Mild Alzheimer's Disease Research Articles

Digital Cognitive Assessment Leveraging the Boston Process Approach Can Flag Emergent Cognitive Decline in Individuals with Subtle and Mild Functional Disability

AbstractBackgroundEarly detection of Mild Cognitive Impairment (MCI) and Alzheimer’s Disease and Related Dementias (ADRD) is key to optimal management. Digital tests allow for the reliable capture of meaningful, process‐based neuropsychological test parameters that traditional paper/pencil measures fail to detect, thus enabling earlier detection. We assessed how subtle functional decline relates to process features extracted from the digital Clock Drawing Test (dCDT) and the digital Trail Making Test‐Part B (dTrB).Methods629 community dwelling participants (58.5% female) were assessed with the Functional Assessment Questionnaire (FAQ), the MMSE, the digital clock drawing test (dCDT) and the digital Trail Making Test‐Part B (dTrB). Three FAQ groups were constructed: FAQ = 0‐2 (minimal functional disability, n = 490); FAQ = 3‐5 (subtle functional disability, n = 90); FAQ = 6‐8 (mild functional disability, n = 49).ResultsParticipants with minimal functional disability were younger (p = 0.027) and scored better on the MMSE (p = 0.001) than other groups. Groups were equated for education. dCDT command/copy component placement was more accurate among participants with minimal functional disability compared to other groups (command dCDT p = 0.001 versus mild functional disability; copy dCDT p = 0.006 versus both subtle and mild functional disability). On the dTrB, participants with minimal disability drew faster than those with subtle or mild disability (mean stroke velocity, p = 0.001). Analyses for percent pen lift time found no difference between participants with minimal versus subtle disability; however, both groups differed from participants with mild disability (p = 0.001). Optimal group classification using stepwise nominal regression with the minimal functional disability group as the reference was achieved using dCDT copy component placement and dTrB mean stroke velocity (X 2 = 28.37, p = 0.001), where dTrB mean velocity entered first (X 2 = 17.73, p = 0.001) followed by dCDT copy component placement (X 2 = 11.19, p = 0.004). Both variables contributed comparably to group classification (Wald statistic range 5.82‐8.88, p = 0.012, respectively).ConclusionsThe digital assessment described above, targeting executive, scanning, visuoconstructional and motor domains, captures highly nuanced, discrete behaviors with precision/ operationalism heretofore unattainable. Consequently, it is reasonable to posit that digital cognitive assessments leveraging the Boston Process Approach can both objectively detect emergent cognitive impairment and infer its likely impact on functional activities, critical for practical assessment in clinical care.

Effect of Diet on Cognitive Function and Gut Microbiota in Aged Rats.

AbstractBackgroundMany patients with mild cognitive impairment and Alzheimer’s disease have alterations in the gut microbiota. Dietary consumption directly modulates gut microbiota; therefore, the quality of a diet may impact cognitive function and susceptibility to memory impairments. We hypothesized that consumption of the Mediterranean diet (MeDi) versus the Western diet (WD) will improve cognitive function through beneficial changes to the gut microbiota.MethodTwelve‐month‐old male Fischer 344 rats (n = 14/group) were randomly assigned to a MeDi, WD, or Chow diet (positive control to MeDi) for three months. Animals then underwent neurobehavioral assessments (n = 10/group) including the Morris water maze and radial arm water maze to assess aspects of short‐ and long‐term memory. Data were analyzed via One‐ or Two‐Way Repeated Measures ANOVA where appropriate. Fecal samples were collected prior to the behavior. Microbial composition was determined by 16S rRNA sequencing.ResultThe MeDi and WD groups consumed more kcals (p<0.05) at various weeks and weighed more compared to the chow group (p<0.05). There was no difference in time to reach the platform between the MeDi and WD or Chow groups in the Morris water maze, however, animals consuming the chow diet were quicker to reach the platform compared to the WD (p = 0.046). There were no differences in total errors measured by the radial arm water maze (p = 0.50) between diets. Gut microbiota composition (β‐diversity) was distinct between diets (Weighted and Unweighted UniFrac, p<0.001).ConclusionThere were no differences in short‐ or long‐term memory in aged animals consuming a MeDi or WD for three months. Diet‐modulated the gut microbiota as exhibited by differences in β‐diversity between the MeDi, WD, and Chow. As animals consumed a chow diet throughout their lifespan, the MeDi or WD may need to be started earlier in life to exhibit differences. Funding: NIH Mentoring Research Excellence in Aging and Regenerative Medicine5P20GM103629‐10

Regional cortical hypoperfusion observed in elderly adults prior to development of mild cognitive impairment

