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BACKGROUND: White matter hyperintensities (WMH) are widely used to assess cerebral small vessel disease but reflect late-stage injury. Diffusion magnetic resonance imaging (MRI) biomarkers have been proposed to capture earlier small vessel disease-related microstructural damage but their temporal progression relative to WMH and risk factors associated with progression remain unexplored. METHODS: We identified 2077 participants from the population-based cohort study of the Mayo Clinic Study of Aging in Olmsted County, Minnesota (aged 50–101 years) collected between 05/2005 and 09/2024 with longitudinal neuroimaging. Using multioutput nonlinear mixed-effects models in those with at least 2 fluid-attenuated inversion recovery-MRI and diffusion MRI scans, we characterized the temporal progression of WMH and 4 diffusion MRI biomarkers: fractional anisotropy of the genu of the corpus callosum, peak width of skeletonized mean diffusivity, free water, and Arteriolosclerosis-score, which were automatically estimated. Models incorporated participant-specific time shifts, correlations between biomarkers, and effects of risk factors (sex, education, APOE ε4 status, cardiometabolic conditions). RESULTS: The study population had a mean age of 78 years, 47% were women, 28% were APOE ε4 allele carriers, and 80% were cognitively unimpaired, with an average follow-up of 5.2 years (SD, 4.3 years) for fluid-attenuated inversion recovery-MRI and 4.3 years (SD, 3.9 years) for diffusion MRI. Arteriolosclerosis-score, fractional anisotropy of the genu of the corpus callosum, free water, and peak width of skeletonized mean diffusivity became abnormal in 50% of the study population 16, 12, 10, and 7 years before WMH become abnormal (half-width of CI <1 year), respectively. Global markers (Arteriolosclerosis-score, free water, peak width of skeletonized mean diffusivity, and WMH) were correlated, indicating shared substrates of widespread white matter injury. Fractional anisotropy of the genu of the corpus callosum, a vascular risk microstructural injury biomarker, was weakly coupled with WMH and had an earlier but more linear worsening across adulthood. Cardiometabolic conditions predicted earlier worsening of all biomarkers. Female participants showed earlier WMH, fractional anisotropy of the genu of the corpus callosum, and Arteriolosclerosis-score abnormalities, whereas male participants exhibited earlier peak width of skeletonized mean diffusivity and free water abnormalities. CONCLUSIONS: Diffusion MRI biomarkers were abnormal at least a decade before WMH become abnormal in the population, revealing a prolonged phase of early small vessel disease and highlighting their potential for small vessel disease prevention.

Abstract INTRODUCTION Although cerebrospinal fluid (CSF) biomarkers reflect neurodegeneration in Alzheimer's disease (AD), it remains unclear whether these biomarkers track neurodegeneration in early‐onset Alzheimer's disease (EOAD). METHODS In 80 EOAD patients, we examined correlations between eight CSF biomarker levels and cortical thickness decreases within the EOAD cortical atrophy signature. Significant correlations were then entered into a multiple regression analysis. We also examined contributions of EOAD atrophy and CSF biomarkers to cognitive impairment. RESULTS The levels of four CSF biomarkers correlated to EOAD signature atrophy. Stepwise regression analyses revealed that CSF neurofilament light chain (NfL) levels best predicted EOAD signature atrophy. Multiple regression showed EOAD signature atrophy combined with CSF NfL levels explained more variance in cognitive impairment than either factor alone. DISCUSSION Within EOAD patients, CSF NfL levels relate to the magnitude of cortical atrophy, and a combination of EOAD signature atrophy and CSF NfL levels most robustly predict cognitive impairment.

