bluuebunny/crossref_metadata_2025 huggingface dataset:
Proteomics analysis characterizing new markers related to Aβ plaques and tau tangles pathologies
Authors: Binette Alexa Pichet , Wennström Malin , Strandberg Olof , Mathys Hansruedi , Tsai Li‐Huei , Mattsson‐Carlgren Niklas , Stomrud Erik , Janelidze Shorena , Vogel Jacob W. , Hansson Oskar
Published: January 2025

Background

Several studies have recently emerged describing relationships between cerebrospinal fluid (CSF) proteins and beta‐amyloid (Aβ) and tau pathology. While these studies have primarily characterized Alzheimer’s disease (AD) proteinopathies using CSF markers, positron emission tomography (PET) more accurately captures these pathologies, especially fibrillar tau pathology. Our objective was to identify the main proteins strongly associated with AD pathology measured by PET, and to further investigate their cellular role using postmortem transcriptomics and immunohistochemistry.

Method

We included 604 BioFINDER‐2 participants with CSF measurements of proteins (Olink Explore3072) at baseline, and Aβ‐PET and tau‐PET at baseline and longitudinally. We fitted linear regressions between protein levels as outcome and (1) global Aβ‐PET and temporal meta‐ROI tau‐PET SUVR or (2) their rate of change as independent variables. Enrichment analyses were performed to characterize biological processes related to the set of significant proteins. Single‐nuclei sequencing datasets were used to investigate cell‐type specificity and differential gene expression of the main proteins in relation to AD pathology.

Result

Analyses were restricted to 127 differentially abundant proteins that we previously identified as related to AD (manuscript in revision). ITGAM and SMOC1 showed the strongest associations with Aβ‐PET load, with SMOC1 being the only protein showing an association in Aβ‐positive participants only (Figure 1a). SMOC1 was mainly expressed in oligodendrocyte precursor cells (OPCs), and ITGAM in microglia (Figure 1b). In a large single‐nuclei human dataset, SMOC1 gene expression was increased with greater AD pathology primarily in OPCs (Figure 2), and immunohistochemistry revealed accumulation in Aβ plaques (Figure 3). Higher baseline tau‐PET and greater longitudinal change were associated with a set of 15 proteins, particularly in Aβ‐positive participants (Figure 1a). Such tau‐related proteins were mainly expressed in neurons (Figure 1b) and enriched for two terms associated with glycolysis, from which the key contributing genes were ENO1, ENO2 and GPI. In single‐nuclei sequencing data, ENO1 and ENO2 gene expression were increased with greater tau tangle pathology primarily in neurons (Figure 2).

Conclusion

Through comprehensive proteomics analysis of CSF proteins recently found to be associated with AD, we identified differential associations with Aβ plaques and tau tangles, and further corroborated such findings in postmortem data.
The effects of the novel phosphodiesterase 9 (pde9) inhibitor E2027 (irsenontrine) on CSF proteomics profile in amyloid positive and amyloid negative Lewy Body Dementia
Authors: Vermunt Lisa ,   Sjors G.J.G. in ’t Veld, Koel‐Simmerlink Marleen JA , Ye Yuanqing , Saxena Satya , Irizarry Michael C. , Sachdev Pallavi , Teunissen Charlotte
Published: January 2025

Background

Irsenontrine (e2027) is a potent and selective PDE9 inhibitor that increases cellular cGMP which is important for glutamatergic synaptic function. Irsenontrine was investigated to improve cognition in Lewy Body Dementia (LBD; DLB and PDD), and recent phase 2 study data suggests that irsenontrine could be more effective in DLB patients without amyloid copathology. Here, we evaluated differential change from baseline levels in proteins associated with cGMP pathway in DLB participants without amyloid co‐pathology (DLB A‐) compared to DLB participants with amyloid co‐pathology (DLB A+). We next evaluated the affected biological pathways.

Method

We employed proximity extension analysis (PEA) proteomics in all available paired pre‐ and post‐treatment CSF samples of a translational medicine trial of E2027 (Figure 1A). This set included six DLB A‐ patients (CSF Lumipulse Ab42/40 cut‐off 0.057) and nine DLB CSF A+ patients with a mean±sd age of 76±6 years and 67% male. We assessed the treatment effect per DLB group by paired Wilcoxon tests of pre‐ vs post‐treatment (1) protein levels (p<0.05) and (2) individual pathway enrichment z‐scores based on 189 KEGG pathways (p<0.05).

Result

Following E2027 treatment, CSF protein changes were apparent in both groups (DLB A‐ 10 proteins increased, and 32 decreased; DLB A+ 16 proteins increased, and 27 decreased; Figure 1B/C). We found that more pathways were affected in DLB A‐ (5 pathways), compared to DLB A+ (3 pathways), and several of these were related to the mechanism of action, including an increase in Pantothenate and CoA biosynthesis z‐scores in both groups, and lower GABAergic synapse in DLB A‐ only (Figure 1D/E).

Conclusion

This global proteomics analyses in DLB clinical trial samples presents that, despite the small number of participants treated with E2027, there were changes in proteins related to the mechanism of action, as indicated by Pantothenate and CoA biosynthesis increase, which amongst others factors related to glutamate metabolism. In addition, multiple proteins and pathways were differentially affected between the DLB A‐ and A+ group, which could lead to improved understanding of differential clinical treatment response in DLB patients.
Longitudinal posterior‐medial functional connectivity changes with age and Alzheimer’s pathology are differentially related to memory performance depending on APOE genotype
Authors: Fischer Larissa , Molloy Eóin N. , Adams Jenna N. , Tremblay‐Mercier Jennifer , Remz Jordana , Binette Alexa Pichet , Villeneuve Sylvia , Maass Anne ,   PREVENT‐AD Research Group
Published: January 2025

Background

The posterior‐medial network is crucial for episodic memory. However, the medial temporal lobe (MTL) and posteromedial cortex (PMC) regions are vulnerable to aging and early Alzheimer’s disease (AD). Both processes might elicit distinct early functional connectivity (FC) changes which could be detrimental or protective/ compensatory regarding cognition. However, this is not well understood. We hypothesized that resting‐state FC strength between key regions (Figure 1a) would decrease with age and memory decline without AD pathology (A‐T‐) but increase with early AD pathology.