AbstractBackgroundCardiovascular disease is associated with increased risk of developing mild cognitive impairment (MCI) and Alzheimer’s disease (AD), although the underlying mechanisms are not well understood. While it has been theorised that cerebral hypoperfusion caused by heart failure may directly lead to the formation of amyloid plaques and neurofibrillary tangles characteristic of AD, it has also been suggested that decreased perfusion occurs later in disease progression. We used arterial spin labelling (ASL) MRI to compare cerebral blood flow (CBF) between cognitively unimpaired elderly individuals who would remain cognitively stable and those who would later develop MCI to determine if hypoperfusion is detectable at a preclinical stage.Method647 cognitively normal elderly participants with ASL and structural T1‐weighted MRI were selected from the Vallecas Project cohort, a single‐centre longitudinal study currently in its 12th year of annual follow‐up. 586 participants remained cognitively stable (CS) while 61 participants developed MCI over the course of the study. Cortical CBF maps derived from ASL images at the visit before MCI diagnosis were analysed in a voxelwise comparison with CS individuals, with age, sex, and total intracranial volume as covariates.ResultCBF was significantly lower in the right insular cortex in future MCI converters than CS individuals (p<0.05, family‐wise error (FWE) corrected). Hypoperfusion was also significant in the anterior corpus callosum in future converters.ConclusionCerebral hypoperfusion, as measured by ASL, can already be observed in individuals before the onset of clinical symptoms.

Saccadic latency differences in preclinical Alzheimer’s disease

AbstractBackgroundPrevious studies indicate that individuals with mild cognitive impairment (MCI) or Alzheimer’s disease (AD) have higher latencies on anti‐saccade tasks than healthy controls. We investigated whether this difference in latency appears even earlier, in cognitively healthy (CH) individuals at high risk of cognitive decline to MCI or AD and whether subliminal priming or task switching further impacted this latency difference.MethodWe studied CH participants whose cerebrospinal fluid (CSF) amyloid / tau ratio was normal (≥2.7132, low risk) or pathological (<2.7132, high risk) (PMID: 24260210). The testing paradigm included three blocks: (1) all saccades, (2) all anti‐saccades, and (3) patterned task switching with two saccades followed by two anti‐saccades. Trials began with a green (saccade) or red (anti‐saccade) cue appearing at a central fixation point. Then, a masked subliminal cue appeared on the right or left, followed by a target congruent or incongruent with the subliminal prime location. Trials ended 1000 ms after the participant first looked directly at the target for saccade trials or away from the target for anti‐saccade trials.ResultPreliminary results (n = 19, 3 high risk) using a 3‐way mixed ANOVA (d.f. = 3484) indicate that high risk participants perform slower across all conditions (F = 26.36, p <<< 0.001). This effect is especially pronounced when task switching (F = 3.41, p < 0.05), with high risk participants performing 70.9 ms slower in the task switching block (Bonferroni‐corrected p = 6.62×10−6, 95% CI = [29.8, 112]). During the block with all anti‐saccades, however, the difference in performance is not significant (Bonferroni‐corrected p = 0.78), unlike the effects previously observed in individuals with MCI or AD. Additionally, subliminal cues do not show a significant overall effect on behavioral data (F = 2.32, p = 0.13).ConclusionPilot results indicate that latency differences when task switching between saccade and anti‐saccade tasks exist in CH people at high risk of cognitive decline. Because eye tracking tasks are much less invasive and expensive than spinal taps, they could provide a potential screening tool for those at risk of cognitive decline.

Two‐stage diffusion model deriving FDG‐PET from T1 Weighted Magnetic Resonance Images for diagnosis of Alzheimer’s disease

AbstractBackgroundAlzheimer’s Disease (AD) is a neurodegenerative disease which is characterized by cognitive and functional impairment, and defined by triad of Amyloid status, Tau pathology, and Neuroimaging marker of neurodegeneration or neuronal injury. An early diagnosis of AD can be challenging and it can be detected earlier in brain functional imaging than brain structural imaging.MethodWe develop a pipeline for synthesizing FDG‐PET/MRI from source MRI‐T1‐Weighted (MRI‐T1W) images based on denoising diffusion mechanism [1]. The pipeline includes a forward pass which encodes the source MRI‐T1WI images to gaussian noise space, and a backward pass which generates the corresponding FDG‐PET from the derived noises with repeated denoising steps. Furthermore, to validate the effectiveness of the synthesized FDG‐PET images, we also develop multiple types of classifiers and the experiments for both single input of MRI‐T1WI and joint input of MRI‐T1WI and synthesized FDG‐PET.ResultThe experiments are performed on 1036 of FDG‐PET/MRI pairs (286,474, 276 for Cognitive Normal, Mild Cognitive Impaiement and Alzheimer’s Disease each) are obtained from ADNI [2] datasets and display the promising results with low Mean Absolute Error (MAE) and high Structural Similarity Index Measure (SSIM) for the two stage diffusion denoising based FDG‐PET synthesis pipeline. The results for the additional classification experiments also show that in most cases the joint input enhances the classifiers' performance in accuracy and F1‐score. The results also indicate that the synthesized FDG‐PET images are not only visually similar to the ground truth images, but also improve the performance of machine learning based AD diagnosis.ConclusionThis work provides support for the notion that machine learning‐derived image analysis may be a useful approach to improving the diagnosis of AD.Reference:[1] Ho, J., Jain, A., & Abbeel, P. (2020). Denoising diffusion probabilistic models. Advances in Neural Information Processing Systems, 33, 6840‐6851.[2] Petersen, R., Aisen, P. S., Beckett, L. A., Donohue, M. C., Gamst, A. C., Harvey, D. J., … & Toga, A. W. (2010). Alzheimer’s disease neuroimaging initiative (ADNI). Neurology, 74(3), 201‐209.

