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INTRODUCTION Recent work has identified unique cognitive profiles for early‐onset Alzheimer's disease (EOAD) relative to late‐onset Alzheimer's disease (LOAD), however, examination has been limited in determining whether the association between age and cognitive severity at presentation also differs across conditions. METHODS A series of linear spline regression models was conducted across baseline cognitive data from 325 EOAD and 314 LOAD participants, after accounting for education, sex, and apolipoprotein ε4 status. RESULTS Significant differences existed in the relationship between baseline age and cognitive performance between EOAD and LOAD samples for Processing Speed/Attention, Executive Functioning, and Episodic Immediate Memory. Younger participants from both EOAD and LOAD groups performed disproportionately worse on non‐amnestic cognitive domains, with this occurring to a greater extent in EOAD than LOAD. DISCUSSION In the age of disease‐modifying treatments, results highlight the importance of assessing for cognitive declines in individuals starting much earlier than age 65. Highlights Early‐onset Alzheimer's disease (EOAD) and late‐onset Alzheimer's disease (LOAD) participants each displayed cognitive impairments relative to same‐aged peers across most domains. Both groups displayed positive relationships between impairment among non‐amnestic cognitive domains and baseline age. This relationship displayed a significantly greater effect in EOAD than LOAD, with domains of Processing Speed/Attention and Executive Functioning skills being the most pronounced. Of those participants developing AD, age displayed a disproportionate impact on their symptom onset.

Objective Age of symptom onset is highly variable in familial frontotemporal lobar degeneration (f‐FTLD). Accurate prediction of onset would inform clinical management and trial enrollment. Prior studies indicate that individualized maps of brain atrophy can predict conversion to dementia in f‐FTLD. We used a Bayesian linear mixed‐effect (BLME) prediction method for identifying accelerated brain volume loss to predict conversion to dementia. Methods Participants included 234 asymptomatic or prodromal carriers of C9orf72 , GRN , or MAPT mutations (including 21 dementia converters) with ≥3 longitudinal magnetic resonance imaging (MRI) T1‐weighted scans. The BLME models established individual voxel‐wise gray matter trajectories using the first 2 scans. Person‐specific clusters of accelerated volume loss were estimated in subsequent scans and tested as predictors of dementia conversion compared with other approaches in time‐varying Cox proportional hazard models covarying for age. Receiver‐operating characteristic (ROC) curves estimated utility of cluster volume in discriminating which participants converted to dementia within 24 months. Results The BLME cluster volume predicted conversion to dementia in f‐FTLD mutation carriers overall and separately in C9orf72 , GRN , and MAPT , with comparable hazard ratios observed for atrophy W‐maps and regional volumes. Within a 24‐month timeframe, BLME cluster volume discriminated dementia converters from non‐converters with larger areas under the curve (AUCs) than other approaches. Interpretation Bayesian‐modeled individualized atrophy scores predict dementia progression among asymptomatic f‐FTLD mutation carriers and may have increased utility compared with other structural imaging methods when studying individuals over shorter timeframes that align with clinical trial design. ANN NEUROL 20269999:n/a–n/a

Introduction: Plasma biomarkers of Alzheimer’s disease (AD), including amyloid-β (Aβ42/Aβ40), phosphorylated tau (p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) have shown strong reliability in predicting dementia risk. White matter hyperintensities (WMH) represent a major vascular contributor to dementia. We investigated how plasma biomarkers of AD interact with WMH on MRI to influence incident dementia risk. Methods: We included dementia-free participants from the Atherosclerosis Risk in Communities (ARIC) Study who underwent MRI and plasma biomarker assessment at Visit 5 (2011–2013). WMH was quantified and considered continuously (log-transformed and standardized), and in tertiles. Plasma biomarkers were log-base-2-transformed. Cox proportional hazards models were used to estimate dementia risk over 10 years associated with plasma biomarkers and WMH, independently and multiplicatively. Models were adjusted for demographic variables (age, sex, race, and education), vascular risk factors (hypertension, diabetes, smoking status, body mass index, and estimated glomerular filtration rate), and APOE ε4 status. Results: Among 1,538 participants (aged 67- 90 years, 29% Black), 30% ( N = 462) developed dementia over the 10-year follow-up period. For every doubling of plasma Aβ42/Aβ40 , indicating lower amyloid burden, dementia risk decreased, while doubling of p-tau 181 , NfL, and GFAP were each associated with increased dementia risk, in separate models; each of these associations was independent of WMH (Table 1). Additionally, dementia risk increased per SD increase in WMH, independent of each plasma biomarker. Although no multiplicative interaction terms reached statistical significance (p<0.05), there was suggestive evidence that Aβ42/Aβ40 and GFAP have smaller effect sizes on dementia risk in subgroups at the highest WMH tertile (p-interactions<0.10; see Table 2). Discussion: Plasma biomarkers and WMH independently predict dementia risk over 10 years, though there remained limited evidence of multiplicative effects. Plasma biomarkers may be less important for dementia risk in individuals who also have extensive WMH. These findings emphasize the importance of incorporating both AD-specific plasma markers as well as indicators of cerebral small vessel disease, such as WMH, into dementia risk profiling.

