Variance decomposition of MRI-based covariance maps using genetically informative samples and structural equation modeling.
Variance decomposition of MRI-based covariance maps using genetically informative samples and structural equation modeling.
复制标题
DOI：
10.1016/j.neuroimage.2008.06.039
复制
发表时间：
2009-08-01
期刊：
影响因子：
5.7
通讯作者：
Giedd JN
中科院分区：
文献类型：
--
作者：
Schmitt JE;Lenroot RK;Ordaz SE;Wallace GL;Lerch JP;Evans AC;Prom EC;Kendler KS;Neale MC;Giedd JN
The role of genetics in driving intracortical relationships is an important question that has rarely been studied in humans. In particular, there are no extant high-resolution imaging studies on genetic covariance. In this article, we describe a novel method that combines classical quantitative genetic methodologies for variance decomposition with recently-developed semi-multivariate algorithms for high-resolution measurement of phenotypic covariance. Using these tools, we produced correlational maps of genetic and environmental (i.e. nongenetic) relationships between several regions of interest and the cortical surface in a large pediatric sample of 600 twins, siblings, and singletons. These analyses demonstrated high, fairly uniform, statistically significant genetic correlations between the entire cortex and global mean cortical thickness. In agreement with prior reports on phenotypic covariance using similar methods, we found mean cortical thickness was most strongly correlated with association cortices. However, the present study suggests that genetics plays a large role in global brain patterning of cortical thickness in this manner. Further, using specific gyri with known high heritabilities as seed regions, we found a consistent pattern of high bilateral genetic correlations between structural homologues, with environmental correlations more restricted to the same hemisphere as the seed region, suggesting that interhemispheric covariance is largely genetically mediated. These findings are consistent with the limited existing knowledge on the genetics of cortical variability as well as our prior multivariate studies on cortical gyri.
登录
查看更多内容
影响因子：
1.3
作者：
COLLINS, DL;NEELIN, P;EVANS, AC
通讯作者：
EVANS, AC
影响因子：
2
作者：
Guerrini, Renzo;Marini, Carla
通讯作者：
Marini, Carla
影响因子：
5.7
作者：
Boddaert, N;De Leersnyder, H;Zilbovicius, M
通讯作者：
Zilbovicius, M
影响因子：
5.7
作者：
Genovese, CR;Lazar, NA;Nichols, T
通讯作者：
Nichols, T
影响因子：
5.7
作者：
Kim, JS;Singh, V;Evans, AC
通讯作者：
Evans, AC