Adam C. Naj, PhD
Associate Professor of Epidemiology
Dr. Naj is an Assistant Professor of Epidemiology in the Department of Biostatistics, Epidemiology and Informatics, and the Department of Pathology and Laboratory Medicine at the University of Pennsylvania Perelman School of Medicine. His research focuses primarily on the genetics of Alzheimer’s Disease (AD) and neurodegeneration, including his genome-wide association analyses in the Alzheimer’s Disease Genetics Consortium (ADGC) which resulted in a first-author paper that was the most cited Alzheimer’s study of 2011.
Joining Penn in 2012, Dr. Naj has extended his roles in analysis and data management in the ADGC, and has been actively co-leading quality control and case-control analysis working groups in the Alzheimer’s Disease Sequencing Project (ADSP), which has collected data on nearly 600 whole genomes and more than 10,500 whole exomes of AD cases and controls to identify rare risk-increasing and protective genomic variants contributing to AD. Of late, his work has included guiding development of a quality control pipeline for next-generation sequence data as part of the Genomic Center on Alzheimer’s Disease (GCAD).
Dr. Naj is also one of several Penn co-founders and organizers of the annual Symposium on Advances in Genetic Epidemiology and Statistics (SAGES), promoting the development of methods to analyze genomic datasets. He has recently expanded his research portfolio to include studies examining genetic loci contributing to multiple neurodegenerative diseases and phenotypes including AD, Parkinson’s disease, and progressive supranuclear palsy, among others, aspiring to identify key genetic contributors to the pathologies underlying neurodegeneration.
Content Area Specialties
Alzheimer's disease (AD), AD-related dementias, Progressive Supranuclear Palsy (PSP), Primary Age-Related Tauopathy (PART), Frontotemporal Dementia (FTD), Lewy Body Pathology
Methodology Specialties
Genetic epidemiology, statistical genetics, Genome-wide Association Studies (GWAS), multi-stage analysis, admixture mapping, trans-ethnic GWAS, genomic meta-analysis