but less absolute benefit over longer durations. Under an assumption of continued slowing beyond the study period, a treatment slowing disease progression by 30% (5.4 months delay in disease progression after 18 months) would lead to treatment differences on CDR‐SB of ‐0.42 and ‐0.72 points for typical MCI and mild dementia patients. With continued slowing beyond the length of the trial, typical MCI patients would have a treatment effect of ‐0.96 points once reaching the same disease stage as the mild dementia patients. Five‐year treatment differences would be approximately ‐2.5 and ‐3.2 points, well beyond all estimates of clinically meaningful differences. Even in the most conservative disease‐modifying scenario assuming no increased time delay after 18 months, observed treatment differences would still increase beyond 18 months due to the nonlinear trajectory of CDR‐SB.ConclusionDisease‐modifying effects of the magnitude observed in recent trials can potentially translate into clearly meaningful differences over a longer duration.

Clinical and biomarker characteristics of amnestic MCI patients exhibiting a temporo‐limbic FDG‐PET pattern suggestive of LATE

AbstractBackgroundWe have recently described a specific temporo‐limbic FDG‐PET signature that characterizes autopsy‐confirmed cases with limbic age‐related TDP‐43 encephalopathy (LATE), and have demonstrated its clinical utility for differential diagnosis of amnestic dementia patients. Here we assessed the utility of this pattern for patient stratification at a predementia disease stage, and further used tau‐PET data to study the degree to which this “LATE‐specific” FDG‐PET signature may correspond to a limbic‐predominant AD subtype.MethodIndividual FDG‐PET scans of 909 amnestic MCI (aMCI) patients from the ADNI cohort were screened for hypometabolic patterns being suggestive of LATE (sLATE) or typical AD (sAD) using automated pattern‐matching to autopsy‐confirmed pathology‐specific FDG‐PET signatures. sLATE and sAD patients were compared on clinical features, APOE4 genotype, and CSF biomarkers. Tau‐PET scans ([18F]Flortaucipir) were available in a smaller subsample (30%) and were analyzed for tau‐positivity using an FDA‐approved visual interpretation method as well as entorhinal SUVR (positivity‐threshold: SUVR = 2.1).Result734 aMCI patients showed evidence of significant regional hypometabolism, and of these 92 had a pronounced temporo‐limbic hypometabolic pattern classified as sLATE, whereas 68 had a classical temporo‐parietal pattern classified as sAD(Fig‐1). Compared to sAD, sLATE patients had similar MMSE and memory scores but more preserved executive function scores, and they showed generally slower cognitive decline over follow‐up (p<0.001)(Fig‐2). They were also significantly older (d = 0.83, p = 0.01), less often APOE4 carriers (39% vs 64%, p<0.001), and had less abnormal CSF Aß42 (d = 0.60, p = 0.001) and p‐tau181 levels (d = ‐0.40, p = 0.01). With regards to tau‐PET, 9/30 sLATE (30%) and 9/10 sAD (90%) patients were visually positive and similar proportions were seen for entorhinal SUVR (40% vs 90%).ConclusionThe majority of amnestic MCI patients exhibiting a LATE‐typical temporo‐limbic FDG‐PET pattern show clinical and biomarker features that deviate from prodromal AD. A smaller subset of these patients shows elevated tau‐PET signal and could thus represent a limbic‐predominant AD subtype.

Semantic cognition as an early cognitive marker of Alzheimer’s disease: importance of executive processes mediation

AbstractBackgroundImpaired semantic memory is one of the earliest characteristic features of Alzheimer’s disease. Its assessment is crucial to accurately predict conversion to Alzheimer disease related disorders (ADRD). Recent evidence supports the necessity to differentiate between subprocesses of semantic cognition: a) activation in the semantic representation system; b) executive processes to control or select relevant aspects of semantic knowledge. In this study we compare semantic memory tests that differ in these subprocesses to find out which of them are the best predictors of conversion of MCI to ACD in two years. We also want to identify which semantic memory tests have more sensitivity and specificity at the baseline in the differentiation MCI‐no converters and MCI converters after two yearsMethodWe assessed 130 amnestic MCI patients. Semantic memory tests more based on integrity of semantic knowledge (Similarities, ACE‐language) and more executive determined (verbal fluency – phonemic and categories, Boston Naming Test) were administered at baseline and at 2‐years follow‐up, together with cognitive screening tools and IADL measures. A binary regression model was used to examine which semantic memory tests predict MCI progression to Alzheimer’s Clinical Syndrome (ACS) in two years. ROC curves were used to study early clinical diagnosis differentiating MCI converters and MCI non convertersResultOnly semantic category fluency test significantly explained the conversion to ACS (p<.01). Baseline score semantic categories fluency were significantly lower in MCI patients who develop ACS after two years (p<.001). ROC curves showed that semantic categories fluency and Boston Naming tests were the best tests to differentiate at baseline between MCI converter and non‐converter (AUC = 0.768, p<0,0001 and AUC = 0.712, p<0,01, respectively)ConclusionSemantic category fluency test was the best predictor from MCI to ACS conversion in two years. Semantic category fluency and Boston Naming tests clearly identify people with high risk to develop ACS in two years. Semantic memory tests including executive contributions could detect and characterize prodromal Alzheimer’s disease

