Heritability of head motion during resting state functional MRI in 462 healthy twins

Abstract

Head motion (HM) is a critical confounding factor in functional MRI. Here we investigate whether HM during resting state functional MRI (RS-fMRI) is influenced by genetic factors in a sample of 462 twins (65% female; 101 MZ (monozygotic) and 130 DZ (dizygotic) twin pairs; mean age: 21 (SD = 3.16), range 16-29). Heritability estimates for three HM components-mean translation (MT), maximum translation (MAXT) and mean rotation (MR)-ranged from 37 to 51%. We detected a significant common genetic influence on HM variability, with about two-thirds (genetic correlations range 0.76-1.00) of the variance shared between MR, MT and MAXT. A composite metric (HM-PC1), which aggregated these three, was also moderately heritable (h(2) = 42%). Using a sub-sample (N = 35) of the twins we confirmed that mean and maximum translational and rotational motions were consistent "traits" over repeated scans (r = 0.53-0.59); reliability was even higher for the composite metric (r = 0.66). In addition, phenotypic and cross-trait cross-twin correlations between HM and resting state functional connectivities (RS-FCs) with Brodmann areas (BA) 44 and 45, in which RS-FCs were found to be moderately heritable (BA44: h(2) = 0.23 (sd = 0.041), BA45: h(2) = 0.26 (sd = 0.061)), indicated that HM might not represent a major bias in genetic studies using FCs. Even so, the HM effect on FC was not completely eliminated after regression. HM may be a valuable endophenotype whose relationship with brain disorders remains to be elucidated.

Keywords: Broca's area; Head motion; Heritability; Resting state fMRI; Twin study.

Figure 1. The Common pathway model showing parameter estimates and covariation between MT, MAXT and MR

In the path diagram, the square boxes represent the observed variables (phenotypes), and the circles the latent variables (A, C, E). A_c and E_c are the Additive genetic and Environmental effects common to the 3 HM measures through the latent HM factor (oval). A_s and E_s are, for each HM variable the specific additive genetic and environment effects. Path coefficients (standardized) are presented in bold. Below each is the percentage of variance for the HM measurement and the latent variable, followed by its 95% confidence interval. Heritability estimates for each HM measure are shown below each HM variable name.

Figure 2. Heritability map of BA45’s network and effect of head motion on the network’s FC

(A) Heritability map of the BA45’s network (heat-map) and corresponding –log(p-values) map (purple) (B) HM-PC1 effect on BA45’s FC with beta maps and corresponding –log(p-values) The negative betas are shown in cold colours (with strongest effect corresponding to green), positive betas are plotted with warm colours (the strongest effect being white). Therefore, all the colorbars rank effect/significance from low to high (i.e. left to right). Effect size and significance are plotted voxel-wise. Heritability and HM effects are projected onto brain maps after averaging the signal (using 12 voxels depth resolution) using MRIcron (Rorden and Brett, 2000). We plotted the top 80% of voxels for heritability and motion effect to facilitate the reading of the image. No thresholding was applied on the p-values maps and significance of all the voxels considered is presented.

Figure 3. Heritability map of BA44’s network and effect of head motion on the network’s FC

(A) Heritability map of the BA44’s network (heat-map) and corresponding –log(p-values) map (purple) (B) HM-PC1 effect on BA44’s FC with beta maps and corresponding –log(p-values) The negative betas are shown in cold colours (with strongest effect corresponding to green), positive betas are plotted with warm colours (the strongest effect being white). Therefore, all the colorbars rank effect/significance from low to high (i.e. left to right). Effect size and significance are plotted voxel-wise. Heritability and HM effects are projected onto brain maps after averaging the signal (using 12 voxels depth resolution) using MRIcron (Rorden and Brett, 2000). We plotted the top 80% of voxels for heritability and motion effect to facilitate the reading of the image. No thresholding was applied on the p-values maps and significance of all the voxels considered is presented.