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Corpus Callosum Size Is Highly Heritable in Humans, and
May Reflect Distinct Genetic Influences on Ventral and
Rostral Regions
Girma Woldehawariat
1
*, Pedro E. Martinez
2
, Peter Hauser
3
, David M. Hoover
4
, Wayne W. C. Drevets
5"
,
Francis J. McMahon
1"
1Genetic Basis of Mood & Anxiety Disorders Section, Human Genetics Branch, National Institute of Mental Health, NIH, DHHS, Bethesda, Maryland, United States of
America, 2Section on Behavioral Endocrinology, National Institute of Mental Health, NIH, DHHS, Bethesda, Maryland, Unites States of America, 3VISN 22 Network Office,
Long Beach, California, United States of America, 4Center for Information Technology, National Institutes of Health, Bethesda, Maryland, United States of America,
5Laureate Institute for Brain Research and the University of Oklahoma College of Medicine, Tulsa, Oklahoma, United States of America
Abstract
Anatomical differences in the corpus callosum have been found in various psychiatric disorders, but data on the genetic
contributions to these differences have been limited. The current study used morphometric MRI data to assess the
heritability of corpus callosum size and the genetic correlations among anatomical sub-regions of the corpus callosum
among individuals with and without mood disorders. The corpus callosum (CC) was manually segmented at the mid-sagittal
plane in 42 women (healthy, n = 14; major depressive disorder, n = 15; bipolar disorder, n = 13) and their 86 child or
adolescent offspring. Four anatomical sub-regions (CC-genu, CC2, CC3 and CC-splenium) and total CC were measured and
analyzed. Heritability and genetic correlations were estimated using a variance components method, with adjustment for
age, sex, diagnosis, and diagnosis x age, where appropriate. Significant heritability was found for several CC sub-regions (P,
0.01), with estimated values ranging from 48% (splenium) to 67% (total CC). There were strong and significant genetic
correlations among most sub regions. Correlations between the genu and mid-body, between the genu and total corpus
callosum, and between anterior and mid body were all .90%, but no significant genetic correlations were detected
between ventral and rostral regions in this sample. Genetic factors play an important role in corpus callosum size among
individuals. Distinct genetic factors seem to be involved in caudal and rostral regions, consistent with the divergent
functional specialization of these brain areas.
Citation: Woldehawariat G, Martinez PE, Hauser P, Hoover DM, Drevets WWC, et al. (2014) Corpus Callosum Size Is Highly Heritable in Humans, and May Reflect
Distinct Genetic Influences on Ventral and Rostral Regions. PLoS ONE 9(6): e99980. doi:10.1371/journal.pone.0099980
Editor: Francis Szele, University of Oxford, United Kingdom
Received September 6, 2013; Accepted May 21, 2014; Published June 26, 2014
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for
any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Funding: This research is funded by National Institutes of Mental Health (NIMH) of the US government. The funders had no role in study design, data collection
and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* Email: hawariag@mail.nih.gov
"These senior authors both contributed equally to this work.
Introduction
The corpus callosum (CC) plays a major role in connecting the
cerebral hemispheres, enabling inter-hemispheric communication
[1]. The CC is the brain’s largest white matter structure [2,3], and
five anatomical sub-regions are commonly recognized: rostrum,
genu, body, isthmus, and splenium [4]. The cortical origins of the
axons passing through each subregion differ across sub regions.
For example, projections from auditory and somatosensory
cortices primarily traverse the body of the CC [5–7], while those
from visual cortex traverse the splenium [5–7]. Further work is
needed to characterize the functional roles of the inter-hemispher-
ic projections contained within the CC, but the entire structure
appears to play an integrative role [2] by facilitating the
coordinated and rapid transfer of information involved in
sensorimotor, attention, language, and other cognitive processes
between contralateral, homologous cortical regions [7–10].
Disturbances in the structure or function of the CC have been
reported in several neuropsychiatric illnesses, including schizo-
phrenia [11–13], bipolar disorder [14], autism [15], and attention-
deficit hyperactivity disorder [16]. In mood disorders, CC
abnormalities have been implicated in some of the cognitive and
other symptoms that occur in bipolar disorder [7,17]; possibly
reflecting compromised efficiency of information transfer between
cerebral hemispheres [18]. Moreover, fractional anisotropy (a
diffusion tensor imaging measure that reflects the degree to which
white matter fibers are aligned in a specific direction) is
significantly lower in the mid-body and genu of the CC in patients
with bipolar disorder, compared to healthy controls [19,20].
