bluuebunny/crossref_metadata_2025 huggingface dataset:
Data‐driven analysis of 10,361 amyloid‐PET scans from the IDEAS study reveals two primary axes of variation
Authors: Giorgio Joseph , Mundada Nidhi S , Blazhenets Ganna , Mejía‐Perez Jhony Alejandro , Schonhaut Daniel R. , Carrillo Maria C. , Hanna Lucy , Gatsonis Constantine , March Andrew , Apgar Charles , Siegel Barry A. , Hillner Bruce E , Whitmer Rachel A. , Jagust William J. , Rabinovici Gil D. , Joie Renaud La
Published: January 2025

Background

The variability in the regional distribution of Aβ‐PET signal and its relation to clinical features is debated. We used data‐driven approaches to uncover heterogeneity in cortical Aβ‐PET signal from a large representative sample collected through the IDEAS study.

Methods

We analysed cross‐sectional Aβ‐PET collected from 10,361 patients with MCI or mild dementia scanned in 295 PET facilities using one of the 3 FDA‐approved tracers. Central image processing resulted in template‐space SUVR images (reference: whole cerebellum) and centiloid (CL) values. Spatial independent component analysis was used to decompose SUVR volumes into 40 independent components. After excluding noise components, participants’ scores were extracted for each of the remaining 11 grey matter (GM) components describing cortical and subcortical binding. K‐means clustering was used on these GM component scores to assign each participant to different Aβ‐PET clusters based on GM binding (Figure 1).

Results

Three informative clusters of PET binding were estimated. Cluster 1: Aβ‐(n=4729, CL mean=2±23) with low GM binding, and two Aβ+ clusters; Cluster 2(n=2484, CL mean=76±34) and Cluster 3(n=3148, CL mean=86±32). Subtracting average SUVR of Clusters 2 and 3 showed they differed along a posterior‐anterior gradient with Cluster 2 showing an occipital predominant pattern. Principal component analysis conducted on the GM scores confirmed two dominant axes of variation separated the clusters, a Aβ‐ to Aβ+ axis and, an anterior‐posterior axis (Figure 2). Statistically significant but weak differences were observed between the two Aβ+ Clusters (2 vs. 3); Visual Read (positive: 95% vs. 92%); Clinical Stage (dementia: 47% vs. 41%); Age (76.9±6.4 vs. 75.9±6.2), however, most clinical variables showed no differences (Figure 3a). 48 ADNI participants with Aβ‐PET and post‐mortem neuropathology data (11 Female, Age mean=79.7±7.4, PET‐Death mean=2.3±1.7years; Aβ‐CL mean=71.2±55.5; APOE4(0/1/2)=22/21/5; Diagnosis(CN/MCI/AD)=6/8/32) were applied to the model fit on IDEAS data. Qualitatively, no differences in neuropathology were observed between the two Aβ+ Clusters (Figure 3b).

Conclusion

Data driven classification of Aβ‐PET reveals two primary axes reflecting Aβ load and anterior‐posterior binding, with the later not clearly related to clinical or pathological variation. Future work will apply new data to this model and investigate if this spatial variation in Aβ‐PET is related to longitudinal changes in pathology.
Assessing Alzheimer’s Disease and Related Dementia risk in American Samoa using the Talanoa research framework
Authors: Tofaeono Vaatausili
Published: January 2025

Background

The American Samoa population has high prevalence for Alzheimer’s Disease and Related Dementia (ADRD) risk factors (e.g. tobacco use, obesity, hypertension, and diabetes), however ADRD risk has not been defined or assessed. The Puipui Malu Manutu (PMM) Study (RF1AG075904) is accomplishing this by assessing knowledge, health literacy, readiness, and resiliency and vulnerability factors using culturally adapted instruments in a sample of 1098 adults aged 50 and above. Additionally, Indigenous populations have unique worldview perspectives and epistemologies that have not been widely accepted in mainstream academia. Therefore, we decolonized Westernized research approaches by incorporating the Talanoa framework into the discussion and decision making of the ADRD risk profile each participant. The Talanoa framework is rooted in Samoan cultural norms to eliminate power, building trusting relationships, and is conducted face‐to‐face in individual or group settings. Talanoa is culturally grounded in four unique perspectives: alofa (love between the participant and researcher), fa’aaloalo (respect), tautau (service to the community), and malamalama (knowledge gained for the community).

Method

We established a Consensus Group comprised of the PMM Multiple Principal Investigators, a Samoan Nurse Practitioner, a Samoan clinical Psychologies, and a Samoan Medical Doctor to define the ADRD risk The Talanoa framework guided the Consensus Group, with the PMM study staff and ADRD risk definition, to openly discuss and decide ADRD risk in participants in a culturally safe manner.

Result

First, a definition of ADRD risk using cut offs and ranges of subjective and objective data gathered by various cognitive assessment tools was created. Second, preliminary results of 26 participants have shown 61.5% are at high risk. Diet and lack of physical activity are contributing risk factors. Further results will be made available at the time of presentation for the AAIC.