Clinical and biomarker characteristics of amnestic MCI patients exhibiting a temporo‐limbic FDG‐PET pattern suggestive of LATE

AbstractBackgroundWe have recently described a specific temporo‐limbic FDG‐PET signature that characterizes autopsy‐confirmed cases with limbic age‐related TDP‐43 encephalopathy (LATE), and have demonstrated its clinical utility for differential diagnosis of amnestic dementia patients. Here we assessed the utility of this pattern for patient stratification at a predementia disease stage, and further used tau‐PET data to study the degree to which this “LATE‐specific” FDG‐PET signature may correspond to a limbic‐predominant AD subtype.MethodIndividual FDG‐PET scans of 909 amnestic MCI (aMCI) patients from the ADNI cohort were screened for hypometabolic patterns being suggestive of LATE (sLATE) or typical AD (sAD) using automated pattern‐matching to autopsy‐confirmed pathology‐specific FDG‐PET signatures. sLATE and sAD patients were compared on clinical features, APOE4 genotype, and CSF biomarkers. Tau‐PET scans ([18F]Flortaucipir) were available in a smaller subsample (30%) and were analyzed for tau‐positivity using an FDA‐approved visual interpretation method as well as entorhinal SUVR (positivity‐threshold: SUVR≥2.1).Result734 aMCI patients showed evidence of significant regional hypometabolism, and of these 92 had a pronounced temporo‐limbic hypometabolic pattern classified as sLATE, whereas 68 had a classical temporo‐parietal pattern classified as sAD(Fig‐1). Compared to sAD, sLATE patients had similar MMSE and memory scores but more preserved executive function scores, and they showed generally slower cognitive decline over follow‐up (p<0.001)(Fig‐2). They were also significantly older (d = 0.83, p = 0.01), less often APOE4 carriers (39% vs 64%, p<0.001), and had less abnormal CSF Aβ42 (d = 0.60, p = 0.001) and p‐tau181 levels (d = ‐0.40, p = 0.01). With regards to tau‐PET, 9/30 sLATE (30%) and 9/10 sAD (90%) patients were visually positive and similar proportions were seen for entorhinal SUVR (40% vs 90%).ConclusionThe majority of amnestic MCI patients exhibiting a LATE‐typical temporo‐limbic FDG‐PET pattern show clinical and biomarker features that deviate from prodromal AD. A smaller subset of these patients shows elevated tau‐PET signal and could thus represent a limbic‐predominant AD subtype.

Discrimination early Alzheimer’s disease from mild cognitive impairment by using Easy Z‐score Imaging System for ECD SPECT

AbstractBackgroundProdromal AD progresses to dementia at a higher annual rate. Since cholinesterase inhibitor benefits early AD patients, discrimination between MCI due to AD and non‐MCI due to AD remains important.MethodWe conducted a retrospective study of MCI cases at National Cheng Kung University Hospital (NCKUH) from 2017 to 2019. Those who showed hypometabolism at posterior cingulate cortex, precuneus, or posterior parietal cortex on brain ECD SPECT and EZIS severity greater than 1.19 were categorized as MCI due to AD; in contrast, patients with EZIS severity lesser than 1.19 were categorized as non‐MCI due to AD. Clinical outcomes included deterioration of CASI, MMSE, SB scores and conversion from MCI to dementia.ResultThere was positive correlation between EZIS severity and deterioration of CASI, MMSE, SB according to multiple regression results, indicating EZIS severity could predict cognitive progression in three years follow‐up. There was no difference in dementia conversion rate between two groups either by chi‐square method or Kaplan‐Meier method, and EZIS severity was not a significant variable in binary logistic regression analysis for conversion. However, there was a trend toward greater dementia conversion rate in the EZIS‐favored MCI due to AD group, and in the second half period of follow‐up as seen on Kaplan‐Meier curves.ConclusionDuring three years of follow‐up, MCI patients with greater EZIS severity were significantly associated with worse cognitive assessment scores, and there was a trend toward greater dementia conversion rate based on cutoff value 1.19 of EZIS severity.

Combining speech biomarkers for cognition and mood improves diagnostic accuracy between MCI and subjective cognitive decliners in a memory clinic sample

