UNIVERSITY OF ILLINOIS AT CHICAGO
Department of Psychiatry
Fifth Annual Research Forum – Extravaganza 2014
POSTER TITLE
Differential predictors of stroke and cardiovascular disease as they relate to
brain structure and function: Implications for the human connectome.
DISEASE/KEY
WORDS:
Stroke, Cardiovascular Disease, Brain Structure, Brain Function
AUTHORS:
Cohen, J., Vardhan, S., Sanchez Diaz, D., Leow, A. & Lamar, M.
MENTEE
CATEGORY:
student
BACKGROUND:
Cardiovascular disease (CVD) and stroke affect over 42.2 million individuals over 60
years of age. Risk prediction scores exist to quantify the likelihood of developing
CVD or having a stroke, taking into account various albeit slightly different vascular
risk factors (VRFs). While these algorithms may predict differential medical
outcomes, it is unclear whether they also predict differential cognitive or
neuropathological outcomes.
29 non-demented, non-depressed adults 60 years or older participated in a
comprehensive assessment of vascular risk, cognition and brain imaging. The
Framingham Study risk prediction scores for probability of CVD and stroke within
10-years were used to examine differences in vascular risk and their associations to
cognitive outcomes including composite z-scores of executive functioning (EF),
language, learning/memory/recognition, and attention/information processing. White
matter hyperintensity (WMH) volumes were quantified using T2-FLAIR.
A paired-sample t-test of risk prediction scores revealed greater CVD than stroke risk
in our sample, t(28)= -3.2; p=.003. Given our small sample size, we focused on
differences in resulting Pearsons correlational r-values between CVD and stroke risk
as related to cognitive z-scores and WMH volumes. Hotelling’s t/Steiger’s z revealed
significant differences favoring stroke risk associations for language, EF and WMH
volumes (all p-values<.05).
Within our population, CVD risk may be a more sensitive medical predictor of future
adverse events while stroke risk may be a more sensitive measure of brain correlates.
Our results, while preliminary, have implications for behavioral outcomes and we are
currently exploring their relevance to the human connectome using multi-modal image
analysis techniques.
METHODS:
RESULTS:
CONCLUSIONS:
RESEARCH MENTOR:
Melissa Lamar