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Mapping abnormal subcortical neurodevelopment in a cohort of Thai
children with HIV
Benjamin S.C. Wade
, Victor G. Valcour
, Thanyawee Puthanakit
, Arvin Saremi
Boris A. Gutman
, Talia M. Nir
, Christa Watson
, Linda Aurpibul
, Pope Kosalaraksa
, Stephen Kerr
, Netsiri Dumrongpisutikul
, Pannee Visrutaratna
, Monthana Pothisri
, Katherine L. Narr
, Paul M. Thompson
, Robert H. Paul
, Neda Jahanshad
, on behalf of the PREDICT and
Resilience Study Groups
Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA,
Ahmanson-Lovelace Brain Mapping Center University of California, Los Angeles, Los Angeles, CA, USA
Missouri Institute of Mental Health, University of Missouri St. Louis, St. Louis, USA
Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
HIV-NAT, the Thai Red Cross AIDS Research Centre, Bangkok, Thailand
Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
RIHES, Chiang Mai University, Chiang Mai, Thailand
Department of Pediatrics, Khon Kaen University, Khon Kaen, Thailand
Chiang Rai Prachanukroh Hospital, Chiang Rai, Thailand
Department of Radiology, Chulalongkorn University Medical Center, Bangkok, Thailand
Department of Radiology, Chiang Mai University, Chiang Mai, Thailand
Department of Radiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
U.S. Military HIV Research Program, Walter Reed Army Institute of Research, MD, USA
Department of Global Health, University of Amsterdam, Amsterdam, the Netherlands
Henry M. Jackson Foundation for the Advancement of Military Medicine, MD, USA
Subcortical shape analysis
Alterations in subcortical brain structures have been reported in adults with HIV and, to a lesser extent, pediatric
cohorts. The extent of longitudinal structural abnormalities in children with perinatal HIV infection (PaHIV) remains
unclear. We modeled subcortical morphometry from whole brain structural magnetic resonance imaging (1.5 T) scans
of 43 Thai children with PaHIV (baseline age = 11.09 ± 2.36 years) and 50 HIV− children (11.26 ± 2.80 years)
using volumetric and surface-based shape analyses. The PaHIV sample were randomized to initiate combination
antiretroviral treatment (cART) when CD4 counts were 15–24% (immediate: n= 22) or when CD4 < 15% (deferred:
n= 21). Follow-up scans were acquired approximately 52 weeks after baseline. Volumetric and shape descriptors
capturing local thickness and surface area dilation were deﬁned for the bilateral accumbens, amygdala, putamen,
pallidum, thalamus, caudate, and hippocampus. Regression models adjusting for clinical and demographic variables
examined between and within group diﬀerences in morphometry associated with HIV. We assessed whether baseline
CD4 count and cART status or timing associated with brain maturation within the PaHIV group. All models were
adjusted for multiple comparisons using the false discovery rate. A pallidal subregion was signiﬁcantly thinner in
children with PaHIV. Regional thickness, surface area, and volume of the pallidum was associated with CD4 count in
children with PaHIV. Longitudinal morphometry was not associated with HIV or cART status or timing, however, the
trajectory of the left pallidum volume was positively associated with baseline CD4 count. Our ﬁndings corroborate
reports in adult cohorts demonstrating a high predilection for HIV-mediated abnormalities in the basal ganglia, but
suggest the eﬀect of stable PaHIV infection on morphological aspects of brain development may be subtle.
Received 5 January 2019; Received in revised form 25 March 2019; Accepted 1 April 2019
Corresponding author at: Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, University of Southern California, 4676 Admiralty Way,
Marina del Rey, CA 90292, USA.
E-mail address: firstname.lastname@example.org (N. Jahanshad).
NeuroImage: Clinical 23 (2019) 101810
Available online 02 April 2019
2213-1582/ © 2019 Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license
Long-term survival and quality of life of children perinatally in-
fected with HIV has improved dramatically with better access to com-
bination antiretroviral therapy (cART). Pediatric HIV-related en-
cephalopathy has decreased in the cART era (Patel et al., 2009;Raskino
et al., 1999;Shanbhag et al., 2005), down to 1.6% from a prevalence of
76% prior to cART (Chiriboga et al., 2005;Cooper et al., 1998), greatly
extending life expectancy. However, as the number of chronically-in-
fected children living with HIV increases, there is a need to understand
the impact of the infection on brain development. HIV is associated
with cognitive and motor impairments in adults (Brew, 2004;Heaton
et al., 1995;Sacktor et al., 2002) and children (Paul et al., 2018;Van
Rie et al., 2008). In adults, these impairments are commonly associated
with disruption to frontal subcortical circuitry, though recent studies
indicate more diﬀuse eﬀects in chronically infected individuals (Baker
et al., 2017;George et al., 2009;Safriel et al., 2000).