AbstractIntroductionDepressive symptoms are a common comorbidity in an old age memory clinic population. Cognitive and affective syndromes coexist, and supposedly modulate each other. While, there have been separate research streams on analysing speech to infer cognitive performance, as well as mood related symptoms, they are seldom investigated side‐by‐side. We present results from a small sub sample of a larger MCI and dementia cohort indicating that modelling both depressive symptoms and cognitive problems from speech can improve the diagnostic accuracy for MCI above speech biomarkers for cognition alone.MethodsThe ki:e Speech Biomarker for cognition (ki:e SB‐C; Tröger et al., 2022) and a free speech task were collected from 35 memory clinic participants (12F) with 10 of them having an MCI diagnosis (compare Table 1). From the free speech tasks (“Tell me about your upcoming vacation plans.”) we extracted speech features using ki:elements proprietary speech analysis engine SIGMA. Free speech features were corrected for cognitive performance, sex and age and then combined into a mood speech biomarker. To benchmark the diagnostic utility of both cognitive and mood speech biomarker side by side, we trained two groups of simple classifiers (tree based classifiers with leave one participant out cross validation) once with SB‐C alone and once with both SB‐C and the newly‐composed mood speech biomarker.ResultsBy combining the speech biomarker for cognition and mood diagnostic performance was significantly improved (AUC of 88%) as compared to classification with the SB‐C alone (AUC of 74%). The mood biomarker correlates significantly with the Geriatric Depression Scale (r = 0.39, p < 0.05). Most important free speech features were jitter, number or pauses, mean pause duration or pronoun rate.ConclusionOverall we present rare evidences that combining speech‐based digital biomarkers tapping both into cognition but also mood‐related symptoms helps to improve diagnostic accuracy in MCI patients. Though just a small feasibility study, the results are clearly encouraging and point towards potential application in both clinical practice as well as clinical research.

Fully Automated Lumipulse Plasma Amyloid and phosphorylated Tau assays for Progression to Alzheimer’s disease in Mild Cognitive Impairment patients

AbstractBackgroundLumipulse G automated immunoassays represent the most widely used method for the quantification of Alzheimer’s disease (AD) biomarkers in cerebrospinal fluid (CSF)1. Less invasive blood‐based markers confer a promising tool for AD diagnosis at prodromal stages (Mild Cognitive Impairment‐MCI)2. Highly sensitive assays for the quantification of amyloid‐beta (Aβ) and phosphorylated Tau‐181 (p‐Tau181) in blood are showing promising results3. In this study we evaluated the clinical performance of the available Lumipulse plasma markers for progression to AD.MethodA group of 138 patients (22 neurological controls‐NC, 72 MCI and 44 AD) recruited at the Dementia Clinic of Centro Hospitalar Universitário de Coimbra (CHUC) was included. Data regarding baseline CSF levels of Ab42, Ab40, t‐Tau and p‐Tau181 was available, allowing for characterization into ATN categories4. Baseline Ab42, Ab40 and p‐Tau181 levels were determined in stored plasma samples using high‐throughput fully automated Lumipulse assays. Progression from MCI to AD dementia was assessed at follow‐up (mean 5.9±3.0 years; 36 converted ‐MCI‐AD/36 stable ‐MCI‐St).ResultIn the total cohort, correlations between CSF and plasma were moderate for p‐Tau 181 (r = 0.61, p<0.001), weak for Aβ42 (r = 0.28, p = 0.001) and non‐significant for Aβ40 (r = ‐0.05, p = 0.54). Plasma p‐Tau181 levels were significantly increased while Aβ42, Aβ42/Aβ40 and Aβ42/p‐Tau181 were significantly decreased (p<0.001) in patients classified as MCI‐AD and AD in relation both to NC and MCI‐St. Plasma p‐Tau181 showed a robust performance in differentiating NC+MCI‐St vs. MCI‐AD+AD (AUC = 0.89, 95%CI:0.83‐0.94), MCI‐St vs. MCI‐AD (AUC = 0.89, 95%CI:0.81‐0.96) and CSF A+ vs. A‐ (AUC = 0.84, 95%CI:0.77‐0.91). Plasma Aβ42/p‐Tau181 gave similar AUC results (AUCs = 0.88, 0.84 and 0.83) and showed no significant differences compared to p‐Tau181 alone (p = 0.34, 0.33 and 0.92). For MCI‐St vs. MCI‐AD, when maximizing for sensitivity (0.92, specificity 0.67), baseline plasma p‐Tau181 levels higher than 1.69 pg/mL predicted future AD dementia (HR = 11.5; 95%CI = 10.9‐12.1).ConclusionOur results show that the measurement of p‐Tau181 in peripheral blood has great potential as a non‐invasive prognostic screening tool for AD dementia in MCI patients.1. Delaby C, et al. Alzheimer’s Dement. 2021; 2.Teunissen CE, et al. Lancet Neurol. 2022; 3.Palmqvist S, et al. Nat Med. 2021; 4.Jack CR, et al. Alzheimer’s Dement. 2018