Social cognition and emotion inference abilities in healthy aging and Mild Cognitive Impairment

AbstractBackgroundSocial cognition (SC) is a neurocognitive domain that can be affected by the pathophysiological changes of aging, and deteriorate in individuals diagnosed with Mild Cognitive Impairment (MCI) and Alzheimer’s Disease. This social‐cognitive function involves the attribution of one’s mental states, including intentions (IA) and emotions (EA). As mentalization abilities may impact on daily functioning, research is focusing on SC processes in individuals at risk for age‐related neurocognitive decline. The present study aimed to 1) investigate SC abilities in MCI, compared to healthy individuals; 2) explore whether specific SC sub‐domains could be associated with MCI diagnosis.MethodN = 468 outpatients referred to Bari University Hospital for neuropsychological assessment were classified into two groups: i) a cognitively spared (n = 166; Mage = 61); ii) MCI (n = 302; Mage = 67), characterized by objective deficits one or more neurocognitive domains (other than SC) not interfering with daily functioning. Sample classification resulted from multidomain, cognitive‐functional assessment procedures consistent with Petersen’s criteria (Petersen et al., 2014). A total of 185 subjects also completed the Story‐Based Empathy Task (SET), yielding four social cognition scores (i.e., global score [GS]; IA; EA; causal inference [CI]). After testing the distribution of the SET variable through the Shapiro‐Wilk test, the Mann‐Whitney U test was used to analyze mean differences between the two groups. Additionally, a binary logistic regression was conducted to assess whether impaired SC could be associated with MCI diagnosis.ResultPatients with MCI showed significantly lower SC performances in all SET sub‐tests, compared to controls (SET‐GS: Z = ‐5.25; p<.001; SET‐IA: Z = ‐3.98; p<.001; SET‐EA: Z = ‐4.02; p<.001; SET‐CI: Z = ‐3.22; p<.001). Binary logistic regression with backward elimination revealed that among all SC sub‐domains, the inability to infer emotional states resulted being associated with MCI diagnosis (B = ‐.678; exp(B) = .507; p<.001). Regression analysis was overall significant (χ2 = 16.68; p<.001), and correctly classified 66% of cases.ConclusionOur findings highlighted significantly poorer SC performances in MCI, notably in the emotional inference sub‐domain. This preliminary evidence may contribute to the clinical understanding of social‐cognitive functioning in elderly individuals with mild/initial cognitive deficits, emphasizing the importance of accounting for SC in neuropsychological assessment to improve early diagnosis and strategies for dementia prevention.

Identifying change on the CERAD Word List with standardized regression‐based scores

AbstractBackgroundList learning and memory tests are frequently used to evaluate older adults for Mild Cognitive Impairment and Alzheimer’s disease. One such test, the Word List subtest of the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD), has been widely‐used in clinical trials track such disorders. However, data is lacking on the amount of change that is needed to accurately identify decline.MethodParticipants included 897 older adults (age in years: M = 81.1, SD = 8.1, range 55‐100; 67% women; education in years: M = 14.8, SD = 2.8, range = 7‐24) who were cognitively intact at two annual visits in a longitudinal observational study from the Uniform Data Set of the National Alzheimer’s Coordinating Center. Each participant completed the Word List subtest at two visits, which were approximately 1 year apart (interval in years: M = 1.3, SD = 1.0). Multiple linear regression predicted Time 2 scores from Time 1 scores and simple demographic variables (age, sex, education). The predicted Time 2 scores were compared to observed Time 2 scores to preliminarily validate this change data.ResultFor three primary scores from the Word List subtest (Acquisition Total Correct, Delay Recall Total Correct, Recognition Total Correct), the Time 2 scores were significantly predicted from the other variables, with R2s ranging from 0.16 – 0.41 (p‐values<0.001). When these predicted Time 2 scores were compared to observed Time 2 scores, there were no significant differences (p‐values≧0.19), indicating preliminary support for these prediction scores.ConclusionThe current prediction equations appear to allow clinicians and researchers to accurately track change on the Word List subtest of the CERAD by comparing their patients/participants to the current sample of robustly intact older adults. Consistent with past work in this area, Time 1 cognitive scores were the best predictors of Time 2 cognitive scores, although demographic variables added to that prediction. Future work should consider if additional variables can improve the prediction equations. Future work should also validate these equations in independent samples to examine their clinical utility.

