Category: Publications

“Detecting early memory changes in preclinical Alzheimer’s disease using TabCAT favorites test: Data from the European Prevention of Alzheimer’s Disease (EPAD) cohort”

Authors: Anna Brugulat-Serrat, Elena Tsoy, Gonzalo Sánchez-Benavides, Marta Milà-Alomà, Leslie S Gaynor, Oriol Grau-Rivera, Juan Domingo Gispert,, Joel H Kramer, Katherine L Possin; European Prevention of Alzheimer’s Disease (EPAD) Consortium

Abstract:

Introduction: Sensitive memory paradigms may allow the detection of subtle memory changes associated with early Alzheimer’s pathology in individuals without established clinical symptomatology.

Methods: We explored the cross-sectional association between performance on Tablet-based Cognitive Assessment Tool (TabCAT) Favorites, a brief computerized memory test, with cerebrospinal fluid AT status (A for amyloid-β and T for phosphorylated tau) and its discriminative validity in 727 clinically asymptomatic participants from the European Prevention of Alzheimer’s Disease (EPAD) Longitudinal Cohort Study. Episodic memory was also evaluated with the Repeatable Battery for the Assessment of Neuropsychological Status Delayed Memory Index (RBANS-MI).

Results: Compared to A-T- individuals, poorer TabCAT Favorites Total Correct (Favorites-TC) cross-sectional performance was associated with an increased likelihood of A+T+ status, but not A+T- status. There were no significant associations between AT status and RBANS-MI. Among individuals with low Favorites-TC performance, AT status predicted progression on the Clinical Dementia Rating > 0.

Discussion: Favorites-TC is a sensitive measure for the early detection of cognitive changes in the early stages of the AD continuum.

Highlights: We explored Tablet-based Cognitive Assessment Tool (TabCAT) Favorites scores and cerebrospinal fluid (CSF) AT status (A for amyloid-β and T for phosphorylated tau) in asymptomatic individuals. Poorer Favorites performance linked to higher A+T+ likelihood. TabCAT Favorites is a sensitive tool for detecting early cognitive changes in Alzheimer’s disease (AD).

DOI: https://doi.org/10.1002/alz.71035

Published online: February 2026 in the journal Alzheimer’s & Dementia

“Preclinical Alzheimer’s and vascular biomarkers alter brain aging in cognitively normal adults: a MRI-based study”

Authors: Unai Torres, David Bernal, Ibai Gurrutxaga, Ainara Estanga, Pablo Martínez-Lage, Olatz Arbelaitz

Abstract:

Introduction: The aging global population underscores the need to understand brain aging and its links to neurodegenerative diseases. While most brain aging studies use cognitive impairment as exclusion criteria, preclinical biomarkers may influence results, potentially masking early pathological effects. This study evaluates how preclinical AD and vascular biomarkers impact brain aging models in cognitively normal subjects.

Methods: Using baseline data from the European Prevention of Alzheimer’s Dementia Longitudinal Cohort Study (EPAD LCS), we analyzed 1,380 cognitively unimpaired participants (50+ years) stratified into five groups based on cerebrospinal fluid biomarkers (Aβ42, t-tau, p-tau) and vascular pathology (Fazekas scale, microbleeds). Structural MRI volumes of cortical/subcortical regions were normalized and compared using Nadaraya-Watson kernel regression. Bootstrapping and Bonferroni-corrected statistical tests assessed differences in the relationship between age and brain volume between groups.

Results: Significant differences emerged in the relationship between age and brain volume in biomarker-negative and biomarker-positive groups, particularly in the entorhinal cortex, amygdalas, and basal forebrain (p < 0.01). The AD and mixed AD/vascular groups showed the largest deviations. Gender-specific analyses revealed stronger effects in males. Vascular pathology alone affected distinct regions (e.g., left entorhinal cortex) without amygdala involvement, suggesting disease-specific atrophy patterns.