Abnormalities of size and morphology of the CC have also been
reported in individuals with unipolar depressive disorders [21,22],
which may reflect alterations in the cortico-limbic-subcortical
circuitry arising in association with the prefrontal cortical and
temporal cortical volumetric differences reported in these condi-
tions [23–25]. The relationship between CC structure and
function under normal conditions, together with the evidence of
structural alterations in mood disorders, underscores the impor-
tance of understanding the role of genes in influencing the size of
PLOS ONE | www.plosone.org 1 June 2014 | Volume 9 | Issue 6 | e99980
the various substructures of the CC, and inter-relationships that
reflect shared genetic factors.
Genetic factors have been shown to play important roles in the
development of a variety of brain structures, including the CC.
Several studies have shown that the volumes of specific brain
structures are significantly heritable [25,27–31]. For example,
relatively high heritability estimates have been reported for
cerebral hemisphere sizes [28], cortical morphology [32] and
white matter volume [30]. Several investigations have reported
significant heritability estimates for total CC size [32–34],
although only a few study addressed the heritability of CC sub
regions [35,36]. While functional and anatomical connectivity
between the CC and other brain regions (27] may imply shared
genetic programs, there is a paucity of information regarding any
genetic correlations among sub regions within the CC [38]. Thus
it remains unclear how much of the morphologic correlation
between sub-regions in the CC is attributable to shared genetic
factors in humans.
The present study was aimed at investigating heritability of CC
volume and genetic correlations among CC sub-regions in
participants with and without mood disorders. The results
demonstrate that genetic factors play an important role in CC
volume, but also suggest that distinct genetic factors are involved
in the development of caudal and rostral regions, consistent with
the divergent functional specialization of these CC sub regions.
Methods
Ethics Statement
The participants provided their written informed consent.
Written informed consent was obtained from the mothers on
behalf of their children. The ethics committee of The National
Institute of Mental Health (NIMH) approved this informed written
consent procedure involving both adults and children. The ethics
of conducting this experiment followed strictly the guidelines of
The National Institutes of Mental Health (NIMH) Institutional
Review Board (IRB), which examined and approved this research
work.
Participants
Participants were drawn from the NIMH Longitudinal Study of
the children of affectively ill and well parents [39]. Forty-two
mothers, ranging in age from 43 to 45 years, and 86 children (76
full siblings and 10 maternal half siblings) from 58 families
underwent scanning, including 15 mothers with major depressive
disorder (MDD), 13 with bipolar disorder (BD) and 14 with no
psychiatric illness (control). All participants were in good physical
health at enrollment and at time of scanning. Offspring included
33 from mothers with MDD, 25 from those with BD, and 28 from
healthy mothers (Table 1). Offspring were initially enrolled
between the ages of 1 and 3, classified by mother’s psychiatric
status, and then reassessed periodically over the following 10-20
years. The MRI scans were acquired in offspring and mothers
when offspring were between age 10 and 18 years. The original
sample was largely of Caucasian ancestry, with a small represen-
tation of Hispanics, African Americans, and Asians (39). A
previous study has shown that race did not have a significant
effect on the various sub-regions of the corpus callosum [40]. Since
heritability estimates in the present study depend on comparisons
of mothers with their own offspring, racial differences between
families have no influence on the estimates.
Magnetic Resonance Imaging
Scans were obtained at the NIH using a Picker Vista 0.5 Tesla
scanner running a gradient echo 3Dacquisition pulse sequence.
