bluuebunny/crossref_metadata_2025 huggingface dataset:
APOE‐ε4 carriership modifies the association of CCL11 and sVCAM1 plasma protein levels with cognitive performance in individuals at risk of Alzheimer's disease
Authors: Hernández‐Villamizar Luis Felipe , Segura‐Retana Pol , Escalante Armand González , Milà‐Alomà Marta , Ortiz‐Romero Paula , Diego‐Osaba Marina De , Braun‐Wolhfahrt Luisa , López‐Martos David , Sánchez‐Benavides Gonzalo , Zetterberg Henrik , Blennow Kaj , Anastasi Federica , Suarez‐Calvet Marc
Published: January 2025

Background

In murine models, peripheral blood factors have been identified as having either a brain rejuvenating or ageing effect. However, it is unclear whether these blood factors have similar effects in humans. We aimed at testing the association between these blood factors and cognitive performance in cognitively unimpaired (CU) individuals at risk of Alzheimer’s disease (AD).

Method

We included 414 CU participants from the ALFA+ cohort [mean age: 61.1(±4.72), women:60.4%, APOE‐ε4 carriers:54.8%, and amyloid‐positive:34.2%]. A subset of participants (n=341) had longitudinal follow‐up [mean follow of 3.28 years (0.50)]. Amyloid positivity was determined by CSF‐Aβ42/40<0.071. Blood factors associated with an ageing effect [β2‐microglobulin(β2‐M), CCL2, CCL11, CCL19, Haptoglobin, sVCAM1] or rejuvenating effect (CSF2 and TIMP2) were measured using ELISA, MSD, or Simoa immunoassays.

Through linear regression analyses we first tested the association between chronological age and each protein, correcting by sex. Then, we tested the association of each protein with baseline cognition and longitudinal cognitive changes at follow‐up, adjusting for age, sex and years of education. Cognitive data included the PACC score and domain‐specific composites (attention, episodic memory[EM] and executive function). The modifying effect of sex, APOE‐ε4 carriership, and amyloid status was also tested and significant interactions stratified.

Result

β2‐M and CCL11 significantly increased with chronological age (Figure 1). Only APOE‐ε4 carriership modified the association of age‐related blood factors CCL11 (pint=0.011) and sVCAM1 (pint=0.006) with cross‐sectional and longitudinal EM, respectively (Figure 2). In APOE‐ε4 non‐carriers, higher CCL11 was associated with better EM at baseline (β=0.105, p=0.025), while higher sVCAM1 was associated with better EM at follow‐up (β=0.076, p=0.010). Inversively, in APOE‐ε4 carriers, higher CCL11 was associated with worse EM at baseline (β=‐0.104, p=0.014), and higher sVCAM1 was associated with worse EM at follow‐up (β=‐0.073, p=0.014).

Conclusion

We observe an association between higher CCL11 and sVCAM1 and worse cognition in APOE‐ε4 carriers. This may suggest that the APOE‐ε4 carriers are more susceptible to the ageing effect of these blood factors.
Cognitive changes in co‐pathological Alzheimer’s disease and Synuclein diseases: A study of amyloid, tau, and alpha‐Synuclein biomarkers in the ADNI dataset
Authors: Wang Jian , Lu Ming , Shcherbinin Sergey , Morris Amanda , Rathore Saima , Iaccarino Leonardo , Pontecorvo Michael , Collins Emily C. , Mintun Mark
Published: January 2025

Background

Alzheimer’s and Synuclein diseases are characterized by distinct biomarkers and frequently co‐occur, suggesting potential interactions between their pathological pathways. This study leverages amyloid and tau PET imaging, along with CSF Phosphorylated tau (P‐tau) and alpha‐synuclein measurements from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to investigate the impact of co‐pathology on cognitive functions.

Method

We conducted an analysis using ADNI data (Table 1) from the 2024‐01‐08 download, including results from the CSF alpha‐Synuclein Seed Amplification Assay (SAA, 2023‐09‐29 release, 1637 samples out of 1638 records included in the analysis). The diagnostic performance of the CSF alpha‐Synuclein SAA was assessed by comparing it to autopsy alpha‐Synuclein immunohistochemistry (IHC) findings. Cognitive and functional assessments were examined in relation to amyloid, tau, and alpha‐synuclein biomarkers, both individually and collectively. Mixed‐model repeated measures (MMRM) analysis was utilized to evaluate ADAS‐Cog13, MMSE, and CDR‐SB score change up to 36 months following CSF collection, adjusting for age, sex, number of APOE e4 alleles, cognitive scores and clinical diagnoses at CSF collection.

Result

The CSF alpha‐Synuclein SAA showed a strong agreement with postmortem alpha‐Synuclein IHC (Figure 1). The probability of positive alpha‐Synuclein (Syn+) was associated with aging and the severity of clinical diagnosis (cognitively normal to mild cognitive impairment to dementia). Cross‐sectionally, subjects with Amyloid+Syn+ had worse cognitive scores compared to those with Amyloid+Syn‐ status. Investigation of the relationship between alpha‐Synuclein and tau biomarkers was pending on additional samples in upcoming data release. MMRM analysis (Figure 2) revealed that longitudinally subjects of MCI or dementia with Amyloid+Syn+ status declined faster in ADAS13, MMSE, and CDRSB scores than those with Amyloid+Syn‐ status. These differences were statistically significant at 36 months post‐CSF collection for MMSE (p < 0.01) and CDR‐SB (p < 0.05).

