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Age at First Exposure to Football Is Associated
with Altered Corpus Callosum White Matter Microstructure
in Former Professional Football Players
Julie M. Stamm,
1–3
Inga K. Koerte,
3,4
Marc Muehlmann,
3,4
Ofer Pasternak,
3,15
Alexandra P. Bourlas,
1,5
Christine M. Baugh,
1,6
Michelle Y. Giwerc,
3
Anni Zhu,
3
Michael J. Coleman,
3
Sylvain Bouix,
3
Nathan G. Fritts,
1
Brett M. Martin,
7
Christine Chaisson,
1,5,7,8
Michael D. McClean,
9
Alexander P. Lin,
3,10
Robert C. Cantu,
1,11–13
Yorghos Tripodis,
1,5,8
Robert A. Stern,
1,2,5,11,14,
*and Martha E. Shenton
3,15,16,
*
Abstract
Youth football players may incur hundreds of repetitive head impacts (RHI) in one season. Our recent research suggests
that exposure to RHI during a critical neurodevelopmental period prior to age 12 may lead to greater later-life mood,
behavioral, and cognitive impairments. Here, we examine the relationship between age of first exposure (AFE) to RHI
through tackle football and later-life corpus callosum (CC) microstructure using magnetic resonance diffusion tensor
imaging (DTI). Forty retired National Football League (NFL) players, ages 40–65, were matched by age and divided into
two groups based on their AFE to tackle football: before age 12 or at age 12 or older. Participants underwent DTI on a 3
Tesla Siemens (TIM-Verio) magnet. The whole CC and five subregions were defined and seeded using deterministic
tractography. Dependent measures were fractional anisotropy (FA), trace, axial diffusivity, and radial diffusivity. Results
showed that former NFL players in the AFE <12 group had significantly lower FA in anterior three CC regions and higher
radial diffusivity in the most anterior CC region than those in the AFE ‡12 group. This is the first study to find a
relationship between AFE to RHI and later-life CC microstructure. These results suggest that incurring RHI during critical
periods of CC development may disrupt neurodevelopmental processes, including myelination, resulting in altered CC
microstructure.
Key words: age at first exposure; American football; corpus callosum; diffusion tensor imaging; repetitive head impacts
Introduction
Traumatic brain injury (TBI) in youth sports is a growing
public health concern given the millions of youth athletes
participating annually in the United States alone.
1
In addition to
concussive injuries, recent evidence indicates that sustaining re-
petitive subconcussive head impacts through sports participation
may result in long-term consequences, including behavioral
symptoms,
2,3
cognitive impairment,
4
brain structure alterations,
5
and neurodegenerative diseases, such as chronic traumatic en-
cephalopathy (CTE).
6–10
Neuroimaging and electrophysiological
studies have identified structural and functional abnormalities in
former contact sport athletes many years after they stopped
playing.
11–15
Tackle football players ages 7–12 may experience
hundreds of repetitive head impacts (RHI), concussive and/or
subconcussive, over the course of one season, several of which may
exceed forces of 80 g.
16,17
Our previous research suggests that
incurring RHI during critical periods of neurodevelopment in
1
CTE Center,
2
Department of Anatomy and Neurobiology,
5
Alzheimer’s Disease Center,
11
Department of Neurosurgery,
14
Department of Neurology,
Boston University School of Medicine, Boston, Massachusetts.
3
Psychiatry Neuroimaging Laboratory,
10
Center for Clinical Spectroscopy,
15
Department of Radiology, Brigham and Women’s Hospital, Harvard
Medical School, Boston, Massachusetts.
4
Department of Child and Adolescent Psychiatry, Psychosomatic, and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany.
6
Interfaculty Initiative in Health Policy, Harvard University, Boston, Massachusetts.
7
Data Coordinating Center,
8
Department of Biostatistics,
9
Department of Environmental Health, Boston University School of Public Health, Boston,
Massachusetts.
12
Sports Legacy Institute, Waltham, Massachusetts.