Discussion: Preclinical AD and vascular biomarkers significantly alter brain aging in cognitively normal individuals. These findings highlight the importance of biomarker stratification in brain age studies to avoid biased estimates. Entorhinal cortex and amygdala volumes may serve as sensitive early indicators of neurodegeneration, supporting their use in targeted interventions and personalized monitoring.

DOI: https://doi.org/10.3389/fnagi.2025.1653074

Published online: 24 November 2025 in the journal Frontiers in Aging Neuroscience

“Deep learning enhanced ALPS reveals genetic and environmental factors of brain glymphatic function”

Authors: Cha Lin, Hao Wu, Wenbiao Xian, Yifan Zheng, Wenxuan Du, Xinyi Chen, Jinxia Li, Weineng Chen, Lishan Lin, Fengjuan Su, Zhong Pei, Ganqiang Liu, For The Alzheimer’s Disease Neuroimaging Initiative For The European Prevention of Alzheimer’s Disease (EPAD) Consortium

Abstract:

Background: The glymphatic system plays a critical role in brain waste clearance and health. Diffusion tensor imaging along the perivascular space (DTI-ALPS) is an emerging approach to assess glymphatic function, but manual analysis is limited by its subjectivity and laboriousness in clinical practice. To address these challenges, we developed a deep learning-enhanced DTI-ALPS (dALPS) method that automates and enhances measurement of DTI-ALPS in large-scale cohorts, enabling us to uncover its genetic and environmental determinants.

Methods: We proposed an automated workflow combining convolutional neural network (CNN) and You Only Look Once (YOLO) for region-of-interest detection in DTI images. Using this method, we calculated dALPS index for over 65,000 participants from UK Biobank and multiple cohorts, and performed a genome-wide association study (GWAS). Additionally, we conducted transcriptome-wide association study (TWAS) and proteome-wide association study (PWAS) to explore the genetic and molecular underpinnings of glymphatic function. Associations between dALPS and demographic, lifestyle, and clinical traits were comprehensively evaluated. Mediation analysis was conducted to explore the potential mediating role of pharmacological treatments, including antidepressants and sleep medications, in the relationship between disease status and dALPS outcomes.

Findings: Our automated dALPS index showed excellent reliability and reproducibility compared to conventional manual techniques (intraclass correlation coefficient = 0·95). We observed that the dALPS index was associated with a wide range of body composition measures and brain structures across different age groups and sex. GWAS identified five significant genetic loci associated with dALPS, two of which were replicated in an independent dataset. Subsequent TWAS and PWAS analyses highlighted potential causal genes and proteins linked to brain fluid dynamics. We found that higher healthy lifestyle index (HLI) was positively correlated with improved dALPS, and confirmed the associations between reduced dALPS and various central nervous system (CNS) disorders, including depression, anxiety and neurodegenerative diseases. Notably, mediation analysis indicated that antidepressants were a risk factor for lower brain glymphatic function (P = 0·004) by partly mediating the risk factor of depression.

Interpretation: The dALPS analysis provides a reliable, precise, and automated biomarker for assessing brain glymphatic function. Our findings illuminate the genetic and environmental determinants of glymphatic activity, underscoring the potential of dALPS in clinical assessment, disease prediction and targeted therapeutic strategies.

DOI: https://doi.org/10.1016/j.ebiom.2026.106133

Published online: 30 January 2026 in the journal eBioMedicine

“The association of diabetes with Alzheimer’s disease biomarkers and vascular burden across European aging and memory clinic cohorts”

Authors: Veerle van Gils, Willemijn J. Jansen, Wiesje M. van der Flier, Pablo Martinez-Lage, Jakub Hort, Inez H. G. B. Ramakers, Olivier Rouaud, Markku Laakso, Sebastiaan Engelborghs, Julius Popp, Alberto Lleó, Anders Wallin, Magda Tsolaki, Charlotte E. Teunissen, Rik Vandenberghe, Yvonne Freund-Levi, Lutz Frölich, Henrik Zetterberg, Johannes Streffer, Simon Lovestone, Justine Moonen, Argonde van Harten, Katerina Veverová, Nienke Legdeur, Anouk den Braber, Daniel Damian, Anette Hall, Janita Bralten, Giuseppe Fanelli, Barbara Franke, Geert Poelmans, Monica Bulló, Susana Jimenez-Murcia, Fernando Fernandez-Aranda, Jordi Salas-Salvadó, Søren Dalsgaard, Pieter Jelle Visser, Stephanie J. B. Vos

Abstract:

Introduction: It remains unclear whether diabetes mellitus (DM) is associated with Alzheimer’s disease (AD) pathology and associated vascular burden.

