Review of twin and family studies on neuroanatomic phenotypes and typical neurodevelopment

Timing of lifespan influences on brain and cognition

Modifiable risk and protective factors for boosting brain and cognitive development and preventing neurodegeneration and cognitive decline are embraced in neuroimaging studies. We call for sobriety regarding the timing and quantity of such influences on brain and cognition. Individual differences in the level of brain and cognition, many of which present already at birth and early in development, appear stable, larger, and more pervasive than differences in change across the lifespan. Incorporating early-life factors, including genetics, and investigating both level and change will reduce the risk of ascribing undue importance and causality to proximate factors in adulthood and older age. This has implications for both mechanistic understanding and prevention.

Genetic and Environmental Variation in Continuous Phenotypes in the ABCD Study®

Twin studies yield valuable insights into the sources of variation, covariation and causation in human traits. The ABCD Study® (abcdstudy.org) was designed to take advantage of four universities known for their twin research, neuroimaging, population-based sampling, and expertise in genetic epidemiology so that representative twin studies could be performed. In this paper we use the twin data to: (i) provide initial estimates of heritability for the wide range of phenotypes assessed in the ABCD Study using a consistent direct variance estimation approach, assuring that both data and methodology are sound; and (ii) provide an online resource for researchers that can serve as a reference point for future behavior genetic studies of this publicly available dataset. Data were analyzed from 772 pairs of twins aged 9-10 years at study inception, with zygosity determined using genotypic data, recruited and assessed at four twin hub sites. The online tool provides twin correlations and both standardized and unstandardized estimates of additive genetic, and environmental variation for 14,500 continuously distributed phenotypic features, including: structural and functional neuroimaging, neurocognition, personality, psychopathology, substance use propensity, physical, and environmental trait variables. The estimates were obtained using an unconstrained variance approach, so they can be incorporated directly into meta-analyses without upwardly biasing aggregate estimates. The results indicated broad consistency with prior literature where available and provided novel estimates for phenotypes without prior twin studies or those assessed at different ages. Effects of site, self-identified race/ethnicity, age and sex were statistically controlled. Results from genetic modeling of all 53,172 continuous variables, including 38,672 functional MRI variables, will be accessible via the user-friendly open-access web interface we have established, and will be updated as new data are released from the ABCD Study. This paper provides an overview of the initial results from the twin study embedded within the ABCD Study, an introduction to the primary research domains in the ABCD study and twin methodology, and an evaluation of the initial findings with a focus on data quality and suitability for future behavior genetic studies using the ABCD dataset. The broad introductory material is provided in recognition of the multidisciplinary appeal of the ABCD Study. While this paper focuses on univariate analyses, we emphasize the opportunities for multivariate, developmental and causal analyses, as well as those evaluating heterogeneity by key moderators such as sex, demographic factors and genetic background.

Associations Between Traumatic Stress, Brain Volumes and Post-traumatic Stress Disorder Symptoms in Children: Data from the ABCD Study

Reduced volumes in brain regions of interest (ROIs), primarily from adult samples, are associated with posttraumatic stress disorder (PTSD). We extended this work to children using data from the Adolescent Brain Cognitive Development (ABCD) Study® (N = 11,848; Mage = 9.92). Structural equation modeling and an elastic-net (EN) machine-learning approach were used to identify potential effects of traumatic events (TEs) on PTSD symptoms (PTSDsx) directly, and indirectly via the volumes 300 subcortical and cortical ROIs. We then estimated the genetic and environmental variation in the phenotypes. TEs were directly associated with PTSDsx (r = 0.92) in children, but their indirect effects (r < 0.0004)-via the volumes of EN-identified subcortical and cortical ROIs-were negligible at this age. Additive genetic factors explained a modest proportion of the variance in TEs (23.4%) and PTSDsx (21.3%), and accounted for most of the variance of EN-identified volumes of four of the five subcortical (52.4-61.8%) three of the nine cortical ROIs (46.4-53.3%) and cerebral white matter in the left hemisphere (57.4%). Environmental factors explained most of the variance in TEs (C = 61.6%, E = 15.1%), PTSDsx (residual-C = 18.4%, residual-E = 21.8%), right lateral ventricle (C = 15.2%, E = 43.1%) and six of the nine EN-identified cortical ROIs (C = 4.0-13.6%, E = 56.7-74.8%). There is negligible evidence that the volumes of brain ROIs are associated with the indirect effects of TEs on PTSDsx at this age. Overall, environmental factors accounted for more of the variation in TEs and PTSDsx. Whereas additive genetic factors accounted for most of the variability in the volumes of a minority of cortical and in most of subcortical ROIs.

Emotionality vs. Other Biobehavioural Traits: A Look at Neurochemical Biomarkers for Their Differentiation

This review highlights the differential contributions of multiple neurochemical systems to temperament traits related and those that are unrelated to emotionality, even though these systems have a significant overlap. The difference in neurochemical biomarkers of these traits is analysed from the perspective of the neurochemical model, Functional Ensemble of Temperament (FET) that uses multi-marker and constructivism principles. Special attention is given to a differential contribution of hypothalamic-pituitary hormones and opioid neuropeptides implicated in both emotional and non-emotional regulation. The review highlights the role of the mu-opioid receptor system in dispositional emotional valence and the role of the kappa-opioid system in dispositional perceptual and behavioural alertness. These opioid receptor (OR) systems, microbiota and cytokines are produced in three neuroanatomically distinct complexes in the brain and the body, which all together integrate dispositional emotionality. In contrast, hormones could be seen as neurochemical biomarkers of non-emotional aspects of behavioural regulation related to the construction of behaviour in fast-changing and current situations. As examples of the role of hormones, the review summarised their contribution to temperament traits of Sensation Seeking (SS) and Empathy (EMP), which FET considers as non-emotionality traits related to behavioural orientation. SS is presented here as based on (higher) testosterone (fluctuating), adrenaline and (low) cortisol systems, and EMP, as based on (higher) oxytocin, reciprocally coupled with vasopressin and (lower) testosterone. Due to the involvement of gonadal hormones, there are sex and age differences in these traits that could be explained by evolutionary theory. There are, therefore, specific neurochemical biomarkers differentiating (OR-based) dispositional emotionality and (hormones-based) body's regulation in fast-changing events. Here we propose to consider dispositional emotionality associated with OR systems as emotionality in a true sense, whereas to consider hormonal ensembles regulating SS and EMP as systems of behavioural orientation and not emotionality.

Identifying Subgroups of Major Depressive Disorder Using Brain Structural Covariance Networks and Mapping of Associated Clinical and Cognitive Variables

Background

Identifying data-driven subtypes of major depressive disorder (MDD) holds promise for parsing the heterogeneity of MDD in a neurobiologically informed way. However, limited studies have used brain structural covariance networks (SCNs) for subtyping MDD.

Methods

This study included 145 unmedicated patients with MDD and 206 demographically matched healthy control subjects, who underwent a structural magnetic resonance imaging scan and a comprehensive neurocognitive battery. Patterns of structural covariance were identified using source-based morphometry across both patients with MDD and healthy control subjects. K-means clustering algorithms were applied on dysregulated structural networks in MDD to identify potential MDD subtypes. Finally, clinical and neurocognitive measures were compared between identified subgroups to elucidate the profile of these MDD subtypes.