Conclusion

Determining ADRD risk will assist public health programs to prioritize risk factors in education and awareness efforts. Decolonizing concepts and paradigms of ADRD research is a first step to ensuring Indigenous values are recognized to achieve a culturally safe environment and build trust for research in our community.
Modifiable risk factors for age‐at‐onset of Alzheimer’s disease through genetic determinants
Authors: Li Yi‐Ju , La Jong ok , Fan Qiao , Martin Eden R.
Published: January 2025

Background

Age and genetic predisposition are well‐known, non‐modifiable risk factors for Alzheimer’s disease (AD). Epidemiological studies have linked several modifiable risk factors to AD, but less is known about their influence on the age‐at‐onset (AAO) of AD. With an increase of genome‐wide association studies (GWASs) and advanced genetic analysis developed, we sought to identify modifiable risk factors for AAO of AD and evaluate their causal effects.

Method

For AAO of AD, we utilized pooled genome‐wide imputed genotype data from 9,219 AD cases and 10,345 controls from 20 cohorts of the Alzheimer Disease Genetics Consortium (ADGC) and our own GWAS summary statistics for AAO of AD (Li et al. 2023). Thirty‐eight exposure factors related to comorbidity, lifestyle, and psychosocial risk factors were screened. The GWAS summary statistics of these exposures were from results released by individual publications or IEU OpenGWAS projects. PRSice‐2 was used to construct polygenic scores (PGS) for each exposure in ADGC subjects. Linear mixed models (LMM) were used to test for association of the exposure‐PGS with AAO, adjusting for sex, APOE‐E4, 10 PCs, and a random intercept by cohort. Exposures meeting p< 0.005 were considered significant risk factors, and they were then evaluated for the causal effect on AAO of AD by a two‐sample Mendelian Randomization (MR) using GWAS summary statistics of exposures (exposure‐GWAS) and AAO of AD. Instrumental variables were selected based on variants meeting p< 5×10−8 and p<5×10−6, respectively, from the exposure‐GWAS. We evaluated causal effects by the MR inverse variance weighted method and then followed by sensitivity analyses using weighted median and MR‐Egger.

Result

Seven genetically inferred exposures via PGS were significantly associated with AAO of AD (p < 0.005), including higher education attainment and relative fat intake delaying AD onset and type 2 diabetes, cardiovascular disease (CVD), hypertension, and smoking leading to earlier AAO. MR analysis showed lower education, T2D, CVD, and hypertension with significant causal effects on shifting AAO earlier (p<0.007).

Conclusion

The seven modifiable risk factors, particularly, the four causal factors for AAO of AD, will facilitate the early intervention and provide targets to delay AD onset.
Associations of positive and negative social connections with brain health in UK Biobank data
Authors: Samtani Suraj , Mahalingam Gowsaly , Wen Wei , Brodaty Henry , Sachdev Perminder S.
Published: January 2025

Background

Social connections are linked to brain health. Studies to date have ignored negative social connections and the association between social connections and white matter health. We explored the relationship between positive and negative social connections and brain imaging including white matter health. We hypothesized that positive and negative social connections would be related to better and worse brain health, respectively.

Method

We analysed UK Biobank data from 5704 adults aged 40+ (Mage = 54.12, 51.19%) who had brain scans at waves 2 and 3. We examined baseline social connections which were positive (household size, friend/family visits, community group engagement, having a confidante) and negative (loneliness, belittling or violence in romantic relationships). Outcome variables were total grey and white matter, amygdala and hippocampus volumes, white matter integrity and hyperintensities, and peak width of skeletonized mean diffusivity (PSMD; a marker of microstructural white matter changes) at waves 2 and 3. We ran linear mixed models controlling for age, sex and scanner (partially adjusted) and additionally for intracranial volumes (for brain volumes), education, physical activity, BMI, depression, hearing loss, alcohol use, smoking, hypertension, CVD, and air pollution (fully adjusted).

Result

In fully adjusted models, having a larger social network was associated with less decline from wave 2 to 3 in total grey matter (B = 671.61, 95%CI: 226.96,1,115.85), white matter (B = 511.72, 95%CI: 52.33,971.82), and right hippocampus volumes (B = 8.99, 95%CI: 1.44,16.54). Living with more people (B = 0.00049, 95%CI: 0.00021, 0.00077) and having a larger network size (B = 0.00035, 95%CI: 0.00024, 0.00045) were associated with less decline in white matter integrity. Experiencing romantic partner violence was associated with a greater increase in PSMD (B = 0.000079, 95%CI: 0.000016, 0.00014). Loneliness was not associated with brain health changes.

Conclusion

In a longitudinal sample of adults aged 40+, having a larger social network was associated with better brain health, including less decline in hippocampal volumes and white matter integrity. Experiencing romantic partner violence was associated with microstructural white matter changes. Our results highlight the need to screen for positive and negative social connections in adults in mid and late life to help maintain good brain health.
Association of basal forebrain atrophy with cognitive decline in early Alzheimer’s disease
Authors: Xia Ying , Dore Vincent , Fripp Jurgen , Bourgeat Pierrick , Laws Simon M. , Fowler Christopher J , Rainey‐Smith Stephanie R , Martins Ralph N , Rowe Christopher C. , Masters Colin L , Coulson Elizabeth J , Maruff Paul
Published: January 2025

Background

In early Alzheimer’s disease (AD), amyloid‐β (Aβ) accumulation is associated with volume loss in the basal forebrain (BF) and cognitive decline. However, the extent to which Aβ‐related BF atrophy manifests as cognitive decline is not understood. This study sought to characterize the relationships between Aβ burden, BF atrophy, and the decline in memory and attention in older individuals without dementia.