Few studies have examined neuroimaging abnormalities in pediatric
HIV. Work by Herting and colleagues (Herting et al., 2015) identiﬁed
associations between HIV severity, peak viral RNA levels and nadir
CD4%, and the functional connectivity of the default mode network
(DMN). Interestingly, disease severity was related to both increased and
decreased BOLD signal correlations both within and between DMN
connectivity. These patterns of connectivity were also predictive of
processing speed. The authors suggest that these ﬁndings may reﬂect a
global reorganization of the DMN and underlie many of the cognitive
dysfunctions found in youth with HIV.
Studies of microstructural brain integrity using diﬀusion tensor
imaging reveal lower whole brain fractional anisotropy in HIV+ youths
(Hoare et al., 2018;Uban et al., 2015), and increased mean and axial
diﬀusivity with higher viral RNA load in plasma (Hoare et al., 2015).
Macrostructural neuroimaging studies have yielded more equivocal
results. Cohen et al. reported more severe white matter hyperintensities
and lower gray and white matter volumes in HIV+ children age 8–18
compared to HIV-uninfected controls (Cohen et al., 2016). Hoare and
colleagues reported decreased cerebral gray matter volumes, cortical
surface area, and decreased gyriﬁcation among 204 adolescence with
paHIV between the ages of 9 to 11 years relative to 44 age-matched
controls (Hoare et al., 2018). Sarma and colleagues reported lower
volumes of the posterior corpus callosum and external capsule, but
increased volumes of multiple cortical and subcortical gray matter re-
gions (Sarma et al., 2014). Recent work by our group to clarify the
discrepancies in gray matter volumes in pediatric HIV revealed larger
volumes of the caudate, accumbens, and cortical gray matter in HIV+
children under age 12, with no diﬀerences in volumes among older
children (Paul et al., 2018b).
Volumetric estimates of relatively large subcortical regions, how-
ever, are not sensitive to potentially subtle disease-related structural
deformations in subsections or subﬁelds of the structures that may
better represent speciﬁc cell types. One means of modeling these more
speciﬁc abnormalities is to use high-dimensional surface-based shape
descriptors on the extracted subcortical region of interest. We have
demonstrated that these shape features are highly sensitive to focal
abnormalities when compared to volumetric measures in HIV+ older
adults (Wade et al., 2015), as well as other patient populations (e.g.,
traumatic brain injury; (Tate et al., 2016;Tate et al., 2018) treatment-
resistant depression (Wade et al., 2016;Wade et al., 2017).
To date, only one study has used shape analysis to characterize local
subcortical deformations in youth with HIV. Lewis-de los Angeles and
colleagues applied multiatlas FreeSurfer-initiated large-deformation
diﬀeomorphic metric mapping (Khan et al., 2008) to identify sub-
cortical shape deformations related to peak HIV viral load and nadir
CD4% in PHACS, a cohort of 40 youth from the United States, all with
perinatally acquired HIV (PaHIV). The group found deformations of the
thalamus, caudate, pallidum, and putamen related to peak HIV RNA
counts. Most deformations were inwards, although outward
deformations were also detected; these outward deformations, local
volumetric expansion, of the medial and posterior thalamus were
identiﬁed in association with higher nadir CD4%. Further, shape var-
iations in the caudate and thalamus were associated with cognitive
impairments (Lewis-de Los Angeles et al., 2016).
Nearly all of these previous studies were limited by their cross
sectional designs, and many did not compare the HIV+ individuals to
matched controls. In this study we investigated whether HIV status
associated with cross sectional or longitudinal structural deformations
in seven subcortical brain regions in a relatively homogeneous sample
of 43 youth with HIV compared to 50 uninfected controls, all from three
scanning sites across Thailand. Participants (age 6 to 16) were enrolled
in a longitudinal study to examine outcomes associated with early
versus deferred initiation of cART (ClinicalTrials.gov, number
NCT00234091; (Puthanakit et al., 2012)). Both adult and adolescent
HIV literature suggest a disproportionate eﬀect of HIV status on sub-
cortical brain structures (Fennema-Notestine et al., 2013;Jernigan
et al., 2011), particularly the basal ganglia (Ances et al., 2012;Li et al.,
2018;Wade et al., 2015). Given this and the need to restrict the number
of statistical comparisons, we focused our analyses on prominent sub-
cortical regions of interest. We hypothesized that children with HIV
would exhibit signiﬁcant deformations in select brain regions, with
reduced local and global volumetric distortions. Within the HIV+
subset, we further evaluated the eﬀect of current CD4 count, and cART
treatment status or timing (early versus deferred initiation), on sub-
cortical morphometry; we hypothesized that higher CD4 count would
show patterns more similar to HIV− controls while cART treatment
status would not show any eﬀects.