Federated BrainAge estimation from MRI: a proof of concept

AbstractBackgroundThe gap between chronological and biological brain‐age, represented by MRI features, associates with dementia risk (Wang et. al., He et. al.). Age‐scores are predicted, however, using deep learning models, which require large amounts of MRI data. This poses a challenge, as patient brain MRI data is highly privacy‐sensitive and legal barriers often impede the sharing or transferring of data. Federated learning provides a potential solution by enabling training a global model on distributed data, allowing biobanks to keep data local while creating a shared model. In this study, we assess whether a federated set‐up is feasible for brain‐age estimation.MethodWe set up a federated learning framework across three biobanks (Fig. 2) to train a BrainAge model (Wang et. al). Data of healthy individuals from the ADNI dataset was randomly split across the three biobanks (N = 221, 219, 217). MRI images were pre‐processed into gray matter density maps (Good et. al.). The model was iteratively trained using federated averaging (McMahan et. al.) on data at two biobanks (70/30 training/validation split), and tested at the remaining biobank. We trained the model for ten rounds, and optimized for the number of epochs, learning rate, and learning decay hyperparameters. These results were compared to a centrally trained model, where the training samples were pooled together. Additionally, we applied the trained model to individuals with Mild Cognitive Impairment and Alzheimer’s Disease and performed a survival analysis. We assessed performance using Mean Absolute Error (MAE).ResultFederated learning (MAE = 4.02) achieves similar test performance as central learning (MAE = 3.94) (Table 1). The model yielded an MAE of 4.89 for MCI and 5.45 for AD patients; this increase may be explained by their neurodegeneration. We also see a statistically different survival curve for developing AD in individuals with a brain‐age‐gap (Fig. 1), displaying an ‘older’ profile for their chronological age. This might indicate higher risk of developing AD, in line with previous results (Wang et. al.).ConclusionResults show federated learning has the potential to address the challenge of data accessibility for machine learning in complex and data hungry research, including dementia.

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.

Higher cortical thickness/volume in Alzheimer’s‐related regions: Protective factor or risk factor?

AbstractBackgroundNeuroimaging signatures based on cortical thickness or volume in regions vulnerable to Alzheimer’s disease (AD) pathology are tools developed to identify brain changes specific to mild AD. Lower thickness/volume signatures (indicating comparatively thinner cortex) are commonly associated with risk of future decline. In contrast, some evidence suggests a biphasic pattern of changes wherein higher, rather than lower, cortical thickness is associated with very early AD pathology. Understanding the difference between high cortical thickness indicating a risk versus a protective factor carries important implications for early identification of AD. We examined whether integrating information from a novel AD brain signature based on gray matter mean diffusivity (MD)—previously shown by our group to be sensitive to early AD‐related changes and predictive of thickness/volume‐based signatures over a decade later—can aid in the interpretation of when high cortical thickness/volume is a risk versus a protective factor for future AD‐related changes.MethodParticipants were 572 men in the Vietnam Era Twin Study of Aging (VETSA) who were cognitively unimpaired (CU) at baseline (mean age = 56 years; range = 51‐60). A validated thickness/volume signature and novel gray matter MD signature, each a weighted average of MRI‐based morphometry in eight AD‐related brain regions, were used in longitudinal mixed models predicting brain and cognitive outcomes. Subgroup analyses included all CU participants with high baseline thickness/volume signatures, regardless of subsequent cognitive status (n = 147).ResultAmong individuals with high thickness/volume signature scores at baseline, those that additionally had high values on MD signature scores showed significantly lower thickness/volume signatures and lower episodic memory performance 12 years later compared to the high thickness/volume‐low MD group. In contrast, group differences in global mean cortical thickness remained stable across waves. Groups did not differ in level of young adult cognitive reserve.ConclusionGray matter MD differences may capture heterogeneous subgroups among individuals with high cortical thickness/volume. Findings are in line with a biphasic model in which increased cortical thickness in AD‐related regions may precede future decline. An AD signature based on cortical MD can be used alongside cortical thickness to identify subgroups with differential risk for poorer brain and cognitive outcomes.

Higher cortical thickness/volume in Alzheimer’s‐related regions: Protective factor or risk factor?