13
Department of Neurosurgery, Emerson Hospital, Concord, Massachusetts.
16
VA Boston Healthcare System, Brockton Division, Brockton, Massachusetts.
*These authors contributed equally.
JOURNAL OF NEUROTRAUMA 32:1768–1776 (November 15, 2015)
ªMary Ann Liebert, Inc.
DOI: 10.1089/neu.2014.3822
1768
childhood may lead to later-life mood, behavioral, and cognitive
impairment.
18,19
However, the impact of RHI incurred during
youth on later-life brain structure has not yet been systematically
examined.
A previous theory proposed that, due to its increased plasticity,
recovery from concussions in the developing brain would be su-
perior to that of the adult brain.
20
More recent evidence suggests
that children and adolescents are more likely to endure prolonged
symptom recovery
21–23
and are more vulnerable to poor out-
comes.
24,25
Moreover, neuroimaging studies show persistent
structural and functional changes in the brain following mild TBI in
children.
26–28
Windows of vulnerability to brain trauma may be
associated with critical periods of brain development occurring
throughout childhood and adolescence.
29–31
One such critical pe-
riod occurs between ages 10–12 in males.
32–38
Amygdalar and
hippocampal volumes, as well as cortical thickness in several brain
regions, reach peak levels during this time,
37–40
with synaptic
pruning beginning shortly thereafter to enhance efficient informa-
tion processing.
41,42
Peaks in the rate of myelination
29,31
and ce-
rebral blood flow,
33
as well as significant improvements in network
organization,
43
also occur between ages 10–12, potentially making
the brain more susceptible to functional and structural alterations
following RHI.
Diffusion tensor imaging (DTI) is an advanced magnetic reso-
nance imaging (MRI) technique that provides insight into the
brain’s white matter microstructure by measuring the magnitude
and direction of the movement of water molecules.
44
Within white
matter, water molecules tend to diffuse along a course parallel to
fiber tracts. The directionality of this diffusion is commonly mea-
sured using fractional anisotropy (FA).
45
Higher FA values denote
greater diffusion along one direction, as is observed in well-
organized tissues.
45
Trace is the sum of diffusion in all directions.
44, 45
In poorly-organized tissues, the multi-directional movement of
water molecules can occur with little resistance, resulting in high
trace values.
45
Other common diffusion measures include axial
(AD) and radial (RD) diffusivity, which are thought to measure
axonal and myelin pathology, respectively.
46
Altered diffusivity is frequently observed following mild TBI
(mTBI).
47
. Recent research using DTI,
5,48–51
as well as other im-
aging modalities,
52–55
also revealed altered brain structure and
connectivity following prolonged exposure to RHI. Further, several
studies report altered diffusivity following just one season of
football
48,49,51
and ice hockey
50
play, when comparing preseason
and post-season DTI measures. Bazarian and colleagues
49
identi-
fied decreased FA and increased mean diffusivity values that per-
sisted for at least 6 months post-season. Moreover, Koerte and
colleagues
5
compared elite adult soccer players with no history of
concussion (i.e., only subconcussive blows to the head) to com-
petitive swimmers and observed higher RD and AD in several brain
regions. Findings from these studies provide further support for the
notion that despite the lack of concussive symptoms, incurring
repeated subconcussive head impacts is not without consequences.
The corpus callosum (CC) is the largest commissural fiber tract
in the brain. It is particularly vulnerable to diffuse axonal injury,
with head impacts due to the density and orientation of fibers, the
position of the dural reflections creating barriers to brain move-
ment, and increased shear strain on the tract when external accel-
eration forces are applied.
56,57
The greatest shear strain occurs in
the genu (anterior CC) and splenium (posterior CC),
57
and these
regions are frequently damaged in TBI.
26,56–60
Studies also report
CC microstructural damage following prolonged exposure to RHI
in football,
49
hockey,
50
and soccer players.