Method

The 476 older adults (72.6 ± 5.9 years old, 55.0% female) from the Australian Imaging, Biomarker and Lifestyle (AIBL) study were included, who underwent Aβ‐PET imaging at baseline and repeated MRI and cognitive assessments over a period up to 13 years. At baseline, participants were classified based on their clinical dementia stage and Aβ status, which were cognitively unimpaired (CU) Aβ−, CU Aβ+, and mild cognitive impairment (MCI) Aβ+. Linear mixed‐effects models assessed atrophy in BF subregions (Ch4p – posterior segment of the nucleus basalis of Meynert; Ch1/Ch2 ‐ medial septal nucleus and vertical limb of the diagonal band of Broca) and hippocampus as well as changes in their AIBL memory and attention composite scores. Associations between baseline Aβ burden, brain atrophy, and cognitive decline were evaluated and explored using mediation analyses.

Result

Compared to the CU Aβ− group, CU Aβ+ and MCI Aβ+ adults both showed faster decline in BF and hippocampal volumes as well as in memory and attention (all p < 0.001). While rates of atrophy across all regions correlated with cognitive decline, baseline Ch4p volume was associated moderately with rates of memory and attention decline (p < 0.001, η2 = 0.046 and 0.023). Furthermore, single‐mediator models demonstrated that rates of atrophy in all regions of interest significantly influenced the effects of Aβ burden on memory and attention decline (Table 1). When considering all three mediators simultaneously, hippocampal atrophy primarily mediated the effects of Aβ burden on memory decline (Figure 1A), whereas Ch4p and hippocampal atrophy play unique mediating roles in Aβ‐related attention decline (Figure 1B).

Conclusion

These findings underscore the important role of early volume loss in the BF, especially in Ch4p, in the complex pathway linking Aβ to cognitive impairment in early AD.
Sex differences in the prevalence of mild cognitive impairment and dementia, and their risk factors, in Bengaluru
Authors: Venugopal Aparna Lalana
Published: January 2025

Background

The burden of dementia is expected to increase owing to the rapidly increasing number of aged populations across the world. It is widely reported that risk of developing dementia is high in women compared to men and the contributing factors resulting these discrepancies are not well understood. In this context, the goal of the current study was to assess whether the prevalence of mild cognitive impairment (MCI) and dementia differs by sex in urban Bengaluru and whether risk factors for MCI and dementia differ by sex.

Method

A community‐based, cross‐sectional study was conducted in urban Bengaluru between January 2021 and December 2021. The study team performed household enumeration to identify individuals who were ≥ 60 years old. Neurologic, neuropsychological, and functionality tests and a risk profile questionnaire were administered to all participants. The assessment tools included Addenbrooke’s Cognitive Examination (ACE‐III; Mekala et al., 2020; Mathuranath et al., 2007), Clinical Dementia Rating Scale (CDR; Morris, 1991), and Instrumental Activities of Daily Living‐Elderly (IADL‐E; Mathuranath et al., 2005). The risk profile questionnaire included screening for common cardiovascular risk factors such as hypertension, heart disease, diabetes and stroke. Participants were categorized as having no cognitive impairment (NCI), MCI, or dementia. MCI was diagnosed based on Petersen’s criteria (2004) and dementia was diagnosed based on DSM‐IV criteria (1994).

Result

Of the 1,234 participants, 665 (53.9%) were female and 569 were male (46.1%). Males were slightly older (mean (SD): 72.0 (8.68) vs. 70.5 (7.79) years, p = 0.001) and had more years of education (mean (SD): 13.3 (4.65) vs. 9.9 (5.75), p<0.001). Of the 1,234 participants, 80 had MCI (6.5%) and 24 (1.9%) had dementia. More males than females had MCI (7.9% vs. 5.3%, p = 0.06). In contrast, males were less likely to be diagnosed with dementia (1.1% vs. 2.7%, p = 0.04). Males had a higher prevalence of heart disease, whereas females had a higher prevalence of hypertension.

Conclusion

The prevalence of MCI and dementia differs by sex in Bengaluru, as does the prevalence of vascular risk factors.
Exploring the Cognitive Health of LGBTQIA+ Older Adults from The Stonewall Generations Study
Authors: Flatt Jason D. , Klenczar Brittany , Uddin Jalal , OHala Max , Benson Sarah , Rosenblatt Andrew , Pudumjee Shehroo
Published: January 2025

Background

Over 2.5 million LGBTQIA+ (lesbian, gay, bisexual, transgender, queer, intersex, asexual or another sexual and/or gender minority identity) adults in the U.S. are aged 50 or older. Past studies have found that LGBTQIA+ older adults report worsening memory and thinking skills more often than non‐LGBTQIA+ older adults. The purpose of this study was to explore the risk and protective factors associated with the cognitive health of LGBTQIA+ older adults.

Methods

We utilized tailored recruitment and engagement strategies to recruit a community‐based sample (n = 67) of racial/ethnically diverse LGBTQIA+ older adults aged 50+ from the U.S. To examine cognitive health, we used the Telephone Interview for Cognitive Status (TICS), with scores ranging from 0‐41. Descriptive statistics were used to summarize demographic characteristics and TICS scores, and we used bivariate analyses to explore potential risk and protective factors associated with cognitive health.