Method

We analysed longitudinal 3‐Tesla resting‐state fMRI data from cognitively unimpaired older adults (OA; PREVENT‐AD cohort). We assessed FC at baseline and after 24 months (FU24) in i) CSF or PET Aβ‐ and tau‐negative OA (A‐T‐, N=96, 63±5years, 70 female, 28 APOE4) and ii) Aβ and p‐tau CSF‐characterized OA with available longitudinal p‐tau181/Aβ1‐42 ratio (N=65, 63±5years, 45 female, 22 APOE4). First, we investigated effects of age, APOE genotype and p‐tau181/Aβ1‐42 ratio on FC controlling for sex and education. Second, we tested the association between baseline FC or change in FC and change in delayed memory recall in multiple regression analyses.

Result

In A‐T‐ OA, FC decreased mainly between regions within the PMC subnetwork over 24 months (Figure 1b). Higher baseline FCwithin‐PMC was related to increasing memory performance over time (p = 0.047; Figure 2a). Longitudinally, increasing FCMTL‐mPFC was associated with increasing memory in APOE4 non‐carriers and decreasing memory in APOE4 carriers (p = 0.016; Figure 2b). In CSF‐characterized OA, p‐tau181/Aβ1‐42 ratio at baseline and FU24 was related to increasing FCMTL‐PMC over time (Figure 3a). Higher baseline FCMTL‐PMC was associated with longitudinally increasing memory in APOE4 non‐carriers and decreasing memory in APOE4 carriers (p = 0.028; Figure 3b).

Conclusion

Our results provide novel longitudinal evidence incorporating age, APOE, Aβ and tau indicating specific memory‐related FC changes in cognitively unimpaired OA. APOE moderated the effects of FC strength on change in episodic memory performance. Higher FCMTL‐PMC and increasing FCMTL‐mPFC seem to be detrimental in APOE4 carriers but beneficial in APOE4 non‐carriers. Importantly, this effect was observed in A‐T‐ OA, hinting that APOE genotype may affect FC earlier than AD‐related pathology.
Prevalence of cerebrospinal fluid AT biomarker profiles according to APOE genotype and across age in persons without dementia
Authors: van der Velden Jolien , Vos Stephanie J. B. , Tijms Betty M. , Oomens Julie Elisabeth , Maserejian Nancy N , Visser Pieter Jelle , Jansen Willemijn J. ,   Amyloid Biomarker Study Group
Published: January 2025

Background

Amyloid‐b deposition and tau tangle formation are the key pathologies of Alzheimer’s disease (AD). The presence of these pathologies in cerebrospinal fluid (CSF) biomarkers is used for a biological diagnosis of AD. It remains unclear how the prevalence of AT biomarker profiles depends on apolipoprotein E (APOE) genotype. A better understanding of the AT biomarker profiles across APOE genotypes and age in the pre‐dementia stages will help inform strategies to prevent or delay AD progression in those with different APOE genotypes.

Methods

Participants with normal cognition (NC; n = 4356) or mild cognitive impairment (MCI; n = 3997) were selected from 45 studies that participated in the Amyloid Biomarker Study based on availability of data on age, CSF amyloid‐b42 (A), CSF phosphorylated tau 181 (T), and APOE genotype (e2e2, e2e3, e2e4, e3e3, e3e4, e4e4). Based on (ab)normal values for A (data‐driven) and T (center‐specific cutoffs) participants were placed into one of four AT biomarker profiles: A‐T‐, A+T‐, A‐T+, or A+T+. A Markov‐Chain‐Monte‐Carlo generalized linear mixed model was performed separately for NC and MCI to evaluate the association of AT profile frequency with age and APOE genotype. Center was included as random effect.

Results

The NC and MCI groups had an average age of 65.1 years (SD = 10.8; 59% female) and 69.3 years (SD = 8.4; 48% female) respectively. Most participants had APOE e3e3 genotype (NC 56%, MCI 45%; Table 1). In both groups, the association of AT profiles with APOE genotype changed across age (both p < .001; Figure 1), except for participants with NC and APOE e2e2 genotype. For NC with APOE e2e3 and e3e3 genotypes, A‐T+ was more frequent in older age than A+T‐ or A+T+. In APOE e3e4 and e4e4 genotypes A+T‐ frequency plateaued around 65 years of age, while A+T+ frequency strongly increased. For MCI, A+T+ was most frequent with aging across APOE e2e4, e3e3, e3e4, and e4e4 genotypes.

Conclusion

Frequencies of AT biomarker profiles changed substantially across APOE genotypes and age in NC and MCI. Studies recruiting participants based on AT biomarker profiles should take age and APOE genotype into account.
Bitter effect of a Sweet Disease‐ Exploring Cognitive dysfunction in Prediabetes from an Aging cohort
Authors: Issac Thomas Gregor , G Sandhya , Menon Anjana J , Diwakar Latha , Sundarakumar Jonas S.
Published: January 2025

Background

India is unfortunately the “Diabetes Capital” of the world with estimated 101 million and 136 million patients suffering from diabetes and prediabetes respectively. Prediabetes is a transition state between euglycemia and diabetes. Although diabetes is associated with cognitive decline, studies that link prediabetes and cognition have been scarce and inconclusive especially from the Low and Middle Income (LMIC) countries. Therefore, the current study attempts to explore the relationship between prediabetes and cognition.

