Disentangling the association between functional connectivity and genetics in Mild Cognitive Impairment via multivariate regression models
Date
2021
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Tartu Ülikool
Abstract
The aim of this study is to analyse links between phenotype and genotype for patients with Mild
Cognitive Impariment (MCI) and Cognitively Normal (CN) using regression based model. Data
was collected from 177 subjects downloaded from The Alzheimer’s Disease Neuroimaging Initiative
(ADNI) database out of which 82 MCI and 95 CN were considered. In this research
work multiple noise reduction pipelines were tested on resting state functional MRI data to
analyse functional connectivity (FC) and extract imaging features. The pipelines performance
was compared and nuisance regression based pipeline was selected. After preprocessing of the
data FC matrices were generated for all subjects. Feature reduction technique was implemented
to summarize the FC matrices into 28 imaging features. Finally, Partial Least Squares (PLS)
model was applied to imaging and genetic features in which correlations are examined. A permutation
test was performed to evaluate the model significance (p < 0:05). PLS model with
LASSO results were investigated and associations between the imaging and genetic features
were reported.
Description
Keywords
kerge kognitiivsete funktsioonide häire, arvutinägemine, funktsionaalne MRI, funktsioonide vähendamine, regressioonanalüüs