The sample included 43 HIV+ (baseline age = 11.09 ± 2.36; 20
female; 32 on cART; 21 deferred cART) and 50 HIV− (baseline
age = 11.26 ± 2.80; 29 female) Thai participants enrolled in the
Pediatric Randomized Early versus Deferred Initiation in Cambodia and
Thailand (PREDICT) clinical trial (ClinicalTrials.gov, number
NCT00234091; (Puthanakit et al., 2013;Puthanakit et al., 2012).
Baseline demographic and clinical characteristics of the groups are
provided in Table 1. Enrollment into the PREDICT trial occurred be-
tween 2005 and 2007, resulting in 150 children randomized to the
immediate arm, 150 randomized to the deferred arm. Two control
samples were recruited, including 164 healthy unexposed uninfected
(HUU) and 155 HIV-exposed but uninfected children (HEU)
(Puthanakit et al., 2013). A neuro-focused substudy was initiated after
the start of the main PREDICT trial, which included neuroimaging and
neuropsychological assessment. This study includes HIV+, HEU, and
HUU children who completed the neurosubstudy. For this imaging
analysis, all participants met the following inclusion criteria: (1)
age < 18 years, (2) able to tolerate MRI, and (3) written informed
consent signed by a caregiver and assent for participants 6 to 17 years
of age. Exclusion criteria included prior or current brain infection,
neurological or psychiatric disorder, any congenital abnormality or
head injury with a loss of consciousness. The Institutional Review
Boards (IRBs) of each study site approved the study.
2.2. Image acquisition
Participants underwent repeat structural magnetic resonance ima-
ging (MRI) with an average of 52 weeks between baseline and follow-up
scans (median = 52.7 weeks; range = 39.2 to 116.7). Whole brain
structural T1-weighted MRI was performed on GE 1.5 T scanners at all
study sites using the following protocol: axial plane, 3D SPGR images
with a minimum TE at full echo, TR = 11.2 ms, slice thick-
ness = 1.0 mm, isotropic voxel size; 256 × 256 imaging matrix. The
B.S.C. Wade, et al. NeuroImage: Clinical 23 (2019) 101810
number of slices acquired were between 130 and 170, and varied per
scan to ensure full head coverage. Quality assurance of the MRI ac-
quisitions was performed throughout the study using a human phantom
to ensure consistent scaling. Motion was assessed in real-time by the
technician. The scan was repeated for any participant for whom motion
artifacts were detected. All participants with longitudinal MRIs used for
this analysis had at least one scan without detectable motion at each
time point. Therefore, motion was not a signiﬁcant issue at the image
processing stage, and no data points were excluded after the data col-
lection was completed. Two of the authors (N.J. and B.W.) reviewed all
subject's FLAIR images to screen for white matter hyperintensities
(WMH) that might compromise regional FreeSurfer segmentations. No
concerning WMHs were identiﬁed in scans of participants that had
originally passed quality control, thus there was no need to exclude
more data on this basis.
2.3. Morphological descriptors
FreeSurfer version 5.3 (Fischl et al., 2002) was used to remove non-
brain tissue, normalize intensities, and conducted semiautomated vo-
lumetric parcellation using probabilistic information from manually
labeled training sets. FreeSurfer's default cross-sectional workﬂow was
applied to each scan. Seven subcortical brain regions of interest (ROI)
were selected: the thalamus, putamen, pallidum, amygdala, accumbens,
caudate, and hippocampus. Segmentations were completed for each
hemisphere with visual quality inspection completed using ENIGMA
protocols: http://enigma.usc.edu/protocols/imaging-protocols/ to en-
sure their quality.