Methods

531 participants aged ≥ 45 years, recruited by CBR‐TLSA (Tata Longitudinal Study of Ageing) were included in this study. Glycosylated Haemoglobin (HbA1c) levels was utilized to categorise the participants into healthy, prediabetes and diabetes based on the American Diabetes Association (ADA), 2017 criteria. Among these participants, 65 were healthy and 234 were prediabetic. The remaining 232 participants with Diabetes were excluded and directed towards appropriate care pathways. The COGNITO (Computerized Assessment of Adult Information Processing) neuropsychological test battery was utilized to assess the cognitive functioning. Generalized Linear Model (GLM) was performed between prediabetes status and cognition after adjusting for confounding variables.

Results

The estimated prevalence of prediabetes in our elderly cohort is 44%. After adjusting for ApoE status, GLM analysis revealed that healthy participants performed better in semantic association (B = 0.314, 95% CI (0.047, 0.582), p = 0.021) and name‐face recognition (B = 1.644, 95% CI (0.516, 2.77), p = 0.004) tasks when compared to prediabetics. Subsequently, after adjusting for age, gender, years of education and ApoE status, it was observed that the scores of semantic association (B = 0.290, 95% CI (0.025, 0.556), p = 0.032) and name‐face recognition (B = 1.390, 95% CI (0.260, 2.520), p = 0.016) tasks were higher among healthy participants.

Conclusion

This study emphasizes the deleterious effect of a potentially modifiable risk factor like prediabetes. Participants with prediabetes performed poorer in memory and language related cognitive tasks. If diagnosed early, interventions aimed at improving prediabetes could potentially prevent or delay the progression to both minor and major neurocognitive disorders.
Longer leukocyte telomere length is associated with lower markers of early Alzheimer's disease pathology, astrocytic reactivity, and synaptic dysfunction
Authors: Rodríguez‐Fernández Blanca , Escalante Armand González , Genius Patricia , Ortiz‐Romero Paula , Brinkmalm Ann , Minguillón Carolina , Kollmorgen Gwendlyn , Quijano‐Rubio Clara , Ashton Nicholas J. , Zetterberg Henrik , Blennow Kaj , Gispert Juan Domingo , Navarro Arcadi , Suarez‐Calvet Marc , Crous‐Bou Marta , Vilor‐Tejedor Natalia ,   for the ALFA study
Published: January 2025

Background

Leukocyte telomere length (LTL) serves as a proxy for tissue‐specific TL and peripheral immune aging. Its association with aging‐related brain endophenotypes, cognitive functioning, and Alzheimer's disease (AD) risk is established, but the underlying molecular mechanisms remain elusive. Investigating LTL's association with AD biomarkers is crucial for identifying its role in brain resilience and disease progression.

Method

We included middle‐aged adults at risk of AD dementia from the ALFA+ study. In CSF, we measured Aβ42, Aβ40, NfL, GFAP, α‐synuclein, neurogranin, S100B, sTREM2, YKL40, and IL6 using the exploratory Roche NeuroToolKit robust prototype assays; p‐tau181 was measured using Elecsys®; GAP‐43 using an in‐house ELISA; and Synaptotagmin‐1 using mass spectrometry. In plasma, we measured Aβ42, Aβ40, p‐tau231, NfL, and GFAP using Simoa. LTL was determined by qPCR from DNA extracted from peripheral blood leukocytes. Multiple linear regression models were used to evaluate the association between LTL and both baseline and the change in CSF and plasma biomarker levels over a three‐year period. Models accounted for age, sex and APOE‐ε4 status, and time between measurements, when interrogating the change in biomarkers. Sensitivity analyses included models adjusted by CSF Aβ42/40, CSF p‐tau181. Sex‐, APOE‐ε4 and disease‐specific effects were explored through interaction and stratified models.

Result

In plasma, longer LTL was associated with lower plasma p‐tau231 at baseline [Figure 1A]. This association was mainly driven by women [Figure 1B]. In CSF, longer LTL was associated with reduced S100B at baseline [Figure 2A] and decreased α‐synuclein over time [Figure 2B], independently of CSF Aβ42/40 and p‐tau181 levels. Over time, longer LTL was associated with increasing CSF IL6 levels among A+T‐ individuals, while the opposite direction was observed among A+T+ individuals [Figure 3A‐3B].

Conclusion

Longer LTL was associated with lower plasma p‐tau231, an early marker of AD pathology, specifically in women. Furthermore, longer LTL was independently associated with lower biomarkers of astrocytic and synaptic dysfunction, regardless of AD pathology. Nevertheless, an AT‐dependent shift in LTL's impact on CSF IL6 change emerged over time. These results collectively propose that peripheral immune aging could be related to the central nervous system along the AD continuum, either independently or in a sex‐ and disease‐specific manner.
White‐matter myelin is reduced in monogenic small vessel disease and MCI: evidence from MRI source separation
Authors: Denecke Jannis , Dewenter Anna , Lee Jongho , Pirpamer Lukas , Franzmeier Nicolai , Gesierich Benno , Duering Marco , Ewers Michael
Published: January 2025

Background

The myelin sheath around axons is of fundamental importance for signal transduction. Myelin is reduced in white matter hyperintensities (WMH), which occur in both small vessel disease (SVD) and Alzheimer’s disease (AD), giving rise to the question to what extent myelin is reduced in these diseases. Here, we employed an advanced MRI based method to assess myelin independently from a major confounding factor, i.e. iron‐related signal, in monogenic small vessel disease (i.e. CADASIL) and in mild cognitive impairment (MCI) & AD dementia.