Objective: Epidemiological data have suggested that late-life depression (LLD) occurs as a consequence of cerebrovascular and neurodegenerative disorders, but there is also some evidence suggesting that the relationship may occur in the other direction, namely that LLD may be a risk factor for cerebrovascular and neurodegenerative disorders. However, the neurobiological basis of these associations remain unclear. This study investigated the associations of LLD with markers of cerebrovascular pathology, brain volumes, and cortical thickness from 3-Tesla brain magnetic resonance imaging (MRI). Methods: Participants from the Atherosclerosis Risk in Communities Study received brain MRI scans in late-life (ages 67-90). The following neuroimaging outcomes were assessed: cortical infarcts, lacunar infarcts, any microhemorrhages, lobar microhemorrhages, subcortical microhemorrhages, white matter hyperintensity volume, total and regional brain volumes (z-scores), and total average and regional cortical thickness (z-scores). At the same visit, LLD was evaluated with the 11-item Center for Epidemiological Studies Depression Scale (CES-D) and defined as CES-D score≥9. Associations between LLD and neuroimaging outcomes were examined using logistic and linear regression models, and were adjusted for age, race-center, sex, education level, vascular risk factors, stroke, cognitive status, APOE e4 carrier status, and total intracranial volume when assessing volumes. Results: Among 1,857 participants, the median age was 76 years, 59.5% were female, 28.3% were Black, and 6.8% had LLD. LLD was not associated with infarcts or microhemorrhages. There was no evidence of an association between LLD and total white matter hyperintensity volume or total average cortical thickness. However, LLD was independently associated with smaller volume (SD) of the rostral anterior cingulate (b 1 : -0.18; 95% CI: -0.33, -0.04) and greater cortical thickness (SD) in the medial orbitofrontal cortex (b 1 : 0.19; 95% CI: 0.01, 0.38), though effect sizes were small and did not survive correction for multiple comparisons. Conclusion: Findings from this study suggest LLD is not cross-sectionally associated with neuroimaging markers of cerebrovascular disease. While LLD may be linked to subtle volume and cortical thickness changes in specific regions of interest, future longitudinal research is warranted to validate and clarify these associations and explore their potentially bidirectional relationship.

Background: Stroke is a leading cause of death and disability despite advances in risk factor management. Many risk factors for stroke have also been implicated as risk factors for mild cognitive impairment (MCI) and dementia. Given these shared risk factors, cognitive impairment (CI) may represent an accumulation of neurological injury that is associated with an elevated risk of stroke. In ARIC-NCS, we aimed to 1) understand the independent relationship between pre-stroke CI (MCI or Dementia) and incident stroke; 2) explore mortality differences in stroke patients with vs without pre-stroke CI; and 3) evaluate modifiers of these relationships. Methods: 5434 stroke-free participants were evaluated for cognitive status at an in-person visit in 2011-13 (visit 5; ages 66-90), based on cognitive testing and informant interviews. Incident definite or probable strokes (ischemic or hemorrhagic) from visit 5 through 2022 were identified via ongoing surveillance (semi-annual telephone calls, with expert classification). Using Cox proportional hazards regression models adjusted for demographics and vascular risk factors, we evaluated associations between CI (MCI or dementia) and incident stroke, and between CI and death among individuals with stroke. Finally, we tested effect modification by age at visit 5, sex, education, and race, via stratified models and formal interaction terms. Results: Compared to those without CI, individuals with CI (23%) were older (77 vs 75 years, p<0.001), and more frequently male (48% vs 40%). Over 10+ years, CI was independently associated with an increased risk of incident stroke (HR:1.52, 95% CI:1.18-1.96). Among individuals with stroke, risk of death was also higher in CI vs non-CI patients (HR 1.78, 95% CI 1.27-2.50). In stratified analysis, we found a significant interaction by sex (p-interaction=0.04): in males, CI was associated with elevated stroke risk (HR:2.01, 95% CI:1.39-2.91) without a similar risk in females (HR:1.22, 95% CI:0.85-1.75). Interactions by race, age, and educational level were not statistically significant, but effect sizes were qualitatively larger in White participants and individuals with more education. Conclusion: CI is associated with incident stroke independent of shared risk factors, especially in men. This work adds to our understanding of populations at risk for stroke, thus aiding efforts to optimize stroke prevention in at-risk populations.

