Vascular endothelial growth factor receptor-1 (FLT1) interactions with amyloid-beta in Alzheimer's disease: A putative biomarker of amyloid-induced vascular damage.

We have identified FLT1 as a protein that changes during Alzheimer's disease (AD) whereby higher brain protein levels are associated with more amyloid, more tau, and faster longitudinal cognitive decline. Given FLT1's role in angiogenesis and immune activation, we hypothesized that FLT1 is upregulated in response to amyloid pathology, driving a vascular-immune cascade resulting in neurodegeneration and cognitive decline. We sought to determine (1) if in vivo FLT1 levels (CSF and plasma) associate with biomarkers of AD neuropathology or differ between diagnostic staging in an aged cohort enriched for early disease, and (2) whether FLT1 expression interacts with amyloid on downstream outcomes, such as phosphorylated tau levels and cognitive performance.

Clinical and demographic factors modify the association between plasma phosphorylated tau-181 and cognition.

Introduction: Plasma phosphorylated tau-181 (p-tau181) associations with global cognition and memory are clear, but the link between p-tau181 with other cognitive domains and subjective cognitive decline (SCD) across the clinical spectrum of Alzheimer's disease (AD) and how this association changes based on genetic and demographic factors is poorly understood.

Methods: Participants were drawn from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and included 1185 adults >55 years of age with plasma p-tau181 and neuropsychological test data. Linear regression models related plasma p-tau181 to neuropsychological composite and SCD scores with follow-up models examining plasma p-tau181 interactions with cognitive diagnosis, apolipoprotein E ε4 carrier status, age, and sex on cognitive outcomes.

Sex and APOE ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer's disease.

Introduction: The effects of sex and apolipoprotein E (APOE)-Alzheimer's disease (AD) risk factors-on white matter microstructure are not well characterized.

Methods: Diffusion magnetic resonance imaging data from nine well-established longitudinal cohorts of aging were free water (FW)-corrected and harmonized. This dataset included 4741 participants (age = 73.

Alzheimer's Disease Sequencing Project Release 4 Whole Genome Sequencing Dataset.

The Alzheimer's Disease Sequencing Project (ADSP) is a national initiative to understand the genetic architecture of Alzheimer's Disease and Related Dementias (AD/ADRD) by sequencing whole genomes of affected participants and age-matched cognitive controls from diverse populations. The Genome Center for Alzheimer's Disease (GCAD) processed whole-genome sequencing data from 36,361 ADSP participants, including 35,014 genetically unique participants of which 45% are from non-European ancestry, across 17 cohorts in 14 countries in this fourth release (R4). This sequencing effort identified 387 million bi-allelic variants, 42 million short insertions/deletions, and 2.

Astrocyte Reactivity Polygenic Risk Score May Predict Cognitive Decline in Alzheimer's Disease.

Alzheimer's disease (AD) is a polygenic disorder with a prolonged prodromal phase, complicating early diagnosis. Recent research indicates that increased astrocyte reactivity is associated with a higher risk of pathogenic tau accumulation, particularly in amyloid-positive individuals. However, few clinical tools are available to predict which individuals are likely to exhibit elevated astrocyte activation and, consequently, be susceptible to hyperphosphorylated tau-induced neurodegeneration.

The Consortium for Clarity in ADRD Research Through Imaging (CLARiTI).

The presence of multiple pathologies is the largest predictor of dementia. A major gap in the field is the in vivo detection of mixed pathologies and their antecedents. The Alzheimer's Disease Research Centers (ADRCs) are uniquely positioned to address this gap.

Pathologic and clinical correlates of region-specific brain GFAP in Alzheimer's disease.

Plasma glial fibrillary acidic protein (GFAP) is an emerging biomarker of Alzheimer's disease (AD), with higher blood GFAP levels linked to faster cognitive decline, particularly among individuals with high brain amyloid burden. However, few studies have examined brain GFAP expression to clarify if peripheral associations reflect brain changes. This study aimed to correlate region-specific GFAP mRNA expression (n = 917) and protein abundance (n=386) with diverse neuropathological measures at autopsy in the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP) and to characterize the interaction between brain GFAP and brain amyloid burden on downstream outcomes.

Free-water: A promising structural biomarker for cognitive decline in aging and mild cognitive impairment.