AbstractBackgroundNeuroimaging signatures based on cortical thickness or volume in regions vulnerable to Alzheimer’s disease (AD) pathology are tools developed to identify brain changes specific to mild AD. Lower thickness/volume signatures (indicating comparatively thinner cortex) are commonly associated with risk of future decline. In contrast, some evidence suggests a biphasic pattern of changes wherein higher, rather than lower, cortical thickness is associated with very early AD pathology. Understanding the difference between high cortical thickness indicating a risk versus a protective factor carries important implications for early identification of AD. We examined whether integrating information from a novel AD brain signature based on gray matter mean diffusivity (MD)—previously shown by our group to be sensitive to early AD‐related changes and predictive of thickness/volume‐based signatures over a decade later—can aid in the interpretation of when high cortical thickness/volume is a risk versus a protective factor for future AD‐related changes.MethodParticipants were 572 men in the Vietnam Era Twin Study of Aging (VETSA) who were cognitively unimpaired (CU) at baseline (mean age = 56 years; range = 51‐60). A validated thickness/volume signature and novel gray matter MD signature, each a weighted average of MRI‐based morphometry in eight AD‐related brain regions, were used in longitudinal mixed models predicting brain and cognitive outcomes. Subgroup analyses included all CU participants with high baseline thickness/volume signatures, regardless of subsequent cognitive status (n = 147).ResultAmong individuals with high thickness/volume signature scores at baseline, those that additionally had high values on MD signature scores showed significantly lower thickness/volume signatures and lower episodic memory performance 12 years later compared to the high thickness/volume‐low MD group. In contrast, group differences in global mean cortical thickness remained stable across waves. Groups did not differ in level of young adult cognitive reserve.ConclusionGray matter MD differences may capture heterogeneous subgroups among individuals with high cortical thickness/volume. Findings are in line with a biphasic model in which increased cortical thickness in AD‐related regions may precede future decline. An AD signature based on cortical MD can be used alongside cortical thickness to identify subgroups with differential risk for poorer brain and cognitive outcomes.

Clinical Manifestations.

In addition to measures of cognition, global Alzheimer's disease (AD) clinical trials commonly include measures to assess functional status (activities of daily living; ADLs) and quality of life (QoL) reported by participants and study partners. Most common assessments were validated with North American, White, English-speaking populations and research suggests that these are not free from cultural and linguistic influence. ADLs and QoL may exhibit regional differences due to socioeconomic and cultural factors. It is important to understand how geo-cultural factors influence these measures, which are often used as trial efficacy endpoints. In this study, we examined the impact of geo-cultural region on ADCS-MCI-ADL and QoL-AD when considering baseline cognitive status. This study included electronic ADCS-MCI-ADL, QoL-AD, and ADAS-Cog data from two multi-national AD clinical trials of participants with prodromal to mild AD. Data were collected from three geo-cultural regions: Asia (n = 688); Western Europe (WE; n = 589); and North America (NA; n = 1925). Participants were stratified into five cohorts based on ADAS-Cog13 scores. QoL-AD Study Partner and AD Participant scores varied significantly across geo-cultural regions (Kruskal-Wallis test; p<0.0001). Both study partner-reported and participant reported QoL-AD scores in Asia were lower than scores in NA and WE for all ADAS-Cog13 cohorts (Dunn's test; p<0.0001). QoL-AD AD Participant scores in NA and WE did not differ. For participants with lower cognitive performance (ADAS-Cog > 40th percentile), study partner-reported QoL-AD scores in NA were significantly higher than those in WE (Dunn's test; p<0.05), but there was not significant difference on the participant-reported QoL-AD scores between these regions. ADCS-MCI-ADL scores were not significantly different across groups. Our study found that QoL-AD, but not ADCS-MCI-ADL scores differed significantly across geo-cultural regions when considering baseline cognitive performance. Both participant and study-partner reported QoL was lower in Asia than in WE and NA. Cross-regional differences in QoL may also be moderated by baseline cognitive performance. Different social norms and aging expectation, healthcare resources, and trial participation may have contributed to the regional variance observed. Future studies should examine if specific constructs are more contextually dependent on the local culture.

GRADUATE I AND II: Revisiting the key findings from two Phase III studies evaluating the efficacy and safety of subcutaneous gantenerumab in early Alzheimer’s disease (AD)

