1. extract image-related features
2. train model on normative dataset to predict age
3. obtain predicted ages on test set
4. compute brain-predicted age difference (brainPAD)
5. make inference: accelerated/ delayed aging
select voxels/ROIs
structural MRI
predicted brain age
DNA-methylation
epigenetic age
- real age
automated ML
(regularized NPDR)
~ genetic variants
Dimensions and stages of aging
Aim 3
Aim 2
Aim 2 + 3
select CpG sites
time
brain age
Aim 1
Develop and evaluate NPDR
Biological processes
Accelerated aging
Disease progression
?
\(allele_i \) carrier
\(allele_i \) non-carrier
composite \(\Delta\) age
By Trang Le
Figures presented in my grant proposal.
#math graduate. Postdoc fellow with Jason Moore.