Conclusion

The worse cross‐sectional cognitive scores, as well as faster longitudinal decline in Amyloid+Syn+ vs Amyloid+Syn‐ subjects suggest that the co‐occurrence of these biomarkers indicates a more aggressive trajectory of dementia. These observations reinforce the importance of comprehensive biomarker profiling in predicting cognitive decline and underscore the need for further studies to investigate the complex dynamics of co‐pathology in Alzheimer’s and Parkinson’s diseases.
Association between temporal lobe cortical NODDI measures and memory function
Authors: Pillai Jay J , Reid Robert I. , Weigand Stephen D. , Cogswell Petrice M , Vemuri Prashanthi , Machulda Mary M. , Knopman David S. , Graff‐Radford Jonathan , Petersen Ronald C. , Jack Clifford R.
Published: January 2025

Background

Cortical structural changes in the temporal lobes including global and hippocampal volume loss and decrease in cortical thickness are well‐associated findings linked to cognitive decline in MCI and dementia patients. Neurite orientation dispersion and density imaging (NODDI) is a multishell diffusion MRI method enabling assessment of tissue microstructural integrity at the axonal and dendritic level. We wished to determine whether changes in temporal cortex orientation dispersion index (ODI) & neurite density index (NDI) correlate with decreases in memory function.

Method

The MCALT_ADIR122 cortical atlas was used for ROI designation. NODDI imaging was obtained on a 3T Siemens Prisma scanner with 2 mm isotropic resolution. Participants (ages 60‐95 years) were cognitively unimpaired (CU) or had mild cognitive impairment (MCI). CU & MCI subjects were enrolled in the Mayo Clinic Study of Aging (MCSA) and underwent neuropsychological testing including 3 memory tests from which a composite memory z score was calculated. A generalized additive regression model was used to estimate z scores as a smooth function of ODI, NDI and cortical thickness or volume with adjustment for age, gender, education, MCSA cycle number, WMH and intracranial volume.

Result

The Table displays demographic data. Figures 1 and 2 show the relationship of NDI and ODI measures to memory z scores across participants in individual ROIs both before and after adjustment for cortical thickness (“structural MRI”) as well as for confounds listed above. Both higher cortical thickness and higher NDI values in the hippocampus and entorhinal cortex were associated with significantly higher memory z‐scores (p<0.001) (Figure 1). Higher ODI values in addition to greater cortical thickness in temporal lobe regions, including within the hippocampus, parahippocampal gyrus, entorhinal cortex and inferior temporal gyrus, were associated with higher memory z‐scores (Figure 2). These significant associations (p <=0.01) were maintained after adjusting for cortical thickness in all these regions except entorhinal cortex for ODI.

Conclusion

NODDI‐derived measures of microstructural integrity (NDI & ODI) within the temporal cortex may provide information about memory decline, beyond what cortical thickness analysis provides, and may be potentially useful for monitoring therapeutic effects of AD immunotherapy in the future.
Astrocyte reactivity associates with tau phosphorylation and neurodegeneration before detectable amyloid‐β pathology
Authors: Saha Pampa , Povala Guilherme , Ferreira Pamela C.L. , Amaral Livia , Abbas Sarah , Lussier Firoza Z , Rodrigues Matheus Scarpatto , Oliveira Markley , Rahmouni Nesrine , Tissot Cécile , Soares Carolina , Therriault Joseph , Servaes Stijn , Stevenson Jenna , Hong Chang‐Hyung , Roh Hyun Woong , Karim Helmet T. , Benedet Andrea L. , Ashton Nicholas J. , Zetterberg Henrik , Blennow Kaj , Karikari Thomas K , Kim Sang Joon , Bellaver Bruna , Pascoal Tharick Ali , Rosa‐Neto Pedro
Published: January 2025

Background

Aβ plaques are the first detectable signs of AD pathology. Our group recently demonstrated that the astrocyte activation marker, glial fibrillary acidic protein (GFAP), has a pivotal role in the association between Aβ burden and tau phosphorylation. However, the role of astrocyte activation in individuals that do not present detectable Aβ pathology using biomarkers is still underexplored. Here we sought to understand the association between plasma GFAP with tau phosphorylation and neurodegeneration in Aβ negative individuals.

Method

598 study participants [cognitively unimpaired, (CU)=200, and cognitively impaired, (CI)=398] from two cohorts (TRIAD, Canada and BICWALZ, South Korea) were assessed for Aβ‐PET, plasma GFAP, p‐tau217, NfL, and hippocampal volume measures. Pearson correlations between plasma GFAP and plasma p‐tau217, plasma NfL along with hippocampal volume was performed in Aβ‐PET negative individuals.

Result

Remarkably, we found that plasma GFAP levels positively correlate with plasma p‐tau217 levels in Aβ‐PET negative individuals in both cohorts [TRIAD cohort: r=0.23, p=0.01; BICWALZ cohort: r=0.21, p=0.0001; Figure: 1A, B]. Further, the correlation between plasma GFAP with plasma NfL has also been found to be positively correlated among the two cohorts [TRIAD cohort: r=0.45, p=0.0001; BICWALZ cohort: r=0.49, p=0.0001; Figure: 2A, B]. We also observed that hippocampal volume, as a neurodegeneration marker, reveals a significant negative Pearson correlation with plasma GFAP levels in Aβ‐PET negative human individuals from both the cohorts [TRIAD cohort: r=‐0.27, p=0.0009; BICWALZ cohort: r=‐0.24, p=0.0001; Figure: 3A, B].

