Andrew Saykin

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Professor and Director, Center for Neuroimaging and Indiana Alzheimer's Disease Research Center

Indiana University School of Medicine

United States

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About

Andrew Saykin is a Professor and Director at the Center for Neuroimaging and the Indiana Alzheimer's Disease Research Center at Indiana University School of Medicine, USA. His research focuses on Alzheimer’s disease, exploring areas such as language performance, sleep disturbances, and gene expression alterations. He has contributed to significant studies involving computational methods for Alzheimer's gene detection and variations across disease stages.

Recent Grants

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Indiana Alzheimer's Disease Research Center

Open Date: 2021-09-01

Close Date: 2026-06-30

Grant: Close

KBASE2: Korean Brain Aging Study, Longitudinal Endophenotypes and Systems Biology

Open Date: 2021-08-15

Close Date: 2026-07-31

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Training Grant on Alzheimer's Disease and ADRD at Indiana University

Open Date: 2021-05-01

Close Date: 2026-04-30

Grant: Close

Ultrascale Machine Learning to Empower Discovery in Alzheimers Disease Biobanks

Open Date: 2020-09-15

Close Date: 2025-08-31

Grant: Close

Cognitive Aging, Alzheimers disease, and Cancer-related Cognitive Decline

Open Date: 2020-08-01

Close Date: 2024-04-30

Articles (20)

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Collaborators (23)

Brent Small

Professor

University of South Florida

UNITED STATES

Andrew Saykin

Research Interests

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About

Recent Grants

Articles (20)

Comprehensive characterization of the transcriptional landscape in Alzheimer’s disease (AD) brains

Facets of language performance in early‐onset and late‐onset Alzheimer's disease dementia

Anxious–depressive symptoms and sleep disturbances across the Alzheimer disease spectrum

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

Gene Expression Alterations in Peripheral Blood Following Sport-Related Concussion in a Prospective Cohort of Collegiate Athletes: A Concussion Assessment, Research and Education (CARE) Consortium Study

Pathway enrichment in genome‐wide analysis of longitudinal Alzheimer's disease biomarker endophenotypes

Interpretable deep clustering survival machines for Alzheimer’s disease subtype discovery

miR‐133b as a potential regulator of a synaptic NPTX2 protein in Alzheimer's disease

Multiparameter cortical surface morphology in former amateur contact sport athletes

Genetic Variants Associated with Longitudinal Cognitive Performance in Older Breast Cancer Patients and Controls

A protein panel in cerebrospinal fluid for diagnostic and predictive assessment of Alzheimer’s disease

Aberrant GAP43 Gene Expression Is Alzheimer Disease Pathology‐Specific

Integrative Co-methylation Network Analysis Identifies Novel DNA Methylation Signatures and Their Target Genes in Alzheimer’s Disease

Altered cerebral blood flow in older adults with Alzheimer’s disease: a systematic review

Genome-Wide Association Analysis across Endophenotypes in Alzheimer’s Disease: Main Effects and Disease Stage-Specific Interactions

APOE ε2 resilience for Alzheimer's disease is mediated by plasma lipid species

Genome-wide association study of brain arteriolosclerosis

Deep learning-based identification of genetic variants: application to Alzheimer’s disease classification

Correction to: BMI1 is associated with CSF amyloid-β and rates of cognitive decline in Alzheimer's disease.

A deep learning framework identifies dimensional representations of Alzheimer's Disease from brain structure.

Collaborators (23)

Brent Small

Jun Wang

Ian James Martins

Jaroslaw Harezlak

Rebecca Baillie

Ralph Martins

Aliza Wingo

Blaine Roberts

Matthias Arnold

Li Shen

Meichen Yu

Brenna C. McDonald

Steven Rowson

Erik Johnson

Yuan Liu

Hande Karahan

Sunita Patel

Jungsu Kim

Kwangsik Nho

Taeho Jo

Allan I. Levey

Pratishtha Chatterjee

John Beilby

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