Neuroimaging studies examining the effects of aging and neuropsychiatric disorders on the cerebral cortex have largely been based on measures of cortical volume. Given that cortical volume is a product of thickness and surface area, it is plausible that measures of volume capture at least 2 distinct sets of genetic influences. The present study aims to examine the genetic relationships between measures of cortical surface area and thickness. Participants were men in the Vietnam Era Twin Study of Aging (110 monozygotic pairs and 92 dizygotic pairs). Mean age was 55.8 years (range: 51-59). Bivariate twin analyses were utilized in order to estimate the heritability of cortical surface area and thickness, as well as their degree of genetic overlap. Total cortical surface area and average cortical thickness were both highly heritable (0.89 and 0.81, respectively) but were essentially unrelated genetically (genetic correlation = 0.08). This pattern was similar at the lobar and regional levels of analysis. These results demonstrate that cortical volume measures combine at least 2 distinct sources of genetic influences. We conclude that using volume in a genetically informative study, or as an endophenotype for a disorder, may confound the underlying genetic architecture of brain structure.
The impact of genetic and environmental factors on human brain structure is of great importance for understanding normative cognitive and brain aging as well as neuropsychiatric disorders. However, most studies of genetic and environmental influences on human brain structure have either focused on global measures or have had samples that were too small for reliable estimates. Using the classical twin design, we assessed genetic, shared environmental, and individualspecific environmental influences on individual differences in the size of 96 brain regions of interest (ROIs). Participants were 474 middle-aged male twins (202 pairs; 70 unpaired) in the Vietnam Era Twin Study (VETSA). They were 51-59 years old, and were similar to U.S. men in their age range in terms of sociodemographic and health characteristics. We measured thickness of cortical ROIs and volume of other ROIs. On average, genetic influences accounted for © 2009 Elsevier Inc. All rights reserved.Correspondence to: William S. Kremen, Ph.D., Department of Psychiatry, University of California, San Diego, 9500 Gilman Drive (MC 0738), La Jolla, CA 92093 Tel: 858-822-2393 Fax: 858-822-5856 wkremen@ucsd.edu. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access Author ManuscriptNeuroimage. Author manuscript; available in PMC 2012 July 16. Elucidating the extent to which genetic and environmental factors influence adult brain structure is of great importance for understanding age-related normal and pathological changes in brain and cognition. Twin studies provide the optimal behavioral genetic method for clarifying this issue because they make it possible to decompose the variance of any variable into genetic, shared environmental influences, and individual-specific environmental influences. The twin method also complements molecular genetic approaches in that heritability-the proportion of phenotypic variance due to genes-is a key component for selection of phenotypes.Despite many published magnetic resonance imaging (MRI) studies involving twins (reviewed by Glahn et al., 2007;Peper et al., 2007;Schmitt et al., 2007a), the picture regarding the heritability of specific brain regions remains incomplete. In some studies, samples sizes were quite small and are thus likely to provide unstable estimates (Visscher, 2004). With a couple of exceptions, relatively few specific regions of interest (ROIs) have been examined. The different ROIs that have been measured in previous studies have often been examined in different samples. It would be advantageous to be able to compare heritabilities of differen...
Understanding the genetic and environmental contributions to measures of brain structure such as surface area and cortical thickness is important for a better understanding of the nature of brain-behavior relationships and changes due to development or disease. Continuous spatial maps of genetic influences on these structural features can contribute to our understanding of regional patterns of heritability, since it remains to be seen whether genetic contributions to brain structure respect the boundaries of any traditional parcellation approaches. Using data from magnetic resonance imaging scans collected on a large sample of monozygotic and dizygotic twins in the Vietnam Era Twin Study of Aging, we created maps of the heritability of areal expansion (a vertex-based area measure) and cortical thickness and examined the degree to which these maps were affected by adjustment for total surface area and mean cortical thickness. We also compared the approach of estimating regional heritability based on the average heritability of vertices within the region to the more traditional region-of-interest (ROI)-based approach. The results suggested high heritability across the cortex for areal expansion and, to a slightly lesser degree, for cortical thickness. There was a great deal of genetic overlap between global and regional measures for surface area, so maps of region-specific genetic influences on surface area revealed more modest heritabilities. There was greater inter-regional variability in heritabilities when calculated using the traditional ROI-based approach compared to summarizing vertex-by-vertex heritabilities within regions. Discrepancies between the approaches were greatest in small regions and tended to be larger for surface area than for cortical thickness measures. Implications regarding brain phenotypes for future genetic association studies are discussed.
Cortical surface area measures appear to be functionally relevant and distinct in etiology, development, and behavioral correlates compared with other size characteristics, such as cortical thickness. Little is known about genetic and environmental influences on individual differences in regional surface area in humans. Using a large sample of adult twins, we determined relative contributions of genes and environment on variations in regional cortical surface area as measured by magnetic resonance imaging before and after adjustment for genetic and environmental influences shared with total cortical surface area. We found high heritability for total surface area and, before adjustment, moderate heritability for regional surface areas. Compared with other lobes, heritability was higher for frontal lobe and lower for medial temporal lobe. After adjustment for total surface area, regionally specific genetic influences were substantially reduced, although still significant in most regions. Unlike other lobes, left frontal heritability remained high after adjustment. Thus, global and regionally specific genetic factors both influence cortical surface areas. These findings are broadly consistent with results from animal studies regarding the evolution and development of cortical patterning and may guide future research into specific environmental and genetic determinants of variation among humans in the surface area of particular regions.
High levels of cortisol, a sign of potential hypothalamic-pituitary-adrenal (HPA) axis dysregulation, have been associated with poor cognitive outcomes in older adults. Most cortisol research has focused on hippocampal-related abilities such as episodic memory; however, the presence of glucocorticoid receptors in the human prefrontal cortex suggests that cortisol regulation is likely to be associated with prefrontally-mediated executive function abilities. We hypothesized that elevated cortisol levels would be associated with poorer frontal-executive function in addition to episodic memory. We assessed cortisol from 15 saliva samples paralleling individual diurnal rhythms across three non-consecutive days in a group of 778 middle-aged twin men ages 51 to 60. Cognitive domains created from 24 standard measures included: general cognitive ability, verbal and visual-spatial ability, verbal and visual-spatial memory, short-term/ immediate memory, working memory, executive function, verbal fluency, abstract reasoning, and psychomotor processing speed. Adjusting for general cognitive ability at age 20, age, race, and multiple health and lifestyle indicators, higher levels of average area-under-the-curve cortisol output across three days were significantly associated with poorer performance in three domains: executive (primarily set-shifting) measures, processing speed, and visual-spatial memory. In a 35-year longitudinal component of the study, we also found that general cognitive ability at age 20 was a significant predictor of midlife cortisol levels. These results possibly support the notion that glucocorticoid exposure is associated with cognitive functions that are mediated by frontal-striatal systems, and is not specific to hippocampal-dependent memory. The results also suggest that the direction of effect is complex.
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