Tracing the spatial extent of cortical tau over time in Alzheimer’s disease

AbstractBackgroundNeuropathological studies defined the paradigm that tau—the pathological hallmark of Alzheimer’s disease (AD)—spreads homogenously across individuals from the medial temporal lobe to the neocortex. This staging system is referred to as Braak stages. However, neuroimaging studies have since highlighted significant inter‐regional and inter‐individual differences in tau spreading patterns. We investigated the spatial extent of cortical tau over time in the amnestic AD spectrum.MethodWe included 195 amyloid‐positive ADNI participants that had at least two tau‐PET scans (90 cognitively unimpaired [CU], 66 with mild cognitive impairment [MCI], 39 with AD dementia; average follow‐up 2.6 years). We derived regional thresholds of tau positivity for 64 cortical regions and the amygdalae using Gaussian mixture modeling and applied them to all tau scans. The same approach was used to obtain thresholds for composite regions corresponding to the Braak stages. For each region, we calculated the rate of change in the amount (i.e., standardized uptake value ratio [SUVR] change) of tau pathology and the annual change in the positivity status (i.e., spatial extent change). These rates were compared between diagnostic groups using linear mixed models.ResultAcross diagnostic groups, change in tau positivity followed Braak staging; over 90% of participants positive at follow‐up either progressed or were already positive on a previous Braak stage at baseline (Fig‐1AI) and greater SUVR change was observed in temporal regions (Fig‐1B). However, across the brain, there was heterogeneity between individual patterns of tau positivity progression (Fig‐1AII). This heterogeneity was most striking in MCI patients, where many regions progressed from low to high levels of tau (Fig‐1C). Regional SUVR change did not differ between participants with AD or with MCI (Fig‐2A), but participants with MCI showed the fastest change in regional positivity compared to participants with AD and CU participants. (Fig‐2B)ConclusionWhile tau propagation follows Braak staging, inter‐individual differences can be found by considering a fine‐grained approach of regional progression to positivity. Furthermore, participants with MCI have the highest number of regions becoming abnormal annually. Our research pushes the importance of considering the entire brain when studying change in tau pathology, particularly before AD diagnosis.

Slow‐breathing induced hypocapnia mitigates deficit of vasoreactivity measured in patients with cognitive impairment

AbstractBackgroundA multi‐center study in Los Angeles (USC), Kansas City (KUMC) and Dallas (UT‐SWMC) has been quantifying the dynamics of CO2 vasoreactivity in MCI/AD patients and cognitively normal controls under spontaneous resting conditions. The goal is to develop effective vasoreactivity physio‐markers for early diagnosis of MCI and pre‐clinical AD, based on previous findings of significantly reduced vasoreactivity in MCI patients [Marmarelis et al., J. Alzh. Dis. 56:89‐105, 2017]. Here, we report on the effects of slow‐paced breathing upon these physio‐markers.MethodSpontaneous changes in arterial blood pressure (ABP), end‐tidal CO2 (etCO2), and cerebral blood flow velocity (CBFV) in middle cerebral arteries were recorded under resting conditions over two 6‐8 min sessions, separated by session of slow‐paced breathing (6 breaths/minute), in 47 MCI and 25 AD patients and 58 age‐matched cognitively normal controls. Using our novel methodology, we obtained predictive models of the dynamic effects of ABP and etCO2 upon CBFV using the universal convolutional form of linear dynamic models, which are defined by the respective “kernels” estimated from time‐series data. The etCO2‐to‐CBFV kernel is used to compute indices (physio‐markers) that quantify the vasoreactivity in each participant.ResultThe vasoreactivity index for each participant is computed from the integrated etCO2‐to‐CBFV kernel as the time‐average over the first 30 sec. The average kernels for patients and controls are shown in Figures 1‐2 for the two sessions respectively. Note the smaller kernel values for patients – while the difference is reduced after slow‐paced breathing. The obtained vasoreactivity indices are significantly smaller for 72 patients (MCI and AD taken together) vs 58 controls for the first session [p = 0.018; mean (SD): 0.057 (0.539) vs 0.424 (1.076)] but NOT for the session after slow‐paced breathing [p = 0.237; mean (SD): 0.193 (0.731) vs 0.361 (0.863)]. Average etCO2 was lower after paced‐breathing [p = 10−6; mean (SD): 36.23 (6.18) vs 33.44 (6.36)].ConclusionQuantitative analysis of cerebral CO2 vasoreactivity under resting spontaneous conditions in 72 MCI/AD patients vs 58 age‐matched controls, before and after slow‐paced breathing, revealed that the significant vasoreactivity deficit in MCI/AD patients is mitigated (at least temporarily) after slow‐paced breathing. This effect may be due to observed hypocapnia induced by slow‐paced breathing.

Neuropsychological and biomarker predictors of conversion to dementia in young‐onset Mild Cognitive Impairment

AbstractBackgroundMild Cognitive Impairment (MCI) is a clinical condition that captures the stage between normal aging and dementia along the continuum of cognitive impairment. While it is usually thought to be precursor of Alzheimer’s Disease, when occurring at young ages (i.e., before 65 years old) it may increase the risk of all forms of neurodegenerative dementing diseases. We studied which neuropsychological and biomarker characteristics are predictors of conversion to dementia in a sample of patients with young‐onset MCI.MethodSubjects with a diagnosis of MCI and early‐onset of cognitive symptoms (< 65 yo) were recruited in a prospective longitudinal study. They underwent extended neuropsychological assessment, Magnetic Resonance Imaging with measurement of hippocampal volume, and lumbar puncture with measurements of cerebrospinal fluid (CSF) light‐chain neurofilaments (NFL), beta‐amyloid 1‐42, total‐ and phosphorylated‐tau. They were followed‐up clinically and repeated the neuropsychological evaluation at 18 months from the baseline. Statistical analyses were performed with Stata15. Each biomarker and neuropsychological variable were added in multivariate Cox regression models with age, sex, and education.Result84 young‐onset MCI patients were recruited. After 18 months, 26 converted to dementia while 58 remained stable (i.e., MCI). Preliminary analyses showed that baseline smaller bilateral hippocampal volumes, lower baseline MMSE scores, baseline worst performances in tests of language, verbal long‐term memory, and executive functions, as well as baseline elevated levels of CSF NFLs increased the risk of conversion to dementia. Among them, the higher risk was given by the Free and Cued Selective Reminding Test (FCSRT), the Corsi Supraspan, the Frontal Assessment Battery, and the CSF NFLs levels, as shown by spline regression analyses (Figure 1). Of note, the FCSRT delayed recall showed a U‐shaped relationship with the risk of conversion (i.e., not only low/bad performance but also high/good performance were both related to a higher risk of conversion) suggesting that the types of predicted conversion may be different.ConclusionOur results suggest that, in young‐onset MCI, a combination of CSF‐NFLs levels and baseline performance at long‐term memory tests may be predictive of conversion to dementia, either AD or FTD.