5
Further, several neu-
roimaging studies in children demonstrate disrupted CC develop-
ment following TBI of varying severity.
26,60–63
Key aspects of CC
development, including high rates of myelination and axonal
growth, occur between ages 8–12.
34,64–66
However, the relationship
between RHI experienced during this critical neurodevelopmental
period and later-life CC microstructure has not been examined.
The purpose of this study was to examine the relationship be-
tween the age of first exposure (AFE) to RHI through tackle foot-
ball and later-life CC microstructural alterations using DTI. We
examined diffusion measures in two groups of former National
Football League (NFL) players: those who started playing tackle
football before age 12 (AFE <12) and those who started at age 12 or
older (AFE ‡12). Twelve was chosen as the cut-off age based on the
neurodevelopmental literature described above
32–38
and previous
work from our group.
18,19
We hypothesized that the AFE <12 group
would have altered diffusivity, particularly in the genu and sple-
nium, compared with the AFE ‡12 group.
Methods
This research is part of Diagnosing and Evaluating Traumatic
Encephalopathy using Clinical Tests (DETECT), an ongoing study
with a primary goal of developing methods for diagnosing CTE
during life. DETECT includes former NFL players and a control
group. For this study, only former NFL players were included.
DETECT study procedures are described elsewhere.
19
The Boston
University Medical Center Institutional Review Board approved all
study procedures, and all neuroimaging procedures were approved
by the Partners Institutional Review Board. Prior to participation,
all participants provided written informed consent.
Participants
Inclusion criteria for former NFL players in DETECT are: male;
age 40–69; a minimum of 12 total years of organized football
participation; and two years of play in the NFL. Additionally,
participants must report a worsening of cognitive, behavioral, and
mood symptoms for at least the last 6 months that is self-perceived,
reported by others, or for which they have received treatment from
a doctor. These symptoms may include difficulties with memory,
planning and organization, impulsivity, violence, depression,
anxiety, and/or apathy. As reported previously (with a sample that
was nearly identical to the present sample),
19
there were significant
group differences in performance on select neuropsychological
tests, with the AFE <12 group performing more poorly than the
AFE ‡12 group; however, the mean performance of both groups
was within 1.5 SD below demographically-corrected norms. Ex-
clusion criteria are MRI and lumbar puncture contraindications or
history of other diagnosed neurologic disease. Of the 74 former
NFL players who had participated in DETECT at the time of the
study, three did not have imaging data acquired. An additional five
cases were excluded due to motion artifact, leaving 66 former NFL
players eligible for this study.
Current age differed significantly between AFE groups when all
subjects were included (AFE <12, n=30, mean =50.3 years,
SD =6.6; AFE ‡12, n=36, mean =57.4 years, SD =7.4; p<0.001).
Because of this age difference and the resulting possibility of dif-
ferences in style of football played in different chronological eras,
we selected age-matched pairs for subsequent analyses. That is, one
subject in the AFE <12 group was randomly paired, a priori, with
another subject of the same age from the AFE ‡12 group if any
existed. Twenty-six subjects (AFE <12 =10 subjects; AFE ‡12 =16
subjects) could not be matched within 2 years of age with a par-
ticipant in the other AFE group, and, therefore, these subjects were
not included in the analysis. The remaining 40 subjects were
matched within 2 years of age, with 20 subjects in each AFE group
WHITE MATTER STRUCTURE IN FORMER NFL PLAYERS 1769
(age at scan range =40–65). Because of the potential impact of
current age on CC integrity, it was determined that focusing on age-
matched pairs was of greater methodological importance than
including a larger sample size with large between-group age dif-
ferences. Moreover, using age-matched pairs in this study reduced
the standard error of the mixed-effects regression estimates, which
increases the power for detecting clinically significant estimates.
Head impact exposure variables
AFE to tackle football was treated as a dichotomous variable and
used to divide subjects into two groups: AFE <12 and AFE ‡12. Not
surprisingly, duration of football play, defined as the total number
of years, differed between AFE groups and was therefore used as a
covariate. Duration was treated as a continuous variable.