To deﬁne shape descriptors on the subcortical surfaces, a 3D co-
ordinate mesh was applied to the outer surface of each ROI. The
parameterization of each surface was obtained using the medial
“Demons” framework detailed in (Gutman et al., 2015;Gutman et al.,
2012). Brieﬂy, each surface was conformally mapped to the spherical
domain and rigidly rotated to a probabilistic atlas. Each segmentation
was warped to a spherical template using Spherical Demons (Gutman
et al., 2013) on the basis of curvature to deﬁne the local thickness of the
surface with respect to a skeletonization or the surface “medial core.”
The medial core and surface-based curvature were mapped to each
surface to render two measures at each point along the surface: (1) the
radial distance (RD), a proxy for the local thickness, and (2) the log of
the Jacobian determinant (JD) which indicates regional surface area
expansion or contraction. For example, if the anterior hippocampus
were signiﬁcantly thinner in a group of elderly patients with Alzhei-
mer's disease compared to age-matched controls, the RD value would be
smaller in the anterior hippocampus of the Alzheimer's patients. If in-
stead the healthy cohort hippocampi did not diﬀer from the Alzheimer's
group on the basis of local thickness but was relatively elongated, the
log-JD would be positive for the healthy group but negative for the
Alzheimer's group, on average. We note that a shorter, yet thicker re-
gion, may not show a diﬀerence in volume, yet the shape characteristics
deﬁned here would help identify these trends. A total of 27,120 vertices
were assessed across the fourteen (seven left and right) selected ROIs.
2.4. Statistical methods
Fixed eﬀects multivariate linear regression analyses were used to
model associations between the subcortical shape features (RD and JD)
or volume and HIV-related factors at baseline and over time. HIV status
represented the main eﬀect of interest tested across all vertices (mod-
eled categorically). We covaried for age, sex, total estimated in-
tracranial volume, measures of socioeconomic status, including edu-
cation level of the caregiver (modeled categorically: greater than
elementary school level or not) and their income level (modeled cate-
gorically: average, above average, or below average). As scans were
collected across three institutions across Thailand, we also adjusted for
scan site (modeled categorically; 3 sites) in all models. Within the HIV
+ group, we separately assessed the eﬀects of baseline CD4 t-cell count
(modeled continuously), cART status (modeled categorically), and
cART timing (modeled categorically as deferred versus immediate in-
itiation) keeping the same covariates as before.
Longitudinal models assessed the relationship between HIV status
and the change in the morphometry over time. Diﬀerence scores for
both RD and JD were deﬁned as morphometry
, and longitudinal models included an additional covariate to
model the time between the scans (in days).
Some variables had missing information: caregiver income level
(N= 8) and education level (N= 1). We therefore ran two models. In
the ﬁrst, the subjects with missing data were not included in the
models, and the second, the missing values for these data were imputed
according to the overall mode of the sample: for patient income this was
average and elementary school or below for education.
All models were adjusted for multiple comparisons across vertices
for shape measures and across structures for volume measures using the
standard false discovery rate (FDR) method with a false-positive rate of
5% (q= 0.05) (Benjamini and Hochberg, 1995). FDR adjustments were
applied within the family of all tests performed on a single surface
correcting for separate tests within each surface. We further required
that a minimum of three adjacent vertices show a signiﬁcant association
with the main eﬀect, after adjustment for vertex wise multiple com-
parisons, to be considered a viable association; this further reduces the
likelihood of false positives. Volumetric models were adjusted using
FDR applied to the whole set of ROIs tested.
HIV+ and HIV− participants did not diﬀer signiﬁcantly by age
(Welch t= −0.31, df = 90.96, p= .75) or sex (χ
=0.80, df = 1,
p= .36). Baseline CD4 counts diﬀered signiﬁcantly by HIV status
(mean HIV− = 954 per μl, sd = 299.81; mean HIV+ = 727 per μl,
sd = 325.29; Welch t= −3.46, df = 86.30, p≤ .001). Days to follow-
up diﬀered signiﬁcantly between groups (Welch t= 4.84, df = 48.85,
p< .0001) with the average days to follow-up for HIV− being 364.44
(sd = 42.97) and HIV+ being 472.69 (sd = 140.84). There were no
signiﬁcant diﬀerences in age, sex or days to follow-up between cART-
positive (cART+) and cART-negative (cART-) HIV+ participants.
Baseline CD4 counts diﬀered signiﬁcantly by cART status (mean
cART+ = 853.53 per μl, sd = 270.80, mean cART- = 362.54 per μl,
sd = 140.49; Welch t= 7.68, df = 33.97, p< .00001).
Demographic and clinical characteristics.
