CORRELATION OF GREY MATTER NETWORK MEASURES IN COGNITIVELY HEALTHY ELDERLY MONOZYGOTIC TWIN PAIRS

Abstract

Grey matter connectivity is disrupted in Alzheimer's disease (AD), and has been associated with amyloid pathology and cognitive decline in non-demented subjects. The contribution of genetic and environmental factors to grey matter connectivity is currently unknown. To estimate the upper limit of genetic contribution to grey matter connectivity, we examined the similarity of this measure in cognitively healthy elderly monozygotic twin pairs. Monozygotic twin pairs were selected from the EMIF-AD PreclinAD study. Inclusion criteria were age ≥ 60 years and having a delayed recall score less than 1.5 SD of normative data. Single-subject grey matter networks were constructed from structural MRI. Small regions of interest were connected when they showed statistical similarity in cortical grey matter structure. We calculated network size, degree, connectivity density, betweenness centrality, normalized clustering coefficient and normalized path length. Monozygotic twin pair correlations were assessed for each connectivity measure after adjusting for age, gender and total grey matter volume. Since monozygotic twins are genetically identical, within pair correlations reflect the upper limit of genetic contribution to a trait. Correlations analyses were repeated for random (non-twin) pairings of subjects. We included 96 monozygotic twin pairs (n = 192 subjects) (age = 70.2 ± 7.3 years; 112 (58%) females; MMSE = 29.0 ± 1.1). All grey matter network properties were correlated in monozygotic twin pairs (figure 1). The highest correlation was found for network size (0.82, p<0.001) and lowest for connectivity density (0.45, p<0.001). The other correlations were: degree (0.53, p<0.001), betweenness centrality (0.79, p<0.001), normalized clustering coefficient (0.68, p<0.001), normalized path length (0.76, p<0.001). Estimating the correlation in non-twin pairs did not yield any significant results. In cognitively healthy elderly monozygotic twins, we found significant within pair correlations of grey matter connectivity. These data suggest that in addition to a moderate-strong genetic background for grey matter connectivity, also non-genetic factors substantially influence this trait. Future studies will focus on identifying environmental risk factors for grey matter connectivity disruptions and determinants of twin discordance. This work has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking EMIF grant agreement n°115372. Correlation of grey matter connectivity measures in monozygotic twins. Displayed are standardized residuals after correcting for age, gender, total grey matter volume. Betweenness centrality, normalized clustering coefficient and normalized path length were additionally corrected for connectivity density. rMZ = Pearson correlation within monozygotic twin pairs.