BACKGROUND: Cerebral hemodynamic impairment in patients with asymptomatic high-grade (>70%) internal carotid artery (ICA) stenosis is associated with risk of stroke and cognitive decline, but correlations between the degree of stenosis and hemodynamic impairment are derived from small case series. Using baseline data from 242 participants in the CREST-H study (Carotid Revascularization and Medical Management for Asymptomatic Carotid Stenosis–Hemodynamics), we hypothesized that the degree of stenosis in the ICA would correlate with time-to-peak (TTP) delay in ipsilateral cerebral blood flow using MR/CT perfusion scans, adjusting for demographic and cardiovascular risk variables. METHODS: From all participants, ICAs were insonated using a 7 to 10 MHz probe for peak systolic velocity (PSV) and end diastolic velocity. Dynamic contrast perfusion imaging was standardized across 61 CREST-H sites, using standard sequential T2*-weighted perfusion imaging. CT perfusion used standard clinical protocols. TTP delay was calculated in the ipsilateral versus contralateral hemispheres. In cross-sectional analysis, linear regression was used to model TTP delay as the outcome variable and PSV, end diastolic velocity, and PSV ICA/common carotid artery ratio on the index and nonindex side as primary predictor variables in 6 separate models, adjusting for covariates, followed by automated backward elimination model reduction. RESULTS: Among 392 CREST-H participants, the 242 with complete data for all variables were included in the regression analysis (age, 70±7.6; 62% M). End diastolic velocity on the index side correlated with TTP delay (β=0.003, P =0.005). PSV had a similar correlation but did not reach significance (β=0.001, P =0.099), nor did ICA/common carotid artery ratio (β=0.003, P =0.126). Nonindex side PSV, end diastolic velocity, and ICA/common carotid artery ratio showed no correlation with TTP delay ( P =0.268, P =0.495, P =0.380, respectively). Circle of Willis completeness did not correlate with TTP. CONCLUSIONS: In this large cohort of patients with high-grade asymptomatic carotid stenosis, higher end-diastolic flow velocities correlated with greater TTP delays, supporting a definition of hemodynamically significant stenosis. Our findings have implications for the management of asymptomatic carotid stenosis, which will be tested in the CREST-H study. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03121209.

Abstract INTRODUCTION The vascular endothelial growth factor (VEGF) signaling family plays a role in neurodegenerative diseases, including Alzheimer's disease (AD). Previous work has shown widespread effects of the members FLT1 , FLT4 , and VEGFB on AD outcomes. However, these analyses have focused within the non‐Hispanic White (NHW) population. METHODS The goal of this study was to analyze the effects of the VEGF family in underrepresented populations, leveraging large and diverse bulk RNA sequencing and tandem mass tag–mass spectrometry (TMT‐MS) proteomic data. Outcomes included measures of AD pathology and diagnosis. RESULTS Within underrepresented populations, we replicated previously reported effects of FLT1 and FLT4 , whereby higher protein abundance was observed in the AD brain and was associated with higher neuropathology burden. In stratified analyses, these associations were largely consistent across race and ethnicity. DISCUSSION This multi‐omic study on the role of the VEGF family in AD emphasizes the need for more representative studies focused on therapeutic targets for AD. Highlights Vascular endothelial growth factor (VEGF) genes and proteins were quantified in four different brain regions. Samples included participants from four different populations. Previously observed effects were replicated in diverse populations. This study is the largest multi‐omic study of the vascular endothelial growth factor (VEGF) genes among Alzheimer's disease (AD) participants from diverse populations.