Results

Source-based morphometry across all individuals identified 28 whole-brain SCNs that encompassed the prefrontal, anterior cingulate, and orbitofrontal cortices; basal ganglia; and cerebellar, visual, and motor regions. Compared with healthy control subjects, individuals with MDD showed lower structural network integrity in three networks including default mode, ventromedial prefrontal cortical, and salience networks. Clustering analysis revealed two MDD subtypes based on the patterns of structural network abnormalities in these three networks. Further profiling revealed that patients in subtype 1 had younger age of onset and more symptom severity as well as greater deficits in cognitive performance than patients in subtype 2.

Conclusions

Overall, we identified two MDD subtypes based on SCNs that differed in their clinical and cognitive profile. Our results represent a proof-of-concept framework for leveraging these large-scale SCNs to parse heterogeneity in MDD.

Quantifying Genetic and Environmental Influence on Gray Matter Microstructure Using Diffusion MRI

Early neuroimaging work in twin studies focused on studying genetic and environmental influence on gray matter macrostructure. However, it is also important to understand how gray matter microstructure is influenced by genes and environment to facilitate future investigations of their influence in mental disorders. Advanced diffusion MRI (dMRI) measures allow more accurate assessment of gray matter microstructure compared with conventional diffusion tensor measures. To understand genetic and environmental influence on gray matter, we used diffusion and structural MRI data from a large twin and sibling study (N = 840) and computed advanced dMRI measures including return to origin probability (RTOP), which is heavily weighted toward intracellular and intra-axonal restricted spaces, and mean squared displacement (MSD), more heavily weighted to diffusion in extracellular space and large cell bodies in gray matter. We show that while macrostructural features like brain volume are mainly genetically influenced, RTOP and MSD can together tap into both genetic and environmental influence on microstructure.

The Genetic Contributions to Maturational Coupling in the Human Cerebrum: A Longitudinal Pediatric Twin Imaging Study

Although prior studies have demonstrated that genetic factors play the dominant role in the patterning of the pediatric brain, it remains unclear how these patterns change over time. Using 1748 longitudinal anatomic MRI scans from 792 healthy twins and siblings, we quantified how genetically mediated inter-regional associations change over time via multivariate longitudinal structural equation modeling. These analyses found that genetic correlations for both lobar volumes and cortical thickness are dynamic, with relatively static effects on surface area. While genetic correlations for lobar volumes decrease over childhood and adolescence, in general they increase for cortical thickness in the second decade of life. Quantification of how genetic factors influence maturational coupling improves our understanding of typical neurodevelopment and informs future molecular genetic analyses.

A Comprehensive Quantitative Genetic Analysis of Cerebral Surface Area in Youth

The genetics of cortical arealization in youth is not well understood. In this study, we use a genetically informative sample of 677 typically developing children and adolescents (mean age 12.72 years), high-resolution MRI, and quantitative genetic methodology to address several fundamental questions on the genetics of cerebral surface area. We estimate that >85% of the phenotypic variance in total brain surface area in youth is attributable to additive genetic factors. We also observed pronounced regional variability in the genetic influences on surface area, with the most heritable areas seen in primary visual and visual association cortex. A shared global genetic factor strongly influenced large areas of the frontal and temporal cortex, mirroring regions that are the most evolutionarily novel in humans relative to other primates. In contrast to studies on older populations, we observed statistically significant genetic correlations between measures of surface area and cortical thickness (rG = 0.63), suggestive of overlapping genetic influences between these endophenotypes early in life. Finally, we identified strong and highly asymmetric genetically mediated associations between Full-Scale Intelligence Quotient and left perisylvian surface area, particularly receptive language centers. Our findings suggest that spatially complex and temporally dynamic genetic factors are influencing cerebral surface area in our species.SIGNIFICANCE STATEMENT Over evolution, the human cortex has undergone massive expansion. In humans, patterns of neurodevelopmental expansion mirror evolutionary changes. However, there is a sparsity of information on how genetics impacts surface area maturation. Here, we present a systematic analysis of the genetics of cerebral surface area in youth. We confirm prior research that implicates genetics as the dominant force influencing individual differences in global surface area. We also find evidence that evolutionarily novel brain regions share common genetics, that overlapping genetic factors influence both area and thickness in youth, and the presence of strong genetically mediated associations between intelligence and surface area in language centers. These findings further elucidate the complex role that genetics plays in brain development and function.

Human Cortical Thickness Organized into Genetically-determined Communities across Spatial Resolutions

The cerebral cortex may be organized into anatomical genetic modules, communities of brain regions with shared genetic influences via pleiotropy. Such modules could represent novel phenotypes amenable to large-scale gene discovery. This modular structure was investigated with network analysis of in vivo MRI of extended pedigrees, revealing a "multiscale" structure where smaller and larger modules exist simultaneously and in partially overlapping fashion across spatial scales, in contrast to prior work suggesting a specific number of cortical thickness modules. Inter-regional genetic correlations, gene co-expression patterns and computational models indicate that two simple organizational principles account for a large proportion of the apparent complexity in the network of genetic correlations. First, regions are strongly genetically correlated with their homologs in the opposite cerebral hemisphere. Second, regions are strongly genetically correlated with nearby regions in the same hemisphere, with an initial steep decrease in genetic correlation with anatomical distance, followed by a more gradual decline. Understanding underlying organizational principles of genetic influence is a critical step towards a mechanistic model of how specific genes influence brain anatomy and mediate neuropsychiatric risk.

Genome-wide association study of 23,500 individuals identifies 7 loci associated with brain ventricular volume

The volume of the lateral ventricles (LV) increases with age and their abnormal enlargement is a key feature of several neurological and psychiatric diseases. Although lateral ventricular volume is heritable, a comprehensive investigation of its genetic determinants is lacking. In this meta-analysis of genome-wide association studies of 23,533 healthy middle-aged to elderly individuals from 26 population-based cohorts, we identify 7 genetic loci associated with LV volume. These loci map to chromosomes 3q28, 7p22.3, 10p12.31, 11q23.1, 12q23.3, 16q24.2, and 22q13.1 and implicate pathways related to tau pathology, S1P signaling, and cytoskeleton organization. We also report a significant genetic overlap between the thalamus and LV volumes (ρ_genetic = −0.59, p-value = 3.14 × 10⁻⁶), suggesting that these brain structures may share a common biology. These genetic associations of LV volume provide insights into brain morphology.

An increase in the volume of the brain lateral ventricles is a sign of normal aging, but can also be associated with neurological and psychiatric disorders. Here, Vojinovic et al. identify seven genetic loci in a GWA study for ventricular volume in 23,500 individuals and find correlation with thalamus volume.

The role of genes and environment on brain alterations in Major Depressive Disorder: A review of twin studies: Special Section on "Translational and Neuroscience Studies in Affective Disorders". Section Editor, Maria Nobile MD, PhD. This Section of JAD focuses on the relevance of translational and neuroscience studies in providing a better understanding of the neural basis of affective disorders. The main aim is to briefly summaries relevant research findings in clinical neuroscience with particular regards to specific innovative topics in mood and anxiety disorders

BACKGROUND

Although it has been consistently reported the important role of genetic and environmental risk factors on structural and functional alterations in Major Depressive Disorder (MDD), the mechanism and the magnitude of the interactions between specific genetic and/or environmental risk factors on brain structures in this disabling disorder are still elusive. Therefore, in the last two decades an increased interest has been devoted to neuroimaging investigations on monozygotic and dizygotic twin samples mainly because their intrinsic characteristics may help to separate the effects of genetic and environmental risk factors on clinical phenotypes, including MDD.

