Andrew J. Saykin

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

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

Divergent amyloid trajectories distinguish normal aging from Alzheimer's disease progression

This paper models Alzheimer's disease progression as a deviation from aging using longitudinal amyloid PET data and a self-supervised trajectory-learning framework, revealing distinct trajectories in early-stage aging and AD.

Cross-Regional Trajectory Analysis Reveals Distinct Temporal Progression of Shared Proteomic Programs in Alzheimer's Disease

The paper analyzes proteomic trajectories in Alzheimer's disease to show distinct temporal progression of shared molecular programs across brain regions.

Genetic architecture of the limbic white matter microstructure in aging and Alzheimer's Disease.

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.

Predicting Autopsy-Confirmed Neuropathology across Clinical, Neuroimaging, and CSF Biomarkers using Machine Learning

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

Gene-Modulated Network Diffusion for Improved Modeling of Amyloid-β Spread in Alzheimer's Disease

This study improves modeling of amyloid-β spread in Alzheimer's Disease using a gene-modulated network diffusion framework, showing better performance in correlation and replicability across cohorts.

Learning a Continuous Progression Trajectory of Amyloid in Alzheimer's disease

This study introduces SLOPE, a method to model amyloid progression in Alzheimer's disease on a continuous trajectory, showing improved sensitivity to early changes compared to global measures.

Individualized Mapping of Functional Brain Networks in Older Adulthood

This study shows that individualized functional brain network mapping in older adults reveals more heterogeneity and improves network fidelity compared to group-averaged approaches.

Network-based amyloid-beta pathology predicts subsequent cognitive decline in cognitively normal older adults

This study uses machine learning to show that integrating brain connectome data with amyloid-beta PET imaging improves prediction of cognitive decline in older adults.

A multi-ancestry polygenic risk score for Alzheimer disease is associated with cognitive decline, hippocampal atrophy and neuropathological hallmarks in diverse populations

This paper develops an APOE-independent polygenic risk score for Alzheimer's disease that shows associations with cognitive decline and neuropathological markers across diverse populations.

Hemispheric Asymmetry of Tau Pathology is Related to Asymmetric Amyloid Deposition in Alzheimer's Disease

The paper investigates whether hemispheric asymmetry in tau pathology in Alzheimer's disease is linked to reduced inter-hemispheric connectivity or asymmetric amyloid-beta distribution, finding a strong association with amyloid-beta laterality.

Genome-wide pleiotropy analysis of longitudinal blood pressure and harmonized cognitive performance measures

This paper identifies genome-wide pleiotropic loci linking blood pressure and cognitive performance measures using longitudinal data from multiple cohorts.

Sex-Specific Genetic Drivers of Memory, Executive Functioning, and Language Performance in Older Adults

The paper identifies sex-specific genetic loci associated with memory, executive functioning, and language performance in older adults through genome-wide meta-analyses.

Multi-Omics Analysis for Identifying Cell-Type-Specific Druggable Targets in Alzheimer's Disease

This study identifies cell-type-specific druggable targets in Alzheimer's disease by integrating GWAS and eQTL data across multiple cell types and datasets.

Evaluating the association of APOE genotype and cognitive resilience in SuperAgers

This study examines the association between APOE genotype and cognitive resilience in SuperAgers, finding lower APOE-ε4 and higher APOE-ε2 frequencies in non-Hispanic White SuperAgers compared to controls and Alzheimer's cases.

LD-informed deep learning for Alzheimer's gene loci detection using WGS data

Deep-Block identifies AD-associated genetic loci using WGS data from ADSP, confirming known variants and discovering novel SNPs within top LD blocks.

Cell Type Differentiation Using Network Clustering Algorithms

This study compares clustering algorithms for cell type annotation in scRNA-seq data, finding that Infomap outperforms others in identifying cell types in PBMC and ROSMAP datasets.

Discovering Genetic Signatures Associated with Alzheimer's Disease in Tiled Whole Genome Sequence Data: Results from the Artificial Intelligence for Alzheimer's Disease (AI4AD) Consortium

The paper uses tiled whole genome sequence data to identify genetic signatures associated with Alzheimer's disease using machine learning methods.

Brain-Age Prediction: Systematic Evaluation of Site Effects, and Sample Age Range and Size

The paper evaluates factors affecting brain-age prediction models using structural neuroimaging data from 35,683 individuals, finding optimal model performance with no site harmonization, age-binning, and a sample size of over 1,600.

Brain Cell-based Genetic Subtyping and Drug Repositioning for Alzheimer Disease

This study identifies genetic subtypes of Alzheimer's Disease using cell-based gene networks and polygenic risk scores, then repositions existing drugs for AD treatment.

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

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

Deciphering the tissue-specific functional effect of Alzheimer risk SNPs with deep genome annotation

This study investigates how Alzheimer's risk SNPs affect chromatin functions and how their genomic context influences these effects.

Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal aging

Genetic variants associated with longitudinal cognitive performance in older breast cancer patients and controls

This study identifies genetic variants associated with cognitive decline in older breast cancer patients compared to controls using longitudinal cognitive data.

Alzheimer Disease Heterogeneity Explained by Polygenic Risk Scores Derived from Brain Transcriptomic Profiles

This study uses polygenic risk scores derived from brain transcriptomic profiles to explain clinical heterogeneity in Alzheimer's disease.

Normative Modeling of Brain Morphometry Across the Lifespan using CentileBrain: Algorithm Benchmarking and Model Optimization

The paper benchmarks and optimizes a normative modeling framework for brain morphometry across the lifespan using MFPR, showing excellent accuracy and stability.

Genome-wide association study of brain biochemical phenotypes reveals distinct genetic architecture of Alzheimer's Disease related proteins

This study performs a genome-wide association study of brain biochemical phenotypes in Alzheimer's patients, identifying novel genetic loci and highlighting distinct genetic architectures for AD-related proteins.

Novel genomic loci and pathways influence patterns of structural covariance in the human brain

The paper identifies 617 novel genomic loci and pathways associated with structural covariance patterns in the human brain using a stochastic multivariate factorization method.

Comprehensive genetic analysis of the human lipidome identifies novel loci controlling lipid homeostasis with links to coronary artery disease

This study identifies 667 genetic loci associated with lipid species and links 186 of them to coronary artery disease through integrative lipidomics and genomics.

Deep trans-omic network fusion reveals altered synaptic network in Alzheimer's Disease

The paper introduces MoFNet, a deep neural network that integrates multi-omic data to identify functional subnetworks associated with Alzheimer's Disease, showing replication in an independent cohort.