MRI acquisition
Diffusion weighted images (DWI) were acquired on a 3T MR
scanner (TIM Verio; Siemens Healthcare, Erlangen, Germany)
with a 32 channel head coil. An echo planar imaging DWI sequence
was used with the following parameters: repetition time,
11,700 msec; echo time, 85 msec; field of view, 256 mm; 128 ·128
matrix; 2.0 mm slice thickness; and parallel imaging using
GRAPPA with acceleration factor 3. Seventy-three slices were
acquired using 87 diffusion directions organized in multiple
b-value shells, consisting of 64 diffusion-weighted images with a
b-value of 900 sec/mm
2
, 10 images with a b-value of 400 sec/mm
2
,
six images with a b-value of 100 sec/mm
2
, and seven images with
b-value of 0 sec/mm
2
used as baseline images.
Post-processing of diffusion tensor imaging data
Affine registration of the DWI to the baseline image was per-
formed to remove intrascan misalignments due to eddy currents and
head motion (FSL 4.1; FMRIB Software Library, the Oxford
Centre for Functional MRI of the Brain, Oxford, UK). Additionally,
an automated evaluation of DWI images for motion artifact was
conducted using in-house software and resulted in the elimination
of four cases. A visual inspection of all 87 components of each DWI
also was performed and resulted in the elimination of one additional
case due to motion artifact. Further, this quality check revealed
dropped signals in less than five of 87 diffusion directions in six
cases (AFE <12 =1 case; AFE ‡12 =5 cases). These six cases were
included in the study. However, to eliminate possible influences of
these signals, we excluded the diffusion directions and gradient
information using in-house software. One direction was removed in
two cases, two directions were removed in three cases, and three
directions were removed in one case. A corrected DWI-file with the
gradients eliminated was obtained for each of the respective par-
ticipants.
Corpus callosum region of interest and tractography
The whole CC was defined manually on the midsagittal slice, with
one slice to each side of the midsagittal slice on the color-oriented FA
map (n=3 slices) using 3D Slicer software package version 4.3.1
(www.slicer.org; Surgical Planning Laboratory, Brigham and Wo-
men’s Hospital, Boston, MA). The whole CC label map was math-
ematically subdivided into five subregions, as described by Hofer
and Frahm
67
(Fig. 1). The five subregions contain commissural fibers
of prefrontal (region I), premotor and supplementary motor (region
II), primary motor (region III), sensory (region IV), and parietal,
temporal and occipital cortical (region V) areas.
67
Seeding of fiber tracts through the whole CC and CC subregions
was conducted in 3D Slicer using a deterministic (streamline)
tractography approach, which uses the principal diffusion direction
in each voxel to obtain fiber trajectories, with stopping criteria of
FA lower than 0.15.
68
To ensure that only CC fibers were included,
exclusion regions of interest (ROIs) were used in the axial plane at
the levels of the superior thalamus and rostral midbrain in order to
eliminate corticothalamic fibers and corticospinal and cortico-
bulbar fibers, respectively. Further, to ensure the accuracy of the
CC subregion fiber extraction, regions not being examined were
excluded (i.e., when fibers were extracted from region I, regions II-
V were considered exclusion ROIs). Each tractography output was
then inspected and if present, fibers clearly representing non-
FIG. 1. Tractography of the corpus callosum. The corpus callosum was subdivided into five regions containing commissural fibers of
prefrontal (region I), premotor and supplementary motor (region II), primary motor (region III), sensory (region IV), and parietal,
temporal and occipital cortical (region V) areas. Tracts were obtained using deterministic (streamline) tractography to trace fiber paths
through the regions of interest. Color image is available online at www.liebertpub.com/neu
1770 STAMM ET AL.
callosal tracts were manually removed in 3D Slicer. Fibers from the
cingulum bundle and inferior longitudinal fasciculus were most
frequently manually removed, while uncinate fasciculus and fornix
fibers were manually removed in fewer cases. Mean FA, trace, AD,
and RD were extracted for each CC tract. All of these procedures
were carried out blind to AFE group membership and age.