Methods

We included 62 CADASIL subjects, 11 with MCI or AD dementia, and 22 elderly controls (HC). Using 3D‐T2‐star‐weighted multi‐echo gradient‐echo MRI, we performed susceptibility source separation of diamagnetic (|χ‐negative|, e.g. myelin) and paramagnetic (χ‐positive, e.g. iron) sources (Shin et al., 2021). Mean diffusivity (MD) was calculated from diffusion tensor imaging. We extracted |χ‐negative| and MD values within WMH, normal appearing white matter (NAWM), and two ROIs including the left anterior thalamic radiation and forceps minor (genu) of the corpus callosum, i.e. two strategic tracts for processing speed. Subject‐level difference‐scores between CADASIL or MCI/dementia patients and group‐averaged HC were derived as abnormality scores. Voxel‐based WMH frequencies were mapped for each group. Group differences in |χ‐negative| and MD values were tested using linear regressions, controlled for χ‐positive scores, age, sex, and education.

Results

Voxel‐wise proportions of WMH are mapped for each group in Figure 1. For CADASIL, |χ‐negative| values were decreased, and MD values increased in each ROI compared to the HC group, with intermediate values for the MCI/dementia group (Figure 2 A&B). Worse |χ‐negative| and MD alterations were observed in WMH compared to NAWM (Figure 2 C‐F) in each disease group. Lower |χ‐negative| values were associated with higher MD in WMH (r=‐0.57, Figure 3) and NAWM (r=‐0.56).

Conclusion

|χ‐negative| values showed a marked decrease in WMH of CADASIL patients, suggesting myelin loss in SVD, with less pronounced myelin reduction present in MCI/AD. |χ‐negative| values were only moderately associated with MD, suggesting that each provides complimentary information. Our results encourage future studies to test the cognitive consequences of myelin loss in SVD and MCI.
Integrated Proteomic Analysis of Alzheimer and Mild Cognitive Impairment in Biofluid using Mass Spectrometry and NULISATM Technology
Authors: Chen Yao , Wesseling Hendrik , Levit Mikhail , Zhang Bailin
Published: January 2025

Background

One hypothesis of lack of effectiveness in most current clinical trials for the AD (Alzheimer’s disease) is the advanced stages of the disease at the time of pharmacological intervention. To aim a robust effect from disease‐modifying therapies, there is an urgent need for biomarkers that can identify patients with MCI and early stages of AD. In this study, we combined in‐house large‐scale LC‐MS and new emerging highly sensitive NULISA proteomics analysis on a medium sized AD cohort sample, aiming an early‐stage protein biomarker discovery in MCI and AD.

Method

59 AD set plasma and 65 AD set CSF were purchased from the vendor. Donor classification strictly followed the disease inclusion/exclusion criteria. One aliquot from each sample were sent to Alamar Bioscience for NULISAseq analysis on ARGOTM system using 120‐plex CNS disease panel. In house LC‐MS was performed on the same set of samples.

Result

Of 59 AD set plasma samples (19 HC, 22 MCI AND 18 AD), 3 significantly up‐regulated protein in MCI and 16 significantly down‐regulated protein in AD and MCI were identified by NULISAseq 120plex CNS panel. One significantly up‐regulated protein in MCI and 3 significantly down‐regulated proteins in AD were also confirmed by in house LC‐MS. Of 65 AD set CSF samples (19 HC, 22 MCI and 24 AD), 12 significantly up‐regulated proteins and 11 significant down‐regulated protein in AD and MCI were identified by NULISAseq 120plex CNS panel. CSF protein profiling by in house LC‐MS is still pending. 5 (3 from plasma, and 2 from CSF) significantly up‐regulated novel proteins in MCI and CD have been reported to be associated with neuronal connectivity, neuro inflammation or acting as a neuromodulator. Sample correlation in CSF between NULISAseq and Simoa (Single Molecule Array) was also verified by NFL and pTau181. Both proteins displayed excellent correlation (R2 was 0.88 and 0.92).

Conclusion

5 novel significantly upregulated protein biomarkers in MCI and AD were identified by combined in house MS and new emerging NULISAseq technologies. The integrated proteomic method could be a powerful tool to identify the molecular signature and pathological pathways associated with AD and MCI.
Plasma biomarkers discrimination accuracy of biologically defined Alzheimer’s disease in a memory clinic setting
Authors: Anastasi Federica , Puig‐Pijoan Albert , Ashton Nicholas J. , Ortiz‐Romero Paula , Jiménez‐Moyano Esther , Torres‐Torronteras Javier , Escalante Armand González , Milà‐Alomà Marta , Contador José , Fernández‐Lebrero Aida , Garcia‐Escobar Greta , Bastard Nathalie Le , Nadal Alicia , Sahajan Aparna , Hao Qinyu , Zhang Bingqing , Grau‐Rivera Oriol , Zetterberg Henrik , del Campo Marta , Blennow Kaj , Suárez‐Calvet Marc
Published: January 2025

Background

Blood‐based biomarkers offer a non‐invasive and cost‐effective means for Alzheimer's disease (AD) detection. In this study, we performed a direct comparison of these novel biomarkers in a memory clinic population to facilitate their implementation into clinical practice.

Method

We included a total of 208 patients with cognitive complaints from the BIODEGMAR cohort at Hospital del Mar (Barcelona, Spain). CSF was used as standard‐of‐truth and patients were categorized as having an AD CSF profile with two approaches: Lumipulse CSF Aβ42/p‐tau181<10.25 (N=208) or Elecsys® p‐tau181/Aβ42>0.022 (N=157). The following biomarkers were measured in paired plasma and CSF samples: Aβ42 and p‐tau181 (Lumipulse CSF, plasma, Fujirebio), Aβ42 and p‐tau181 (NeuroToolKit (NTK) a panel of robust prototype assays (Roche Diagnostics International Ltd), and p‐tau181, p‐tau217, p‐tau231 and MAP‐T (NULISA, Alamar). P‐value and effect size of the group comparison (AD vs non‐AD CSF profiles) were calculated using a Mann‐Whitney U test. ROC curve analysis evaluated plasma biomarkers accuracy to discriminate AD from non‐AD CSF profiles. Spearman test was used to assess the correlation between plasma and CSF biomarkers.