Conclusion

Our study provides evidence from research and clinical cohorts that astrocyte reactivity may be associated with very early tau phosphorylation and neurodegeneration in the absence of Aβ pathology.
Resting‐State EEG Features of Cognitive Fluctuations in Patients with Lewy Body Dementia
Authors: Negida Ahmed , Lageman Sarah , Mukhopadhyay Nitai , Barrett Matthew J
Published: January 2025

Background

Lewy body dementia (LBD) is characterized by fluctuations in arousal and alertness, i.e., cognitive fluctuations (CF). Although CF significantly impacts quality of life, its neurophysiological basis remains poorly understood. This study's objective was to identify specific EEG features associated with cognitive fluctuations in patients with LBD.

Method

We conducted a cross‐sectional study of 35 patients prospectively enrolled through the outpatient clinics of the Department of Neurology at Virginia Commonwealth University. Based on the Clinician Assessment of Fluctuations, participants with Parkinson’s disease, Parkinson disease with dementia, and dementia with Lewy bodies were categorized as Lewy body disease without CF (LBwoCF) and Lewy body dementia with CF (LBDwCF). All patients underwent resting‐state EEG recording with eyes closed and eyes open for 3 minutes each. EEG data were preprocessed and cleaned, and the following features were extracted: dominant frequency (DF), dominant frequency variability (DFV), dominant frequency prevalence (DFP) within the alpha band (8 to 13 Hz), individual alpha peak frequency (IAF), and alpha reactivity. Kruskal‐Wallis tests and logistic regression models were used to evaluate the relationship between EEG features and group (LBDwCF vs. LBwoCF).

Result

We analyzed EEG features for 17 LBDwCF and 18 LBwoCF. For both EEG conditions, eyes open and eyes closed, the LBDwCF group had significantly lower DF, posterior DF, DFP (alpha), and IAF but not alpha reactivity or DFV, compared to LBwoCF (all P<0.003, Table 1). The EEG feature with the largest effect size (ε²=0.43) was DFP within the alpha band measured from the posterior electrodes in the eyes closed condition. These EEG features, except for IAF, remained significant predictors of group (LBDwCF vs. LBwoCF, all P<0.03, Table 2) in logistic regression models adjusting for age and Montreal Cognitive Assessment (MoCA) score.

Conclusion

Among patients with LBD and PD, resting‐state EEG features were associated with CF. These features were significant predictors of CF even after adjustment for MoCA scores and age. The development of an EEG‐based biomarker of cognitive fluctuations may improve diagnosis of this clinical feature and thus diagnosis of LBD.
Relationships between PET and blood plasma biomarkers in corticobasal syndrome
Authors: Singh Neha Atulkumar , Alnobani Alla , Graff‐Radford Jonathan , Machulda Mary M. , Mielke Michelle M. , Schwarz Christopher G. , Senjem Matthew L. , Jack Clifford R. , Lowe Val J. , Kanekiyo Takahisa , Josephs Keith A. , Whitwell Jennifer L.
Published: January 2025

Background

Corticobasal syndrome (CBS) is a progressive neurodegenerative syndrome that can result from several underlying neuropathologies, including Alzheimer’s disease (AD). Little is known about the utility of blood plasma measures to predict PET biomarker confirmed AD in CBS.

Method

Eighteen CBS patients (8 PET Aβ+; 10 PET Aβ‐) and 8 cognitively unimpaired Aβ‐ individuals (CU) were recruited by the Neurodegenerative Research group from the Department of Neurology, Mayo Clinic, Rochester, MN, underwent Aβ (Pittsburgh Compound‐B) and tau (18F‐flortaucipir) PET and provided a blood sample. Blood plasma analysis was performed to assess p‐tau 181, total tau, Aβ 42/40, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) using the Quanterix Simoa platform. Plasma concentrations were compared between Aβ‐, and Aβ+ CBS and controls using Kruskal‐Wallis corrected for multiple comparisons using Dunn’s test, with effect size measured with area under the receiver operating characteristic curve (AUROC) analysis. Spearman correlations were calculated to assess relationships between plasma concentrations and Aβ and tau PET uptake.

Result

The CBS Aβ+ group showed reduced Aβ42/40 ratio, with elevated p‐tau 181, GFAP and NfL plasma concentrations compared to CU, while the CBS Aβ‐ group only showed elevated NfL concentration compared to CU (Figure 1). Both p‐tau 181 (AUROC=0.95) and GFAP (AUROC=0.91) plasma concentrations were able to differentiate CBS Aβ‐ from CBS Aβ+. Plasma p‐tau 181 and GFAP concentrations showed a positive correlation to both Aβ and tau PET uptake, and the Aβ42/40 ratio showed a negative correlation to Aβ PET uptake (Figure 2). No correlations were observed between NfL and Aβ and tau PET.

Conclusion

This study supports the use of plasma p‐tau 181 and GFAP to detect AD in CBS, while NfL shows potential as a nonspecific disease biomarker of CBS regardless of underlying pathology. Plasma concentrations of these biomarkers may potentially be incorporated into clinical trials targeting CBS patients with underlying AD pathology.
Machine learning on unbiased proteomics of cerebrospinal fluid uncovers differential molecular signatures of Alzheimer’s disease and Normal Pressure Hydrocephalus
Authors: de Geus Matthijs B , Wu Chao‐Yi , Dodge Hiroko H , Leslie Shannon N , Wang Weiwei , Lam TuKiet , Nairn Angus C , Kivisäkk Pia , Arnold Steven E. , Carlyle Becky C.
Published: January 2025

Background

The differential diagnosis of Alzheimer’s disease (AD) and normal pressure hydrocephalus (NPH) is complicated by overlapping clinical manifestations. This challenges accurate clinical diagnosis and highlights the need for molecular level investigations to understand underlying pathologies. There have been few proteomic investigations into NPH, which were limited by low sample sizes and limited analytical depth. Here we applied machine learning to investigate the distinct and overlapping proteomic signatures associated with AD and NPH, compared to that of cognitively unimpaired controls (CU).