Methods: We included cognitively normal (CN), mild cognitive impairment (MCI), and dementia individuals. We assessed associations between DM and AD biomarkers (amyloid beta [Aβ], phosphorylated tau‐181 [p‐tau181], total tau [t‐tau], and medial temporal atrophy [MTA]) and vascular burden (white matter hyperintensities, microbleeds) by logistic regression. Secondary analyses assessed associations between DM and profiles of Aβ combined with p‐tau181/t‐tau/MTA/white matter hyperintensity/microbleeds.

Results: We included 5550 participants (65.8+‐8.7 years, 8.7% DM). DM was associated with lower odds of abnormal AD biomarkers: Aβ in MCI (odds ratio [OR] = 0.70, 95% confidence interval [CI]: 0.51–0.95, p = 0.02) and dementia (OR = 0.44, 0.26–0.78, p = 0.003), and p‐tau181 in dementia (OR = 0.64, 0.41–1.00, p = 0.045). Secondary analyses indicated associations of DM with abnormal t‐tau (OR = 1.57, 1.00–2.46, p = 0.048) and MTA (OR = 1.96, 1.05–3.68, p = 0.04) only in CN individuals with normal Aβ.

Discussion: In cognitively impaired individuals, DM was associated with lower odds of Aβ pathology, whereas DM was associated with neurodegeneration markers in CN individuals without Aβ pathology.

DOI: https://doi.org/10.1002/alz.70804

Published online: 30 October 2025 in the journal of Alzheimer’s & Dementia

“Associations of lifestyle factors with amyloid pathology in persons without dementia”

Authors: Julie E. Oomens et al, for the Alzheimer’s Disease Neuroimaging Initiative (ADNI); A4 Study group; Dominantly Inherited Alzheimer Network (DIAN); European Prevention of Alzheimer’s Dementia (EPAD) consortium, Fundació ACE Healthy Brain Initiative (FACEHBI); Japan Alzheimer’s Disease Neuroimaging Initiative (J-ADNI), Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s Disease (KBASE); Presymptomatic Evaluation of Experimental or Novel Treatments for Alzheimer’s Disease (PREVENT-AD)

Abstract:

Background: The association between lifestyle factors and Alzheimer’s disease (AD) pathophysiology remains incompletely understood.

Objective: The aim of this study was to assess the association of alcohol consumption, smoking behavior, sleep quality and physical, cognitive, and social activity with cerebral amyloid pathology.

Methods: For this cross-sectional study, we selected participants from the Amyloid Biomarker Study data pooling initiative. We used generalized estimating equations to assess associations of dichotomized lifestyle measures with amyloid pathology.

Results: We included 9171 participants with normal cognition (NC) and 2555 participants with mild cognitive impairment (MCI) from the Amyloid Biomarker Study. Of participants with NC, 58% were women, 34% were APOE ε4 carrier, and 27% had amyloid pathology. Of participants with MCI, 48% were women, 47% were APOE ε4 carrier, and 57% had amyloid pathology. In NC, cognitively active participants were less likely to have amyloid pathology (OR = 0.77, 95%CI 0.66–0.89, p < 0.001). In MCI, participants who had ever smoked or had sleep problems were less likely to have amyloid pathology (OR = 0.85, 95%CI 0.73–0.99, p = 0.029; OR = 0.62, 95%CI 0.45–0.86, p = 0.004).

Concluaions: In NC, cognitive activity was associated with a lower frequency of amyloid pathology. In MCI, favorable lifestyle behaviors were not associated with a lower frequency of amyloid pathology. The results of the current study contribute to the broader evidence base on lifestyle and AD by further characterizing the role of lifestyle behaviors in AD pathology across different clinical stages.