Diffusion MRI derived free-water (FW) metrics show promise in predicting cognitive impairment and decline in aging and Alzheimer's disease (AD). FW is sensitive to subtle changes in brain microstructure, so it is possible these measures may be more sensitive than traditional structural neuroimaging biomarkers. In this study, we examined the associations among FW metrics (measured in the hippocampus and two AD signature meta-ROIs) with cognitive performance, and compared FW findings to those from more traditional neuroimaging biomarkers of AD.

Cognitive status and demographics modify the association between subjective cognition and amyloid.

Objective: This study examined the effect of cognitive status, education, and sex on the association between subjective cognitive decline (SCD) and Alzheimer's disease (AD) biomarkers in non-demented older adults.

Methods: Vanderbilt Memory and Aging Project participants (n = 129), dementia or stroke free, completed fasting lumbar puncture, SCD assessment, and cognitive assessment. Cerebrospinal fluid (CSF) biomarkers for AD were analyzed.

Evaluation of Mean Shift, ComBat, and CycleGAN for Harmonizing Brain Connectivity Matrices Across Sites.

Connectivity matrices derived from diffusion MRI (dMRI) provide an interpretable and generalizable way of understanding the human brain connectome. However, dMRI suffers from inter-site and between-scanner variation, which impedes analysis across datasets to improve robustness and reproducibility of results. To evaluate different harmonization approaches on connectivity matrices, we compared graph measures derived from these matrices before and after applying three harmonization techniques: mean shift, ComBat, and CycleGAN.

Alzheimer's disease genetic risk and changes in brain atrophy and white matter hyperintensities in cognitively unimpaired adults.

Reduced brain volumes and more prominent white matter hyperintensities on MRI scans are commonly observed among older adults without cognitive impairment. However, it remains unclear whether rates of change in these measures among cognitively normal adults differ as a function of genetic risk for late-onset Alzheimer's disease, including -ɛ4, -ɛ2 and Alzheimer's disease polygenic risk scores (AD-PRS), and whether these relationships are influenced by other variables. This longitudinal study examined the trajectories of regional brain volumes and white matter hyperintensities in relationship to genotypes ( = 1541) and AD-PRS ( = 1093) in a harmonized dataset of middle-aged and older individuals with normal cognition at baseline (mean baseline age = 66 years, SD = 9.

Disentangling the genetic underpinnings of neuropsychiatric symptoms in Alzheimer's disease in the Alzheimer's Disease Sequencing Project: Study design and methodology.

Introduction: Neuropsychiatric symptoms (NPS) are highly prevalent in Alzheimer's disease (AD). There are no effective treatments targeting these symptoms.

Methods: To facilitate identification of causative mechanistic pathways, we initiated an effort (NIH: U01AG079850) to collate, harmonize, and analyze all available NPS data (≈ 100,000 samples) of diverse ancestries with whole-genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP).

Proteomics identifies potential immunological drivers of postinfection brain atrophy and cognitive decline.

Infections have been associated with the incidence of Alzheimer disease and related dementias, but the mechanisms responsible for these associations remain unclear. Using a multicohort approach, we found that influenza, viral, respiratory, and skin and subcutaneous infections were associated with increased long-term dementia risk. These infections were also associated with region-specific brain volume loss, most commonly in the temporal lobe.

Proteomic analyses reveal plasma EFEMP1 and CXCL12 as biomarkers and determinants of neurodegeneration.

Introduction: Plasma proteomic analyses of unique brain atrophy patterns may illuminate peripheral drivers of neurodegeneration and identify novel biomarkers for predicting clinically relevant outcomes.

Methods: We identified proteomic signatures associated with machine learning-derived aging- and Alzheimer's disease (AD) -related brain atrophy patterns in the Baltimore Longitudinal Study of Aging (n = 815). Using data from five cohorts, we examined whether candidate proteins were associated with AD endophenotypes and long-term dementia risk.

Proteome-wide analysis identifies plasma immune regulators of amyloid-beta progression.

While immune function is known to play a mechanistic role in Alzheimer's disease (AD), whether immune proteins in peripheral circulation influence the rate of amyloid-β (Aβ) progression - a central feature of AD - remains unknown. In the Baltimore Longitudinal Study of Aging, we quantified 942 immunological proteins in plasma and identified 32 (including CAT [catalase], CD36 [CD36 antigen], and KRT19 [keratin 19]) associated with rates of cortical Aβ accumulation measured with positron emission tomography (PET). Longitudinal changes in a subset of candidate proteins also predicted Aβ progression, and the mid- to late-life (20-year) trajectory of one protein, CAT, was associated with late-life Aβ-positive status in the Atherosclerosis Risk in Communities (ARIC) study.