METHODS

In this context, the present review summarizes results from structural and functional Magnetic Resonance Imaging studies that investigated twin samples in correlation with MDD.

RESULTS

Overall the results confirmed that a) MDD is characterized by significant alterations in selective brain areas presiding over emotion recognition and evaluation, including amygdala, insula and prefrontal cortices, and b) both genetic and environmental risk factors play a key role in the pathophysiology of this disorder.

LIMITATIONS

Few MRI studies exploring MDD in twin samples.

CONCLUSIONS

The specific contribution of both aspects is still not fully elucidated especially because genes and environment have an impact on the same brain areas, which are particularly vulnerable in MDD. Expansion of the current twin sample sizes would help to clearly establish the potential relationship between risk factors and the development of MDD.

The utility of twins in developmental cognitive neuroscience research: How twins strengthen the ABCD research design

The ABCD twin study will elucidate the genetic and environmental contributions to a wide range of mental and physical health outcomes in children, including substance use, brain and behavioral development, and their interrelationship. Comparisons within and between monozygotic and dizygotic twin pairs, further powered by multiple assessments, provide information about genetic and environmental contributions to developmental associations, and enable stronger tests of causal hypotheses, than do comparisons involving unrelated children. Thus a sub-study of 800 pairs of same-sex twins was embedded within the overall Adolescent Brain and Cognitive Development (ABCD) design. The ABCD Twin Hub comprises four leading centers for twin research in Minnesota, Colorado, Virginia, and Missouri. Each site is enrolling 200 twin pairs, as well as singletons. The twins are recruited from registries of all twin births in each State during 2006-2008. Singletons at each site are recruited following the same school-based procedures as the rest of the ABCD study. This paper describes the background and rationale for the ABCD twin study, the ascertainment of twin pairs and implementation strategy at each site, and the details of the proposed analytic strategies to quantify genetic and environmental influences and test hypotheses critical to the aims of the ABCD study.

The ABCD study of neurodevelopment: Identifying neurocircuit targets for prevention and treatment of adolescent substance abuse

Substance use disorders (SUD) can be considered developmental disorders in light of their frequent origins in substance initiation during adolescence. Cross-sectional functional magnetic resonance imaging (fMRI) studies of adolescent substance users or adolescents with SUD have indicated aberrations in brain structures or circuits implicated in motivation, self-control, and mood-regulation. However, attributing these differences to the neurotoxicological effects of chronic substance use has been problematic in that these circuits are also aberrant in at-risk children, such as those with prenatal substance exposure, externalizing disorders (such as conduct disorder), or prodromal internalizing disorders such as depression. To better isolate the effects of substance exposure on the adolescent brain, the newly-launched Adolescent Brain Cognitive Development (ABCD) study, funded by the National Institutes of Health, will follow the neurodevelopmental trajectories of over 11,000 American 9/10-year-olds for 10 years, into emerging adulthood. This study will provide a rich open-access dataset on longitudinal interactions of neurodevelopment, environmental exposures, and childhood psychopathology that confer addiction risk. The ABCD twin study will further clarify genetic versus experiential influences (e.g., substance use) on neurodevelopmental and psychosocial outcomes. Neurocircuitry thought to regulate mood and behavior has been directly normalized by administration of psychoactive medications and by cognitive therapies in adults. Because of this, we contend that ABCD project data will be a crucial resource for prevention and treatment of SUD in adolescence because its cutting-edge neuroimaging and childhood assessments hold potential for discovery of additional targetable brain differences earlier in development that are prognostic of (or aberrant in) SUD. The ABCD sample size will also have the power to illuminate how sex differences, environmental interactions and other individual differences interact with neurodevelopment to inform treatment in different groups of adolescents.

Assessing Variations in Areal Organization for the Intrinsic Brain: From Fingerprints to Reliability

Resting state fMRI (R-fMRI) is a powerful in-vivo tool for examining the functional architecture of the human brain. Recent studies have demonstrated the ability to characterize transitions between functionally distinct cortical areas through the mapping of gradients in intrinsic functional connectivity (iFC) profiles. To date, this novel approach has primarily been applied to iFC profiles averaged across groups of individuals, or in one case, a single individual scanned multiple times. Here, we used a publically available R-fMRI dataset, in which 30 healthy participants were scanned 10 times (10 min per session), to investigate differences in full-brain transition profiles (i.e., gradient maps, edge maps) across individuals, and their reliability. 10-min R-fMRI scans were sufficient to achieve high accuracies in efforts to "fingerprint" individuals based upon full-brain transition profiles. Regarding test-retest reliability, the image-wise intraclass correlation coefficient (ICC) was moderate, and vertex-level ICC varied depending on region; larger durations of data yielded higher reliability scores universally. Initial application of gradient-based methodologies to a recently published dataset obtained from twins suggested inter-individual variation in areal profiles might have genetic and familial origins. Overall, these results illustrate the utility of gradient-based iFC approaches for studying inter-individual variation in brain function.

Longitudinal changes in hippocampal volume in the Edinburgh High Risk Study of Schizophrenia

Schizophrenia is associated with structural brain abnormalities that are likely to be present before disease onset. It remains unclear to what extent these represent general vulnerability indicators or are associated with the developing clinical state itself. It also remains unclear whether such state or trait alterations may be evident at any given time-point, or whether they progress over time. To investigate this, structural brain scans were acquired at two time-points (mean scan-interval 1.87years) in a cohort of young unaffected individuals at high familial risk of schizophrenia (baseline, n=142; follow-up, n=64) and healthy controls (baseline, n=36; follow-up, n=18). Sub-cortical reconstructions of the hippocampus and amygdala were generated using the longitudinal pipeline available with Freesurfer. The high risk cohort was subdivided into individuals that remained well during the study (HR[well], baseline, n=68; follow-up, n=30), transient and/or partial symptoms that were insufficient to support a formal diagnosis (HR[symp], baseline, n=57; follow-up, n=26) and individuals that subsequently developed schizophrenia according to ICD-10 criteria (HR[ill], baseline, n=17; follow-up, n=8). Longitudinal change in the hippocampus and amygdala was compared, focusing first on overall differences between high-risk individuals and controls and then on sub-group differences within the high-risk cohort. We found a significantly altered developmental trajectory for all high risk individuals compared to controls, with controls showing a significant increase in hippocampal volume over time compared to those at high risk. We did not find evidence of altered longitudinal trajectories based on clinical outcome within the high risk cohort. These results suggest that an altered developmental trajectory of hippocampal volume is associated with a general familial predisposition to develop schizophrenia, as this alteration was not related to subsequent clinical outcome.

BrainPrint: a discriminative characterization of brain morphology

We introduce BrainPrint, a compact and discriminative representation of brain morphology. BrainPrint captures shape information of an ensemble of cortical and subcortical structures by solving the eigenvalue problem of the 2D and 3D Laplace-Beltrami operator on triangular (boundary) and tetrahedral (volumetric) meshes. This discriminative characterization enables new ways to study the similarity between brains; the focus can either be on a specific brain structure of interest or on the overall brain similarity. We highlight four applications for BrainPrint in this article: (i) subject identification, (ii) age and sex prediction, (iii) brain asymmetry analysis, and (iv) potential genetic influences on brain morphology. The properties of BrainPrint require the derivation of new algorithms to account for the heterogeneous mix of brain structures with varying discriminative power. We conduct experiments on three datasets, including over 3000 MRI scans from the ADNI database, 436 MRI scans from the OASIS dataset, and 236 MRI scans from the VETSA twin study. All processing steps for obtaining the compact representation are fully automated, making this processing framework particularly attractive for handling large datasets.