HIV+ (n= 43) HIV− (n= 50)
Age, mean (sd), y 11.09 (2.36) 11.26 (2.80)
Sex, M/F 23/20 29/21
cART status, Y/N 32/11 –
Age of cART initiation, mean (sd), y
9.39 (3.23) –
Log Viral RNA count, mean (sd), copies/ml 9.85 (11.16) –
Detectable/undetectable vRNA, (%)
CD4 count, mean (sd), cells/mL
728 (323) 954 (299)
HEU/HUU – 25/25
Site, Chula/CM/KKU 15/25/3 20/29/0
Income, above average/average/below
Education, high school or greater/up to
Days to follow-up
Based on the date that a participant received the ﬁrst drug in the cART
Undetectable vRNA levels are < 50 copies per mLl.
B.S.C. Wade, et al. NeuroImage: Clinical 23 (2019) 101810
3.2. HIV status
The thickness (RD) of the right medial inferior pallidum was sig-
niﬁcantly lower in the HIV+ group, relative to controls by approxi-
mately 4%. The area of this shape deformation covered 0.06% of the
right pallidum surface (8 adjacent vertices; mean t-value = −4.002;
mean p-value < .001) is illustrated in Fig. 1. The extent of this sig-
niﬁcant association was only moderately increased when income was
not included as a covariate (see Supplementary Fig. 1) but was elimi-
nated when subjects with missing income values were excluded (i.e.,
when we did not impute their values). No volumetric associations with
HIV status were found at baseline. No longitudinal diﬀerences in shape
or volume measures were associated with HIV status.
To conﬁrm that shape and volume measures associated with de-
velopment, we evaluated the eﬀect of age in the same regression models
in which HIV status was the main eﬀect. We observed widespread as-
sociations between RD, JD, and volume measures with age across all
subcortical regions at baseline; only a minority of regions exhibited
longitudinal volumetric associations with age.
Similarly, we evaluated shape and volume associations with income
and education levels to determine if these socioeconomic measures
confer a larger eﬀect on morphometry than HIV status. At baseline, no
associations were found with education level, however, the volume of
the bilateral putamen and JD of the right putamen (~8% of the total
surface) was signiﬁcantly reduced in subjects with an average income
relative to those with above average income. An important caveat,
though, is that there were only n= 9 participants in the above-average-
income category. No longitudinal associations with socioeconomic or
demographic measures were observed longitudinally.
3.3. Baseline CD4 count and treatment status within HIV+ adolescents
Baseline CD4 count was signiﬁcantly associated with RD across 43%
of the total surface of the left pallidum (mean t-value = −3.0; mean p-
value < .01); see Fig. 2 (a-b). Similarly, baseline CD4 count was sig-
niﬁcantly associated with JD across 34% of the surface of the left pal-
lidum (mean t-value = −3.0; mean p-value < .01); see Fig. 2 (c-d). The
distribution of signiﬁcant associations with CD4 count were similar
when we did not covary for income level (see Supplementary Fig. 2).
When the eight PaHIV participants with missing covariate information
(speciﬁcally missing family income) were excluded the extent of the
signiﬁcant association with CD4 count was greatly reduced in the left
pallidum and additional regional associations in the right caudate and
bilateral amygdala were identiﬁed (see Supplementary Fig. 3). The total
volume of the left pallidum was also signiﬁcantly and negatively as-
sociated with baseline CD4 count (t= −3.42; p< .05; b = −0.42);
see Fig. 3(a). The signiﬁcance of this association remained when in-
come was not included as a covariate but did not survive when parti-
cipants with missing income data were excluded. All signiﬁcant asso-
ciations were such that participants with higher CD4 counts had smaller
RD, JD, and volume measures, on average. Baseline CD4 count was
signiﬁcantly associated with the trajectory of the left pallidal volume
(t= 3.32; p < .05; b = 0.25) but not shape; children with higher CD4
counts had increased rates of left pallidum volume growth compared to
those with lower CD4 counts (see Fig. 3(b)). This signiﬁcant long-
itudinal association, however, did not survive multiple comparisons
correction when four potential outliers in the volumetric range ﬂagged
by the interquartile range rule were excluded (p> .1). As hypothe-
sized, neither cART status nor cART timing were signiﬁcantly asso-
ciated with baseline or longitudinal shape or volume among the parti-
cipants with HIV.