Result

Demographic information of the study cohort is reported in Table 1 for both classification thresholds. All plasma biomarkers were significantly different between the AD and non‐AD CSF profile groups, but the effect size varied among them. Specifically, NULISA p‐tau217, Lumipulse p‐tau181 and NULISA p‐tau231 reported the greatest effect sizes for the Lumipulse threshold and NULISA p‐tau217, NTK p‐tau181, Lumipulse p‐tau181 and NULISA p‐tau231 reported the greatest effect sizes for the Elecsys® threshold (Table 1). ROC curve analysis performed consistently over the two thresholds with the following discrimination accuracy (AUC) values (from highest to lowest): NULISA p‐tau217, NTK p‐tau181, NULISA p‐tau231, Lumipulse p‐tau181, NULISA p‐tau181 (Figure 1). In comparison to the p‐tau assays, Aβ42 reported modest effect size and AUCs. NULISA p‐tau217 and NULISA p‐tau231 had the highest correlation between plasma and CSF (Spearman ρ=0.75 and ρ=0.60, respectively, with both FDR corrected p‐values<0.001), Figure 2.

Conclusion

In a memory clinic population, various plasma Aβ and tau plasma biomarkers, targeting different epitope and using different platforms, demonstrated high performance in distinguishing patients with biologically defined AD from those without.
A Large Public Release of Clinical and Imaging Data from the Mayo Clinic Study of Aging
Authors: Schwarz Christopher G. , Kremers Walter K. , Prakaashana Carl M. , Przybelski Scott A. , Christenson Luke R. , Wiliams Josie M. , Gunter Jeffrey L. , Senjem Matthew L. , Arani Arvin , Reid Robert I. , Machulda Mary M. , Fields Julie A. , Lowe Val J. , Kantarci Kejal , Graff‐Radford Jonathan , Vemuri Prashanthi , Petersen Ronald C. , Knopman David S. , Jack Clifford R.
Published: January 2025

Background

The Mayo Clinic Study of Aging (MCSA) is a longitudinal, population‐based study of residents of Olmsted County, Minnesota, USA. MCSA is releasing de‐identified clinical and imaging data on GAAIN.org to benefit the research community.

Method

We included longitudinal clinical data from all participants of the Mayo Clinic Study of Aging 30‐90 years of age (average 70.0y) through the first 15 years of the study. Clinical data includes age, sex, self‐reported race/ethnicity, APoE4 allele status, cognitive impairment status (normal, MCI, dementia, or other), height, weight, blood pressure, multi‐domain neuropsychological scores, neuroimaging summary measurements, medications, cardiovascular risk factors, social activity, sleep, mood/anxiety, functional measures, and more.

For our initial release of imaging data, we selected the first imaging timepoint acquired on 3T GE MRI scanners and amyloid (PiB) PET during the same visit, from all available imaging participants 50‐90 years of age (average 70.7y). Currently, we included 3D T1‐weighted (MPRAGE) MRI (1x1x1.2mm3), T2‐weighted FLAIR MRI (0.85x0.85x3.6mm3), diffusion MRI (2.7mm resolution with 41 directions at b=1000 and 5 b=0), and numeric cortical global SUVR and Centiloid values from PiB PET scans at 40‐60 minutes post‐injection. All images are released in DICOM format and thoroughly de‐identified using CTP while ensuring preservation of necessary fields for analyses. T1‐weighted and T2‐FLAIR MRI were also de‐faced (identifiable face imagery was removed and replaced with an average) using mri_reface version 0.3.3 to further protect participants’ privacy, and all de‐faced images were visually inspected by a trained data scientist for quality assurance.

Result

The first phase of our public data release includes clinical data from 5925 unique participants from the Mayo Clinic Study of Aging (MCSA), each ranging from 1‐12 visits at roughly 15‐month intervals, and three MRI sequences (T1‐w, T2‐w‐FLAIR, and diffusion) from 1802 unique participants. Demographic summaries are given in Table 1.

Conclusion

This large, richly characterized, de‐identified clinical and imaging dataset is available to the research community at https://www.gaaindata.org/partner/MCSA, and it is suitable for a wide range of research uses. Additional data will be released over time, including de‐faced amyloid PET images.
Multi‐ancestry genome‐wide association study of plasma glial fibrillary acidic protein (GFAP)
Authors: Fornage Myriam , Xia Rui , Almeida Marcio A , Bis Joshua C , Cui Biqi , de Rojas Itziar , Decarli Charles , Gudmundsdottir Valborg , Jian Xueqiu , Mishra Aniket , Mosley Thomas H. , Olivé Clàudia , Yang Qiong , Sanchez‐Juan Pascual , Blangero John , Debette Stéphanie , González Hector M , Gudnason Vilmundur , Launer Lenore J. , Psaty Bruce M. , Ruiz Agustin , Satizabal Claudia L , Seshadri Sudha
Published: January 2025

Background

Glial fibrillary acidic protein (GFAP) is an astrocytic cytoskeletal protein and a promising blood biomarker for Alzheimer's disease (AD) and other neurodegenerative diseases. To date, the genetic architecture of plasma GFAP has not been characterized. We conducted a multi‐ancestry meta‐analyses of genome‐wide association studies (GWAS) in diverse population‐based cohorts to identify genetic variants associated with plasma levels of GFAP and to investigate their implication for neurological diseases.

Methods

Circulating GFAP levels were assayed by ultrasensitive single molecule array (Simoa) immunoassay. We performed ancestry‐specific and ancestry‐combined meta‐analyses of GWAS in 17,028 individuals (mean age: 64.5 years; 60% women) of diverse ancestry (African (AA), N=1163; Hispanic (HA), N=7405; European (EA), N=8460) from 12 community‐based cohorts.