Clinical Manifestations.

The capacity to handle money and personal finances is crucial for living independently. Cognitive decline can lead to financial mismanagement (e.g., forgetting to pay bills, overspending) and exploitation (e.g., falling for financial scams). While greater susceptibility to financial mismanagement and exploitation is commonly reported by carers of people with dementia, objective neuropsychological measures of these financial skills are scarce. It is also unclear whether profiles of change in financial skills vary across different stages and subtypes of dementia. A normative sample of 112 healthy controls and individuals with mild cognitive impairment (MCI; n = 16), Alzheimer's disease (AD; n = 7) or behavioural-variant frontotemporal dementia (bvFTD; n = 18) completed a novel neuropsychological Test of Financial Skills (TOFS), which assessed performance across three key areas: everyday financial tasks, susceptibility to financial scams and financial goal planning. For all patients and controls, measures of dementia severity (Clinical Dementia Rating Scale) and general cognition (Addenbrooke's Cognitive Examination, 3rd Ed.) were also collected. Relative to controls, AD and bvFTD patients showed lower overall performance on the TOFS, whereas MCI patients did not differ significantly from controls. While AD and bvFTD patients showed similar levels of impairment on everyday financial tasks and financial goal planning, bvFTD patients performed significantly worse on the financial scams subtest. Across all participants, lower TOFS performance was associated with greater dementia severity and cognitive impairment. Our results are consistent with previous studies of carer-reported changes in financial mismanagement and exploitation in people with dementia. Notably, we found important differences in the areas of financial skills impacted by different stages and subtypes of dementia. These findings provide novel insights into the different factors that contribute to deficits in financial skills in people with dementia, highlight the importance of objective neuropsychological assessments in this area, and open avenues for targeted financial support strategies.

Predictive value for cerebrospinal fluid Alzheimer’s disease profile of different measures of verbal episodic memory in patients with mild cognitive impairment

AbstractBackgroundEpisodic memory deficits represent the typical manifestation of prodromal Alzheimer’s disease (AD), namely amnestic Mild Cognitive Impairment (a‐MCI). Current neuropsychological criteria for MCI recommend the use of at least two measures for each cognitive domain. Rey Auditory Verbal Learning Test (RAVLT) and Logical Memory (LM) are two widely used verbal episodic memory measures. Our aim was to investigate the value of these measures in predicting cerebrospinal fluid (CSF) AD biomarkers positivity in a retrospective fully characterized consecutive MCI cohort.MethodOne‐hundred and six MCI patients were included. All of them underwent a comprehensive neuropsychological assessment including RAVLT (sub‐measures: RAVLT‐imm, RAVLT‐del, RAVLT‐false_recognitions) and LM. All patients underwent lumbar puncture for the analysis of CSF core AD biomarkers (Aβ42/Aβ40 ratio, phospho‐tau, total tau). By applying the A/T/(N) classification model, patients were classified as AD (A+T+, MCI‐AD, n. 62) and non‐AD (A‐T*, MCI, n. 44). Pearson’s r correlation coefficient was used to assess the relationship of RAVLT and LM sub‐scores with diagnosis. WALD logistic regression model was used to find which memory sub‐measures show the best predictive value on biomarkers positivity. To evaluate the discriminatory power of different sub‐measures for CSF AD profile, receiver‐operating characteristic (ROC) curves were generated.ResultWith respect to non‐AD MCI, MCI‐AD patients showed worse scores on all RAVLT and LM sub‐measures. RAVLT‐del could predict both positivity of each biomarker (p<0.01) and CSF AD‐like profile (p<0.01). The combination of RAVLT‐del with other measures (RAVLT‐imm+RAVLT‐false_recognition+LM) discriminated these groups (AUC: 0.76, 95% CI: 0.67‐0‐85) with a sensitivity of 0.74 and a specificity of 0.66.ConclusionOur study shows that the combination of all RAVLT memory sub‐measures and LM reaches the higher diagnostic accuracy in discriminating non‐AD MCI from MCI‐AD patients. Since RAVLT and LM measure different aspects of verbal episodic memory, they should be considered as complementary, rather than interchangeable, tasks. Our findings support the use of different memory measures in the neuropsychological assessment of MCI patients.