AbstractBackgroundGantenerumab is a fully human monoclonal antibody administered subcutaneously. It binds to aggregated forms of amyloid‐beta protein. GRADUATE I (NCT03444870) and GRADUATE II (NCT03443973) were two 27‐month, global, Phase III, randomized, placebo‐controlled trials designed to investigate the efficacy and safety of gantenerumab in participants with early AD (mild cognitive impairment due to AD or mild AD dementia).MethodEligible participants with early AD were randomized 1:1 to receive gantenerumab or placebo. A universal titration scheme was used for all participants receiving gantenerumab, irrespective of APOEε4 genotype, in order to reach target dose of 510 mg every 2 weeks. The primary endpoint was change from baseline to Week 116 in Clinical Dementia Rating scale – Sum of Boxes (CDR‐SB). Secondary efficacy endpoints, imaging and fluid biomarkers were also assessed.ResultGRADUATE I and II enrolled 985 and 980 participants, respectively. The studies did not meet their primary endpoints. Change from baseline in CDR‐SB at Week 116 for the gantenerumab and placebo groups respectively was 3.35 and 3.65 in GRADUATE I (difference –0.31; 95% confidence interval [CI] –0.66 to 0.05; p = 0.095; 8% relative reduction [RR]) and 2.82 and 3.01 in GRADUATE II (difference –0.19; 95% CI –0.55 to 0.17; p = 0.2998; 6% RR). Secondary measures including ADAS‐Cog13, ADCS‐ADL, FAQ had non‐significant point estimates in favor of gantenerumab, as did the majority of exploratory measures, including NPI‐Q (Table 1). In the gantenerumab arm, change in amyloid PET from baseline to Week 116 was –57.4 (SE 2.84) centiloids for GRADUATE I and –48.0 (SE 2.85) centiloids for GRADUATE II. ARIA‐E occurred with gantenerumab and were manageable and mostly asymptomatic. Plasma exposure using Q2W dosing was comparable to previous data and similar between the GRADUATE studies (At steady state: mean Cmax and Cmin: GRADUATE I 88.1 µg/mL and 54.1 µg/mL; GRADUATE II 88.5 µg/mL and 56.8 µg/mL).ConclusionThe GRADUATE studies did not meet their primary endpoints, although non‐statistically significant effects favoring gantenerumab were observed across the majority of clinical outcome measures. Clinical benefit may require amyloid plaque removal to a threshold level; however, the parameters remain to be defined.

PP125 Why Understanding The Burden Of The Population Is Fundamental

IntroductionDespite intense efforts in development of new treatments over the last two decades, symptomatic treatments remain the only option for the vast majority patients diagnosed with dementia due to Alzheimer’s disease (AD). There remains a significant unmet need for disease modifying therapies (DMTs) to slow or stop AD progression. DMTs in development are targeting early stages of AD (pre-clinical, mild cognitive impairment and mild dementia stages), thereby creating an entirely new treatment paradigm for patients, clinicians, and payers. A key challenge will be in identifying the appropriate patient for treatment in a very heterogenous population. We have performed a literature review to better understand and define the AD population, with a view to enabling more targeted treatment in future.MethodsEmbase, MEDLINE and the Cochrane Library were searched to identify publications between 2010-2021 on observational studies reporting evidence on prevalence and subgroup identification, including clinical feasibility of identification. The search was restricted to English language.ResultsWe identified 45 studies, mostly from Europe, USA and Asia. Populations were primarily grouped based on generic demographic factors (e.g., age, sex, gender), AD staging, comorbidities or biomarkers. Prevalence data was available for six subpopulations: pre-dementia stage, mild dementia, age, Apolipoprotein E (APOE) genotype, comorbid obesity and hypertension. Across these, data on prevalence were heterogenous depending on study design and country of origin, and ranging between 66 million to 102 million for people with mild AD dementia, or as another example, ranging between 46 million to 92 million for APOE genotype carriers worldwide.ConclusionsThe heterogeneity and the uncertainty in prevalence of the AD population represent big challenges to clinicians and payers. Future discussions on target patient identification for new treatments should be aligned and integrated with current clinical practice e.g. leveraging validated biomarkers as diagnostic tools. Additional research on an integrated approach to identify patients who would benefit the most from DMTs will be needed.

Memory dysfunction in mild cognitive impairment (MCI) and early Alzheimer disease (AD) dementia is closely associated with synapse loss, and shows significant correlation with pathological tau in synapses and inflammatory glial cell responses in postmortem human brain

AbstractBackgroundSynapse density loss is among the strongest histopathological correlates of dementia in AD. Prodromal stages of AD, comprising amnestic MCI and mild AD dementia, represent the most promising timepoints for interventions aimed at attaining efficacious neurobiological and clinical effects. Yet, the understanding of other contributing neuropathologic changes in these prodromal disease stages and their impact on early cognitive dysfunction remains limited.MethodsWe studied the visual cortex of 28 demented and non‐demented human brains who had died at Braak III‐IV stages of NFT pathology, and who showed a comparable β‐amyloid plaque burden and absence of NFT deposits in the studied brain region, and a group of age‐matched healthy controls. We used immunohistochemical analyses with artificial intelligence quantifications, expansion microscopy, synaptosome extractions, and Western blotting, to assess associations between antemortem MMSE scores and synapse densities, glial cell phenotypes, and pathological tau.ResultsWe found a significant loss of presynapses (Synapsin 1+), excitatory postsynapses (PSD95+), and colocalized synapses (Synapsin1‐PSD95+) in the brains of demented compared to non‐demented and controls. Moreover, we observed an association between excitatory synapse loss and memory dysfunction (MMSE score) as well as rate of disease progression (MMSE loss/time). MMSE scores were further associated with increase in tau oligomers (TOC1+) and phospho‐tau (AT270+) in synaptosomes, but not with 4G8+ β‐amyloid burden. Additionally, disease severity and rate of progression were significantly correlated with inflammatory glial changes.ConclusionsOur data suggest that excitatory synapse loss could serve as an early and robust neuropathologic correlate of disease severity and rate of progression from MCI stages of the disease, and be a closer and better determinant of cognitive decline than β‐amyloid and tau deposits. Moreover, early increases in soluble tau in synapses together with local inflammatory glial cell responses could drive development of incipient changes in memory function and serve as potential early biomarkers. Our results point to the importance of early detection and interventions aimed at synapse preservation from prodromal stages of AD, and suggest soluble tau and inflammatory glial cell changes as key targets in the early AD phases.