Genetic and environmental contributions to the relationships between brain structure and average lifetime cigarette use

Chronic cigarette use has been consistently associated with differences in the neuroanatomy of smokers relative to nonsmokers in case-control studies. However, the etiology underlying the relationships between brain structure and cigarette use is unclear. A community-based sample of male twin pairs ages 51-59 (110 monozygotic pairs, 92 dizygotic pairs) was used to determine the extent to which there are common genetic and environmental influences between brain structure and average lifetime cigarette use. Brain structure was measured by high-resolution structural magnetic resonance imaging, from which subcortical volume and cortical volume, thickness and surface area were derived. Bivariate genetic models were fitted between these measures and average lifetime cigarette use measured as cigarette pack-years. Widespread, negative phenotypic correlations were detected between cigarette pack-years and several cortical as well as subcortical structures. Shared genetic and unique environmental factors contributed to the phenotypic correlations shared between cigarette pack-years and subcortical volume as well as cortical volume and surface area. Brain structures involved in many of the correlations were previously reported to play a role in specific aspects of networks of smoking-related behaviors. These results provide evidence for conducting future research on the etiology of smoking-related behaviors using measures of brain morphology.

Heritable influences on amygdala and orbitofrontal cortex contribute to genetic variation in core dimensions of personality

While many studies have reported that individual differences in personality traits are genetically influenced, the neurobiological bases mediating these influences have not yet been well characterized. To advance understanding concerning the pathway from genetic variation to personality, here we examined whether measures of heritable variation in neuroanatomical size in candidate regions (amygdala and medial orbitofrontal cortex) were associated with heritable effects on personality. A sample of 486 middle-aged (mean=55 years) male twins (complete MZ pairs=120; complete DZ pairs=84) underwent structural brain scans and also completed measures of two core domains of personality: positive and negative emotionality. After adjusting for estimated intracranial volume, significant phenotypic (r(p)) and genetic (r(g)) correlations were observed between left amygdala volume and positive emotionality (r(p)=.16, p<.01; r(g)=.23, p<.05, respectively). In addition, after adjusting for mean cortical thickness, genetic and nonshared-environmental correlations (r(e)) between left medial orbitofrontal cortex thickness and negative emotionality were also observed (r(g)=.34, p<.01; r(e)=-.19, p<.05, respectively). These findings support a model positing that heritable bases of personality are, at least in part, mediated through individual differences in the size of brain structures, although further work is still required to confirm this causal interpretation.

The Genetic Association Between Neocortical Volume and General Cognitive Ability Is Driven by Global Surface Area Rather Than Thickness

Total gray matter volume is associated with general cognitive ability (GCA), an association mediated by genetic factors. It is expectable that total neocortical volume should be similarly associated with GCA. Neocortical volume is the product of thickness and surface area, but global thickness and surface area are unrelated phenotypically and genetically in humans. The nature of the genetic association between GCA and either of these 2 cortical dimensions has not been examined. Humans possess greater cognitive capacity than other species, and surface area increases appear to be the primary driver of the increased size of the human cortex. Thus, we expected neocortical surface area to be more strongly associated with cognition than thickness. Using multivariate genetic analysis in 515 middle-aged twins, we demonstrated that both the phenotypic and genetic associations between neocortical volume and GCA are driven primarily by surface area rather than thickness. Results were generally similar for each of 4 specific cognitive abilities that comprised the GCA measure. Our results suggest that emphasis on neocortical surface area, rather than thickness, could be more fruitful for elucidating neocortical-GCA associations and identifying specific genes underlying those associations.

The heritability of volumes of brain structures and its relationship to age: a review of twin and family studies

Total brain volume (BV) and the volumes of brain substructures are influenced by genes, the magnitude of which changes with age. One approach to the examination of genetic influences on the volumes of brain structures is to determine their heritability using twin and family studies. We reviewed published cross-sectional studies which examined heritability in healthy subjects at different ages. We identified 32 studies, which examined a total of 77 brain volumetric measures. The findings of our review showed that BVs are under significant genetic influence at all ages, although different brain regions showed different heritability levels. Furthermore, the cross-sectional approach of our review found that heritability factor for the majority of BVs declined with age, such as in the total brain and cerebrum, followed by subsequent increment of environmental influences. Overall, this study identified for the first time a cross-sectional pattern for brain structures' heritability changes with age, and suggests the potential for longitudinal investigations in the future.

Conceptual and data-based investigation of genetic influences and brain asymmetry: a twin study of multiple structural phenotypes

Right-left regional cerebral differences are a feature of the human brain linked to functional abilities, aging, and neurodevelopmental and mental disorders. The role of genetic factors in structural asymmetry has been incompletely studied. We analyzed data from 515 individuals (130 monozygotic twin pairs, 97 dizygotic pairs, and 61 unpaired twins) from the Vietnam Era Twin Study of Aging to answer three questions about genetic determinants of brain structural asymmetry: First, does the magnitude of heritability differ for homologous regions in each hemisphere? Despite adequate power to detect regional differences, heritability estimates were not significantly larger in one hemisphere versus the other, except left > right inferior lateral ventricle heritability. Second, do different genetic factors influence left and right hemisphere size in homologous regions? Interhemispheric genetic correlations were high and significant; in only two subcortical regions (pallidum and accumbens) did the estimate statistically differ from 1.0. Thus, there was little evidence for different genetic influences on left and right hemisphere regions. Third, to what extent do genetic factors influence variability in left-right size differences? There was no evidence that variation in asymmetry (i.e., the size difference) of left and right homologous regions was genetically determined, except in pallidum and accumbens. Our findings suggest that genetic factors do not play a significant role in determining individual variation in the degree of regional cortical size asymmetries measured with MRI, although they may do so for volume of some subcortical structures. Despite varying interpretations of existing data, we view the present results as consistent with previous findings.

Genetics of brain structure: contributions from the Vietnam Era Twin Study of Aging

Understanding the genetics of neuropsychiatric disorders requires an understanding of the genetics of brain structure and function. The Vietnam Era Twin Study of Aging (VETSA) is a longitudinal behavioral genetic study focused on cognitive and brain aging. Here, we describe basic science work carried out within the VETSA MRI study that provides meaningful contributions toward the study of neuropsychiatric disorders. VETSA produced the first comprehensive assessment of the heritability of cortical and subcortical brain structure sizes, all within the same individuals. We showed that neocortical thickness and surface area are largely genetically distinct. With continuous neocortical thickness maps, we demonstrated regional specificity of genetic influences, and that genetic factors did not conform to traditional regions of interest (ROIs). However, there was some evidence for different genetic factors accounting for different types of cortex, and for genetic relationships across cortical regions corresponding to anatomical and functional connectivity and brain maturation patterns. With continuous neocortical surface area maps, we confirmed the anterior-posterior gradient of genetic influences on cortical area patterning demonstrated in animal models. Finally, we used twin methods to create the first map of cortical ROIs based entirely on genetically informative data. We conclude that these genetically based cortical phenotypes may be more appropriate for genetic studies than traditional ROIs based on structure or function. Our results also suggest that cortical volume-the product of thickness and surface area-is a problematic phenotype for genetic studies because two independent sets of genes may be obscured. Examples supporting the validity of these conclusions are provided.