Results

In the combined sample, we identified 7 loci associated with plasma GFAP. These were located in or near genes encoding APOE, CAPN1, CAPN2, GFAP, TMEM106B, PPP1R3C, and LOC105375672. The strongest association was with the APOE4 variant rs429358 (P=2.6x10‐40). However, this association was heterogeneous by ancestry, with stronger effects in EA, weaker in HA, and no association in AA. Ancestry‐specific meta‐analyses identified additional loci, including ZFAND3 in EA (Figure 1) and CAPN2 in HA (Figure 2), which were not observed in the other ancestries. No locus reached genome‐wide significance in AA. Using fine‐mapping methods incorporating functional annotation, gene expression, and linkage disequilibrium, we further prioritized potential causal variants and genes at the identified loci and investigated their implication for major neurological diseases, including AD.

Conclusion

Our GWAS of plasma GFAP has identified multiple loci with ancestry‐specific or cross‐ancestry effects. Our multi‐ancestry, integrative approach extends knowledge about the biology of GFAP and its shared genetic architecture with neurological disease.
Comparing de‐facing software MiDeFace and mri_reface according to privacy protection and effects on downstream measurements
Authors: Schwarz Christopher G. , Prakaashana Carl M. , Kremers Walter K. , Gunter Jeffrey L. , Senjem Matthew L. , Vemuri Prashanthi , Kantarci Kejal , Graff‐Radford Jonathan , Knopman David S. , Petersen Ronald C. , Jack Clifford R. ,   The Alzheimer's Disease Neuroimaging Initiative
Published: January 2025

Background

Several programs are available for automatically “de‐facing” brain images. These are designed to prevent the potential use of face imagery to re‐identify research participants. Previous works have compared available software and mri_reface is frequently among the top methods. The “Minimally Invasive DeFacing of MRI images” (MiDeFace) program was more recently added to FreeSurfer, but minimal validation of MiDeFace has been published.

Method

We ran mri_reface 0.3.3 and MiDeFace 7.3.2 on two datasets: A) 207 participants with face photographs and 3D T1‐weighted and 3D T2‐weighted‐FLAIR MRI from the Mayo Clinic Study of Aging (all unimpaired, Siemens); and B) 300 participants from ADNI3 with 3D T1‐weighted MRI (50 unimpaired + 50 with clinical AD, from each of 3 vendors). For dataset A, we tested the rate at which Microsoft Azure face recognition matched each participant’s photographs with the correct MRI, comparing unmodified images, those from mri_reface, and those from MiDeFace. For dataset B, we compared measured regional brain volume and cortical thickness from original vs. de‐faced images with SPM12, FreeSurfer 7.4.1, and the FSL‐UK Biobank pipeline. For both datasets, images were visually rated to assess removal of the face and retention of brain tissue.

Result

Automated face recognition match rates were lower with mri_reface (17/207 8.2%) than with MiDeFace (24/207 11.6%), indicating stronger identity protection with mri_reface, but both were greatly reduced vs. unmodified images (203/207 98.1%). Example images with both programs are shown in Figure 1. From visual ratings (Table 1), rates of complete success (modification of the entire face while retaining the entire brain) were much higher with mri_reface, but the great majority of failures from MiDeFace were subtle and occurred in relatively less recognizable face regions. The effects of both programs on downstream imaging measurements (Figure 2) were small and very comparable, but MiDeFace was favored mildly for SPM12 and for FSL, while mri_reface was more favored for FreeSurfer.

Conclusion

Altogether, mri_reface more reliably removed the complete face, leading to smaller rates of potential re‐identification (8.2% vs 11.6%). Effects on downstream image measurements were small and comparable with both methods.
Spatial Pattern of Medial Temporal Lobe Cross‐Sectional and Longitudinal Structural Change in Cognitively Normal Individuals
Authors: Xie Long , Das Sandhitsu R. , Li Yue , Wisse Laura E.M. , McGrew Emily , Lyu Xueying , DiCalogero Michael , Shah Ujashi , Ilesanmi Ademola , Denning Amanda E , Brown Christopher D. , Cohen Jesse S , Sreepada Lasya P , Dong Mengjin , Sadeghpour Niyousha , Khandelwal Pulkit , Ittyerah Ranjit , Ravikumar Sadhana , Sadaghiani Shokufeh , Hrybouski Stanislau , de Flores Robin , Gibson Eli , Yushkevich Paul A. , Wolk David A
Published: January 2025

Background

The medial temporal lobe's (MTL) early involvement in tau pathology makes it a key focus in the development of preclinical Alzheimer’s disease (AD) biomarkers. ROI analyses in prior studies reported significant MTL structural differences in cognitively normal individuals with and without β‐amyloid (A+/‐CN). Pointwise analysis, offering spatial information of early neurodegeneration, has potential to pinpoint “signature regions” of pathological change, but has been underexplored in the MTL. This study employs a specialized pointwise analysis pipeline to examine the spatial pattern of MTL structural change in subgroups dichotomized by both β‐amyloid and tau status in a large cohort of CN individuals.

Methods

A dataset of 3036 CN (A‐/A+: 1270/1558, Table 1) individuals from ADNI, HABS, A4 and ABC were analyzed. We extracted MTL regional thickness maps from MRI using tailored pipelines, ASHS‐T1 and CRASHS. For participants with prospective longitudinal MRI (five years follow‐up), regional maps of longitudinal atrophy rate were extracted using SkelDBM. Subjects with cross‐sectional tau PET available (N=563) were further divided into A and T subgroups by tracer uptake. General linear modeling was performed on each surface point to investigate cross‐sectional and longitudinal MTL structural group differences (detailed in Figure 1) and their correlation with MTL tau burden in All/A+/A‐ CN. Age and sex were covariates and cluster‐level multiple comparison correction was performed.

