Genetic relatedness of axial and radial diffusivity indices of cerebral white matter microstructure in late middle age

Abstract

Two basic neuroimaging-based characterizations of white matter tracts are the magnitude of water diffusion along the principal tract orientation (axial diffusivity, AD) and water diffusion perpendicular to the principal orientation (radial diffusivity, RD). It is generally accepted that decreases in AD reflect disorganization, damage, or loss of axons, whereas increases in RD are indicative of disruptions to the myelin sheath. Previous reports have detailed the heritability of individual AD and RD measures, but have not examined the extent to which the same or different genetic or environmental factors influence these two phenotypes (except for corpus callosum). We implemented bivariate twin analyses to examine the shared and independent genetic influences on AD and RD. In the Vietnam Era Twin Study of Aging, 393 men (mean age = 61.8 years, SD = 2.6) underwent diffusion-weighted magnetic resonance imaging. We derived fractional anisotropy (FA), mean diffusivity (MD), AD, and RD estimates for 11 major bilateral white matter tracts and the mid-hemispheric corpus callosum, forceps major, and forceps minor. Separately, AD and RD were each highly heritable. In about three-quarters of the tracts, genetic correlations between AD and RD were >.50 (median = .67) and showed both unique and common variance. Genetic variance of FA and MD were predominately explained by RD over AD. These findings are important for informing genetic association studies of axonal coherence/damage and myelination/demyelination. Thus, genetic studies would benefit from examining the shared and unique contributions of AD and RD.

Multiple mechanisms underpin cerebral and cerebellar white matter deficits in Friedreich ataxia: The IMAGE‐FRDA study

“…Taken together, these findings suggest that FA, AD, MTR, and volume may each provide unique and complementary information in FRDA, with the spatial overlap of between‐group differences possibly representing co‐occurrence of independent pathological processes ‐ for example, white matter volume loss and abnormal white matter microstructure. Furthermore, the strong shared variance between FA and RD may indicate that they reflect similar underlying properties of the white matter (consistent with findings that FA and RD have a high level of shared genetic variance; Hatton et al, ), which likely explains their striking overlap in the between‐group differences shown here and in previous work (e.g., Rezende et al, ). As such, it may be pertinent to be cautious in interpreting FA and RD effects as separate and additive lines of evidence regarding white matter abnormalities in FRDA.…”

Predominantly global genetic influences on individual white matter tract microstructure

“…Diffusion tensor imaging (DTI) estimates the directionality and magnitude of the diffusion of water molecules within the brain, which aids in characterizing white matter microstructure. Findings from twin, family, and association studies have revealed that much of the variability in white matter tracts across multiple DTI metrics is influenced by genetic factors (Chiang et al, 2011; Hatton et al, 2018; Jahanshad et al, 2013; Kochunov et al, 2016; Lee et al, 2017; Vuoksimaa et al, 2017). However, it is unclear to what extent these genetic influences are due to (i) unique factors specific to each tract, or (ii) general variance in white matter across the entire brain.…”

“…However, it is unclear to what extent these genetic influences are due to (i) unique factors specific to each tract, or (ii) general variance in white matter across the entire brain. Greater understanding of the genetic and environmental influences on white matter structure may expedite ongoing efforts to use genome-wide association studies to identify the genetic influences on white matter microstructure (Hatton et al, 2018). This knowledge in turn could improve our understanding of associations between white matter microstructure and outcomes such as cognitive ability, psychiatric disorders, and brain aging.…”

“…However, because Chiang et al’s adolescent heritability estimate was based on a small sample, replication using a much larger sample is required to confirm this age-related trend. More recent findings suggest that the genetic influences on AD and RD within a given tract are moderately correlated (Hatton et al, 2018).…”

“…Finally, we conducted parallel genetic analyses for the AD and RD diffusion metrics, from which FA and MD are calculated. AD and RD share some genetic variance but there are also some genetic influences that are unique to each (Hatton et al, 2018). These analyses are mostly described in the supplementary material.…”