In this study we observed a strong association between CD4 t-cell
count and regional morphometry of the left pallidum among adoles-
cence with HIV. Speciﬁcally, those with higher CD4 counts had reduced
thickness and surface area of pallidal subregions and total pallidal vo-
lume. Nevertheless, longitudinally, the left pallidum total volume in-
creased signiﬁcantly more among children with higher baseline CD4
counts. We further observed that adolescence with HIV had only
minimal morphological diﬀerences compared to uninfected controls at
baseline; income level was seemingly more associated with subcortical
shape and volume than HIV status. Nevertheless, a medial inferior re-
gion of the right pallidum was thinner in adolescence with HIV com-
pared to controls. Longitudinal volumetric diﬀerences were associated
with baseline CD4 count; however, no longitudinal shape or volume
diﬀerences were associated with HIV or cART status.
The basal ganglia has been shown to be highly aﬀected in HIV
(Aylward et al., 1993;Berger and Arendt, 2000;Berger and Nath, 1997;
Wright et al., 2016). The predilection for the basal ganglia may be
mediated through a mutli-deterministic model including weak tight
junctions between astrocytic feet comprising the blood brain barrier,
high concentration of CCR5 chemokine receptors, and susceptibility to
oxidative stress. Previous work by our group showed that the pallidum's
volume is signiﬁcantly reduced in elderly patients with HIV.
Fig. 1. Subcortical shape diﬀerences in the right pallidum between HIV+ and HIV− participants. (a) T-value map highlighting region of signiﬁcantly diﬀerent local
thickness (RD value) associated with HIV status. (b) Boxplots of average local thickness in vertices identiﬁed as signiﬁcantly diﬀerent in (a).
B.S.C. Wade, et al. NeuroImage: Clinical 23 (2019) 101810
Interestingly, this same study identiﬁed a trend-level increase in the
local volume of the anterior right pallidum associated with extended
time since diagnosis (Wade et al., 2015). Lewis-de Los Angeles et al.
also observed shape variations, both local volumetric dilations and re-
ductions, of the pallidum and putamen associated with HIV severity (as
captured by peak HIV RNA load) (Lewis-de Los Angeles et al., 2016).
Our ﬁnding suggests that on average, adolescents with higher baseline
CD4 counts have lower regional thickness, surface area, and total vo-
While in most cases, larger or thicker neuroimaging derived sub-
cortical regions are considered to be associated with healthier brains,
this is not always the case, particularly for the pallidum. For example,
Turner and colleagues reported signiﬁcantly larger pallidum volumes in
people with autism spectrum disorder (ASD) based on a sample of 472
ASD and 538 non-ASD controls between the ages of 6–64 years (Turner
et al., 2016). Jørgensen et al. also reported an increased volume of the
pallidum among 82 patients with long-term treated schizophrenia re-
lative to 106 healthy controls (Jorgensen et al., 2016). Enlarged pal-
lidum volumes in schizophrenia was also reported in a much larger
study by van Erp and the ENIGMA consortium who reported an in-
creased pallidum volume in a meta-analysis of 2028 patients with
schizophrenia and 2540 controls (van Erp et al., 2016).
More directly related to our current study, Randall et al. in-
vestigated abnormalities in subcortical gray matter volumes in 43 HIV
+ and 18 HIV− 5-year old Xhosa children who were initiated to ART
before 18 months of age; 27 initiated ART before 12 weeks of age and
Fig. 2. Left pallidum shape (RD top and JD bottom) associations with CD4 count within HIV+ participants. T-value maps highlighting clusters of vertices where
shape is signiﬁcantly associated with CD4 count; all were inversely associated (a & c). Figures b & d are scatterplots showing the average RD or JD values within
signiﬁcant regions plotted against participant CD4 count.
B.S.C. Wade, et al. NeuroImage: Clinical 23 (2019) 101810
16 initiated after 12 weeks. The group reported that HIV+ children had
larger left pallidum volumes compared to the uninfected group and that
this diﬀerence was largely driven by children initiated to ART after
12 weeks of age (Randall et al., 2017). The authors suggest that larger
diﬀerences in the later-initiated group is evidence neuroprotective ef-
fects of earlier treatment. Our analysis of cART timing and status,
however, did not identify signiﬁcant associations with brain morpho-
metry. This is possibly due to two factors: The number of children in
this sample who did not undergo cART was very small thus limiting the
power of between-group analyses. Additionally, children were selected
for the parent study due to ability to survive without cART at the time
of randomization. Thus, survivor tendencies may mitigate our ability to
detect direct associations with cART and its beneﬁts.