Results

Mean age was 64.5 with range of 50 to 87 years. About 6% had high school degree or less and 23% reported an annual income of $30,000 or less. In terms of race/ethnicity, 85% identified as White, 10% Black, 6% American Indian/Alaska Native, and 10% Hispanic/Latino. For gender identity, 36% identified as women, 39% men, 18% transgender men/women, 12% another gender identity, and one person identified as intersex. For sexual orientation, 43% identified as gay, 36% lesbian, 12% bisexual, 10% queer, 9% heterosexual, 8% asexual, and 5% another identity. TICS scores ranged from 16 to 41 with a mean of 28.05 (SD = 4.92), with 16% falling into the mildly impaired and 9% in the moderately‐to‐severely impaired ranges. A lower TICS score was associated with lower education, functional impairment, past LGBTQIA+ related discrimination (minority stress), and PTSD‐related symptoms (p‐values <0.05).

Conclusions

Our current findings highlight the need for additional research on risk and protective factors for the cognitive health of diverse LGBTQIA+ older adults. Understanding the risk of cognitive impairment among LGBTQIA+ older adults is critical to defining the burden of Alzheimer’s disease and developing targeted prevention strategies for these understudied populations.
Family history and amyloid PET in white, Black, and Hispanic/Latino, cognitively normal individuals
Authors: Glenn Phelan , Mooney Katelyn Elizabeth , Kadiri Ose , Robinson Talia L , Amariglio Rebecca E , Sperling Reisa A , Deters Kacie
Published: January 2025

Background

Family history (FH) of AD increases risk for sporadic AD, and has been associated with increased amyloid accumulation. Most of these studies were done in non‐Hispanic white groups, limiting the generalizability of these findings. The goal of this study was to determine if FH was associated with levels of amyloid in White, Black, and Hispanic/Latino participants.

Methods

This study included cognitively normal individuals screening for the Anti‐Amyloid Treatment in Asymptomatic Alzheimer’s (A4) cohort whom self‐identified as Non‐Hispanic/Latino Black (NHB; N=145), Non‐Hispanic white (NHW; N=3766), or Hispanic/Latino white (HL; N=107). The effect of FH (father, mother or both, vs none) on amyloid PET SUVr was assessed using linear regression analysis within each ethnic and racialized group. Age and sex were used as covariates. This analysis was repeated adding APOE e4 allele as a moderator.

Results

NHB participants were more likely to be female (71.7%), had the lowest FH rate (56.6%), and were less likely to be amyloid positive (20%) compared to HL participants (female=64.5%; FH=62.6%; amyloid+=27.1%) and NHW participants (female=59.7%; FH=66.2%; amyloid+=30.2%). Having a FH of AD was associated with higher levels of amyloid SUVr (β=0.028, p=2e‐05) in NHW participants only (Table). This effect became non‐significant when APOE e4 was included in the model.

Conclusions

FH was associated with higher levels of amyloid SUVr in White participants only, but not in the presence of APOE e4. For Black and Hispanic participants, FH was not associated with levels of amyloid. These findings support previous findings in which risk factors for AD are not shared equally across different ethnic and racialized groups.
Longitudinal Trajectories of Blood‐based biomarkers for Alzheimer’s Disease in Subjective Cognitive Decline; the SCIENCe project
Authors: Trieu Calvin , van Harten Argonde C. , van Leeuwenstijn Mardou S. S. A. , Schlüter Lisa‐Marie , Verberk Inge M.W. , Boonkamp Lynn , Aladdin Azzam , Teunissen Charlotte , van der Flier Wiesje M.
Published: January 2025

Background

Blood‐based biomarkers are increasingly able to identify Alzheimer’s Disease pathology in the preclinical stages of the disease. These biomarkers hold promise to study development and progression of the disease. Our aim is to investigate the longitudinal trajectories of Aβ42/40 ratio, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) in individuals with subjective cognitive decline (SCD).

Method

From the SCIENCe cohort, we selected 298 individuals with SCD (age: 61.7±8.1), of whom 80 were amyloid positive (A+; 65.2±7.2) and 218 were amyloid negative (A‐; 60.3±8.0). Amyloid status was assessed using amyloid PET scans or CSF AD biomarkers. Participants underwent annual assessments to evaluate clinical progression to MCI or AD dementia (conversion: n=33). Plasma biomarkers, including Aβ42/40 ratio, GFAP, and NfL (pTau217‐pending analysis), were assessed approximately every two years with a mean follow up of 5.3±2.7 years on the SiMoA platform (Quanterix; total sample number: n=819). We used linear mixed models to examine associations between amyloid status and biomarker changes over time, with terms for amyloid status, time, and their interactions. Next, we examined associations between progression to MCI/dementia and biomarker changes over time, with terms for conversion, time, and their interactions.

Result

Aβ42/40 was lower in SCD A+ compared to SCD A‐ at baseline (p<0.001), but did not change over time in either group. GFAP and NfL were higher at baseline in SCD A+ (p<0.001; p=0.001). Both increased over time, but only NfL showed a more pronounced increase in SCD A+ compared to SCD A‐ (p=0.006). Aβ42/40 was lower in converters than non‐converters at baseline (p<0.001), with no longitudinal differences. NfL and GFAP were higher at baseline in converters (p<0.001; p=0.001), and both displayed a trend toward greater increase over time in converters compared to non‐converters (p=0.059; p=0.095).