Method

Banked cerebrospinal fluid (CSF) samples were obtained from diagnostic lumbar punctures at an outpatient neurology clinic. Participants were classified based on clinical presentation, improvement after a high‐volume LP, and CSF amyloid‐b status as CU (N = 53), AD (N = 158), or NPH (N = 56). Proteomic quantification was done using data‐independent acquisition mass spectrometry. Defining molecular signatures between classes was investigated with random forest models in two‐way fashion and top features were assessed using Gini importance. Additionally, to determine functional changes, we examined enriched and depleted pathways with gene‐set enrichment analysis (GSEA) using fold‐change data between classes.

Result

Random forest models obtained high classification accuracy (>75%). Comparison of the top 30 proteins of each model indicated four proteins, MASP1, NRXN2, VCAN and LTBP2 as defining features in NPH compared to both CU and AD. Six proteins, SMOC1, PTPRN2, NPTX2, LUM, APLP1 and GFRA2 were defining features for both AD and NPH compared to CU. One protein, TTR, was a defining feature comparing AD to both CU and NPH. GSEA indicated 91 pathways to be differentially regulated in NPH compared to both CU and AD. Further analysis indicated specific enrichment of complement activation and immune response pathways in NPH. Pathways differentially regulated in AD compared to both CU and NPH included pathways related to glycolysis and metabolic processes.

Conclusion

Our analyses validate previously suggested mechanisms and provide novel insights into the differential pathologies of AD and NPH. Hereby, we aim to contribute to the development of more refined and early diagnostic tools, facilitating targeted therapeutic approaches for these neurologically challenging disorders.
Examining the relationship between angiopoietin‐2 and cognition in early Alzheimer’s disease
Authors: Song Bing Xin , Beroncal Erika , Andreazza Ana C. , Gallagher Damien , Marzolini Susan , Rapoport Mark J. , Charles Jocelyn , Herrmann Nathan , Oh Paul I. , Kiss Alex , Swardfager Walter , MacIntosh Bradley J. , Rajji Tarek K. , Marotta Giovanni , Siddiqui Mehreen , Vieira Danielle , Kusumo Raphael , Lanctôt Krista L.
Published: January 2025

Background

Angiopoietin‐2, which regulates endothelial permeability and angiogenesis functions, is emerging as a potential biomarker for early Alzheimer’s disease (AD). Elevated levels of cerebrospinal fluid angiopoietin‐2 concentrations have been found in early AD and may be associated with the breakdown of blood‐brain barrier that can contribute to cognitive decline. There is a lack of research on blood angiopoietin‐2 levels and cognition in early AD. Hence, we examined the association between serum angiopoietin‐2 and global cognition.

Method

Participants were diagnosed with mild cognitive impairment (MCI) due to AD or mild Alzheimer’s dementia using the Diagnostic and Statistical Manual of Mental Disorders 5 criteria for mild or major neurocognitive disorder. Serum angiopoietin‐2 concentrations (ng/mL) were measured and analyzed using enzyme‐linked immunosorbent assays. Global cognition was assessed by the Montreal Cognitive Assessment (MoCA). Linear regression analyses were used to assess the association between angiopoietin‐2 levels and cognition adjusting for covariates selected a priori: age and the presence of cardiovascular risk factors or disease (cardiovascular status). Angiopoietin‐2 levels were log‐transformed prior to analyses due to significant departure from normality in Shapiro‐Wilk tests.

Result

Of 30 participants [17 (57%) male, 21 (70%) MCI, 22 (73%) with cardiovascular risk factors or disease], the mean (SD) age was 74.8 (8.7), years of education was 16.3 (2.2), MoCA total score was 21.9 (3.4), and angiopoietin‐2 levels were 4.0 (3.6) ng/mL. Higher angiopoietin‐2 was associated with better cognition [F(3,26) = 6.7, p = .002, R2 = .44]. Controlling for age and cardiovascular status, one log angiopoietin‐2 unit was associated with a 4.2 (SE= 2.0) higher score in global cognition (p = .048, f2 = .10).

Conclusion

In this sample, higher serum angiopoietin‐2 concentrations were associated with better global cognition, controlling for age and cardiovascular status. This relationship supports the potential involvement of angiogenesis in cognitive functions and neurodegenerative diseases and suggests the need for further research to explore cardiovascular functions and cognition in early AD.
Dissociable spatial topography of neurodegeneration in Early‐onset and Late‐onset Alzheimer’s Disease: A head‐to‐head comparison of MRI‐derived atrophy measures between the LEADS and ADNI cohorts
Authors: Katsumi Yuta , Touroutoglou Alexandra , Brickhouse Michael , Eckbo Ryan , Joie Renaud La , Eloyan Ani , Nudelman Kelly N. , Foroud Tatiana M. , Dage Jeffrey L. , Carrillo Maria C. , Rabinovici Gil D. , Apostolova Liana G. , Dickerson Bradford C. ,   the LEADS Consortium
Published: January 2025

Background

Understanding how early‐onset Alzheimer’s disease (EOAD) differs from typical late‐onset AD (LOAD) is an important goal of AD research that may help increase the sensitivity of unique biomarkers for each phenotype. Building upon prior work based on small samples, here we leveraged two large, well‐characterized natural history study cohorts of AD patients (LEADS and ADNI3) to test the hypothesis that EOAD patients would show more prominent lateral and medial parietal and lateral temporal cortical atrophy sparing the medial temporal lobe (MTL), whereas LOAD patients would show prominent MTL atrophy.