DOI: https://doi.org/10.1177/13872877251379083

Published online: 13 November 2025 in the journal of Alzheimer’s disease

“Cerebral Microbleeds and Amyloid Pathology Estimates From the Amyloid Biomarker Study”

Authors: Julie E. Oomens et al, for the European Prevention of Alzheimer’s Dementia (EPAD) Consortium; for the Fundació ACE Healthy Brain Initiative (FACEHBI) Study Group; for the BIOFACE Study Group

Abstract:

Importance: Baseline cerebral microbleeds (CMBs) and APOE ε4 allele copy number are important risk factors for amyloid-related imaging abnormalities in patients with Alzheimer disease (AD) receiving therapies to lower amyloid-β plaque levels.

Objective: To provide prevalence estimates of any, no more than 4, or fewer than 2 CMBs in association with amyloid status, APOE ε4 copy number, and age.

Design, Setting, and Participants:  This cross-sectional study used data included in the Amyloid Biomarker Study data pooling initiative (January 1, 2012, to the present [data collection is ongoing]). Data from 15 research and memory clinic studies were pooled and harmonized. Participants included individuals for whom data on age, cognitive status, amyloid status, and presence of CMBs were available. Data were analyzed from October 22, 2023, to April 26, 2024.

Main Outcomes and Measures:  The main outcomes were age, cognitive status, amyloid status and presence, location, and number of CMBs. Presence of amyloid pathology was determined based on 42 amino acid–long form of amyloid-β peptide (Aβ₄₂) levels in cerebrospinal fluid or on amyloid–positron emission tomography. Presence and, in a subset, location (lobar vs deep) and number of CMBs were determined on magnetic resonance imaging (locally with visual rating).

Results:  Among 4080 participants included in the analysis, the mean (SD) age was 66.5 (8.9) years, and 2241 (54.9%) were female. A total of 2973 participants had no cognitive impairment (cognitive unimpairment [CU]), and 1107 had mild cognitive impairment (MCI) or AD dementia (ADD). One thousand five hundred and thirteen participants (37.1%) had amyloid pathology, 1368 of 3599 (38.0%) with data available were APOE ε4 carriers, and 648 (15.9%) had CMBs. In the CU group, amyloid pathology and APOE ε4 copy number were not associated with presence of any, no more than 4, or fewer than 2 CMBs but were associated with increased odds of lobar CMBs (odds ratio [OR] for amyloid, 1.42 [95% CI, 1.20-1.69], P < .001; OR for 2 vs 0 alleles, 1.81 [95% CI, 1.19-2.74], P = .006; OR for 1 vs 0 alleles, 1.10 [95% CI, 0.83-1.46], P = .49; and OR for 2 vs 1 allele, 1.64 [95% CI, 0.90-2.97], P = .11; overall P = .02). In the MCI-ADD group, amyloid pathology was associated with presence of any CMBs (OR, 1.51 [95% CI, 1.17-1.96], P = .002), no more than 4 CMBs (OR, 1.44 [95% CI, 1.18-1.82], P = .002), and fewer than 2 CMBs (OR 1.34 [95% CI, 1.03-1.74], P = .03) but not lobar CMBs. APOE ε4 copy number was associated with presence of any (OR for 2 vs 0 alleles, 1.72 [95% CI, 0.88-3.35], P = .11; OR for 1 vs 0 alleles, 0.78 [95% CI, 0.59-1.04], P = .09; and OR for 2 vs 1 allele, 2.20 [95% CI, 1.32-3.67], P = .002; overall P < .001) and no more than 4 CMBs (OR for 2 vs 0 alleles, 1.31 [95% CI, 0.64-2.68], P = .45; OR for 1 vs 0 alleles, 0.75 [95% CI, 0.54-1.04], P = .08; and OR for 2 vs 1 allele, 1.76 [95% CI, 0.97-3.19], P = .06; overall P = .03) but not with fewer than 2 or lobar CMBs. Prevalence estimates of CMBs ranged from 6% at 50 years of age in a non–APOE ε4 allele carrier with no amyloid pathology and no cognitive impairment to 52% at 90 years of age in an APOE ε4 homozygote carrier with amyloid pathology and cognitive impairment.