Deciphering the role of docosahexaenoic acid in brain maturation and pathology with magnetic resonance imaging

Animal studies have found that deficits in brain docosahexaenoic acid (DHA, 22:6n-3) accrual during perinatal development leads to transient and enduring abnormalities in brain development and function. Determining the relevance of this evidence to brain disorders in humans has been hampered by an inability to determine antimortem brain DHA levels and limitations associated with a postmortem approach. Accordingly, there is a need for alternate or complementary approaches to better understand the role of DHA in cortical function and pathology, and conventional magnetic resonance imaging (MRI) techniques may be ideally suited for this application. A major advantage of neuroimaging is that it permits prospective evaluation of the effects of manipulating DHA status on both clinical and neuroimaging variables. Emerging evidence from MRI studies suggest that greater DHA status is associated with cortical structural and functional integrity, and suggest that reduced DHA status and abnormalities in cortical function observed in psychiatric disorders may be interrelated phenomenon. Preliminary evidence from animal MRI studies support a critical role of DHA in normal brain development. Neuroimaging research in both human and animals therefore holds tremendous promise for developing a better understanding of the role of DHA status in cortical function, as well as for elucidating the impact of DHA deficiency on neuropathological processes implicated in the etiology and progression of neurodevelopmental and psychiatric disorders.

White matter heritability using diffusion tensor imaging in neonatal brains

Understanding genetic and environmental effects on white matter development in the first years of life is of great interest, as it provides insights into the etiology of neurodevelopmental disorders. In this study, the genetic and environmental effects on white matter were estimated using data from 173 neonatal twin subjects. Diffusion tensor imaging scans were acquired around 40 days after birth and were non-rigidly registered to a group-specific atlas and parcellated into 98 ROIs. A model of additive genetic, and common and specific environmental variance components was used to estimate overall and regional genetic and environmental contributions to diffusion parameters of fractional anisotropy, radial diffusivity, and axial diffusivity. Correlations between the regional heritability values and diffusion parameters were also examined. Results indicate that individual differences in overall white matter microstructure, represented by the average diffusion parameters over the whole brain, are heritable, and estimates are higher than found in studies in adults. Estimates of genetic and environmental variance components vary considerably across different white matter regions. Significant positive correlations between radial diffusivity heritability and radial diffusivity values are consistent with regional genetic variation being modulated by maturation status in the neonatal brain: the more mature the region is, the less genetic variation it shows. Common environmental effects are present in a few regions that tend to be characterized by low radial diffusivity. Results from the joint diffusion parameter analysis suggest that multivariate modeling approaches might be promising to better estimate maturation status and its relationship with genetic and environmental effects.

Brain SCALE: brain structure and cognition: an adolescent longitudinal twin study into the genetic etiology of individual differences

From childhood into adolescence, the child's brain undergoes considerable changes in both structure and function. Twin studies are of great value to explore to what extent genetic and environmental factors explain individual differences in brain development and cognition. In The Netherlands, we initiated a longitudinal study in which twins, their siblings and their parents are assessed at three year intervals. The participants were recruited from The Netherlands Twin Register (NTR) and at baseline consisted of 112 families, with 9-year-old twins and an older sibling. Three years later, 89 families returned for follow-up assessment. Data collection included psychometric IQ tests, a comprehensive neuropsychological testing protocol, and parental and self-ratings of behavioral and emotional problems. Physical maturation was measured through assessment of Tanner stages. Hormonal levels (cortisol, luteinizing hormone, follicle-stimulating hormone, testosterone, and estrogens) were assessed in urine and saliva. Brain scans were acquired using 1.5 Tesla Magnetic Resonance Imaging (MRI), which provided volumetric measures and measures of cortical thickness. Buccal swabs were collected for DNA isolation for future candidate gene and genome-wide analysis studies. This article gives an overview of the study and the main findings. Participants will return for a third assessment when the twins are around 16 years old. Longitudinal twin-sibling studies that map brain development and cognitive function at well-defined ages aid in the understanding of genetic influences on normative brain development.

Mapping genetic and environmental influences on cortical surface area of pediatric twins

Cortical surface area has been largely overlooked in genetic studies of human brain morphometry, even though phylogenetic differences in cortical surface area between individuals are known to be influenced by differences in genetic endowment. In this study, we examined the relative contribution of genetic and environmental influences on cortical surface areas in both the native and stereotaxic spaces for a cohort of homogeneously-aged healthy pediatric twins. Bilateral hemispheric surface and all lobar surface areas except the occipital lobes in native space showed high heritable estimates, while the common environmental effect on bilateral occipital lobes reached statistical significance. The proportion of genetic variance for cortical surface areas measured in stereotaxic space was lower than that measured in native space, whereas the unique environmental influences increased. This is reasonable since whole brain volume is also known to be heritable itself and so removing that component of areal variance due to overall brain size via stereotaxic transformation will reduce the genetic proportion. These findings further suggest that cortical surface areas involved in cognitive, attention and emotional processing, as well as in creating and retaining of long-term memories are likely to be more useful for examining the relationship between genotype and behavioral phenotypes.

Prefrontal deviations in function but not volume are putative endophenotypes for schizophrenia

This study sought to systematically investigate whether prefrontal cortex grey matter volume reductions are valid endophenotypes for schizophrenia, specifically investigating their presence in unaffected relatives, heritability, genetic overlap with the disorder itself and finally to contrast their performance on these criteria with putative neuropsychological indices of prefrontal functioning. We used a combined twin and family design and examined four prefrontal cortical regions of interest. Superior and inferior regions were significantly smaller in patients. However, the volumes of these same regions were normal in unaffected relatives and therefore, we could confirm that such deficits were not due to familial effects. Volumes of the prefrontal and orbital cortices were, however, moderately heritable, but neither shared a genetic overlap with schizophrenia. Total prefrontal cortical volume reductions shared a significant unique environmental overlap with the disorder, suggesting that the reductions were not familial. In contrast, prefrontal (executive) functioning deficits were present in the unaffected relatives, were moderately heritable and shared a substantial genetic overlap with liability to schizophrenia. These results suggest that the well recognized prefrontal volume reductions are not related to the same familial influences that increase schizophrenia liability and instead may be attributable to illness related biological changes or indeed confounded by illness trajectory, chronicity, medication or substance abuse, or in fact a combination of some or all of them.

Neuroprogression in bipolar disorder

OBJECTIVE

Recent theories regarding the neuropathology of bipolar disorder suggest that both neurodevelopmental and neurodegenerative processes may play a role. While magnetic resonance imaging has provided significant insight into the structural, functional, and connectivity abnormalities associated with bipolar disorder, research assessing longitudinal changes has been more limited. However, such research is essential to elucidate the pathophysiology of the disorder. The aim of our review is to examine the extant literature for developmental and progressive structural and functional changes in individuals with and at risk for bipolar disorder.

METHODS

We conducted a literature review using MEDLINE and the following search terms: bipolar disorder, risk, child, adolescent, bipolar offspring, MRI, fMRI, DTI, PET, SPECT, cross-sectional, longitudinal, progressive, and developmental. Further relevant articles were identified by cross-referencing with identified manuscripts.