Method

We investigated differences in the spatial topography of cortical atrophy between EOAD and LOAD patients by analyzing structural MRI data collected from 211 patients with sporadic EOAD and 88 cognitively unimpaired (CU) participants from the LEADS cohort as well as 144 patients with LOAD and 365 CU participants from the ADNI3 cohort. MRI data were processed via FreeSurfer v6.0 to estimate cortical thickness for each participant. A direct comparison of cortical thickness was performed between EOAD and LOAD patients based on W‐scores (i.e., Z‐scores adjusted for age and sex relative to CU participants within each cohort) while controlling for MMSE total scores. All patients underwent amyloid PET with 18F‐Florbetaben or 18F‐Florbetapir and amyloid positivity was centrally determined by quantification‐supported visual read.

Result

As expected, a direct comparison of cortical thickness between patients with EOAD and LOAD revealed a double dissociation between AD clinical phenotype and localization of cortical atrophy: EOAD patients showed greater atrophy in widespread cortical areas including the inferior parietal lobule (EOAD marginal mean W‐score ± SEM = ‐1.33±0.08 vs. LOAD = ‐0.52±0.09, p<.001, η2=.097), precuneus (‐1.66±0.09 vs. ‐0.59±0.10, p<.001, η2=.13), and caudal middle frontal gyrus (‐1.65±0.08 vs. ‐0.90±0.10, p<.001, η2=.074), whereas LOAD patients showed greater atrophy in the entorhinal/perirhinal cortex and temporal pole (‐1.00±0.09 vs. ‐1.41±0.11, p<.008, η2=.019).

Conclusion

These findings demonstrate a clearly dissociable spatial pattern of neurodegeneration between EOAD and LOAD, supporting our previously developed LOAD and EOAD signatures of cortical atrophy, which underlies the distinct episodic memory and other cognitive characteristics of these AD clinical phenotypes.
Integrative Analysis of Genetic Network and Brain Imaging using Generative Models for Alzheimer’s Disease Prediction
Authors: Lee Dong‐gi , Jung Sang‐Hyuk , Shen Li , Kim Dokyoon
Published: January 2025

Background

The structural characteristics of the brain, specifically the decrease of individual gray (or white) matter volumes, provide valuable insights into brain function and cognitive decline, including the development of Alzheimer’s disease (AD). In addition, genetic factors can play a significant role in changes in brain volumes, influencing biological activities and interacting in complex ways. In this study, we aim to investigate the relationship between genetic factors, structural brain volume, and the risk of AD.

Method

The proposed method utilizes a SNP network to capture interactions between genetic variants based on linkage disequilibrium scores. The network represents the complex relationships among genetic factors. Feature propagation, a technique that refines genetic variant information based on graph neural networks (GNNs), is then employed to predict AD risk scores. Meanwhile, brain imaging endophenotypes, following the concept of transcriptome‐wide association studies (TWAS), are used to enhance prediction power and identify significant regions affecting specific diseases. Moreover, a generative artificial intelligence model is applied to produce pseudo‐imaging endophenotypes for samples with only genetic information.

Result

The proposed method was applied to data including (i) both genetic and brain imaging information from two datasets: UK Biobank (UKBB), Alzheimer's Disease Neuroimaging Initiative (ADNI), and (ii) only genetic information from the All of Us research program (AoU). The results were cross‐validated from the two datasets (UKBB and ADNI), and a generative model was applied to AoU. The final prediction results were compared with other models, including the polygenic risk score–continuous shrinkage (PRS‐CS) model. Compared to the other methods, the proposed method demonstrated superior prediction performance and revealed genetic variants and brain regions that impact AD.

Conclusion

By integrating genetic information and brain imaging data, this study achieved improved disease risk prediction and a deeper understanding of the phased mechanism of AD associated with genetic variants and brain lesions. Furthermore, the insights gained into the relationship between genetics, brain structure, and diseases are expected to contribute to advancing our knowledge of disease progression and inform future research and clinical strategies for the prevention and management of these conditions.
GEAR 2.0 ‐ Detection of Dementia and Cognitive Impairment
Authors: Hwang Ula
Published: January 2025

Older adults use the emergency department (ED) as an important source of acute medical care, making 20+ million visits annually. Persons living with dementia are twice as likely to use the ED and 1.5 times more likely to have an avoidable visit. When in the ED, they often struggle with the fast‐paced setting and may not be able to give a complete medical history. These challenges, along with other adverse events, put patients with dementia at greater risk for poor outcomes. Yet emergency care for older adults is suboptimal, and care is especially poor for older adults with dementia, even though these adults seek ED‐based care more regularly than matched controls.

Three decades of research has shown that dementia is under‐recognized in emergency departments, despite a proliferation of screening tools. Under‐recognition of dementia in the ED leads to under‐recognition in inpatient services, which has broad‐reaching consequences, such as longer hospital stays, lower patient satisfaction, accelerated cognitive declines, and increased health care costs. Better detection of dementia may improve the ED staff’s ability to implement interventions that can reduce the rate of cognitive decline and improve care coordination and patient safety.

