Amnestic Mild Cognitive Impairment Research Articles

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Amyloid-negative amnestic mild cognitive impairment (MCI) patients have a conversion rate to dementia of approximately 10% within 2 years. This study aimed to investigate whether brain age, calculated using quantitative data obtained from brain magnetic resonance imaging (MRI) artificial intelligence (AI) software can be an important factor in predicting the conversion of dementia in amyloid-negative amnestic MCI patients. We conducted a retrospective cohort study of patients with amyloid-negative amnestic MCI who visited the memory clinic of Asan Medical Center. All participants underwent detailed neuropsychological testing, brain MRI, and [18F]-florbetaben (FBB) positron emission tomography (PET) scan. Conversion to dementia was determined by a neurologist based on a clinical interview with a detailed neuropsychological test or a decline in the Korean version of the Mini-Mental State Examination score of more than 4 points per year combined with impaired activities of daily living. Brain age was determined through volumetric assessment of 12 distinct brain regions using commercially available segmentation software, Neurophet AQUA. During the follow-up period, 38% (35/91) of patients converted to dementia from amnestic MCI. 73% (66/91) of patients had a higher brain age than their actual chronological age. In the conversion group, all participants except three (91%, 32/35) had a brain age older than their chronological age. Conversely, the conversion rate to dementia was significantly lower in the group with a younger brain age than their actual age. The subjects were divided into eight groups based on sex, education level, and brain age. When defining the 'survival' as the non-conversion of MCI to dementia, these groups significantly differed in survival probability with a p-value of 0.036. The low-educated female group with a higher brain age than their actual age had the lowest survival rate of all groups. Our findings suggest that MRI-based brain age used in this study can contribute to predicting conversion to dementia in patients with amyloid-negative amnestic MCI.

Prospective cohort of elderly patients after hospitalization due to COVID‐19: preliminary results

AbstractBackgroundPost Covid‐19 syndrome can cause cognitive impairment and may be associated with a higher risk of developing dementia in older people.MethodThis is a cohort study that is evaluating over 12 months the functional status and cognition of elderly people after hospital discharge. One group is composed of elderly people admitted to the hospital for Covid‐19 and the other group is composed of elderly people hospitalized for other clinical reasons. The groups are evaluated with The Mattis (DRS), AD8, ADCS‐ADL, PCL‐C, GDS‐15, FIM, COPM, CFS, FSS, mMRC and SARC‐calf. We will describe the preliminary results of the first 31 patients included in the COVID‐19 group on functional status, cognition, mood and quality of life.ResultThirty‐one patients with COVID‐19 were evaluated three months after hospital discharge. One was excluded due to previous mental disorder and another due to a request to be excluded from the study. We found a mean age of 69.55 ± 7.72 years, schooling 7.14 ± 4.48 years, 51.7% female, Charlson Comorbidity Index 2.21 ± 1.84, 48.3% with smoking history and 62.9% had incomplete vaccine protection for COVID‐19. Considering cognition, 13.9% of the sample had no impairment, 55.1% had mild cognitive impairment (MCI) (17.2% amnestic MCI and 37.9% non‐amnesic MCI) and 31% had dementia. 24.1% declared their health status and quality of life as fair or poor. Mean CFS was 4.45 ± 1.18, GDS‐15 4.28 ± 3.38, FSS 30.76 ± 19.24, PCL‐c 29.34 ± 10.41, SARC‐calf 4.03 ± 4.61. All had mMRC dyspnea classified between 1 and 4.ConclusionThere was a high prevalence of mild cognitive impairment and dementia among patients after three months of discharge, with a predominance of mild frailty due to CFS and the presence of fatigue. It is noteworthy that a quarter of the sample reported low quality of life.

The molar ratio between PAI‐1 and BDNF is increased in Alzheimer’s disease patients with full dementia and negatively correlates with MMSE score

AbstractBackgroundIn a previous study, we demonstrated that the enzyme plasminogen activator inhibitor‐1 (PAI‐1), which inhibits plasmin synthesis in the central nervous system (CNS), is increased in the serum of patients with Alzheimer’s disease (AD). In addition to reducing the accumulation of Ab, plasmin in the CNS regulates the synthesis of the trophic factor brain‐derived neurotrophic factor (BDNF) which appears to be altered in the brain of patients with AD. We investigated whether BDNF serum levels in AD and amnestic mild cognitive impairment (aMCI) patients are altered compared to cognitively healthy controls. Moreover, we examined the PAI‐1/BDNF ratio in these patient groups and correlated with cognitive scores as measured by Mini‐Mental State Examination (MMSE).Method40 AD, 40 aMCI and 10 healthy controls were recruited. Venous blood was collected and BDNF serum concentration were quantified by sandwich ELISAs. Comparisons among the experimental groups (AD dementia, aMCI patients, and cognitively healthy controls) on BDNF serum levels were performed using univariate analyses of variance (ANOVA). Pearson correlation coefficients were calculated to explore relationships between biochemical and clinical data. The level of statistical significance was set at p<0.05.ResultThe results showed that BDNF serum levels are decreased in AD as compared to aMCI patients (p < .05). In addition, there was a positive correlation between PAI‐1 and BDNF serum levels (r = .190, p < .05). Furthermore, PAI‐1/BDNF ratio was significantly increased in AD patients as compared to aMCI (p < .001) and controls (p < .001). Lastly, PAI‐1/BDNF ratio negatively correlated with MMSE score (r = ‐.508, p < .001).ConclusionThese data suggest that in AD a reduction of plasmin caused by PAI‐1 may negatively affect the production of BDNF and promote disease progression. Our results also demonstrate that the PAI‐1/BDNF ratio is increased in AD patients compared with aMCI and controls. They also suggest that this ratio could be used as a marker of AD in a state of overt cognitive impairment, as supported by the strong negative correlation between PAI‐1/BDNF ratio and MMSE.

