Spectral dynamic causal modelling of resting-state fMRI: an exploratory study relating effective brain connectivity in the default mode network to genetics

• Published in: Statistical applications in genetics and molecular biology Vol. 19; no. 3
• Main Authors: Nie, Yunlong, Opoku, Eugene, Yasmin, Laila, Song, Yin, Wang, Jie, Wu, Sidi, Scarapicchia, Vanessa, Gawryluk, Jodie, Wang, Liangliang, Cao, Jiguo, Nathoo, Farouk S.
• Format: Journal Article
• Language: English
• Published: Germany De Gruyter 31.08.2020; Walter de Gruyter GmbH
• Subjects: Aged; Aged, 80 and over; Alzheimer Disease - diagnostic imaging; Alzheimer Disease - genetics; Brain; Brain - diagnostic imaging; Brain - pathology; Brain Mapping - methods; Cognitive Dysfunction - diagnostic imaging; Cognitive Dysfunction - genetics; Connectome - methods; Databases, Genetic; effective brain connectivity; Empirical analysis; Female; function-on-scalar regression; Genetics; Humans; imaging genetics; Linear Models; longitudinal resting-state fMRI; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Medical imaging; Models, Theoretical; Nucleotides; parametric bootstrap; Polymorphism, Single Nucleotide; Regression analysis; spectral dynamic causal modeling; longitudinal resting-state fMRI; parametric bootstrap; effective brain connectivity; imaging genetics; function-on-scalar regression; spectral dynamic causal modeling
• ISSN: 2194-6302; 1544-6115; 1544-6115
• DOI: 10.1515/sagmb-2019-0058

We conduct an imaging genetics study to explore how effective brain connectivity in the default mode network (DMN) may be related to genetics within the context of Alzheimer’s disease and mild cognitive impairment. We develop an analysis of longitudinal resting-state functional magnetic resonance imaging (rs-fMRI) and genetic data obtained from a sample of 111 subjects with a total of 319 rs-fMRI scans from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. A Dynamic Causal Model (DCM) is fit to the rs-fMRI scans to estimate effective brain connectivity within the DMN and related to a set of single nucleotide polymorphisms (SNPs) contained in an empirical disease-constrained set which is obtained out-of-sample from 663 ADNI subjects having only genome-wide data. We relate longitudinal effective brain connectivity estimated using spectral DCM to SNPs using both linear mixed effect (LME) models as well as function-on-scalar regression (FSR). In both cases we implement a parametric bootstrap for testing SNP coefficients and make comparisons with p-values obtained from asymptotic null distributions. In both networks at an initial -value threshold of 0.1 no effects are found. We report on exploratory patterns of associations with relatively high ranks that exhibit stability to the differing assumptions made by both FSR and LME.