Conclusions and Relevance:  In this cross-sectional study of 4080 participants, prevalence estimates of CMBs were associated with amyloid status, APOE ε4 copy number, and age. CMB prevalence estimates may help inform safety evaluations for antiamyloid clinical trials.

DOI: 10.1001/jamanetworkopen.2024.55571

Published online: 22 January 2026 in the journal JAMA Network Open

“Polygenic pathways shape white matter vulnerability to Alzheimer’s disease-related pathophysiological changes”

Authors: Mario Tranfa, Leonard Pieperhoff, Giuseppe Pontillo, Emma S. Luckett, Lyduine E. Collij, Tiago Gil Oliveira, Niccoló Tesi, Natalia Vilor-Tejedor, André Altmann, Luca Roccatagliata, Matteo Pardini, Henne Holstege, Marcel Reinders, Pierre Payoux, Pablo Martinez-Lage, Craig W. Ritchie, Adam Waldman, Joanna M. Wardlaw, Juan Domingo Gispert, Gemma Salvadó, Arturo Brunetti, Henk J.M.M. Mutsaerts, Alle Meije Wink, Frederik Barkhof & Luigi Lorenzini

Abstract:

Background: The accumulation of amyloid-β₁₋₄₂ (Aβ₁₋₄₂) peptides and phosphorylated-Tau₁₈₁ (p-Tau₁₈₁) tangles from the preclinical stages of Alzheimer’s disease (AD) has led to a biological definition of the disease. However, among Aβ₁₋₄₂-positive individuals, cognitive decline onset varies, and some never develop symptoms. Genetic influences on molecular pathways and their interactions with proteinopathy may underlie this heterogeneity. Leveraging data from a large sample of cognitively intact older adults in the European Prevention of Alzheimer Dementia (EPAD) cohort, we examined how AD-related pathophysiological changes (i.e., Aβ₁₋₄₂ and p-Tau₁₈₁), polygenic pathways and their interaction are associated with WM micro- and macrostructural properties.

Methods: We selected 803 individuals (mean age = 64.7 ± 7.3 years, 458 [57.0%] females, 275 [34.2%] APOE-ε4 carriers) with CSF-Aβ₁₋₄₂ and p-Tau₁₈₁ measurements available, full genotyping, and structural and diffusion MRI. Polygenic risk scores (PRSs) were computed using 85 AD-related genetic variants. These were mapped to their corresponding genes and, after excluding those belonging to the APOE locus, clustered by function into six pathway-specific PRSs (i.e., immune activation, signal transduction, inflammation, lipid, amyloid, and clearance pathways). Diffusion MRIs were processed through the fixel-based analysis framework to derive fiber density (FD) and fiber cross-section (FC) metrics, which were averaged within WM tracts. Linear models assessed the effects of AD-related pathophysiological changes, global and pathway-specific PRSs, and their interactions on FD and FC at both the tract and fixel levels. Models were corrected for multiple comparisons.

Results: P-Tau₁₈₁ was primarily associated with greater FD. The lipid pathway was associated with greater FD and FC, with these effects predominantly occurring in the left hemisphere, consistent with evidence of hemispheric dominance. The clearance pathway moderated the effect of Aβ₁₋₄₂ on FD, with a positive slope in A + compared to A- individuals. The immune activation pathway moderated the effect of p-Tau₁₈₁ on FD, with a negative slope in T + compared to T- individuals.

Conclusions: Pathway-specific genetic vulnerability to AD is associated with alterations in WM tracts both directly and by moderating the effects of AD-related pathophysiological changes. AD-associated genetic risk should be integrated into the AD diagnostic framework to enable targeted screening and intervention for future preclinical trials aimed at specific biological pathways.