The absence of cART-related ﬁndings in this cohort squared with
our expectations for several reasons. Children in the parent study were
treatment-naive at the time of enrollment. The participants were then
randomly assigned to begin cART when CD4 < 15% or when
CD4 < 25% deferred or immediate treatment arms. Thus, only some of
the original deferred group would not be on cART at baseline. Further,
as only 11 children were untreated at baseline, we anticipated that this
sample was underpowered to resolve treatment eﬀects.
Though speculative, it is possible that the observed inverse corre-
lation between CD4 count and left pallidal volume reﬂects ongoing
disease mechanisms among individuals with low CD4 cell count; but,
further studies directly assessing markers of inﬂammation are needed to
test this hypothesis. Further, higher baseline CD4 counts were sig-
niﬁcantly associated with increased subsequent growth of the left pal-
lidum's total volume which suggests that pallidal growth is increased in
HIV-associated cognitive impairment is an important topic of in-
vestigation and has been widely reported in a number of previous
studies (Brew, 2004;Sacktor et al., 2002;Van Rie et al., 2008). We did
not explore associations between cognition and brain morphometry in
this study, however, as a prior study of this same cohort described
cognitive abnormalities in paHIV and reported minimal disease-related
cognitive changes (Paul et al., 2018). As such, the present study was
conducted to investigate brain integrity longitudinally in paHIV using
an innovative and sensitive analysis of parenchymal morphology.
Several notable limitations should be considered in interpreting
these ﬁndings. First, the one-year time frame between baseline and
follow-up scans may not have been suﬃcient to observe important
changes. The average baseline age of our participants was 11 years and
ranged from 6 to 16 across diagnostic groups, an age span characterized
by complex patterns of age and sex-dependent rates of gray matter
pruning and myelination (Giedd, 2004). Given this, a wider time frame
and future follow-up imaging sessions would be beneﬁcial. However,
numerous baseline and longitudinal abnormalities among the HIV+
cohort were identiﬁed. We additionally note that the time to follow-up
was signiﬁcantly longer in the HIV+ cohort. While this cannot be
completely corrected, we included time to follow-up as a covariate in
our longitudinal models. As discussed previously, the original sample
included three time points, however, the HIV+ cohort was a year older
at baseline relative to the control group and it is possible that the use of
diﬀerent baseline time points across the two groups introduced a sys-
tematic bias in our models. Another limitation for this study was that
certain data points, primarily for income level, required imputation.
While this is an inherent limitation, we observed only minor diﬀerences
in the distribution of signiﬁcant associations between models that in-
cluded or excluded income levels (see Supplementary Figures).
In conclusion, we observed shape abnormalities among HIV+
children at ﬁrst scan, which attenuated in magnitude over the course of
12 months as longitudinal subcortical abnormalities were non-sig-
niﬁcant. The most robust HIV-related eﬀects were instead shape and
volumetric associations with CD4 cell count within the pallidum of
paHIV children. Although more work needs to be done to disentangle
potential eﬀects of neuroinﬂammatory processes, this approach has not
previously been applied to identify abnormalities in longitudinal ima-
ging proﬁles of children with paHIV. Taken together, our ﬁndings
suggest that the eﬀects of treated HIV on the morphometry of sub-
cortical structures in adolescence is somewhat minor.
Supplementary data to this article can be found online at https://
200 400 600 800 1000 1200 1400
−200 0 200 400 600
200 400 600 800 1000 1200 1400
1000 1500 2000 2500
Baseline CD4 Count
Left Pallidum Volume mm3: Baseline
Baseline CD4 Count
Left Pallidum Volume Change mm3: Follow-u p - Baseline
Fig. 3. Scatterplots highlighting the signiﬁcant associations between baseline CD4 counts and (a) baseline left pallidum volume and (b) the change in left pallidum
volume between baseline and follow-up time points. In b, red points indicate four subjects that are potentially outliers in terms of volumetric change as ﬂagged by the
interquartile range rule. The red dashed regression line is ﬁt to the set of subjects excluding the potential outliers.
B.S.C. Wade, et al. NeuroImage: Clinical 23 (2019) 101810
Conﬂict of interest
JA has received honorarium for advisory meetings participation
from Merck, ViiV Healthcare and Tetralogic. PMT and NJ have research
related grant support from BioGen Inc., unrelated to the contents of this
manuscript. Other authors have no disclosures related to the study.
