Matthew S. Panizzon

Distinct Genetic Influences on Cortical Surface Area and Cortical Thickness

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.

Hierarchical Genetic Organization of Human Cortical Surface Area

Building the Brain Brain connectivity is often described as a network of discrete independent cables analogous to a switchboard, but how is the physical structure of the brain constructed (see the Perspective by Zilles and Amunts)? Wedeen et al. (p. 1628) used high-resolution diffusion tensor imaging in humans and four species of nonhuman primates to identify and compare the geometric structure of large fiber tracts in the brain. Fiber tracts followed a highly constrained and regular geometry, which may provide an efficient solution for pathfinding during ontogenetic development. Much of development occurs through elaboration and assembly of semiautonomous building blocks. Chen et al. (p. 1634) applied statistical analysis to the form of the human cortex in brain-imaging studies that compared more than 400 di- and mono-zygotic twins. The findings suggest that the structure of the human cortex is defined by genetics. Human brain structure is genetically controlled in a hierarchical, modular, and symmetric fashion. Surface area of the cerebral cortex is a highly heritable trait, yet little is known about genetic influences on regional cortical differentiation in humans. Using a data-driven, fuzzy clustering technique with magnetic resonance imaging data from 406 twins, we parceled cortical surface area into genetic subdivisions, creating a human brain atlas based solely on genetically informative data. Boundaries of the genetic divisions corresponded largely to meaningful structural and functional regions; however, the divisions represented previously undescribed phenotypes different from conventional (non–genetically based) parcellation systems. The genetic organization of cortical area was hierarchical, modular, and predominantly bilaterally symmetric across hemispheres. We also found that the results were consistent with human-specific regions being subdivisions of previously described, genetically based lobar regionalization patterns.

Genetic and environmental influences on the size of specific brain regions in midlife: The VETSA MRI study

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 individual-specific 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 of Aging (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 approximately 70% of the variance in the volume of global, subcortical, and ventricular ROIs and approximately 45% of the variance in the thickness of cortical ROIs. There was greater variability in the heritability of cortical ROIs (0.00-0.75) as compared with subcortical and ventricular ROIs (0.48-0.85). The results did not indicate lateralized heritability differences or greater genetic influences on the size of regions underlying higher cognitive functions. The findings provide key information for imaging genetic studies and other studies of brain phenotypes and endophenotypes. Longitudinal analysis will be needed to determine whether the degree of genetic and environmental influences changes for different ROIs from midlife to later life.

Cortical Thickness Is Influenced by Regionally Specific Genetic Factors

BACKGROUND Although global brain structure is highly heritable, there is still variability in the magnitude of genetic influences on the size of specific regions. Yet, little is known about the patterning of those genetic influences, i.e., whether the same genes influence structure throughout the brain or whether there are regionally specific sets of genes. METHODS We mapped the heritability of cortical thickness throughout the brain using three-dimensional structural magnetic resonance imaging in 404 middle-aged male twins. To assess the amount of genetic overlap between regions, we then mapped genetic correlations between three selected seed points and all other points comprising the continuous cortical surface. RESULTS There was considerable regional variability in the magnitude of genetic influences on cortical thickness. The primary visual (V1) seed point had strong genetic correlations with posterior sensory and motor areas. The anterior temporal seed point had strong genetic correlations with anterior frontal regions but not with V1. The middle frontal seed point had strong genetic correlations with inferior parietal regions. CONCLUSIONS These results provide strong evidence of regionally specific patterns rather than a single, global genetic factor. The patterns are largely consistent with a division between primary and association cortex, as well as broadly defined patterns of brain gene expression, neuroanatomical connectivity, and brain maturation trajectories, but no single explanation appears to be sufficient. The patterns do not conform to traditionally defined brain structure boundaries. This approach can serve as a step toward identifying novel phenotypes for genetic association studies of psychiatric disorders and normal and pathological cognitive aging.

Genetic topography of brain morphology

Significance How diverse functional cortical regions develop is an important neuroscience question. Animal experiments show that regional differentiation is controlled by genes that express in a graded and regionalized pattern; however, such investigation in humans is scarce. Using noninvasive imaging techniques to acquire brain structure data of genetically related subjects (i.e., twins), we estimated the spatial pattern of genetic influences on cortical structure. We developed a genetic parcellation of cortical thickness to delineate the boundaries of cortical divisions that are—within each division—maximally under control of shared genetic influences. We also found differences in genetic influences on cortical surface area and thickness along two orthogonal axes. The concept of gradations is crucial for understanding the organization of the human brain. Animal data show that cortical development is initially patterned by genetic gradients largely along three orthogonal axes. We previously reported differences in genetic influences on cortical surface area along an anterior-posterior axis using neuroimaging data of adult human twins. Here, we demonstrate differences in genetic influences on cortical thickness along a dorsal-ventral axis in the same cohort. The phenomenon of orthogonal gradations in cortical organization evident in different structural and functional properties may originate from genetic gradients. Another emerging theme of cortical patterning is that patterns of genetic influences recapitulate the spatial topography of the cortex within hemispheres. The genetic patterning of both cortical thickness and surface area corresponds to cortical functional specializations. Intriguingly, in contrast to broad similarities in genetic patterning, two sets of analyses distinguish cortical thickness and surface area genetically. First, genetic contributions to cortical thickness and surface area are largely distinct; there is very little genetic correlation (i.e., shared genetic influences) between them. Second, organizing principles among genetically defined regions differ between thickness and surface area. Examining the structure of the genetic similarity matrix among clusters revealed that, whereas surface area clusters showed great genetic proximity with clusters from the same lobe, thickness clusters appear to have close genetic relatedness with clusters that have similar maturational timing. The discrepancies are in line with evidence that the two traits follow different mechanisms in neurodevelopment. Our findings highlight the complexity of genetic influences on cortical morphology and provide a glimpse into emerging principles of genetic organization of the cortex.