Statistical analysis
Due to the need to include covariates in the analysis, a multi-
variate mixed-effects linear regression model was used to deter-
mine the effect of AFE to tackle football on all DTI measures. This
model included duration of play and body mass index (BMI) as
covariates. BMI has been shown to be negatively correlated with
the integrity of the corpus callosum.
69
The model also adjusted for
correlations within the age-matched pairs and between DTI mea-
sures from the same subject to account for possible inflation of type
I error. All analyses were conducted using SAS 9.3.
Results
Participant demographics and athletic history
Demographic information, athletic history, and other health-
related factors for the age-matched groups are described in Table 1.
AFE across the 40 participants ranged from age 6 to age 17 (me-
dian =11.5 years old). Duration of football play (AFE <12,
mean =20.3 years, SD =3.4; AFE ‡12, mean =18.1 years,
SD =3.1; p=0.039) and BMI (AFE <12, mean =30.4, SD =3.0;
AFE ‡12, mean =33.7, SD =,4.7; p<0.013) differed significantly
between these two age-matched groups.
AFE group comparison
Results from the mixed-effects linear model investigating
between-group differences are shown in Table 2. Duration of play
and BMI were not significant predictors of any measures. After
adjustment for duration of play and BMI,
69
the AFE <12 group
displayed significantly lower FA in the anterior CC regions (I, II,
and III) and higher RD in region I, compared with the AFE ‡12
group (Fig. 2). AD and trace did not differ significantly between
groups.
Discussion
This study is the first to evaluate the relationship between the age
a retired NFL player began playing tackle football and later-life CC
white matter microstructure. We observed significantly lower FA
(regions I, II, and III) and higher RD (region I) in the anterior CC in
former NFL players who began playing tackle football prior to age
12, compared with those who began playing tackle football at age
12 or older. Although preliminary, these results suggest that in-
curring RHI through tackle football play during a critical period of
anterior CC growth before age 12 may disrupt developmental
processes, possibly resulting in lasting alterations in anterior CC
white matter microstructure.
The results of this study extend our previous research showing
greater later-life mood, behavioral impairment, and cognitive im-
pairment in retired NFL players with exposure to RHI through
tackle football prior to age 12.
18,19
Bourlas and colleagues
18
studied
former high school, college, and professional football players and
Table 1. Demographic and Athletic Information
Mean (SD)
AFE <12 years AFE ‡12 years
(n=20) (n=20) T Value pValue
Age at scan (years) 52.2 (6.5) 52.5 (6.2) -0.150 0.882
Age of first exposure to tackle football (years) 9.1 (1.4) 14.1 (1.4) -11.313 <0.001
Education (years) 16.7 (1.1) 16.3 (0.9) 1.292 0.204
Duration of football play (years) 20.3 (3.4) 18.1 (3.1) 2.140 0.039
Duration of play in the NFL (years) 7.4 (2.4) 9.1 (2.8) -1.993 0.053
*Total number of concussions, median (IQR) 45 (179.5) 40 (285.3) 395 0.697
a
Body mass index 30.4 (3.0) 33.7 (4.7) -2.623 0.013
Race, African American, n(%) 6 (30.0) 11 (55.0) 2.558
-
0.11
b
Primary position group, n(%) 10.921
-
0.053
b
Offensive line, n(%) 1 (2.5) 9 (22.5)
Running back, n(%) 1 (2.5) 1 (2.5)
Tight end, n(%) 1 (2.5) 1 (2.5)
Defensive line, n(%) 3 (7.5) 4 (10.0)
Linebacker, n(%) 7 (17.5) 3 (7.5)
Defensive back, n(%) 7 (17.5) 2 (5.0)
Played other contact sport, n(%) 6 (30.0) 8 (40.0) 0.440 0.507
b
Use of performance enhancing drugs, n(%) 4 (21.1) 2 (11.8) 0.662
c
Significant use of alcohol, n(%) 11 (55.0) 12 (60.0) 0.102 0.749
b
Significant use of illicit drugs, n(%) 12 (60.0) 11 (55.0) 0.102 0.749
b
Hypertension, n(%) 11 (55.0) 9 (45.0) 0.400 0.527
b
High cholesterol, n(%) 8 (42.1) 12 (60.0) 1.249 0.264
b
Heart disease, n(%) 1 (5.3) 1 (5.6) 1.000
c
Diabetes, n(%) 1 (5.0) 3 (15.8) 0.342
c
*After being given a modern definition of concussion.
