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Sperling, R. A.

Publications and source records attributed to Sperling, R. A..

5 recordsLinked to original sources

Topographic reference modelling of white matter hyperintensities across the adult lifespan

White matter hyperintensities (WMH) are among the most common MRI findings in older adults. They are widely regarded as markers of brain aging and cerebral small-vessel disease, and associated with risk for cognitive decline, Alzheimers disease and related dementias (ADRD), and stroke. White matter hyperintensities (WMH) are typically interpreted by total lesion burden, but lesions with similar volumes can occupy different anatomical locations, potentially reflecting distinct pathological processes. Here we present voxelwise topographic reference modelling (vTRM), a framework for characterizing individual WMH masks against age- and sex-stratified frequency maps derived from cognitively unimpaired individuals. Using 42,469 FLAIR-derived lesion masks from twelve adult cohorts, we mapped population-level WMH spatial vulnerability, characterized age-related changes in its distribution across periventricular, lobar and arterial-territory compartments, and constructed paired percentile charts for lesion burden and spatial typicality. A quadrant-based classification defined by these two percentile dimensions revealed graded relationships with ADRD pathophysiology, neurodegeneration, and cognitive impairment, while identifying WMH patterns differentially associated with ageing-related, vascular and neurodegenerative processes among individuals with similar lesion volumes. These reference charts establish a benchmark for normative WMH ageing, enabling quantification of individual deviations from typical age-, sex- and burden-related patterns and identification of WMH phenotypes associated with vascular, neurodegenerative or mixed etiologies. The framework, together with a deployable 3D U-Net model trained on these data for automated WMH segmentation, is available through the Brain Lesion Analytics platform (https://brainlesionanalytics.org/).

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Network Localization of Anxiety as an Early Manifestation of Alzheimer's Disease-related Neurodegeneration

Objective Anxiety is a prominent neuropsychiatric symptom in preclinical Alzheimer's disease (AD), but the neural circuitry linking anxiety and AD remains uncharacterized. We assessed whether anxiety in preclinical AD is independently associated with AD-related neurodegeneration and localizes to a common anxiety network. Methods In cognitively unimpaired (CU) older adults with 3T MRI and amyloid-beta PET (N=1,775), we examined whether an established AD-related atrophy network is associated with anxiety (STAI-6). Then, using Atrophy Network Mapping (ANM), which maps individual cortical atrophy patterns onto a normative functional connectome (N=1000), we derived an anxiety network. We tested its 1) spatial convergence with the AD network and with a causal anxiety network derived from lesion and neuromodulation data, 2) specificity relative to depression, 3) generalizability in samples from independent cohorts with AD and Parkinson's disease (total n=878), and 4) association with longitudinal outcomes. Results In CU older adults, greater AD-network atrophy was associated with higher anxiety, independent of depression, cognition, cortical atrophy, and amyloid burden. Anxiety localized to a network closely resembling the AD network (r=0.74, p=0.04) and the causal anxiety network (r=0.72, p=0.02). This convergence extended across the AD continuum and to the Parkinson's disease cohort and was specific to anxiety relative to depression. Greater anxiety-network atrophy was associated with cognitive decline over 4.6 years. Conclusion Anxiety localizes to a brain circuit resembling the AD-related atrophy network, is consistent across the AD continuum and may extend beyond AD. These findings support anxiety as an independent marker of early AD-related neurodegeneration.

neuroscience↗

Continuous amyloid staging complements global amyloid burden in early Alzheimer's disease

Introduction: Early Alzheimer's disease (AD) staging remains challenging because clinical categories and global amyloid PET measures provide only coarse characterization of disease progression. We developed a continuous amyloid staging score from regional amyloid PET to complement global amyloid burden. Methods: Using longitudinal florbetapir PET from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we trained an end-to-end deep learning model to directly estimate a continuous amyloid staging score. We evaluated longitudinal consistency, its relationship with global amyloid burden, regional contributors to early-stage variation, and whether the staging score stratified subsequent memory decline among participants matched for baseline global amyloid burden. Cognitive analyses were replicated in A4+LEARN. Results: The staging score better preserved longitudinal visit order than existing amyloid staging approaches. During early disease stages, it captured regional amyloid variation despite relatively stable global amyloid burden. Among participants with similar baseline global amyloid burden, higher staging scores were associated with faster subsequent memory decline in both ADNI and A4+LEARN. Discussion: A continuous amyloid staging score complements global amyloid burden for early AD staging and cognitive risk stratification. Keywords: Alzheimer's disease; amyloid PET; disease staging; cognitive decline