Measurement of amyloid beta in nasal secretions as a potential biomarker for Alzheimer’s disease

AbstractBackgroundWe investigated the level of amyloid beta (Aβ) in nasal secretions of patients with Alzheimer’s disease using multichannel impedance analyzer (ToAD) and electrical‐immunosorbent assay (El‐ISA), and determined the predictive value of Aβ in nasal secretions for AD diagnosis.MethodNasal secretions were obtained from 84 participants with probable AD dementia (ADD), 83 with amnestic mild cognitive impairment (MCI), 22 with cognitive decline associated with other neurological disorders (OND), and 62 cognitively unimpaired (CU) participants. Aβ oligomers in nasal secretions were analyzed using ToAD / El‐ISA analytical systems. Capture antibodies in El‐ISA kits specifically capture Aβ oligomer in nasal secretion, and then detection probes for El‐ISA method bind with amyloid beta oligomer sequentially. Finally, unbound free detection probes in solution was electrochemically measured by ToAD analyzer for quantifying Aβ oligomers. Because this analytical method is based on the back‐titration, the change of electrical signal is inversely proportional with the concentration of detectable Aβ oligomers. Electrical signals finally expressed to Cantis AD Index (CAI, 0∼99) which normalized by standards for system calibration.ResultThe CAI was higher in the probable ADD group than in the CU group (p < 0.05). The accuracy of the CAI was fair in separating into the probable ADD and CU groups (AUC of the ROC curve = 0.665, 95% CI = 0.572‐0.758, SE = 0.047, p = 0.001). The accuracy of the CAI was fair in separating into the participants with positive amyloid PET scan and those with negative amyloid PET scan (area under curve [AUC] of the receiver operating characteristic [ROC] curve = 0.697, 95% confidence interval [CI] = 0.629‐0.766, SE = 0.035, p < 0.001). The CAI has a negative correlation with Mini‐Mental State Examination score and positive correlations with Clinical Dementia Rating scale‐Sum of Boxes and amyloid PET centiloid scale scores.ConclusionThese results demonstrate that the level of Aβ in nasal secretions increases in AD and the detection of Aβ in nasal secretions using ToAD / El‐ISA analytical systems may be possible in predicting ADD.

Transcranial Magnetic Stimulation based Network Integrity Assessment in Alzheimer’s disease

AbstractBackgroundAlzheimer’s disease (AD) has a relatively well‐characterized pathology of amyloid‐β and tau accumulation. Yet, disease progression from preclinical to clinical stage remains largely unpredictable at the individual level. Growing evidence shows disrupted synaptic signaling in functionally connected brain networks early in the preclinical stage, and suggests impaired network integrity, assessed with functional connectivity measures, as potential markers for disease symptomatology in AD.MethodHere propose a novel TMS‐induced causal connectivity measure reflecting integrity of multi‐synaptic signaling within the stimulated brain networks. In a preliminary sample of 9 cognitively normal older adults (Healthy Controls: HCs) and 11 patients with amnestic mild cognitive impairment or mild dementia (early AD), we applied 150 single pulses of TMS to inferior parietal lobule (IPL), a distinct brain region within the default mode network (DMN) showing decreased metabolism in early AD and recorded TMS evoked neural responses with simultaneous electroencephalography (TMS‐EEG). We also characterized spontaneous brain activity with resting‐state EEG (rsEEG) measurements. We performed source space spectral power analyses and seed‐based power envelope correlations (PEC) to estimate cortical distribution of relative alpha power and spontaneous IPL connectivity as rsEEG measurements. Network integrity was defined as the ratio of significantly activated vertices to the total number of vertices within the DMN following TMS of IPL.ResultAlthough relative alpha power (8‐12 Hz) was slightly lower and seed based connectivity was slightly higher within the IPL node in AD participants, no network specific differences was observed across the cortex for both rsEEG measures. On the other hand, DMN integrity was substantially lower in AD participants with an average ratio of 0.53 (0.79 in HC) indicating that almost half of the vertices within the DMN were not activated by TMS.ConclusionOverall, these preliminary analyses suggest that perturbation‐based (TMS‐EEG) measures may reveal neurophysiological signatures of brain network dysfunction that are not observable in spontaneous brain oscillations, and thus may characterize defining features of network failure in preclinical and mild AD.