Objective Magnetic resonance imaging (MRI)‐visible enlarged perivascular spaces (PVS) are markers of cerebral small vessel disease (SVD) and aging, processes implicated in both neurodegenerative and cerebrovascular pathologies. However, longitudinal positron emission tomography (PET) studies examining PVS as a mechanism underlying Alzheimer's disease (AD) pathophysiological progression are lacking. Our overall objective was to investigate the associations of baseline PVS burden with white matter hyperintensity (WMH) volume, amyloid‐PET, and tau‐PET, both cross‐sectionally and longitudinally. Methods We examined 2,229 participants across the aging‐AD spectrum from the Mayo Clinic Study of Aging (MCSA) and the Mayo Alzheimer's Disease Research Center (ADRC) (mean age = 68.59 ± 12.70 and 48.94% women). PVS and WMH were quantified using a novel in‐house algorithm. Amyloid on [ 11 C]Pittsburgh Compound B (PiB)‐PET and tau on AV1451‐PET were measured. Cross‐sectional regional and global associations were examined using canonical correlation analysis (CCA). Longitudinal associations were examined using age‐ and sex‐adjusted linear mixed effect (LME) models with natural splines and subject‐wise 10‐fold cross‐validation. Result Three distinct associations were observed: (1) PVS in the basal ganglia (PVS‐BG) was associated with greater WMH volume both cross‐sectionally and longitudinally; (2) PVS‐BG covaried with higher PiB standardized uptake value ratio (SUVR) cross‐sectionally, with longitudinal trajectory associations limited to amyloid‐negative individuals; (3) PVS in the centrum semiovale (PVS‐CSO) was not associated with amyloid or tau, but was associated with occipital WMH, a pattern characteristic of CAA. Interpretation Findings lend support for PVS‐BG as an early indicator of small vessel dysfunction and WMH pathogenesis. Individuals with higher PVS‐BG burden exhibited higher WMH burden and faster WMH progression, suggesting that PVS‐BG may identify individuals at increased risk of progressive SVD. Evidence linking PVS to downstream AD biomarker progression was weaker. Findings support the relevance of PVS‐CSO to CAA, suggesting that they may reflect changes occurring early in the disease process. ANN NEUROL 2026

Background: Alzheimer’s disease (AD) and cerebrovascular pathology are the two most common causes of dementia, frequently co-occurring in older people. Community-based neuropathology studies indicate that vascular disease accounts for approximately one-third of the population-attributable risk of dementia, controlling for other pathologies (including AD). The proportion with vascular disease as co-pathology is likely to be higher (50–70%). The most common vascular substrate is cerebral small vessel disease, which includes small artery fibrosis (arteriolosclerosis), vascular amyloid deposits (cerebral amyloid angiopathy), and monogenic forms of small vessel disease, the commonest being Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL). Post-stroke cognitive impairment following both ischemic stroke and intracerebral hemorrhage also contributes. Aims and Methods: In this World Stroke Organization (WSO) scientific statement, we assembled a multi-disciplinary international group of experts to review the vascular contribution to dementia, encompassing both vascular and neurodegenerative dementia. This statement has been reviewed and approved by the WSO executive. Results: We summarize the epidemiology, neuropathology, cognitive profile, clinical impact and management of vascular disease in dementia and discuss the recent VasCog-2-WSO diagnostic criteria. We consider the substantial overlap with clinical stroke and with AD dementia. We catalog transcriptomic and proteomic studies that have revealed novel candidate molecules ( COL4A1/4A2, HTRA1, TRIM47, FOXF2 ) as possible treatment targets. We appraise imaging-based biomarkers relevant to vascular disease and potential biochemical markers (vascular endothelial growth factor-A, placental growth factor, interleukin-6, matrix metalloproteinase-9, cathepsin-B). We highlight the potential for vascular interventions to treat not only vascular dementia but also the vascular component of neurodegenerative dementia. We review recent clinical trials targeting multiple pathways, including nitric oxide signaling, high blood pressure, the GABAergic system, angiogenic activity, microglial inhibition, PDE3 and PDE5 inhibition, as well as dietary supplementation with omega-3 fatty acids, s-equol and vitamin E. Finally, we consider upcoming opportunities and challenges relevant to vascular disease in dementia. Conclusion: The vascular contribution to dementia is i) substantial, ii) increasingly understood at molecular and mechanistic levels, iii) a source of potential treatment opportunities. Data Access Statement: no original data are presented in this document.

Importance Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. Objective To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. Data Sources PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Study Selection Studies were included if they provided Centiloids, radiotracer, age, and sex. Data Extraction and Synthesis Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. Results This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I 2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I 2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I 2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I 2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I 2 = 80%). Conclusions and Relevance In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.