Conclusion

Only NfL had a more pronounced increase over time in SCD A+ compared to SCD A‐, whereas all biomarkers differed between the groups at baseline. This suggests that Aβ42/40 may have already reached a plateau in SCD A+, while the neurodegeneration marker NfL continues to increase beyond what can be attributed solely to the aging process after the initial SCD diagnosis.
A Bayesian machine learning approach to Nature vs. Nurture: Predicting a cognitive marker of Alzheimer’s risk in a deeply‐phenotyped cohort of cognitively unimpaired older African Americans
Authors: Fausto Bernadette A. , Budak Miray , Sheikh Mustafa , Perez José Mojica , Li Shengguo , Hu Liangyuan , Gluck Mark A.
Published: January 2025

Background

Late‐onset Alzheimer’s disease (AD) arises from interactions between genetic (nature) and environmental/behavioral (nurture) factors, but their relative contributions are not well defined. With the development of sensitive cognitive tasks for early detection and the growing applications of machine learning to AD research, there are unprecedented opportunities to uncover the most salient genetic and environmental/behavioral factors for preclinical AD risk. Our previous studies show that generalization performance––the ability to apply prior learning to new contexts––is a cognitive risk marker for preclinical AD. Using a novel technique combining Bayesian machine learning and bootstrap imputation, the present study identified among various candidate genetic and environmental/behavioral factors which most strongly predicted generalization performance in a deeply‐phenotyped cohort of cognitively unimpaired older African Americans.

Method

472 older African American participants from the Pathways to Healthy Aging in African Americans cohort study (Mage=68.34 years, SD=6.99; Meducation=13.93 years, SD=2.36; MMMSE=27.65, SD=1.95) responded to demographic, health, and lifestyle questionnaires; provided a saliva sample for the following AD risk genotyping: ABCA7 rs115550680, APOE‐ε4 status, ABCA7 rs3764650; and completed a cognitive battery including a generalization task (Concurrent Discrimination and Transfer Task). We employed Bayesian Additive Regression Trees (a.k.a., BART) with a bootstrap imputation‐based variable selection procedure to extract the top three variables in terms of relative contribution to generalization performance.

Result

Among 25 candidate variables, the top three ranked variables related to generalization included ABCA7 rs115550680, est.=3.29 [95% CI 0.42, 6.19]; APOE‐ε4 status, est.=2.41 [95% CI 0.37, 4.46]; and their performance on the training phase of the generalization task, est.=0.92, [95% CI 0.86, 0.99], above and beyond other demographic, health, lifestyle, and cognitive variables.

Conclusion

Using novel machine learning techniques and a sensitive cognitive risk marker, we identified that generalization performance is most strongly driven by genetic vulnerability to AD among older African Americans. These findings suggest a greater contribution of genetic factors (nature) compared to environmental/behavioral factors (nurture) to late‐onset AD risk within this population.
The Neuronal Synuclein Disease Integrated Staging System ‐– Opportunities to advance Lewy body dementia research
Authors: Poston Kathleen L.
Published: January 2025

Recent advances in biomarkers, enabling the in vivo detection of pathological aggregates of alpha‐synuclein (asyn), allow a shift from a clinical to a biological definition of Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). The newly proposed “Neuronal alpha‐Synuclein Disease (NSD)” is defined by the presence of pathologic neuronal (n‐asyn) species detected in vivo (S), irrespective of any specific clinical syndrome. Additional biological anchors include dopaminergic neuronal dysfunction (D). This biological definition forms the basis for the NSD Integrated Staging System (NSD‐ISS), rooted in the biological anchors (S and D) and the degree of functional impairment caused by clinical signs/symptoms.

Stage 1 and 2 are marked by S alone (Stage 1A or 2A), or both S and D (Stage 1B or 2B), differentiated by absence of signs/symptoms (stage 1) or appearance of subtle signs/symptoms without functional impairment (stage 2). Critically, these patients could progress to Stage 3 by developing a functional impairment due to cognitive or motor or other non‐motor impairments. Stages 2B‐6 require both S and D, with Stages 3‐6 defined by their stage‐specific increases in functional impairment.

The NSD definition and NSD‐ISS framework will enhance drug development and clinical trial efficacy by facilitating the selection of a homogeneous target population with biological consistency, which is particularly relevant to drug development in Lewy body dementias. Also critical to research in Lewy body dementias, NSD could inform how and when to co‐enroll patients with dementia regardless whether they initially presented with motor or cognitive impairments. The NSD‐ISS framework will also context for considering research in Lewy body dementia patients with and without ATN biomarkers. Currently NSD‐ ISS is a research tool and is not intended for clinical use.
Physical activity and amyloid onset age: Findings from three studies of community‐dwelling adults
Authors: Dougherty Ryan J. , Wang Jiangxia , Bilgel Murat , Betthauser Tobey J. , Resnick Susan M. , Okonkwo Ozioma C , Johnson Sterling C. , Schrack Jennifer A , Albert Marilyn S.
Published: January 2025

Background

Higher levels of physical activity, measured through accelerometry, have shown associations with several indices of brain and cognitive health in middle‐to‐late aged individuals. The association of physical activity and AD‐specific biomarkers measured through positron emission tomography (PET), however, remains unclear. Previous studies show no direct association of physical activity with amyloid‐PET levels, but associations with the onset of amyloid positivity remain unexplored. This study used estimated amyloid onset age (EAOA), defined as the age at which a participant is expected to attain the amyloid positivity threshold based on longitudinal PET, to investigate if higher levels of physical activity are associated with later EAOA across three cohort studies including: the Biomarkers of Cognitive Decline among Normal Individuals (BIOCARD) study, the Baltimore Longitudinal Study of Aging (BLSA), and the Wisconsin Registry for Alzheimer’s Prevention (WRAP) study.

