Steven E. Arnold

About

Steven E. Arnold, M.D., is an Emeritus Professor of Psychiatry at the University of Pennsylvania. He serves as Associate Director of the Institute on Aging and the Alzheimer Disease Core Center at the same institution. Dr. Arnold is also the Director of the Geriatric Psychiatry Section and the Penn Memory Center/Alzheimer's Disease Center Clinical Core at the University of Pennsylvania. His educational background includes an M.D. from Boston University, where he also earned a B.A. in Medical Science and Philosophy, graduating Summa cum laude in 1983. His research expertise encompasses schizophrenia, neuropsychiatry, cognition in aging and neurodegenerative dementias, clinicopathological correlation studies, postmortem research, cellular and molecular neuropathology, and quantitative microscopy. Dr. Arnold's clinical expertise involves evaluation, diagnosis, and medical management of complex neuropsychiatric disorders, including Alzheimer's disease, other neurodegenerative dementias, traumatic brain injury, and the cognitive, mood, and behavioral complications of neurological illness and injury. His contributions include advancing understanding in neurodegenerative diseases and improving diagnostic and treatment approaches for neuropsychiatric conditions associated with aging and neurological injury.

Research topics

• Medicine
• Biology
• Internal medicine
• Neuroscience
• Psychology
• Pathology
• Genetics
• Computer Science
• Bioinformatics
• Machine Learning

Selected publications

• New insights into the genetic etiology of Alzheimer’s disease and related dementias

  Nature Genetics · 2022 · 2403 citations

  Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted mi…

  DOI

• Spread of pathological tau proteins through communicating neurons in human Alzheimer’s disease

  Nature Communications · 2020 · 532 citations

  Tau is a hallmark pathology of Alzheimer's disease, and animal models have suggested that tau spreads from cell to cell through neuronal connections, facilitated by β-amyloid (Aβ). We test this hypothesis in humans using an epidemic spreading model (ESM) to simulate tau spread, and compare these simulations to observed patterns measured using tau-PET in 312 individuals along Alzheimer's disease continuum. Up to 70% of the variance in the overall spatial pattern of tau can be explained by our mod…

  DOI

• Exceptionally low likelihood of Alzheimer’s dementia in APOE2 homozygotes from a 5,000-person neuropathological study

  Nature Communications · 2020 · 484 citations

  Each additional copy of the apolipoprotein E4 (APOE4) allele is associated with a higher risk of Alzheimer's dementia, while the APOE2 allele is associated with a lower risk of Alzheimer's dementia, it is not yet known whether APOE2 homozygotes have a particularly low risk. We generated Alzheimer's dementia odds ratios and other findings in more than 5,000 clinically characterized and neuropathologically characterized Alzheimer's dementia cases and controls. APOE2/2 was associated with a low Alz…

  PublisherOA PDFDOI

• Functional brain architecture is associated with the rate of tau accumulation in Alzheimer’s disease

  Nature Communications · 2020 · 338 citations

  In Alzheimer's diseases (AD), tau pathology is strongly associated with cognitive decline. Preclinical evidence suggests that tau spreads across connected neurons in an activity-dependent manner. Supporting this, cross-sectional AD studies show that tau deposition patterns resemble functional brain networks. However, whether higher functional connectivity is associated with higher rates of tau accumulation is unclear. Here, we combine resting-state fMRI with longitudinal tau-PET in two independe…

  DOI

• Challenges and Opportunities with Causal Discovery Algorithms: Application to Alzheimer’s Pathophysiology

  Scientific Reports · 2020 · 133 citations

  Causal Structure Discovery (CSD) is the problem of identifying causal relationships from large quantities of data through computational methods. With the limited ability of traditional association-based computational methods to discover causal relationships, CSD methodologies are gaining popularity. The goal of the study was to systematically examine whether (i) CSD methods can discover the known causal relationships from observational clinical data and (ii) to offer guidance to accurately disco…

  DOI

Recent grants

• NIH Grant K20MH000978

  NIH · $679k · 1997

• NIH Grant R01AG03947802

  NIH · $505k · 2016

• NIH Grant R29MH055199

  NIH · $550k · 2001

Frequent coauthors

• Keith A. Johnson

  Massachusetts General Hospital

  3052 shared

• D. Cheng

  2268 shared

• Joseph C. Wu

  1944 shared

• Monte S. Buchsbaum

  University of California, Irvine

  1620 shared

• Marcelo F. Di Carli

  Harvard University

  1620 shared

• Carl K. Hoh

  University of California, San Diego

  1620 shared

• Carolyn C. Meltzer

  University of Southern California

  1296 shared

• Darin E. Olson

  University of Alabama at Birmingham

  972 shared

Education

• MD

  Boston University School of Medicine

  1983

Similar researchers at University of Pennsylvania

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• Craig B. Thompsonh-277
• Daniel J Raderh-236