Life-course experiences have been postulated to program hypothalamus–pituitary–adrenal (HPA) axis activity, suggesting that HPA axis activity is, at least partially, stable over time. Yet, there is paucity of data on the long-term stability of cortisol production and metabolism. We performed a prospective follow-up study in twins recruited from a nationwide register to estimate the stability of cortisol production and metabolism over time, and the contribution of genetic and environmental factors to this stability. In total, 218 healthy mono- and dizygotic twins were included. At the ages of 9, 12 and 17 years, morning urine samples were collected for assessment (by gas chromatography-tandem mass spectrometry) of cortisol metabolites, enabling the calculation of cortisol metabolite excretion rate and cortisol metabolism activity. Our results showed a low stability for both cortisol metabolite excretion rate (with correlations <.20) and cortisol metabolism activity indices (with correlations of .25 to .46 between 9 and 12 years, −.02 to .15 between 12 and 17 years and .09 to .28 between 9 and 17 years). Because of the low stability over time, genetic and environmental contributions to this stability were difficult to assess, although it seemed to be mostly determined by genetic factors. The low stability in both cortisol production and metabolism between ages 9 and 17 years reflects the dynamic nature of the HPA axis.

The large body of literature on the association between blood pressure (BP) and cognitive functioning has yielded mixed results, possibly due to the presence of non-linear effects across age, or because BP affects specific brain areas differently, impacting more on some cognitive skills than on others. If a robust association was detected among BP and specific cognitive tasks, the causal nature of reported associations between BP and cognition could be investigated in twin data, which allow a test of alternative explanations, including genetic pleiotropy. The present study first examines the association between BP and cognition in a sample of 1,140 participants with an age range between 10 and 86 years. Linear and quadratic effects of systolic BP (SBP) and diastolic BP (DBP) on cognitive functioning were examined for 17 tests across five functions. Associations were corrected for effects of sex and linear and quadratic effects of age. Second, to test a causal model, data from 123 monozygotic (MZ) twin pairs were analyzed to test whether cognitive functioning of the twins with the higher BP was different from that of the co-twins with lower BP. Associations between BP and cognitive functioning were absent for the majority of the cognitive tests, with the exception of a lower speed of emotion identification and verbal reasoning in subjects with high diastolic BP. In the MZ twin pair analyses, no effects of BP on cognition were found. We conclude that in the population at large, BP level is not associated with cognitive functioning in a clinically meaningful way.

The present study examined the genetic and environmental contributions to the temporal stability of verbal, non-verbal and general intelligence across a developmental period spanning childhood and adolescence (5–18 years). Longitudinal twin data collected in four different studies on a total of 1,748 twins, comprising 4,641 measurement points in total, were analyzed using genetic adaptations of the simplex model. The heterogeneity in the type of instrument used to assess psychometric intelligence across the different subsamples and ages allowed us to address the auxiliary question of how to optimally utilize the existing longitudinal data in the context of gene-finding studies. The results were consistent across domains (verbal, non-verbal and general intelligence), and indicated that phenotypic stability was driven primarily by the high stability of additive genetic factors, that the stability of common environment was moderate, and that the unique environment contributed primarily to change. The cross-subscale stability was consistently low, indicating a small overlap between different domains of intelligence over time. The high stability of additive genetic factors justifies the use of a linear combination of scores across the different ages in the context of gene-finding studies.

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.

The human electroencephalogram (EEG) consists of oscillations that reflect the summation of postsynaptic potentials at the dendritic tree of cortical neurons. The strength of the oscillations (EEG power) is a highly genetic trait that has been related to individual differences in many phenotypes, including intelligence and liability for psychopathology. Here, we investigated whether brain anatomy underlies these EEG power differences by correlating it to gray and white matter volumes (GMV, WMV), and additionally investigated whether this association can be attributed to genes or environmental factors. EEG was measured in a sample of 405 young adult twins and their siblings, and power in the theta (~4 Hz), alpha (~10 Hz), and beta (~20 Hz) frequency bands determined. A subset of 121 subjects were also scanned in a 1.5 T MRI scanner, and gray and white matter volumes defined as the total of cortical and subcortical volumes, excluding cerebellum. Both MRI-based volumes and EEG power spectra were highly heritable. GMV and WMV correlated .25 to .29 with EEG power for the slower oscillations (theta, alpha). Moreover, these phenotypic correlations largely reflected genetic covariation, irrespective of oscillation frequency and volume type. Genetic correlations (.31 < rA < .43) revealed that only moderate proportions of the heritable variance overlapped between MRI volumes and EEG power. The results suggest that MRI volumes and EEG power share genetic sources of variation, which may reflect such processes as myelination, synaptic density, and dendritic outgrowth.