This session will review the literature of current and past dementia detection approaches and discuss top research questions generated by the patients, care partners and members of the transdisciplinary GEAR Detection Work Group.
A machine learning approach to predict amyloid and tau positivity using clinical features
Authors: Arnold Daniel , Borelli Wyllians Vendramini , Machado Luiza Santos , Rahmouni Nesrine , Therriault Joseph , Servaes Stijn , Stevenson Jenna , Macedo Arthur C. , Schumacher‐Schuh Artur Francisco , Mattjie Christian , Barros Rodrigo C. , de Bastiani Marco Antônio , Lussier Firoza Z , Chamoun Mira , Bezgin Gleb , Benedet Andrea L. , Pascoal Tharick , Rosa‐Neto Pedro , Zimmer Eduardo R. ,   Alzheimer's Disease Neuroimaging Initiative (ADNI)
Published: January 2025

Background

Screen failure due to amyloid negativity is yet a problem in clinical trials for anti‐amyloid drugs. In this context, clinical characteristics of patients presenting with cognitive decline may decrease the screen failure ratio by increasing the odds of selecting individuals with brain amyloid pathology. Herein, we aimed at estimating amyloid and tau positivity in individuals using clinical variables in a machine learning model of prediction.

Method

We selected 1694 participants with amyloid and tau status from ADNI, TRIAD, PPMI databases. Commonly shared clinical features selected between datasets were age, total MOCA scores, clinical diagnosis, sex, education, BMI, heart disease, stroke, hyperlipidemia and diabetes. Amyloid positivity was defined by amyloid‐PET (PIB‐PET, FBB‐PET or AZD4694‐PET) or CSF AB42 and Tau positivity defined by Tau‐PET (MK6240‐PET or AV1451‐PET) or CSF p‐tau181. The dataset was split into training (49%), validation (21%), and testing datasets (30%). A XGBoost model was tuned, and then used to predict the tau status outcome in the testing dataset.

Result

A total of 927 men and 767 women were included with mean MOCA 25.7 ± 3.8 scores (Table). The population consisted of 1276 CN, 290 MCI and 128 dementia individuals (1357 A‐T‐ and 337 A+T+). The receiver‐operator characteristic (ROC) analysis showed that the area under the curve (AUC) was 0.86 for discriminating A‐T‐ vs. A⁺T⁺, with 0.82 as sensitivity, specificity as 0.90 and accuracy as 0.88. The top 3 most impactful features were found to be age, diagnosis and MOCA score through a SHAP value analysis (Figure).

Conclusion

Predicting amyloid and tau positivity with clinically collectible variables may improve selection of individuals for anti‐amyloid trials. A two‐step workflow using this approach may significantly reduce the costs of AD trials. The following studies may incorporate an individualized calculator using clinical variables to estimate amyloid and tau positivity.
Multi‐omics analysis of neuron‐derived small extracellular vesicles to identify novel peripheral biomarker of cognitive impairment in individuals with type 2 diabetes
Authors: Kumar Ashish , Cleary Jacob Alexander , Su Yixin , Singh Sangeeta , Howard Marjorie , Hayden Kathleen M. , Lee Jingyun , Furdui Cristina M , Espeland Mark A. , Ding Jingzhong , Deep Gagan
Published: January 2025

Background

Central nervous system (CNS) dysregulated insulin and peripheral hyperinsulinemia has been associated with AD. However, analyzing CNS insulin resistance in living subjects and its implication on cognitive impairment/ AD is difficult to establish due to inaccessibility of brain tissue. In this study we isolated and characterized plasma neuron‐derived small extracellular vesicles (NDE), and adopted multi‐omics approaches to discover novel biomarkers of AD and CNS insulin resistance and suggested their possible association.

Method

Plasma samples were obtained from Look AHEAD‐MIND study with 28 cognitively normal (18 female and 10 male) and 28 individuals with probable dementia (11 female and 17 male) based on central adjudication by an expert panel. These individuals had established type 2 diabetes (T2D) and overweight/obesity when enrolled in a randomized controlled clinical trial of a 10‐year behavioral intervention. NDE were enriched from plasma sequentially using CD171 and synaptophysin surface markers by immunoprecipitation and characterized for non‐coding RNAs by small RNA‐sequencing and proteomics by mass spectrometry.

Result

The small RNA‐sequencing analysis identified the expression of over 100 miRNAs in NDE from both groups. The Comparison of differentially expressed miRNAs revealed 42 miRNAs to be downregulated, while 23 miRNAs were upregulated in individuals with dementia. Importantly, all these miRNAs (both up‐ and –downregulated) were found to be over‐represented in AD‐ and insulin signaling‐related pathways. Also, the targets of these miRNAs were associated with pathways like protein phosphorylation, autophagy, cell cycle and nervous system development. Alongside, the mass spectrometry‐based proteomics analysis identified 3 proteins (haptoglobin, complement component C6, and alpha‐2‐macroglobulin) to be significantly downregulated and 1 protein (desmocolin‐1) to be upregulated in the NDE of individuals with dementia. Interestingly, NDE showed upregulated expression of miR‐185‐5p, with concomitant downregulation of one of its potential targets complement protein C6, both known to be associated with AD and insulin signaling.

Conclusion

The study demonstrated multi‐omics approach to identify novel plasma NDE biomarkers for dementia pathogenesis and its association with CNS insulin resistance in individuals with T2D.
Retinal mitochondrial Fluorescence‐Lifetime Ophthalmoscopy data in patients with Alzheimer’s Disease
Authors: Shivok Kylee , Affel Elizabeth , Sergott Robert C.
Published: January 2025

Background

FLIO a novel in vivo reproducible, non‐invasive imaging technology, measures fluorescence lifetime decay in two spectral channels for short‐lived retinal chromophores in two domains: Channel 1 emission wavelength 498‐560 nm corresponding to NADH and FAD/ATP function and Channel 2, 560‐720 nm wavelength corresponding to lipofuscin/lysosomal function. These data reflect the retinal mitochondrial molecular environment. Mitochondrial dysfunction has been recently explored as a cause of decreased synaptic function and cognitive decline in AD. Only very limited data with first generation FLIO technology were previously reported.