Method

Cognitively unimpaired participants from BIOCARD (N = 133), BLSA (N = 117), and WRAP (N = 115) who completed accelerometer‐measured physical activity monitoring over 7 days and underwent 11C‐Pittsburgh compound B PET imaging were included. Total daily physical activity was measured through wrist‐worn (BIOCARD, BLSA) or waist‐worn (WRAP) accelerometers and EAOA was estimated using sampled Iterative Local Approximation. Proportional Hazard Cox regression models assessed whether physical activity is associated with EAOA, using right‐censoring for participants who did not develop amyloid positivity, adjusting for sex and APOE status. Potential interactions between physical activity and APOE status were also assessed.

Result

Participant demographics are displayed in Table 1. Across all three cohorts, APOE status was associated with EAOA (all p<.05), such that APOE‐e4 carriers had an earlier amyloid onset. We did not observe associations between physical activity and EAOA among BIOCARD (z‐score HR = 1.27, p = 0.27), BLSA (z‐score HR = 1.01, p = 0.97), or WRAP participants (z‐score HR = 0.96, p = 0.85). Furthermore, no significant interactions between physical activity and APOE status were observed (all p>.05).

Conclusion

Across three separate studies of community‐dwelling middle‐ age and older adults, we did not observe an association between accelerometer‐measured physical activity and EAOA. Further research is needed to i) determine if alternate methods for assessing physical activity are associated with AD biomarkers and ii) investigate non‐AD pathways through which physical activity may impact cognitive function and AD risk.
Utilizing Advanced Artificial Intelligence for Automated Detection and Segmentation of Amyloid‐Related Imaging Abnormality (ARIA)
Authors: Xie Long , Yushkevich Paul A. , Das Sandhitsu R. , Wolk David A , Gibson Eli
Published: January 2025

Background

The recent breakthrough in monoclonal antibody treatment for Alzheimer’s disease (AD) has ushered in a new phase in AD healthcare. However, associated amyloid‐related imaging abnormalities (ARIA) present a significant risk to patients, necessitating careful monitoring. Detection by radiologists can be challenging and may suffer from inconsistency. This study investigates the potential of advanced artificial intelligence (AI) for automated detection of micro‐hemorrhage (mH) in GRE MRI and ARIA‐like abnormal hyper‐intensity in FLAIR MRI, the two primary manifestations of ARIA.

Methods

In a multi‐site clinical MRI dataset, we selected 399 GRE scans with micro‐hemorrhage as well as 161 FLAIR scans from stroke and posterior reversible encephalopathy syndrome (PRES) patients with ARIA‐like abnormal hyper‐intensity. Expert annotators, under the supervision of a radiologist, manually delineated micro‐hemorrhage and abnormal hyper‐intensity. An additional 2789 GRE scans of normal subjects were included to evaluate micro‐hemorrhage detection performance. 75% of the data was used to train two AI models to segment micro‐hemorrhage and abnormal hyper‐intensity respectively. Both AI models, adopting the U‐Net architecture, were fine‐tuned from a foundational model pretrained on another 5322 clinical MRI scans in a self‐supervised manner. Evaluation was conducted on the test set (the remaining 25%). The receiver operating characteristic (ROC) analysis was performed to investigate the discrimination of GRE scans with and without micro‐hemorrhage. Additionally, the sensitivity, and false positives of detecting individual micro‐hemorrhage were reported. For abnormal FLAIR hyperintensity, the Dice coefficient of the AI‐derived segmentation was computed.

Results

The prototype discriminated GRE scans with and without micro‐hemorrhage with an ROC area under the curve of 0.93 (Figure 1‐d). At the single micro‐hemorrhage level, the AI system achieved a detection sensitivity of 0.81 with 0.82 false positives per scan. For abnormal FLAIR hyper‐intensity segmentation, our AI model achieved an average Dice coefficient of 0.76±0.07 (Figure 2). Qualitative results are presented in Figures 1 and 2.

Conclusions

The findings demonstrate that the proposed AI systems, grounded in foundational AI techniques, can reliably detect micro‐hemorrhage from GRE scans and segment ARIA‐like abnormal FLAIR hyper‐intensity. These systems may play a crucial role in the automated detection and monitoring of ARIA, leading to enhanced patient care.
Affective response to exercise and physical activity engagement: preliminary results
Authors: Stojanovic Marta , Morris John C. , Ances Beau , Head Denise M
Published: January 2025

Background

Due to multiple benefits of sustained exercise and physical activity, it is important to understand factors that can facilitate regular engagement in physical activity in later adulthood. Prior work found that a more positive affective response to acute exercise was associated with greater physical activity levels in younger adults. However, this determinant has been understudied in older adults and individuals at risk of Alzheimer disease (AD). Hence, the first goal of the study was to examine whether affective response to acute exercise predicted physical activity levels in middle‐aged and older adults. In addition, depression has been linked to reduced physical activity levels and might impact the role of affective response. Furthermore, there is often a decline in physical activity engagement with accumulation of AD pathology. Hence, the second goal was to examine whether depressive symptoms and AD genetic risk moderate the association between affective response to exercise and physical activity levels.