AB1601 Phase 2 Study of ABvac40, an Anti‐Aβ40 Vaccine: Safety and Immunogenicity of a Cross‐Over Extension

AbstractBackgroundAmyloid‐β (Aβ) immunotherapy is a promising strategy for treating Alzheimer’s disease (AD). Previous studies suggested that Aβ40 could have an important role in AD, especially in relation to amyloid deposition in blood vessels in AD. The AB1601 (NCT03461276) is a multicenter, randomized, double‐blind, placebo‐controlled, phase 2 study in patients with amnestic mild cognitive impairment (a‐MCI) or very mild AD (vm‐AD) which investigated the safety, tolerability and immunogenicity of repeated subcutaneous injections of ABvac40, a vaccine targeting Aβ40. The 24‐month study (Part A) showed that ABvac40 was safe, well‐tolerated and highly immunogenic. Here, an additional 18‐month cross‐over study (Part B) was conducted to evaluate safety, tolerability and immunogenicity of ABvac40 in patients randomized to placebo in Part A (Delayed start group), and to assess safety and immunogenicity of a delayed booster of ABvac40 in ABvac40‐treated patients in Part A (Booster group).MethodA total of 124 patients with a‐MCI (N = 80) or vm‐AD (N = 44) were initially included in Part A. Seventy‐seven out of 101 patients who completed Part A transitioned to Part B. Safety assessments included the frequency of amyloid‐related imaging abnormalities (ARIA). Immune response was assessed by quantification of specific anti‐Aβ40 antibodies in plasma samples.ResultABvac40 continued to show a favorable safety profile. Specifically, no ARIA‐E was reported and ARIA‐H incidence was low, equally distributed in both groups, and similar to the placebo group (Part A). Delayed start group showed a strong and specific immune response, with a time course equivalent to the ABvac40 group in Part A. A delayed booster of ABvac40 elicited a large increase in anti‐Aβ40 antibody plasma levels, exceeding the concentrations observed throughout the active dosing phase of Part A.ConclusionThe cross‐over extension of the AB1601 Phase 2 study confirmed the excellent safety and tolerability profile of ABvac40, making this vaccine a potential candidate to be combined with other disease‐modifying therapies. Results on immunogenicity supported those obtained in Part A, demonstrating that ABvac40 elicited a strong, specific, sustained and boostable immune response. This could have important implications for long‐term treatments, especially in the context of preventive approaches. Additional exploratory efficacy results of Part B are expected in Q4‐2023.

Structural Correlates of Speech Biomarkers in Alzheimer’s Disease and Mild Cognitive Impairment

AbstractBackgroundIn the present study, we aimed to confirm the association between speech characteristics of individuals with Alzheimer’s disease (AD) and amnestic mild cognitive impairment (MCI) and brain regions, and to investigate the neurobiological basis of speech‐based AD detection.MethodIndividuals with MCI (n = 13, age = 78.3), mild‐to‐moderate AD (n = 12, age = 77.8) underwent a structural MRI scan and engaged in three speech tasks: an interview, sentence repetition, and paragraph recall. From the speech samples, we extracted frequency‐related, intensity‐related, and temporal features which were found to be altered in the course of AD and MCI pathology. We selected nine regions of interest (ROI) which were found to be involved in speech production and reduced in MCI and AD pathology; the Inferior Frontal Gyrus (IFG), the Medial Frontal Gyrus (MFG), the Precuneus, the Inferior Parietal Lobe (IPL), Inferior Temporal Gyrus (ITG), Medial Temporal Gyrus (MTG), the Superior Temporal Gyrus (STG), the Fusiform Gyrus (FFG), and the Cerebellum. The linear mixed‐effect analysis was used to identify the associations between speech features and regional brain volumes.ResultThe Left IPL (χ2 (1) = 7.69, corrected P = 0.033), the Right ITG (χ2 (1) = 11.5, corrected P = 0.0128) the Right FFG (χ2 (1) = 9.35, corrected P = 0.0198) reduced the pitch of voice by about 0.887 ± 0.292, 1.368 ± 0.329, and 1.69 ± 0.429 respectively. The associations between the Right FFG (χ2 (1) = 4.58, corrected P = 0.0900), Left FFG (χ2 (1) = 5.87, corrected P = 0.0675) and loudness were marginally significant, with the reduction of volumes in the Right FFG and Left FFG decreasing the loudness by 0.096 ± 0.041, and 0.1165 ± 0.0454. The marginally significant associations were observed between the Right IPL (χ2 (1) = 4.75, corrected P = 0.0900), the Left FFG (χ2 (1) = 0.39, corrected P = 0.53) and the speech rate, and the atrophy of brain regions decreased the speech rate by 0.0824 ± 0.0363, 0.0535 ± 0.0079.ConclusionThe present study identified the associations between speech biomarkers and regional brain volumes providing clinical validity for the speech‐based Alzheimer’s disease detection.

Gene co‐expression network analyses in Mild cognitive impairment

AbstractBackgroundMultiomic data analysis has been extensively developed in recent years. Particularly, microarray data can be used as biomarkers of disease of progression specially in pathologies as cancer, autoimmunity and others. (Dahinden et al., 2010; Soleimani Zakeri et al., 2020). This modality of data analysis can also be employed in other multifactorial diseases as Alzheimer’s disease including the progression from normal cognition to mild cognitive impairment and finally to dementia. These genes work in intricate relationship with each other. The establishment of computational gene interaction networks shows the intricacy of the biological systems but increases the complexity of the analysis, for this reason, the removal of redundant edges leaves a network backbone revealing important driver nodes that are essential for the observed interactions, reducing the number of genes of interest and narrowing potential diagnostic or therapeutic targets. (Gates et al., 2021)MethodsWe used data from the ImaGENE study and the Weighted gene co‐expression network analysis (WGCNA) pipeline to analyze gene‐gene interactions of mRNA transcripts obtaining hierarchical clustering of genes and eigengenes in a sample of 160 individuals (Table 1). The backbones were obtained using the shortest path computation. (Gates et al., 2021; Simas et al., 2021). Gene ontology was used to classify processes associated with these genes.ResultsWe identified 42 hubs of differentially expressed genes and we analyzed the top 5 groups with the strongest association with amnestic mild cognitive impairment (MCI) phenotype (pfdr<0.0001). This cluster consisting of 46 genes was further classified according to function and interactions with other nodes in the backbone identifying processes like calcium signaling, nucleotide excision repair, fatty acid metabolism among others.ConclusionThere is an identifiable difference in gene expression in individuals with MCI compared to normal controls. The analysis of the backbone of the gene hubs allowed to reduce the number of genes of interest. This approach can help to elucidate important biological interactions, potential therapeutic targets and could eventually be used as risk factors markers for the development of MCI and AD.

