Trang Le
#math graduate. Postdoc fellow with Jason Moore.
Effect of ibuprofen on BrainAGE:
a randomized, placebo-controlled,
dose-response exploratory study
Trang Lê
Biomedical Researcher
Institute for Biomedical Informatics
University of Pennsylvania
Laureate Institute for Brain Research, Tulsa, OK
extract image-related features
train a machine learning model on a large normative dataset
to predict age
obtain predicted ages on a separate dataset of interest with the trained model
compute each subject’s Brain Age Gap Estimate (BrainAGE)
make inferences about accelerated or delayed aging
T1-weighted structural
diffusion tensor
functional MRI
\textrm{BrainAGE}_i = \widehat\textrm{age}_{\textrm{brain, i}} - \widehat\textrm{age}_{\textrm{chrono, i}}
SVR
RVR
GPR
\widehat\textrm{age}_{\textrm{brain, i}}
medial prefrontal cortex: strong age predictor
Gray matter density 3334 course voxels
r = 0.76, MAE = 5.34 years
SVR 10-fold CV: , C
\epsilon
20 healthy participants (10 males)
ICC = = 0.96
(95% CI=(0.92, 0.98)
\frac{\hat\sigma^2_B}{\hat\sigma^2_B + \hat\sigma^2_W}
F=5.83, p=0.006
BrainAGE was reduced by
- 200mg: 1.15 year (t=-2.95, p=0.005)
- 600mg: 1.18 year (t=-2.97, p=0.005)
Cohen's D (95% CI):
- D200mg-placebo: 0.57 (0.27, 0.95)
- D600mg-placebo: 0.69 (0.39, 1.15)
\textrm{BrainAGE} = (\beta_0 + u_i) + \beta_1(\textrm{ibu 200mg}) + \beta_2(\textrm{ibu 600mg}) + \epsilon
u_i \sim N(0, \sigma^2_B)
\epsilon \sim N(0, \sigma^2_W)
random intercept
within-subject variation
@trang1618
Thank you!
Funding: The William K. Warren Foundation
LIBR collaborators:
- Rayus Kuplicki
- Henry Yeh
- Martin Paulus
BrainAGE and ibuprofen
By Trang Le