Importance Multidomain lifestyle interventions slow cognitive decline in at-risk older adults, but effects on cerebrovascular injury and whether any effect differs by age or across magnetic resonance imaging (MRI) markers remain unclear. Objectives To test whether a structured multidomain lifestyle intervention, vs a self-guided program, alters trajectories of cerebrovascular MRI markers and whether baseline diffusion MRI estimates subsequent vascular injury. Design, Setting, and Participants POINTER Imaging was a prespecified secondary imaging analysis of the US POINTER (US Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk) randomized clinical trial conducted at multiple US sites. Starting August 1, 2020, and continuing until March 1, 2023, all newly enrolled US POINTER trial participants who met criteria, including being 60 to 79 years of age and at increased risk for cognitive decline, were given the opportunity to enroll in POINTER Imaging. Annual MRIs were performed at baseline and up to 2 follow-up visits at 12 and 24 months. The imaging study ended May 14, 2025. Interventions Structured multidomain lifestyle arm (supervised exercise, dietary counseling, cognitive and social engagement, and health coaching) vs self-guided educational arm. Main Outcomes and Measures Primary outcomes were cerebrovascular MRI markers of global white matter free water (FW), fractional anisotropy (FA), peak width of skeletonized mean diffusivity (PSMD), analysis along the perivascular space (ALPS) index, white matter hyperintensity (WMH) volume, and incident cerebral microbleeds (CMBs). Age-group analyses (&amp;lt;70 vs ≥70 years) were prespecified. Linear mixed-effects models tested time, intervention arm, age group, and interactions for continuous outcomes; logistic regression evaluated incident CMBs. All analyses were adjusted for sex, hypertension, diabetes, and smoking and were conducted for the evaluable population. Data were analyzed September 5 to December 11, 2025. Results For 959 participants included in the analysis, the mean (SD) age was 68 (5) years, and 594 (61.9%) were female. A significant time × arm × age group interaction was observed for FW (β = 0.050; SE = 0.018; P = .006). In participants younger than 70 years, the structured intervention, compared with the self-guided intervention, attenuated the FW increase over time (β = −0.031; SE = 0.012; P = .009); no intervention arm difference was observed in participants aged 70 years or older (β = 0.019; SE = 0.014; P = .18). No intervention-related interactions were detected (eg, time × intervention arm interaction) for WMH (β = 0.002; SE = 0.016; P = .90), FA (β = 0.016; SE = 0.016; P = .30), PSMD (β = −0.011; SE = 0.021; P = .60), or ALPS (β = 0.006; SE = 0.021; P = .79). Overall, greater odds of incident CMBs were associated with higher baseline FW (odds ratio, 1.63 [95% CI, 1.24-2.14]; P &amp;lt; .001) and PSMD (odds ratio, 1.40 [95% CI, 1.08-1.81]; P &amp;lt; .001). Greater WMH progression was associated with higher baseline FW (β = 0.014; SE = 0.006; P = .02) and lower baseline FA (β = −0.018; SE = 0.006; P = .004). Conclusions and Relevance In this secondary imaging analysis of a randomized clinical trial, FW was the cerebrovascular MRI marker most responsive to lifestyle intervention in adults 60 to 70 years of age, showing attenuated small-vessel disease–related injury. Findings suggested greater microvascular benefit when intensive lifestyle intervention is implemented earlier in late life. Trial Registration ClinicalTrials.gov Identifier: NCT03688126

Diffusion MRI (dMRI) enables assessment of white matter microstructural abnormalities in Alzheimer's disease (AD), and multisite datasets enable more robust modeling of non-biological variation that can confound analyses. The Alzheimer's Disease Neuroimaging Initiative (ADNI) includes over 10 dMRI protocols, necessitating robust methods to model protocol-related variability when pooling data. Here, we compared three harmonization approaches: (1) mixed-effects models, (2) ComBat-GAM, and (3) eHarmonize, a reference-based lifespan method. We assessed their ability to reduce protocol-related variability in diffusion tensor imaging fractional anisotropy (FA) and mean diffusivity (MD) while preserving associations with cognitive impairment (CI), and amyloid-beta (Aβ) and tau PET burden in 1,086 ADNI3/4 participants. All approaches yielded more closely aligned FA/MD distributions across protocols. Associations with clinical indicators of CI were highly consistent across approaches, whereas PET associations were less widespread and more variable. Overall, multiple strategies effectively modeled protocol-related variability while preserving AD-related associations.