This work was supported by R01MH089722 (V. Valcour) and
R01MH102151 (T. Puthanakit and J. Ananworanich) and also in part
by NIH ‘Big Data to Knowledge’ (BD2K) Center of Excellence grant
U54EB020403, P41EB015922, R01AG059874, R01MH117601, NIH
Institutional Training Grant T32AG058507, the National Science
Foundation Graduate Research Fellowship under Grant No. DGE-
0707424 (BW) and by a NARSAD Young Investigator Grant from the
Brain & Behavior Research Foundation (27786; BW). The main rando-
mized study was supported by a grant from the National Institute of
Allergy and Infectious Diseases of the US National Institutes of Health
through the Comprehensive International Program of Research on AIDS
Network (U19 AI53741), and was co-funded by the Eunice Shriver
Kennedy National Institute of Child Health and Human Development
and the National Institute of Mental Health, the National Research
Council of Thailand, and National Health Security Oﬃce, Thailand.
Antiretroviral drugs were provided by ViiV Healthcare,
GlaxoSmithKline, Boehringer Ingelheim, Merck, Abbott, and Roche.
The views expressed are those of the authors and should not be con-
strued to represent the positions of the U.S. Army, the Department of
Defense, the National Science Foundation, the National Institutes of
Health or US Department of Health and Human Services.
We would also like to acknowledge the PREDICT study group con-
sisting of the following:
HIV Netherlands Australia Thailand (HIV-NAT) Research
Collaboration, Thai Red Cross AIDS Research Center, Bangkok,
Thailand; Dr.Kiat Ruxrungtham, Dr.Jintanat Ananworanich,
Dr.Thanyawee Puthanakit, Dr.Chitsanu Pancharoen, Dr.Torsak
Bunupuradah, Dr.Wasana Prasitsuebsai, Stephen Kerr, Sasiwimol
Ubolyam, Apicha Mahanontharit, Tulathip Suwanlerk, Jintana Intasan,
Kanchana Pruksakaew, Chulalak Sriheara, Tanakorn Apornpong,
Jiratchaya Sophonphan, Ormrudee Rit-im, Wanchai Thongsee, Orathai
Chaiya, Kesdao Nantapisan, Umpaporn Methanggool, Dr.Sukalaya
Lerdlum, Mantana Pothisri Bamrasnaradura Infectious Diseases
Institute, Nonthaburi,Thailand; Dr.Jurai Wongsawat, Supeda
Thongyen, Piyawadee Chathaisong, Vilaiwan Prommool, Duangmanee
Suwannamass, Simakan Waradejwinyoo, Nareopak Boonyarittipat,
Thaniya Chiewcharn,Sirirat Likanonsakul, Chatiya Athichathana,
Boonchuay Eampokalap, Wattana Sanchiem. Srinagarind Hospital,
Khon Kaen University, Khon Kaen, Thailand; Dr.Pope Kosalaraksa,
Dr.Pagakrong Lumbiganon, Piangjit Tharnprisan, Chanasda Sopharak,
Viraphong Lulitanond, Samrit Khahmahpahte, Ratthanant Kaewmart,
Prajuab Chaimanee, Mathurot Sala, Thaniita Udompanit, Ratchadaporn
Wisai, Somjai Rattanamanee, Yingrit Chantarasuk, Sompong
Sarvok,Yotsombat Changtrakun,Soontorn Kunhasura, Sudthanom
Kamollert, Petcharakorn Hanpanich, Wuttisak Boonphongsathian.
Queen Savang Vadhana Memorial Hospital, Chonburi, Thailand;
Dr.Wicharn Luesomboon, Isara Limpet-ngam, Daovadee Naraporn,
Pornpen Mathajittiphun, Chatchadha Sirimaskul, Woranun Klaihong,
Pipat Sittisak, Tippawan Wongwian, Kansiri Charoenthammachoke,
Pornchai Yodpo. Nakornping Hospital, Chiang Mai, Thailand;
Dr.Suparat Kanjanavanit, Thida Namwong, Duangrat Chutima, Suchitra
Tangmankhongworakun,Pacharaporn Yingyong, Juree Kasinrerk,
Montanee Raksasang,Pimporn Kongdong,Siripim Khampangkome,
Suphanphilat Thong-Ngao, Sangwan Paengta, Kasinee Junsom, Ruttana
Khuankaew, Parichat Moolsombat, Duanpen Khuttiwung, Chanannat
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Rawiwan Hansudewechakul, Dr. Yaowalak Jariyapongpaiboon, Dr.
Chulapong Chanta, Areerat Khonponoi, Chaniporn Yodsuwan, Warunee
Srisuk, Pojjavitt Ussawawuthipong, Yupawan Thaweesombat, Polawat
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