Regional amyloid‐β is linked to disruptions in connected speech in amnestic mild cognitive impairment

AbstractBackgroundSpeech changes in amnesic mild cognitive impairment (aMCI) are potential markers for the early detection of Alzheimer disease (AD). However, few studies investigate the relationship between speech and amyloid‐β burden. The focus of this study was to examine the relationship between the linguistic features and the distribution of amyloid‐β load in aMCI.MethodThis study recruited 25 aMCI patients (52% female, aged 70‐85 years) and 25 healthy elders (44% female, aged 68‐80 years) from the memory clinic of Cardinal Tian Hospital in Taiwan. All participants received [18F] florbetaben PET and standardized cognitive tests. Amyloid‐β load using a standardized uptake value ratio (SUVr) was estimated from 5 cortical regions (parietal, frontal, cingulate, temporal, and occipital). Spontaneous speech was recorded using the picture description task (three Taiwanese culture‐related pictures) and transcribed verbatim. Linguistic features were extracted, including lexical richness (total words, unique words, type‐token‐ratio, lexical density, and frequency), syntactic complexity (mean length of utterance/sentence, ratio of verbs/pronouns/passive sentence), and speech fluency (ratio of long pauses/ fillers).ResultEighteen subjects with high amyloid burden (SUVr > 1.21) progressed (defined as CDR‐SB change≧1) within 1 year. We performed linear regression analyses between linguistic features (dependent variables, separate models) and amyloid‐β load in brain regions. Analyses were adjusted for age and education. The data revealed that a high amyloid‐β burden in the frontal region was associated with fewer unique words, less lexical density, and an increased proportion of long pauses and fillers. Reduced passive sentence, short mean length of utterance and lower scores on episodic memory tests related to increased amyloid‐β burden in the parietal region.ConclusionLexical richness and speech fluency was associated with amyloid‐β burden in the frontal region, indicating that voluntary lexical retrieval may require the additional recruitment of frontal lobe. Less syntactic complexity related to increased amyloid‐β burden in the parietal region. In conclusion, regional amyloid‐β is linked to subtle spontaneous speech deficits in aMCI.

Psychometric properties and diagnostic utility of the Technology‐Activities of Daily Living Questionnaire (T‐ADLQ) for illiteracy in Lima, Peru

AbstractBackgroundFunctional decline (FD) is defined as the deterioration of the ability to perform activities of daily living (ADLs). This FD is a critical dimension that allows determining the threshold between dementia disorders and previous stages of cognitive impairment. ADLs include activities that are divided into three main dimensions: basic (BADL), instrumental (IADL), and advanced (AADL). The Technology‐Activities of Daily Living Questionnaire (T‐ADLQ) (1) assesses these different ADL dimensions. To date, the dimensions of ADLs have not been assessed in the continuum ranging from healthy controls (HC), amnestic mild cognitive impairment (a‐MCI), to Alzheimer’s disease dementia (ADD) in the illiterate population. The study aimed is to validate the T‐ADLQ and evaluate FD across the three dimensions of ADL in healthy and cognitively impaired illiterate adults >50 years.MethodA cross‐sectional study of illiterate subjects in Peru. Inclusion criteria: men and women over 50 years of age; with less than one whole year of formal education and unable to read and write and grouped into 1 of 3 cognitive categories: healthy controls (HC) (n = 64), a‐MCI (n = 60), and early ADD (n = 63). Neuropsychological measures included the RUDAS, MMSE, and IFS. FD was assessed with the FAQ and the T‐ADLQ. The latter questionnaire, assessed by informants, evaluated the different dimensions of ADLs.ResultThe results on the global FD (T‐ADLQ total score) and the three ADL dimensions differed significantly among the three groups (Table 1). The T‐ADLQ total score correlated significantly with the FAQ (Table 2) and had high internal consistency (Cronbach’s alpha = 0.966). In addition, the T‐ADLQ total correlated significantly with instruments of global cognition and executive functions (Table 2). Finally, receiver operating characteristic (ROC) analyses, through the calculation of the area under the curve (AUC), showed that the total T‐ADLQ and the different dimensions discriminated better between HC vs. ADD and HC vs. a‐MCI but not between a‐MCI and ADD (Table 3).ConclusionThe total T‐ADLQ scale and its three dimensions have good psychometric properties (validity and reliability) and excellent diagnostic utility. This result demonstrates that the T‐ADLQ is a good instrument to evaluate FD in illiterate populations.