We recently showed that the correlation of gray and white matter volume with full scale IQ and the Working Memory dimension are completely mediated by common genetic factors (Posthuma et al., 2002). Here we examine whether the other WAIS III dimensions (Verbal Comprehension, Perceptual Organization, Processing Speed) are also related to gray and white matter volume, and whether any of the dimensions are related to cerebellar volume. Two overlapping samples provided 135 subjects from 60 extended twin families for whom both MRI scans and WAIS III data were available. All three brain volumes are related to Working Memory capacity (r = 0.27). This phenotypic correlation is completely due to a common underlying genetic factor. Processing Speed was genetically related to white matter volume (rg = 0.39). Perceptual Organization was both genetically (rg = 0.39) and environmentally (re= −0.71) related to cerebellar volume. Verbal Comprehension was not related to any of the three brain volumes. It is concluded that brain volumes are genetically related to intelligence which suggests that genes that influence brain volume may also be important for intelligence. It is also noted however, that the direction of causation (i.e., do genes influence brain volume which in turn influences intelligence, or alternatively, do genes influence intelligence which in turn influences brain volume), or the presence or absence of pleiotropy has not been resolved yet.

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 (rp) was .72 for both measures and was explained by genetic and common environmental correlations across time (FSIQ, rg = .96, rc = 1.0; VIQ, rg =.78, rc = 1.0). Stability of PIQ (rp =.56) was lower and was explained by genetic influences (rg = .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.

To investigate whether genetic and/or disease-related factors are involved in progressive structural brain changes in schizophrenia, magnetic resonance imaging scans with a 5-year scan interval were acquired in patients, their same-gender siblings and matched healthy controls. Structural equation modelling was applied to assess disease and familial effects. Whole brain and cerebral grey matter volumes decreased excessively in patients compared with their siblings and the controls, suggesting that the progressive brain loss in schizophrenia may be related to the disease process.

Background. Autism is a neurodevelopmental disorder with an estimated genetic origin of 90%. Previous studies have reported an increase in brain volume of approximately 5% in autistic subjects, especially in children. If this increase in brain volume is genetically determined, biological parents of autistic probands might be expected to show brain enlargement, or at least intracranial enlargement, as well. Identifying structural brain abnormalities under genetic control is of particular importance as these could represent endophenotypes of autism.

Method. Using quantitative anatomic brain magnetic resonance imaging, volumes of intracranial, total brain, frontal, parietal, temporal and occipital lobe, cerebral and cortical gray and white matter, cerebellum, lateral ventricle, and third ventricle were measured in biological, non-affected parents of autistic probands (19 couples) and in healthy, closely matched control subjects (20 couples).

Results. No significant differences were found between the parents of the autistic probands and healthy control couples in any of the brain volumes. Adding gender as a factor in a second analysis did not reveal a significant interaction effect of gender by group.

Conclusions. The present sample of biological, non-affected parents of autistic probands did not show brain enlargements. As the intracranium is not enlarged, it is unlikely that the brain volumes of the parents of autistic probands have originally been enlarged and have been normalized. Thus, increased brain volume in autism might be caused by the interaction of paternal and maternal genes, possibly with an additional effect of environmental factors, or increased brain volumes might reflect phenotypes of autism.

Background. To establish whether high-functioning children with autism spectrum disorder (ASD) have enlarged brains in later childhood, and if so, whether this enlargement is confined to the gray and/or to the white matter and whether it is global or more prominent in specific brain regions.

Method. Brain MRI scans were acquired from 21 medication-naive, high-functioning children with ASD between 7 and 15 years of age and 21 comparison subjects matched for gender, age, IQ, height, weight, handedness, and parental education, but not pubertal status.

Results. Patients showed a significant increase of 6% in intracranium, total brain, cerebral gray matter, cerebellum, and of more than 40% in lateral and third ventricles compared to controls. The cortical gray-matter volume was evenly affected in all lobes. After correction for brain volume, ventricular volumes remained significantly larger in patients.

Conclusions. High-functioning children with ASD showed a global increase in gray-matter, but not white-matter and cerebellar volume, proportional to the increase in brain volume, and a disproportional increase in ventricular volumes, still present after correction for brain volume. Advanced pubertal development in the patients compared to the age-matched controls may have contributed to the findings reported in the present study.