Method

Cognitively normal individuals from the Knight ADRC Adult Children Study (n = 65; age range 44‐85 years) completed an acute bout of moderate‐intensity exercise. Affect was measured at baseline, immediately after, 15 minutes, and 30 minutes post‐exercise. Participants also completed one week of actigraphy, which provided an objective estimate of their physical activity levels. Finally, the 15‐item Geriatric Depression Scale (n = 49) and APOE phenotyping (n = 61) were obtained from a subset of individuals.

Result

Greater increase in high arousal positive affect following the acute exercise was associated with higher levels of moderate‐to‐vigorous physical activity (p = 0.041). There was no moderation by depressive symptoms (p = 0.288) or APOE genotype (p = 0.962).

Conclusion

These results suggest that a positive affective response to moderate‐intensity exercise might be predictive of physical activity levels across later adulthood. However, depressive symptoms and genetic risk for AD might be limited as moderators of this association. Future studies should use a larger sample size and consider additional measures of AD pathology as potential moderators.
Blood‐based biomarkers and risk of MCI symptom onset over the short and long‐term
Authors: Soldan Anja , Pettigrew Corinne , Wang Jiangxia , Albert Marilyn S. , Blennow Kaj , Bittner Tobias , Moghekar Abhay
Published: January 2025

Background

Blood‐based biomarkers of amyloid and tau have been shown to predict AD‐dementia risk. Much less is known about their ability to predict risk of Mild Cognitive Impairment (MCI) among cognitively normal individuals. It is also unclear how AD non‐specific blood markers of neurodegeneration and neuroinflammation predict MCI and whether they add predictive power above and beyond AD biomarkers. The current study examined whether levels of blood biomarkers of amyloid (Ab42/Ab40), tau (p‐tau181), neurodegeneration (NfL), and neuroinflammation (GFAP, YKL40, sTREM2) collected when participants were cognitively normal predict the time to onset of MCI, both alone and in combination.

Method

The plasma assays were based on the NeuroToolKit (cobas Elecsys assays, Roche Diagnostics) and obtained from 271 cognitively unimpaired BIOCARD Study participants at their initial baseline evaluation (mean age=57.5y, including 82 who progressed to MCI/dementia). A second ‘baseline’ specimen (collected using different procedures) was evaluated for a subset of participants who were cognitively normal ∼7 years later (N=202) (mean age = 64.5y), including 31 who later developed MCI/dementia, Table 1). Mean clinical follow‐up was 15.5 years for Baseline 1 and 9.9 years for ‘Baseline 2’. Cox regression models tested the association of biomarker levels with time to MCI symptom onset, separately for both baselines.

Results

For both baselines, lower levels of Ab42/Ab40, higher GFAP, and a higher ratio of p‐tau181/Ab42/Ab40were each associated with an earlier time to MCI symptom onset (p’s<=0.034, Table 2). For baseline 2, higher p‐tau181 (p=0.009) was also associated with earlier MCI symptom onset (p=0.009), and higher NfL was associated with earlier MCI symptom onset for progression within 7 years (p=0.05). When combining biomarkers, Ab42/Ab40 and p‐tau181 independently predicted progression (p’s <0.03), but neither GFAP nor NFL added predictive value after accounting for Ab42/Ab40 and p‐tau181. YKL40 and sTREM2 were not associated with MCI onset in any analyses.

Conclusion

This indicate that during preclinical AD, more abnormal blood biomarker levels of amyloid (Ab42/Ab40), tau (p‐tau181), neurodegeneration (NfL), and neuroinflammation (GFAP) individually predict progression from normal cognition to MCI, but that AD non‐specific neurodegeneration and inflammation do not improve prediction after accounting for amyloid and p‐tau levels.
Lower plasma p‐tau levels and larger hippocampi may protect African American SuperAgers from age‐related cognitive decline and Alzheimer’s disease
Authors: Piaszczynska Wiktoria , Budak Miray , Fausto Bernadette A. , White Payton G. , Perna Robert , Fitzgerald‐Bocarsly Patricia , Tawe Fanyu Hercules , Ashton Nicholas J. , Blennow Kaj , Zetterberg Henrik , Gluck Mark A.
Published: January 2025

Background

Advancing age is typically associated with a decline in memory capacity and increased risk of Alzheimer’s disease (AD)1. However, there is a subgroup of the older adult population defined as SuperAgers that presents excellent memory performance reflecting resilience to the typical and pathological pathways of aging 2. Atrophy in hippocampal subregions, key areas for memory formation, are early anatomical markers of preclinical AD3. Plasma p‐tau levels, particularly p‐tau 231, also show sensitivity to preclinical AD neuropathology.4 This study aimed to investigate structural neuroimaging and plasma biomarker differences between the SuperAger phenotype and typical agers among African Americans.

Method

Participants were drawn from the ongoing longitudinal study, Pathways to Healthy Aging in African Americans conducted at Rutgers University–Newark. 100 participants (matched for SuperAger and typical ager status) completed a neuroimaging visit and a blood draw for plasma biomarkers. AFNI and ANTs were used for the segmentation of the medial temporal lobe and hippocampal regions of interest. Furthermore, plasma aliquots were sent for p‐tau 231 processing via Quanterix Simoa™.

Result

SuperAgers had lower levels of p‐tau 231, (t(19) = 2.85, p = 0.010, d = 20.38) than typical agers suggesting reduced AD neuropathology burden. African American SuperAgers also had greater DG/CA3 volumes, (t(19) = ‐2.756, p = 0.013, d = 46.42) than typical agers.