DOI: https://doi.org/10.1186/s13195-025-01888-3

Published online: 10 November 2025 in the journal Alzheimer’s Research & Therapy

“Deep normative modelling reveals insights into early-stage Alzheimer’s disease using multi-modal neuroimaging data”

Authors: Ana Lawry Aguila, Luigi Lorenzini, Mohammed Janahi, Frederik Barkhof, Andre Altmann

Abstract:

Background: Exploring the early stages of Alzheimer’s disease (AD) is crucial for timely intervention to help manage symptoms and set expectations for affected individuals and their families. However, the study of the early stages of AD involves analysing heterogeneous disease cohorts which may present challenges for some modelling techniques. This heterogeneity stems from the diverse nature of AD itself, as well as the inclusion of undiagnosed or ‘at-risk’ AD individuals or the presence of comorbidities which differentially affect AD biomarkers within the cohort. Normative modelling is an emerging technique for studying heterogeneous disorders that can quantify how brain imaging-based measures of individuals deviate from a healthy population. The normative model provides a statistical description of the ‘normal’ range that can be used at subject level to detect deviations, which may relate to pathological effects.

Methods: In this work, we applied a deep learning-based normative model, pre-trained on MRI scans in the UK Biobank, to investigate ageing and identify abnormal age-related decline. We calculated deviations, relative to the healthy population, in multi-modal MRI data of non-demented individuals in the external EPAD (ep-ad.org) cohort and explored these deviations with the aim of determining whether normative modelling could detect AD-relevant subtle differences between individuals.

Results: We found that aggregate measures of deviation based on the entire brain correlated with measures of cognitive ability and biological phenotypes, indicating the effectiveness of a general deviation metric in identifying AD-related differences among individuals. We then explored deviations in individual imaging features, stratified by cognitive performance and genetic risk, across different brain regions and found that the brain regions showing deviations corresponded to those affected by AD such as the hippocampus. Finally, we found that ‘at-risk’ individuals in the EPAD cohort exhibited increasing deviation over time, with an approximately 6.4 times greater t-statistic in a pairwise t-test compared to a ‘super-healthy’ cohort.

Conclusion: This study highlights the capability of deep normative modelling approaches to detect subtle differences in brain morphology among individuals at risk of developing AD in a non-demented population. Our findings allude to the potential utility of normative deviation metrics in monitoring disease progression.

DOI: https://doi.org/10.1186/s13195-025-01753-3

Published online: 15 May 2025 in the journal Alzheimer’s Research & Therapy

“Blood pressure and Alzheimer’s disease biomarkers in cognitively unimpaired adults: a multicenter study”

Authors: Mariona Osset-Malla, Aitana Martínez-Velasco, Gonzalo Sánchez-Benavides , Mariateresa Buongiorno, Alejandro de la Sierra, Mahnaz Shekari, Carolina Minguillon, Gwendlyn Kollmorgen, Clara Quijano-Rubio, Henrik Zetterberg, Kaj Blennow, David Vállez García, Marc Suárez-Calvet, Juan Domingo Gispert, Oriol Grau-Rivera, ALFA Study

Abstract:

Background: Hypertension is a modifiable risk factor for dementia, potentially influencing Alzheimer’s disease (AD) pathology. Understanding this relationship is essential for developing interventions to reduce dementia risk.

Objectives: We investigated cross-sectional and longitudinal associations between blood pressure and AD biomarkers in cerebrospinal fluid (CSF) and amyloid (Aβ) positron emission tomography (PET) in cognitively unimpaired adults.

Design: Prospective observational study.

Setting: We analyzed data from cognitively unimpaired participants from three observational prospective European studies: ALFA+ (NCT02485730), EPAD-LCS (NCT02804789), and AMYPAD PNHS (EudraCT: 2018-002,277-22).

Measurements: ALFA+ participants had either CSF biomarkers (CSF Aβ42, Aβ40, p-tau181, t-tau) and/or Aβ PET data. EPAD participants had CSF biomarkers (CSF Aβ42, p-tau181, t-tau), and AMYPAD participants had Aβ PET data. All participants had available data about diabetes, use of hypertensive medication, and waist-to-hip ratio. Multivariable linear regression models were used to analyze cross-sectional associations between systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP) with CSF biomarkers or Aβ PET (Centiloid units, CL); longitudinal associations were tested by means of delta CL scores between baseline and follow-up to assess Aβ PET changes over time.