Electrical field strength from anodal prefrontal tDCS determines degree of white matter integrity changes in amnestic MCI patients

AbstractBackgroundAn electrical field (EF) strength induced by tDCS affects a therapeutic effect. Additionally, sequential tDCS has improved white matter integrity in cognitively impaired patients. However, researchers have not evaluated the impact of EF strength on white matter integrity in the prodromal stage of dementia. This study aimed to elucidate the effect of EF strength from prefrontal anodal tDCS on white matter integrity change and the modulating role of relevant genetic and pathologic factors in this effect in amnestic mild cognitive impairment (MCI) patients.MethodIn 55 amnestic MCI patients, we delivered anodal‐tDCS (2 mA/day, five times/week, for two weeks) over the left dorsolateral prefrontal cortex (DLPFC), calculated the EF strength for the left inferior frontal gyrus and DLPFC through the stimulation navigation program analysis. Additionally, we assessed the white matter integrity by diffusion tensor imaging before and after two weeks of stimulation; finally, we evaluated the modulating factors: amyloid‐beta (Aβ) deposition, APOE ε4‐allele status, and BDNF polymorphism.ResultAs the EF intensity in the left inferior frontal gyrus increased, the range of changes in white matter integrity significantly increased in left anterior thalamic radiation, corticospinal tract, inferior fronto‐occipital fasciculus, and inferior longitudinal fasciculus. Additionally, we found that greater change in white matter integrity was observed with higher regional EF strength in the APOE ε4 non‐carriers and BDNF MET non‐carrier, which could be attributed to an interaction between these modulating factors and EF intensity in the left anterior thalamic radiation and right uncinate fasciculus.ConclusionThese findings provide evidence for the precision‐medicine‐based application of tDCS in the prodromal stage of dementia, inducing the optimized therapeutic effect.

The Pattern of Hippocampus and Entorhinal Cortex Subregion Atrophy in Early Alzheimer’s Disease

AbstractBackgroundAtrophy of the hippocampus and entorhinal cortex (EC) develops early in Alzheimer’s disease (AD). The nature of atrophy along the anterior‐posterior longitudinal axis of the hippocampus and EC in individuals with amnestic mild cognitive impairment (aMCI) with positive AD biomarkers (AD aMCI) has been less researched. We aimed to reveal a possible different pattern of atrophy in longitudinal axis of the hippocampus and EC between AD aMCI individuals and those with AD biomarker negative aMCI (non‐AD aMCI).MethodIn total, 100 older adults with AD aMCI (n = 26), non‐AD aMCI (n = 23), mild AD dementia (n = 22) and cognitively normal (CN; n = 29) from the Czech Brain Aging Study (CBAS) underwent clinical and cognitive testing, and brain MRI with the 3‐dimensional T1‐weighted high‐resolution magnetization‐prepared rapid gradient echo sequences. An automated processing pipeline using the Advanced Normalization Tools based on the CBAS population template and a manual segmentation protocol were used to measure left and right subregional hippocampus and EC volumes including hippocampus head (HH), body (HB) and tail (HT), and anterolateral (alEC) and posteromedial (pmEC) entorhinal cortex volumes, respectively. Volumes were normalized to estimated total intracranial volume.ResultCompared to the CN group, the AD aMCI group had lower subregional hippocampus and EC volumes (p<0.05) except for right and left HH volumes. Compared to the non‐AD aMCI group, the AD aMCI group had lower right HB (p<0.05), right and left HT (p<0.01), right alEC (p<0.05), and right (p<0.01) and left (p<0.05) pmEC volumes. The mild AD dementia group had lower all subregional hippocampus and EC volumes compared to the CN group (p<0.05).ConclusionThese results are in line with previous research that demonstrated atrophy of the hippocampus and EC in early AD and indicate that atrophy of the posterior hippocampus and EC subregions may reflect AD pathology in aMCI individuals. Volumetric differences along the anterior‐posterior axis of the hippocampus and EC could serve as a potential biomarker to identify the underlying pathology in different neurodegenerative diseases.

Predicted Brain Age Difference Scores at Age 56 Are Associated with Executive Function Changes Across 12 Years

AbstractBackgroundPredicted brain age difference (PBAD) scores are novel metrics which compare chronological age to age predicted from neuroimaging data. PBADs are highly relevant to Alzheimer’s disease (AD) and cognitive aging. Individuals with AD have predicted brain ages about 10 years older than their chronological age (Franke et al. 2010). Less is known about PBADs in midlife, but recent work on the sample studied here has demonstrated that PBADs are highly heritable (59‐75%), highly stable between middle‐ and early‐old age, and moderated by modifiable lifestyle behaviors earlier in midlife (age 40). The current study examined how midlife PBAD (mean age 56) predicted executive functions concurrently and longitudinally into early old age (mean age 68).MethodWe examined 779 non‐demented men in the Vietnam Era Twin Study of Aging (VETSA) who completed cognitive and neuroimaging assessments at up to three assessments (M = 56, 62, and 68 years). PBADs were based on two methods (Liem et al., 2017, Cole et al. 2019) which include information about grey matter or both gray and white matter. Executive function was based on six tasks spanning inhibition, shifting and working memory. Analyses controlled for age, diabetes, hypertension, and APOE‐ε4 dosage.ResultLatent growth models revealed that greater PBAD at age 56 (i.e., greater brain age than chronological age) was associated with worse executive functioning at baseline and greater decline in executive functioning over the following 12 years. The latter association was observed only for PBADs that included white matter (Cole et al., 2019) and persisted even when excluding N = 61 individuals with amnestic mild cognitive impairment (MCI). Subsequent analyses indicated that associations were not moderated by APOE allele status or cognitive reserve (general cognitive ability at mean age 20).ConclusionOur findings indicate that PBAD is associated with executive functioning in midlife and predicts executive function changes into early old age. They also suggest that PBADs capturing more information about brain health are better predictors of executive function decline across midlife into early‐old age. Finally, the persistence of these effects within cognitively normal subjects suggests PBADs are important predictors of cognitive decline before the onset of MCI/AD.