CONCLUSIONS

There is some evidence for developmental and progressive neurophysiological alterations in bipolar disorder, but the interpretation of correlations between neuroimaging findings and measures of illness exposure or age in cross-sectional studies must be performed with care. Prospective longitudinal studies placed in the context of normative developmental and atrophic changes in neural structures and pathways thought to be involved in bipolar disorder are needed to improve our understanding of the neurodevelopmental underpinnings and progressive changes associated with bipolar disorder.

Pilot multimodal twin imaging study of generalized anxiety disorder

BACKGROUND

Generalized anxiety disorder (GAD) is a common chronic condition that is relatively understudied compared to other psychiatric syndromes. Neuroimaging studies have begun to implicate particular neural structures and circuitry in its pathophysiology; however, no genetically informative research has examined the potential sources of reported brain differences.

METHODS

We acquired spectroscopic, volumetric, and diffusion tensor magnetic resonance imaging data from a pilot study of 34 female subjects selected from monozygotic twin pairs based upon their affection status for GAD, and examined brain regions previously implicated in fear and anxiety for their relationship with affection status and genetic risk.

RESULTS

Lifetime GAD associated with increased creatine levels in the amygdala, smaller left hippocampal volume, and lower fractional anisotropy in the uncinate fasciculus which connects amygdala and frontal cortex. In addition, GAD genetic risk predicted increases in myo-inositol in the amygdala and, possibly, glutamate/glutamine/GABA alterations in the hippocampus. The association of lifetime GAD with smaller hippocampal volume was independent of major depression and might represent a common genetic risk marker for internalizing disorders.

CONCLUSIONS

These preliminary data suggest that GAD and its genetic risk factors are likely correlated with volumetric and spectroscopic changes in fear-related limbic structures and their connections with the frontal cortex.

Genetic patterns of correlation among subcortical volumes in humans: results from a magnetic resonance imaging twin study

Little is known about genetic influences on the volume of subcortical brain structures in adult humans, particularly whether there is regional specificity of genetic effects. Understanding patterns of genetic covariation among volumes of subcortical structures may provide insight into the development of individual differences that have consequences for cognitive and emotional behavior and neuropsychiatric disease liability. We measured the volume of 19 subcortical structures (including brain and ventricular regions) in 404 twins (110 monozygotic and 92 dizygotic pairs) from the Vietnam Era Twin Study of Aging and calculated the degree of genetic correlation among these volumes. We then examined the patterns of genetic correlation through hierarchical cluster analysis and by principal components analysis. We found that a model with four genetic factors best fit the data: a Basal Ganglia/Thalamus factor; a Ventricular factor; a Limbic factor; and a Nucleus Accumbens factor. Homologous regions from each hemisphere loaded on the same factors. The observed patterns of genetic correlation suggest the influence of multiple genetic influences. There is a genetic organization among structures which distinguishes between brain and cerebrospinal fluid spaces and between different subcortical regions. Further study is needed to understand this genetic patterning and whether it reflects influences on early development, functionally dependent patterns of growth or pruning, or regionally specific losses due to genes involved in aging, stress response, or disease.

A twin study of attachment style in young adults

The relative contribution of genetic and environmental influences to individual differences in attachment security is still incompletely understood. We assessed attachment style with the Experiences in Close Relationships questionnaire in a volunteer sample of 677 twins (43% male) ages 23-24 years drawn from the population-based Italian Twin Register, who belonged to 244 complete pairs (46% monozygotic) and 189 unmatched pairs. Genetic structural equation modeling was performed with the Mx program. Genetic effects accounted for 45% and 36% of individual differences in attachment-related anxiety and avoidance, respectively. Furthermore, the covariation between anxiety and avoidance was found to be mainly due to genetic factors, with heritability of the latent attachment security phenotype estimated at 62%. Unshared environmental factors explained the remaining proportion of variance. Although our findings are best regarded as preliminary given some study limitations, they suggest that both nature and nurture contribute to individual differences in adult attachment.

Genetic and environmental influences of white and gray matter signal contrast: a new phenotype for imaging genetics?

The estimation of cortical thickness is in part dependent on the degree of contrast in T1 signal intensity between white matter and gray matter along the cortical mantle. The ratio of white matter to gray matter signal (WM/GM contrast) has been found to vary as a function of age and Alzheimer's disease status, suggesting a biological component to what might otherwise be labeled as a nuisance variable. The aim of the present study was to determine if measures of WM/GM contrast are genetically influenced, as well as the degree to which this phenotype may be related to the genetic and environment determinants of cortical thickness. Participants were 514 male twins (130 monozygotic, 97 dizygotic pairs, and 60 unpaired individuals) from the Vietnam Era Twin Study of Aging. Ages ranged from 51 to 59 years. Measures of WM/GM contrast and cortical thickness were derived for 66 cortical regions of interest (ROI) using FreeSurfer-based methods. Univariate and bivariate twin analyses were used in order to estimate the heritability of WM/GM contrast, as well as the degree of shared genetic and environmental variance between WM/GM contrast and cortical thickness. WM/GM contrast was found to be significantly heritable in the majority of ROIs. The average heritability across individual ROIs was highest in the occipital lobe (.50), and lowest in the cingulate cortex (.24). Significant phenotypic correlations between WM/GM contrast and cortical thickness were observed for most of the ROIs. The majority of the phenotypic correlations were negative, ranging from ?.11 to ?.54. Of the 66 associations, only 17 significant genetic correlations were found, ranging from ?.16 to ?.34, indicating small amounts of shared genetic variance. The majority of the phenotypic correlations were accounted for by small unique environmental effects common between WM/GM contrast and cortical thickness. These findings demonstrate that like cortical thickness, WM/GM contrast is a genetically influenced brain structure phenotype. The lack of significant genetic correlations with cortical thickness suggests that this measure potentially represents a unique source of genetic variance, one that has yet to be explored by the field of imaging genetics.

The limits of brain determinacy

The genes do not control everything that happens in a cell or an organism, because thermally induced molecular movements and conformation changes are beyond genetic control. The importance of uncontrolled events has been argued from the differences between isogenic organisms reared in virtually identical environments, but these might alternatively be attributed to subtle, undetected differences in the environment. The present review focuses on the uncontrolled events themselves in the context of the developing brain. These are considered at cellular and circuit levels because even if cellular physiology was perfectly controlled by the genes (which it is not), the interactions between different cells might still be uncoordinated. A further complication is that the brain contains mechanisms that buffer noise and others that amplify it. The final resultant of the battle between these contrary mechanisms is that developmental stochasticity is sufficiently low to make neurobehavioural defects uncommon, but a chance component of neural development remains. Thus, our brains and behaviour are not entirely determined by a combination of genes-plus-environment.

Genetic influences on cortical regionalization in the human brain

Animal data demonstrate that the development of distinct cortical areas is influenced by genes that exhibit highly regionalized expression patterns. In this paper, we show genetic patterning of cortical surface area derived from MRI data from 406 adult human twins. We mapped genetic correlations of areal expansion between selected seed regions and all other cortical locations, with the selection of seed points based on results from animal studies. "Marching seeds" and a data-driven, hypothesis-free, fuzzy-clustering approach provided convergent validation. The results reveal strong anterior-to-posterior graded, bilaterally symmetric patterns of regionalization, largely consistent with patterns previously reported in nonhuman mammalian models. Broad similarities in genetic patterning between rodents and humans might suggest a conservation of cortical patterning mechanisms, whereas dissimilarities might reflect the functionalities most essential to each species.

