The association between brain volume and intelligence is of genetic origin

Posthuma, Daniëlle; Geus, Eco J. C. de; Baaré, William F.C.; Pol, Hilleke E. Hulshoff; Kahn, René S.; Boomsma, Dorret I.

doi:10.1038/nn0202-83

Cited by 333 publications

(299 citation statements)

References 11 publications

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“…This association is mediated by genes shared between structural brain measures and full scale IQ in adulthood (Hulshoff Pol et al, 2006;Posthuma et al, 2002). In our pediatric twin cohort we demonstrated that this genetic association between brain structure and IQ is already present at a young age.…”

Section: Brain Structure and Cognitionsupporting

confidence: 52%

Brain SCALE: Brain Structure and Cognition: an Adolescent Longitudinal Twin Study into the Genetic Etiology of Individual Differences

et al. 2012

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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 genomewide 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.

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Section: Brain Structure and Cognitionsupporting

confidence: 52%

Brain SCALE: Brain Structure and Cognition: an Adolescent Longitudinal Twin Study into the Genetic Etiology of Individual Differences

et al. 2012

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“…First of all, previous twin studies indicated that the association between general intelligence and brain volume was mediated by genetic factors (Betjemann et al, 2010;Posthuma et al, 2002). Moreover, Li et al (2009) reported that the association between white matter architecture in the hippocampus formation and intelligence quotient (IQ) was modulated by the COMT gene, which codes for a key enzyme responsible for inactivating released DA in the brain.…”

Section: Discussionmentioning

confidence: 99%

“…These results are relevant to the current study because WM is considered a major component of general intelligence, and both the COMT gene and NTSR1 gene play an important role in DA transmission. Since genetic factors can mediate the relations between brain volumes and intelligence (Posthuma et al, 2002), it is reasonable to expect that the relation between hippocampal volume and WM is mediated by genes. To our knowledge, the present study is the first to report a specific source of the genetic variation influencing the association between hippocampal volume and WM.…”

Section: Discussionmentioning

confidence: 99%

The NTSR1 gene modulates the association between hippocampal structure and working memory performance

Jin¹,

Lei²,

Wang³

et al. 2013

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The genetic and neural basis of working memory (WM) has been extensively studied. Many dopamine (DA) related genes, including the NTSR1 gene (a DA modulator gene), have been reported to be associated with WM performance. The NTSR1 protein is predominantly expressed in the cerebral cortex and the hippocampus, the latter of which is closely involved in WM processing based on both lesion and fMRI studies. Thus far, however, no study has examined the joint effects of NTSR1 gene polymorphism and hippocampal morphology on WM performance. Participants of the current study were 330 healthy Chinese college students. WM performance was measured with a 2-back WM paradigm. Structural MRI data were acquired and then analyzed using an automated procedure with atlas-based FreeSurfer segmentation software (v 4.5.0) package. Linear regression analyses were conducted with a NTSR1 C/T polymorphism which was previously reported to be associated with WM (rs4334545), hippocampal volume, and their interaction as predictors of WM performance, with gender and intracranial volume (ICV) as covariates. Results showed a significant interaction between NTSR1 genotype and hippocampal volume (p b .05 for both the left and right hippocampi). Further analysis showed that the correlation between hippocampal volume and WM scores was significant for carriers of the NTSR1 T-allele (p b .05 for both hippocampi), but not for CC homozygotes. These results indicate that the association between hippocampal structure and WM performance was modulated by variation in the NTSR1 gene, and suggest that further studies of brain-behavior associations should take genetic background information into account.

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“…They are also of interest from a behavioral neuroscience standpoint. The quantity of frontal gray matter, for example, is under strong genetic control and is also linked with IQ (Posthuma et al, 2002;Thompson et al, 2001a,b). These genetic brain maps therefore help establish links, at the systems level, between genes, brain structure, and behavior (see Gray and Thompson, 2004, for a review).…”

Section: Heritabilitymentioning

confidence: 99%

Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia

et al. 2004

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This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhoodand adult-onset schizophrenia, bipolar disorder, attention-deficit/ hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages. D 2004 Published by Elsevier Inc.

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The association between brain volume and intelligence is of genetic origin

Cited by 333 publications

References 11 publications

Brain SCALE: Brain Structure and Cognition: an Adolescent Longitudinal Twin Study into the Genetic Etiology of Individual Differences

Brain SCALE: Brain Structure and Cognition: an Adolescent Longitudinal Twin Study into the Genetic Etiology of Individual Differences

The NTSR1 gene modulates the association between hippocampal structure and working memory performance

Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia

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