AMYPAD: Correlation of Amyloid PET results with anxiety and depressive symptoms in SCD+, MCI and dementia patients

AbstractBackgroundDepression and anxiety are two frequent neuropsychiatric symptoms in Alzheimer’s disease (AD). Moreover, depressive symptoms and anxiety are frequently associated with greater amyloid deposition and risk of Alzheimer’s dementia. The aim of the present study is to assess the association between anxiety and depression and amyloid burden.MethodIn the AMPYAD study, participants with subjective cognitive decline (SCD+, n = 244), mild cognitive impairment (MCI, n = 341) and dementia (n = 255) were enrolled in eight European memory clinics between 2018 and 2020. They underwent three study visits (baseline, six months, thirteen months) with collection of cognitive data and symptoms of depression and anxiety (Hospital Anxiety and Depression Scale, HADS) as well as measures of quality of life and coping strategies. Amyloid burden was obtained as the standardized centiloid values (CL). Correlation analyses were carried out for HADS‐Scores and CL. We analyzed the progression of depressive and anxiety symptoms over time between patients with and without presence of amyloid (CL≥21) using mixed‐model‐ANOVA. All analyses were corrected for time of PET result disclosure.ResultA total of 840 patients (46.2% female; mean age of 70.9 (SD = 7.8)) were included. Among SCD+ patients, CL values were positively correlated with baseline anxiety scores (r(216) = .14, p = .038). In contrast, MCI and dementia patients showed a negative correlation between CL and depressive symptoms (r(296) = ‐.16, p = .005; r(209) = ‐.23, p<.001). In SCD+, there was no significant interaction between time and CL status for anxiety (p = .512), but a significant main effect of time (F(2,302) = 3.4, p = .036, η² = .02), indicating a decline in anxiety symptoms over time. A trend indicated higher anxiety for amyloid positive participants, but the effect missed statistical significance (p = .068). For depressive symptoms, we found no main effects and no significant interaction of time and CL status.ConclusionThe AMYPAD study contains a large amyloid‐PET data set of patients from eight European memory clinics. We observed an association of increased anxiety scores with amyloid load in SCD+, but reduced symptoms of depression with higher amyloid load in the MCI and dementia group. These findings and their longitudinal development over time will be put into a broader context of patient characteristics.

Memory alteration test (M@T) is correlated with CSF biomarkers and neurodegeneration in patients with aMCI and AD in a low‐and‐middle‐ income country

AbstractBackgroundAs new therapies become available, early detection of Alzheimer’s disease (AD) becomes increasingly important. However, the use of biomarkers or advanced imaging has not been fully implemented in low‐ and ‐middle income countries (LMICs), especially in Latin America. Given that brief cognitive tests (BCTs) are widely available and easy to administer, we evaluated the capacity of the AD‐focused BCT, the Memory Alteration Test (M@T), to detect AD, neurodegeneration markers in MRI, and its correlation with CSF biomarkers.MethodThis is a secondary analysis from a previously published cohort of 63 controls, 53 amnestic MCI (aMCI), and 69 AD patients. They underwent testing with the M@T and a complete neuropsychological battery. Total‐tau (t‐tau), phosphorylated tau (p‐tau) and β‐amyloid in CSF were measured in all included patients. Neurodegeneration was determined by Medial Temporal Atrophy (MTA) score in MRI. We used Receiver‐Operator Curves to determine the discriminative capacity of the total M@T score as well as its subdomains. We used the Pearson coefficient and performed a linear regression between total score and CSF biomarkers.ResultThe M@T score had an AUC of 0.994 to discriminate between controls and cognitively impaired (aMCI or AD) patients, and an AUC of 0.98 to differentiate between aMCI and AD patients. Free‐recall and cued recall had the highest AUCs of all subdomains. Total score was strongly correlated with t‐tau (‐0.77) and p‐tau (‐0.72), and moderately correlated with β‐amyloid (0.66). The AUC for discrimination of neurodegeneration was 0.87.ConclusionThe M@T brief cognitive test had excellent discrimination of MCI and AD patients in an LMIC. It was also strongly correlated with CSF biomarkers and had good discrimination of Neurodegeneration. The recall sub‐domains presented the highest diagnostic capacity. Its use as a screening tool could allow LMICs to enrich samples of patients who may benefit from new available therapies.

Plasma based assessment of extracellular vesicles biomarkers in Alzheimer’s Disease