Parameters for image acquisition were optimized for tissue
contrast resolution in pilot studies performed in independent
samples [41]. Sagittal images 2 mm thick were obtained at voxel
size = 26161 mm (TR = 20 ms, TE = 6 ms, flip angle = 45 de-
grees, FOV = 26 cm, matrix = 1306256, acquisition time = 7.9
14;minutes). Image data were processed with ANALYZE
(Biomedical Imaging Resource, Mayo Foundation, Rochester,
MN). In the mid-sagittal plane, the CC was manually traced and
segmented into six sub regions, CC1 (corresponding to the
relatively small rostrum plus the much larger genu region [42],
CC2 (anterior CC body), CC3 (mid CC body), CC4 (posterior CC
body), CC5 (isthmus), and CC6 (splenium) [40]. In the present
study only the data from the CC1, CC2, CC3 and CC6 regions
were analyzed, as these regions had the highest inter-rater
reliability. Briefly, a horizontal line was drawn from the base of
the splenium to the base of the genu. Vertical lines, perpendicular
to the horizontal reference line, were drawn at the anterior aspect
of the genu and posterior aspect of the splenium. The midpoint of
the horizontal reference line between these two vertical reference
lines were determined, and radial divisors were placed at that
midpoint to divide the CC into sub-regions of C1, C2, C3 C4, C5
and C6 (Figure 1). Area measures (in mm
2
) were obtained from
each sub-region and for the total CC area. Whole brain area was
determined by manually tracing the cerebrum in the midsagittal
plane. All tracings were performed with the rater blind to subject
identity. Although this technology has now been replaced by
higher resolution scanners, inter-rater reliability as measured by
intra-class correlation [43] was excellent: 0.92 for the genu, 0.92
for the splenium, 0.90 for CC2, 0.90 for CC3 and 0.92 for total
CC, based on 22 scans traced by two raters each. We did not have
measures of overall brain size, but each sub region was expressed
as a proportion of total CC size, thus minimizing the impact of
individual differences in overall brain size.
Quantitative Genetic Analysis
Information from full and half siblings and their mothers were
used to conduct quantitative genetic analysis. The effects of age,
sex, maternal psychiatric diagnosis, age
2
, and their interactions
(age6sex, age6psychiatric diagnosis, sex6psychiatric diagnosis)
were examined in a variance components analysis implemented by
SOLAR [44]. Maternal diagnosis of MDD has been previously
shown to affect CC size in offspring [45]. Covariates with
significant statistical effects were included in the final model to
determine heritability and genetic correlations.
Narrow-sense heritability (h
2
) and genetic correlations between
brain regions were estimated using the maximum likelihood
variance components method [44]. Narrow-sense heritability is
defined as the proportion of the total phenotypic variance
attributable to additive genetic variance:
h2~VA
VP
Genetic correlation analysis estimates the proportion of genetic
variance that two traits share in common. A significant genetic
correlation implies that a gene or genes shared among individuals
influences both traits. A positive correlation indicates that genetic
differences affect measured values in the same direction for both
traits. SOLAR partitions the phenotypic variance into components
Quantitative Genetic Analysis of Corpus Callosum
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attributable to genetic and environmental factors, and can account
for the effects of covariates (age, sex, and diagnostic status).
Genetic correlations between CC volumes were investigated
using a multivariate extension of the variance components method
[43,46]. This approach is based on the covariance between
phenotypes of related individuals after accounting for the effects of
significant covariates [47]. Likelihood methods were used to obtain
the statistical significance of the estimate of each parameter by
comparing a model in which that parameter is constrained to zero
against the general model in which all parameters were estimated
simultaneously. Further details regarding the population genetic
theory and the specific analytical methods used can be found in
Almasy and Blangero [46] and Comuzzie et al. [47].
Results
Estimation of Covariate Effects
In order to estimate the effects of potential confounding
variables, age (including age
2
), sex, psychiatric diagnosis, and
interactions were included as covariates in the initial model.
Covariates that significantly influenced one or more CC subre-
gions were included in the final model estimating heritability and
genetic correlations (table 2).
Age significantly influenced size of the total CC and its sub
regions (Table 2) while Age
2
did not have a significant effect. Sex
significantly influenced CC2, splenium (CC6) and total CC size,
but did not significantly influence CC-genu or CC-3. Psychiatric
diagnosis (MDD, BD or healthy) had a significant effect on the size
of the genu, the splenium and CC-total but not on CC2 and CC3.
On the basis of these results, age was included as a covariate in
all analyses, sex was included as a covariate for analyses of CC2,
splenium, and total size, and diagnosis was included as a covariate
for analyses of genu, splenium and CC-total. The interaction of
age x diagnosis had a significant effect only on splenium and CC-
total, hence it was included as a covariate in the analysis of
splenium and CC-total.
