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.

Frontal and anterior temporal hypometabolism post chemoradiation in head and neck cancer: A real-world PET study.

Background And Purpose: Adverse neurological effects after cancer therapy are common, but biomarkers to diagnose, monitor, or risk stratify patients are still not validated or used clinically. An accessible imaging method, such as fluorodeoxyglucose positron emission tomography (FDG PET) of the brain, could meet this gap and serve as a biomarker for functional brain changes. We utilized FDG PET to evaluate which brain regions are most susceptible to altered glucose metabolism after chemoradiation in patients with head and neck cancer (HNCa).

A Clinical PET Imaging Tracer ([F]DASA-23) to Monitor Pyruvate Kinase M2-Induced Glycolytic Reprogramming in Glioblastoma.

Purpose: Pyruvate kinase M2 (PKM2) catalyzes the final step in glycolysis, a key process of cancer metabolism. PKM2 is preferentially expressed by glioblastoma (GBM) cells with minimal expression in healthy brain. We describe the development, validation, and translation of a novel PET tracer to study PKM2 in GBM.

Generalization of deep learning models for ultra-low-count amyloid PET/MRI using transfer learning.

Purpose: We aimed to evaluate the performance of deep learning-based generalization of ultra-low-count amyloid PET/MRI enhancement when applied to studies acquired with different scanning hardware and protocols.

Methods: Eighty simultaneous [F]florbetaben PET/MRI studies were acquired, split equally between two sites (site 1: Signa PET/MRI, GE Healthcare, 39 participants, 67 ± 8 years, 23 females; site 2: mMR, Siemens Healthineers, 64 ± 11 years, 23 females) with different MRI protocols. Twenty minutes of list-mode PET data (90-110 min post-injection) were reconstructed as ground-truth.

APOE ε4-specific associations of VEGF gene family expression with cognitive aging and Alzheimer's disease.

Literature suggests vascular endothelial growth factor A (VEGFA) is protective among those at highest risk for Alzheimer's disease (AD). Apolipoprotein E (APOE) ε4 allele carriers represent a highly susceptible population for cognitive decline, and VEGF may confer distinct protection among APOE-ε4 carriers. We evaluated interactions between cortical expression of 10 VEGF gene family members and APOE-ε4 genotype to clarify which VEGF genes modify the association between APOE-ε4 and cognitive decline.

Brain expression of the vascular endothelial growth factor gene family in cognitive aging and alzheimer's disease.

Vascular endothelial growth factor (VEGF) is associated with the clinical manifestation of Alzheimer's disease (AD). However, the role of the VEGF gene family in neuroprotection is complex due to the number of biological pathways they regulate. This study explored associations between brain expression of VEGF genes with cognitive performance and AD pathology.

Sex differences in the association between AD biomarkers and cognitive decline.

Women are disproportionately affected by Alzheimer's disease (AD) in terms of both disease prevalence and severity. Previous autopsy work has suggested that, in the presence of AD neuropathology, females are more susceptible to the clinical manifestation of AD. This manuscript extends that work by evaluating whether sex alters the established associations between cerebrospinal fluid (CSF) biomarker levels and brain aging outcomes (hippocampal volume, cognition).

Genetic variation modifies risk for neurodegeneration based on biomarker status.

Background: While a great deal of work has gone into understanding the relationship between Cerebrospinal fluid (CSF) biomarkers, brain atrophy, and disease progression, less work has attempted to investigate how genetic variation modifies these relationships. The goal of this study was two-fold. First, we sought to identify high-risk vs.

Differences in age-related effects on brain volume in Down syndrome as compared to Williams syndrome and typical development.

Background: Individuals with Down Syndrome (DS) are reported to experience early onset of brain aging. However, it is not well understood how pre-existing neurodevelopmental effects versus neurodegenerative processes might be contributing to the observed pattern of brain atrophy in younger adults with DS. The aims of the current study were to: (1) to confirm previous findings of age-related changes in DS compared to adults with typical development (TD), (2) to test for an effect of these age-related changes in a second neurodevelopmental disorder, Williams syndrome (WS), and (3) to identify a pattern of regional age-related effects that are unique to DS.

Genetic modification of the relationship between phosphorylated tau and neurodegeneration.

Background: A subset of individuals present at autopsy with the pathologic features of Alzheimer's disease having never manifest the clinical symptoms. We sought to identify genetic factors that modify the relationship between phosphorylated tau (PTau) and dilation of the lateral inferior ventricles.

Methods: We used data from 700 subjects enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI).

Interactions between GSK3β and amyloid genes explain variance in amyloid burden.

The driving theoretical framework of Alzheimer's disease (AD) has been built around the amyloid-β (Aβ) cascade in which amyloid pathology precedes and drives tau pathology. Other evidence has suggested that tau and amyloid pathology may arise independently. Both lines of research suggest that there may be epistatic relationships between genes involved in amyloid and tau pathophysiology.

Genetic interactions within inositol-related pathways are associated with longitudinal changes in ventricle size.

The genetic etiology of late-onset Alzheimer's disease (LOAD) has proven complex, involving clinical and genetic heterogeneity and gene-gene interactions. Recent genome wide association studies in LOAD have led to the discovery of novel genetic risk factors; however, the investigation of gene-gene interactions has been limited. Conventional genetic studies often use binary disease status as the primary phenotype, but for complex brain-based diseases, neuroimaging data can serve as quantitative endophenotypes that correlate with disease status and closely reflect pathological changes.

Genetic interactions found between calcium channel genes modulate amyloid load measured by positron emission tomography.

Late-onset Alzheimer's disease (LOAD) is known to have a complex, oligogenic etiology, with considerable genetic heterogeneity. We investigated the influence of genetic interactions between genes in the Alzheimer's disease (AD) pathway on amyloid-beta (Aβ) deposition as measured by PiB or AV-45 ligand positron emission tomography (PET) to aid in understanding LOAD's genetic etiology. Subsets of the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohorts were used for discovery and for two independent validation analyses.

Genetic interactions associated with 12-month atrophy in hippocampus and entorhinal cortex in Alzheimer's Disease Neuroimaging Initiative.

Missing heritability in late onset Alzheimer disease can be attributed, at least in part, to heterogeneity in disease status and to the lack of statistical analyses exploring genetic interactions. In the current study, we use quantitative intermediate phenotypes derived from magnetic resonance imaging data available from the Alzheimer's Disease Neuroimaging Initiative, and we test for association with gene-gene interactions within biological pathways. Regional brain volumes from the hippocampus (HIP) and entorhinal cortex (EC) were estimated from baseline and 12-month magnetic resonance imaging scans.