From Unidimensional to Multidimensional Aging Clocks: Uncovering Heterogeneity in Brain and Biologic
Wednesday, November 18, 2026
2:30 PM-3:30 PM
Dornsife's Department of Epidemiology and Biostatistics Seminar Series welcomes Fengqing Zoe Zhang, PhD, a professor in the Department of Psychological and Brain Sciences at Drexel.
About this talk
Surrogate aging biomarkers such as brain or biological age estimated with
machine learning models and imaging or blood-based markers allow us to examine
health as an integrative process and can predict diverse health outcomes.
Comparing these measures with chronological age helps characterize individual
differences in aging.
This talk presents four studies advancing the quantification of brain and
biological aging. Study 1 used up to eight years of longitudinal neuroimaging
data to characterize brain age gap (BAG) trajectories and examine variations by
sex, APOE ε4 status, and disease status. Study 2 introduced individualized pace
of aging (IPOA), a personalized, data driven metric accounting for baseline
health differences to capture biological aging trajectories associated with
physical, behavioral, and mental health outcomes among youth with perinatally
acquired HIV. Study 3 developed a multidimensional brain age index (MBAI) using
regional gray matter volumes from 556 individuals, identifying distinct
developmental trajectories and deriving cluster specific brain age estimates.
Study 4 integrated spatial and temporal representations of 134 regional gray
matter volumes and 54 blood and anthropometric biomarkers from 46,398 UK
Biobank participants to derive system specific aging clocks and individual
uncertainty estimates using conformal inference.
Across developmental and adult populations, these studies demonstrate the
value of moving beyond unitary aging measures toward multidimensional
approaches. Region and system specific aging clocks capture complementary aging
signals, reveal heterogeneous trajectories, and distinguish disease groups.
These approaches may improve the characterization of individual differences in
development and aging, facilitate early identification of atypical
trajectories, and advance the study of healthy aging and age-related disease.
About Dr. Zhang
Dr. Zhang received her PhD in Statistics from Northwestern University in
2014 and then joined Drexel University as an Assistant Professor in the area of
Statistics and Quantitative Psychology. She is currently a tenured Professor in
the Department of Psychological and Brain Sciences at Drexel University. Her
research focuses on the development and application of advanced statistical and
machine learning methods for analyzing complex, high-dimensional data,
including neuroimaging data, and intensive behavioral data. She has published
over 100 peer-reviewed journal articles, and her research has been supported by
NIH and other private foundations. Dr. Zhang has also held leadership roles
within the American Statistical Association, including serving as President of
the ASA Philadelphia Chapter in 2019.
Join us in person or via Zoom.
Contact Information
Nancy Colon-Anderson
nanderson@drexel.edu