77
a
Wilcoxon signed rank test.
b
Chi-square test.
c
Fisher’s exact test.
SD, standard deviation; AFE, age of first exposure; NFL, National Football League; IQR interquartile range.
WHITE MATTER STRUCTURE IN FORMER NFL PLAYERS 1771
found that the AFE <12 group self-reported greater executive
dysfunction, apathy, and depression than the AFE ‡12 group.
Further, the AFE <12 group had approximately three times greater
odds of having later-life clinically-meaningful depression and ex-
ecutive dysfunction. Stamm and colleagues
19
found that former
NFL players in an AFE <12 group performed significantly worse on
objective measures of executive functioning, memory, and esti-
mated verbal intelligence than those in the AFE ‡12 group. The
results of the present study further support the vulnerability of the
developing brain to RHI prior to age 12 and for the first time, show a
relationship between AFE to RHI and later-life white matter mi-
crostructure alterations.
Callosal anatomy and neurodevelopment may at least partially
explain the findings of this study. FA increases rapidly in the CC
prior to age 12, and this rise is thought to be driven by a decrease in
RD associated with increased myelination.
34,65,66,70
The genu and
splenium reach 90% of peak FA by age 11,
34
followed by a much
slower increase in FA until peak levels are reached in the early
20s.
34,64,65
Snook and colleagues
66
showed a greater slope of in-
crease in FA in the genu than in the splenium between ages 8–12,
suggesting greater anterior CC development during this time. The
genu and anterior midbody of the CC contain small-diameter,
lightly-myelinated fibers, and the genu has the highest proportion of
unmyelinated fibers in the adult CC.
71
These fiber types are pref-
erentially vulnerable to damage and have limited ability to recover
following TBI.
72,73
It is possible that anterior callosal neuroanat-
omy, combined with incomplete and rapid myelination between
ages 8–12, may predispose the anterior CC to detrimental effects of
RHI experienced during this critical neurodevelopmental period.
The reduced RD observed in the AFE <12 group in this study
suggests that RHI may disrupt the normal myelination process in
childhood, possibly leading to a reduced peak level of myelination
in the adult brain. However, further research beginning in children
is needed to better understand the long-term consequences that
incurring RHI has on the developing brain.
Although the AFE <12 group played football for approximately
2 years longer than those in the AFE ‡12 group, duration of football
play was not a significant predictor of white matter microstructural
outcome in this study. Previous studies examining the effect of
duration, as a proxy for overall exposure, on brain structure and
function has been mixed. One study found an association between
duration of play and presence and severity of CTE neuropathology,
8
while other studies found no effect of this variable on later-life
mood, behavior, and cognitive functioning
18,19
or diffusivity
measures.
5
More research is needed to elucidate the relationship
between duration of football and later-life brain structure, function,
and neurodegeneration, and on the interaction effects of total du-
ration of play and initial age of play on later life changes.