Method

Twenty‐two individuals [48 eyes], 11 AD patients and 11 controls, underwent FLIO with second generation FLIO manufactured by Heidelberg Engineering. Imaging data were analyzed using SPCImage technology.

Result

Patients with AD demonstrated a right shift towards longer wavelength chromophores for both channels 1 and 2. The mean fluorescence decay time of the eye was also extended, leading to much broader wavelength plateaus compared to relative small areas under normal parabolic curve found in controls. In this small cohort, no differences were observed between amnestic and non‐amnestic patients with AD. Mitochondrial changes were more pronounced with longer disease duration and severity.

Conclusion

FLIO detected changes consistent with changes in the retinal mitochondrial molecular environment for both NADH, FAD, and lipofuscin not otherwise visible with other retinal imaging techniques. FLIO data add support to the hypothesis that mitochondrial dysfunction may contribute to AD neurodegeneration. FLIO may help to resolve the question of whether mitochondrial dysfunction is a primary event for AD and/or a secondary amplifier of the disease. Because it is non‐invasive, painless, reproducible, FLIO has promise as an imaging biomarker to aid in the diagnosis of AD as well as an outcome metric for longitudinal clinical trials.
Characterizing the Effects of APOE4 on AD Risk Markers in Mexican‐Americans
Authors: Contreras Joey A , Aslanyan Vahan , Espejo Kimberly , Pa Judy
Published: January 2025

Background

There is a growing need to determine if APOE status infers the same risk for Alzheimer’s disease (AD) in a Hispanic/Latino cohort as it would for a White cohort. To address this, we must first establish the relationship between APOE4 and known at‐risk markers for AD, such as amyloid beta (Aβ), tau, and inflammation. The following analysis compares these markers in non‐e4 carriers and e4 carriers within a Hispanic/Latino Cohort to help answer the question of whether APOE status correlates to AD pathology and inflammation in the same way as we have seen in other populations.

Method

Using baseline data from the Health and Aging Brain Study‐Health Disparities (HABS‐HD), a one‐way ANCOVA was conducted to determine group differences between Ab42, total tau, phosphorylated tau, and inflammatory marker Tumor Necrosis Factor (TNF)‐a among Mexican American APOE4 carriers and non‐carriers while controlling for sex and education. Outlier analysis was also conducted for inflammatory marker, TNF‐alpha. Participants with missing data and TNF‐α outlier values were excluded.

Result

The data used included 856 Hispanic participants, 699 APOE4 carriers (65%female, mean age ±SD=63.81(7.89)), and 157 non‐carriers (68% female, mean age ±SD=63.92(8.43)). There was significant differences between Mexican American APOE4 carriers and non‐carriers among AD pathology markers; Ab42(p=0.002), total tau(p=0.037), and inflammatory marker, TNF‐α(0.003) (Table 1). The bar graph illustrates mean differences in risk markers evaluated between both groups (Figure 1).

Conclusion

The obtained results indicate that individuals without the APOE4 gene variant exhibit elevated levels of total tau and increased inflammation (as indicated by TNF‐a), contradicting findings from prior literature. This suggests that genetic risk factors may not be as ubiquitous as previously reported and that the extent of the risk associated with the e4 variant could be influenced by race/ethnicity. Subsequent studies will contribute to this discovery by augmenting the sample size within the existing dataset and directly comparing it to a white cohort possessing more comprehensive neuroinflammatory biomarker data. Further details about the HABS‐HD cohort are provided in the description below.
Use of MRI for Alzheimer’s Disease Across Latin American Countries: A Systematic Review
Authors: Malaga Marco , Rivera Valeria , Morales Valeria , Bustamante‐Paytan Diego , Damian Andres , García‐Fontes Margarita , Montesinos Rosa , Custodio Nilton
Published: January 2025

Background

The worldwide prevalence of Alzheimer's Disease (AD) surpasses 55 million, with Latin America reaching 11%, driven by demographic changes. Precise diagnosis necessitates neuroimaging, particularly magnetic resonance imaging (MRI). However, low‐ to middle‐income countries face challenges in MRI accessibility due to limited imaging equipment and a shortage of specialized healthcare professionals trained in neuroimaging.

Methods

A systematic literature in English and Spanish was conducted in three databases for AD studies where MRI was conducted. Fifty‐three studies were included based in the inclusion and exclusion criteria. A narrative summary of protocols sequencing, and qualitative analysis was performed. For quality assessment, we evaluated the reporting of their imaging methodology based in the ADNI 3 study imaging protocol version 1.

Result

A total of 2370 reports were initially identified. Fifty‐three studies were ultimately included in the review, predominantly originating from Brazil (Figure 1). Within these studies, 38.6% employed the TI‐weighted non‐volumetric sequence (Figure 2). Functional analysis, regional brain volume, and white matter lesion quantification were reported in 20%, 20%, and 22% of the studies, respectively. Notably, research sites omitted information on whether they had obtained proper certification for health professionals and imaging equipment before the study. Most studies (71.7%) did not disclose whether pre‐scan contraindications evaluations were conducted, and only 11.3% specified the correct position for each participant during MRI subject pre‐scan procedures. In terms of external storage mode for acquired images (e.g., DVD, CD, online cloud, etc.), only three studies (5.7%) provided this information. As for scan procedures, merely one study (1.9%) documented instances where patients chose not to continue with the procedure, and no studies reported cases of repeat MRI scans (Table 1).

