Title :
Predicting temporal lobe volume on MRI from genotypes using L1-L2 regularized regression
Author :
Kohannim, Omid ; Hibar, Derrek P. ; Jahanshad, Neda ; Stein, Jason L. ; Hua, Xue ; Toga, Arthur W. ; Jack, Clifford R., Jr. ; Weinen, Michael W. ; Thompson, Paul M.
Author_Institution :
Sch. of Med., Dept. of Neurology, UCLA, Los Angeles, CA, USA
Abstract :
Penalized or sparse regression methods are gaining increasing attention in imaging genomics, as they can select optimal regressors from a large set of predictors whose individual effects are small or mostly zero. We applied a multivanate approach, based on L1-L2-regularized regression (elastic net) to predict a magnetic resonance imaging (MRI) tensor-based morphometry-derived measure of temporal lobe volume from a genome-wide scan in 740 Alzheimer´s Disease Neuroimaging Initiative (ADNI) subjects. We tuned the elastic net model´s parameters using internal cross-validation and evaluated the model on independent test sets. Compared to 100,000 permutations performed with randomized imaging measures, the predictions were found to be statistically significant (p ~ 0.001). The rs9933137 variant in the RBFOX1 gene was a highly contributory genotype, along with rs10845840 in GRIN2B and rs2456930, discovered previously in a univanate genome-wide search.
Keywords :
biomedical MRI; brain; diseases; genetics; genomics; medical image processing; molecular biophysics; neurophysiology; regression analysis; Alzheimer´s disease neuroimaging initiative; L1-L2 regularized regression; MRI tensor-based morphometry; RBFOX1 gene; elastic net model; genotypes; imaging genomics; magnetic resonance imaging; multivanate approach; optimal regressors; penalized regression method; permutation; randomized imaging measures; sparse regression method; temporal lobe volume; univanate genome-wide search; Decision support systems; Elastic net; Imaging Genetics; MRI; Neuroimaging; Prediction;
Conference_Titel :
Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4577-1857-1
DOI :
10.1109/ISBI.2012.6235766