Table 2. Mixed Effects Linear Regression Results Comparing Age of First Exposure (AFE) Groups
AFE <12 years (n=20) AFE ‡12 years (n=20) Adjusted estimated
difference
Adjusted mean Standard error Adjusted mean Standard error (AFE ‡12 - AFE <12)
Standard
error pValue
Whole CC
FA 0.5667 0.02211 0.5756 0.02279 0.00888 0.00480 0.066
Trace 0.002618 0.000128 0.002609 0.000132 -0.000009 0.00004 0.817
AD 0.001504 0.000056 0.001509 0.000058 0.000004 0.00002 0.799
RD 0.000551 0.000040 0.000544 0.000042 -0.000007 0.00001 0.549
Region I
FA 0.5568 0.02229 0.5723 0.02296 0.01549 0.00620 0.013
Trace 0.002537 0.000127 0.002490 0.000131 -0.00005 0.00003 0.164
AD 0.001442 0.000056 0.001435 0.000058 -0.000007 0.00002 0.642
RD 0.000542 0.000040 0.000521 0.000041 -0.00002 0.00001 0.048
Region II
FA 0.5451 0.02215 0.5553 0.02283 0.01020 0.00515 0.049
Trace 0.002541 0.000127 0.002518 0.000131 -0.00002 0.00003 0.487
AD 0.001436 0.000056 0.001434 0.000058 -0.000001 0.00002 0.947
RD 0.000547 0.000040 0.000535 0.000041 -0.00001 0.00001 0.222
Region III
FA 0.5618 0.02210 0.5778 0.02278 0.01602 0.00466 <0.001
Trace 0.002497 0.000126 0.002478 0.000130 -0.00002 0.00002 0.445
AD 0.001437 0.000055 0.001446 0.000057 0.000010 0.00001 0.433
RD 0.000524 0.000040 0.000509 0.000041 -0.00001 0.00001 0.052
Region IV
FA 0.5366 0.02276 0.5510 0.02342 0.01441 0.00901 0.112
Trace 0.002607 0.000128 0.002621 0.000132 0.000014 0.00004 0.739
AD 0.001456 0.000056 0.001481 0.000058 0.000024 0.00002 0.167
RD 0.000569 0.000041 0.000564 0.000042 -0.000006 0.00002 0.703
Region V
FA 0.5895 0.02298 0.5958 0.02364 0.006353 0.01008 0.529
Trace 0.002774 0.000135 0.002767 0.000138 -0.000007 0.00007 0.9182
AD 0.001618 0.000058 0.001621 0.000059 0.000003 0.00003 0.9051
RD 0.000572 0.000043 0.000567 0.000044 -0.000006 0.00002 0.8169
Adjusted for duration (years) of football and body mass index.
FA, fractional anisotropy; CC, corpus callosum; AD, axial diffusivity; RD, radial diffusivity.
1772 STAMM ET AL.
The segmentation method used in this study may have contrib-
uted to the lack of differences between groups in the posterior CC
regions.
67
Region V represents posterior callosal fibers connecting
temporal, parietal, and occipital regions. However, the temporal
and parietal fibers coursing through this CC region are smaller and
lightly myelinated, while the CC fibers connecting occipital regions
are larger and highly myelinated.
71
These fibers may be differen-
tially affected by RHI. Combining both fiber types in one region
may have reduced the ability to observe posterior differences be-
tween AFE groups in this study. Future research should consider
investigating the effects of AFE to RHI in CC fibers connecting
temporal, parietal, and occipital fibers separately. Additionally,
differing developmental trajectories of anterior and posterior CC
regions also may contribute to the lack of diffusivity differences
between AFE groups in posterior CC regions.
There are several limitations to this study that should be taken
into account. First, the generalizability of these results may not
extend to other groups. For example, the biomechanics and amount
of RHI experienced by former NFL players may differ from that of
athletes in other high-risk sports, such as soccer and ice hockey.
Additionally, developmental trajectories
37–39
and outcomes
74
fol-
lowing mTBI differ between males and females; therefore, these
results also may not apply to females exposed to RHI during youth.