Results

A+CN demonstrated a significantly faster atrophy rate than A‐CN across the whole MTL, primarily driven by A+T+CN individuals (Figure 1‐b). Notably, A‐T+CN showed significantly faster atrophy rate in the entorhinal cortex (ERC) and Brodmann area 35 (BA35), the earliest sites of tau pathology (Figure 1‐b, second column). Figure 2‐b displays an MTL‐wise significant correlation between atrophy rate and tau in All/A+/A‐ CN. In both analyses, cross‐sectional effects are consistently weaker than longitudinal ones, but have some significant clusters in ERC and BA35.

Conclusions

Pointwise analysis revealed extensive tau‐associated accelerated neurodegeneration in the MTL in preclinical AD. Furthermore, accelerated atrophy was observed in early Braak regions in A‐CN with evidence of tau pathology, potentially driven by primary age‐related tauopathy (PART). These pointwise longitudinal MTL measures provide sensitive measures that may allow for disease monitoring in preclinical AD.
Among older African Americans, high‐risk ABCA7‐80 allele carriers have lower medial temporal lobe dynamic network flexibility than APOE‐ε4 allele carriers
Authors: Budak Miray , Fausto Bernadette A. , Piaszczynska Wiktoria , White Payton G. , Gluck Mark A.
Published: January 2025

Background

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by amyloid plaques and neurofibrillary tangles which cause neurodegeneration and cognitive decline1. APOE‐ε4 is identified as the first common genetic risk factor with high penetrance in the early onset of AD3. ABCA7 (rs115550680) (ABCA7‐80) is associated with the development of late‐onset AD among African Americans2. The medial temporal lobe (MTL) is the first region that displays atrophy and neurofibrillary tangle involvement during AD4. However, the comparative influence of APOE‐ε4 and ABCA7‐80 on neural functions among African Americans is not yet known. The present study investigated the effect of APOE‐ε4 and ABCA7‐80 high‐risk alleles on the MTL dynamic network flexibility among cognitively unimpaired older African Americans.

Method

175 older, cognitively unimpaired African Americans drawn from the ongoing longitudinal study, Pathways to Healthy Aging in African Americans completed saliva collection for genotyping and underwent an MRI scan in a Siemens 3T Prisma scanner. AFNI and ANTs were used for dynamic functional MRI processing and analysis for MTL dynamic network flexibility. Gender, age, and education were used as covariates for analysis.

Result

The analysis revealed trend‐level differences in MTL Dynamic network flexibility between high‐risk and non‐risk allele carriers for ABCA7‐80 (F = 3.531, η² = 0.025, p = 0.062) and for APOE‐ε4 allele (F = 2.421, η² = 0.017, p = 0.122). Individuals with the ABCA7‐80 high‐risk allele exhibited significantly lower MTL dynamic network flexibility compared to those with the APOE‐ε4 allele (F = 4.577, η² = 0.067, p = 0.036).

Conclusion

ABCA7‐80 high‐risk allele may better capture the dynamic neural dysfunction in the MTL network rather than APOE‐ε4 among cognitively unimpaired older African Americans.
Association of CSF Proteome with CSF P‐tau181 levels and other biomarkers of Alzheimer's Disease
Authors: Qiao Min N , Rookyard Alex N , Das Lipi N , Zerlin‐Esteves Marielba , Reyes‐Dumeyer Dolly , Lee Annie J. , Lantigua Rafael A. , Medrano Martin , Mejia Diones Rivera , Honig Lawrence S. , Brown Lewis M , Mayeux Richard , Vardarajan Badri N.
Published: January 2025

Background

We investigated the relationship between the cerebrospinal fluid (CSF) proteome in Alzheimer’s disease (AD) and the clinical and biomarker‐assisted diagnoses.

Methods

CSF was collected in 500 individuals of non‐Hispanic white, African Americans, and Caribbean Hispanic individuals from Dominican Republic and New York City. CSF biomarkers of AD were measured including P‐tau181, Aβ40, Aβ42, total‐tau, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP). CSF was depleted of abundant proteins followed by precipitation, cysteine reduction/alkylation, and proteolytic cleavage by trypsin. Peptides were measured using a Q Exactive HF mass spectrometer (Thermo Scientific). Association of individual and co‐abundant modules of proteins were tested with the clinical diagnosis of AD, as well as biologically defined AD pathological process based on CSF P‐tau181 and other biomarker levels.

Results

We detected 1030 protein groups (with at least one peptide per protein), yielding an overall data completeness value of 97%. CSF levels of 41 proteins were significantly associated with P‐tau181 levels after multiple testing correction. Notably, phospholipase D3 (PLD3, p=2.41E‐09), APOE (p=4.25e‐08) and osteopontin (OSTP, p=1.4E‐16) were increased and ceruloplasmin (CERU, p=2.72E‐07) decreased among individuals with high P‐tau181 levels. These proteins were also associated with CSF Aβ42/Aβ40 ratio and total Tau levels but not with NfL. OSTP was also associated with CSF levels of GFAP (p=1.32e‐05). We did not identify any protein association with clinical AD. Among proteins associated with P‐tau181 levels, pathways related to axon development (p=2.4E‐12), axonogenesis (p=1.45E‐11) and regulation of axonogenesis (p=5.1E‐09) were enriched.