Gamma‐band transcranial alternating current stimulation in amnestic mild cognitive impairment: A pilot study

AbstractBackgroundAmnestic mild cognitive impairment (aMCI) is a pre‐dementia stage of Alzheimer’s disease (AD) associated with dysfunctional episodic memory and limited treatment options. Recent findings from animal models of AD show that 40 Hz (gamma) stimulation (e.g., through light, sound, magnetic, or electrical stimulation sources) can improve episodic memory and learning, can facilitate neurogenesis, and can also reduce biomarkers associated with AD pathology including beta‐amyloid (Aβ) and tau. Although preliminary studies regarding the efficacy of gamma stimulation in humans has been promising, evidence is limited, neuroplastic changes are unclear, and the feasibility of electrical‐based gamma stimulation is still under investigation. Here, we aimed to characterize feasibility and neuroplastic changes associated with possible improvements in episodic memory following electrical non‐invasive neurostimulation.Method13 individuals with aMCI received eight 60‐minute sessions of 40‐Hz (gamma) transcranial alternating current stimulation (tACS), in a single‐arm design. Primary outcomes assessed side‐effects and drop‐out as indicators of feasibility. Secondary outcomes included episodic memory, plasma‐based Aβ and tau. Exploratory measures included neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP) and white matter fractional anisotropy. Additionally, neuroplastic changes were characterized by resting state functional connectivity (RSFC) within an episodic memory network and neuronal excitatory/inhibitory (Glx/GABA) balance via magnetic resonance spectroscopy.ResultResults revealed that gamma tACS was feasible (minimal side effects and no drop‐outs due to tACS). Moreover, aMCI participants demonstrated improvement in multiple metrics of episodic memory, but no changes in Aβ, tau, NfL, or GFAP. Improvements in episodic memory were most pronounced in participants who had the highest modeled tACS‐induced electric fields and exhibited the greatest changes in RSFC – all within an episodic memory network. Increased RSFC was also associated with greater hippocampal excitability and higher baseline white matter integrity across numerous tracts.ConclusionThis study highlights the potential of gamma tACS to improve episodic memory in an aMCI population by modulating functional connectivity and excitability within an episodic memory network.

Cognitive and Functional Connectivity Outcomes from a Phase I Trial of Accelerated High‐Dose Repetitive Transcranial Magnetic Stimulation in Amnestic MCI

AbstractBackgroundRepetitive transcranial magnetic stimulation (rTMS), most widely used to treat depression, may have secondary benefits for cognition. Accelerated high‐dose protocols such as intermittent theta burst (iTBS)‐rTMS shorten the treatment course by >50%, potentially improving the feasibility of use in patients with cognitive impairments. Here, we present the results of a phase I trial of iTBS‐rTMS for improving cognition in individuals with amnestic mild cognitive impairment (aMCI) and we explore whether functional brain changes relate to improved cognition.MethodTwenty‐two patients with clinically diagnosed aMCI received 24 sessions of open‐label iTBS‐rTMS to left dorsolateral prefrontal cortex (l‐dlPFC) over 3 days. Nineteen had complete brain MRI and cognitive testing pre‐ and immediately post‐treatment. The primary cognitive outcome was the norm‐adjusted fluid cognition composite T‐score from the NIH Toolbox Cognition Battery. Resting‐state functional connectivity was computed from subject‐specific parcellations mapped to each individual’s functional topology. We examined changes in connectivity within and between the FPN (of with the l‐dlPFC is a hub) and networks implicated in cognition (FPN, dorsal and ventral attention, limbic, default mode). We assessed whether connectivity changes (post minus pre) related to change in fluid cognition.ResultWe achieved a high retention rate of 95%. Treatment with iTBS‐rTMS was safe, with no adverse neuroradiological, neuropsychiatric, or neurocognitive effects. Side effects were minimal and acceptability ratings were high. Treatment produced significant, large effect size (d = 0.98) improvements in fluid cognition (Fig. 1A), and we observed preliminary evidence of related changes in functional connectivity. Specifically, there was a numerical increase in within‐FPN connectivity and a marginally significant increase in connectivity between cognitive networks (Fig. 1B). Further, there was a medium‐strength and marginally significant association between increased within‐FPN connectivity and improved fluid cognition (Fig. 1C).ConclusionThis phase I trial demonstrated that iTBS‐rTMS is safe, feasible, and acceptable in aMCI. Although not dosed for efficacy, we observed large improvements in fluid cognition and preliminary evidence of increased functional connectivity in expected brain networks that related to improved cognition. These promising results support iTBS‐rTMS as potentially efficacious in improving cognition in aMCI, directly informing larger, planned follow‐up randomized controlled phase II trials.