neuroscience↗

Blood-based Transcriptomics Reveal Sex- and Amyloid-Modulated Biology of Plasma pTau217 in Preclinical Alzheimer's Disease

Plasma pTau217, an emerging Alzheimers disease (AD) biomarker, may reflect a synaptic response to {beta}-amyloid (A{beta}) plaques before cortical tangle formation, but its broader biological correlates remain unclear. We sought to identify associations between whole blood gene expression and plasma pTau217, and to determine whether APOE{varepsilon}4, sex, and neocortical A{beta}-PET modify these associations in 724 participants from the Anti-Amyloid Treatment in Asymptomatic Alzheimers and accompanying LEARN studies (A4/LEARN, Agemean(SD)=72.2(4.6); 63%female). Of 20,621 genes tested (1,048 X-linked), none were directly associated with pTau217; one gene was moderated by APOE{varepsilon}4, 1,540 genes by A{beta}-PET, and 772 genes by both A{beta}-PET and sex. Over 100 of these significant associations were X-linked, supporting a role of the X chromosome in AD. Sex interactions were only observed in the presence of elevated A{beta}-PET. Our results underscore the complexity of molecular mechanisms that can be linked to plasma pTau217, particularly in the context of elevated A{beta}-PET.

neuroscience↗

Amyloid-β and tau pathologies relate to distinctive brain dysconnectomics in preclinical autosomal-dominant Alzheimer's disease

The human brain is composed of functional networks that have a modular topology, where brain regions are organized into communities that form internally dense (segregated) and externally sparse (integrated) subnetworks that underlie higher-order cognitive functioning. It is hypothesized that amyloid-{beta} and tau pathology in preclinical Alzheimers disease (AD) spread through functional networks, disrupting neural communication that results in cognitive dysfunction. We used high-resolution (voxel-level) graph-based network analyses to test whether in vivo amyloid-{beta} and tau burden was associated with the segregation and integration of brain functional connections, and episodic memory, in cognitively-unimpaired Presenilin-1 E280A carriers who are expected to develop early-onset AD dementia in approximately 13 years on average. Compared to non-carriers, mutation carriers exhibited less functional segregation and integration in posterior default-mode network (DMN) regions, particularly the precuneus, and in the retrospenial cortex, which has been shown to link medial temporal regions and cortical regions of the DMN. Mutation carriers also showed greater functional segregation and integration in regions connected to the salience network, including the striatum and thalamus. Greater tau burden was associated with lower segregated and integrated functional connectivity of DMN regions, particularly the precuneus and medial prefrontal cortex. In turn, greater tau pathology was related to higher segregated and integrated functional connectivity in the retrospenial cortex, and the anterior cingulate cortex, a hub of the salience network. These findings enlighten our understanding of how AD-related pathology distinctly alters the brains functional architecture in the preclinical stage, possibly contributing to pathology propagation and ultimately resulting in dementia. SIGNIFICANCE STATEMENTAmyloid-{beta} and tau pathologies in Alzheimers disease (AD) are hypothesized to propagate through functional networks. Research is needed to elucidate how AD-related pathologies alter the brains functional connections years before symptom-onset to help predict pathology accumulation and dementia risk. Using high-resolution (voxel-level) graph-based network analyses and PET imaging, we showed that greater tau burden was associated with largely dysconnectivity of posterior default-mode network brain regions, and increased connectivity of structures associated with the salience network and others that are critical for integrating information across neural systems in cognitively-unimpaired Presenilin-1 E280A carriers. Findings enlighten how amyloid-{beta} and tau relate to distinct patterns of functional connectivity in regions that underlie memory functioning and are critical for information processing, helping predict disease progression.

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