A Twin Study of Smoking, Nicotine Dependence, and Major Depression in Men

This study examined the nature of the relationship among lifetime major depression, smoking, and nicotine dependence. Subjects were 8,169 male twins from the Vietnam Era Twin Registry. Biometrical modeling demonstrated a genetic influence on daily smoking, nicotine dependence, and major depression, and a family environmental influence on daily smoking. Genetic factors influencing nicotine dependence also strongly influenced major depression. We also compared probands with a history of major depression (n = 398) from pairs discordant for major depression, their nondepressed cotwins (n = 364), and controls (n = 1,863) on a number of secondary smoking outcomes. Major depression was associated with current daily smoking and certain nicotine withdrawal symptoms. Individuals with a familial vulnerability for major depression, even without a personal history of major depression, were more likely to smoke despite a serious illness and to report nervousness, restlessness, difficulty concentrating, and depressed mood during past quit attempts. Among the 237 monozygotic pairs discordant for major depression, depressed probands were more likely to have a lifetime history of nicotine dependence than were cotwins. Findings extend Kendler and colleagues (1993) study of female twins by demonstrating in men that shared genetic factors predispose not only to major depression and daily smoking but also to major depression and nicotine dependence.

Genes Determine Stability and the Environment Determines Change in Cognitive Ability During 35 Years of Adulthood

Previous research has demonstrated stability of cognitive ability and marked heritability during adulthood, but questions remain about the extent to which genetic factors account for this stability. We conducted a 35-year longitudinal assessment of general cognitive ability using the Armed Forces Qualification Test administered to 7,232 male twins in early adulthood and readministered to a subset of 1,237 twins during late middle age. The proportion of variance in cognitive functioning explained by genetic factors was .49 in young adulthood and .57 in late middle age. The correlation between the two administrations was .74 with a genetic correlation of 1.0, indicating that the same genetic influences operated at both times. Genetic factors were primarily responsible for stability, and nonshared environmental factors were primarily responsible for change. The genetic factors influencing cognition may change across other eras, but the same genetic influences are operating from early adulthood to late middle age.

Impulsiveness, impulsive aggression, personality disorder, and spousal violence.

Impulsiveness has become a key concept in thinking about the determinants of violence and aggression. In this study of spouse abusers, the relationship between impulsiveness, impulsive aggression, and physical violence is confirmed. Impulsiveness and impulsive aggression have significant correlations with physical aggression. Impulsiveness and impulsive aggression are also correlated with measures of Borderline Personality Disorder and Antisocial Personality Disorder. In addition, the measures of Borderline and Antisocial Personality Disorder (PD) are significantly correlated with physical aggression. The violent and non-violent groups differed on impulsive aggression and on Borderline Personality Disorder. A partial replication of Tweed and Dutton’s findings (1998) revealed sub-groups of high- and low-violence men. The high-violence group was very different from the low-violent and the non-violent groups. The high-violence group had higher pathology scores on all clinical scales, except Mania, of the Personality Assessment Inventory. These findings have implications for violence prediction and for treatment of violent men.

Genetic and Environmental Contributions to Regional Cortical Surface Area in Humans: A Magnetic Resonance Imaging Twin Study

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.

Salivary cortisol and prefrontal cortical thickness in middle-aged men: A twin study

Although glucocorticoid receptors are highly expressed in the prefrontal cortex, the hippocampus remains the predominant focus in the literature examining relationships between cortisol and brain. We examined phenotypic and genetic associations of cortisol levels with the thickness of prefrontal and anterior cingulate cortex regions, and with hippocampal volume in a sample of 388 middle-aged male twins who were 51-59 years old. Small but significant negative phenotypic associations were found between cortisol levels and the thickness of left dorsolateral (superior frontal gyrus, left rostral middle frontal gyrus) and ventrolateral (pars opercularis, pars triangularis, pars orbitalis) prefrontal regions, and right dorsolateral (superior frontal gyrus) and medial orbital frontal cortex. Most of the associations remained significant after adjusting for general cognitive ability, cardiovascular risk factors, and depression. Bivariate genetic analyses suggested that some of the associations were primarily accounted for by shared genetic influences; that is, some of the genes that tend to result in increased cortisol levels also tend to result in reduced prefrontal cortical thickness. Aging has been associated with reduced efficiency of hypothalamic-pituitary-adrenal function, frontal lobe shrinkage, and increases in health problems, but our present data do not allow us to determine the direction of effects. Moreover, the degree or the direction of the observed associations and the extent of their shared genetic underpinnings may well change as these individuals age. Longitudinal assessments are underway to elucidate the direction of the associations and the genetic underpinnings of longitudinal phenotypes for changes in cortisol and brain morphology.