Conclusion

SuperAgers demonstrated larger hippocampal subregions implicated in memory formation and lower plasma p‐tau levels suggesting potential neuroprotective mechanisms in this unique population. SuperAgers may represent a valuable model for understanding cognitive resilience and for developing novel therapeutic strategies to mitigate age‐related cognitive decline and AD.
Cognitive, behavioral, and functional outcomes of suspected mild traumatic brain injury in community‐dwelling older persons without mild cognitive impairment or dementia
Authors: Guan Dylan X. , Peters Matthew E. , Pike G. Bruce , Smith Eric E. , Ismail Zahinoor
Published: January 2025

Background

Traumatic brain injury (TBI) is a risk factor for dementia and is linked to earlier age of onset. This study investigated whether later‐life changes in everyday cognition and behavior – risk markers of AD – could be observed in cognitively unimpaired older persons who sustained suspected mild TBI (smTBI) earlier in life and whether these cognitive and behavioral changes behavior mediated the link between smTBI and daily function.

Method

Data for 1274 participants from the Canadian Platform for Research Online to Investigate Health, Quality of Life, Cognition, Behaviour, Function, and Caregiving in Aging (CAN‐PROTECT) study were analyzed. A self‐reported brain injury screening questionnaire was used to determine smTBI. Outcomes were measured using the Everyday Cognition (ECog‐II) scale, MBI Checklist (MBI‐C), and Standard Assessment of Global Everyday Activities (SAGEA). SCD was operationalized based on a score of ≥2 (i.e., consistently a little or much worse) on any ECog‐II item. MBI+ status was defined by MBI‐C total scores ≥8. Age, sex, years of education, marital status, and ethnocultural origin were balanced across exposure groups using inverse probability of treatment weighting. Weighted logistic and negative binomial regressions were used to model smTBI (exposure) associations with SCD and MBI+ statuses, and ECog‐II and MBI‐C total scores, respectively.

Result

Sample characteristics are shown in Table 1. Sustaining smTBI throughout the life course was linked to a higher odds of participants reporting SCD or MBI, as well as higher ECog‐II or MBI‐C total scores [Table 2]. Finally, SCD partially mediated, whereas MBI+ fully mediated, the association between smTBI and SAGEA total scores; SCD and MBI+ statuses accounted for approximately 45% and 70% of the total effect, respectively [Table 3].

Conclusion

Sustaining smTBI throughout the life course is linked to poorer cognition and behavior even in community‐dwelling older persons without MCI or dementia. Older persons with smTBI may benefit from early dementia risk assessment using tools that measure changes in cognition and behavior. Interventions for declining cognition and behavior may also be beneficial in this population to address functional impairment.
Matched Proteomics of Cerebrospinal Fluid and Brain Reveals Conserved and Discordant Mechanisms of Progressive Aβ Pathology in Mice
Authors: Tfaily Ali , Srivastava Upasna , Rayaprolu Sruti , Kumar Prateek , Xiao Hailian , Duong Duc M , Dammer Eric B. , Seyfried Nicholas T , Rangaraju Srikant
Published: January 2025

Background

Cerebrospinal fluid (CSF) is an important source of protein biomarkers for diagnosis, risk stratification, and predicting treatment response in Alzheimer's disease (AD). Proximity to brain parenchyma suggests that CSF proteomic alterations may mirror brain pathological changes. Understanding the evolution of CSF proteomic changes and their alignment with concurrent brain pathology necessitates matched CSF and brain analyses, which are possible using animal models of AD pathology.

Method

CSF and brain (cortex) from 86 mice (47 wild‐type (WT) and 39 5xFAD, age groups of 1.8, 3, 6, 10, 14 months, equal males and females) underwent tandem‐mass‐tag mass spectrometry (TMT‐MS) across six TMT batches. After batch‐correction of data, we identified differentially enriched proteins (DEPs, ANOVA p<0.05), comparing WT and 5xFAD across various ages. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were conducted to elucidate conserved and discordant pathways in CSF and brain (Figure 1A).

Result

Of 8,535 brain proteins and 3,721 CSF proteins, 3,236 proteins were present in both (Figure 1B). In CSF, most DEPs were found at 1.8‐10‐month ages, followed by a marked decrease at 14 months. In contrast with CSF, DEPs in brain progressively increased with age (Figures. 1C‐1D). GSVA revealed that early unique CSF changes involved synaptic dysfunction and cellular stress, while later changes involved mitochondrial dysfunction and neuronal death. In brain, our analysis indicated heightened immune/glial activation and alterations in cellular structure, with late‐stage changes indicative of cellular, synaptic, and vascular dysfunction. DEPs (5xFAD vs. CSF) in CSF minimally overlapped with brain DEPs (<10%) at 1.8 and 3 months, but increased to >30% at later (6‐14 months) time points. Concordance between CSF and brain changes was highest at 6 and 10 months, particularly in immune response mechanisms and metabolic processes (Figures. 1E‐1F).

Conclusion

Our findings underscore distinct patterns in the CSF and brain proteomes during the progression of Aβ pathology. Although 87% of CSF proteins are shared with brain, limited DEPs overlap shows unique molecular signatures, suggesting that most CSF changes do not reflect brain‐level changes. Despite this, immune, metabolic, and proteostasis‐related mechanisms show temporal concordance between CSF and the brain.