Conclusion

Significant and concerning gaps exist in Latin America regarding the acquisition of images for diagnosing AD. The development of standardized protocols is imperative to enhance the quality of neuroimaging outcomes in Alzheimer's Disease studies within this region.
Neurodegeneration Focused Biorepositories: NCRAD, BioSEND, MJFF
Authors: Edler Michael C. , Lacy Kaci , Snoddy Casey , Mitchell Colleen M. , Case K. Rose , Hobbick Chris , Nudelman Kelly N. , Hamer Jan , Wegel Claire , Faber Kelley M. , Jackson Jacqueline M , Foroud Tatiana M.
Published: January 2025

Background

Biorepositories play an integral role in the advancement of our understanding of neurodegenerative diseases and improving human health outcomes. Research efforts are accelerated when access to high‐quality clinical specimens is made available from a large, diverse participant group. Indiana University is home to three important neurodegenerative disease‐focused biorepositories including the NIA‐funded National Centralized Repository for Alzheimer’s Disease and Related Dementias (NCRAD), the NINDS‐funded Biospecimen Exchange for Neurological Disorders (BioSEND), and the Michael J. Fox Foundation (MJFF) biorepository. Having all three repositories in one location presents a unique opportunity to leverage common protocols and shared resources to provide researchers with access to a wide breadth of specimens, facilitating broad specimen sharing and standardization across studies and repositories.

Method

All three repositories provide exceptional data and study coordination, data management, scientific support, and technical resources. Uniform best practice standard operating procedures (SOPs) and materials for collection and processing of samples yield consistently high‐quality specimens across studies from all repositories. Banked specimen types include DNA, RNA, whole blood, plasma, serum, cerebrospinal fluid, urine, stool, brain tissue, peripheral blood mononuclear cells (PBMCs), fibroblasts, and induced pluripotent stem cells (iPSCs). Online catalogs are available for specimen selection along with project management that can assist in the selection and approval of specimens across studies and repositories.

Result

Among the three repositories, over 4 million specimen aliquots from more than 150 studies have been banked. This collection represents over 142,000 unique participants across a diverse array of neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, Amyotrophic Lateral Sclerosis, Frontotemporal Dementia, Lewy Body Dementia, Concussion, Traumatic Brain Injury, Huntington’s Disease, Spinocerebellar Ataxia and other neurodegenerative proteinopathies. More than 600,000 specimen aliquots have been distributed to over 370 investigators, resulting in almost 1,000 publications.

Conclusion

NCRAD, BioSEND, and MJFF serve as crucial resources for investigators requiring high‐quality clinical specimens collected and processed in accordance with best practice SOPs. The centralized location at Indiana University provides the opportunity to synergize and align common study objectives to provide shared resources with broader sample diversity, increased statistical power, improved reproducibility, and enhanced opportunities for broad specimen sharing, thereby fostering collaborative research initiatives.
Using Inflammatory Plasma Biomarkers to Predict Preclinical Alzheimer’s Disease
Authors: Leclerc Haley , Alber Jessica , Kunicki Zachary J. , O'Bryant Sid E. , Lee Athene KW
Published: January 2025

Background

Plasma biomarkers have recently emerged to detect symptomatic Alzheimer Disease (AD), but have yet to be validated in preclinical AD populations, where Aβ accumulates in the brain but older adults are cognitively unimpaired (CU). In addition to AD pathologic plasma biomarkers (amyloid and tau), inflammatory markers can accurately detect symptomatic AD. We used pathologic and inflammatory plasma biomarkers to predict amyloid PET status in CU older adults.

Method

Participants were 125 CU older adults (mean age = 68) from the Butler Hospital Alzheimer’s Prevention Registry who completed amyloid PET through a separate research study. Blood samples were collected and analyzed for the following: an inflammatory panel consisting of 21 proteins, Aβ40, Aβ42, tau (total), p‐tau181, p‐tau 231, p‐tau217, GFAP and NfL. Multiple regression was used to evaluate the best predictors of amyloid PET status (positive vs. negative) in CU older adults. Model 1 included predictors age, education, and gender. Model 2 and 3 added predictors APOE status, Aβ42/40 ratio and p‐tau181 respectively. Random forest (RF) modeling was used to establish the five proteomic markers that best predicted amyloid PET status, and these markers were added in Model 4.

Result

We tested RF models that included all 21 inflammatory proteins, as well as the top 10, 8 and 5 inflammatory proteins. Models were compared based on sensitivity, specificity, PPV, NPV, and AUC. The model including the top 5 inflammatory proteins (CRP, SAA, sVCAM1, TNFα, and TARC) was the best fit with sensitivity of .88, specificity of .31, PPV of .71, NPV of .57 and AUC of .63. Multiple regression analysis showed that the best model for predicting amyloid PET positivity included age, years of education, gender, APOE E4 status, Aβ42/40 ratio and p‐tau181(p<.01). Adding the top 5 proteomic markers did not significantly improve the model.

Conclusion

Results revealed that the proteomic inflammatory markers in plasma did not add predictive value to standard AD pathologic plasma biomarkers in predicting amyloid PET positivity in CU older adults. This may reflect that the changes associated with inflammatory biomarkers occur later downstream in the pathogenesis and disease progression of AD.