Abstract INTRODUCTION Face identification algorithms have increased the risk of study participants being identified through different neuroimaging modalities. De‐facing algorithms can de‐identify neuroimages; however, none are validated in individuals with Down syndrome (DS) – a population at high risk of Alzheimer's disease and the focus of numerous Alzheimer's disease cohort studies. METHODS Overall, 37 adults with DS were parcellated using FreeSurfer before and after de‐facing with mri_reface . A group of neurotypically developed individuals balanced on age, sex, and magnetic resonance imaging scanner manufacturer served as controls. RESULTS De‐facing produced no effect on cortical thickness or volumetrics in adults with DS compared to controls or regional discrimination based on an area under the receiver operating characteristic curve analysis after correcting for multiple comparisons. DISCUSSION FreeSurfer‐derived volumetric and cortical thickness measures changed minimally following de‐facing with mri_reface in adults with DS and are unlikely to influence study outcomes. De‐facing should be considered prior to data sharing in studies of adults with DS.

Abstract Histopathological assessment has served as the gold standard for diagnosing Alzheimer’s disease (AD). Emerging technological advancements, including the development of amyloid positron emission tomography (PET), have enabled early detection of amyloid pathology, one of the neuropathological hallmarks of AD. Genome-wide association study (GWAS) across cohorts of aging and AD, leveraging different measurements of amyloid burden, may facilitate the identification of novel genetic variants that drive the earliest neuropathological changes in AD. This study presents the largest GWAS of brain amyloidosis to date, leveraging amyloid β (Aβ) measured by in vivo amyloid PET and postmortem histopathology from 13,555 individuals of European ancestry. Amyloid positivity was defined as moderate or frequent neuritic plaques according to the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) staging scores for each postmortem cohort. A Gaussian mixture model (GMM) was applied to each amyloid PET cohort to identify the cohort and tracer-specific cut-offs that differentiate amyloid positive and negative populations. In silico and ex vivo analyses further characterized implicated loci, including interrogating the association between bulk and single-nucleus gene expression profiles and AD-related traits. Genetic covariance analysis assessed the extent amyloid PET and postmortem measures reflect the shared genetic architecture of brain amyloidosis. Our combined amyloidosis GWAS identified three established AD risk loci: BIN1 (rs6733839, OR = 1.20, 95% CI 1.14-1.26, P = 1.32 × 10−11), CR1 (rs4844610, OR = 1.24, 95% CI = 1.16-1.32, P = 4.21 × 10−10), APOE (rs429358, OR = 4.01, 95% CI = 3.66-4.38, P = 4.54 × 10−201), and a newly identified brain amyloidosis-associated variant on chromosome 17 (rs35635959, OR = 1.18, 95% CI = 1.12-1.25, P = 1.47 × 10−8). SuSiE fine-mapping identified a single credible set of 15 putative causal variants with rs35635959 as the lead variant. Subsequent eQTL and SuSiE-based colocalization analyses prioritized rs35635959 as a strong eQTL for TUBG2, encoding tubulin gamma 2, which is involved in microtubule organization and synaptic plasticity. Further cell-type-specific characterization of this gene in neurons from dorsolateral prefrontal cortex tissue indicated that decreased TUBG2 expression was associated with increased Aβ burden and AD case status (PFDR &lt; 0.045). Furthermore, our study is the first to report a modest genetic covariance (covariance=0.17, P &lt; 6.54 × 10−8) between the genetic architecture of amyloid burden captured by different modalities. While APOE showed a strong association with both amyloid endophenotypes, the observed genetic covariance was not substantially attenuated after excluding variants within the APOE region (covariance=0.16, P &lt; 1.32 × 10−7). Our results highlight the benefits of leveraging compatible, harmonized AD endophenotypes to increase power to uncover new molecular insights into the etiology of AD neuropathology. Wang et al. present the largest GWAS of brain amyloidosis to date, analysing 13,555 individuals using amyloid PET and postmortem Aβ measures. They identify a novel amyloidosis-associated variant on chromosome 17, demonstrate genetic covariance between modalities, and highlight complex traits sharing genetic architecture with Aβ burden.