AbstractBackgroundCurrently there are no widely accepted diagnostic tests for Alzheimer’s disease (AD). Although there is much excitement in the field of biomarker development, most proposed tests for AD are expensive, require highly specialized sample handling, invasive approaches or radiation exposure. The goal of this project was to develop non‐invasive AD biomarker assessment using nanoflow cytometry to examine proteins on circulating brain‐derived extracellular vesicles in plasma.MethodPlasma samples were collected from a population of individuals clinically diagnosed with MCI and mild, moderate or severe Alzheimer’s disease and cognitively intact control subjects. Plasma was incubated with fluorescently‐conjugated antibodies against candidate biomarkers including oligomeric amyloid, fibrillar amyloid, amyloidβ‐42, pTau‐T181, pTau‐T217, pTau‐S235, Ubiquitin, Neurofilament, α‐synuclein and synaptophysin. After incubation, labelled events were quantified using the Apogee Microplus nanoflow cytometer. Using Receiver‐Operator Curve (ROC) analysis, the ability of individual markers and various combinations to distinguish diagnostic groups was determined.ResultNanoflow cytometry quantification of pTau‐T181, pTau‐T217, pTau‐S235, pTau‐T231, Aβ‐42 (among others) successfully distinguished MCI and AD plasma from healthy controls. Using ROC analysis, our most sensitive antibodies (pTau‐ T231) separate controls from AD patients with an AUC of 0.96 (Sens: 0.95/Spec: 1.0). Other prominent antibodies include pTau 181 with an AUC of 0.93 (Sens: 0.92/Spec: 0.92). The most promising combination of antibodies combines beta‐amyloid42 and pTau‐181 to separate AD patients from controls with an AUC of 0.960 (Sens: 0.93, Spec: 0.92). Isolation of EVs from plasma and validation of marker labeling was performed with Western Blot, ELISA and transmission electron microscopy.ConclusionHere we demonstrate the use of nanoflow cytometry to directly quantitate proteins on circulating extracellular vesicles in plasma from MCI and AD patients. The assays are rapid, inexpensive, directly quantitative, and require mini sample volume and manipulation. Future studies are required involving a larger population of patients who have had ‘gold standard’ biomarkers (Amyloid and tau CSF measurements), longitudinal follow‐up and/or autopsy confirmed diagnosis of AD.

Plasma SNAP‐25 as a potential Alzheimer’s disease biomarker

AbstractBackgroundSynaptic degeneration and dysfunction are hallmarks of several neurodegenerative diseases, including Alzheimer’s disease (AD). Several studies have shown that the presynaptic protein, synaptosomal‐associated‐protein‐25 (SNAP‐25), is increased in the cerebrospinal fluid (CSF) of AD patients. In the era of ultra‐sensitive immunoassays, the quantification of SNAP‐25 concentration in blood could provide an easily accessible measure of synaptic integrity in AD.MethodIn this pilot study, we investigated 42 participants (n = 23 cognitively unimpaired [CU]; n = 19 MCI or AD dementia patients [CI]) from Geneva University Hospital. A total of 27 participants underwent amyloid positron emission tomography (PET) scans and 14 underwent tau PET scans within 1 year. Global cognition was assessed with Mini Mental State Examination (MMSE). Mann‐Whitney tests were used to assess differences in plasma SNAP25 levels between diagnostic, amyloid (A+/‐) and tau (T+/‐) classification. Furthermore, we used Pearson correlations to assess the association between SNAP25, amyloid centiloid, Tau SUVr and MMSE.ResultThe mean age was 66.9 years +/‐ 7.6 years and 57% were female. SNAP‐25 was significantly increased in CI patients (0.87 pg/mL ±/‐ 0.19) compared to CU participants (0.59 pg/mL ±/‐ 0.11; p>0.001). SNAP‐25 levels were also significantly increased in A+ (0.89 pg/mL ±/‐ 0.18) and T+ (0.92 pg/mL ±/‐ 0.19) individuals compared to A‐ (0.65 pg/mL ±/‐ 0.09; p<0.001) and T‐ (0.717 pg/mL ±/‐ 0.07; p = 0.041). Moreover, we observed a significant correlation between the SNAP‐25 levels and amyloid centiloid (p = 0.016, rho = 0.48), while the correlation was not significant between SNAP‐25 and tau SUVr (p = 0.146, rho = 0.41). Finally, we observed a significant correlation between SNAP‐25 levels and MMSE score (p = 0.033, rho = ‐0.35).ConclusionThe novel plasma single molecular array (Simoa) can accurately quantify SNAP‐25 in blood plasma. In a pilot study, we observed significantly elevated plasma SNAP‐25 levels in cognitively impaired individuals and amyloid and tau positive individuals. Our findings suggest that SNAP‐25 is a potential biomarker indexing synaptic loss in AD. Further results will extend to a memory clinic cohort of >350 participants to assess its diagnostic and prognostic power and relationship to amyloid, tau, MRI and CSF biomarkers.