Heritability
Heritabilities were determined for each of the four CC sub-
regions, along with the total.
CC size (Table 3). Significant heritability was found for the sizes
of the genu, CC2, CC3, and total CC (all P,0.01), and for the
splenium (P,0.05). Heritability (h
2
) values were substantial, he
estimated heritability ranging from 48% (splenium) to 67% (total
CC; Table 3). Thus genetic factors were found to have a
substantial influence in all of the CC regions tested.
Genetic Correlations
We found significant genetic correlations between all rostral and
between all ventral sub regions (p,0.01), but not between CC2
and splenium or CC3 and splenium (Table 3). Particularly strong
correlations were detected between the genu and mid-body
structures (CC1 and CC3; 90%), between the genu and total
CC (96%), and between anterior and mid-body structures (CC2
and CC3; 100%).
Discussion
Brain size and morphology are significantly heritable [26–30].
Likewise, many previous studies have reported that the size of the
corpus callosum (CC) is significantly heritable in humans [32–34],
but few studies have characterized the heritability of CC
substructures [60]. This is important, since anterior and rostral
regions of the CC seem to perform distinct functions. Significant
heritability estimates for area measures of the genu (66%), body
(54%), and splenium (57%) have been reported [35]. In another
paper, the same laboratory [36] reported significant heritabilities
for genu (59%), body (62%), and splenium (75%). Significant
heritabilities for CC substructures were also reported in non-
human primates [48]. A recent genetic analysis of diffusion tensor
images found significant heritability estimates for genu, body, and
splenium [49].
The present study examined heritabilities and genetic correla-
tions of total CC size and 4 sub-regions of the CC. While our
sample size was limited, the heritability findings largely agree with
previous reports, indicating that the size of the CC and its
Table 1. Demographic data.
Mothers Offspring
Males Females
Status Number Age Number Age (yrs.) Number Age (yrs.)
Control 14 456515 1563131662
Bipolar 13 43649 1563161562
Unipolar 15 456613 1562201762
Total 42 37 49
doi:10.1371/journal.pone.0099980.t001
Figure 1. T1-weighted mid-sagittal view of the corpus callosum
(CC). Six sub regions are shown: CC1 (genu), CC2, CC3, CC4, CC5 and
CC6 (splenium).
doi:10.1371/journal.pone.0099980.g001
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substructures are under strong genetic influence. We also show
significant genetic correlations between many CC sub-regions.
This conforms with the findings of Philips et al [48] in baboons,
but has not to our knowledge been demonstrated before in
humans. The present study also suggests for the first time that
distinct genetic factors are involved in ventral and rostral regions
of the CC. These results may have important implications for our
understanding of how genetic factors operate during brain
development.
We found significant, positive genetic correlations among all
rostral, and among all ventral, sub regions of the CC, but not
between ventral and rostral structures. While the genetic
correlations between ventral and rostral structures are not
significantly different from zero in this sample, only a larger
sample could exclude the possibility that similar or overlapping
genetic factors affect both ventral and rostral regions. Distinct
genetic factors would be consistent with the divergent functional
specialization of these brain regions [50–53]. Many genes have so
far been shown to influence early brain development, but few
studies have directly contrasted genetic influences on rostral and
dorsal telencephalon. Among these, two patterning genes (Foxg1
and Fgf8) have been found to be involved in both rostral and
dorsal telencephalic development in model organisms [54–56].
Most previous heritability studies of brain structure have used
twin designs; the present study used parent-offspring pairs. Twin
designs have many advantages, but also some pitfalls. Twins share
similar environments from conception to birth and over the period
during which they are reared together. This fact may confound
shared genes with shared environments, inflating narrow sense
heritability (h
2
) estimates [57]. Parent-offspring pair designs
exclude shared prenatal environments, but do have other
limitations, including shared recent environment, age differences,
and uncertainties in offspring paternity. Shared current environ-
ment might be a major confound for certain traits, but brain
anatomy is largely determined early in life, during which
environmental influences on mothers and their offspring (typically
born 20–30 years later) may be quite different.