In‐vivo Braak Stage Distribution of Screened and Randomized Participants from Auτonomy, a Phase 2 Anti‐p‐tau Monoclonal Antibody Trial in Early Symptomatic Alzheimer’s Disease

AbstractBackgroundTau PET is the gold standard for in‐vivo quantification of tau neurofibrillary tangles (NFT) which, along with amyloid plaques and neurodegeneration, constitute the pathological hallmarks of Alzheimer’s Disease (AD). The ongoing Autonomy trial (NCT04619420) enrolls participants presenting with mild cognitive impairment (MCI) or mild AD dementia who are tau PET positive. The Janssen plasma p217+tau assay is being used as a pre‐screen for eligibility to proceed to tau PET to reduce participant burden and improve screening efficiency. Using preliminary screening data available to date, we report on the in‐vivo PET‐based Braak stage distribution and compare the outcomes to published, histology‐based Braak staging.MethodNFT levels were quantified using 18F‐MK‐6240 SUVR in Braak Regions Of Interest (ROI)[1] using cerebellar gray as the reference region. In‐vivo Braak staging (Braakiv) was implemented following the approach by Biel et al.[2], with 18F‐flortaucipir to 18F‐MK‐6240 SUVR threshold conversion from Gogola et al.[3]. Participants with atypical[2] stages were reassigned to the Braak stage corresponding to the highest Braak ROI with average SUVR &gt; 1.4. The screening results reported herein are from the first 355 participants with available biomarker screening data.ResultOf 355 screened participants, 90% were assigned to typical Braakiv stages. Of the 10% atypical stages, 94% were lacking elevated uptake in Braak 2 ROI. When using the coerced stage assignment, the average Braakiv stage was 3.7 across all screened participants and 3.6 in randomized participants (Figure 1). For the 221 randomized participants, 59% were Braakiv stage 4 or less, and 40% were Braakiv stage 3 or less.ConclusionIn early Alzheimer’s disease participants who were screened with tau PET in the ongoing Autonomy trial, the average Braakiv stage was consistent with the average histology‐based Braak stage in MCI patients of 3.57 [4]. These results further support the use of tau PET‐based in‐vivo staging[5] as a proxy for histology‐based Braak staging. [1] Schöll et al. Neuron 2016. [2] Biel, D., et al. Alz Res Therapy 2021. [3] Gogola A. et al. J Nucl Med. 2022. [4] Markesbery WR. J Alzheimers Dis. 2010. [5] Therriault, J. et al. Nat Aging 2022

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&lt;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&lt;0.05), right and left HT (p&lt;0.01), right alEC (p&lt;0.05), and right (p&lt;0.01) and left (p&lt;0.05) pmEC volumes. The mild AD dementia group had lower all subregional hippocampus and EC volumes compared to the CN group (p&lt;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.

A logarithm derived from Mokken scaling analysis of the Addenbrooke’s Cognitive Examination–Revised discriminates with high accuracy Alzheimer’s disease from behavioral variant frontotemporal dementia

AbstractBackgroundThe ACE‐R is an accurate and brief cognitive battery for the detection of mild dementia, especially for the discrimination between Alzheimer’s disease (AD) and behavioral variant frontotemporal dementia (bvFTD). The aim of this study was to develop a logarithm based on discriminative items of the ACE‐R for AD combined with relevant demographic characteristics that may help to differentiate AD from bvFTD.MethodThe ACE‐R was administered to 102 patients with mild dementia due to probable AD and 37 patients with mild bvFTD from two Brazilian research centers. All individuals were submitted to the Mattis Dementia Rating Scale (DRS) and the ACE‐R. The performance of the patients was compared and analyzed. Mokken scaling analysis was applied to identify the latent trait on the AD Group, and later, multivariate logistic regression and ROC curve analysis were carried out to assess the ACE‐R’s ability to discriminate AD and bvFTD.ResultMean ± SD total scores in the ACE‐R were 70.2 ± 10.8 in AD and 72.2 in bvFTD. AD Mokken ACE‐R (MokACE‐R‐AD) comprises 12 items measuring the same latent concept. In our sample, logistic regression with cross‐validation pointed that MokACE‐R‐AD, Age, Male sex, and items Orientation to time and location and the item of Memory (name and address recall) share importance as independent variables (p&lt;0.05) to differentiate AD from bvFTD. The proposed logarithm reached an area under the ROC curve of 0.922, with 88% sensitivity, 88% specificity, 71% PPV and 96% NPV.ConclusionThe new logarithm using the ACE‐R items achieved high diagnostic accuracy in identifying mild AD versus bvFTD. Furthermore, the final ROC curves showed the superiority of the model proposed in relation to the analysis of the subscales individually or the VLOM ratio, as the literature previously reported. Further analysis in larger samples, with biomarkers or pathological confirmation, are necessary to confirm these findings.