Spatial navigation performance differentiates Alzheimer´s disease biomarker positive and biomarker negative cognitively impaired older adults

AbstractBackgroundSpatial navigation deficits including egocentric (body‐centered) and allocentric (world‐centered) navigation impairment are present early in Alzheimer´s disease (AD). We evaluated a potential of a realistic‐looking spatial navigation task to differentiate older adults with amnestic mild cognitive impairment (aMCI) who have positive AD biomarkers (AD aMCI) from those with negative AD biomarkers (non‐AD aMCI).MethodParticipants with AD aMCI (n = 24), non‐AD aMCI (n = 25), mild AD dementia (n = 14) and cognitively normal (CN) older adults (n = 35) underwent spatial navigation assessment in the virtual Supermarket task. Participants passively travelled through the supermarket and followed different routes to reach specific locations. In the final location, the participants had to indicate their starting location (egocentric heading) and their current location and final heading orientation on an aerial spatial map of the supermarket (distance from the correct location and allocentric heading, respectively, both measures of allocentric navigation).ResultIn the egocentric heading, the AD aMCI and mild AD dementia groups indicated their original starting location less accurately than the CN group (p<0.001) and with similar accuracy as the non‐AD aMCI group (p> = 0.219). The non‐AD aMCI group did not significantly differ from the CN group (p = 0.055). In the first allocentric task (distance from the correct location), the AD aMCI group and mild AD dementia groups indicated their positions on a paper aerial map of the supermarket with greater distance errors compared to the non‐AD aMCI group (p< = 0.013) and CN (p<0.001) groups. The non‐AD aMCI group had comparable performance to the CN group (p = 0.172). In the second allocentric task (allocentric heading), both the AD aMCI and mild AD dementia groups made more errors indicating final heading orientation than the non‐AD aMCI (p< = 0.040) and the CN (p<0.001) groups. The non‐AD aMCI group had worse performance than the CN group (p = 0.004). The sensitivity and specificity for discriminating AD aMCI and non‐AD aMCI was 72% and 71%, respectively.ConclusionBoth, egocentric and allocentric spatial navigation tasks detected spatial navigation impairment in older adults with AD aMCI. However, only the allocentric tasks differentiated AD aMCI from non‐AD aMCI. The virtual Supermarket task has a potential to become a screening tool for early AD‐related spatial navigation deficits.

Measurement Invariance of the NIH Toolbox‐Cognition Battery Across Demographic Characteristics

AbstractBackgroundThe tablet‐based NIH Toolbox‐Cognition Battery (NIHTB‐CB) was compared against the established NACC Uniform Data Set 3.0 (UDS 3.0) neuropsychological battery (used across Alzheimer’s Disease Research Centers). NIHTB‐CB factor invariance is critical for drawing appropriate cross‐demographic conclusions. Invariance was assessed across both batteries for consensus‐driven clinical diagnosis, sex, and age in a large sample of participants from the Advancing Reliable Measurement in Alzheimer’s Disease and Cognitive Aging (ARMADA) study. Goals of this project were to establish the factor relationship of these two batteries and examine their invariance across the aforementioned demographic characteristics.MethodNIHTB‐CB tasks measure Crystalized and Fluid ability. Tests were administered to 571 participants aged 65 to 99 years (mean age 77.2±7.8, 41% female) with normal cognition or amnestic mild cognitive impairment. Groups were classified for age (< = 85 and > 85), gender, and diagnosis. Exploratory Factor Analysis (EFA) was tested for each group with confirmatory factor analysis. If the model fit sufficiently between groups for the configural model, then metric, scalar, and strict invariance models were also examined. Uncorrected standard scores were used for analyses.ResultA four‐factor model emerged as the best fitting model and was invariant across all demographic groups through adjustments. Factor 1: Language (MINT Total, Oral Reading, Picture Vocabulary); Factor 2: Auditory retention (Digits Forward Total and Digits Backward Total); Factor 3: Learning/Memory (List Sorting Working Memory, Picture Sequence Memory, Craft Story 21 Immediate Recall, Craft Story 21 Delayed Recall, Benson Delayed Recall, Animals Category, Vegetables Category, and MoCA Total Score); Factor 4: Attention/Executive Functioning (Dimensional Card Sort, Flanker, Trails A, Trails B, Pattern Comparison Processing Speed, and Benson Recall). We found strong support for strict invariance across the assessed demographic characteristics.ConclusionA four‐factor structure comprised of NIHTB‐CB and UDS 3.0 tests supports the validity of the NIHTB‐CB by matching both UDS 3.0 and NIHTB‐CB measures as expected. Strong support for strict invariance reflects the psychometric equivalence of the NIHTB‐CB construct across the groups. The psychometric properties of the NIHTB‐CB subtests therefore are generalizable across samples. By satisfying the assumption of measurement invariance, inferences made using the NIHTB‐CB about between‐group differences are presumed valid.

P71: Predicting amyloid-ß deposition status in amnestic mild cognitive impairment using neuropsychological profiles.