Mothers in this sample were psychiatrically healthy or suffered
from a major mood disorder. Despite this potentially important
independent variable, psychiatric diagnosis had a significant effect
only on the size of the genu and the splenium and did not
significantly affect heritability estimates. Our results suggest that
maternal bipolar and unipolar disorders do not substantially affect
CC morphology – or do so similarly in mothers and their
offspring. This finding contrasts with some previous work
indicating that the genu of the corpus callosum was smaller in
offspring of mothers with a history of MDD but not in the
offspring of mothers with BD [45]. Our sample size did not permit
comparisons between mothers with different types of mood
disorder and we may have missed differences confined to MDD.
As in all imaging studies, the morphological differences we
observed could represent cause or consequence of mood disorder.
However, if mood disorders cause changes in CC morphology, this
could not explain the significant correlation in CC size that we
observed between mothers and their offspring. If on the other
hand smaller CC contributes to mood disorder, then both CC size
and mood disorder risk would be transmitted from mothers to
offspring, consistent with our observations. Different study designs
will be needed to fully disentangle the genetic influences on mood
disorders from those on CC morphology.
We used ROI analyses to manually trace each brain area, blind
to clinical and demographic variables. Some prior studies have
suggested that this approach may be less sensitive to small
variations in brain structure or tissue type distribution, compared
Table 2. Significance levels of covariates and corresponding beta coefficients, by sub-regions of the corpus callosum.
Traits
Covariates CC-genu CC2 CC3 CC-splenium CC-total
p-value Beta p-value Beta p-value beta p-value beta p-value beta
Age ,0.001 0.0460.0 ,0.001 0.0260.0 ,0.001 0.0360.0 ,0.001 0.0360.0 ,0.001 0.0360.0
Sex ns ns ,0.05 0.4060.2 ns ns ,0.001 0.6760.2 ,0.02 2.2560.1
Diagnostic group ,0.01 0.2760.1 ns ns ns ns ,0.001 2.3960.1 ns 0.5260.2
Age x Diagnostic group ns ns ,0.05 2.0160.0 ns ns ,0.001 2.0260.0 ,0.02 20.0260.0
ns
P.0.05.
doi:10.1371/journal.pone.0099980.t002
Quantitative Genetic Analysis of Corpus Callosum
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to computer modeling methods [58–60]. On the other hand,
manual tracing is not subject to many of the assumptions that
underlie computer-modeling approaches.
In summary, our findings demonstrate that genetic factors play
an important role in determining size of the CC and its
substructures. While the same genes are involved in anatomically
adjacent CC substructures, distinct genes seem to contribute to
ventral and rostral regions. These findings suggest that the CC is a
reasonable target for studies aimed at identifying the specific genes
involved in regional brain development. To the extent that mental
illnesses are disorders of brain circuitry, genes important in CC
development are also likely to play an important role in mental
illness, but this is still to be determined.
Acknowledgments
This study utilized the high-performance computational capabilities of the
Helix Systems at the National Institutes of Health, Bethesda, MD (http://
helix.nih.gov). We thank Mr. Charles Peterson, senior system analyst at
Texas Biomedical Research Institute, for consultation in SOLAR
programming.
Author Contributions
Conceived and designed the experiments: GW WWCD FJM. Performed
the experiments: WWCD PEM PH. Analyzed the data: GW DMH.
Contributed reagents/materials/analysis tools: WWCD. Wrote the paper:
GW FJM WWCD.
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Table 3. Heritability (diagonal) and Genetic Correlations (above diagonal)
a
.
Area CC-genu CC2 CC3 CC-splenium CC-Total
CC-genu 0.5060.21** 0.7160.20** 0.9060.15** 0.8560.16** 0.9660.06**
CC2 0.6260.22** 1.0060.15** 0.5460.24 0.8760.10**
CC3 0.5060.23** 0.5860.27 0.9660.07**
CC-splenium 0.4860.22* 0.8560.12**
CC-Total 0.6760.22**
a
Mean and standard deviation.
**P#0.01,
*P#0.05.
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Quantitative Genetic Analysis of Corpus Callosum
PLOS ONE | www.plosone.org 6 June 2014 | Volume 9 | Issue 6 | e99980