In‐vivo Braak Stage Distribution of Screened and Randomized Participants from Auτonomy, a Phase 2 Anti‐p‐tau Monoclonal Antibody Trial in Early Symptomatic Alzheimer’s Disease

AbstractBackgroundTau PET is the gold standard for in‐vivo quantification of tau neurofibrillary tangles (NFT) which, along with amyloid plaques and neurodegeneration, constitute the pathological hallmarks of Alzheimer’s Disease (AD). The ongoing Auτonomy trial (NCT04619420) enrolls participants presenting with mild cognitive impairment (MCI) or mild AD dementia who are tau PET positive. The Janssen plasma p217+tau assay is being used as a pre‐screen for eligibility to proceed to tau PET to reduce participant burden and improve screening efficiency. Using preliminary screening data available to date, we report on the in‐vivo PET‐based Braak stage distribution and compare the outcomes to published, histology‐based Braak staging.MethodNFT levels were quantified using 18F‐MK‐6240 SUVR in Braak Regions Of Interest (ROI)[1] using cerebellar gray as the reference region. In‐vivo Braak staging (Braakiv) was implemented following the approach by Biel et al.[2], with 18F‐flortaucipir to 18F‐MK‐6240 SUVR threshold conversion from Gogola et al.[3]. Participants with atypical[2] stages were reassigned to the Braak stage corresponding to the highest Braak ROI with average SUVR &gt; 1.4. The screening results reported herein are from the first 355 participants with available biomarker screening data.ResultOf 355 screened participants, 90% were assigned to typical Braakiv stages. Of the 10% atypical stages, 94% were lacking elevated uptake in Braak 2 ROI. When using the coerced stage assignment, the average Braakiv stage was 3.7 across all screened participants and 3.6 in randomized participants (Figure 1). For the 221 randomized participants, 59% were Braakiv stage 4 or less, and 40% were Braakiv stage 3 or less.ConclusionIn early Alzheimer’s disease participants who were screened with tau PET in the ongoing Auτonomy trial, the average Braakiv stage was consistent with the average histology‐based Braak stage in MCI patients of 3.57 [4]. These results further support the use of tau PET‐based in‐vivo staging[5] as a proxy for histology‐based Braak staging.[1] Schöll et al. Neuron 2016.[2] Biel, D., et al. Alz Res Therapy 2021.[3] Gogola A. et al. J Nucl Med. 2022. [4] Markesbery WR. J Alzheimers Dis. 2010.[5] Therriault, J. et al. Nat Aging 2022

The association between anxiety and Alzheimer’s disease plasma biomarkers across stages

AbstractBackgroundAnxiety is associated with faster progression of Alzheimer’s disease (AD) and related imaging biomarkers. However, the association of anxiety with plasma biomarkers of AD is unclear. We investigated the relationship between various plasma AD biomarkers and anxiety at different AD stages.MethodThe study included 192 older adults evaluated at the NYU Alzheimer’s Disease Research Center with a consensus diagnosis of cognitively normal (CN, n = 99), mild cognitive impairment (MCI, n = 52), and mild AD dementia (AD, n = 41). Anxiety and depression were measured by study partner report via the Neuropsychiatric Inventory Questionnaire (NPI‐Q). Plasma levels of Aβ40, Aβ42, neurofilament light (NfL) and total tau were measured using ultra‐sensitive, single‐molecule array (SIMOA) technology. Secondarily‐calculated measures included Aβ42/Aβ40 and tau/Aβ42 ratios.ResultAnxiety had a prevalence of 14%, 48%, and 24% at CN, MCI, and AD, respectively. Comparing plasma biomarkers from participants with and without anxiety within each stage, anxiety associated with a significantly higher plasma tau/Aβ42 ratio in AD (p = 0.0127). In contrast, while depression had a higher prevalence of 37% at the AD stage, it was not associated with a significant difference in tau/Aβ42 ratio (p = 0.6459). Comparing stages, plasma tau/Aβ42 was significantly elevated in AD versus CN only among participants with anxiety (p = 0.034). In contrast, plasma NfL was significantly elevated in AD versus CN among participants with (p = 0.0475) and without (p &lt; 0.0001) anxiety.ConclusionThe presence of anxiety uniquely modulates the levels of specific plasma biomarkers depending on stage, as well as the ability of specific biomarkers to distinguish AD stages. These results highlight a complex relationship between neuropsychiatric symptoms and plasma biomarkers that warrants further study.