Prefrontal and striatal volumes in monozygotic twins concordant and discordant for schizophrenia

Frontostriatal networks mediating important cognitive and motor functions have been shown to be abnormal structurally and functionally in schizophrenia. However, the influence of genetic risk for schizophrenia on structural abnormalities in these areas is not well established. This study therefore aimed to investigate prefrontal and striatal volume alterations in schizophrenia and to define the extent to which they are dependent on genetic vulnerability for the condition. We employed structural magnetic resonance imaging (sMRI) in monozygotic (MZ) twins with or without schizophrenia. A sample of 129 twins completed sMRI, consisting of 21 MZ twin pairs concordant for schizophrenia, 17 MZ schizophrenic twins and 18 MZ nonschizophrenic twins drawn from 19 pairs discordant for schizophrenia, and 26 MZ control twin pairs without schizophrenia. Groups did not significantly differ in age, gender, handedness, height, level of education, parental socioeconomic status, and ethnicity. Using a region-of-interest approach, we measured the gray matter volumes (in cm(3)) of superior, middle, inferior, and orbital frontal cortices (SFC, MFC, IFC, and OFC, respectively); the caudate; and putamen. Covarying for whole-brain volume, age, and gender, we found that concordant but not discordant twins with schizophrenia had significantly lower volumes of MFC and OFC than control twins. In contrast, both patient groups had significantly lower SFC volumes than both groups of nonschizophrenic twins. There were no significant group differences in IFC and the striatum. We conclude that the prefrontal cortex shows a heterogeneous pattern of genetic influences on volumetric reductions in schizophrenia.

Heritability of volumetric brain changes and height in children entering puberty

The human brain undergoes structural changes in children entering puberty, while simultaneously children increase in height. It is not known if brain changes are under genetic control, and whether they are related to genetic factors influencing the amount of overall increase in height. Twins underwent magnetic resonance imaging brain scans at age 9 (N = 190) and 12 (N = 125). High heritability estimates were found at both ages for height and brain volumes (49-96%), and high genetic correlation between ages were observed (r(g) > 0.89). With increasing age, whole brain (+1.1%), cerebellum (+4.2%), cerebral white matter (+5.1%), and lateral ventricle (+9.4%) volumes increased, and third ventricle (-4.0%) and cerebral gray matter (-1.6%) volumes decreased. Children increased on average 13.8 cm in height (9.9%). Genetic influences on individual difference in volumetric brain and height changes were estimated, both within and across traits. The same genetic factors influenced both cerebral (20% heritable) and cerebellar volumetric changes (45%). Thus, the extent to which changes in cerebral and cerebellar volumes are heritable in children entering puberty are due to the same genes that influence change in both structures. The increase in height was heritable (73%), and not associated with cerebral volumetric change, but positively associated with cerebellar volume change (r(p) = 0.24). This association was explained by a genetic correlation (r(g) = 0.48) between height and cerebellar change. Brain and body each expand at their own pace and through separate genetic pathways. There are distinct genetic processes acting on structural brain development, which cannot be explained by genetic increase in height.

Genetic influences on thinning of the cerebral cortex during development

During development from childhood to adulthood the human brain undergoes considerable thinning of the cerebral cortex. Whether developmental cortical thinning is influenced by genes and if independent genetic factors influence different parts of the cortex is not known. Magnetic resonance brain imaging was done in twins at age 9 (N = 190) and again at age 12 (N = 125; 113 repeated measures) to assess genetic influences on changes in cortical thinning. We find considerable thinning of the cortex between over this three year interval (on average 0.05 mm; 1.5%), particularly in the frontal poles, and orbitofrontal, paracentral, and occipital cortices. Cortical thinning was highly heritable at age 9 and age 12, and the degree of genetic influence differed for the various areas of the brain. One genetic factor affected left inferior frontal (Broca's area), and left parietal (Wernicke's area) thinning; a second factor influenced left anterior paracentral (sensory-motor) thinning. Two factors influenced cortical thinning in the frontal poles: one of decreasing influence over time, and another independent genetic factor emerging at age 12 in left and right frontal poles. Thus, thinning of the cerebral cortex is heritable in children between the ages 9 and 12. Furthermore, different genetic factors are responsible for variation in cortical thickness at ages 9 and 12, with independent genetic factors acting on cortical thickness across time and between various brain areas during childhood brain development.

Heritability of working memory brain activation

Although key to understanding individual variation in task-related brain activation, the genetic contribution to these individual differences remains largely unknown. Here we report voxel-by-voxel genetic model fitting in a large sample of 319 healthy, young adult, human identical and fraternal twins (mean ± SD age, 23.6 ± 1.8 years) who performed an n-back working memory task during functional magnetic resonance imaging (fMRI) at a high magnetic field (4 tesla). Patterns of task-related brain response (BOLD signal difference of 2-back minus 0-back) were significantly heritable, with the highest estimates (40-65%) in the inferior, middle, and superior frontal gyri, left supplementary motor area, precentral and postcentral gyri, middle cingulate cortex, superior medial gyrus, angular gyrus, superior parietal lobule, including precuneus, and superior occipital gyri. Furthermore, high test-retest reliability for a subsample of 40 twins indicates that nongenetic variance in the fMRI brain response is largely due to unique environmental influences rather than measurement error. Individual variations in activation of the working memory network are therefore significantly influenced by genetic factors. By establishing the heritability of cognitive brain function in a large sample that affords good statistical power, and using voxel-by-voxel analyses, this study provides the necessary evidence for task-related brain activation to be considered as an endophenotype for psychiatric or neurological disorders, and represents a substantial new contribution to the field of neuroimaging genetics. These genetic brain maps should facilitate discovery of gene variants influencing cognitive brain function through genome-wide association studies, potentially opening up new avenues in the treatment of brain disorders.

Genetic influences on alexithymia and their relationship with depressive symptoms

OBJECTIVE

The factors involved in the etiology of alexithymia are still unclear. While a few studies suggested substantial genetic influences on alexithymia, it remains to be determined if these influences are independent of genetic influences on other mental health variables correlated with alexithymia, such as depression. This study is aimed at confirming previous findings of a genetic contribution to alexithymia, examining whether there are genetic or environmental influences common to alexithymia facets, and investigating whether genetic influences on alexithymia are independent of genetic influences on depression.

METHODS

The 20-item Toronto Alexithymia Scale and a validated measure of depression were administered to a sample of 729 twins (45% males) aged 23-24 years drawn from the population-based Italian Twin Register. Genetic structural equation modeling was performed with the Mx program.

RESULTS

Genetic factors accounted for 42% of individual differences in alexithymia. Unshared environmental factors explained the remaining proportion of variance. There was a substantial (0.65) genetic correlation between alexithymia and depression. The inclusion of depression as a covariate in the genetic models reduced the heritability estimate for alexithymia to 33%.

CONCLUSIONS

Despite some limitations, this study corroborates the notion that genetic factors contribute substantially to individual differences in alexithymia, with unshared environmental factors also playing an important role. Also, it suggests a genetic link between alexithymia and depression.

