Home
Mission
The mission of the Center for Neurodegenerative Disease Research (CNDR) is to promote and conduct multidisciplinary clinical and basic research to increase the understanding of the causes and mechanisms leading to brain dysfunction and degeneration in neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Lewy body dementia (LBD), Frontotemporal degeneration (FTD), Amyotrophic lateral sclerosis (ALS), Primary lateral sclerosis (PLS), Motor neuron disease (MND), and related disorders that occur increasingly with advancing age. Implicit in the mission of the CNDR are two overarching goals: 1.) Find better ways to cure and treat these disorders, 2. Provide training to the next generation of scientists.
“My goal for CNDR is not only to collaborate with researchers at Penn and from institutions across the globe with the mutual goal of finding better ways to diagnose and treat neurodegenerative diseases, but also to inspire and encourage the next generation of scientists on the importance of investigating these disorders that occur more frequently with advancing age.” – Virginia M.-Y. Lee, PhD, Director, CNDR
John Q. Trojanowski, MD, PhD | 1946 - 2022
In loving memory of John Q. Trojanowski, MD, PhD
Latest Research
-
Neuroimaging PheWAS and molecular phenotyping implicate PSMC3 in Alzheimer's disease
Tuesday, February 24, 2026
INTRODUCTION: Neuroimaging genetics has advanced our understanding of Alzheimer's disease (AD); however, frameworks using functional genomics are needed to elucidate mechanisms connecting loci to neurological outcomes. To address this need, we explored relationships between AD-associated variants and disease via their impact on gene expression and neuroanatomical phenotypes.
-
Identifying TRIM11 Upregulators as Therapeutic Targets in Alzheimer's Disease: A Bayesian Network Approach
Monday, February 23, 2026
A recent study shows that TRIM11 is downregulated in Alzheimer's Disease (AD) but has been demonstrated to improve cognitive function when overexpressed in mouse AD models. Based on this discovery, our study aims to identify potential genetic regulators of TRIM11 using single-cell and single-nucleus RNA sequencing, and graph learning methods. In this study we explore two publicly available datasets: GSE173731 and GSE227222. To identify the potential regulators of TRIM11, we use a probabilistic...
-
Fair Multi-modal Canonical Correlation Analysis: A Neuroimaging Study of Alzheimer's Disease
Monday, February 23, 2026
This study addresses fairness concerns in Multi-modal Canonical Correlation Analysis (MCCA), a technique for analyzing relationships across multiple datasets. We introduce Fair MCCA (F-MCCA), which mitigates bias by optimizing for both correlation performance and demographic fairness. Our method quantifies disparities using Correlation Disparity Error (CDE) and employs a multi-objective optimization framework to derive projection matrices that achieve consistent correlation levels across...