Conclusion

Unbiased profiling of circulating CSF proteins identified key proteins associated with β‐amyloid and phosphorylated tau pathology. Biologically based diagnostic criteria may aid in the identification of unique pathogenic mechanisms.
Longitudinal neurodegeneration in Early‐Onset Alzheimer’s Disease: A summary of MRI‐derived atrophy in LEADS
Authors: Touroutoglou Alexandra , Katsumi Yuta , Eckbo Ryan , Brickhouse Michael , 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

Prior work has advanced our understanding of cortical atrophy in early‐onset Alzheimer’s disease (EOAD), but longitudinal data are sparse. Current longitudinal MRI studies point to progressive atrophy in cerebral cortex exhibiting a posterior‐to‐anterior gradient, but these studies include small samples with mostly amnestic EOAD. Here, we analyzed a large sample of sporadic EOAD patients from the Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS) to test the central hypothesis that areas in our recently described EOAD signature (Touroutoglou et al., 2023) affected at baseline in the posterior lateral temporal cortex, inferior parietal lobule, and PCC/precuneus will continue to degenerate and additional longitudinal atrophy will be found in the medial temporal lobe and frontal regions as cognitive decline progresses over time in multiple domains.

Method

We investigated longitudinal changes in cortical thickness by analyzing structural MRI data collected from 367 patients with EOAD and 99 cognitively unimpaired (CN) older adults, totaling 839 MRI scans across the cohorts with up to 4 years of follow‐up. MRI data were longitudinally processed in FreeSurfer 6.0. Linear mixed effects models were constructed to estimate the rate of cortical atrophy with random intercepts and slopes for individual participants while controlling for baseline age and sex.

Result

EOAD patients exhibited cortical atrophy at a faster rate than controls in widespread areas of the cerebral cortex. As expected, the regions exhibiting accelerated longitudinal atrophy included not only the EOAD signature regions as a whole (EOAD: ‐0.052±0.002 mm/year vs. CN: 0.0001±0.002 mm/year; Dslopes = ‐0.052, p<.001), but also those that were minimally atrophied at baseline, such as superior frontal gyrus (EOAD: ‐0.052+/‐0.004 vs. CN: ‐0.001+/‐0.004, Dslopes = ‐ 0.051, p<.001) and medial temporal lobe (EOAD: ‐0.083±0.005 mm/year vs. CN: 0.001±0.006 mm/year; Dslopes = ‐0.082, p<.001). We observed no difference in the rate of atrophy in the calcarine fissure (a control region not expected to change; Dslopes = ‐0.002, p£.69).

Conclusion

Our findings show that neurodegeneration in EOAD accelerates over time in the EOAD signature regions and spreads to additional areas within large‐scale brain networks (consistent with those observed in late‐onset AD) contributing to the worsening of symptoms over time.
Older African Americans with the ABCA7‐80 high‐risk genotype have diminished slow oscillation power during non‐REM sleep
Authors: White Payton G. , Budak Miray , Arnasalam Alyssa , Sheikh Mustafa , Fausto Bernadette A. , Gluck Mark A.
Published: January 2025

Background

African Americans are among the most vulnerable demographic groups to both sleep deficiencies and Alzheimer’s disease (AD)3. ABCA7‐80 (rs115550680) known as adenosine triphosphate (ATP)‐binding cassette member 7, plays a role in the transport of amyloid precursor protein, clearance of cellular Aβ, and lipid metabolism: three processes associated with late‐onset AD2. Slow oscillations, which characterize non‐REM sleep, are implicated in waste clearance and memory consolidation in the brain1. The present study investigated the putative association between ABCA7‐80 risk on non‐REM slow wave oscillations among cognitively unimpaired older African Americans.

Method

Participants were drawn from the ongoing longitudinal study, Pathways to Healthy Aging in African Americans conducted at Rutgers University–Newark. 75 participants, ages 60‐87 years old completed a saliva test for genotyping and underwent at‐home sleep monitoring over two nights using the DREEM 3 Headband. MANCOVA statistical analysis was performed on the sample data.

Result

Individuals with the ABCA7‐80 high‐risk allele, had significantly lower frontal slow oscillation relative power than individuals with the non‐risk allele (F= 2.175, η 2= 0.137, p= 0.084).

Conclusion

This preliminary data shows that individuals who have the ABCA7‐80 high‐risk genotype may have lower slow oscillation relative power. This holds importance for AD in African Americans as there is evidence that ABCA7‐80 is more relevant for cognitively unimpaired older African Americans.
Elevated plasma p‐tau levels may be linked to reduced sleep spindles among older African Americans
Authors: White Payton G. , Budak Miray , Arnasalam Alyssa , Sheikh Mustafa , Fausto Bernadette A. , Fitzgerald‐Bocarsly Patricia , Tawe Fanyu Hercules , Ashton Nicholas J. , Blennow Kaj , Zetterberg Henrik , Gluck Mark A.
Published: January 2025

Background

Biomarkers, such as blood p‐tau181, p‐tau217, and p‐tau231, have been created and verified to mirror the pathophysiology of tau and amyloid‐β (Aβ) in the brain 2. Sleep spindles are known to contribute to memory consolidation and generalization and may therefore be a promising biomarker in preclinical Alzheimer’s Disease (AD) 3,4,5. The present study investigated the relationship between sleep spindles and p‐tau levels in cognitively healthy older African Americans.

Method

Participants were drawn from the ongoing longitudinal study, Pathways to Healthy Aging in African Americans conducted at Rutgers University–Newark. 75 participants, ages 60‐87 years old (completed a blood draw and underwent at‐home sleep monitoring over two nights using the DREEM 3 Headband. Plasma was extracted from blood samples to assess p‐tau 231 levels using Single molecule array technology, measured by in‐house Simoa methods at the University of Gothenburg. Based on the sample median thresholds, a subset of participants were characterized as having higher p‐tau231 levels (> 8.9447 pg/mL).

Result

Individuals with high levels of p‐tau 231 (> 8.9447 pg/mL) had significantly lower frontal sleep spindle relative power than individuals with lower p‐tau 231 levels (< 8.9447 pg/mL) (F= 1.110, η 2= 0.175, p= 0.378).

Conclusion

Sleep spindle relative power may serve as a potential marker for p‐tau231 levels among cognitively unimpaired older African Americans in preclinical AD.