Results: We included 405 participants from ALFA+ (mean age 61.1 years; 60 % female), 1104 from EPAD (mean age 64.8 years; 59.1 % female), and 340 from AMYPAD (mean age 71.8 years; 60 % female). In ALFA+, DBP was negatively associated with CSF Aβ40 (p = 0.016) and p-tau181 (p = 0.050), while there was a non-significant trend towards a positive association between SBP and CL over time (p = 0.058). In EPAD, DBP was negatively associated with CSF Aβ42 (p < 0.001) and p-tau181 (p = 0.014), while PP was positively associated with CSF Aβ42 (p = 0.024). In AMYPAD, SBP (p = 0.002) and PP (p = 0.003) were positively associated with CL at baseline, with a similar non-significant trend being found for DBP (p = 0.089). Higher DBP (p = 0.042) was significantly associated to increased CL over time, with a similar non-significant trend being found for SBP (p = 0.072). We did not find significant associations between blood pressure and longitudinal changes in CSF biomarkers.

Conclusions: Elevated blood pressure was associated with increased Aβ PET accumulation in cognitively unimpaired individuals. Further research is warranted to elucidate potential mechanisms underlying the negative associations between DBP and CSF biomarkers, which do not reflect the typical AD molecular signature. These findings highlight the relevance of high blood pressure as a potential risk factor for cognitive decline.

DOI: https://doi.org/10.1016/j.tjpad.2025.100304

Published online: 11 August 2025 in the journal of Prevention of Alzheimer’s disease

“Cortical thickness subtypes in cognitively unimpaired individuals: Differential network and transcriptomic vulnerability to cortical thinning”

Authors: Luigi Lorenzini, Mario Tranfa, Leonard Pieperhoff, Federico Masserini, Mara ten Kate, Lyduine E. Collij, Giuseppe Pontillo, Emma S. Luckett, Alle Meije Wink, Henk JMM Mutsaerts, Tiago Gil Oliveira, Daniele Altomare, Mercè Boada, Anouk den Braber, Cindy Birck, Christopher Buckley, Gill Farrar, Wiesje van der Flier, Giovanni B. Frisoni, Rossella Gismondi, Juan Domingo Gispert, Bernard J. Hanseeuw, Frank Jessen, Marta Marquié, Anja Mett, Craig Ritchie, Gemma Salvadó, Michael Schöll, Mahnaz Shekari, Andrew W. Stephens, Betty M. Tijms, David Vállez García, Rik Vandenberghe, Pieter Jelle Visser, Luca Roccatagliata, Neil P. Oxtoby, Matteo Pardini, Frederik Barkhof

Abstract:

Introduction: The emergence, stability, and contributing factors of Alzheimer’s disease (AD) gray matter subtypes remain unclear.

Methods: We analyzed data from 1323 individuals without a diagnosis of dementia (CDR < 1) with T1w-MRI and amyloid-PET, including 622 with longitudinal data (3.66 ± 1.78 years). Cortical thickness subtypes were identified using a non-negative matrix factorization (NMF) clustering algorithm. We examined clinical and demographic differences, subtype stability, and longitudinal thinning patterns using brain network models and imaging-transcriptomic analysis. Replication was performed with an alternative clustering approach and a validation cohort.

Results: Two stable subtypes emerged: limbic-predominant and hippocampal-sparing. Limbic-predominant participants were older, had higher amyloid burden, and faster memory decline, while hippocampal-sparing individuals showed greater attention and executive function decline. Distinct thinning patterns were linked to specific network properties and gene expression profiles.

Discussion: These MRI-based subtypes reflect underlying pathophysiological mechanisms and may aid in prognostication and clinical trial stratification.

DOI: https://doi.org/10.1002/alz.70762

Published online: 14 October 2025 in the journal Alzheimer’s & Dementia