INCREASED CATALASE ACTIVITY IN AGING ADULTS WITH DOWN SYNDROME: ASSOCIATIONS WITH AGE AND COGNITIVE DECLINE

AbstractBackgroundThe aging process in Down syndrome (DS) is associated with a high prevalence of dementia, which is regarded as a variant form of early‐onset Alzheimer’s disease (AD). In addition to the central role played by amyloid pathology, DS‐dementia (DS‐D) may also be related to abnormal regulation of oxidative stress. The copper/zinc‐dependent superoxide dismutase (SOD1) gene is also located on chromosome 21, and studies have suggested an association of SOD1 overexpression with disrupted redox homeostasis. We hypothesize that such abnormalities may be further related to cognitive decline in DS.Method30 aging adults with DS were enrolled to the study, of whom 14 were cognitively stable (DS‐S) and 16 had evidence of cognitive decline (DS‐D). Two comparison groups were constituted with euploid volunteers, i.e., 30 age‐matched, cognitively healthy subjects (euploid controls, EU‐C); and 60 MCI and AD patients (EU‐MCI‐AD). We used an enzymatic assay to determine catalase activity.ResultAs compared to euploid controls, catalase activity was increased in DS irrespective of the presence of cognitive decline (p<0.004). This finding was also observed when the DS group was stratified according to the presence of cognitive decline (EU‐C vs. DS‐S, p<0.001; EU‐C vs. DS‐D, p<0.01). Catalase activity was also increased among cognitively stable DS as compared to MCI‐AD (DS‐S vs. EU‐MCI‐AD, p<0.027).When the DS group was stratified by age (18‐34y, 35‐49y, and ≥ 50y), catalase activity was found to be increased in younger and middle‐aged DS‐S as compared to EU‐C (18‐34y, p<0.01; 35‐49y, p<0.01) and in middle‐aged DS‐S as compared to SD‐D (35‐49y: p< 0.03).ConclusionOur preliminary findings suggest a systemic pro‐oxidant status in DS, evidenced by the increased catalase activity, presumably as a physiological compensation for redox imbalance due to the upregulation of SOD1 (data not shown). Furthermore, antioxidant defense functions decline with aging in the DS carrying. Thus, catalase could be a predictive biomarker candidate for AD.

Novel EEG tools to predict early cognitive impairments in Parkinson’s disease

AbstractBackgroundParkinson’s disease (PD) is a neurodegenerative disorder mainly characterised by motor symptoms but often also associated with dementia, increasing in likelihood with duration of disease. Electroencephalography (EEG) can aid in the early diagnosis of those at risk of developing dementia. Therefore, we analysed EEG recordings across conscious states from PD patients with and without cognitive symptoms (Latreille et al in 2016, https://doi.org/10.1093/brain/aww018).MethodBaseline data (REM sleep, NREM sleep, WAKE) from 38 PD patients (15 with and 23 without mild cognitive impairment) and 27 healthy subjects provided power spectra (qEEG), relative band power, as well as dominant frequency and its standard deviation to investigate markers for cognitive impairment. At follow‐up (an average 4.5 years after baseline), 11 patients developed dementia (PDD). Connectivity measures for left and right occipital and central electrodes were obtained as described in Crouch et al, 2018, https://doi.org/10.1038/s41598‐018‐19707‐1.ResultqEGG analyses confirmed previous reports of enhanced theta power during REM, NREM and WAKE for patients who developed PDD. A reduction in alpha power during WAKE was observed for MCI and PDD groups when compared to controls. Alpha rhythms generally decrease with age, alongside enhanced theta power, and this outcome may contribute to the global cognitive status of patients. A reduced and less variable dominant frequency was evident for MCI and PDD patients during WAKE, indicative of reduced flexibility of the network. Finally, rPDC detected disease‐specific changes, such as enhanced cross‐hemispheric connectivity in PDD in the alpha band during NREM sleep that indicate a lack of dynamism in the network. Also noted was the diminished interhemispheric communication in delta power between both central and occipital channels in PDD during WAKE.ConclusionTogether, we here confirm that changes of theta and alpha power are optimal discriminatory biomarkers for PD with cognitive decline (with MCI and at risk of dementia). Also, spectral and rPDC analyses indicate that dementia in PD is preceded by a loss of dynamism in EEG activity during MCI stages, both at the electrode and network level.

Prediction of short‐term MCI‐to‐AD conversion using multi‐modal neuroimaging features, and demographics

AbstractBackgroundMulti‐modality data can achieve better classification and regression performance than the use of only the single modality data. For this reason, we observed the potential of multiple data for early dementia conversion.MethodIn this study, the conversion group was defined as cases where MCI patients converted to dementia between 2 and 4 years, and T1‐weighted, T2 FLAIR, and Amyloid PET images were acquired from 4 domestic hospitals and ADNI. 114 volume features, WMH volume, and Fazekas scale were acquired from T1, T2 FLAIR images, and SUVR was calculated from amyloid PET. In addition to image features, age, sex, MMSE, and ApoE genotype were used. The 206 cases dataset was divided in a stratified way into a training set (80%) and testing set (20%), keeping the sample percentage of each class in both sets. We wanted to check the performance of each model on our dataset. The models used for this purpose were Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Linear Regression Classifier (LR), Gradient Boosting Model (GBM), Extreme Gradient Boosting (XGB). We trained and tuned each model, set up a grid search through hyperparameters to select a model that generalized well. The metrics used to evaluate model performance were BA, SE, SP, and AUC.ResultTable 2 and 3 present the obtained results of all ML models for the two‐class classification task using 10‐fold cross‐validation and testing. In the case of 10‐fold cross‐validation, the model with highest mean BA was the SV model with 0.927. However, in the case of testing, we can see in Table 3 that the model with the highest BA, SE, and SP obtained was the GBM model, which was 0.917, 0.900, and 0.933, respectively. When ensemble was performed using the top3 models, BA, SE, SP, and AUC of the ensemble model were 0.917, 0.900, 0.933, and 0.963, respectively.ConclusionMuti‐modal neuroimaging features with minimal demographic information showed reliable results in predicting the converters and non‐converters between 2 and 4 years. This study suggests it could be utilized for future clinical trials to provide a high‐risk group for dementia conversion in advance.