Second, it is not known whether continued exposure to RHI in
adolescence and adulthood influences the brain’s ability to recover
following childhood exposure to RHI. Future studies should in-
vestigate individuals whose highest levels of football played were
college and high school, as well as individuals with an AFE <12 but
who stopped incurring RHI after age 12. Third, establishment of
causality between AFE to RHI and altered anterior callosal diffu-
sivity cannot be made due to the cross-sectional nature of the study
design. Future studies should, therefore, utilize a longitudinal de-
sign beginning with younger, current athletes.
Fourth, the results of this study should not be interpreted as
concluding that incurring RHI at or after age 12 is without conse-
quences to CC integrity. AFE could be one of several factors, in-
cluding other aspects of head impact or injury exposure, genetics,
and other health-related issues, that may influence later-life out-
come following RHI. Fifth, although using age-matched pairs was
appropriate for this study, it resulted in a reduced sample size, which
is an important limitation of this research. Lastly, although CC pa-
thology has been reported in CTE, the results of this study do not
suggest that the participants have or will develop this neurodegen-
erative disease. Pathological processes resulting from disrupted
white matter development may differ from the tauopathy-based
neurodegeneration of CTE. More research is needed to determine
whether or not incurring RHI during critical neurodevelopmental
periods is a risk factor for the development of CTE.
Increased awareness of the acute and long-term consequences of
repeated concussive and subconcussive head trauma has resulted in
policy and rule changes in multiple sports at all levels of play, as well
as legislation intended to protect youth and adolescent athletes.
16,75
However, replication of our results is necessary before using these
findings as rationale to implement significant rule or policy changes.
Further, it has been suggested that a recent decline in youth sport
participation may be attributed, in part, to concerns of parents and
guardians about brain trauma.
76
More investigation into later-life
outcomes from exposure to RHI in childhood is necessary to address
these concerns, to increase safety in youth sports, and to allow youth
athletes to take advantage of the enormous benefits of sports par-
ticipation without the possibility of long-term consequences.
In conclusion, this study found that former NFL players who
started playing tackle football prior to age 12 had lower FA and
greater RD in anterior CC regions, compared with those who started
playing football at age 12 or older. Exposure to RHI during a
critical period of neurodevelopment may disrupt normal axonal
maturation and myelination, leading to permanently altered white
matter microstructure. More research is needed to understand the
impact of RHI incurred in childhood on later-life brain structure
and function.
FIG. 2. Scatter plots illustrating fractional anisotropy (FA) in corpus callosum regions I, II, and III, and radial diffusivity (RD) in
region I. Those with an age of first exposure to tackle football prior to age 12 had significantly lower FA in Regions I, II, and III, and
higher RD in Region I, than those who began playing football at age 12 or later. Error bars signify one standard deviation from the mean.
Color image is available online at www.liebertpub.com/neu
WHITE MATTER STRUCTURE IN FORMER NFL PLAYERS 1773
Acknowledgments
The authors extend their appreciation to the study participants
who make this work possible.
This study was supported by the National Institutes of Health
(R01 NS 078337; F31 NS 081957 [J.M.S.]; P30 AG13846; UL1-
TR000157, P41 EB015902 [O.P.]; T32MH019733 [C.M.B.]), and
participant travel was funded by gifts from JetBlue Airlines, the
National Football League (NFL), and the NFL Players Association.
This study was also partly supported by the Else Kro
¨ner-Fresenius
Foundation, Germany (I.K., M.M.), and by a VA Merit Award
(M.E.S., M.C., L.L., A.Z.).
Author Disclosure Statement
RAS is a paid consultant to Quest Diagnostics, Amarantus
Bioscience, and Adelphi Values. He also serves as an expert advisor
to attorneys for cases pertaining to the long-term consequences of
repetitive brain trauma. He receives royalties from Psychological
Assessment Resources for the publication of neuropsychological
tests. For all other authors, no competing financial interests exist.
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Address correspondence to:
Robert A. Stern, PhD
CTE Center, Boston University School of Medicine
72 East Concord Street, B7800
Boston, MA 02118
E-mail: bobstern@bu.edu
1776 STAMM ET AL.