Genetic influences on hippocampal volume differ as a function of testosterone level in middle-aged men

The hippocampus expresses a large number of androgen receptors; therefore, in men it is potentially vulnerable to the gradual age-related decline of testosterone levels. In the present study we sought to elucidate the nature of the relationship between testosterone and hippocampal volume in a sample of middle-aged male twins (average age 55.8 years). We found no evidence for a correlation between testosterone level and hippocampal volume, as well as no indication of shared genetic influences. However, a significant moderating effect of testosterone on the genetic and environmental determinants of hippocampal volume was observed. Genetic influences on hippocampal volume increased substantially as a function of increasing testosterone level, while environmental influences either decreased or remained stable. These findings provide evidence for an apparent gene-by-hormone interaction on hippocampal volume. To the best of our knowledge, this is the first study to demonstrate that the heritability of a brain structure in adults may be modified by an endogenous biological factor.

Putative structural neuroimaging endophenotypes in schizophrenia: a comprehensive review of the current evidence

The genetic contribution to schizophrenia etiopathogenesis is underscored by the fact that the best predictor of developing schizophrenia is having an affected first-degree relative, which increases lifetime risk by tenfold, as well as the observation that when both parents are affected, the risk of schizophrenia increases to approximately 50%, compared with 1% in the general population. The search to elucidate the complex genetic architecture of schizophrenia has employed various approaches, including twin and family studies to examine co-aggregation of brain abnormalities, studies on genetic linkage and studies using genome-wide association to identify genetic variations associated with schizophrenia. ‘Endophenotypes’, or ‘intermediate phenotypes’, are potentially narrower constructs of genetic risk. Hypothetically, they are intermediate in the pathway between genetic variation and clinical phenotypes and can supposedly be implemented to assist in the identification of genetic diathesis for schizophrenia and, possibly, in redefining clinical phenomenology.

Genetic architecture of context processing in late middle age: more than one underlying mechanism

Studies comparing young and older adults suggest a deficit in processing context information as a key mechanism underlying cognitive aging. However, the genetic architecture of context processing has not been examined. Consistent with previous results, we found evidence of functionally dissociable components of context processing accuracy in 1127 late middle-aged twins ages 51-60. One component emphasizes use of context cues to prepare responses (proactive cognitive control), and the other emphasizes adjustment of responses after probes are presented (reactive control). Approximately one-quarter of the variance in each component was accounted for by genes. Multivariate twin analysis indicated that genetic factors underlying two important components of context processing were independent of one another, thus implicating more than one underlying mechanism. Slower reaction time (RT) on noncontext processing trials was positively correlated with errors on the strongly proactive control component on which young adults outperform older adults, but RT was negatively correlated with errors on the strongly reactive control component on which older adults perform better. Although this RT measure was uncorrelated with chronological age in our age-homogeneous sample, slower RT was associated with performance patterns that were more like older adults. However, this did not generalize to other processing speed measures. Genetic correlations, which reflect shared genetic variance, paralleled the phenotypic correlations. There was also a positive genetic correlation between general cognitive ability and accuracy on the proactive control component, but there were still mostly distinct genetic influences underlying these measures. In contrast, the reactive control component was unrelated to general cognitive ability.

How does your cortex grow?

Understanding human cortical maturation is a central goal for developmental neuroscience. Significant advances toward this goal have come from two recent strands of in vivo structural magnetic resonance imaging research: (1) longitudinal study designs have revealed that factors such as sex, cognitive ability, and disease are often better related to variations in the tempo of anatomical change than to variations in anatomy at any one time point; (2) largely cross-sectional applications of new surface-based morphometry (SBM) methods have shown how the traditional focus on cortical volume (CV) can obscure information about the two evolutionarily and genetically distinct determinants of CV: cortical thickness (CT) and surface area (SA). Here, by combining these two strategies for the first time and applying SBM in >1250 longitudinally acquired brain scans from 647 healthy individuals aged 3-30 years, we deconstruct cortical development to reveal that distinct trajectories of anatomical change are hidden within, and give rise to, a curvilinear pattern of CV maturation. Developmental changes in CV emerge through the sexually dimorphic and age-dependent interaction of changes in CT and SA. Moreover, SA change itself actually reflects complex interactions between brain size-related changes in exposed cortical convex hull area, and changes in the degree of cortical gyrification, which again vary by age and sex. Knowing of these developmental dissociations, and further specifying their timing and sex-biases, provides potent new research targets for basic and clinical neuroscience.

Heritability of verbal and performance intelligence in a pediatric longitudinal sample

The longitudinal stability of IQ is well-documented as is its increasing heritability with age. In a longitudinal twin study, we addressed the question to what extent heritability and stability differ for full scale (FSIQ), verbal (VIQ), and performance IQ (PIQ) in childhood (age 9-11 years), and early adolescence (age 12-14 years). Genetic and environmental influences and correlations over time were evaluated in an extended twin design, including Dutch twins and their siblings. Intelligence was measured by the Wechsler Intelligence Scale for children - Third version (WISC III). Heritability in childhood was 34% for FSIQ, 37% for VIQ, and 64% for PIQ, and increased up to 65%, 51%, and 72% in early adolescence. The influence of common environment decreased between childhood and early adolescence from explaining 43% of the phenotypic variance for FSIQ to 18% and from 42% for VIQ to 26%. For PIQ common environmental influences did not play a role, either in childhood or in early adolescence. The stability in FSIQ and VIQ across the 3-year interval (r(p)) was .72 for both measures and was explained by genetic and common environmental correlations across time (FSIQ, r(g) = .96, r(c) = 1.0; VIQ, r(g) =.78, r(c) = 1.0). Stability of PIQ (r(p) =.56) was lower and was explained by genetic influences (r(g) = .90). These results confirm the robust findings of increased heritability of general cognitive abilities during the transition from childhood to adolescence. Interestingly, results for PIQ differ from those for FSIQ and VIQ, in that no significant contribution of environment shared by siblings from the same family was detected.

Heritability of head size in Dutch and Australian twin families at ages 0-50 years

We assessed the heritability of head circumference, an approximation of brain size, in twin-sib families of different ages. Data from the youngest participants were collected a few weeks after birth and from the oldest participants around age 50 years. In nearly all age groups the largest part of the variation in head circumference was explained by genetic differences. Heritability estimates were 90% in young infants (4 to 5 months), 85-88% in early childhood, 83-87% in adolescence, 75% in young and mid adulthood. In infants younger than 3 months, heritability was very low or absent. Quantitative sex differences in heritability were observed in 15- and 18-year-olds, but there was no evidence for qualitative sex differences, that is, the same genes were expressed in both males and females. Longitudinal analysis of the data between 5, 7, and 18 years of age showed high genetic stability (.78 > R(G) > .98). These results indicate that head circumference is a highly heritable biometric trait and a valid target for future GWA studies.

In-vivo measurement of cortical morphology: means and meanings

PURPOSE OF REVIEW

Study of the variability of the cortical mantle thickness is now a key issue in neuroimaging. Here we describe a more recent trend aiming at the study of the variability of the cortical folding morphology.

RECENT FINDINGS

Computerized three-dimensional versions of gyrification index and other morphometric features dedicated to the folding patterns are modified in psychiatric syndromes and neurologic disorders. These observations provide new insights into the mechanisms involved in abnormal development or abnormal aging.

SUMMARY

Quantification of the folding morphology will contribute to the global endeavor aiming at building biomarkers from neuroimaging data, with a specific focus on developmental diseases.