Elizabeth C. Mormino

This paper develops a continuous amyloid staging score from regional amyloid PET to improve early Alzheimer's disease staging and cognitive risk stratification.

SPHERE enables the use of sensitive datasets in AI and open science by creating synthetic twins that preserve statistical properties and privacy.

This study identifies structural and molecular pathways affecting sustained attention in older adults, showing independent contributions of white matter integrity and preclinical Alzheimer's disease markers.

This study identifies genetic loci and pathways associated with limbic white matter microstructure in aging and Alzheimer's Disease using multi-cohort diffusion MRI and bulk RNA-seq data.

The paper uses machine learning to predict autopsy-confirmed neuropathology from clinical, neuroimaging, and CSF biomarkers, finding that different modalities best predict specific pathologies.

This study uses brain state dynamics to predict early amyloid accumulation and cognitive impairment in older adults.

The paper identifies a plasma proteomic signature linked to blood-brain barrier dysfunction, which predicts cognitive decline after ischemic stroke.

This study evaluates deep learning models that predict multiple dementia-related neuropathologies using MRI, clinical, and genetic data, showing the potential of multimodal AI for non-invasive profiling.

The paper uses long-read genome sequencing and multi-omics data to identify structural variants associated with aging and neurodegenerative diseases, finding that SVs are more likely to be causal than SNVs.

This paper introduces a conditional diffusion model to denoise 7T MRI scans, improving image quality and outperforming existing methods.

This study examines how APOE ε4 and Alzheimer's pathology interact to affect neural correlates of episodic memory in cognitively unimpaired older adults.

CSF YWHAG:NPTX2 synapse protein ratio, from proteomics of 3,416 individuals across six cohorts, explains cognitive impairment beyond amyloid and tau and predicts decline (hazard ratio 15.4).

The paper examines how top-down attention and Alzheimer's pathology affect neural selectivity during learning in older adults, linking these factors to memory performance.

The paper examines how sex, race, and APOE-ε4 allele status affect white matter microstructure across multiple aging and Alzheimer's disease cohorts.

The paper examines amygdalar tau binding and connectivity in preclinical Alzheimer's disease, finding associations with anxiety symptoms.

The paper examines the association between static and dynamic functional network connectivity and genetic risk of Alzheimer's disease using rs-fMRI and APOE data from cognitively normal individuals.

This study examines dynamic functional connectivity in the cognitive control network across Alzheimer's disease stages, finding altered temporal connectivity patterns associated with symptom progression.

The paper identifies four latent atrophy factors in posterior cortical atrophy using Bayesian modeling, finding that most patients exhibit mixed profiles rather than distinct variants.

This study identifies genetic variants and pathways associated with cognitive resilience to Alzheimer's disease, finding a novel locus linked to bile acid metabolism and methylation changes.

This study uses fMRI data from older adults to show that hippocampal activity and cortical reinstatement predict episodic memory performance, with age reducing cortical reinstatement and its link to memory.

The paper develops a polygenic risk score integrating AD biomarkers and shows it better predicts cognitive decline than a clinical AD-based PRS.

This paper identifies three atrophy-cognitive factors in Alzheimer’s disease using a hierarchical Bayesian model, showing they are stable across cohorts and associated with distinct Tau deposition patterns.

The paper identifies genetic variants associated with Alzheimer's disease and cardiovascular risk factors, showing lipid-related enrichment and pleiotropy beyond APOE.

This study evaluates whether a polygenic hazard score (PHS) can enhance the prediction of amyloid and tau deposition and progression to Alzheimer’s dementia when combined with biomarkers in nondemented individuals.