Objective:Previous studies investigating neuropsychological profiles of cognitive impairment people have found a learning curve can be a useful indicator of AD diagnosis or progression. However, the data on the relationship between amyloid β (Aβ) deposition status and the learning curve in amnestic mild cognitive impairment (aMCI) are limited. In this study, we investigate the role of the learning curve in predicting Aβ deposition status in patients with aMCI.Methods:This is a cross-sectional study of 67 aMCI patients (N = 67; 33 aMCI with amyloid positive (Aβ-PET (+)), and 34 aMCI with amyloid negative (Aβ-PET (-))). All participants underwent Seoul Neuropsychological Screening Battery for a comprehensive neuropsychological test battery and brain MRI. To determine Aβ deposition status, each participant underwent amyloid PET scans using 18F-florbetaben. The learning curve was obtained using immediate recall of Seoul Verbal Learning Test-learning curve (SVLT- learning curve). The association of cognitive test scores and dichotomized Aβ deposition status was examined using logistic regression models in patients with aMCI. Receiver operating characteristic (ROC) curves were used to examine the predictive ability of cognitive test to detect Aβ deposition status in aMCI.Results:Logistic regression models showed that SVLT-learning curve and Rey Complex Figure Test- delayed recall (RCFT-delayed recall) scores were significantly associated with Aβ deposition status. In ROC analysis to assess the predictive power, SVLT-learning curve (area under the curve (AUC) = 0.734, P = 0.001) and RCFT-delayed recall (AUC = 0.739, P = 0.001) independently discriminated Aβ-PET (+) and Aβ-PET (-). The combination of these clinical markers (SVLT-learning curve and RCFT-delayed recall) improved the predictive accuracy of Aβ-PET (+) (AUC = 0.833, P < 0.001).Conclusions:Our findings of association of Aβ deposition status with SVLT-learning curve and RCFT- delayed recall suggest that these cognitive tests could be a useful screening tool for Aβ deposition status among aMCI patients in resource-limited clinics.

Mclena‐1: A Phase II Clinical Trial for the Assessment of Safety, Tolerability, and Efficacy of Lenalidomide in Patients with Mild Cognitive Impairment Due to Alzheimer’s Disease; Interim progress

AbstractBackgroundAccumulating evidence indicates that inflammation mediated by tumor necrosis factor alpha (TNF alpha), interleukins (e.g. IL‐1 beta, IL‐2, and IL‐6), and chemokines (e.g. IL‐8), is prominent in Alzheimer’s disease (AD) patients. These data suggest that systemic inflammation plays a crucial role in the cause and effects of AD neuropathology. Thus, we propose that modulating systemic inflammation via a pleiotropic immunomodulator is a putative therapeutic intervention if administered at a proper time window during the course of the disease.MethodThis is a Phase II, proof‐of mechanism, placebo‐controlled clinical study on amnestic mild cognitive impairment (aMCI) male and female subjects administered 10 mg/day the immunomodulator, anti‐cancer agent lenalidomide for 12 months on a 1:1 ratio (15 placebo + 15 drug‐treated subjects total) followed by a 6 months washout period. Amyloid loads is measured by FBP PET. The primary endpoints are cognition measured via a large battery cognitive tests every 3 months, and comparison of brain amyloid loads (Florbetapir PET imaging) and neurodegeneration (volumetric MRI) pre‐ and post‐drug treatment. The secondary endpoints are safety, which is evaluated through reported adverse events (AEs), clinical laboratory tests (hematology, serum chemistry, and urinalysis), vital signs, physical and neurological examinations, and electrocardiograms. The tertiary and exploratory objectives will assess blood inflammatory markers after lenalidomide vs. placebo administration.ResultsTo date, 15 participants have signed consent, 7 screen failed, 2 withdrew consent and 6 have completed treatment after 12 months. Adverse events occurred as expected in cancer cohorts. No severe AEs have occurred so far. Importantly, assuming a 1:1 randomization in the blinded phase, several participants have received lenalidomide continuously for 12 months without interruption. Though blinded, the completers appeared to be stable.ConclusionIn the current project we aim to investigate lenalidomide as a possible AD therapy. Our study should allow determining whether or not lenalidomide is safe in subjects suffering neurological disorders, and whether it can alter the clinical course of AD. To date, AEs are as expected and the safety and tolerability are manageable. A second trial coined MCLENA 2 will start soon. It will focus on biomarker endpoints (rather than cognition) following treatment for 6 months

Examining Automatic Generated Language Features of Chinese Spontaneous Speech for Early Detection of Cognitive Decline

AbstractBackgroundConnected speech is sensitive on detecting cognitive decline in early Alzheimer disease. In this study, we apply artificial intelligence to develop an automatic assessment for analyzing speech data.Method79 samples of picture description speech data were collected. All participants were native Chinese speakers including 31 normal controls (59‐88 yrs) and 49 patients (amnestic mild cognitive impairment and early Alzheimer’s disease) (58‐88 yrs). We extracted 16 linguistic features from the manually transcribed text. These linguistic features were generated by well‐trained linguists or automatically processed by the machine. We also trained decision tree models with those two sets of linguistic features. Seventy percent of the data was used for training and the remainder was used for testing. We also applied a cross‐validation method to avoid overfitting.ResultTotal words, unique words, and content words generated from linguists or machines were highly correlated (about r = 0.99, p < .001). However, the correlations between verb ratio, mean length of sentences, and filler ratio were relatively low (about r = 0.75, p < .001). With manually corrected features, the model could achieve 91.67% accuracy. Among them, the pronoun ratio and MLU (mean length of utterance) appeared to be equally crucial for model prediction. By contrast, with automatically generated features, the model achieved 83.33% accuracy only. MLU and MLS (mean length of sentences) were essential features for prediction.ConclusionAutomatic assessment could also achieve a good accuracy rate compared to humans (83.33% v.s. 91.67%). Some linguistic features such as fillers or sentences were still highly dependent on the expert’s judgment. Interestingly, MLU was critical in the prediction model of automatic or experts.