Elsevier

NeuroImage

Volume 17, Issue 1, September 2002, Pages 256-271
NeuroImage

Regular Article
Genetic Contributions to Regional Variability in Human Brain Structure: Methods and Preliminary Results

https://doi.org/10.1006/nimg.2002.1163Get rights and content

Abstract

Twin studies provide one approach for investigating and partitioning genetic and environmental contributions to phenotypic variability in human brain structure. Previous twin studies have found that cerebral volume, hemispheric volume, ventricular volume, and cortical gyral pattern variability were heritable. We investigated the contributions of genetic and environmental factors to both global (brain volume and lateral ventricular volume) and regional (parcellated gray matter) variability in brain structure. We examined MR images from 10 pairs of healthy monozygotic and 10 pairs of same-sex dizygotic twins. Regional gray matter volume was estimated by automated image segmentation, transformation to standard space, and parcellation using a digital atlas. Heritability was estimated by path analysis. Estimated heritability for brain volume variability was high (0.66; 95% confidence interval 0.17, 1.0) but the major effects on lateral ventricular volume variability were common and unique environmental factors. We constructed a map of regional brain heritability and found large genetic effects shared in common between several bilateral brain regions, particularly paralimbic structures and temporal–parietal neocortex. We tested three specific hypotheses with regard to the genetic control of brain variability: (i) that the strength of the genetic effect is related to gyral ontogenesis, (ii) that there is greater genetic control of left than of right hemisphere variability, and (iii) that random or fluctuating asymmetry in bilateral structures is not heritable. We found no evidence in support of the first two hypotheses, but our results were consistent with the third hypothesis. Finally, we used principal component (PC) analysis of the genetic correlation matrix, to identify systems of anatomically distributed gray matter regions which shared major genetic effects in common. Frontal and parietal neocortical areas loaded positively on the first PC; some paralimbic and limbic areas loaded negatively. Bilateral insula, some frontal regions, and temporal neocortical regions functionally specialized for audition and language loaded strongly on the second PC. We conclude that large samples are required for powerful investigation of genetic effects in imaging data from twins. However, these preliminary results suggest that genetic effects on structure of the human brain are regionally variable and predominantly symmetric in paralimbic structures and lateral temporal cortex.

References (57)

  • A.J. Bartley et al.

    Genetic variability of human brain size and cortical gyral patterns

    Brain

    (1997)
  • K.A. Bollen

    Structural Equations with Latent Variables

    (1989)
  • E.T. Bullmore et al.

    Global, voxel and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain

    IEEE Trans. Med. Imag.

    (1999)
  • E.T. Bullmore et al.

    Colored noise and computational inference in neurophysiological (fMRI) time series analysis: Resampling methods in time and wavelet domains

    Human Brain Mapp.

    (2001)
  • T.D. Cannon et al.

    Genetic and perinatal determinants of structural brain deficits in schizophrenia

    Arch. Gen. Psychiatry

    (1989)
  • G. Carey

    Inference about genetic correlations

    Behav. Genet.

    (1998)
  • D. Carmelli et al.

    Evidence for heritability of brain structure in elderly male twins

    Mol. Psychiatry

    (1999)
  • J.M. Cheverud

    Phenotypic, genetic, and environmental morphological integration in the cranium

    Evolution

    (1982)
  • J.G. Chi et al.

    Gyral development of the human brain

    Ann. Neurol.

    (1977)
  • J.C. Christian et al.

    Comparison of analysis of variance and maximum likelihood based path analysis of twin data: Partitioning genetic and environmental sources of covariance

    Genet. Epidemiol.

    (1995)
  • P.J. Dempsey et al.

    Genetic covariance structure of incisor crown size in twins

    J. Dental Res.

    (1995)
  • M.F. Egan et al.

    Effect of COMT Val (108/158) Met genotype on frontal lobe function and risk for schizophrenia

    Proc. Natl. Acad. Sci. USA

    (2001)
  • K.J. Friston et al.

    Statistical parametric maps in functional imaging: A general approach

    Human Brain Mapp.

    (1995)
  • I.T. Jolliffe

    Principal Components Analysis

    (1986)
  • J.A. Kieser

    Human Adult Odontometrics: The Study of Variation in Adult Tooth Size

    (1990)
  • J.G. Kingsolver et al.

    Development, function, and the quantitative genetics of wing melanin pattern in Pieris butterflies

    Evolution

    (1991)
  • J.C. Loehlin

    Latent Variable Models: An Introduction to Factor, Path and Structural Analysis

    (1987)
  • J.C. Loehlin

    The Cholesky approach: A cautionary note

    Behav. Genet.

    (1996)
  • Cited by (181)

    • Uncovering the genetics of the human connectome

      2023, Connectome Analysis: Characterization, Methods, and Analysis
    • Corticolimbic Circuitry and Genomic Risk for Stress-Related Psychopathology

      2020, Stress: Genetics, Epigenetics and Genomics Volume 4: Handbook of Stress
    View all citing articles on Scopus
    View full text